Publications

Alturki, R & Gay, V 2019, 'Augmented and Virtual Reality in Mobile Fitness Applications: A Survey' in Applications of Intelligent Technologies in Healthcare, Springer International Publishing, pp. 67-75.
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Obesity is a major issue around the world. It is the main reason for several chronic diseases. Obesity can be stopped by encouraging people to do physical activities and making behaviour intervention regarding lifestyle. Mobile fitness apps are emerging because of the unique features that are provided. They are seen as a vital tool to motivate people suffering from obesity to perform physical activities and make behaviour intervention regarding health and fitness. Augmented reality (AR) and virtual reality (VR) technologies have been used successfully in different kinds of mobile apps. This paper presents a systematic review of some of the most recent AG and VR researches in mobile apps. It discusses the main findings of applying both technologies in different fields of mobile apps. Based on this systematic review, a fitness mobile app for obese individuals that consider both AR and VR technology will be developed.

Hoang, DT & Niyato, D 2019, 'RF-Based Energy Harvesting Cognitive Cellular Networks' in Wei, Z (ed), Handbook of Cognitive Radio, Springer Singapore, Switzerland, pp. 1235-1277.
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Recently, fundamental research has demonstrated great potentials of integrating radio frequency (RF) energy harvesting techniques into cognitive cellular networks (CCNs). Such an integration can improve spectrum utilization and energy efficiency of wireless communication services. In CCNs with RF energy harvesting capability, when cellular base stations, i.e., primary transmitters, transmit signals to their mobile devices, secondary users (SUs) can harvest energy from the cellular channel, i.e., the primary channel, and store the energy in their batteries. Then, when the cellular channel becomes idle, the SUs can use the harvested energy to transmit data to their receivers. As such, we can utilize not only the available spectrum when the channel is idle but also energy scavenging when the channel is busy. This chapter first presents an overview of RF-based energy harvesting CCNs. Then, limitations are discussed, and some new solutions using ambient backscattering communication techniques are introduced to overcome the limitations. Finally, the chapter concludes with a discussion on the development of such networks and possible research directions.

Hoang, TM, Quoc Ngo, H, Duong, TQ & Tuan, HD 2019, 'Security for Cell‐free Massive MIMO Networks' in Ultra-dense Networks for 5G and Beyond, Wiley, pp. 135-150.
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Cell-free massive multi-input multi-output (MIMO), where many access points (APs) distributed in a wide area coherently serve many users in the same time/frequency resource, is one of the most promising technologies for the next generation of wireless systems. This chapter provides some basic concepts of cell-free massive MIMO and investigates the security aspect of cell-free massive MIMO under a pilot spoofing attack. It presents a simple counterattack scheme that is based on the power allocation at the APs to deal with the attack. The chapter provides another perspective on a cell-free massive MIMO system in the presence of an eavesdropper. Noticeably, the attacks by eavesdroppers can be classified into two types: passively eavesdropping attacks and actively eavesdropping attacks. When compared with each other, it is shown that active eavesdroppers are more dangerous than passive eavesdroppers.

Kiran, MR, Farrok, O & Guo, Y 2019, 'Superconducting Linear Machines for Electrical Power Generation from the Oceanic Wave' in Advanced Linear Machines and Drive Systems, Springer Singapore, pp. 281-302.
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LU, S, Oberst, S, Zhang, G & Luo, Z 2019, 'Theory and Applications of Time Series Analysis' in Valenzuela, O, Rojas, F, Pomares, H & Rojas, I (eds), Theory and Applications of Time Series Analysis, Springer International Publishing, Cham, Switzerland, pp. 57-70.
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Forbidden ordinal patterns are known to be useful to discriminate between chaotic and stochastic systems. However, while uncorrelated noise can be separated from deterministic signals using forbidden ordinal patterns, correlated noise exhibits apparently forbidden ordinal patterns, which can impede distinguishing noise from chaos. Here, we introduce order patterns recurrence plots to visualise the difference among deterministic chaotic systems, and stochastic systems of uncorrelated and correlated noise. In an order pattern plot of a chaotic system with an optimal embedding dimension, the diagonal lines remain preserved, while uncorrelated noise shows up as thinly isolated dots and correlated noise forms clusters. We propose two measures, the mean and the median of relative frequencies of order patterns that appear in a time series to distinguish those dynamics. The effectiveness of the two measures is analysed using bifurcation diagrams of the logistic map, the tent map, the delayed logistic map and the Hénon map. Our results show, that both, the mean and the median, distinguish chaos from quasiperiodicity in the delayed logistic map. The mean of relative frequencies of order pattern is reciprocal to the number of order patterns that occur in a given time series and thus can be a measure of forbidden structures—which becomes unbounded. While the mean is robust to the change of parameters in the bifurcation diagrams, the median exhibits sensitive changes, which is significant to characterise chaotic signals.

Mahmud, K, Nizami, MS, Ravishankar, J & Hossain, MJ 2019, 'Power-demand management in a smart grid using electric vehicles' in ICT for Electric Vehicle Integration with the Smart Grid, Institution of Engineering and Technology, pp. 111-142.
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Quevedo, DE, Aguilera, RP & Geyer, T 2019, 'Model Predictive Control for Power Electronics Applications' in Raković, SV & Levine, WS (eds), Handbook of Model Predictive Control, Springer International Publishing, pp. 551-580.
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Power electronics converters use switching elements to manipulate voltage and current waveforms. This enables the interconnection of components having different requirements, e.g., when incorporating renewable energy sources into the grid. The use of switching elements may lead to high energy efficiency. However, switching dynamical systems are difficult to analyse and design. In this chapter, we outline how model predictive control concepts can be used in power electronics and electrical drives. Special emphasis is given on the finite-set nature of manipulated variables and associated stability and optimization issues. For particular classes of system models, we discuss practical algorithms, which make long-horizon predictive control suitable for power electronics applicationsFrom a control systems perspective, power electronic systems give rise to in- trinsically challenging design problems. Specifically, three major challenges can be identified:

Abbasi, MH, Taki, M, Rajabi, A, Li, L & Zhang, J 2019, 'Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach', Applied Energy, vol. 239, pp. 1294-1307.
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© 2019 Elsevier Ltd As the number of electric vehicles (EVs) is steadily increasing, their aggregation can offer significant storage to improve the electric system operation in many aspects. To this end, a comprehensive stochastic optimization framework is proposed in this paper for the joint operation of a fleet of EVs with a wind power producer (WPP) in a three-settlement pool-based market. An aggregator procures enough energy for the EVs based on their daily driving patterns, and schedules the stored energy to counterbalance WPP fluctuations. Different sources of uncertainty including the market prices and WPP generation are modeled through proper scenarios, and the risk is hedged by adding a risk measure to the formulation. To obtain more accurate results, the battery degradation costs are also included in the problem formulation. A detailed case study is presented based on the Iberian electricity market data as well as the technical information of three different types of EVs. The proposed approach is benchmarked against the disjoint operation of EVs and WPP. Numerical simulations demonstrate that the proposed strategy can effectively benefit EV owners and WPP by reducing the energy costs and increasing the profits.

Abidi, IH, Mendelson, N, Tran, TT, Tyagi, A, Zhuang, M, Weng, L, Özyilmaz, B, Aharonovich, I, Toth, M & Luo, Z 2019, 'Selective Defect Formation in Hexagonal Boron Nitride', Advanced Optical Materials, vol. 7, no. 13, pp. 1900397-1900397.
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AbstractLuminescent defects in hexagonal boron nitride (hBN) have emerged as promising single photon emitters (SPEs) due to their high brightness and robust operation at room temperature. The ability to create such emitters with well‐defined optical properties is a cornerstone toward their integration into on‐chip photonic architectures. Here, an effective approach is reported to fabricate hBN SPEs with desired emission properties in distinct spectral regions via the manipulation of boron diffusion through copper during atmospheric pressure chemical vapor deposition (CVD)—a process termed gettering. Using the gettering technique the resulting zero‐phonon line is deterministically placed between the regions 550 and 600 nm or from 600 to 650 nm, paving the way for hBN SPEs with tailored emission properties. Additionally, rational control over the observed SPE density in the resulting films is demonstrated. The ability to control defect formation during hBN growth provides a cost effective means to improve the crystallinity of CVD hBN films, and lower defect density making it applicable to hBN growth for a wide‐range of applications. The results are important to understand defect formation of quantum emitters in hBN and deploy them for scalable photonic technologies.

Abidi, S, Piccardi, M, Tsang, IW & Williams, M-A 2019, 'Well-M$^3$N: A Maximum-Margin Approach to Unsupervised Structured Prediction', IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 3, no. 6, pp. 427-439.
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Unsupervised structured prediction is of fundamental importance for the clustering and classification of unannotated structured data. To date, its most common approach still relies on the use of structural probabilistic models and the expectation-maximization (EM) algorithm. Conversely, structural maximum-margin approaches, despite their extensive success in supervised and semi-supervised classification, have not raised equivalent attention in the unsupervised case. For this reason, in this paper we propose a novel approach that extends the maximum-margin Markov networks (M3N) to an unsupervised training framework. The main contributions of our extension are new formulations for the feature map and loss function of M3N that decouple the labels from the measurements and support multiple ground-truth training. Experiments on two challenging segmentation datasets have achieved competitive accuracy and generalization compared to other unsupervised algorithms such as k-means, EM and unsupervised structural SVM, and comparable performance to a contemporary deep learning-based approach.

Acuna, P, Rojas, CA, Baidya, R, Aguilera, RP & Fletcher, JE 2019, 'On the Impact of Transients on Multistep Model Predictive Control for Medium-Voltage Drives', IEEE Transactions on Power Electronics, vol. 34, no. 9, pp. 8342-8355.
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© 1986-2012 IEEE. In medium-voltage drives, multistep model predictive control (MPC) can lower the total harmonic distortion of the stator currents and thereby reduce losses and improve efficiency. However, from the point of view of implementation, there is still uncertainty as to whether transients have a major adverse effect on achieving this improved steady-state performance. The time-varying nature of machine drives, initialization of the optimization process, and limited computational resources are identified as key factors. This paper analyzes the link between these key factors in detail, thus a suitable reformulation and selective initialization approach is designed to enable the deterministic use of multistep finite-control-set MPC irrespective of the drive system conditions. Guidelines to select the prediction horizon, weighting factor, and minimum switching frequency considering the control platform limitations are presented. The significant impacts of transients on the design and experimental validation, covering several drive conditions, are evaluated in a scaled-down three-level induction machine drive switching at 350 Hz. This paper is accompanied by a video demonstrating the real-Time implementation of multistep MPC.

Afshar, S, Hamilton, TJ, Tapson, J, van Schaik, A & Cohen, G 2019, 'Investigation of Event-Based Surfaces for High-Speed Detection, Unsupervised Feature Extraction, and Object Recognition', Frontiers in Neuroscience, vol. 12.
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Ali, A & Lee, JE-Y 2019, 'Fully Differential Piezoelectric Button-Like Mode Disk Resonator for Liquid Phase Sensing', IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 66, no. 3, pp. 600-608.
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Al‐Soeidat, M, Cheng, T, Lu, DD & Agelidis, VG 2019, 'Experimental study of static and dynamic behaviours of cracked PV panels', IET Renewable Power Generation, vol. 13, no. 16, pp. 3002-3008.
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© The Institution of Engineering and Technology 2019. Solar cell power performance is greatly affected by two critical factors ageing and crack. In order to mitigate their negative effects on the solar system, these cells are to be substituted by new cells, thus, replacing the panels. This study presents an active crack detection method that detects the cracked cells within a solar string by using AC parameter characterisation without a need to have a physical inspection. The mathematical module of the solar cell shows that it constitutes of series and parallel resistors in addition to a parallel capacitor and that their values change by ageing and crack. In addition to studying the effects of the crack on the solar cell, it is verified by the experiment that the solar cells behave as a capacitive circuit, and their capacitance increases when the cell gets cracked, getting higher as the crack becomes more serious. The experiment is extended to investigate the effect of series and parallel PV strings, which are affected by cracked and partially shaded cells to evaluate their criticality levels. By monitoring the AC parameter of the solar cell and the change of the capacitance, it is easy to detect the crack when it occurs.

Al-Soeidat, M, Lu, DD-C & Zhu, J 2019, 'An Analog BJT-Tuned Maximum Power Point Tracking Technique for PV Systems', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 4, pp. 637-641.
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© 2004-2012 IEEE. In this brief, an analog, bipolar junction transistor (BJT)-tuned voltage reference maximum power point tracking (MPPT) method for photovoltaic modules is proposed. The conventional fixed voltage reference method is the simplest method for tracking, but it does not obtain good MPPT efficiency because the maximum power point (MPP) voltage changes at different insolation levels. In reality, an approximately linear slope is formed when connecting the MPPs measured from the highest insolation level to the lowest. Utilizing this characteristic, a BJT, which has a similar electrical property, is used to implement a variable voltage reference that improves the accuracy of the MPP voltage when the insolation changes. The proposed circuit is simple and easy to implement, and it can track the MPP very quickly without the need for a digital controller or PID controller. Hence, the circuits cost and complexity are reduced. Experimental results are given to verify the feasibility of the proposed MPPT method.

Alturki, R & Gay, V 2019, 'The Development of an Arabic Weight-Loss App Akser Waznk: Qualitative Results', JMIR Formative Research, vol. 3, no. 1, pp. e11785-e11785.
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Amiri, M, Tofigh, F, Shariati, N, Lipman, J & Abolhasan, M 2019, 'Miniature tri‐wideband Sierpinski–Minkowski fractals metamaterial perfect absorber', IET Microwaves, Antennas & Propagation, vol. 13, no. 7, pp. 991-996.
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© The Institution of Engineering and Technology 2019. With rapidly growing adoption of wireless technologies, requirements for the design of a miniature wideband multiresonators are increasing. In this study, a compact fractal-based metamaterial structure with lumped resistors is described. The structure of the authors proposed absorber is a combination of Sierpinski curve and Minkowski fractal. The new combination provides larger capacitance and inductance in the system enabling perfect absorption at lower frequencies. The final structure with dimensions of 20 × 20 × 1.6 mm3 and an air gap of 12.5 mm provides three main resonances at frequencies of 2.1, 5.1, and 12.8 GHz with bandwidth (absorption ratio over 90%) of 840 MHz, 1.05 GHz, and 910 MHz, respectively.

Amjadipour, M, MacLeod, J, Lipton-Duffin, J, Tadich, A, Boeckl, JJ, Iacopi, F & Motta, N 2019, 'Electron effective attenuation length in epitaxial graphene on SiC', Nanotechnology, vol. 30, no. 2, pp. 025704-025704.
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The inelastic mean free path (IMFP) for carbon-based materials is notoriously challenging to model, and moving from bulk materials to 2D materials may exacerbate this problem, making the accurate measurements of IMFP in 2D carbon materials critical. The overlayer-film method is a common experimental method to estimate IMFP by measuring electron effective attenuation length (EAL). This estimation relies on an assumption that elastic scattering effects are negligible. We report here an experimental measurement of electron EAL in epitaxial graphene on SiC using photoelectron spectroscopy over an electron kinetic energy range of 50-1150 eV. We find a significant effect of the interface between the 2D carbon material and the substrate, indicating that the attenuation length in the so-called 'buffer layer' is smaller than for free-standing graphene. Our results also suggest that the existing models for estimating IMFPs may not adequately capture the physics of electron interactions in 2D materials.

An, L, Cheng, T & Lu, DD-C 2019, 'Single-Stage Boost-Integrated Full-Bridge Converter With Simultaneous MPPT, Wide DC Motor Speed Range, and Current Ripple Reduction', IEEE Transactions on Industrial Electronics, vol. 66, no. 9, pp. 6968-6978.
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© 1982-2012 IEEE. This paper presents a new approach to controlling and optimizing a single-stage boost-integrated full-bridge dc-dc converter for a stand-alone photovoltaic-battery-powered dc motor system by combining pulse-frequency modulation (PFM), pulsewidth modulation (PWM), and phase angle shift (PAS). Unlike most of the existing multiport dc-dc converters, which aim at regulating the output voltage (first-or second-quadrant operation), the dc motor load requires both voltage and current reversals (four-quadrant operation). The converter is able to perform three tasks simultaneously: maximum power point tracking (MPPT), battery charging/discharging, and driving the dc motor at variable speeds including bidirectional and stall motions. To achieve these control objectives, the boost inductor and the motor inductance operate in different modes such that PFM and PWM can be used to achieve MPPT and a wide motor voltage range, respectively. By properly adjusting the PAS of the duty cycles, the capacitor and battery rms current value can be reduced, while the operation of the converter remains unchanged, hence improving the conversion efficiency. Experimental results of a 26-W laboratory prototype converter confirmed the proposed design and operation and the efficiency improvement by 2-6%.

Ansari, M, Zhu, H, Shariati, N & Guo, YJ 2019, 'Compact Planar Beamforming Array With Endfire Radiating Elements for 5G Applications', IEEE Transactions on Antennas and Propagation, vol. 67, no. 11, pp. 6859-6869.
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© 1963-2012 IEEE. In this paper, a compact 4×6 Butler matrix (BM) based on microstrip lines is designed and applied to a linear antenna array. The proposed design creates four beams in four different directions within the 27.5 and 28.5 GHz band. One of the advantages of this BM is a reduction in the size of the beamforming network (BFN). In order to attain this objective, the basic microstrip-based 4×4 BM is designed, and then modified to a 4×6 BM through a dual-substrate structure to avoid crossing lines using microstrip-to-slotline transitions. The BFN is cascaded with a six-element linear antenna array with endfire radiating elements. The array can be conveniently integrated into the BFN. The resulting design benefits from low-loss characteristics, ease of realization, and low fabrication cost. The array is fabricated and tested, and the experimental results are in good agreement with the simulated ones. The multi-beam antenna size is 5.6 λ × 4.6 λ including feed lines and feed network, while the new BM design is only 3.5λ0 × 1.4λ0 , which is almost half as large as the traditional one. The measured radiation patterns show that the beams cover roughly a spatial range of 90° with a peak active gain of 11 dBi.

Argha, A, Su, SW & Celler, BG 2019, 'Control allocation-based fault tolerant control', Automatica, vol. 103, pp. 408-417.
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© 2019 Elsevier Ltd This paper describes a novel scheme for fault tolerant control using a robust optimal control design method. This scheme can also be employed as actuator redundancy management for over-actuated linear systems. In contrast to many existing methods in the literature, this scheme can be applied to systems whose control input matrix cannot be factorised into two matrices whose ranks are equal and less than the minimum of the number of columns and rows of the input matrix. The so-called virtual control, in this scheme, is calculated using a robust ℋ 2 -based feedback design approach constructed to be robust against uncertainties emanating from visibility of the control allocator to the controller and imperfection in the estimated effectiveness gain. Then, using a new control allocation scheme along with a novel Tikhonov-based re-distributor mechanism, the obtained virtual control signal is re-distributed among remaining (redundant or non-faulty) set of actuators. As the proposed scheme is modular-based, it can be employed as a real-time fault tolerant control scheme with no need to reconfigure the controller in the case of actuator faults or failures. The effectiveness of the proposed scheme is demonstrated by a numerical example.

Argha, A, Su, SW & Celler, BG 2019, 'Static output feedback fault tolerant control using control allocation scheme', International Journal of Robust and Nonlinear Control, vol. 29, no. 1, pp. 98-116.
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SummaryThis paper describes two novel schemes for fault tolerant control using robust suboptimal static output feedback design methods. These schemes can also be employed as actuator redundancy management for overactuated uncertain linear systems. In contrast to many existing methods in the literature that assume the control input matrix (i) is not of full‐rank such that it can be factorized into two matrices and (ii) it does not involve uncertainty, these schemes can be applied to systems whose control input matrix cannot be factorized and/or involve uncertainty. The so‐called virtual control, in these schemes, is calculated using suboptimal ‐based static output feedback design schemes constructed to be robust against uncertainties emanating from inherent input matrix uncertainty and visibility of the control allocator to the controller. Then, using two proposed control allocation schemes (fixed and on‐line), the obtained virtual control signal is redistributed among remaining (redundant or nonfaulty) set of actuators. As the proposed schemes are modular‐based, they can be employed as real‐time fault tolerant control schemes with no need to reconfigure the controller in the case of actuator faults or failures. The effectiveness of the proposed schemes is discussed and compared with numerical examples.

Argha, A, Su, SW, Savkin, A & Celler, B 2019, 'A framework for optimal actuator/sensor selection in a control system', International Journal of Control, vol. 92, no. 2, pp. 242-260.
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© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. When dealing with large-scale systems, manual selection of a subset of components (sensors/actuators), or equivalently identification of a favourable structure for the controller, that guarantees a certain closed-loop performance, is not very feasible. This paper is dedicated to the problem of concurrent optimal selection of actuators/sensors which can equivalently be considered as the structure identification for the controller. In the context of a multi-channel H 2 dynamic output feedback controller synthesis, we formulate and analyse a framework in which we incorporate two extra terms for penalising the number of actuators and sensors into the variational formulations of controller synthesis problems in order to induce a favourable controller structure. We then develop an explicit scheme as well as an iterative process for the purpose of dealing with the multi-objective problem of controller structure and control law co-design. It is also stressed that the immediate application of the proposed approach lies within the fault accommodation stage of a fault tolerant control scheme. By two numerical examples, we demonstrate the remarkable performance of the proposed approach.

Argha, A, Su, SW, Savkin, A & Celler, B 2019, 'Design of optimal sliding-mode control using partial eigenstructure assignment', International Journal of Control, vol. 92, no. 7, pp. 1511-1523.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group This paper describes a new framework for the design of a sliding surface for a given system while multi-channel (Formula presented.) performances of the closed-loop system are under control. In contrast to most of the current sliding surface design schemes, in this new method, the level of control effort required to maintain sliding is penalised. The proposed method for the design of optimal sliding mode control is implemented in two stages. In the first stage, a state feedback gain is derived using a linear matrix inequality (LMI)-based scheme that can assign a number of the closed-loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage by using one of the two different methods developed for this goal. The proposed theory is evaluated by using numerical examples including the problem of steady-state output tracking via a state-feedback SMC for flight control.

Argha, A, Su, SW, Zheng, WX & Celler, BG 2019, 'Sliding‐mode fault‐tolerant control using the control allocation scheme', International Journal of Robust and Nonlinear Control, vol. 29, no. 17, pp. 6256-6273.
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SummaryThis paper is devoted to the design of a novel fault‐tolerant control (FTC) using the combination of a robust sliding‐mode control (SMC) strategy and a control allocation (CA) algorithm, referred to as a CA‐based sliding‐mode FTC (SMFTC). The proposed SMFTC can also be considered a modular‐design control strategy. In this approach, first, a high‐level SMC, designed without detailed knowledge of systems' actuators/effectors, commands a vector of virtual control signals to meet the overall control objectives. Then, a CA algorithm distributes the virtual control efforts among the healthy actuators/effectors using the real‐time information obtained from a fault detection and reconstruction mechanism. As the underlying system is not assumed to have a rank‐deficient input matrix, the control allocator module is visible to the SMC module resulting in an uncertainty. Hence, the virtual control, in this scheme, is designed to be robust against uncertainties emanating from the visibility of the control allocator to the controller and imperfections in the estimated effectiveness gain. The proposed CA‐based SMFTC scheme is a unified FTC, which does not need to reconfigure the control system in the case of actuator fault or failure. Additionally, to cope with actuator saturation limits, a novel redistributed pseudoinverse‐based CA mechanism is proposed. The effectiveness of the proposed schemes is discussed with a numerical example.

Argha, A, Wu, J, Su, SW & Celler, BG 2019, 'Blood Pressure Estimation From Beat-by-Beat Time-Domain Features of Oscillometric Waveforms Using Deep-Neural-Network Classification Models', IEEE Access, vol. 7, pp. 113427-113439.
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In general, existing machine learning based approaches, developed for systolic and diastolic blood pressure (SBP and DBP) estimation from oscillometric waveforms (OWs), employ features extracted from the OW envelope (OWE) alone and ignore important beat-by-beat (BBB) features which represent fundamental physical properties of the entire non-invasive blood pressure (NIBP) measurement system. Unlike the existing literature, this paper proposes a novel deep-learning based method for BP estimation trained with BBB time-domain features extracted from OWs. First, we extract six time-domain features from each beat of the OW, relative to the preceding beat. Second, using the extracted BBB features along with the corresponding cuff pressures, we form a feature vector for each OW beat and locate it in one of three different classes, namely pre-systolic (PS), between systolic and diastolic (BSD) and after diastolic (AD). We then devise a deep-belief network (DBN)-deep neural network (DNN) classification model as well as a novel artificial feature extraction method for estimating SBP and DBP from feature vectors extracted from OWs and their corresponding deflation curves. The proposed DBN-DNN classification approach can effectively learn the complex nonlinear relationship between the artificial feature vectors and target classes. The SBP and DBP points are then obtained by mapping the beats at which the network output sequence switches from PS phase to BSD phase and from BSD phase to AD phase, respectively, to the deflation curve. Adopting a 5-fold cross-validation scheme and using a data base of 350 NIBP recordings gave an average mean absolute error of 1.1±2.9 mmHg for SBP and 3.0±5.6 mmHg for DBP relative to reference values. We experimentally show that the proposed DBN-DNN-based classification algorithm trained with BBB time-domain features can outperform traditional deep-learning based methods for BP estimation trained with features extracted only from OWEs.

Arockia Baskaran, AGR, Nanda, P, Nepal, S & He, S 2019, 'Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks', Concurrency and Computation: Practice and Experience, vol. 31, no. 23.
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Summary6LoWPAN networks involving wireless sensors consist of resource starving miniature sensor nodes. Since secured authentication is one of the important considerations, the use of asymmetric key distribution scheme may not be a perfect choice. Recent research shows that Lucky Thirteen attack has compromised Datagram Transport Layer Security (DTLS) with Cipher Block Chaining (CBC) mode for key establishment. Even though EAKES6Lo and S3 K techniques for key establishment follow the symmetric key establishment method, they strongly rely on a remote server and trust anchor. Our proposed Lightweight Authentication Protocol (LAUP) used a symmetric key method with no preshared keys and comprised of four flights to establish authentication and session key distribution between sensors and Edge Router in a 6LoWPAN environment. Each flight uses freshly derived keys from existing information such as PAN ID (Personal Area Network IDentification) and device identities. We formally verified our scheme using the Scyther security protocol verification tool. We simulated and evaluated the proposed LAUP protocol using COOJA simulator and achieved less computational time and low power consumption compared to existing authentication protocols such as the EAKES6Lo and SAKES. LAUP is evaluated using real‐time testbed and achieved less computational time, which is supportive of our simulated results.

Awwad, S, Tarvade, S, Piccardi, M & Gattas, DJ 2019, 'The use of privacy-protected computer vision to measure the quality of healthcare worker hand hygiene', International Journal for Quality in Health Care, vol. 31, no. 1, pp. 36-42.
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© 2018 The Author(s). Objectives: (i) To demonstrate the feasibility of automated, direct observation and collection of hand hygiene data, (ii) to develop computer visual methods capable of reporting compliance with moment 1 (the performance of hand hygiene before touching a patient) and (iii) to report the diagnostic accuracy of automated, direct observation of moment 1. Design: Observation of simulated hand hygiene encounters between a healthcare worker and a patient. Setting: Computer laboratory in a university. Participants: Healthy volunteers. Main outcome measures: Sensitivity and specificity of automatic detection of the first moment of hand hygiene. Methods: We captured video and depth images using a Kinect camera and developed computer visual methods to automatically detect the use of alcohol-based hand rub (ABHR), rubbing together of hands and subsequent contact of the patient by the healthcare worker using depth imagery. Results: We acquired images from 18 different simulated hand hygiene encounters where the healthcare worker complied with the first moment of hand hygiene, and 8 encounters where they did not. The diagnostic accuracy of determining that ABHR was dispensed and that the patient was touched was excellent (sensitivity 100%, specificity 100%). The diagnostic accuracy of determining that the hands were rubbed together after dispensing ABHR was good (sensitivity 83%, specificity 88%). Conclusions: We have demonstrated that it is possible to automate the direct observation of hand hygiene performance in a simulated clinical setting. We used cheap, widely available consumer technology and depth imagery which potentially increases clinical application and decreases privacy concerns.

Bah, AO, Qin, P-Y, Ziolkowski, RW, Guo, YJ & Bird, TS 2019, 'A Wideband Low-Profile Tightly Coupled Antenna Array With a Very High Figure of Merit', IEEE Transactions on Antennas and Propagation, vol. 67, no. 4, pp. 2332-2343.
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© 1963-2012 IEEE. A wideband, low-profile, tightly coupled antenna array with a simple feed network is presented. The dipole and feed networks in each unit cell are printed on both sides of a single RT/Duroid 6010 substrate with a relative dielectric constant of 10.2. The feed network, composed of meandered impedance transformer and balun sections, is designed based on Klopfenstein tapered microstrip lines. The wide-angle impedance matching is empowered by a novel wideband metasurface superstrate. For the optimum design, scanning to 70° along the E-plane is obtained together with a very high array figure of merit P A = 2.84. The H-plane scan extends to 55°. The broadside impedance bandwidth is 5.5:1 (0.80-4.38) GHz with an active voltage standing-wave ratio value ≤2. The overall height of the array above the ground plane is 0.088λ L, where λ L is the wavelength at the lowest frequency of operation. A prototype was fabricated and tested to confirm the design concepts.

Bao, F-H, Bao, J-F, Lee, JE-Y, Bao, L-L, Khan, MA, Zhou, X, Wu, Q-D, Zhang, T & Zhang, X-S 2019, 'Quality factor improvement of piezoelectric MEMS resonator by the conjunction of frame structure and phononic crystals', Sensors and Actuators A: Physical, vol. 297, pp. 111541-111541.
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Basnet, S, He, Y, Dutkiewicz, E & Jayawickrama, BA 2019, 'Resource Allocation in Moving and Fixed General Authorized Access Users in Spectrum Access System', IEEE Access, vol. 7, pp. 107863-107873.
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© 2013 IEEE. Spectrum access system (SAS) is a spectrum sharing framework proposed to share the spectrum between the incumbent users and the citizen broadband radio service devices, i.e. Priority access users and general authorized access (GAA) users. In this paper, we propose an interfering angle based method for the joint resource (channel and transmit power) allocation problem to the mobile and fixed GAA users. With mobile GAA users, the set of GAA users that can hear each other will change at different time instants making the resource allocation problem more challenging. The resource allocation of fixed and mobile GAA users is done considering coexistence with priority users, as well as coexistence between mobile and fixed GAA users. For the conflict-free resource allocation to fixed and mobile GAA users, we propose to use the maximum allowed transmit power for the beams of fixed GAA users that lie within the interference range of mobile GAA users. The simulation results show improved capacity from our proposed method while satisfying a predetermined interference constraint.

Bautista, MG, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Dutkiewicz, E 2019, 'Compact Millimeter-Wave Bandpass Filters Using Quasi-Lumped Elements in 0.13-$\mu$ m (Bi)-CMOS Technology for 5G Wireless Systems', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 7, pp. 3064-3073.
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© 1963-2012 IEEE. A design methodology for a compact millimeter-wave on-chip bandpass filter (BPF) is presented in this paper. Unlike the previously published works in the literature, the presented method is based on quasi-lumped elements, which consists of a resonator with enhanced self-coupling and metal-insulator-metal capacitors. Thus, this approach provides inherently compact designs comparing with the conventional distributed elements-based ones. To fully understand the insight of the approach, simplified LC-equivalent circuit models are developed. To further demonstrate the feasibility of using this approach in practice, the resonator and two compact BPFs are designed using the presented models. All three designs are fabricated in a standard 0.13- \mu \text{m} (Bi)-CMOS technology. The measured results show that the resonator can generate a notch at 47 GHz with the attenuation better than 28 dB due to the enhanced self-coupling. The chip size, excluding the pads, is only 0.096 \times 0.294 mm2. In addition, using the resonator for BPF designs, the first BPF has one transmission zero at 58 GHz with a peak attenuation of 23 dB. The center frequency of this filter is 27 GHz with an insertion loss of 2.5 dB, while the return loss is better than 10 dB from 26 to 31 GHz. The second BPF has two transmission zeros, and a minimum insertion loss of 3.5 dB is found at 29 GHz, while the return loss is better than 10 dB from 26 GHz to 34 GHz. Also, more than 20-dB stopband attenuation is achieved from dc to 20.5 GHz and from 48 to 67 GHz. The chip sizes of these two BPFs, excluding the pads, are only 0.076\times 0.296 mm2 and 0.096\times 0.296 mm2, respectively.

Belotti, Y, Tolomeo, S, Conneely, MJ, Huang, T, McKenna, SJ, Nabi, G & McGloin, D 2019, 'High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells', Scientific Reports, vol. 9, no. 1.
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AbstractWorldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, time-resolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.

Ben, X, Gong, C, Zhang, P, Jia, X, Wu, Q & Meng, W 2019, 'Coupled Patch Alignment for Matching Cross-View Gaits', IEEE Transactions on Image Processing, vol. 28, no. 6, pp. 3142-3157.
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© 1992-2012 IEEE. Gait recognition has attracted growing attention in recent years, as the gait of humans has a strong discriminative ability even under low resolution at a distance. Unfortunately, the performance of gait recognition can be largely affected by view change. To address this problem, we propose a coupled patch alignment (CPA) algorithm that effectively matches a pair of gaits across different views. To realize CPA, we first build a certain amount of patches, and each of them is made up of a sample as well as its intra-class and inter-class nearest neighbors. Then, we design an objective function for each patch to balance the cross-view intra-class compactness and the cross-view inter-class separability. Finally, all the local-independent patches are combined to render a unified objective function. Theoretically, we show that the proposed CPA has a close relationship with canonical correlation analysis. Algorithmically, we extend CPA to 'multi-dimensional patch alignment' that can handle an arbitrary number of views. Comprehensive experiments on CASIA(B), USF, and OU-ISIR gait databases firmly demonstrate the effectiveness of our methods over other existing popular methods in terms of cross-view gait recognition.

Bobba, SS & Agrawal, A 2019, 'Author Correction: Ultra-broad Mid-IR Supercontinuum Generation in Single, Bi and Tri Layer Graphene Nano-Plasmonic waveguides pumping at Low Input Peak Powers', Scientific Reports, vol. 9, no. 1.
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A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Chacon, A, Guatelli, S, Rutherford, H, Bolst, D, Mohammadi, A, Ahmed, A, Nitta, M, Nishikido, F, Iwao, Y, Tashima, H, Yoshida, E, Akamatsu, G, Takyu, S, Kitagawa, A, Hofmann, T, Pinto, M, Franklin, DR, Parodi, K, Yamaya, T, Rosenfeld, A & Safavi-Naeini, M 2019, 'Comparative study of alternative Geant4 hadronic ion inelastic physics models for prediction of positron-emitting radionuclide production in carbon and oxygen ion therapy', Physics in Medicine & Biology, vol. 64, no. 15, pp. 155014-155014.
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Chacon, A, Safavi-Naeini, M, Bolst, D, Guatelli, S, Franklin, DR, Iwao, Y, Akamatsu, G, Tashima, H, Yoshida, E, Nishikido, F, Kitagawa, A, Mohammadi, A, Gregoire, M-C, Yamaya, T & Rosenfeld, AB 2019, 'Monte Carlo investigation of the characteristics of radioactive beams for heavy ion therapy', Scientific Reports, vol. 9, no. 1.
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AbstractThis work presents a simulation study evaluating relative biological effectiveness at 10% survival fraction (RBE10) of several different positron-emitting radionuclides in heavy ion treatment systems, and comparing these to the RBE10s of their non-radioactive counterparts. RBE10 is evaluated as a function of depth for three positron-emitting radioactive ion beams (10C, 11C and 15O) and two stable ion beams (12C and 16O) using the modified microdosimetric kinetic model (MKM) in a heterogeneous skull phantom subject to a rectangular 50 mm × 50 mm × 60 mm spread out Bragg peak. We demonstrate that the RBE10 of the positron-emitting radioactive beams is almost identical to the corresponding stable isotopes. The potential improvement in PET quality assurance image quality which is obtained when using radioactive beams is evaluated by comparing the signal to background ratios of positron annihilations at different intra- and post-irradiation time points. Finally, the incidental dose to the patient resulting from the use of radioactive beams is also quantified and shown to be negligible.

Chen, C, liu, Z & Jin, D 2019, 'Bypassing the limit in volumetric imaging of mesoscale specimens', Advanced Photonics, vol. 1, no. 02, pp. 1-1.
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Chen, F, Hua, W, Huang, W, Zhu, J & Tong, M 2019, 'Open-circuit Fault-tolerant Strategies for a Five-phase Flux-switching Permanent Magnet Motor Based on Model Predictive Torque Control Method', Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, vol. 39, no. 2, pp. 337-346.
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To improve the fault-tolerant performance of five-phase flux-switching permanent magnet (FSPM) motor under open-circuit fault, the model predictive torque control (MPTC) was investigated. For the comprehensive control of the fundamental and harmonic subspaces, the torque, the amplitude of the stator flux linkage and the current in the harmonic subspace were employed as the control targets. Moreover, a pre-selective method, which was inspired by the switching table in the direct torque control, was developed to reduce the number of active switching states as well as the computational burden. By combining the sector where the stator flux linkage is located with the variations of the torque and the stator flux linkage magnitude, the specific voltage vectors instead of all vectors were determined as the vector candidates. As a result, the number of traversals was effectively reduced, and the computational burden was significantly alleviated. Consequently, the effectiveness of the proposed MPTC methods had been validated by simulations and experiments.

Chen, G, Jin, Z, Liu, Y, Hu, Y, Zhang, J & Qing, X 2019, 'Programmable Topology Derivation and Analysis of Integrated Three-Port DC-DC Converters with Reduced Switches for Low-Cost Applications', IEEE Transactions on Industrial Electronics, vol. 66, no. 9, pp. 1-1.
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IEEE Thanks to the favorable advantage of low cost, integrated three-port dc-dc converters with reduced switches have attracted extensive attention. In order to provide more new topologies, this paper aims to propose a programmable topology derivation method, which effectively simplifies the cumbersome process of the conventional combination method. Instead of the manual connection and examination, the proposed alternative can quickly and rigorously derive multiple viable integrated three-port dc-dc topologies from a great number of possible connections with the aid of computer program. Besides, generalized analysis is also accomplished, with which performance characteristics of all derived converters are simultaneously obtained and then a comprehensive comparison can be easily conducted to select a preferred one for the practical application. Finally, an example specific application with one input and two outputs is given, with topology selection, design and experimental results demonstrated in detail.

Chen, S-L, Karmokar, DK, Li, Z, Qin, P-Y, Ziolkowski, RW & Guo, YJ 2019, 'Circular-Polarized Substrate-Integrated-Waveguide Leaky-Wave Antenna With Wide-Angle and Consistent-Gain Continuous Beam Scanning', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4418-4428.
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© 2019 IEEE. Circularly polarized (CP) antennas are in high demand for use in future wireless communications. To advance the development of CP substrate-integrated-waveguide (SIW) leaky-wave antennas (LWAs) with the intent to meet this demand, a novel benzene-ring-shaped slot-loaded LWA with partially reflecting wall (PRW) vias is investigated and verified to realize wide-angle continuous beam scanning with consistent gain. The dispersion features of slot-loaded SIW LWAs with PRW vias are theoretically explored using an equivalent circuit model. The CP radiation feature is investigated numerically utilizing the E- A nd H-field distributions of an initial design and its equivalent magnetic currents. The results of these studies are used to demonstrate that improved CP performance over a wide-angle scan range can be attained with a change from a standard slot shape to a benzene-ring-shaped slot. The resulting benzene-ring-shaped slot-loaded CP SIW LWA was optimized, fabricated, and measured. The measured results verify that a CP beam was continuously scanned through a wide angle from backward to forward directions with a consistent gain. The prototype exhibits a continuous 97.1° CP beam scan with a gain variation between 8 and 11.3 dBic when the source frequency is swept from 9.35 to 11.75 GHz.

Chen, S-L, Karmokar, DK, Li, Z, Qin, P-Y, Ziolkowski, RW & Guo, YJ 2019, 'Continuous Beam Scanning at a Fixed Frequency With a Composite Right-/Left-Handed Leaky-Wave Antenna Operating Over a Wide Frequency Band', IEEE Transactions on Antennas and Propagation, vol. 67, no. 12, pp. 7272-7284.
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© 1963-2012 IEEE. Fixed-frequency beam scanning leaky-wave antennas (LWAs) that can scan their main beam over a specific frequency band are highly desired for future wireless communication systems. A composite right-/left-handed (CRLH) LWA is developed in this article that facilitates fixed-frequency continuous beam scanning over a wide operational frequency band. A variation of a simple single-layer nonreconfigurable frequency-based continuous beam scanning CRLH LWA is considered first. Its dispersion properties are approximately investigated using an equivalent circuit model. It is reported how two groups of varactor diodes can be incorporated into its basic circuit model to electronically control its dispersion behavior. An optimized reconfigurable CRLH LWA with practical dc biasing lines is then realized from this nonreconfigurable design. Fixed-frequency continuous beam scanning, from backward to forward directions through broadside, is reported over a wide operational frequency band. Simulations predict that the antenna can operate from 4.75 to 5.25 GHz with the main beam being continuously scannable at each frequency point. A prototype was fabricated, assembled, and tested. The measured results confirm its simulated performance characteristics.

Chen, X, Kong, X, Xu, M, Sandrasegaran, K & Zheng, J 2019, 'Road Vehicle Detection and Classification Using Magnetic Field Measurement', IEEE Access, vol. 7, pp. 52622-52633.
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Chen, X, Ni, W, Chen, T, Collings, IB, Wang, X, Liu, RP & Giannakis, GB 2019, 'Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining', IEEE Transactions on Mobile Computing, vol. 18, no. 12, pp. 2899-2912.
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IEEE Network Function Virtualization (NFV) can cost-efficiently provide network services by running different virtual network functions (VNFs) at different virtual machines (VMs) in a correct order. This can result in strong couplings between the decisions of the VMs on the placement and operations of VNFs. This paper presents a new fully decentralized online approach for optimal placement and operations of VNFs. Building on a new stochastic dual gradient method, our approach decouples the real-time decisions of VMs, asymptotically minimizes the time-average cost of NFV, and stabilizes the backlogs of network services with a cost-backlog tradeoff of [1], for any 0. Our approach can be relaxed into multiple timescales to have VNFs (re)placed at a larger timescale and hence alleviate service interruptions. While proved to preserve the asymptotic optimality, the larger timescale can slow down the optimal placement of VNFs. A learn-and-adapt strategy is further designed to speed the placement up with an improved tradeoff. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 23% and reduce the queue length (or delay) by 74%, as compared to existing benchmarks.

Chen, X, Ni, W, Collings, IB, Wang, X & Xu, S 2019, 'Automated Function Placement and Online Optimization of Network Functions Virtualization', IEEE Transactions on Communications, vol. 67, no. 2, pp. 1225-1237.
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Cheng, H, Zhang, J, Wu, Q & An, P 2019, 'A Computational Model for Stereoscopic Visual Saliency Prediction', IEEE Transactions on Multimedia, vol. 21, no. 3, pp. 678-689.
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© 2018 IEEE. Depth information plays an important role in human vision as it provides additional cues that distinguish objects from their backgrounds. This paper explores depth information for analyzing stereoscopic saliency and presents a computational model that predicts stereoscopic visual saliency based on three aspects of human vision: 1) the pop-out effect; 2) comfort zones; and 3) background effects. Through an analysis of these three phenomena, we find that most of the stereoscopic saliency region can be explained. Our model comprises three modules, each describing one aspect of saliency distribution, and a control function that can be used to adjust the three models independently. The relationship between the three models is not mutually exclusive. One, two, or three phenomena may appear in one image. Therefore, to accurately determine which phenomena the image conforms to, we have devised a selection strategy that chooses the appropriate combination of models based on the content of the image. Our approach is implemented within a framework based on the multifeature analysis. The framework considers surrounding regions, color/depth contrast, and points of interest. The selection strategy can improve the performance of the framework. A series of experiments on two recent eye-tracking datasets shows that our proposed method outperforms several state-of-the-art saliency models.

Cheng, T, Al‐Soeidat, M, Lu, DD & Agelidis, VG 2019, 'Experimental study of PV strings affected by cracks', The Journal of Engineering, vol. 2019, no. 18, pp. 5124-5128.
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Crack is one critical factor that degrades the performance of photovoltaic (PV) panels. To gain a better understanding of the impacts of cracks appeared on PVs and also to mitigate it, its failure mechanism, detrimental effects, criticality, and potential risks on independent PV panels are firstly reviewed in this study. An experimental study which investigates the degree of series connected and parallel connected PV strings which are affected by cracked cells are presented. A comparison of impacts of the partially shaded PV panel string and cracked cells happened to the PV panel string is given to evaluate their criticality levels. The experimental results show that the series connected PV panel string is strongly affected once the cell is seriously cracked, as the current generation capability is clamped. Partial shading, however, shows better performance. In addition, though the overall power the parallel connected PV string is reduced, it is less affected by the cracked cells compared to the series connected one. Lastly, a bypass diode is added to a series connected PV panel string with cracked cells, and the experimental results show that it can be an effective way to minimise the negative impacts of cracks.

Cheng, Z, Xiong, G, Liu, Y, Zhang, T, Tian, J & Guo, YJ 2019, 'High‐efficiency Doherty power amplifier with wide OPBO range for base station systems', IET Microwaves, Antennas & Propagation, vol. 13, no. 7, pp. 926-929.
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© The Institution of Engineering and Technology 2019. A high-efficiency, S-band Doherty power amplifier (DPA) with wide output power back-off (OPBO) range is presented. A novel parasitic capacitance compensation approach is applied at the output of Cree's GaN high-electron-mobility transistor to achieve high saturation efficiency in a wide OPBO range. Specifically, a parallel shorting microstrip line between the transistor output and its match network is adopted to realise parasitic capacitance compensation. The measurement results indicate good Doherty behaviour with 10 dB back-off efficiency of 40.6-44.2% and saturation efficiency of 70.2-73.3% over 2.9-3.3 GHz. When stimulated by a 20-MHz LTE signal with 7.5 dB PAPR, the proposed Doherty amplifier power, combined with digital predistortion, achieved adjacent channel leakage ratios below -47.2 dBc. The DPA demonstrate superior performance in OPBO range and efficiency, which makes it an ideal component for base station communication systems.

Cui, P-F, Zhang, JA, Lu, W-J, Guo, YJ & Zhu, H 2019, 'Statistical Sparse Channel Modeling for Measured and Simulated Wireless Temporal Channels', IEEE Transactions on Wireless Communications, vol. 18, no. 12, pp. 5868-5881.
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© 2002-2012 IEEE. Time-domain wireless channels are generally modeled by Tapped Delay Line (TDL) model and its variants. These models are not effective for channel representation and estimation when the number of multipath taps is large. Compressive sensing (CS) provides a powerful tool for sparse channel modeling and estimation. Most of the research has been focusing on sparse channel estimation, while sparse channel modeling (SCM) is rarely considered for centimetre-wave channels. In this paper, we investigate statistical sparse channel modeling, using both measured and simulated channels over a frequency range of 6 to 8.5 GHz. We first introduce the triple equilibrium principle to explore the trade-off between sparsity, modeling accuracy, and algorithm complexity in SCM, and provide a methodology for characterizing the sparsity of time-domain channels using single-measurement-vector compressive sensing algorithms. Using mainly the selected wavelet dictionary and various CS reconstruction (aka recovery) algorithms, we then present comprehensive statistical sparse channel models, including channel sparsity, magnitude decaying profile, sparse coefficient distribution and atomic index distribution. Connections between the parameters of conventional TDL and sparse channel models are mathematically established. We also propose three methods for generating simulated channels from the developed sparse channel models, which validates their effectiveness.

Cui, Q, Wang, Y, Chen, K-C, Ni, W, Lin, I-C, Tao, X & Zhang, P 2019, 'Big Data Analytics and Network Calculus Enabling Intelligent Management of Autonomous Vehicles in a Smart City', IEEE Internet of Things Journal, vol. 6, no. 2, pp. 2021-2034.
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Dang, C, Zhang, J, Kwong, C-P & Li, L 2019, 'Demand Side Load Management for Big Industrial Energy Users Under Blockchain-Based Peer-to-Peer Electricity Market', IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6426-6435.
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© 2010-2012 IEEE. Blockchain is the key technology of Bitcoin and other cryptocurrencies, and it is one of the most exciting technologies changing the world as of late. Targeting at big industrial energy users, this paper first presents a new market structure (i.e., transaction rules) under existing blockchain-based electricity transaction platforms to cover popular types of markets such as contract, day-ahead, adjustment and balancing markets; and then focuses on the optimal load management problem for a particular industrial user. The proof-of-work cost from blockchain is also modeled. A key feature of this load management problem is that the user has direct control on its own load. The obtained load control model is much more accurate than existing approaches in which system operators or demand aggregators cannot control load directly and have to rely on inaccurate estimations. As a case study, the pumping load of a water supply plant is investigated to illustrate how the demand load is managed under this blockchain-based market. From the case study, it is found that 18.9% of total cost can be saved under this new market structure.

Dietrich, A, Bürk, M, Steiger, ES, Antoniuk, L, Tran, TT, Nguyen, M, Aharonovich, I, Jelezko, F & Kubanek, A 2019, 'Reply to “Comment on ‘Observation of Fourier transform limited lines in hexagonal boron nitride’”', Physical Review B, vol. 100, no. 4.
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© 2019 American Physical Society. In this Reply, we answer to the comments by Langbein [Phys. Rev. B 100, 047401 (2019)10.1103/PhysRevB.100.047401]. We disagree with the argument that our measured spectral shapes and the extracted linewidths are caused by temporal blinking. We give detailed information on our evaluation process to exclude blinking events. Beyond the question raised in the Comment, we analyze the influence of spectral diffusion. Although spectral diffusion is an ongoing limitation for defect centers in hexagonal boron nitride, we prove that it is not influencing our extracted linewidths.

Ding, G, Zhang, S, Khan, S, Tang, Z, Zhang, J & Porikli, F 2019, 'Feature Affinity-Based Pseudo Labeling for Semi-Supervised Person Re-Identification', IEEE Transactions on Multimedia, vol. 21, no. 11, pp. 2891-2902.
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© 1999-2012 IEEE. Vision-based person re-identification aims to match a person's identity across multiple images, which is a fundamental task in multimedia content analysis and retrieval. Deep neural networks have recently manifested great potential in this task. However, a major bottleneck of existing supervised deep networks is their reliance on a large amount of annotated training data. Manual labeling for person identities in large-scale surveillance camera systems is quite challenging and incurs significant costs. Some recent studies adopt generative model outputs as training data augmentation. To more effectively use these synthetic data for an improved feature learning and re-identification performance, this paper proposes a novel feature affinity-based pseudo labeling method with two possible label encodings. To the best of our knowledge, this is the first study that employs pseudo-labeling by measuring the affinity of unlabeled samples with the underlying clusters of labeled data samples using the intermediate feature representations from deep networks. We propose training the network with the joint supervision of cross-entropy loss together with a center regularization term, which not only ensures discriminative feature representation learning but also simultaneously predicts pseudo-labels for unlabeled data. We show that both label encodings can be learned in a unified manner and help improve the overall performance. Our extensive experiments on three person re-identification datasets: Market-1501, DukeMTMC-reID, and CUHK03, demonstrate significant performance boost over the state-of-the-art person re-identification approaches.

Dou, Y, Li, Y, Zhu, J, Wang, L, Li, A & Zhang, C 2019, 'High-frequency effects analysis of windings in magnetic properties tester with nanocrystalline core', International Journal of Applied Electromagnetics and Mechanics, vol. 61, pp. S81-S88.
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Du, G, Xu, W, Zhu, J & Huang, N 2019, 'Rotor Stress Analysis for High-Speed Permanent Magnet Machines Considering Assembly Gap and Temperature Gradient', IEEE Transactions on Energy Conversion, vol. 34, no. 4, pp. 2276-2285.
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© 1986-2012 IEEE. For predesigned high speed permanent magnet machines (HSPMMs), the accurate evaluation of rotor strength is extremely important to ensure the reliability of the rotor at high speeds. This paper mainly addresses a comprehensive study on the rotor stress of one predesigned HSPMM with predetermined dimensions, by considering the effect of the assembly gaps between the segmented PMs and between the PMs and the pole filler, and temperature gradient in the rotor. First, the influence of the assembly gaps for different rotor structures, different PM segments, different pole fillers, different material properties on the rotor stress are summarized by Ansys Workbench. Then, the full investigation on the rotor stress distribution is performed under the influence of the rotor temperature gradient, which is obtained by Ansys-Cfx. And then, by considering the non-isothermal distribution of rotor temperature, the 3D temperature-stress coupling analysis is performed to obtain the optimal sleeve thickness. After fabricating the prototype, continuous operation test is carried out, which validates the effectiveness of aforementioned theoretical analysis.

Duan, L, Sun, C-A, Zhang, Y, Ni, W & Chen, J 2019, 'A Comprehensive Security Framework for Publish/Subscribe-Based IoT Services Communication', IEEE Access, vol. 7, pp. 25989-26001.
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Duan, N, Xu, W, Li, Y, Wang, S & Zhu, J 2019, 'A Temperature and Stress Dependent Hysteresis Model with Experiment Validation', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 34, no. 13, pp. 2686-2692.
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The design and performance analysis of the electrical equipment usually involve the coupling of electrical, magnetic, thermal, mechanical and other physical fields. With the development of numerical calculation technology of electromagnetic field and the improvement of computer performance, the electromagnetic field numerical simulation software has been widely used to analyze the coupling problem of electromagnetic field, thermal field and mechanical field. The magnetic properties of magnetic material under work conditions will be influenced by some non-magnetic factors, such as temperature and stress. However, these characteristics are difficult to be simulated by the traditional hysteresis models. In this paper, based on the microscopic magnetization mechanisms of magnetic materials, a hysteresis elemental operator, which contains two easy axes and two hard axes, has been presented. Besides, with the help of the energy minimum principle, the octagonal law which can determine the orientation of the magnetization has been introduced. By taking into account the differences between the laboratory conditions and the practical engineering manufacturing and operation, the temperature-depended saturation magnetization, temperature-depended anisotropy, and stress-depended distribution function are introduced to the hysteresis elemental operator. With the employment of the Gaussian-Gaussian distribution function and the interaction field, a temperature and stress dependent hysteresis model is proposed to simulate the magnetic properties under different temperature and stress conditions. Finally, by comparing the simulation results with the experimental measurement results, the effectiveness and viability of this proposed hysteresis model have been confirmed.

Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2019, 'Correction: Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models', PLOS ONE, vol. 14, no. 4, pp. e0214973-e0214973.
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© 2019 Esmaili et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. After publication of this article [1], concerns were raised that the references to the software packages used for this analysis had been omitted. The authors utilized Stata Statistical Software: Release 15. The reference is StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC. The authors also utilized the seqHMM package package in R. The reference is: Helske S, Helske J. Mixture hidden markov models for sequence data: the seqhmm package in R. arXiv preprint arXiv:1704.00543. 2017 Apr 3.

Fan, Y, Lin, X, Liang, W, Tan, G & Nanda, P 2019, 'A secure privacy preserving deduplication scheme for cloud computing', Future Generation Computer Systems, vol. 101, pp. 127-135.
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© 2019 Elsevier B.V. Data deduplication is a key technique to improve storage efficiency in cloud computing. By pointing redundant files to a single copy, cloud service providers greatly reduce their storage space as well as data transfer costs. Despite of the fact that the traditional deduplication approach has been adopted widely, it comes with a high risk of losing data confidentiality because of the data storage models in cloud computing. To deal with this issue in cloud storage, we first propose a TEE (trusted execution environment) based secure deduplication scheme. In our scheme, each cloud user is assigned a privilege set; the deduplication can be performed if and only if the cloud users have the correct privilege. Moreover, our scheme augments the convergent encryption with users’ privileges and relies on TEE to provide secure key management, which improves the ability of such cryptosystem to resist chosen plaintext attacks and chosen ciphertext attacks. A security analysis indicates that our scheme is secure enough to support data deduplication and to protect the confidentiality of sensitive data. Furthermore, we implement a prototype of our scheme and evaluate the performance of our prototype, experiments show that the overhead of our scheme is practical in realistic environments.

Gabela, J, Kealy, A, Li, S, Hedley, M, Moran, W, Ni, W & Williams, S 2019, 'The Effect of Linear Approximation and Gaussian Noise Assumption in Multi-Sensor Positioning Through Experimental Evaluation', IEEE Sensors Journal, vol. 19, no. 22, pp. 10719-10727.
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© 2001-2012 IEEE. Assumptions of Gaussianity in describing the errors of ranging data and linearization of the measurement models are well-accepted techniques for wireless tracking multi-sensor fusion. The main contribution of this paper is the empirical study on the effect of these assumptions on positioning accuracy. A local positioning system (LPS) was set up and raw data were collected using both the global satellite navigation system (GNSS) and the LPS. These data were fused to estimate position using both an extended Kalman filter (EKF) and a particle filter (PF). For these data, it was shown that the PF had an improvement in accuracy over the EKF of 67 cm (72%) with achieved accuracy of 26 cm. This improvement was attributed to the PF handling the non-linear system dynamics, rather than a linear approximation as in the EKF. Furthermore, when the PF used the fitted three-component Gaussian mixture model as the better approximation of the actual LPS ranging error distribution, rather than a Gaussian approximation, a further 3 cm (13%) reduction in positioning error was observed. Overall, the average accuracy of 23 cm was achieved for the proposed multi-sensor positioning system when the assumptions of Gaussianity are not made and the non-linear measurement model is not linearized.

Gao, X, Du, J, Zhang, T & Guo, YJ 2019, 'High-<italic>T_c </italic> Superconducting Fourth-Harmonic Mixer Using a Dual-Band Terahertz On-Chip Antenna of High Coupling Efficiency', IEEE Transactions on Terahertz Science and Technology, vol. 9, no. 1, pp. 55-62.
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© 2019 IEEE. This paper presents a dual-band on-chip antenna-coupled high-Tc superconducting (HTS) Josephson-junction subterahertz (THz) fourth-harmonic mixer. The antenna utilizes a couple of different structured twin slots to enable the resonant radiations at two frequencies, and integrates a well-designed coplanar waveguide network for achieving good radiation coupling and signal isolation characteristics. The electromagnetic simulations show that coupling efficiencies as high as -4 and -3.5 dB are achieved for the 160- and 640-GHz operating frequency bands, respectively. Based on this dual-band antenna, a 640-GHz HTS fourth-harmonic mixer is developed and characterized in a range of operating temperatures. The mixer exhibits a measured conversion gain of around -18 dB at 20 K and -22 dB at 40 K, respectively. The achieved intermediate frequency bandwidth is larger than 23 GHz. These are the best results reported for HTS harmonic mixers at comparable sub-THz frequency bands to date.

Gargiulo, G, Bifulco, P, Cesarelli, M, McEwan, A, Nikpour, A, Jin, C, Gunawardana, U, Sreenivasan, N, Wabnitz, A & Hamilton, T 2019, 'Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented', Sensors, vol. 19, no. 4, pp. 772-772.
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The Open-electroencephalography (EEG) framework is a popular platform to enable EEG measurements and general purposes Brain Computer Interface experimentations. However, the current platform is limited by the number of available channels and electrode compatibility. In this paper we present a fully configurable platform with up to 32 EEG channels and compatibility with virtually any kind of passive electrodes including textile, rubber and contactless electrodes. Together with the full hardware details, results and performance on a single volunteer participant (limited to alpha wave elicitation), we present the brain computer interface (BCI)2000 EEG source driver together with source code as well as the compiled (.exe). In addition, all the necessary device firmware, gerbers and bill of materials for the full reproducibility of the presented hardware is included. Furthermore, the end user can vary the dry-electrode reference circuitry, circuit bandwidth as well as sample rate to adapt the device to other generalized biopotential measurements. Although, not implemented in the tested prototype, the Biomedical Analogue to Digital Converter BIOADC naturally supports SPI communication for an additional 32 channels including the gain controller. In the appendix we describe the necessary modification to the presented hardware to enable this function.

Gay, VC, Garcia, JA & Leong, TW 2019, 'Using Asynchronous Exergames to Encourage an Active Ageing Lifestyle: Solitaire Fitness Study Protocol.', Stud Health Technol Inform, vol. 266, pp. 70-75.
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A healthy and active lifestyle can significantly improve the well-being and quality of life; however, some elderly people struggle to stay motivated and engaged with any form of exercise. The project Elaine (Elderly, AI and New Experiences) addresses this problem by seeking to improve the quality of life of the elderly through exergames. Currently, the project explores a novel approach in the field of health informatics called asynchronous exergaming. This approach, a new trend in games in the health domain, allows the elderly to workout at their own pace, and in their own time, with their physical activity linked asynchronously to a game. This paper presents the study protocol for Solitaire Fitness, a new asynchronous exergame developed by the team. The game aims at increasing the motivation of the elderly to engage in physical exercise whilst helping to maintain their cognitive abilities. It also describes the protocol for the trial. The result of this research has the potential to benefit elderly that need nudging to be motivated to exercise, health care providers treating people with sedentary lifestyles and researchers investigating ways to encourage the elderly to exercise.

Geng, L, Lu, Z, He, L, Zhang, J, Li, X & Guo, X 2019, 'Smart charging management system for electric vehicles in coupled transportation and power distribution systems', Energy, vol. 189, pp. 116275-116275.
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© 2019 Elsevier Ltd With the increasing popularity of electric vehicles, the connections between urban transportation and power distribution systems gradually change from independent to tightly coupled. To promote the coordinated operation of the two kind of systems, this paper proposes a smart charging management system considering the elastic response of electric vehicle users to electricity charging price. In this system, a multi-class user traffic equilibrium assignment model with elastic charging demand is formulated to capture link flow distributions of vehicles across the urban transportation network and estimate charging demand of each fast charging station. An alternating current optimal power flow model for power distribution network is also established to calculate optimal charging capacity of each fast charging station and scheduling plan of generators. Combining the above two models, a distributed coordination pricing method is designed based on alternating direction multiplier method, which can obtain a proper electricity charging price signal to better manage electric vehicles. A case study is performed to show the effectiveness of the proposed model and the distributed coordination pricing method.

Ghadi, MJ, Ghavidel, S, Rajabi, A, Azizivahed, A, Li, L & Zhang, J 2019, 'A review on economic and technical operation of active distribution systems', Renewable and Sustainable Energy Reviews, vol. 104, pp. 38-53.
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© 2019 Elsevier Ltd Along with the advent of restructuring in power systems, considerable integration of renewable energy resources has motivated the transition of traditional distribution networks (DNs) toward new active ones. In the meanwhile, rapid technology advances have provided great potentials for future bulk utilization of generation units as well as the energy storage (ES) systems in the distribution section. This paper aims to present a comprehensive review of recent advancements in the operation of active distribution systems (ADSs) from the viewpoint of operational time-hierarchy. To be more specific, this time-hierarchy consists of two stages, and at the first stage of this time-hierarchy, four major economic factors, by which the operation of traditional passive DNs is evolved to new active DNs, are described. Then the second stage of the time-hierarchy refers to technical management and power quality correction of ADSs in terms of static, dynamic and transient periods. In the end, some required modeling and control developments for the optimal operation of ADSs are discussed. As opposed to previous review papers, potential applications of devices in the ADS are investigated considering their operational time-intervals. Since some of the compensating devices, storage units and generating sources may have different applications regarding the time scale of their utilization, this paper considers real scenario system operations in which components of the network are firstly scheduled for the specified period ahead; then their deviations of operating status from reference points are modified during three time-intervals covering static, dynamic and transient periods.

Ghadi, MJ, Rajabi, A, Ghavidel, S, Azizivahed, A, Li, L & Zhang, J 2019, 'From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors', Applied Energy, vol. 253, pp. 113543-113543.
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© 2019 Elsevier Ltd Restructuring of power systems along with the integration of renewable energy resources in electricity networks have transformed traditional distribution networks (DNs) into new active distribution systems (ADSs). In addition, rapid advancement of technology has enabled the bulk utilization of power generation units and energy storage (ES) systems in distribution networks. The next step in this trend is to decentralize ADSs to microgrids (MGs). This paper aims to present a review on the recent advancements in the development of ADSs and MGs. In this respect, the regulatory requirements and economic concepts, by which the traditional passive DNs are evolved into ADSs, are categorized and illustrated first. Then, the state-of-the-art of ADS formation is detailed based on the novel standpoint of grid operation factors which are involved in deregulated electricity markets at the distribution level. After presenting highlighted projects of MGs across the world, a similar review approach has been adopted to explain the formation of MGs which play a vital role in the decentralization of ADSs. This survey can provide both policy makers and distribution system planners with new perspectives to establish or participate in day-ahead wholesale markets.

Ghasemi, M, Akbari, E, Rahimnejad, A, Razavi, SE, Ghavidel, S & Li, L 2019, 'Phasor particle swarm optimization: a simple and efficient variant of PSO', Soft Computing, vol. 23, no. 19, pp. 9701-9718.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Particle swarm optimizer is a well-known efficient population and control parameter-based algorithm for global optimization of different problems. This paper focuses on a new and primary sample for PSO, which is named phasor particle swarm optimization (PPSO) and is based on modeling the particle control parameters with a phase angle (θ), inspired from phasor theory in the mathematics. This phase angle (θ) converts PSO algorithm to a self-adaptive, trigonometric, balanced, and nonparametric meta-heuristic algorithm. The performance of PPSO is tested on real-parameter optimization problems including unimodal and multimodal standard test functions and traditional benchmark functions. The optimization results show good and efficient performance of PPSO algorithm in real-parameter global optimization, especially for high-dimensional optimization problems compared with other improved PSO algorithms taken from the literature. The phasor model can be used to expand different types of PSO and other algorithms. The source codes of the PPSO algorithms are publicly available at https://github.com/ebrahimakbary/PPSO.

Ghavidel, S, Rajabi, A, Ghadi, MJ, Azizivahed, A, Li, L & Zhang, J 2019, 'Risk‐constrained demand response and wind energy systems integration to handle stochastic nature and wind power outage', IET Energy Systems Integration, vol. 1, no. 2, pp. 114-120.
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Ghosh, S & Lee, JE-Y 2019, 'Piezoelectric-on-Silicon MEMS Lorentz Force Lateral Field Magnetometers', IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 66, no. 5, pp. 965-974.
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Ghosh, SS, Nathan, KS, Siwakoti, YP & Long, T 2019, 'Dual polarity DC–DC converter integrated grid‐tied single‐phase transformer less inverter for solar application', The Journal of Engineering, vol. 2019, no. 17, pp. 3962-3966.
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Golsorkhi, MS, Shafiee, Q, Lu, DD-C & Guerrero, JM 2019, 'Distributed Control of Low-Voltage Resistive AC Microgrids', IEEE Transactions on Energy Conversion, vol. 34, no. 2, pp. 573-584.
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IEEE This paper proposes a distributed control strategy for coordination of distributed energy resources (DERs) in low-voltage resistive microgrids. The proposed framework consists of two level structure; primary and secondary control. Unlike the existing distributed control solutions, the proposed method is based upon the practical assumption of resistive network impedance. The primary control level consists of a V-I droop mechanism, where GPS timing is used to synchronize the control agents. A consensus-based distributed secondary control method is introduced to improve the voltage regulation and load sharing accuracy of the V-I droop method. In the proposed approach, the d-axis component of the voltage is altered so as to regulate the average microgrid voltage to the rated value while guarantying proper sharing of active power among the DERs. Additionally, the q-axis component of voltage is adjusted to perform proper current and, accordingly reactive power sharing. The proposed control methodology accounts for the distribution line impedances. It features a plug-and-play environment; prior system knowledge is not required, and an arbitrary DER can enter the microgrid without any need for additional synchronization. An AC microgrid is prototyped to experimentally demonstrate the efficacy of the proposed method.

Gong, S, Gao, L, Xu, J, Guo, Y, Hoang, DT & Niyato, D 2019, 'Exploiting Backscatter-Aided Relay Communications With Hybrid Access Model in Device-to-Device Networks', IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 835-848.
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© 2015 IEEE. The backscatter and active RF radios can complement each other and bring potential performance gain. In this paper, we envision a dual-mode radio structure that allows each device to make smart decisions on mode switch between backscatter communications (i.e., the passive mode) or RF communications (i.e., the active mode), according to the channel and energy conditions. The flexibility in mode switching also makes it more complicated for transmission control and network optimization. To exploit the radio diversity gain, we consider a wireless powered device-to-device network of hybrid radios and propose a sum throughput maximization by jointly optimizing energy beamforming and transmission scheduling in two radio modes. We further exploit the user cooperation gain by allowing the passive radios to relay for the active radios. As such, the sum throughput maximization is reformulated into a non-convex. We first present a sub-optimal algorithm based on successive convex approximation, which optimizes the relays' reflection coefficients by iteratively solving semi-definite programs. We also devise a set of heuristic algorithms with reduced computational complexity, which are shown to significantly improve the sum throughput and amenable for practical implementation.

Gong, S, Hoang, DT, Niyato, D, El Shafie, A, De Domenico, A, Strinati, EC & Hoydis, J 2019, 'Introduction to the special section on deep reinforcement learning for future wireless communication networks', IEEE Transactions on Cognitive Communications and Networking, vol. 5, no. 4, pp. 1019-1023.
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Guo, H, Wang, F, Li, L, Zhang, L & Luo, J 2019, 'A Minimum Loss Routing Algorithm Based on Real-Time Transaction in Energy Internet', IEEE Transactions on Industrial Informatics, vol. 15, no. 12, pp. 6446-6456.
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© 2005-2012 IEEE. Due to capacity constraints and the uneven distribution of resources, it becomes a trend that multiple microgrids are interconnected as a net structure through energy routers. With the large-scale penetration of distributed energy, the supply mode of energy networks has been gradually transformed into multisource, multipath, and networked supply. In order to adapt to the energy supply mode and the real-time power transaction, a minimum loss routing (MLR) algorithm based on real-time transaction is proposed to realize the end-to-end energy transmission. On the basis of bidding information, the real-time transaction is introduced to determine the source and destination address of power transmission and the amount and transmission time of power flows. Then, an MLR is selected for transaction power, which minimizes the power loss caused by conversion and transmission. As the key of power real-time transaction, the solutions to transmission time difference, single-loop or double-loop power supply modes, and congestion managements are incorporated with the Dijkstra algorithm to find a no-congestion MLR in this paper. Finally, the effectiveness of the proposed optimization algorithm in the selection of MLR and congestion managements is verified by simulations.

Guo, K & Guo, Y 2019, 'Key Parameter Design and Analysis of Flux Reversal Linear Rotary Permanent Magnet Actuator', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-5.
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© 2002-2011 IEEE. Flux reversal linear rotary permanent magnet actuator (FR-LRPMA) is a two-degree-of-freedom actuator with two ferromagnetic (Fe) poles and two permanent magnet (PM) poles mounted on the surface of each stator pole. The flux linkage waveform of the actuator is more sinusoidal than that of the traditional topology, which are analyzed by the ideal linear model of one stator section of the proposed actuator. In order to reduce the amplitudes of the cogging torque and detent force, a key space gap parameter of the FR-LRPMA between the Fe pole and PM pole is studied in the circumferential and axial directions. The expressions of cogging torque and detent force are derived by the magnetomotive force analytical method, which are used to obtain the optimal space gap parameter value. The electromagnetic characteristics of the actuator are analyzed by the finite-element method. The amplitudes of cogging torque and detent force are reduced and the back electromotive force waveform is more sinusoidal than that of the original topology, which are verified by the experiment.

Guo, K, Chai, R, Candra, H, Guo, Y, Song, R, Nguyen, H & Su, S 2019, 'A Hybrid Fuzzy Cognitive Map/Support Vector Machine Approach for EEG-Based Emotion Classification Using Compressed Sensing', International Journal of Fuzzy Systems, vol. 21, no. 1, pp. 263-273.
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© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Due to the high dimensional, non-stationary and non-linear properties of electroencephalogram (EEG), a significant portion of research on EEG analysis remains unknown. In this paper, a novel approach to EEG-based human emotion study is presented using Big Data methods with a hybrid classifier. An EEG dataset is firstly compressed using compressed sensing, then, wavelet transform features are extracted, and a hybrid Support Vector Machine (SVM) and Fuzzy Cognitive Map classifier is designed. The compressed data is only one-fourth of the original size, and the hybrid classifier has the average accuracy by 73.32%. Comparing to a single SVM classifier, the average accuracy is improved by 3.23%. These outcomes show that psychological signal can be compressed without the sparsity identity. The stable and high accuracy classification system demonstrates that EEG signal can detect human emotion, and the findings further prove the existence of the inter-relationship between various regions of the brain.

Guo, L, Zhu, H & Abbosh, A 2019, 'Phase Reconfigurable Microwave Power Divider', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 1, pp. 21-25.
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© 2004-2012 IEEE. A reconfigurable power divider (PD) that can operate either in an in-phase mode or out-of-phase mode is presented. To that end, the novel concept of using tunable phase shifter, which is a reflection-type loaded coupled lines, to emulate an effective variable length transmission line (TL) is utilized. The proposed PD uses a quarter-wavelength TL, a 100 Ω isolation resistor and two tunable phase shifters. The presented theoretical analysis shows that by properly selecting the parameters of the phase shifter, it can be used to approximate the performance of variable length TL. To validate the design, a prototype of dimensions 50 mm × 25 mm is built, using Rogers RO3010 substrate, and tested. The results indicate that the device can operate as an in-phase and out-of-phase by using suitable biasing voltages. Across the band 0.9-1.1 GHz, the device has more than 12 dB return loss at all the ports and more than 15 dB isolation between the two output ports with less than 5° phase deviation for both of the in-phase and out-of-phase states.

Guo, Q, Zhang, Y, Celler, BG & Su, SW 2019, 'Neural Adaptive Backstepping Control of a Robotic Manipulator With Prescribed Performance Constraint', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3572-3583.
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IEEE This paper presents an adaptive neural network (NN) control of a two-degree-of-freedom manipulator driven by an electrohydraulic actuator. To restrict the system output in a prescribed performance constraint, a weighted performance function is designed to guarantee the dynamic and steady tracking errors of joint angle in a required accuracy. Then, a radial-basis-function NN is constructed to train the unknown model dynamics of a manipulator by traditional backstepping control (TBC) and obtain the preliminary estimated model, which can replace the preknown dynamics in the backstepping iteration. Furthermore, an adaptive estimation law is adopted to self-tune every trained-node weight, and the estimated model is online optimized to enhance the robustness of the NN controller. The effectiveness of the proposed control is verified by comparative simulation and experimental results with Proportional-integral-derivative and TBC methods.

Gurjar, DS, Nguyen, HH & Tuan, HD 2019, 'Wireless Information and Power Transfer for IoT Applications in Overlay Cognitive Radio Networks', IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3257-3270.
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IEEE This paper proposes and investigates an overlay spectrum sharing system in conjunction with the simultaneous wireless information and power transfer (SWIPT) to enable communications for the Internet of Things (IoT) applications. Considered is a cooperative cognitive radio network, where two IoT devices (IoDs) exchange their information and also provide relay assistance to a pair of primary users (PUs). Different from most existing works, in this paper, both IoDs can harvest energy from the radio-frequency (RF) signals received from the PUs. By utilizing the harvested energy, they provide relay cooperation to PUs and realize their own communications. For harvesting energy, a time-switching (TS) based approach is adopted at both IoDs. With the proposed scheme, one round of bidirectional information exchange for both primary and IoT systems is performed in four phases, i.e., one energy harvesting (EH) phase and three information processing (IP) phases. Both IoDs rely on the decode-and-forward operation to facilitate relaying, whereas the PUs employ selection combining (SC) technique. For investigating the performance of the considered network, this paper first provides exact expressions of user outage probability (OP) for the primary and IoT systems under Nakagami-m fading. Then, by utilizing the expressions of user OP, the system throughput and energy efficiency are quantified together with the average end-to-end transmission time. Numerical and simulation results are provided to give useful insights into the system behavior and to highlight the impact of various system/channel parameters.

Ha, QP, Yen, L & Balaguer, C 2019, 'Robotic autonomous systems for earthmoving in military applications', Automation in Construction, vol. 107, pp. 102934-102934.
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© 2019 Elsevier B.V. Along with increasing innovations in frontier engineering sciences, the advancement in Robotic Autonomous Systems (RAS) has brought about a new horizon in earthmoving processes for construction. In the military domain, there is also an increasing interest in utilising RAS technologies. In particular, ground-based forces are frequently called upon to conduct earthmoving tasks as part of military operations, tasks which could be partially or fully aided by the employment of RAS technologies. There have been rapid developments in military construction automation using high-mobility ground-based platforms, human-machine and machine-machine interfaces, teleoperation and control systems, data transmission systems, machine perception and manipulation capabilities, as well as advances in networked robotics and cyberphysical systems. Given these developments it is timely to undertake a comprehensive overview on the topic of interest to the research community and the authority. This paper presents an overview of the RAS development for platform-centric earthworks together with an analysis of the technical feasibility, maturity, key technical challenges, and future directions for the application of RAS technologies to earthmoving tasks of interest to the army.

Han, L, Han, XF, Ou, XP & Guo, Y 2019, 'Operating performances analysis of brushless doubly-fed machine using magnetic equivalent circuit', Dianji yu Kongzhi Xuebao/Electric Machines and Control, vol. 23, no. 1, pp. 27-34.
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There are few effective tools to quickly and correctly analyze the operating performances of Brushless Doubly-Fed Machine (BDFM) due to its special structure and complex magnetic field modulation mechanism. Based on the basic concept of Magnetic Equivalent Circuit (MEC), this paper described the method for establishing the MEC model of BDFM with cage rotor, considering the effects of special structure of BDFM, core saturation and rotor revolution. Furthermore, a dynamic MEC model of a prototype with cage rotor was built up and solved by the mesh method. And then, the operating performances of the prototype under different operating conditions were obtained and analyzed. Finally, the results of dynamic MEC model were compared with those of Finite Element Analysis (FEA) and experiment data. The results show that the dynamic MEC model can correctly predict the operating performances of BDFM with cage rotor and is much faster than FEA. This work can broaden the research thought for analyzing the operating performances of BDFM of cage rotor.

Han, L, Zhou, M, Han, S, Jia, W, Sun, C & Fu, C 2019, 'Targeting malware discrimination based on reversed association task', Concurrency and Computation: Practice and Experience, vol. 31, no. 23.
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SummaryRegarding the current situation that the recognition rate of malware is decreasing, the article points out that the reason for this dilemma is that more and more targeting malware have emerged, which share little or no common feature with traditional malware. The premise of malware recognition judging whether a software is malicious or benign is actually a decision problem. We propose that malware discrimination should resort to the corresponding task or purpose. We first present a formal definition of a task and then provide further classifications of malicious tasks. Based on the decidable theory, we prove that task performed by any software is recursive and determinable. By establishing a mapping from software to task, we prove that software is many‐to‐one reducible to corresponding tasks. Thus, we demonstrate that software, including malware, is also recursive and can be determined by the corresponding tasks. Finally, we present the discrimination process of our method. Nine real malwares are presented, which were firstly discriminated by our method but at that time could not be identified by Kaspersky, McAfee, Symantec Norton, or Kingsoft Antivirus.

Han, L, Zhou, M, Jia, W, Dalil, Z & Xu, X 2019, 'Intrusion detection model of wireless sensor networks based on game theory and an autoregressive model', Information Sciences, vol. 476, pp. 491-504.
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© 2018 Elsevier Inc. An effective security strategy for Wireless Sensor Networks (WSNs) is imperative to counteract security threats. Meanwhile, energy consumption directly affects the network lifetime of a wireless sensor. Thus, an attempt to exploit a low-consumption Intrusion Detection System (IDS) to detect malicious attacks makes a lot of sense. Existing Intrusion Detection Systems can only detect specific attacks and their network lifetime is short due to their high energy consumption. For the purpose of reducing energy consumption and ensuring high efficiency, this paper proposes an intrusion detection model based on game theory and an autoregressive model. The paper not only improves the autoregressive theory model into a non-cooperative, complete-information, static game model, but also predicts attack pattern reliably. The proposed approach improves on previous approaches in two main ways: (1) it takes energy consumption of the intrusion detection process into account, and (2) it obtains the optimal defense strategy that balances the system's detection efficiency and energy consumption by analyzing the model's mixed Nash equilibrium solution. In the simulation experiment, the running time of the process is regarded as the main indicator of energy consumption of the system. The simulation results show that our proposed IDS not only effectively predicts the attack time and the next targeted cluster based on the game theory, but also reduces energy consumption.

Hassan, W, Lu, DD & Xiao, W 2019, 'Analysis and experimental verification of a single‐switch high‐voltage gain ZCS DC–DC converter', IET Power Electronics, vol. 12, no. 8, pp. 2146-2153.
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Hayat, T, Afzal, MU, Lalbakhsh, A & Esselle, KP 2019, '3-D-Printed Phase-Rectifying Transparent Superstrate for Resonant-Cavity Antenna', IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 7, pp. 1400-1404.
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© 2019 IEEE. A three-dimensional (3-D)-printed nonplanar highly transmitting superstrate is presented to improve the directive radiation characteristics of a resonant-cavity antenna (RCA). Classical RCAs are reported with nonuniform aperture-field distribution that compromises their far-field directivity. The concept of near-field phase correction has been used here to design a phase-rectifying transparent superstrate (PRTS), which was fabricated using the 3-D printing technology. The PRTS is printed using easily accessible polylactic acid filament. It has a significantly lower cost and weight compared to its recently published counterparts, while its performance is comparable. The 3-D printing technology yielded the prototype in less than 4 h, which is considerably less compared to the traditional machining methods. Measurements of the prototype indicated close correspondence between the predicted and the measured results. Significant increase in the antenna performance has been achieved, due to the rectification of the aperture phase distribution. Notable aspects encompass 7.3 dB increase in the antenna peak directivity (from 13-20.3 dBi), significant sidelobe level suppression, and an improvement of aperture efficiency by 36.1%, with a PRTS that costs less than 2.5 USD.

Hayat, T, Afzal, MU, Lalbakhsh, A & Esselle, KP 2019, 'Additively Manufactured Perforated Superstrate to Improve Directive Radiation Characteristics of Electromagnetic Source', IEEE Access, vol. 7, pp. 153445-153452.
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© 2013 IEEE. Additively manufactured perforated superstrate (AMPS) is presented to realize directive radio frequency (RF) front-end antennas. The superstrate comprises spatially distributed dielectric unit-cell elements with square perforations, which creates a pre-defined transmission phase delay pattern in the propagating electric field. The proposed square perforation has superior transmission phase characteristics compared to traditionally machined circular perforations and full-wave simulations based parametric analysis has been performed to highlight this supremacy. The AMPS is used with a classical electromagnetic-bandgap resonator antenna (ERA) to improve its directive radiation characteristics. A prototype is developed using the most common, low-cost and easily accessible Acrylonitrile Butadiene Styrene (ABS) filament. The prototype was rapidly fabricated in less than five hours and weighs 139.3 g., which corresponds to the material cost of only 2.1 USD. The AMPS has remarkably improved the radiation performance of ERA by increasing its far-field directivity from 12.67 dB to 21.12 dB and reducing side-lobe level from-7.3 dB to-17.2 dB.

He, L, Lu, Z, Pan, L, Zhao, H, Li, X & Zhang, J 2019, 'Optimal Economic and Emission Dispatch of a Microgrid with a Combined Heat and Power System', Energies, vol. 12, no. 4, pp. 604-604.
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With the rapid development of the new concept of energy internet, electric power systems often need to be investigated together with thermal energy systems. Additionally, to reduce pollution from gas emissions, it is very important to study the economic and emission dispatch of integrated electrical and heating systems. Hence, this paper proposes a multi-objective optimization dispatch model for a microgrid (MG) with a combined heat and power (CHP) system. This CHP-based MG system consists of a CHP unit, a wind turbine, a PV system, a fuel cell, an electric boiler, an electric storage, and a heat storage. It can exchange electricity with the distribution network and exchange heat with the district heating network. Minimum economic cost and minimum environmental cost are considered as the two objectives for the operation of this CHP-based MG system. To solve the two objective optimization problem, the multi-objective bacterial colony chemotaxis algorithm is utilized to obtain the Pareto optimal solution set, and the optimal solution is chosen by the Technique for Order of Preference by Similarity to Ideal Solution method. Finally, numerical case studies demonstrate the effectiveness of proposed model and method for the optimal economic and emission dispatch of the CHP-based MG system.

He, T, Wu, M, Lu, DD-C, Aguilera, RP, Zhang, J & Zhu, J 2019, 'Designed Dynamic Reference With Model Predictive Control for Bidirectional EV Chargers', IEEE Access, vol. 7, pp. 129362-129375.
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© 2013 IEEE. This paper presents a finite control set model predictive control (MPC) using a designed dynamic reference for bidirectional electric vehicle (EV) chargers. In the conventional MPC scheme, a PI controller is involved to generate an active power reference from the DC voltage reference. It is hard to find one fixed set of coefficients for all working conditions. In this paper, a designed dynamic reference based MPC strategy is proposed to replace the PI control loop. In the proposed method, a DC voltage dynamic reference is developed to formulate the inherent relationship between the DC voltage reference and the active power reference. Multi-objective control can be achieved in the proposed scheme, including controlling of the DC voltage, battery charging/discharging current, active power and reactive power, independently. Bidirectional power flow is operated effectively between the EV- and the grid-side. Experimental results are obtained from a laboratory three-phase two-stage bidirectional EV charger controlled by dSPACE DS1104. The results show that fast dynamic and good steady state performance of tracking the above objectives can be achieved with the proposed method. Compared with the system performance obtained by the conventional MPC method, the proposed method generates less active power ripples and produces a better grid current performance.

He, T, Zhu, J, Lu, DD-C & Zheng, L 2019, 'Modified Model Predictive Control for Bidirectional Four-Quadrant EV Chargers With Extended Set of Voltage Vectors', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 274-281.
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© 2013 IEEE. This paper presents a modified model predictive control (MMPC) for bidirectional power flow control between the electric vehicle (EV) chargers and the main grid. In contrast to the conventional finite control set MPC which selects an optimal switching state from eight possible voltage vectors, the proposed MMPC is based on the application of an optimal voltage vector chosen from an extended set of 20 modulated voltage vectors with a fixed duty ratio. To reduce the computational burden introduced by the increased number of voltage sets, a preselection algorithm is developed for the MMPC method. Six voltage vectors are preselected from the 20 sectors. Due to the increased number of the voltage space vectors, the grid currents and active and reactive power performance can be improved by using the proposed MMPC scheme. Both the conventional and proposed methods are compared through experimental test results of a two-level three-phase off-board EV charger.

He, W, Sun, C, Wunsch, DC & Xu, RYD 2019, 'Guest Editorial Special Issue on Intelligent Control Through Neural Learning and Optimization for Human–Machine Hybrid Systems', IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3530-3533.
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Hesamian, MH, Jia, W, He, X & Kennedy, P 2019, 'Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges', Journal of Digital Imaging, vol. 32, no. 4, pp. 582-596.
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© 2019, The Author(s). Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.

Hoang, DT, Nguyen, DN, Alsheikh, MA, Gong, S, Dutkiewicz, E, Niyato, D & Han, Z 2019, ''Borrowing Arrows with Thatched Boats': The Art of Defeating Reactive Jammers in IoT Networks', IEEE Wireless Communications Magazine, vol. 27, no. 3, pp. 79-87.
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In this article, we introduce a novel deception strategy which is inspired bythe 'Borrowing Arrows with Thatched Boats', one of the most famous militarytactics in the history, in order to defeat reactive jamming attacks forlow-power IoT networks. Our proposed strategy allows resource-constrained IoTdevices to be able to defeat powerful reactive jammers by leveraging their ownjamming signals. More specifically, by stimulating the jammer to attack thechannel through transmitting fake transmissions, the IoT system can not onlyundermine the jammer's power, but also harvest energy or utilize jammingsignals as a communication means to transmit data through using RF energyharvesting and ambient backscatter techniques, respectively. Furthermore, wedevelop a low-cost deep reinforcement learning framework that enables thehardware-constrained IoT device to quickly obtain an optimal defense policywithout requiring any information about the jammer in advance. Simulationresults reveal that our proposed framework can not only be very effective indefeating reactive jamming attacks, but also leverage jammer's power to enhancesystem performance for the IoT network.

Hossain, MA, Pota, HR, Hossain, MJ & Blaabjerg, F 2019, 'Evolution of microgrids with converter-interfaced generations: Challenges and opportunities', International Journal of Electrical Power & Energy Systems, vol. 109, pp. 160-186.
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© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

Hu, J, Li, Z, Zhu, J & Guerrero, JM 2019, 'Voltage Stabilization: A Critical Step Toward High Photovoltaic Penetration', IEEE Industrial Electronics Magazine, vol. 13, no. 2, pp. 17-30.
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© 2007-2011 IEEE. The increasing photovoltaic (PV) power sources connected to low-voltage (LV) distribution networks generate a new grid environment featuring various types of power generations near consumers and bidirectional active and reactive power flows. However, the large-scale deployment of PVs is hindered by the power quality problems, particularly voltage deviation. To overcome this obstacle, proper mitigation techniques should be developed to eliminate the negative impacts of high-PV penetration in LV networks. This article provides an in-depth review of recently developed technologies that prevent voltage deviation in LV grids with PVs. Following an investigation of the voltage fluctuation phenomena along the distribution feeder due to variable PV output and power demand, the mathematical relationship between power flow and voltage level is revealed. The solutions that mitigate the voltage variation are then investigated and classified. Their effectiveness, advantages, and disadvantages are illustrated. Finally, the current trend in grid integration of PVs and other distributed generators (DGs) under future grid framework is discussed.

Hu, S, Xu, M, Zhang, H, Xiao, C & Gui, C 2019, 'Affective Content-aware Adaptation Scheme on QoE Optimization of Adaptive Streaming over HTTP', ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 15, no. 3s, pp. 1-18.
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The article presents a novel affective content-aware adaptation scheme (ACAA) to optimize Quality of Experience (QoE) for dynamic adaptive video streaming over HTTP (DASH). Most of the existing DASH adaptation schemes conduct video bit-rate adaptation based on an estimation of available network resources, which ignore user preference on affective content (AC) embedded in video data streaming over the network. Since the personal demands to AC is very different among all viewers, to satisfy individual affective demand is critical to improve the QoE in commercial video services. However, the results of video affective analysis cannot be applied into a current adaptive streaming scheme directly. Correlating the AC distributions in user's viewing history to each being streamed segment, the affective relevancy can be inferred as an affective metric for the AC related segment. Further, we have proposed an ACAA scheme to optimize QoE for user desired affective content while taking into account both network status and affective relevancy. We have implemented the ACAA scheme over a realistic trace-based evaluation and compared its performance in terms of network performance, QoE with that of Probe and Adaptation (PANDA), buffer-based adaptation (BBA), and Model Predictive Control (MPC). Experimental results show that ACAA can preserve available buffer time for future being delivered affective content preferred by viewer's individual preference to achieve better QoE in affective contents than those normal contents while remain the overall QoE to be satisfactory.

Huang, L, Zhang, J, Zuo, Y & Wu, Q 2019, 'Pyramid-Structured Depth MAP Super-Resolution Based on Deep Dense-Residual Network', IEEE Signal Processing Letters, vol. 26, no. 12, pp. 1723-1727.
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© 1994-2012 IEEE. Although deep convolutional neural networks (DCNN) show significant improvement for single depth map (SD) super-resolution (SR) over the traditional counterparts, most SDSR DCNNs do not reuse the hierarchical features for depth map SR resulting in blurred high-resolution (HR) depth maps. They always stack convolutional layers to make network deeper and wider. In addition, most SDSR networks generate HR depth maps at a single level, which is not suitable for large up-sampling factors. To solve these problems, we present pyramid-structured depth map super-resolution based on deep dense-residual network. Specially, our networks are made up of dense residual blocks that use densely connected layers and residual learning to model the mapping between high-frequency residuals and low-resolution (LR) depth map. Furthermore, based on the pyramid structure, our network can progressively generate depth maps of various levels by taking advantages of features from different levels. The proposed network adopts a deep supervision scheme to reduce the difficulty of model training and further improve the performance. The proposed method is evaluated on Middlebury datasets which shows improved performance compared with 6 state-of-the-art methods.

Huang, L, Zhe, T, Wu, J, Wu, Q, Pei, C & Chen, D 2019, 'Robust Inter-Vehicle Distance Estimation Method Based on Monocular Vision', IEEE Access, vol. 7, pp. 46059-46070.
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© 2013 IEEE. Advanced driver assistance systems (ADAS) based on monocular vision are rapidly becoming a popular research subject. In ADAS, inter-vehicle distance estimation from an in-car camera based on monocular vision is critical. At present, related methods based on a monocular vision for measuring the absolute distance of vehicles ahead experience accuracy problems in terms of the ranging result, which is low, and the deviation of the ranging result between different types of vehicles, which is large and easily affected by a change in the attitude angle. To improve the robustness of a distance estimation system, an improved method for estimating the distance of a monocular vision vehicle based on the detection and segmentation of the target vehicle is proposed in this paper to address the vehicle attitude angle problem. The angle regression model (ARN) is used to obtain the attitude angle information of the target vehicle. The dimension estimation network determines the actual dimensions of the target vehicle. Then, a 2D base vector geometric model is designed in accordance with the image analytic geometric principle to accurately recover the back area of the target vehicle. Lastly, area-distance modeling based on the principle of camera projection is performed to estimate distance. The experimental results on the real-world computer vision benchmark, KITTI, indicate that our approach achieves superior performance compared with other existing published methods for different types of vehicles (including front and sideway vehicles).

Huang, W, Hua, W, Chen, F, Qi, J & Zhu, J 2019, 'Performance Improvement of Model Predictive Current Control of Fault-Tolerant Five-Phase Flux-Switching Permanent Magnet Motor Drive', IEEE Transactions on Industry Applications, vol. 55, no. 6, pp. 6001-6010.
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© 1972-2012 IEEE. To improve the fault-tolerant performance of a five-phase flux-switching permanent magnet (FSPM) motor drive under open-circuit fault (OCF) condition, a model predictive current control (MPCC) with pre-selective method and duty ratio control (DRC) technology is proposed and investigated in this paper. First, on the principle of minimizing harmonic voltages in x-y subspace, two zero switching states and the switching state, which generates a larger voltage vector in α-β subspace are pre-selected. Second, voltage vector references in α-β subspace and x-y subspace are predicted to further select active voltage vector candidates. Consequently, the number of current predictions has been significantly reduced, resulting in the alleviation of the computational complexity and the increase of sampling frequency. Third, the DRC approach is applied in conjunction with the pre-selection-based MPCC to improve the steady-state performance. Finally, the effectiveness of the proposed MPCC method for the OCF tolerant five-phase FSPM motor drive is validated by comparative experiments.

Huang, X, An, P, Cao, F, Liu, D & Wu, Q 2019, 'Light-field compression using a pair of steps and depth estimation', Optics Express, vol. 27, no. 3, pp. 3557-3557.
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© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. Advanced handheld plenoptic cameras are being rapidly developed to capture information about light fields (LFs) from the 3D world. Rich LF data can be used to develop dense sub-aperture images (SAIs) that can provide a more immersive experience for users. Unlike conventional 2D images, 4D SAIs contain both the positional and directional information of light rays; the practical applications of handheld plenoptic cameras are limited by the huge volume of data required to capture this information. Therefore, an efficient LF compression method is vital for further application of the cameras. To this end, the pair of steps and depth estimation (PoS&DE) method is proposed in this paper, and the multiview video and depth (MVD) coding structure is used to relieve the LF coding burden. More specifically, a precise depth-estimation approach is presented for SAIs based on the cost function, and an SAI-guided depth optimization algorithm is designed to refine the initial depth map based on pixel variation tendency. Meanwhile, to reduce running time, intermediate SAI synthesis quality and coding bitrates, including the key SAIs selected and cost-computation steps, are set via extensive statistical experiments. In this way, only a limited number of optimally selected SAIs and their corresponding depth maps must be encoded. The experimental results demonstrate that our proposed LF compression solution using PoS&DE can obtain a satisfied coding performance.

Huang, X, Zhang, JA, Liu, RP, Guo, YJ & Hanzo, L 2019, 'Airplane-Aided Integrated Networking for 6G Wireless: Will It Work?', IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 84-91.
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© 2019 IEEE. As demand for wireless connectivity increases, communication technology is moving toward integrating terrestrial networks with space networks. Creating this integrated space and terrestrial network (ISTN) is critically important for industries such as logistics, mining, agriculture, fisheries, and defense. However, a number of significant technological challenges must be overcome for ISTN through low-cost airborne platforms and high-data-rate backbone links.

Huang, Y, Xu, J, Wu, Q, Zheng, Z, Zhang, Z & Zhang, J 2019, 'Multi-Pseudo Regularized Label for Generated Data in Person Re-Identification', IEEE Transactions on Image Processing, vol. 28, no. 3, pp. 1391-1403.
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© 1992-2012 IEEE. Sufficient training data normally is required to train deeply learned models. However, due to the expensive manual process for a labeling large number of images (i.e., annotation), the amount of available training data (i.e., real data) is always limited. To produce more data for training a deep network, generative adversarial network can be used to generate artificial sample data (i.e., generated data). However, the generated data usually does not have annotation labels. To solve this problem, in this paper, we propose a virtual label called Multi-pseudo Regularized Label (MpRL) and assign it to the generated data. With MpRL, the generated data will be used as the supplementary of real training data to train a deep neural network in a semi-supervised learning fashion. To build the corresponding relationship between the real data and generated data, MpRL assigns each generated data a proper virtual label which reflects the likelihood of the affiliation of the generated data to pre-defined training classes in the real data domain. Unlike the traditional label which usually is a single integral number, the virtual label proposed in this paper is a set of weight-based values each individual of which is a number in (0,1] called multi-pseudo label and reflects the degree of relation between each generated data to every pre-defined class of real data. A comprehensive evaluation is carried out by adopting two state-of-the-art convolutional neural networks (CNNs) in our experiments to verify the effectiveness of MpRL. Experiments demonstrate that by assigning MpRL to generated data, we can further improve the person re-ID performance on five re-ID datasets, i.e., Market-1501, DukeMTMC-reID, CUHK03, VIPeR, and CUHK01. The proposed method obtains +6.29%, +6.30%, +5.58%, +5.84%, and +3.48% improvements in rank-1 accuracy over a strong CNN baseline on the five datasets, respectively, and outperforms state-of-the-art methods.

Huang, Y, Zhong, Y, Wu, Q, Dutkiewicz, E & Jiang, T 2019, 'Cost-Effective Foliage Penetration Human Detection Under Severe Weather Conditions Based on Auto-Encoder/Decoder Neural Network', IEEE Internet of Things Journal, vol. 6, no. 4, pp. 6190-6200.
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© 2014 IEEE. Military surveillance events and rescue activities are vital missions for the Internet-of-Things. To this end, foliage penetration for human detection plays an important role. However, although the feasibility of that mission has been validated, we observe that it still cannot perform promisingly under severe weather conditions, such as rainy, foggy, and snowy days. Therefore, in this paper, experiments are conducted under severe weather conditions based on a proposed deep learning approach. We present an auto-encoder/decoder (Auto-ED) deep neural network that can learn the deep representation and conduct classification task concurrently. Since the property of cost-effective, the device-free sensing techniques are used to address human detection in our case. As we pursue the signal-based mission, two components are involved in the proposed Auto-ED approach. First, an encoder is utilized that encode signal-based inputs into higher dimensional tensors by fractionally strided convolution operations. Then, a decoder is leveraged with convolution operations to extract deep representations and learn the classifier simultaneously. To verify the effectiveness of the proposed approach, we compare it with several machine learning approaches under different weather conditions. Also, a simulation experiment is conducted by adding additive white Gaussian noise to the original target signals with different signal to noise ratios. Experimental results demonstrate that the proposed approach can best tackle the challenge of human detection under severe weather conditions in the high-clutter foliage environment, which indicates its potential application values in the near future.

Huo, S, Liu, M, Wu, L, Liu, M, Xu, M, Ni, W & Yan, Y-M 2019, 'Synthesis of ultrathin and hierarchically porous carbon nanosheets based on interlayer-confined inorganic/organic coordination for high performance supercapacitors', Journal of Power Sources, vol. 414, pp. 383-392.
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Huynh, NV, Hoang, DT, Nguyen, DN & Dutkiewicz, E 2019, 'Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks', IEEE Journal on Selected Areas in Communications, vol. 37, no. 6, pp. 1-1.
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Effective network slicing requires an infrastructure/network provider to dealwith the uncertain demand and real-time dynamics of network resource requests.Another challenge is the combinatorial optimization of numerous resources,e.g., radio, computing, and storage. This article develops an optimal and fastreal-time resource slicing framework that maximizes the long-term return of thenetwork provider while taking into account the uncertainty of resource demandfrom tenants. Specifically, we first propose a novel system model which enablesthe network provider to effectively slice various types of resources todifferent classes of users under separate virtual slices. We then capture thereal-time arrival of slice requests by a semi-Markov decision process. Toobtain the optimal resource allocation policy under the dynamics of slicingrequests, e.g., uncertain service time and resource demands, a Q-learningalgorithm is often adopted in the literature. However, such an algorithm isnotorious for its slow convergence, especially for problems with largestate/action spaces. This makes Q-learning practically inapplicable to our casein which multiple resources are simultaneously optimized. To tackle it, wepropose a novel network slicing approach with an advanced deep learningarchitecture, called deep dueling that attains the optimal average reward muchfaster than the conventional Q-learning algorithm. This property is especiallydesirable to cope with real-time resource requests and the dynamic demands ofusers. Extensive simulations show that the proposed framework yields up to 40%higher long-term average return while being few thousand times faster, comparedwith state of the art network slicing approaches.

Huynh, NV, Nguyen, DN, Hoang, DT & Dutkiewicz, E 2019, ''Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications', IEEE Journal on Selected Areas in Communications, vol. 37, no. 11, pp. 2603-2620.
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With conventional anti-jamming solutions like frequency hopping or spreadspectrum, legitimate transceivers often tend to 'escape' or 'hide' themselvesfrom jammers. These reactive anti-jamming approaches are constrained by thelack of timely knowledge of jamming attacks. Bringing together the latestadvances in neural network architectures and ambient backscatteringcommunications, this work allows wireless nodes to effectively 'face' thejammer by first learning its jamming strategy, then adapting the rate ortransmitting information right on the jamming signal. Specifically, to dealwith unknown jamming attacks, existing work often relies on reinforcementlearning algorithms, e.g., Q-learning. However, the Q-learning algorithm isnotorious for its slow convergence to the optimal policy, especially when thesystem state and action spaces are large. This makes the Q-learning algorithmpragmatically inapplicable. To overcome this problem, we design a novel deepreinforcement learning algorithm using the recent dueling neural networkarchitecture. Our proposed algorithm allows the transmitter to effectivelylearn about the jammer and attain the optimal countermeasures thousand timesfaster than that of the conventional Q-learning algorithm. Through extensivesimulation results, we show that our design (using ambient backscattering andthe deep dueling neural network architecture) can improve the averagethroughput by up to 426% and reduce the packet loss by 24%. By augmenting theambient backscattering capability on devices and using our algorithm, it isinteresting to observe that the (successful) transmission rate increases withthe jamming power. Our proposed solution can find its applications in bothcivil (e.g., ultra-reliable and low-latency communications or URLLC) andmilitary scenarios (to combat both inadvertent and deliberate jamming).

Iacopi, F & McIntosh, M 2019, 'Opportunities and perspectives for green chemistry in semiconductor technologies', Green Chemistry, vol. 21, no. 12, pp. 3250-3255.
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Semiconductor technologies offer a plethora of technological challenges and opportunities for a more extensive implementation of green chemistry principles.

Irfansyah, AN, Lehmann, T, Jenkins, J, Tong, T & Hamilton, TJ 2019, 'A resistive DAC for a multi-stage sigma-delta modulator DAC with dynamic element matching', Analog Integrated Circuits and Signal Processing, vol. 98, no. 1, pp. 109-123.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. This paper presents a study and implementation of a shunt–shunt resistive voltage divider digital-to-analog converter (DAC) for use as a multibit DAC in a multi-stage noise shaping sigma-delta modulator DAC design with dynamic element matching. This resistive DAC structure is employed to address the problem of code-dependent finite output impedance and thus aims to improve systematic linearity, while still being suitable for scaled CMOS processes. Chip measurement results from an implementation in CMOS 180 nm technology are presented. At low sampling clock frequencies, an SFDR of 71.81 dB is achieved, while at a higher sampling clock frequency of 600 MHz the SFDR is measured to be 59.73 dB, all for an OSR of 32. Our results show that low systematic nonlinearity can be achieved with this resistive DAC at low sampling frequencies, and we discuss potential enhancements to our prototype to obtain better SFDR at higher sampling rate.

Islam, M, Mithulananthan, N, Hossain, J & Shah, R 2019, 'Dynamic voltage stability of unbalanced distribution system with high penetration of single‐phase PV units', The Journal of Engineering, vol. 2019, no. 17, pp. 4074-4080.
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Islam, M, Nadarajah, M & Hossain, MJ 2019, 'Short-Term Voltage Stability Enhancement in Residential Grid With High Penetration of Rooftop PV Units', IEEE Transactions on Sustainable Energy, vol. 10, no. 4, pp. 2211-2222.
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© 2010-2012 IEEE. Short-term voltage instability (STVI) imposes a severe threat to modern distribution networks (DNs) where a large number of intermittent distributed generator (DG) units, like rooftop photovoltaic (PV), is being integrated. Consequently, most of the international standards have been revised by incorporating the requirement of the dynamic voltage support (DVS) through DG units, which is a promising approach to alleviate the STVI. In this paper, a novel DVS strategy is proposed to improve the short-term voltage stability (STVS) in residential grids. In comparison with other DVS strategies, the proposed DVS scheme maximizes the active power support from PV units following a contingency utilizing the maximum allowable current of the PV inverters. Moreover, the inverter design margin is taken into account in designing the proposed scheme to limit the injected grid current within the maximum allowable inverter current. The impact of the inverter design margin on the STVS is explained, and the effectiveness of the proposed strategy compared with the conventional DVS is demonstrated. The feasibility of the DVS control strategies in practical application is studied. Several case studies are carried out on benchmark IEEE 4 bus and IEEE 13 node test feeder systems, and finally, on a ring-type DN. The results show that the proposed DVS scheme is feasible, and achieved superior performance compared to the other strategies. Furthermore, it has been shown that implementation of the proposed DVS scheme can avoid the installation of an expensive 1200-kVA D-STATCOM for STVS improvement in the target system.

Islam, MR, Lu, H, Hossain, MJ & Li, L 2019, 'Mitigating unbalance using distributed network reconfiguration techniques in distributed power generation grids with services for electric vehicles: A review', Journal of Cleaner Production, vol. 239, pp. 117932-117932.
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© 2019 Elsevier Ltd With rapid movement to combat climate change by reducing greenhouse gases, there is an increasing trend to use more electric vehicles (EVs) and renewable energy sources (RES). With more EVs integration into electricity grid, this raises many challenges for the distribution service operators (DSOs) to integrate such RES-based, distributed generation (DG) and EV-like distributed loads into distribution grids. Effective management of distribution network imbalance is one of the challenges. The distribution network reconfiguration (DNR) techniques are promising to address the issue of imbalance along with other techniques such as the optimal distributed generation placement and allocation (OPDGA) method. This paper presents a systematic and thorough review of DNR techniques for mitigating unbalance of distribution networks, based on papers published in peer-reviewed journals in the last three decades. It puts more focus on how the DNR techniques have been used to manage network imbalance due to distributed loads and DG units. To the best of our knowledge, this is the first attempt to review the research works in the field using DNR techniques to mitigate unbalanced distribution networks. Therefore, this paper will serve as a prime source of the guidance for mitigating network imbalance using the DNR techniques to the new researchers in this field.

Jafari, M, Malekjamshidi, Z, Lu, DD-C & Zhu, J 2019, 'Development of a Fuzzy-Logic-Based Energy Management System for a Multiport Multioperation Mode Residential Smart Microgrid', IEEE Transactions on Power Electronics, vol. 34, no. 4, pp. 3283-3301.
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IEEE In this paper a grid-tied residential smart micro-grid topology is proposed which integrates energies of a PV, a fuel cell and a battery bank to supply the local loads through a combination of electric and magnetic buses. In contrast to multiple-converter based micro-grids with a common electric bus, using a multi-port converter with a common magnetic bus can effectively reduce the number of voltage conversion stages, size and cost of the micro-grid and isolates the conversion ports. The resultant topology utilizes a centralized system level control which leads to the faster and more flexible energy management. The proposed micro-grid is able to operate in multiple grid-connected and off-grid operation modes. A fuzzy controlled energy management unit is designed to select the appropriate operation mode considering both real-time and long-term-predicted data of the system. A mode transition process is designed to smooth the mode variation by using a state transition diagram and bridging modes. To improve the micro-grid operation performance, appropriate control techniques such as synchronized bus-voltage balance are used. A prototype of the proposed micro-grid is developed and experimentally tested for three different energy management scenarios. Energy distribution and energy cost analysis are performed to validate the proposed control method.

Jamborsalamati, P, Fernandez, E, Moghimi, M, Hossain, MJ, Heidari, A & Lu, J 2019, 'MQTT-Based Resource Allocation of Smart Buildings for Grid Demand Reduction Considering Unreliable Communication Links', IEEE Systems Journal, vol. 13, no. 3, pp. 3304-3315.
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© 2018 IEEE. This paper proposes an autonomous resource allocation system (RAS) for smart neighborhood areas in presence of distributed energy resources and storage systems, with the purpose of grid demand reduction (GDR). Different from the past research on RAS, most of which are not broken down into resource allocation of individual appliances, do not address practical implementation of RAS with communication systems, and do not consider realistic case scenarios with network latency and communication link failure, this paper presents an improved appliance-level RAS developed in four operational modes with a designed bidding mechanism to exchange energy among neighborhood members through a common storage facility, a hierarchical cloud-based two-layered communication architecture founded on message queuing telemetry transport protocol to implement local and global messaging required for the proposed RAS, and realistic case scenarios by considering data from a real-world residential area and utilizing a virtual wide area network emulator to emulate characteristics of a real network in order to investigate the effects of network latency or communication link failure on the implemented RAS. From the results of diverse scenarios, it could be observed that the proposed system performs effectively to achieve GDR, even if the communication system fails partially in the smart community under test.

Ji, L-Y, Qin, P-Y, Li, J-Y & Zhang, L-X 2019, '1-D Electronic Beam-Steering Partially Reflective Surface Antenna', IEEE Access, vol. 7, pp. 115959-115965.
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A 1-D electronic beam-steering partially reflective surface (PRS) antenna using a new reconfigurable PRS unit cell is proposed in this paper. The proposed work addresses the challenge to achieve a large beam steering angle with small gain variation and a small number of active/lumped elements by using a reconfigurable PRS superstrate only. The PRS unit cell consists of two back-to-back T-shaped strips with one PIN diode inserted between them and a pair of trapezoid patches (a rectangular patch and a pair of triangle parasitic patches). Beam steering is achieved by controlling the different states of PIN diodes. Thanks to the trapezoid patches, the proposed unit cell can generate a larger phase difference between different states, thereby leading to a larger beam steering angle. Furthermore, due to the addition of more degrees of freedom in the proposed unit cell, the phase difference can be easily manipulated. Moreover, since the T-shaped strips in each unit cell is connected with adjacent ones, the biasing network is very simple without needing a large number of lumped elements and dc biasing lines. The beam steering property is analyzed by using phased array theory. An antenna prototype with a main beam direction towards 0°, -18° and 18° operating at 5.5 GHz in the H-plane is fabricated and measured. Good agreement between the predicted simulation and measurement results for the input reflection coefficients and radiation patterns is achieved, which validates the feasibility of the design. The measured realized gains are over 11 dBi for all states with a 0.8 dBi gain variation.

Jiang, S, Li, K & Da Xu, RY 2019, 'Relative Pairwise Relationship Constrained Non-Negative Matrix Factorisation', IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 8, pp. 1595-1609.
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IEEE Non-negative Matrix Factorisation (NMF) has been extensively used in machine learning and data analytics applications. Most existing variations of NMF only consider how each row/column vector of factorised matrices should be shaped, and ignore the relationship among pairwise rows or columns. In many cases, such pairwise relationship enables better factorisation, for example, image clustering and recommender systems. In this paper, we propose an algorithm named, Relative Pairwise Relationship constrained Non-negative Matrix Factorisation (RPR-NMF), which places constraints over relative pairwise distances amongst features by imposing penalties in a triplet form. Two distance measures, squared Euclidean distance and Symmetric divergence, are used, and exponential and hinge loss penalties are adopted for the two measures respectively. It is well known that the so-called "multiplicative update rules" result in a much faster convergence than gradient descend for matrix factorisation. However, applying such update rules to RPR-NMF and also proving its convergence is not straightforward. Thus, we use reasonable approximations to relax the complexity brought by the penalties, which are practically verified. Experiments on both synthetic datasets and real datasets demonstrate that our algorithms have advantages on gaining close approximation, satisfying a high proportion of expected constraints, and achieving superior performance compared with other algorithms.

Jiao, S & Liu, RP 2019, 'A survey on physical authentication methods for smart objects in IoT ecosystem', Internet of Things, vol. 6, pp. 100043-100043.
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Johnson, B, Chang, L, Afridi, K, Ali, MH, von Appen, J, Chen, Y-M, Davoudi, A, Dhople, S, Enslin, JH, Flicker, J, Islam, MR, Koutroulis, E, Kim, KA, Li, Y, Liserre, M, Long, T, Lu, X, Mattavelli, P, Rodriguez, P, Ruan, X, Suntio, T, Wang, H, Xu, D, Xu, W, Yazdani, A, Zeineldin, H & Zhu, J 2019, 'Guest Editorial Joint Special Section on Power Conversion & Control in Photovoltaic Power Plants', IEEE Transactions on Energy Conversion, vol. 34, no. 1, pp. 159-160.
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Ju, M, Ding, C, Guo, YJ & Zhang, D 2019, 'Remote Sensing Image Haze Removal Using Gamma-Correction-Based Dehazing Model', IEEE Access, vol. 7, pp. 5250-5261.
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© 2013 IEEE. Haze is evident in most remote sensing (RS) images, particularly for the RS scenes captured in inclement weather, which severely hinders image interpretation. In this paper, two simple yet effective visibility restoration formulas are proposed for RGB-channel RS (RRS) images and multi-spectral RS (MSRS) images, respectively. More specifically, a robust gamma-correction-based dehazing model (RGDM) is first defined, which can better address the non-uniform illumination problem in hazy images. Then, the scene albedo restoration formula (SARF) used for the RRS images is obtained by imposing the existing prior knowledge on this RGDM, which enables us to simultaneously eliminate the interferences of haze and non-uniform illumination. In subsequence, according to Rayleigh's law, an expanded restoration formula (E-SARF) is further developed for MSRS data. Using the proposed E-SARF, the spatially varying haze in each band can be thoroughly removed without using any extra information. The experiments are conducted on the challenging RRS and MSRS images, including images with non-uniform illumination, non-uniform haze distribution, and heavy haze. The results reveal that the SARF and the E-SARF are superior to most other state-of-the-art techniques in terms of both the recover quality and the implementation efficiency.

Ju, M, Ding, C, Zhang, D & Guo, YJ 2019, 'BDPK: Bayesian Dehazing Using Prior Knowledge', IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 8, pp. 2349-2362.
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IEEE Atmospheric scattering model (ASM) has been widely used in hazy image restoration. However, the recovered albedo might deviate from the real scene once the input hazy image cannot fully satisfy the model’s assumptions such as the homogeneous atmosphere and even illumination. In this paper, we break these limitations and redefine a more reliable atmospheric scattering model (RASM) that is extremely adaptable for various practical scenarios. Benefiting from RASM, a simple yet effective Bayesian dehazing algorithm (BDPK) is further proposed based on the prior knowledge. Our strategy is to convert the single image dehazing problem into a maximum a-posteriori probability (MAP) one that can be approximated as an optimization function using the existing priori constraints. To efficiently solve this optimization function, the alternating minimizing technique (AMT) is introduced, which enables us to directly restore the scene albedo. Experiments on a number of challenging images reveal the power of BDPK on removing haze and verify its superiority over several state-of-the-art techniques in terms of quality and efficiency.

Kamal, MS, Sarowar, MG, Dey, N, Ashour, AS, Ripon, SH, Panigrahi, BK & Tavares, JMRS 2019, 'Self-organizing mapping based swarm intelligence for secondary and tertiary proteins classification', International Journal of Machine Learning and Cybernetics, vol. 10, no. 2, pp. 229-252.
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Karmokar, DK, Chen, S-L, Bird, TS & Guo, YJ 2019, 'Single-Layer Multi-Via Loaded CRLH Leaky-Wave Antennas for Wide-Angle Beam Scanning With Consistent Gain', IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 2, pp. 313-317.
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© 2018 IEEE. Achieving continuous backward-to-forward wide-angle beam scanning with consistent gain by employing composite right/left-handed (CRLH) leaky-wave antennas (LWAs) is reported. For structural and design simplicity, a single-layer one-dimensional structure is considered in which each unit cell consists of a patch shorted centrally to the ground plane. It was found that, when using only one via at the center of a unit cell, a continuous beam scan requires a large-diameter via when all other parameters remain unchanged. To eliminate this limitation while maintaining a single-layer structure, novel unit cells are proposed using multiple vias in each unit cell. An LWA design for continuous beam scan with three vias in each unit cell is investigated, and the results show good performance and design flexibility. A prototype antenna has been realized, and the measured results show that the antenna can scan the radiation beam continuously in a wide range, from -60° to +66° with a consistent gain. The measured gain variation within the scan range is only 2.9 dB, and the 3 dB gain bandwidth is 58.6%.

KASAUKA, D, SUGIYAMA, K, TSUTSUI, H, OKUHATA, H & MIYANAGA, Y 2019, 'An Architecture for Real-Time Retinex-Based Image Enhancement and Haze Removal and Its FPGA Implementation', IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E102.A, no. 6, pp. 775-782.
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Kavehei, O, Hamilton, TJ, Truong, ND & Nikpour, A 2019, 'Opportunities for Electroceuticals in Epilepsy', Trends in Pharmacological Sciences, vol. 40, no. 10, pp. 735-746.
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© 2019 Elsevier Ltd Epilepsy is a neurological disorder that affects ∼1% of the world population. Nearly 30% of epilepsy patients suffer from pharmacoresistant epilepsy that cannot be treated with antiepileptic drugs. Depending on seizure type, a diverse range of therapies are available, including surgery, vagus nerve stimulation, and deep brain stimulation. We review the sensing and stimulation technologies most used in neurological disorders, and provide a vision of minimally invasive electroceuticals to enable accurate forecasting of epileptic seizures and therapy. The use of such systems could potentially help patients to prevent injuries and, in combination with an intervention mechanism, could provide a method of suppressing seizures in epileptic patients.

Keshavarz, S, Abdipour, A, Mohammadi, A & Keshavarz, R 2019, 'Design and implementation of low loss and compact microstrip triplexer using CSRR loaded coupled lines', AEU - International Journal of Electronics and Communications, vol. 111, pp. 152913-152913.
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Khan, AA, Abolhasan, M, Ni, W, Lipman, J & Jamalipour, A 2019, 'A Hybrid-Fuzzy Logic Guided Genetic Algorithm (H-FLGA) Approach for Resource Optimization in 5G VANETs', IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6964-6974.
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© 2019 IEEE. To support diversified quality of service demands and dynamic resource requirements of users in 5G driven VANETs, network resources need flexible and scalable resource allocation strategies. Current heterogeneous vehicular networks are designed and deployed with a connection-centric mindset with fixed resource allocation to a cell regardless of traffic conditions, static coverage, and capacity. In this paper, we propose a hybrid-fuzzy logic guided genetic algorithm (H-FLGA) approach for the software defined networking controller, to solve a multi-objective resource optimization problem for 5G driven VANETs. Realizing the service oriented view, the proposed approach formulates five different scenarios of network resource optimization in 5G VANETs. Furthermore, the proposed fuzzy inference system is used to optimize weights of multi-objectives, depending on the type of service requirements of customers. The proposed approach shows the minimized value of multi-objective cost function when compared with the GA. The simulation results show the minimized value of end-to-end delay as compared to other schemes. The proposed approach will help the network service providers to implement a customer-centric network infrastructure, depending on dynamic customer needs of users.

Khan, SA, Guo, Y & Zhu, J 2019, 'Model Predictive Observer Based Control for Single-Phase Asymmetrical T-Type AC/DC Power Converter', IEEE Transactions on Industry Applications, vol. 55, no. 2, pp. 2033-2044.
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© 1972-2012 IEEE. This paper presents a robust control strategy for the control of single-phase five-level asymmetrical T-type ac/dc power converter. A cascaded control scheme consisting of a finite control set model predictive control (FCS-MPC) with an extended state observer (ESO) is proposed to govern the converter. In this scheme, a proportional integral (PI) controller combined with an ESO-based disturbance observer is employed as an external control loop. This control loop dynamically modifies the active power reference to realize the desired operating point of the system state (converter output voltage). The proposed control system presents a high degree of disturbance rejection capability and robustness against the external disturbances to the converter, whereas the conventional PI control performance suffers in the presence of these disturbances. In this paper, the inner current tracking loop is accomplished by an FCS-MPC algorithm. This algorithm is derived to force the input currents to track the reference values while realizing a user-defined reactive power and maintaining balanced voltages in the series-connected capacitors. Theoretical analysis and the design procedure of the proposed control system are presented. Finally, experimental studies are conducted to verify the effectiveness of the proposed control scheme.

Khan, SA, Islam, MR, Guo, Y & Zhu, J 2019, 'A New Isolated Multi-Port Converter With Multi-Directional Power Flow Capabilities for Smart Electric Vehicle Charging Stations', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-4.
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© 2018 IEEE. If the batteries are charged by clean renewable energy sources, electric vehicles (EVs) can have zero gas emission, contributing greatly toward the preservation of the green environment. In a smart micro-grid, EVs together with other distributed energy storage units can be used to supply electricity to the loads during the peak hours so as to minimize the effects of the load shedding and improve the quality of electricity. To achieve these goals, an isolated hybrid multi-port converter is required to control the power flows and balance the energy among renewable energy sources, EVs, and the grid. In this paper, a new isolated multi-port converter is proposed, which can control the power flow in multiple directions. The converter is modeled in the matlab/Simulink software environment and this validates the technology with a laboratory prototype test platform. The modeling, implementation, and results are discussed comprehensively.

Khan, SA, Islam, MR, Guo, Y & Zhu, J 2019, 'An Amorphous Alloy Magnetic-Bus-Based SiC NPC Converter With Inherent Voltage Balancing for Grid-Connected Renewable Energy Systems', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-8.
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© 2002-2011 IEEE. This paper presents an amorphous alloy magnetic-bus-based neutral point clamped (NPC) converter for grid-connected renewable generation systems. In the proposed system, the amorphous alloy high-frequency high-power density multi-winding magnetic bus generates balanced dc supplies for the five-level (5L) NPC converter for high-quality power conversion. Compared to the traditional NPC converter topologies, the proposed magnetic-bus-based architecture does not require any control circuit for voltage balancing of the series connected capacitors. The magnetic bus inherently overcomes galvanic isolation issues and may reduce the size of the boosting inductor. In this paper, a finite control set model predictive control algorithm is derived to control the grid-connected 5L-NPC inverter for multilevel voltage synthesizing, while achieving the user-defined active and reactive power values. To verify the proposed concept, a simulation model is developed and analyzed in MATLAB/Simulink environment. To validate the technology, a scale d-down prototype test platform is developed in the laboratory with silicon carbide switching devices, which achieves high blocking voltage, low power dissipation, high switching frequency, and high-Temperature operation. Based on the simulation and the experimental results, it is expected that the proposed converter will have a great potential for widespread application in renewable generation systems including superconducting generator-based wind turbines.

Khan, TA & Ling, SH 2019, 'Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications', Algorithms, vol. 12, no. 5, pp. 88-88.
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Electrical impedance tomography (EIT) has been a hot topic among researchers for the last 30 years. It is a new imaging method and has evolved over the last few decades. By injecting a small amount of current, the electrical properties of tissues are determined and measurements of the resulting voltages are taken. By using a reconstructing algorithm these voltages then transformed into a tomographic image. EIT contains no identified threats and as compared to magnetic resonance imaging (MRI) and computed tomography (CT) scans (imaging techniques), it is cheaper in cost as well. In this paper, a comprehensive review of efforts and advancements undertaken and achieved in recent work to improve this technology and the role of artificial intelligence to solve this non-linear, ill-posed problem are presented. In addition, a review of EIT clinical based applications has also been presented.

Khawwaf, J, Zheng, J, Chai, R, Lu, R & Man, Z 2019, 'Adaptive Microtracking Control for an Underwater IPMC Actuator Using New Hyperplane-Based Sliding Mode', IEEE/ASME Transactions on Mechatronics, vol. 24, no. 5, pp. 2108-2117.
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Kumar, R, Binetti, L, Nguyen, TH, Alwis, LSM, Agrawal, A, Sun, T & Grattan, KTV 2019, 'Determination of the Aspect-ratio Distribution of Gold Nanorods in a Colloidal Solution using UV-visible absorption spectroscopy', Scientific Reports, vol. 9, no. 1.
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AbstractKnowledge of the distribution of the aspect ratios (ARs) in a chemically-synthesized colloidal solution of Gold Nano Rods (GNRs) is an important measure in determining the quality of synthesis, and consequently the performance of the GNRs generated for various applications. In this work, an algorithm has been developed based on the Bellman Principle of Optimality to readily determine the AR distribution of synthesized GNRs in colloidal solutions. This is achieved by theoretically fitting the longitudinal plasmon resonance of GNRs obtained by UV-visible spectroscopy. The AR distribution obtained from the use of the algorithm developed have shown good agreement with those theoretically generated one as well as with the previously reported results. After bench-marking, the algorithm has been applied to determine the mean and standard deviation of the AR distribution of two GNRs solutions synthesized and examined in this work. The comparison with experimentally derived results from the use of expensive Transmission Electron Microscopic images and Dynamic Light Scattering technique shows that the algorithm developed offers a fast and thus potentially cost-effective solution to determine the quality of the synthesized GNRs specifically needed for many potential applications for the advanced sensor systems.

La, HM, Dinh, TH, Pham, NH, Ha, QP & Pham, AQ 2019, 'Automated robotic monitoring and inspection of steel structures and bridges', Robotica, vol. 37, no. 5, pp. 947-967.
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SummaryThis paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.

Lalbakhsh, A, Afzal, MU, Esselle, KP & Smith, SL 2019, 'Wideband Near-Field Correction of a Fabry–Perot Resonator Antenna', IEEE Transactions on Antennas and Propagation, vol. 67, no. 3, pp. 1975-1980.
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© 1963-2012 IEEE. A systematic approach to correcting electric near-field phase and magnitude over a wideband for Fabry-Perot resonator antennas (FPRAs) is presented. Unlike all other unit-cell-based near-field correction techniques for FPRAs, which merely focus on phase correction at a single frequency, this method delivers a compact near-field correcting structure (NFCS) with a wide operational bandwidth of 40%. In this novel approach, a time-average Poynting vector in conjunction with a phase gradient analysis is utilized to suggest the initial configuration of the NFCS for wideband performance. A simulation-driven optimization algorithm is then implemented to find the thickness of each correcting region, defined by the gradient analysis, to complete the NFCS design. According to the predicted and measured results, the phase and magnitude distributions of the electric near field have been greatly improved, resulting in a high aperture efficiency of 70%. The antenna under NFCS loading has a peak measured directivity of 21.6 dB, a 3 dB directivity bandwidth of 41% and a 10 dB return loss bandwidth of 46%, which covers the directivity bandwidth. The diameter of the proposed NFCS is 3.8 λ0c, which is around half that of all the other unit-cell-based phase-correcting structures, where λ0c is the free-space wavelength at the central frequency of the NFCS (13.09 GHz).

Lalbakhsh, A, Afzal, MU, Esselle, KP, Smith, SL & Zeb, BA 2019, 'Single-Dielectric Wideband Partially Reflecting Surface With Variable Reflection Components for Realization of a Compact High-Gain Resonant Cavity Antenna', IEEE Transactions on Antennas and Propagation, vol. 67, no. 3, pp. 1916-1921.
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© 1963-2012 IEEE. This communication presents a design methodology for a compact low-cost partially reflecting surface (PRS) for a wideband high-gain resonant cavity antenna (RCA) which requires only a single commercial dielectric slab. The PRS has one nonuniform double-sided printed dielectric, which exhibits a negative transverse-reflection magnitude gradient and, at the same time, a progressive reflection phase gradient over frequency. In addition, a partially shielded cavity is proposed as a method to optimize the directivity bandwidth and the peak directivity of RCAs. A prototype of the PRS was fabricated and tested with a partially shielded cavity, showing good agreement between the predicted and measured results. The measured peak directivity of the antenna is 16.2 dBi at 11.4 GHz with a 3 dB bandwidth of 22%. The measured peak gain and 3 dB gain bandwidth are 15.75 dBi and 21.5%, respectively. The PRS has a radius of 29.25 mm (1.1λ0 ) with a thickness of 1.52 mm ( 0.12λg ), and the overall height of the antenna is 0.6λ0, where λ0 and λg are the free-space and guided wavelengths at the center frequency of 11.4 GHz.

Lammie, C, Hamilton, TJ, van Schaik, A & Rahimi Azghadi, M 2019, 'Efficient FPGA Implementations of Pair and Triplet-Based STDP for Neuromorphic Architectures', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, no. 4, pp. 1558-1570.
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© 2018 IEEE. Synaptic plasticity is envisioned to bring about learning and memory in the brain. Various plasticity rules have been proposed, among which spike-timing-dependent plasticity (STDP) has gained the highest interest across various neural disciplines, including neuromorphic engineering. Here, we propose highly efficient digital implementations of pair-based STDP (PSTDP) and triplet-based STDP (TSTDP) on field programmable gate arrays that do not require dedicated floating-point multipliers and hence need minimal hardware resources. The implementations are verified by using them to replicate a set of complex experimental data, including those from pair, triplet, quadruplet, frequency-dependent pairing, as well as Bienenstock-Cooper-Munro experiments. We demonstrate that the proposed TSTDP design has a higher operating frequency that leads to 2.46 × faster weight adaptation (learning) and achieves 11.55 folds improvement in resource usage, compared to a recent implementation of a calcium-based plasticity rule capable of exhibiting similar learning performance. In addition, we show that the proposed PSTDP and TSTDP designs, respectively, consume 2.38 × and 1.78 × less resources than the most efficient PSTDP implementation in the literature. As a direct result of the efficiency and powerful synaptic capabilities of the proposed learning modules, they could be integrated into large-scale digital neuromorphic architectures to enable high-performance STDP learning.

Le, AT, Tran, LC, Huang, X & Guo, YJ 2019, 'Analog Least Mean Square Loop With I/Q Imbalance for Self-Interference Cancellation in Full-Duplex Radios', IEEE Transactions on Vehicular Technology, vol. 68, no. 10, pp. 9848-9860.
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© 1967-2012 IEEE. Analog least mean square (ALMS) loop is a promising structure for self-interference (SI) mitigation in full-duplex radios due to its simplicity and adaptive capability. However, being constructed from in-phase/quadrature (I/Q) demodulators and modulators to process complex signals, the ALMS loop may face I/Q imbalance problems. Thus, in this paper, the effects of frequency-independent I/Q imbalance in the ALMS loop are investigated. It is revealed that I/Q imbalance affects the loop gain and the level of SI cancellation. The loop gain can be easily compensated by adjusting the gain at other stages of the ALMS loop. Meanwhile, the degradation on cancellation performance is proved to be insignificant even under severe conditions of I/Q imbalance. In addition, an upper bound of the degradation factor is derived to provide an essential reference for the system design. Simulations are conducted to confirm the theoretical analyses.

Le, AT, Tran, LC, Huang, X, Guo, YJ & Vardaxoglou, JYC 2019, 'Frequency-Domain Characterization and Performance Bounds of ALMS Loop for RF Self-Interference Cancellation', IEEE Transactions on Communications, vol. 67, no. 1, pp. 682-692.
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© 1972-2012 IEEE. Analog least mean square (ALMS) loop is a promising method to cancel self-interference (SI) in in-band full-duplex (IBFD) systems. In this paper, the steady state analyses of the residual SI powers in both analog and digital domains are firstly derived. The eigenvalue decomposition is then utilized to investigate the frequency domain characteristics of the ALMS loop. Our frequency domain analyses prove that the ALMS loop has an effect of amplifying the frequency components of the residual SI at the edges of the signal spectrum in the analog domain. However, the matched filter in the receiver chain will reduce this effect, resulting in a significant improvement of the interference suppression ratio (ISR). It means that the SI will be significantly suppressed in the digital domain before information data detection. This paper also derives the lower bounds of ISRs given by the ALMS loop in both analog and digital domains. These lower bounds are joint effects of the loop gain, tap delay, number of taps, and transmitted signal properties. The discovered relationship among these parameters allows the flexibility in choosing appropriate parameters when designing the IBFD systems under given constraints.

Le, NT & Hoang, DB 2019, 'A Threat Computation Model using a Markov Chain and Common Vulnerability Scoring System and its Application to Cloud Security', Journal of Telecommunications and the Digital Economy, vol. 7, no. 1, pp. 37-56.
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Securing cyber infrastructures has become critical because they are increasingly exposed to attackers while accommodating a huge number of IoT devices and supporting numerous sophisticated emerging applications. Security metrics are essential for assessing the security risks and making effective decisions concerning system security. Many security metrics rely on mathematical models, but are mainly based on empirical data, qualitative methods, or compliance checking, and this renders the outcome far from satisfactory. Computing the probability of an attack, or more precisely a threat that materialises into an attack, forms an essential basis for a quantitative security metric. This paper proposes a novel approach to compute the probability distribution of cloud security threats based on a Markov chain and Common Vulnerability Scoring System. Moreover, the paper introduces the method to estimate the probability of security attacks. The use of the new security threat model and its computation is demonstrated through their application to estimating the probabilities of cloud threats and types of attacks.

Lei, G, Liu, C, Li, Y, Chen, D, Guo, Y & Zhu, J 2019, 'Robust Design Optimization of a High-Temperature Superconducting Linear Synchronous Motor Based on Taguchi Method', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-6.
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© 2002-2011 IEEE. This paper investigates the efficient robust design and optimization of a high-Temperature superconducting (HTS) linear synchronous motor by using the Taguchi parameter design approach. The manufacturing tolerances of the HTS magnets, primary iron core and the air gap are considered in the robust design to ensure that the optimal design is less sensitive to these uncertainties. To overcome the disadvantages of the conventional Taguchi parameter design approach, a sequential Taguchi robust optimization method is presented for improvement of the motor performance and manufacturing quality. The proposed method is efficient because it holds the advantages of both Taguchi method and sequential optimization strategy. It can significantly increase the average thrust and decrease the thrust ripple of the investigated HTS linear synchronous motor.

Li, C, Xie, H-B, Fan, X, Xu, RYD, Van Huffel, S, Sisson, SA & Mengersen, K 2019, 'Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein’s Unbiased Risk Estimator', IEEE Transactions on Image Processing, vol. 28, no. 10, pp. 4899-4911.
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© 1992-2012 IEEE. Singular value thresholding (SVT)- or nuclear norm minimization (NNM)-based nonlocal image denoising methods often rely on the precise estimation of the noise variance. However, most existing methods either assume that the noise variance is known or require an extra step to estimate it. Under the iterative regularization framework, the error in the noise variance estimate propagates and accumulates with each iteration, ultimately degrading the overall denoising performance. In addition, the essence of these methods is still least squares estimation, which can cause a very high mean-squared error (MSE) and is inadequate for handling missing data or outliers. In order to address these deficiencies, we present a hybrid denoising model based on variational Bayesian inference and Stein's unbiased risk estimator (SURE), which consists of two complementary steps. In the first step, the variational Bayesian SVT performs a low-rank approximation of the nonlocal image patch matrix to simultaneously remove the noise and estimate the noise variance. In the second step, we modify the conventional SURE full-rank SVT and its divergence formulas for rank-reduced eigen-triplets to remove the residual artifacts. The proposed hybrid BSSVT method achieves better performance in recovering the true image compared with state-of-the-art methods.

Li, G, Hu, J, Li, Y & Zhu, J 2019, 'An Improved Model Predictive Direct Torque Control Strategy for Reducing Harmonic Currents and Torque Ripples of Five-Phase Permanent Magnet Synchronous Motors', IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 5820-5829.
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© 1982-2012 IEEE. Five-phase permanent magnet synchronous motors offer merits of high fault tolerant capability and high torque per rms ampere and, thus, are suitable for applications, such as aerospace and electric vehicles. However, the complex machine model causes difficulties in controller design. Besides, having 32 voltage vectors with various effects on currents and torque, the selection of the optimal switching state becomes a challenge to achieve a performance tradeoff. This paper proposes an improved model predictive direct torque control (MPDTC) strategy consisting of a quadratic evaluation method (QEM) and a harmonic voltage elimination method (HVEM). In QEM, the preliminary vector is first chosen from the vectors of the outer decagon according to a cost function for torque and flux regulation. This preliminary vector, composed of three sets of different amplitudes, is further synthesized according to the error between the actual torque/flux and the references. In this way, the optimal voltage vector can be obtained without significantly increasing the computational burden. In HVEM, by subtracting the harmonics voltage component from the vector determined previously in QEM, the final voltage vector is obtained for mitigating stator harmonic currents. The proposed control strategy is compared with the conventional MPDTC approach. The results confirm the effectiveness of the proposed methods with good steady-state performance while maintaining quick dynamic responses.

Li, H, Wang, TQ, Huang, X & Jay Guo, Y 2019, 'Adaptive AoA and Polarization Estimation for Receiving Polarized mmWave Signals', IEEE Wireless Communications Letters, vol. 8, no. 2, pp. 540-543.
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© 2012 IEEE. This letter proposes a novel hybrid dual-polarized antenna array which exploits two orthogonally collocated dipoles to capture the full power of a polarized millimeter wave signal. To maximize the received signal-to-noise ratio (SNR), we study the adaptive angle-of-arrival and polarization state estimation, and develop a differential beam tracking algorithm and a cross-correlation-to-power ratio polarization tracking algorithm for interleaved hybrid dual-polarized arrays. Simulation results verify the superior performance of the proposed algorithms, and confirm the significant improvement of SNR obtained by using the proposed array and algorithms.

Li, H, Wang, TQ, Huang, X, Zhang, JA & Guo, YJ 2019, 'Low-Complexity Multiuser Receiver for Massive Hybrid Array mmWave Communications', IEEE Transactions on Communications, vol. 67, no. 5, pp. 3512-3524.
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© 1972-2012 IEEE. In this paper, we study the low complexity reception of multiuser signals in uplink millimeter wave (mmWave) communications using a partially connected hybrid antenna array. Exploiting the mmWave channel property, we propose a low-complexity user-directed multiuser receiver with three novel schemes for allocating subarrays to users. This receiver only requires the knowledge of angles-of-Arrival (AoAs) for dominating paths and a small amount of equivalent channel information instead of perfect channel state information. For comparison, we also derive a successive interference cancellation-based solution as a performance benchmark. We design two types of reference signals with the channel estimation method to enable efficient and simple estimation for AoA and equivalent baseband channel. Also, we provide analytical results for the performance of the AoA estimation, using the lower bounds of mean square errors in line-of-sight dominated mmWave channels. The simulation results validate that the proposed channel estimation method is effective when employed in combination with a zero-forcing equalizer.

Li, J, Li, Q & Zhu, J 2019, 'Health condition assessment of wind turbine generators based on supervisory control and data acquisition data', IET Renewable Power Generation, vol. 13, no. 8, pp. 1343-1350.
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Li, K, Lu, L, Ni, W, Tovar, E & Guizani, M 2019, 'Secret Key Agreement for Data Dissemination in Vehicular Platoons', IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 9060-9073.
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© 2019 IEEE. In a vehicular platoon, the lead vehicle that is responsible for managing the platoon's moving directions and velocity periodically disseminates messages to the following automated vehicles in a multi-hop vehicular network. However, due to the broadcast nature of wireless channels, this kind of communication is vulnerable to eavesdropping and message modification. Generating secret keys by extracting the shared randomness in a wireless fading channel is a promising way for wireless communication security. We study a security protocol for data dissemination in the platoon, where the vehicles cooperatively generate a shared secret key based on the quantized fading channel randomness. To improve conformity of the generated key, the probability of secret key agreement is formulated, and a novel secret key agreement algorithm is proposed to recursively optimize the channel quantization intervals, maximizing the key agreement probability. Numerical evaluations demonstrate that the key agreement probability achieved by our security protocol given different platoon size, channel quality, and number of quantization intervals. Furthermore, by applying our security protocol, the probability that the encrypted data being cracked by an eavesdropper is less than 5%.

Li, K, Ni, W, Abolhasan, M & Tovar, E 2019, 'Reinforcement Learning for Scheduling Wireless Powered Sensor Communications', IEEE Transactions on Green Communications and Networking, vol. 3, no. 2, pp. 264-274.
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© 2017 IEEE. In a wireless powered sensor network, a base station transfers power to sensors by using wireless power transfer (WPT). Inadequately scheduling WPT and data transmission causes fast battery drainage and data queue overflow of some sensors who could have potentially gained high data reception. In this paper, scheduling WPT and data transmission is formulated as a Markov decision process (MDP) by jointly considering sensors' energy consumption and data queue. In practical scenarios, the prior knowledge about battery level and data queue length in MDP is not available at the base station. We study reinforcement learning at the sensors to find a transmission scheduling strategy, minimizing data packet loss. An optimal scheduling strategy with full-state information is also investigated, assuming that the complete battery level and data queue information are well known by the base station. This presents the lower bound of the data packet loss in wireless powered sensor networks. Numerical results demonstrate that the proposed reinforcement learning scheduling algorithm significantly reduces network packet loss rate by 60%, and increases network goodput by 67%, compared to existing non-MDP greedy approaches. Moreover, comparing the optimal solutions, the performance loss due to the lack of sensors' full-state information is less than 4.6%.

Li, K, Ni, W, Tovar, E & Jamalipour, A 2019, 'On-Board Deep Q-Network for UAV-Assisted Online Power Transfer and Data Collection', IEEE Transactions on Vehicular Technology, vol. 68, no. 12, pp. 12215-12226.
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© 1967-2012 IEEE. Unmanned Aerial Vehicles (UAVs) with Microwave Power Transfer (MPT) capability provide a practical means to deploy a large number of wireless powered sensing devices into areas with no access to persistent power supplies. The UAV can charge the sensing devices remotely and harvest their data. A key challenge is online MPT and data collection in the presence of on-board control of a UAV (e.g., patrolling velocity) for preventing battery drainage and data queue overflow of the devices, while up-To-date knowledge on battery level and data queue of the devices is not available at the UAV. In this paper, an on-board deep Q-network is developed to minimize the overall data packet loss of the sensing devices, by optimally deciding the device to be charged and interrogated for data collection, and the instantaneous patrolling velocity of the UAV. Specifically, we formulate a Markov Decision Process (MDP) with the states of battery level and data queue length of devices, channel conditions, and waypoints given the trajectory of the UAV; and solve it optimally with Q-learning. Furthermore, we propose the on-board deep Q-network that enlarges the state space of the MDP, and a deep reinforcement learning based scheduling algorithm that asymptotically derives the optimal solution online, even when the UAV has only outdated knowledge on the MDP states. Numerical results demonstrate that our deep reinforcement learning algorithm reduces the packet loss by at least 69.2%, as compared to existing non-learning greedy algorithms.

Li, K, Voicu, RC, Kanhere, SS, Ni, W & Tovar, E 2019, 'Energy Efficient Legitimate Wireless Surveillance of UAV Communications', IEEE Transactions on Vehicular Technology, vol. 68, no. 3, pp. 2283-2293.
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© 1967-2012 IEEE. Unmanned aerial vehicles (UAVs) enhance connectivity and accessibility for civilian and military applications. Criminals or terrorists can potentially use UAVs for committing crimes and terrorism, thus endangering public safety. In this paper, we consider that a legitimate UAV is employed to track flight of suspicious UAVs for preventing safety and security threats. To obtain flight information of the suspicious UAVs, the legitimate UAV intentionally jams the suspicious receiver so as to force the suspicious UAV to reduce its data rate, and hence increase the eavesdropping success. An energy-efficient jamming strategy is proposed for the legitimate UAV to maximize the amount of eavesdropped packets. Moreover, a tracking algorithm is developed for the legitimate UAV to track the suspicious flight by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter's signal. A new simulation framework is implemented to combine the complementary features of optimization toolbox with channel modeling (in MATLAB) and discrete event-driven mobility tracking (in NS3). Moreover, numerical results validate the proposed algorithms in terms of packet eavesdropping rate and tracking accuracy of the suspicious UAVs' trajectory.

Li, N, Zhu, J, Lin, M, Yang, G, Kong, Y & Hao, L 2019, 'Analysis of Axial Field Flux-Switching Memory Machine Based on 3-D Magnetic Equivalent Circuit Network Considering Magnetic Hysteresis', IEEE Transactions on Magnetics, vol. 55, no. 6, pp. 1-4.
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Li, Q, Su, T & Wu, K 2019, 'Accurate DOA Estimation for Large-Scale Uniform Circular Array Using a Single Snapshot', IEEE Communications Letters, vol. 23, no. 2, pp. 302-305.
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© 1997-2012 IEEE. A large-scale antenna array is an enabling technique for millimeter-wave communications. Uniform circular arrays (UCAs) have the spatial invariance property, ensuring the same beamforming performance in the whole angular region. However, the direction-of-arrival (DOA) estimation in UCAs is challenging since the array response of a UCA does not conform to a Vandermonde structure as that of a uniform linear array. This letter proposes an accurate and low-complexity DOA estimation approach by exploiting the good correlation property of the array response of the UCA. The DOA estimates are first obtained from a circular convolution between a single snapshot and the designed coefficient vector. Then, by searching for the best initial phase of the coefficient vector, the DOA estimates can be refined to a configurable accuracy. The simulation results demonstrate that the proposed approach outperforms the state of the art by orders of magnitude in estimation accuracy.

Li, W, Liu, BM, Liu, D, Liu, RP, Wang, P, Luo, S & Ni, W 2019, 'Unified Fine-Grained Access Control for Personal Health Records in Cloud Computing', IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 3, pp. 1278-1289.
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© 2013 IEEE. Attribute-based encryption has been a promising encryption technology to secure personal health records (PHRs) sharing in cloud computing. PHRs consist of the patient data often collected from various sources including hospitals and general practice centres. Different patients' access policies have a common access sub-policy. In this paper, we propose a novel attribute-based encryption scheme for fine-grained and flexible access control to PHRs data in cloud computing. The scheme generates shared information by the common access sub-policy, which is based on different patients' access policies. Then, the scheme combines the encryption of PHRs from different patients. Therefore, both time consumption of encryption and decryption can be reduced. Medical staff require varying levels of access to PHRs. The proposed scheme can also support multi-privilege access control so that medical staff can access the required level of information while maximizing patient privacy. Through implementation and simulation, we demonstrate that the proposed scheme is efficient in terms of time. Moreover, we prove the security of the proposed scheme based on security of the ciphertext-policy attribute-based encryption scheme.

Li, Z, Guo, YJ, Chen, S-L & Wang, J 2019, 'A Period-Reconfigurable Leaky-Wave Antenna With Fixed-Frequency and Wide-Angle Beam Scanning', IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 3720-3732.
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© 1963-2012 IEEE. A novel fixed-frequency beam-scanning leaky-wave antenna (LWA) based on a period-reconfigurable structure is presented. Operating at 5 GHz, the antenna consists of a slotted substrate integrated waveguide and 54 electrically small patches. Each patch element is etched with two dumbbell-shaped slots, and its operating state can be flexibly controlled by the biasing of the p-i-n diode on a parasitic strip. An ideal array model employing isotropic point sources is used for the analysis on the scanning mechanism, based on which a new method for suppressing the higher order space harmonics is developed. Using this method, the monoharmonic radiation range can be dramatically extended, and a wide-angle beam scanning can be achieved by manipulating the period length of the LWA. An FPGA controlling platform is designed for the electronic control of the antenna. The measured results validate that the proposed antenna achieves good performance of wide-angle scanning (125°) with a peak gain of 11.8 dBi at a fixed frequency.

Li, Z, Zhang, S, Wang, J, Li, Y, Chen, M, Zhang, Z & Guo, YJ 2019, 'A Method of Generating Radiation Null for Periodic Leaky-Wave Antennas', IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 4241-4246.
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© 1963-2012 IEEE. A systematic method for generating a radiation null region in the radiation pattern of periodic leaky-wave antennas (LWAs) is proposed using the theory of effective radiation sections (ERSs). In this method, the aperture field is expanded into spatial harmonics using the mode expansion method, and the ERSs of the harmonics are studied. Based on this, the radiation null region is introduced by suppressing the radiation of the ERSs corresponding to the radiating mode. The proposed method is applied to a periodic-strip LWA. The validity of the proposed method is verified by both simulated and experimental results, showing an obvious radiation null in the prescribed angular range. This method has the advantages of easy calculation and implementation, and has little influence on the gain and beamwidth. It is illustrated that only simple modification to the antenna structure is needed to achieve nulling.

Liang, J, Mondal, AK, Wang, D & Iacopi, F 2019, 'Graphene‐Based Planar Microsupercapacitors: Recent Advances and Future Challenges', Advanced Materials Technologies, vol. 4, no. 1, pp. 1800200-1800200.
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AbstractThe continuous development of integrated electronics such as maintenance‐free biosensors, remote and mobile environmental sensors, wearable personal electronics, nanorobotics etc. and their continued miniaturization has led to an increasing demand for miniaturized energy storage units. Microsupercapacitors with graphene electrodes hold great promise as miniaturized, integrated power sources thanks to their fast charge/discharge rates, superior power performance, and long cycling stability. In addition, planar interdigitated electrodes also have the capability to reduce ion diffusion distances leading to a greatly improved electrochemical performance. Either as standalone power sources or complementing energy harvesting units, it is expected that graphene‐based microsupercapacitors will play a key role as miniaturized power sources in electronic microsystems. This review highlights the recent development, challenges, and perspectives in this area, with an emphasis on the link between material and geometry design of planar graphene‐based electrodes and their electrochemical performance and integrability.

Liu, F, Liu, Y, Xu, KD, Ban, Y-L, Liu, QH & Guo, YJ 2019, 'Synthesizing Uniform Amplitude Sparse Dipole Arrays With Shaped Patterns by Joint Optimization of Element Positions, Rotations and Phases', IEEE Transactions on Antennas and Propagation, vol. 67, no. 9, pp. 6017-6028.
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Liu, L, Amirgholipour, S, Jiang, J, Jia, W, Zeibots, M & He, X 2019, 'Performance-enhancing network pruning for crowd counting', Neurocomputing, vol. 360, pp. 246-253.
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© 2019 The Counting Convolutional Neural Network (CCNN) has been widely used for crowd counting. However, they typically end up with a complicated network model resulting in a challenge for real-time processing. Existing solutions aim to reduce the size of the network model, but unavoidably sacrifice the network accuracy. Different from existing pruning solutions, in this paper, a new pruning strategy is proposed by considering the contributions of various filters to the final result. The filters in the original CCNN model are grouped into positive, negative and irrelevant types. We prune the irrelevant filters of which feature maps contain little information, and the negative filters determined by a mask learned from the training dataset. Our solution improves the results of the counting model without fine-tuning or retraining the pruned model. We demonstrate the advantages of our proposed approach on the problem of crowd counting. Our experimental results on benchmark datasets show that the network model pruned using our approach not only reduces the network size but also improves the counting accuracies by 4% to 17% less MAE than the state of the arts.

Liu, M, Luo, Y, Nanda, P, Yu, S & Zhang, J 2019, 'Efficient solution to the millionaires' problem based on asymmetric commutative encryption scheme', Computational Intelligence, vol. 35, no. 3, pp. 555-576.
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AbstractSecure multiparty computation is an important scheme in cryptography and can be applied in various real‐life problems. The first secure multiparty computation problem is the millionaires' problem, and its protocol is an important building block. Because of the less efficiency of public key encryption scheme, most existing solutions based on public key cryptography to this problem are inefficient. Thus, a solution based on the symmetric encryption scheme has been proposed. In this paper, we formally analyse the vulnerability of this solution, and propose a new scheme based on the decisional Diffie‐Hellman assumption. Our solution also uses 0‐encoding and 1‐encoding generated by our modified encoding method to reduce the computation cost. We implement the solution based on symmetric encryption scheme and our protocol. Extensive experiments are conducted to evaluate the efficiency of our solution, and the experimental results show that our solution can be much more efficient and be approximately 8000 times faster than the solution based on symmetric encryption scheme for a 32‐bit input and short‐term security. Moreover, our solution is also more efficient than the state‐of‐the‐art solution without precomputation and can also compare well with the state‐of‐the‐art protocol while the bit length of private inputs is large enough.

Liu, T, Zhang, W, Ye, L, Ueland, M, Forbes, SL & Su, SW 2019, 'A novel multi-odour identification by electronic nose using non-parametric modelling-based feature extraction and time-series classification', Sensors and Actuators B: Chemical, vol. 298, pp. 126690-126690.
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© 2019 Elsevier B.V. The electronic nose (e-nose) is an olfaction system that consists of an array of chemical sensors and effective machine learning algorithms for the detection of various target odours. Feature extraction and classification methods are of great importance in improving the performance of the e-nose system. In this paper, a novel odour identification method is presented. Firstly, we use the kernel-based system modelling approach to extract odour features. Its solution is a series of finite impulse responses which containing discriminant information of different odours. In addition, a parameter optimisation method based on normalised mean square error and information entropy is proposed to optimise the kernel function. The entropy is effective in preventing the finite impulse responses from overfitting. Multi-odour classification is achieved based on Gaussian mixture density hidden Markov model (GMM-HMM) considering the characteristic of the extracted features. Also, parameter selection for GMM-HMM is realised according to BIC index and cross-validation. Then, we validate the performance of the proposed feature extraction method in resistance to noise and compare it with other existed features. The modelling-based feature reached the highest performance even without applying any filtering or smoothing techniques. Finally, we compare the proposed combination of feature extraction and classification algorithms with other approaches. The proposed method outperformed other approaches reaching 93.56% in sensitivity and 98.71% in specificity. The results demonstrate that the proposed method is applicable in e-nose-based odour identification.

Liu, Y, Xu, W, Zhu, J & Blaabjerg, F 2019, 'Sensorless Control of Standalone Brushless Doubly Fed Induction Generator Feeding Unbalanced Loads in a Ship Shaft Power Generation System', IEEE Transactions on Industrial Electronics, vol. 66, no. 1, pp. 739-749.
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© 1982-2012 IEEE. The standalone brushless doubly fed induction generator (BDFIG) has demonstrated excellent energy-saving performance in ship shaft power generation applications. As a standalone system, it exhibits unbalanced terminal voltages and poor performance under unbalanced loads. However, the existing control scheme of grid-connected BDFIGs cannot be directly applied to stabilize the amplitude and frequency of terminal voltage when the rotor speed and electrical load vary. This paper presents a new sensorless control scheme for the standalone BDFIG under unbalanced load conditions in the ship shaft power generation system. A second-order generalized integrator-based quadrature signal generator is introduced to realize the rotor speed observer for the standalone BDFIG feeding unbalanced loads. The compensation method of negative-sequence power winding voltage is proposed to eliminate the negative-sequence component of the unbalanced power winding voltage. Comprehensive experiments are carried out on a prototype BDFIG with and without the compensation of negative-sequence power winding voltage. The good performance of the proposed sensorless control scheme is verified by the experimental test results.

Lu, S, Oberst, S, Zhang, G & Luo, Z 2019, 'Bifurcation analysis of dynamic pricing processes with nonlinear external reference effects', Communications in Nonlinear Science and Numerical Simulation, vol. 79, pp. 104929-104929.
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© 2019 Elsevier B.V. Dynamic pricing has been widely implemented to hedge against volatile demand. One challenging problem is the study of optimal price choices under the influence of this volatility. Stochastic demand is a prevalent assumption when it comes to model the volatility on pricing decisions. However, the demand volatility might also be produced by deterministic chaos, which has rarely been studied in this field of research to-date. We propose deterministic dynamic pricing processes that aim to maximise the revenue and to mimic a real pricing decision. Our model includes nonlinear consumer expectations that explain the effects of external information on consumers and discrete optimisations due to a non-smooth demand function that considers asymmetries in the perceptions of gains or losses of consumers and finite price choices of companies. Volatile markets can show up because of non-periodic consumer expectations, period adding bifurcations, codimension-2 points and coexisting solutions. Results highlight that optimal pricing strategies should agree with the dynamics of consumer expectations. Disregarding deterministic dynamics may not only cause revenue losses in practice but might also mislead regulators about the underlying mechanisms that consumers and companies respond to. We introduce for the first time an irregular pricing strategy: a company can make the first return iteration of each sales price non-periodic to follow non-periodic consumer expectations when having finite price choices. These results may justify implementing irregular pricing strategies in the case of practical pricing decisions. Here, the existence of coexisting solutions can assist to identify potential market manipulations within a monopoly market. This not only contributes to a fresh look on volatile markets but also emphasises the importance of initial conditions to pricing decisions and price regulations.

Lu, W, Meng, F, Wang, S, Zhang, G, Zhang, X, Ouyang, A & Zhang, X 2019, 'Graph-Based Chinese Word Sense Disambiguation with Multi-Knowledge Integration', Computers, Materials & Continua, vol. 61, no. 1, pp. 197-212.
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© 2019 Tech Science Press. All rights reserved. Word sense disambiguation (WSD) is a fundamental but significant task in natural language processing, which directly affects the performance of upper applications. However, WSD is very challenging due to the problem of knowledge bottleneck, i.e., it is hard to acquire abundant disambiguation knowledge, especially in Chinese. To solve this problem, this paper proposes a graph-based Chinese WSD method with multi-knowledge integration. Particularly, a graph model combining various Chinese and English knowledge resources by word sense mapping is designed. Firstly, the content words in a Chinese ambiguous sentence are extracted and mapped to English words with BabelNet. Then, English word similarity is computed based on English word embeddings and knowledge base. Chinese word similarity is evaluated with Chinese word embedding and HowNet, respectively. The weights of the three kinds of word similarity are optimized with simulated annealing algorithm so as to obtain their overall similarities, which are utilized to construct a disambiguation graph. The graph scoring algorithm evaluates the importance of each word sense node and judge the right senses of the ambiguous words. Extensive experimental results on SemEval dataset show that our proposed WSD method significantly outperforms the baselines.

Lu, Z, Zhao, B, He, L, Zhang, D & Zhang, J 2019, 'Security‐level classification based on power system partitioning', IET Generation, Transmission & Distribution, vol. 13, no. 5, pp. 703-709.
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Luo, Y, Zhang, JA, Huang, X, Ni, W & Pan, J 2019, 'Optimization and Quantization of Multibeam Beamforming Vector for Joint Communication and Radio Sensing', IEEE Transactions on Communications, vol. 67, no. 9, pp. 6468-6482.
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© 1972-2012 IEEE. Joint communication and radio sensing (JCAS) in millimeter-wave (mmWave) systems requires the use of a steerable beam. For analog antenna arrays, a single beam is typically used, which limits the sensing area within the direction of the communication. Multibeam technology can overcome this limitation by separately generating package-level direction-varying sensing subbeams and fixed communication subbeams and then combine them coherently. In this paper, we investigate the optimal combination of the two subbeams and the quantization of the beamforming (BF) vector that generates the combined beam. When either the full channel matrix or only the angle of departure (AoD) of the dominating line-of-sight (LOS) path is known at the transmitter, we derive the closed-form expressions for the optimal combining coefficients that maximize the received communication signal power. For the quantization of the BF vector, we focus on the two-phase-shifter array where two phase shifters are used to represent each BF weight. We propose novel joint quantization methods by combining the codebooks of the two phase shifters. The mean squared quantization error is derived for various quantization methods. Extensive simulation results validate the accuracy of the analytical results and the effectiveness of the proposed multibeam optimization and joint quantization methods.

Luong, NC, Hoang, DT, Gong, S, Niyato, D, Wang, P, Liang, Y-C & Kim, DI 2019, 'Applications of Deep Reinforcement Learning in Communications and Networking: A Survey', IEEE Communications Surveys & Tutorials, vol. 21, no. 4, pp. 3133-3174.
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© 1998-2012 IEEE. This paper presents a comprehensive literature review on applications of deep reinforcement learning (DRL) in communications and networking. Modern networks, e.g., Internet of Things (IoT) and unmanned aerial vehicle (UAV) networks, become more decentralized and autonomous. In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment. Reinforcement learning has been efficiently used to enable the network entities to obtain the optimal policy including, e.g., decisions or actions, given their states when the state and action spaces are small. However, in complex and large-scale networks, the state and action spaces are usually large, and the reinforcement learning may not be able to find the optimal policy in reasonable time. Therefore, DRL, a combination of reinforcement learning with deep learning, has been developed to overcome the shortcomings. In this survey, we first give a tutorial of DRL from fundamental concepts to advanced models. Then, we review DRL approaches proposed to address emerging issues in communications and networking. The issues include dynamic network access, data rate control, wireless caching, data offloading, network security, and connectivity preservation which are all important to next generation networks, such as 5G and beyond. Furthermore, we present applications of DRL for traffic routing, resource sharing, and data collection. Finally, we highlight important challenges, open issues, and future research directions of applying DRL.

Luong, NT, Vo, TT & Hoang, D 2019, 'FAPRP: A Machine Learning Approach to Flooding Attacks Prevention Routing Protocol in Mobile Ad Hoc Networks', Wireless Communications and Mobile Computing, vol. 2019, pp. 1-17.
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Request route flooding attack is one of the main challenges in the security of Mobile Ad Hoc Networks (MANETs) as it is easy to initiate and difficult to prevent. A malicious node can launch an attack simply by sending an excessively high number of route request (RREQ) packets or useless data packets to nonexistent destinations. As a result, the network is rendered useless as all its resources are used up to serve this storm of RREQ packets and hence unable to perform its normal routing duty. Most existing research efforts on detecting such a flooding attack use the number of RREQs originated by a node per unit time as the threshold to classify an attacker. These algorithms work to some extent; however, they suffer high misdetection rate and reduce network performance. This paper proposes a new flooding attacks detection algorithm (FADA) for MANETs based on a machine learning approach. The algorithm relies on the route discovery history information of each node to capture similar characteristics and behaviors of nodes belonging to the same class to decide if a node is malicious. The paper also proposes a new flooding attacks prevention routing protocol (FAPRP) by extending the original AODV protocol and integrating FADA algorithm. The performance of the proposed solution is evaluated in terms of successful attack detection ratio, packet delivery ratio, and routing load both in normal and under RREQ attack scenarios using NS2 simulation. The simulation results show that the proposed FAPRP can detect over 99% of RREQ flooding attacks for all scenarios using route discovery frequency vector of sizes larger than 35 and performs better in terms of packet delivery ratio and routing load compared to existing solutions for RREQ flooding attacks.

Lyu, X, Ren, C, Ni, W, Tian, H, Liu, RP & Dutkiewicz, E 2019, 'Optimal Online Data Partitioning for Geo-Distributed Machine Learning in Edge of Wireless Networks', IEEE Journal on Selected Areas in Communications, vol. 37, no. 10, pp. 2393-2406.
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© 1983-2012 IEEE. To enable machine learning at the edge of wireless networks (such as edge cloud), close to mobile users, is critical for future wireless networks, but challenging since the lower layers in edge cloud are substantially different from existing machine learning configurations in the cloud. In such geo-distributed computing environment, streaming data need to be evenly and cost-efficiently partitioned for different workers to produce an unbiased learning model with reduced parameter synchronization frequency. This paper presents a new online approach to optimally partitioning streaming data under time-varying network conditions. A new measure is proposed to quantify the evenness of data partitioning and restrain the optimization of data admission, partitioning, and processing. Stochastic gradient descent is applied to learn the optimal decisions online and asymptotically maximize the time-average utility of data partitioning. A new protocol is designed to further reduce the measurements of link costs, while preserving the asymptotic optimality, data evenness, and stability of the platform. Simulation results show that the proposed approach is superior to the state of the art in terms of throughput and cost efficiency, while only 24% of the links need to be measured to achieve the asymptotic optimality.

Mahmud, K, Hossain, MJ & Ravishankar, J 2019, 'Peak-Load Management in Commercial Systems With Electric Vehicles', IEEE Systems Journal, vol. 13, no. 2, pp. 1872-1882.
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© 2007-2012 IEEE. Electric vehicles (EVs) are getting popular as one of the effective solutions for increased energy efficiency in commercial systems. This paper proposes an improved algorithm for commercial peak-load management using EVs, battery-energy-storage systems, and photovoltaic units. It uses the bidirectional vehicle-to-grid technique to utilize the energy from EVs in a parking lot. The proposed system has been tested in a real power distribution network in realistic load and weather conditions. The financial benefit of the system is also investigated, and it is found that the industrial peak load can be reduced by 50%, and the energy cost can be reduced by up to 27.3%. It also enhances the load factor by 9%. The performance of the proposed control algorithm is compared with that of an artificial-neural-network-based technique and tested in a laboratory prototype. From simulated and experimental results, it is found that the proposed approach provides substantial savings, while reducing the peak demand of the existing grids.

Makhdoom, I, Abolhasan, M, Abbas, H & Ni, W 2019, 'Blockchain's adoption in IoT: The challenges, and a way forward', Journal of Network and Computer Applications, vol. 125, pp. 251-279.
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© 2018 Elsevier Ltd The underlying technology of Bitcoin is blockchain, which was initially designed for financial value transfer only. Nonetheless, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as pseudonymous identities, data integrity and authentication, researchers and security analysts around the world are focusing on the blockchain to resolve security and privacy issues of IoT. However, presently, not much work has been done to assess blockchain's viability for IoT and the associated challenges. Hence, to arrive at intelligible conclusions, this paper carries out a systematic study of the peculiarities of the IoT environment including its security and performance requirements and progression in blockchain technologies. We have identified the gaps by mapping the security and performance benefits inferred by the blockchain technologies and some of the blockchain-based IoT applications against the IoT requirements. We also discovered some practical issues involved in the integration of IoT devices with the blockchain. In the end, we propose a way forward to resolve some of the significant challenges to the blockchain's adoption in IoT.

Makhdoom, I, Abolhasan, M, Lipman, J, Liu, RP & Ni, W 2019, 'Anatomy of Threats to the Internet of Things', IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1636-1675.
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© 1998-2012 IEEE. The world is resorting to the Internet of Things (IoT) for ease of control and monitoring of smart devices. The ubiquitous use of IoT ranges from industrial control systems (ICS) to e-Health, e-Commerce, smart cities, supply chain management, smart cars, cyber physical systems (CPS), and a lot more. Such reliance on IoT is resulting in a significant amount of data to be generated, collected, processed, and analyzed. The big data analytics is no doubt beneficial for business development. However, at the same time, numerous threats to the availability and privacy of the user data, message, and device integrity, the vulnerability of IoT devices to malware attacks and the risk of physical compromise of devices pose a significant danger to the sustenance of IoT. This paper thus endeavors to highlight most of the known threats at various layers of the IoT architecture with a focus on the anatomy of malware attacks. We present a detailed attack methodology adopted by some of the most successful malware attacks on IoT, including ICS and CPS. We also deduce an attack strategy of a distributed denial of service attack through IoT botnet followed by requisite security measures. In the end, we propose a composite guideline for the development of an IoT security framework based on industry best practices and also highlight lessons learned, pitfalls and some open research challenges.

Malekjamshidi, Z, Jafari, M, Zhu, J & Xiao, D 2019, 'Comparative Analysis of Input Power Factor Control Techniques in Matrix Converters Based on Model Predictive and Space Vector Control Schemes', IEEE Access, vol. 7, pp. 139150-139160.
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Model Predictive Control (MPC) with a finite control set and space vector modulation (SVM) are the most common control methods for the matrix converters (MCs). This paper is focused on the input and output currents performance analysis of the matrix converter controlled by SVM and MPC. A closed-loop control of the input current displacement angle is employed in the SVM strategy to provide unity input power factor over a wide range of voltage transfer ratio. For MPC, a discrete-time model of the converter, including the input filter and load, are used to predict the input and output currents for each valid switching state. The MPC, SVM, and power factor controlled SVM (PFC-SVM) methods are analyzed in detail, and their performance in controlling the input power factor, current quality, and transient response are compared through numerical simulations and experimental tests.

Malekjamshidi, Z, Jafari, M, Zhu, J & Xiao, D 2019, 'Comparison of matrix converter stabilisation techniques based on the damping resistor and digital filter approaches for bidirectional power flow control', IET Power Electronics, vol. 12, no. 15, pp. 3964-3976.
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The matrix converter is becoming a mature technology with its specific advantages and limitations, and can be effectively used as an interface link in the future smart grids. In this context, the stability of the converter under different power flow conditions is highly important and needs more clarification. The input inductor-capacitor filter can significantly impact the stability of the converter when the output is tightly regulated, especially in bidirectional power flow control applications where a low-impedance source is connected to the converter output. This paper investigates the matrix converter stability for bidirectional power flow control, considering the input filter and other parameters of the system. A detailed analysis of two commonly used active and passive stabilization techniques known as digital filter and damping resistor approaches is presented, and a third method based on a combination of these two methods is suggested in this paper. The converter stability region for the proposed technique is determined by using the small-signal model of the converter. The converter performance for the methods is compared in terms of the efficiency, stability, transients and quality of the input and output currents. Numerical simulations and experimental tests are conducted on a prototype direct matrix converter to validate the proposed method.

Md Rafi, FH, Hossain, MJ, Town, G & Lu, J 2019, 'Smart Voltage-Source Inverters With a Novel Approach to Enhance Neutral-Current Compensation', IEEE Transactions on Industrial Electronics, vol. 66, no. 5, pp. 3518-3529.
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© 1982-2012 IEEE. The presence of a neutral current is quite common in three-phase (3P) four-wire (4W) distribution systems due to an unequal distribution of linear and nonlinear single-phase (1P) loads and small distributed generators. However, a high neutral current can overload the neutral conductor and distribution transformer, which can cause electrical safety concerns and even fire. Among several existing neutral current compensators, the 3P four-leg (4L) voltage-source inverter (VSI) provides better control flexibility and more efficient performance than the passive compensators but requires a higher VSI capacity for the fourth-leg operation. To provide a solution to the aforementioned problem, this paper presents a novel control method to utilize the available capacity of a 3P-4L VSI after active and reactive power regulation to enhance the neutral-current compensation. A smart VSI (SVSI) is designed to operate with a solar photovoltaic unit, regulate the ac side voltage, and minimize the neutral current. Case studies are conducted with actual load data from a commercial building in the PSCAD/EMTDC software environment. The designed system with the proposed control method can provide a significant improvement in the neutral-current compensation, phase balancing, and unbalance factor compared to a fixed-capacity 3P-4L SVSI. Experimental results using a TMS320F28335 digital signal processor microcontroller and modified Semiteach 3P-4L inverter are presented to verify the robustness of the designed controller and the enhancement to the neutral-current compensation using the proposed dynamic capacity-control method.

Men, X, Wu, G, Guo, Y, Zhu, Z & Gao, J 2019, 'Development of an Advanced Motor Control System for Electric Vehicles', SAE Technical Paper Series, vol. 2019-April, no. April.
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© 2019 SAE International. All Rights Reserved. Electric vehicles are considered as one of the most popular way to decrease the consumption of petroleum resources and reduce environmental pollutions. Motor control system is one of the most important part of electric vehicles. It includes power supply module, IGBT driver, digital signal processing (DSP) controller, protection adjustment module, and resolver to digital convertor. To implement the control strategies on motor control system, a lot of practical aspects need to be taken into accounts. It includes setup of the initial excitation current, consistency of current between motor and program code, over-modulation, field weakening control, current protection, and so on. In this paper, an induction motor control system for electric vehicles is developed based on DSP. The control strategy is based on the field-oriented control (FOC) and space vector pulse width modulation (SVPWM). Speed calculation, over-modulation, field weakening control, PI controller, and fault diagnosis are also applied in this DSP algorithm. As an industry product running on a real electric bus with a 100kW induction motor, communication with vehicle control unit (VCU) by CAN bus, control system safety and PC software designed for lab experiments are also discussed. This paper focused on how to develop the advanced motor control system for electric vehicles for industrial application. The steady-state and transient performances of this motor control system are analyzed by both test-bench experiments and road experiments. Its performance is satisfactory when applied to the real electric vehicle.

Mendelson, N, Xu, Z-Q, Tran, TT, Kianinia, M, Scott, J, Bradac, C, Aharonovich, I & Toth, M 2019, 'Engineering and Tuning of Quantum Emitters in Few-Layer Hexagonal Boron Nitride', ACS Nano, vol. 13, no. 3, pp. 3132-3140.
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© 2019 American Chemical Society. Quantum technologies require robust and photostable single photon emitters (SPEs). Hexagonal boron nitride (hBN) has recently emerged as a promising candidate to host bright and optically stable SPEs operating at room temperature. However, the emission wavelength of the fluorescent defects in hBN has, to date, been shown to be uncontrolled, with a widespread of zero phonon line (ZPL) energies spanning a broad spectral range (hundreds of nanometers), which hinders the potential development of hBN-based devices and applications. Here we demonstrate chemical vapor deposition growth of large-area, few-layer hBN films that host large quantities of SPEs: -100-200 per 10 × 10 μm 2 . More than 85% of the emitters have a ZPL at (580 ± 10) nm, a distribution that is an order of magnitude narrower than reported previously. Furthermore, we demonstrate tuning of the ZPL wavelength using ionic liquid devices over a spectral range of up to 15 nm-the largest obtained to date from any solid-state SPE. The fabricated devices illustrate the potential of hBN for the development of hybrid quantum nanophotonic and optoelectronic devices based on two-dimensional materials.

Mishra, N, Bosi, M, Rossi, F, Salviati, G, Boeckl, J & Iacopi, F 2019, 'Growth of graphitic carbon layers around silicon carbide nanowires', Journal of Applied Physics, vol. 126, no. 6, pp. 065304-065304.
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We demonstrate the ability to synthesize graphitic carbon sheets around cubic silicon carbide nanowires via an alloy-mediated catalytic process. The transmission electron microscopy analysis shows multilayer graphitic carbon sheets with a large interatomic layer distance of ∼0.45 nm, suggesting the presence of oxygen in the graphitic system. Oxygen-related peaks observed by energy-dispersive X-ray spectroscopy, Raman spectroscopy, and Fourier-transform infrared spectroscopy further confirm the oxidation of the graphitic carbon layers. A detailed investigation of the Raman spectra reveals a turbostratic stacking of the graphitic carbon layers. The turbostratic nature and the presence of oxidation in the graphitic carbon surrounding the silicon carbide nanowires make them a suitable platform for further functionalization, of particular interest for biosensing, as both graphitic carbon and silicon carbide are biocompatible.

Mora, A, Cardenas-Dobson, R, Aguilera, RP, Angulo, A, Donoso, F & Rodriguez, J 2019, 'Computationally Efficient Cascaded Optimal Switching Sequence MPC for Grid-Connected Three-Level NPC Converters', IEEE Transactions on Power Electronics, vol. 34, no. 12, pp. 12464-12475.
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© 1986-2012 IEEE. In this work, a model predictive control (MPC) strategy based on optimal switching sequence (OSS) concepts is proposed for a grid-connected three-level neutral-point clamped converter. The proposed cascaded-OSS-MPC strategy does not require a weighting factor to balance the dc-link capacitor voltages and optimally controls both the grid currents and the capacitor voltages even during disturbances and large step changes in the references. The resulting MPC strategy allows operating the converter with a predefined harmonic spectrum, fixed switching frequency, and fast and robust dynamic response. Besides, an efficient optimization algorithm is also introduced to reduce the computational burden typically observed in this kind of MPC strategies. Experimental and simulation results are provided to demonstrate the effectiveness and high-quality performance of the proposed strategy.

Mostaan, A, Yuan, J, Siwakoti, YP, Esmaeili, S & Blaabjerg, F 2019, 'A Trans-Inverse Coupled-Inductor Semi-SEPIC DC/DC Converter With Full Control Range', IEEE Transactions on Power Electronics, vol. 34, no. 11, pp. 10398-10402.
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© 1986-2012 IEEE. This letter proposes a single switch magnetically coupled dc-dc converter with a high voltage gain. The unique features of the converter are summarized as follows: 1) voltage gain of the converters is raised by lowering its magnetic turn ratio; 2) wide control range (0< D< 1); 3) continuous current from the source that makes it a suitable candidate for renewable energy applications; and 4) there is no dc current saturation in the core due to the presence of capacitor in the primary winding of the inductor. The feasibility of the proposed converter is studied in details supported by circuit analysis and simulation results. Furthermore, the proposed converter is analyzed and compared with other converters with similar features. Finally the superior performance of the circuit is validated experimentally.

Mueck, MD, Badic, B, Ahn, H, Bender, P, Choi, S & Ivanov, V 2019, 'Market Access for Radio Equipment in Europe Enabled by the Radio Equipment Directive: Status, Next Steps and Implications', IEEE Communications Magazine, vol. 57, no. 12, pp. 20-24.
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In Europe, market access for radio equipment is governed through the Radio Equipment Directive (RED), which replaced the Radio Equipment and Telecommunications Terminal Equipment (R&TTE) Directive in 2016. The essential requirements were introduced by RED and subsequently processed by European standards organizations: the European Telecommunications Standards Institute, the European Committee for Electrotechnical Standardization, and the European Committee for Standardization, in order to develop harmonised standards (HSs). These HSs may be used by manufacturers in order to achieve self-declaration of conformity of radio equipment. Compared to the previously applicable R&TTE Directive, RED contains a set of new Articles, including RED Articles 3(3)(a) to 3(3)(i) and Article 4, which were not enacted when RED was originally published. This article discusses the process for "activating" the corresponding articles, and provides commentary on related ongoing activities in European Commission Expert Groups and detailed implications on radio equipment design. Indeed, new requirements need to be met in order to achieve market access, such as reconfigurability, privacy, and security features. Finally, implications such as time to market and RED compliance certification cost are assessed, and a comparison to other regulation regimes is given, including those in the United States, Korea, and Russia.

Mukhtar, NM & Lu, DD-C 2019, 'A Bidirectional Two-Switch Flyback Converter With Cross-Coupled LCD Snubbers for Minimizing Circulating Current', IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 5948-5957.
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© 1982-2012 IEEE. This paper proposes a novel isolated bidirectional two-switch flyback converter with two integrated non-dissipative inductor-capacitor-diode (LCD) snubbers. In the proposed topology, the main flyback transformer and the LCD snubbers are cross coupled to minimize circulating current that would occur in the non-cross-coupled case, in addition to recycle leakage energy and protect the power transistors. The same current circulation issue also occurs in the bidirectional flyback converter with conventional resistor-capacitor-diode (RCD) snubbers. The main objective of this paper is to illustrate this issue and propose an alternate circuitry to reduce the current circulation and improve the conversion efficiency. The experimental results of a laboratory prototype are reported to verify the design.

Naing, HMS, Hidayat, R, Winduratna, B & Miyanaga, Y 2019, 'Psychoacoustical masking effect-based feature extraction for robust speech recognition', International Journal of Innovative Computing, Information and Control, vol. 15, no. 5, pp. 1641-1654.
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A new approach for speech feature extraction in automatic speech recognition (ASR) is proposed in this paper. It is based on the human auditory system. Generally, the mel frequency cepstral coefficients (MFCC) are the most widely used speech features in ASR systems, but one of their main drawbacks is background noise, which can affect and hamper the results. This paper proposes noise robust speech features which improve upon the MFCC. A psychoacoustic model-based feature extraction that simulates the perception of sound in the human auditory system is investigated and integrated into the MFCC. The complexity of the signal can be reduced by using a masking effect during feature extraction, minimizing the feature components without any significant loss in perceiving quality of sound. Moreover, it can reduce the noise effect of speech signal. In this paper, a hidden Markov model is employed to recognize English isolated digits. These experiments verify that the proposed modified method effectively improves the recognition under adverse situations. With respect to the use of perceptual masking effect-based cepstral features, the accuracy reached up to 97.16% in signal to noise ratio at 10dB, 95.02% at 5dB, 90.34% at 0dB, 77.08% at −5dB and 62.76% at −10dB, respectively.

Nasir, AA, Tuan, HD, Duong, TQ & Debbah, M 2019, 'NOMA Throughput and Energy Efficiency in Energy Harvesting Enabled Networks', IEEE Transactions on Communications, vol. 67, no. 9, pp. 6499-6511.
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© 1972-2012 IEEE. An energy harvesting (EH) enabled network is capable of delivering energy to users, who are located sufficiently close to the base stations. However, wireless energy delivery requires much more transmit power than what the normal information delivery does. It is very challenging to provide the quality of wireless information and power delivery simultaneously. It is of practical interest to employ non-orthogonal multiple access (NOMA) to improve the network throughput, while fulfilling the EH requirements. To realize both the EH and information decoding, this paper considers a transmit time-switching (transmit-TS) protocol. Two important problems of users' max-min throughput optimization and energy efficiency maximization under power constraint and EH thresholds, which are non-convex in beamforming vectors, are addressed by efficient path-following algorithms. In addition, the conventional power splitting (PS)-based EH receiver is also considered. The provided numerical results confirm that the proposed transmit-TS-based algorithms clearly outperform the PS-based algorithms in terms of throughput and energy efficiency.

Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2019, 'Improper Gaussian Signaling for Broadcast Interference Networks', IEEE Signal Processing Letters, vol. 26, no. 6, pp. 808-812.
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© 1994-2012 IEEE. For a multi-user multi-cell network, which suffers both intra-cell and inter-cell interference, this letter considers improper Gaussian signaling (IGS) as a means to improve the achievable rate. The problem of interest is designing of improper Gaussian signals' augmented covariance matrices to maximize the users' minimum rate subject to transmit power constraints. This problem is seen as a nonconvex matrix optimization problem, which cannot be solved by conventional techniques, such as weighted minimum mean square error minimization or alternating optimization. A path-following algorithm, which iterates a sequence of improved feasible points, is proposed for its computation. The provided simulation results for three cells serving 18 users show that IGS offers a much better max-min rate compared with that achieved by conventional proper Gaussian signaling. Another problem of maximizing the energy efficiency in IGS is also considered.

Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2019, 'UAV-Enabled Communication Using NOMA', IEEE Transactions on Communications, vol. 67, no. 7, pp. 5126-5138.
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© 2019 IEEE. Unmanned aerial vehicles (UAVs) can be deployed as flying base stations (BSs) to leverage the strength of line-of-sight connections and effectively support the coverage and throughput of wireless communication. This paper considers a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA). The max-min rate optimization problem is formulated under total power, total bandwidth, UAV altitude, and antenna beamwidth constraints. The objective of max-min rate optimization is non-convex in all optimization variables, i.e., UAV altitude, transmit antenna beamwidth, power allocation, and bandwidth allocation for multiple users. A path-following algorithm is proposed to solve the formulated problem. Next, orthogonal multiple access (OMA) and dirty paper coding (DPC)-based max-min rate optimization problems are formulated and respective path-following algorithms are developed to solve them. The numerical results show that NOMA outperforms OMA and achieves rates similar to those attained by DPC. In addition, a clear rate gain is observed by jointly optimizing all the parameters rather than optimizing a subset of parameters, which confirms the desirability of their joint optimization.

Nasir, AA, Tuan, HD, Nguyen, HH & Nguyen, NM 2019, 'Physical Layer Security by Exploiting Interference and Heterogeneous Signaling', IEEE Wireless Communications, vol. 26, no. 5, pp. 26-31.
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© 2002-2012 IEEE. Physical layer security (PLS) aims to protect end users who are equipped with low-complexity receivers for which implementing cryptographic algorithms for security purposes is not practical. This article presents a different approach to PLS and suggests natural and simple ways to achieve security in wireless networks. A practical assumption on the availability of channel state information (CSI) is considered for eavesdroppers (EVs) at the transmitter. Moreover, there is no restriction on EVs' placement, and as such EVs could be in better channel conditions when they are closer to the transmitter. The article describes how the interference channels can be exploited to simultaneously reduce the interference for the users' received signals and amplify the interference at the EV's received signal. It is also shown that when considering communication with energy-constrained nodes, the heterogeneous nature of the transmitted signals is an asset and can be exploited to confuse the eavesdropper. This is because information and energy signals are transmitted over different fractions of a time slot, and the EV can be confused since it does not know the time-fraction when information signal or energy signal is transmitted. Finally, the article also suggests how we can achieve secure information transmission under poor scattering environments, such as unmanned-aerial-vehicle-enabled communications.

Nathan, K, Ghosh, S, Siwakoti, Y & Long, T 2019, 'A New DC–DC Converter for Photovoltaic Systems: Coupled-Inductors Combined Cuk-SEPIC Converter', IEEE Transactions on Energy Conversion, vol. 34, no. 1, pp. 191-201.
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© 1986-2012 IEEE. An enhanced DC-DC converter is proposed in this paper, based on the combination of the Cuk and SEPIC converters, which is well-suited for solar photovoltaic (PV) applications. The converter uses only one switch (which is ground-referenced, so simple gate drive circuitry may be used), yet provides dual outputs in the form of a bipolar DC bus. The bipolar output from the DC-DC converter is able to send power to the grid via any inverter with a unipolar or bipolar DC input, and leakage currents can be eliminated if the latter type is used without using lossy DC capacitors in the load current loop. The proposed converter uses integrated magnetics cores to couple the input and output inductors, which significantly reduces the input current ripple and hence greatly improves the power extracted from the solar PV system. The design methodology along with simulation, experimental waveforms, and efficiency measurements of a 4-kW DC-DC converter are presented to prove the concept of the proposed converter. Furthermore, a 1-kW inverter is also developed to demonstrate the converter's grid-connection potential.

Nathan, KS, Ghosh, SS, Tripathi, PR, Siwakoti, YP, Flack, TJ, Li, X & Long, T 2019, 'Benefits of the CI‐CCS converter', The Journal of Engineering, vol. 2019, no. 17, pp. 4527-4531.
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Nguyen, CT, Hoang, DT, Nguyen, DN, Niyato, D, Nguyen, HT & Dutkiewicz, E 2019, 'Proof-of-Stake Consensus Mechanisms for Future Blockchain Networks: Fundamentals, Applications and Opportunities', IEEE Access, vol. 7, pp. 85727-85745.
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© 2013 IEEE. The rapid development of blockchain technology and their numerous emerging applications has received huge attention in recent years. The distributed consensus mechanism is the backbone of a blockchain network. It plays a key role in ensuring the network's security, integrity, and performance. Most current blockchain networks have been deploying the proof-of-work consensus mechanisms, in which the consensus is reached through intensive mining processes. However, this mechanism has several limitations, e.g., energy inefficiency, delay, and vulnerable to security threats. To overcome these problems, a new consensus mechanism has been developed recently, namely proof of stake, which enables to achieve the consensus via proving the stake ownership. This mechanism is expected to become a cutting-edge technology for future blockchain networks. This paper is dedicated to investigating proof-of-stake mechanisms, from fundamental knowledge to advanced proof-of-stake-based protocols along with performance analysis, e.g., energy consumption, delay, and security, as well as their promising applications, particularly in the field of Internet of Vehicles. The formation of stake pools and their effects on the network stake distribution are also analyzed and simulated. The results show that the ratio between the block reward and the total network stake has a significant impact on the decentralization of the network. Technical challenges and potential solutions are also discussed.

Nguyen, HT, Tuan, HD, Duong, TQ, Poor, HV & Hwang, W-J 2019, 'Collaborative Multicast Beamforming for Content Delivery by Cache-Enabled Ultra Dense Networks', IEEE Transactions on Communications, vol. 67, no. 5, pp. 3396-3406.
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© 1972-2012 IEEE. Caching and multicast have surged as effective tools to alleviate the heavy load from the backhaul links while enabling content-centric delivery in communication networks. The main focus of work in this area has been on the cache placements to manage the network delay and backhaul transmission cost. An important issue of optimizing the cost efficiency in content delivery has not been addressed. This paper tackles this issue by proposing collaborative multicast beamforming in cache-enabled ultra-dense networks. The objective is to maximize the cost efficiency, which is defined as the ratio of the content throughput to the sum of power consumption and backhaul cost, in providing quality-of-service for content delivery. Zero-forcing beamforming and generalized zero-forcing beamforming are employed to force the multi-content interference to zero or mitigate it while amplifying the desired signals for users. These problems of collaborative multicast beamforming design are computationally difficult. Path-following algorithms, which invoke a simple convex quadratic program at each iteration, are developed for their solution. Numerical results are provided to demonstrate the computational efficiency of the proposed algorithms and also give insights into the impact of caching on the cost efficiency.

Nguyen, LD, Tuan, HD, Duong, TQ & Poor, HV 2019, 'Multi-User Regularized Zero-Forcing Beamforming', IEEE Transactions on Signal Processing, vol. 67, no. 11, pp. 2839-2853.
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© 1991-2012 IEEE. Regularized zero-forcing beamforming (RZFB) is an interesting class of linear signal processing problems, which is very attractive for use in large-scale communication networks due its simple visualization as a straightforward extension of the well-accepted zero-forcing beamforming (ZFB). However, unlike ZFB, which is multi-user interference free, RZFB must manage multi-user interference to achieve its high throughput performance. Most existing works focus on the performance analysis of particular RZBF schemes such as the equip-power allocated RZBF under a fixed regularization parameter. This paper is the first work to consider the joint design of power allocation and regularization parameter for RZFB to maximize the worst users' throughput or the quality-of-service awarded energy efficiency under a fixed transmit power constraint. Such designs pose very computationally challenging optimization problems, for which the paper proposes two-stage optimization algorithms of low computational complexity. Their computational and performance efficiencies are substantiated through numerical examples.

Nguyen, M-N, Nguyen, LD, Duong, TQ & Tuan, HD 2019, 'Real-Time Optimal Resource Allocation for Embedded UAV Communication Systems', IEEE Wireless Communications Letters, vol. 8, no. 1, pp. 225-228.
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© 2012 IEEE. We consider device-to-device (D2D) wireless information and power transfer systems using an unmanned aerial vehicle (UAV) as a relay-assisted node. As the energy capacity and flight time of UAVs is limited, a significant issue in deploying UAV is to manage energy consumption in real-time application, which is proportional to the UAV transmit power. To tackle this important issue, we develop a real-time resource allocation algorithm for maximizing the energy efficiency by jointly optimizing the energy-harvesting time and power control for the considered (D2D) communication embedded with UAV. We demonstrate the effectiveness of the proposed algorithms as running time for solving them can be conducted in milliseconds.

Nguyen, TMC & Hoang, DB 2019, 'S-MANAGE protocol for provisioning IoT applications on demand', Journal of Telecommunications and the Digital Economy, vol. 7, no. 3, pp. 37-57.
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Internet of Things (IoT)-based services have started making an impact in various domains, such as agriculture, smart farming, smart cities, personal health, and critical infrastructures. Sensor/IoT devices have become one of the indispensable elements in these IoT systems and services. However, their development is restricted by the rigidity of the current network infrastructure, which accommodates heterogeneous physical devices. Software-Defined Networking-Network Functions Virtualization (SDN-NFV) has emerged as a service-enabling solution, supporting network and network function programmability. Provisioning IoT applications on demand is a natural application of programmability. However, these technologies cannot be directly deployed in the sensing/monitoring domain due to the differences in the functionality of SDN network devices and sensor/IoT devices, as well as the limitation of resources in IoT devices. This paper proposes an S-MANAGE protocol that preserves the SDN-NFV paradigm but provides a practical solution in controlling and managing IoT resources for provisioning IoT applications on demand. S-MANAGE is proposed as a new southbound protocol between the software-defined IoT controller and its IoT elements. The paper presents the design of S-MANAGE and demonstrates its use in provisioning IoT services dynamically.

Ni, W & Cassidy, MJ 2019, 'Cordon control with spatially-varying metering rates: A Reinforcement Learning approach', Transportation Research Part C: Emerging Technologies, vol. 98, pp. 358-369.
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Ni, W, Li, Y, Cai, L, Dong, C, Fang, H, Chen, Y, Li, H, Yao, M & Xiao, N 2019, 'SUMOylation is required for PIPK1γ‐driven keratinocyte migration and growth', The FEBS Journal, vol. 286, no. 23, pp. 4709-4720.
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PIPKIγ, a key member of the type I phosphatidylinositol 4‐phosphate kinase (PIPKI) family that regulates the spatial‐temporal generation of PIP2, has been implicated in diverse biological processes including cell survival, cell polarity, and cell migration. An essential role of PIPKIγ in tumor cells and nerve cells has been established in previous studies. However, the function and regulatory mechanism of PIPKIγ remains incompletely understood. Here, we showed that PIPKIγ can specifically associate with the SUMO‐conjugating (E2) enzyme UBC9 and can be SUMOylated both in vivo and in vitro. We further identified that Lys‐591 is the critical SUMO‐acceptor site of PIPKIγ and that SUMO conjugation at this site is required for PIPKIγ‐driven keratinocyte migration and growth. Mechanistically, SUMOylation deficiency significantly disrupts PIPKIγ‐mediated generation of intracellular PIP2, rather than the subcellular translocation and protein stability of PIPKIγ. Our findings reveal that PIPKIγ is a novel SUMOylation target and highlight the essential role of PIPKIγ SUMOylation in human keratinocyte function, providing an important orientation for in‐depth study of wound repair.

Nie, X, Wang, L, Ding, H & Xu, M 2019, 'Strawberry Verticillium Wilt Detection Network Based on Multi-Task Learning and Attention', IEEE Access, vol. 7, pp. 170003-170011.
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© 2013 IEEE. Plant disease detection has an inestimable effect on plant cultivation. Accurate detection of plant disease can control the spread of disease early and prevent unnecessary loss. Strawberry verticillium wilt is a soil-borne, multi-symptomatic disease. To detect strawberry verticillium wilt accurately, we first propose a disease detection network based on Faster R-CNN and multi-task learning to detect strawberry verticillium wilt. Then, the strawberry verticillium wilt detection network (SVWDN), which uses attention mechanisms in the feature extraction of the disease detection network, is proposed. SVWDN detects verticillium wilt according to the symptoms of detected plant components (i.e.,young leaves and petioles). Compared with other existing methods for detecting disease from the whole plant appearance, the SVWDN automatically classifies the petioles and young leaves while determining whether the strawberry has verticillium wilt. To provide a dataset for evaluating and testing our method, we construct a large dataset that contains 3, 531 images with 4 categories (Healthy-leaf, Healthy-petiole, Verticillium-leaf and Verticillium-petiole). Each image also has a label to indicate whether the strawberry is suffering from verticillium wilt. With the proposed strawberry verticillium wilt detection network, we achieved a mAP of 77.54% on object detection of 4 categories and 99.95% accuracy for strawberry verticillium wilt detection.

Nikolay, N, Mendelson, N, Sadzak, N, Böhm, F, Tran, TT, Sontheimer, B, Aharonovich, I & Benson, O 2019, 'Very Large and Reversible Stark-Shift Tuning of Single Emitters in Layered Hexagonal Boron Nitride', Physical Review Applied, vol. 11, no. 4.
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© 2019 American Physical Society. Combining solid-state single-photon emitters (SPEs) with nanophotonic platforms is a key goal in integrated quantum photonics. In order to realize functionality in potentially scalable elements, suitable SPEs have to be bright, stable, and widely tunable at room temperature. In this work, we show that selected SPEs embedded in a few-layer hexagonal boron nitride (h-BN) meet these demands. In order to show the wide tunability of these SPEs we employ an atomic force microscope (AFM) with a conductive tip to apply an electrostatic field to individual h-BN emitters sandwiched between the tip and an indium-tin-oxide-coated glass slide. A very large and reversible Stark shift of (5.5±0.3)nm at a zero-field wavelength of 670 nm is induced by applying just 20 V, which exceeds the typical resonance linewidths of nanodielectric and even nanoplasmonic resonators. Our results help to further understand the physical origin of SPEs in h-BN as well as for practical quantum photonic applications where wide spectral tuning and on/off resonance switching are required.

Nizami, MSH, Haque, ANMM, Nguyen, PH & Hossain, MJ 2019, 'On the application of Home Energy Management Systems for power grid support', Energy, vol. 188, pp. 116104-116104.
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© 2019 Elsevier Ltd Home Energy Management Systems (HEMSs) are being implemented for residential energy management in various parts of the world. Conventionally, a HEMS is developed from the consumer's perspective, with the principal aim of cost-saving while maintaining optimal consumers' comfort. In recent years, various Demand Response programs are being incorporated into HEMSs to address the power grid constraints. In this paper, the functionality of grid support through the HEMSs is presented. The developed scheme utilizes an agent-based coordination mechanism in an active distribution network and manages the household appliances to comply with thermal and voltage constraints of the grid. The proposed mechanism is evaluated through simulation of a typical Dutch low-voltage (LV) residential feeder. A hardware prototype has also been developed and tested in the laboratory environment. The proposed methodologies show promising perspectives for local voltage-violation support and direct load control for congestion management of the grid.

Parajuli, N, Sreenivasan, N, Bifulco, P, Cesarelli, M, Savino, S, Niola, V, Esposito, D, Hamilton, TJ, Naik, GR, Gunawardana, U & Gargiulo, GD 2019, 'Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation', Sensors, vol. 19, no. 20, pp. 4596-4596.
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Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each amputee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each individual is required for maximum utility across amputees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world (amputee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on amputees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on amputee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations.

Parvez Mahmud, MA, Hossain, MJ, Nizami, MSH, Rahman, MS, Farjana, SH, Huda, N & Lang, C 2019, 'Advanced power routing framework for optimal economic operation and control of solar photovoltaic‐based islanded microgrid', IET Smart Grid, vol. 2, no. 2, pp. 242-249.
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© 2019 Institution of Engineering and Technology. All rights reserved. Energy sharing through a microgrid (MG) is essential for islanded communities to maximise the use of distributed energy resources (DERs) and battery energy storage systems (BESSs). Proper energy management and control strategies of such MGs can offer revenue to prosumers (active consumers with DERs) by routing excess energy to their neighbours and maintaining grid constraints at the same time. This paper proposes an advanced power-routing framework for a solarphotovoltaic (PV)-based islanded MG with a central storage system (CSS). An optimisation-based economic operation for the MG is developed that determines the power routing and energy sharing in the MG in the day-ahead stage. A modified droop controller-based real-time control strategy has been established that maintains the voltage constraints of the MG. The proposed power-routing framework is verified via a case study for a typical islanded MG. The outcome of the optimal economic operation and a controller verification of the proposed framework are presented to demonstrate the effectiveness of the proposed powerrouting framework. Results reveal that the proposed framework performs a stable control operation and provides a profit of 57 AU$/day at optimal conditions.

Pou, J, Perez, MA & Aguilera, RP 2019, 'Modular Multilevel Converters', IEEE Transactions on Industrial Electronics, vol. 66, no. 3, pp. 2204-2206.
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Puthal, D, Ranjan, R, Nanda, A, Nanda, P, Jayaraman, PP & Zomaya, AY 2019, 'Secure authentication and load balancing of distributed edge datacenters', Journal of Parallel and Distributed Computing, vol. 124, pp. 60-69.
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© 2018 Edge computing is an emerging research area to incorporate cloud computing into edge network devices. An Edge datacenter, also referred to as EDC, processes data streams and user requests in real-time and is therefore used to decrease the latency and congestion in the network. EDC is usually setup as a distributed system and is accordingly placed between the cloud datacenter and the data source. These EDCs work as an intermediate layer in the fog hierarchy between IoT and Cloud datacenter. EDC's are aided by load balancers, responsible for distributing the workload amongst multiple EDC, in order to optimize resource utilization and response time. The load balancers make sure that the workload is equally divided amongst the available EDCs to avoid over loading of some EDCs while other remain idle as this directly impacts the user response and real-time event detection. Given the fact that EDCs are deployed in remote environments, the need for secure authentication is of major importance. In this paper we propose a novel load balancing technique that enables EDC authentication as well as identification of idle EDCs for better load balancing. The proposed load balancing technique is also compared with existing approaches and proves to be more efficient in locating EDC's with less workload. In addition to the improved efficiency, the proposed scheme also strengthens the security of the network by incorporating destination EDC authentication.

Qin, C, Ni, W, Tian, H, Lu, L & Liu, RP 2019, 'Radio over Cloud (RoC): Cloud-Assisted Distributed Beamforming for Multi-Class Traffic', IEEE Transactions on Mobile Computing, vol. 18, no. 6, pp. 1368-1379.
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IEEE Cloud has yet to be applied to computationally intensive radio signal processing, due to closely coupled computing tasks resulting from interference. This paper presents a new cloud-assisted joint beamforming architecture, where computations are decoupled for individual wireless users and pipelined for cloud execution, using Difference of Convex (DC), l1-norm approximations, and dual decompositions. User-specific tasks are constructed and aligned with the cloud to leverage computation reuses and minimize overhead. The time-complexity is dramatically improved to support networks with tens to hundreds of base stations and users, without compromising the sum rate and quality-of-service. Further, the superiority of DC to the state-of-the-art Weighted Minimum Mean Square Error (WMMSE) in terms of convex relaxation is observed and discussed. Corroborated by simulations, the reason is revealed as WMMSE aggressively increases the data rate at interim stages, hence adversely interacting with l1-norm approximation and reducing the feasible solution regions at later stages.

Qin, P-Y, Song, L-Z & Guo, YJ 2019, 'Beam Steering Conformal Transmitarray Employing Ultra-Thin Triple-Layer Slot Elements', IEEE Transactions on Antennas and Propagation, vol. 67, no. 8, pp. 5390-5398.
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© 1963-2012 IEEE. A novel conformal transmitarray with beam steering ability is presented. First, an ultra-thin transmitarray element consisting of three layers of identical square ring slots is developed. The element has a thickness of 0.508 mm (0.04 wavelength in the free space at 25 GHz), achieving a transmission phase range of 330° with a maximum 3.6 dB loss. The element is then applied to a curved transmitarray conformal to a cylindrical surface fed by a standard gain horn with about a 10-dBi gain. A prototype is fabricated radiating a boresight beam with a peak measured gain of 19.6 dBi and an aperture efficiency of 25.1%. Second, when the transmitting surface of the above array is divided into two parts from the middle with different main beam directions, the combined beam can be radiated to an oblique angle with respect to the boresight direction. Using this method, a mechanical beam scanning conformal transmitarray antenna is designed. Its size is about 2.5 times larger than the fixed-beam one and consists of six transmitting surfaces with main beams directed to different angles. By rotating the feed horn to different positions, the main beam of the array can be switched to ±15°, ±10°, ±5°, and 0°. A prototype is fabricated with a stable gain of about 18.7 dBi at all beam angles.

Rahman, MA, Islam, MR, Muttaqi, KM, Guo, Y, Zhu, J, Sutanto, D & Lei, G 2019, 'A Modified Carrier-Based Advanced Modulation Technique for Improved Switching Performance of Magnetic-Linked Medium-Voltage Converters', IEEE Transactions on Industry Applications, vol. 55, no. 2, pp. 2088-2098.
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© 1972-2012 IEEE. The high-frequency magnetic link is gaining popularity due to its lightweight, small volume, and inherent voltage balancing capability. Those features can simplify the utilization of a multilevel converter (MLC) for the integration of renewable energy sources to the grid with compact size and exert economic feasibility. The modulation and control of the MLC are crucial issues, especially for grid-connected applications. To support the grid, the converter may need to operate in an overmodulation (OVM) region for short periods depending upon the loading conditions. This OVM operation of the converter causes increased harmonic losses and adverse effects on the overall system efficiency. On top of that, the size and cost of filtering circuitry become critical to eliminate the unwanted harmonics. In this regard, a modified OVM scheme with phase-disposed carriers for a grid-connected high-frequency magnetic-link-based cascaded H-bridge (CHB) MLC is proposed for the suppression of harmonics and the reduction of converter loss. Furthermore, with the proposed OVM technique, the voltage gain with the modulation index can be increased up to the range which is unlikely to be achieved using the classical ones. Extensive simulations are carried out with a 2.24 MVA permanent magnet synchronous generator based wind energy conversion system, which is connected to the 11 kV ac grid through a high-frequency magnetic-link and a five-level CHB MLC. A scaled down laboratory prototype is implemented to validate the performance of the converter.

Rajabi, A, Eskandari, M, Jabbari Ghadi, M, Ghavidel, S, Li, L, Zhang, J & Siano, P 2019, 'A pattern recognition methodology for analyzing residential customers load data and targeting demand response applications', Energy and Buildings, vol. 203, pp. 109455-109455.
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© 2019 Elsevier B.V. The availability of smart meter data allows defining innovative applications such as demand response (DR) programs for households. However, the dimensionality of data imposes challenges for the data mining of load patterns. In addition, the inherent variability of residential consumption patterns is a major problem for deciding on the characteristic consumption patterns and implementing proper DR settlements. In this regard, this paper utilizes a data size reduction and clustering methodology to analyze residential consumption behavior. Firstly, the distinctive time periods of household activity during the day are identified. Then, using these time periods, a modified symbolic aggregate approximation (SAX) technique is utilized to transform the load patterns into symbolic representations. In the next step, by applying a clustering method, the major consumption patterns are extracted and analyzed. Finally, the customers are ranked based on their stability over time. The proposed approach is applied on a large dataset of residential customers’ smart meter data and can achieve three main goals: 1) it reduces the dimensionality of data by utilizing the data size reduction, 2) it alleviates the problems associated with the clustering of residential customers, 3) its results are in accordance with the needs of systems operators or demand response aggregators and can be used for demand response targeting. The paper also provides a thorough analysis of different aspects of residential electricity consumption and various approaches to the clustering of households which can inform industry and research activity to optimize smart meter operational use.

Rao, T, Li, X, Zhang, H & Xu, M 2019, 'Multi-level region-based Convolutional Neural Network for image emotion classification', Neurocomputing, vol. 333, pp. 429-439.
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© 2018 Analyzing emotional information of visual content has attracted growing attention for the tendency of internet users to share their feelings via images and videos online. In this paper, we investigate the problem of affective image analysis, which is very challenging due to its complexity and subjectivity. Previous research reveals that image emotion is related to low-level to high-level visual features from both global and local view, while most of the current approaches only focus on improving emotion recognition performance based on single-level visual features from a global view. Aiming to utilize different levels of visual features from both global and local view, we propose a multi-level region-based Convolutional Neural Network (CNN) framework to discover the sentimental response of local regions. We first employ Feature Pyramid Network (FPN) to extract multi-level deep representations. Then, an emotional region proposal method is used to generate proper local regions and remove excessive non-emotional regions for image emotion classification. Finally, to deal with the subjectivity in emotional labels, we propose a multi-task loss function to take the probabilities of images belonging to different emotion classes into consideration. Extensive experiments show that our method outperforms the state-of-the-art approaches on various commonly used benchmark datasets.

Ren, C, Lyu, X, Ni, W, Tian, H & Liu, RP 2019, 'Distributed Online Learning of Fog Computing Under Nonuniform Device Cardinality', IEEE Internet of Things Journal, vol. 6, no. 1, pp. 1147-1159.
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© 2014 IEEE. Processing data around the point of capture, fog computing can support computationally demanding Internet-of-Things (IoT) services. Distributed online optimization is important given the size of IoT, but challenging due to time variations of random traffic and nonuniform connectivity (or cardinality) of edge servers and IoT devices. This paper presents a distributed online learning approach to asymptotically minimizing the time-average cost of fog computing in the absence of the a-priori knowledge on traffic randomness, for light-weight, and delay-tolerant application scenarios. Stochastic gradient descent is exploited to decouple the optimizations between time slots. A graph matching problem is then formulated for every time slot by decoupling and unifying the nonuniform cardinalities, and solved in a distributed manner by developing a new linear (1/2)-approximation method. We prove that the optimality loss resulting from the distributed approximate graph matching method can be compensated and diminish by increasing the learning time. Corroborated by simulations, the proposed distributed online learning is asymptotically optimal and superior to the state of the art in terms of throughput and energy efficiency.

Ren, C, Lyu, X, Ni, W, Tian, H & Liu, RP 2019, 'Profitable Cooperative Region for Distributed Online Edge Caching', IEEE Transactions on Communications, vol. 67, no. 7, pp. 4696-4708.
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© 2019 IEEE. Cooperative caching can unify network storage to improve efficiency, but the effective placement and search of contents are challenging especially in distributed edge clouds with neither a-priori knowledge on content requests nor instantaneous global view. This paper establishes a new profitable cooperative region for every content request admitted at an edge server, within which the content, if cached, can be retrieved with guaranteed profit against a direct retrieval from the network backbone. This narrows down the search for the content. The caching density of the content can also be significantly reduced, e.g., to a cached copy per region. The regions are based on a novel distributed framework which allows individual servers to spontaneously admit/dispatch requests and deliver/forward contents, while asymptotically maximizing the time-average profit of caching. The cooperative region for content is erected at individual servers by comparing the upper and lower bounds for the backlogs of unsatisfied requests of the content. Simulations show the substantially improved profit of the proposed approach over existing solutions. The regions can help automate the placement of contents with reduced density and improved efficiency.

Roselin, AG, Nanda, P, Nepal, S, He, X & Wright, J 2019, 'Exploiting the Remote Server Access Support of CoAP Protocol', IEEE Internet of Things Journal, vol. 6, no. 6, pp. 9338-9349.
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© 2014 IEEE. The constrained application protocol (CoAP) is a specially designed Web transfer protocol for use with constrained nodes and low-power networks. The widely available CoAP implementations have failed to validate the remote CoAP clients. Each CoAP client generates a random source port number when communicating with the CoAP server. However, we observe that in such implementations it is difficult to distinguish the regular packet and the malicious packet, opening a door for a potential off-path attack. The off-path attack is considered a weak attack on a constrained network and has received a less attention from the research community. However, the consequences resulting from such an attack cannot be ignored in practice. In this article, we exploit the combination of IP spoofing vulnerability and the remote server access support of CoAP is to be launch an off-path attack. The attacker injects a fake request message to change the credentials of the 6LoWPAN smart door keypad lock system. This creates a request spoofing vulnerability in CoAP, and the attacker exploits this vulnerability to gain full access to the system. Through our implementation, we demonstrated the feasibility of the attack scenario on the 6LoWPAN-CoAP network using smart door keypad lock. We proposed a machine learning (ML)-based approach to mitigate such attacks. To the best of our knowledge, we believe that this is the first article to analyze the remote CoAP server access support and request spoofing vulnerability of CoAP to launch an off-path attack and demonstrate how an ML-based approach can be deployed to prevent such attacks.

Salah, AA, Dorrell, DG & Guo, Y 2019, 'A Review of the Monitoring and Damping Unbalanced Magnetic Pull in Induction Machines Due to Rotor Eccentricity', IEEE Transactions on Industry Applications, vol. 55, no. 3, pp. 2569-2580.
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Samal, PB, Soh, PJ & Zakaria, Z 2019, 'Compact Microstrip-Based Textile Antenna for 802.15.6 WBAN-UWB with Full Ground Plane', International Journal of Antennas and Propagation, vol. 2019, pp. 1-12.
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The paper presents the design and investigation of a flexible all-textile antenna operating in the wireless body area network (WBAN) ultrawideband (UWB) specified by the IEEE 802.15.6 standard. The proposed antenna features an innovative and compact UWB radiator on top of the overall structure with a full ground plane on its reverse side. The radiator, which is based on a microstrip patch combined with multiple miniaturization and broadbanding methods, resulted in a simple topology and a compact size of 39 mm×42 mm×3.34 mm (0.51×0.55×0.043λ). In comparison to the literature, the proposed structure is considered to be the most compact microstrip-based textile UWB antenna to date featuring a full ground plane. The choice of the commercial textiles is also made based on cost efficiency, ease of accessibility, and ease of fabrication using simple tools. Meanwhile, the full ground plane enables the antenna operation in the vicinity of the human body with minimal body coupling and radiation towards it, ensuring operational safety. Besides its operation in the mandatory channels of the WBAN-UWB low and high bands, the proposed antenna also operates and preserves its performance in five other optional channels of the high band when placed on the body and under bend conditions of 30° and 60°. The proposed antenna successfully achieved the specific absorption rate below the regulated limit specified by the Federal Communications Commission.

Sang, L, Xu, M, Qian, S & Wu, X 2019, 'Multi-modal multi-view Bayesian semantic embedding for community question answering', Neurocomputing, vol. 334, pp. 44-58.
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© 2018 Semantic embedding has demonstrated its value in latent representation learning of data, and can be effectively adopted for many applications. However, it is difficult to propose a joint learning framework for semantic embedding in Community Question Answer (CQA), because CQA data have multi-view and sparse properties. In this paper, we propose a generic Multi-modal Multi-view Semantic Embedding (MMSE) framework via a Bayesian model for question answering. Compared with existing semantic learning methods, the proposed model mainly has two advantages: (1) To deal with the multi-view property, we utilize the Gaussian topic model to learn semantic embedding from both local view and global view. (2) To deal with the sparse property of question answer pairs in CQA, social structure information is incorporated to enhance the quality of general text content semantic embedding from other answers by using the shared topic distribution to model the relationship between these two modalities (user relationship and text content). We evaluate our model for question answering and expert finding task, and the experimental results on two real-world datasets show the effectiveness of our MMSE model for semantic embedding learning.

Sarker, PC, Islam, MR, Guo, Y, Zhu, J & Lu, HY 2019, 'State-of-the-Art Technologies for Development of High Frequency Transformers with Advanced Magnetic Materials', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-11.
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© 2002-2011 IEEE. With the development of advanced soft magnetic materials of high-saturation flux density and low specific core loss and semiconductor power devices, the high-frequency transformer (HFT) has received significant attention in recent years for its widespread emerging applications. The optimal design of high-power-density HFTs for high-performance energy conversion systems is, however, a multiphasic problem that needs special considerations on various aspects such as core material selection, minimization of parasitic components, and thermal management. This paper presents a comprehensive review on advancement of soft magnetic materials for high-power-density magnetic devices and advanced technologies for characterizations and optimal design of HFTs. The future research and development trends are also discussed.

Seifollahi, S, Bagirov, A, Zare Borzeshi, E & Piccardi, M 2019, 'A simulated annealing‐based maximum‐margin clustering algorithm', Computational Intelligence, vol. 35, no. 1, pp. 23-41.
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AbstractMaximum‐margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing‐based algorithm that is able to mitigate the issue of local minima in the maximum‐margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k‐means++ and SVM at each step of the annealing process. More precisely, k‐means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.

Shahid, I, Thalakotuna, D & Heimlich, M 2019, 'A bi-patch loaded microstrip line based 1-D periodic structure with enhanced stop bandwidth and band switching characteristics', Journal of Electromagnetic Waves and Applications, vol. 33, no. 10, pp. 1329-1342.
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A one-dimensional periodic structure comprising of eight unit cells each having two metallic patches sandwiched between microstrip line and ground plane has been investigated. Patches bearing dissimilar dimensions present distinct reactive loads, determined by their respective areas, to generate relatively wider bandgap. Patches can be selectively connected to ground or left floating through a combination of vias and externally controlled FET switches. Dispersion analysis of the structure has been carried out to determine the propagating modes of the line for all four possible states of the unit cell. A top-down, design guide approach has been adopted with the effect of parameters determining performance attributes captured. The proposed structure acts as an all pass filter from DC to 19.5 GHz with all patches floating and exhibits stopband characteristics from 6 to 19.5 GHz with different combinations of the switches offering an overall stop bandwidth greater than 100%. The proposed structure offers tunability from no bandgap to bandgap with added advantages of band switching capability with double the number of unique reconfigurable switch patterns as compared to conventional single patch structures.

Shashidharan, S, Zhu, F & Yang, Y 2019, 'Coupling of supermodes in dual-core mPOF and its application in temperature and strain sensing', Optik, vol. 195, pp. 163112-163112.
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© 2019 Elsevier GmbH This paper shows a novel dual core microstructured polymer fiber made of poly-methyl-methacrylate (PMMA) with an external diameter of 128 μm. The two solid fiber cores of diameter 4 μm were made of polycarbonate separated by a single air hole of 1 μm diameter at the center of the structure. The cutoff wavelength of each core was designed to be 600 nm. A very minute change in the shape/position of cores or air hole diameter 0.5 microns will result a change in the coupling length between the cores. Mode coupling in dual-core mPOF for y- and x- polarization were examined using effective index of propagating modes. The effect of temperature and strain to the mPOF causes the transmittance nulls to either red shift or blue shift. The numerical calculation from the shifts in transmission nulls shows a sensitivity up to 1.3 nm N/ m2 in the wavelength range of 600-850nm

Shashidharan, S, Zhu, F & Yang, Y 2019, 'Microstructured Multicore Polymer Optical Fiber Temperature-insensitive Stress Sensor', Optik, vol. 186, pp. 458-463.
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© 2018 We describe a novel microstructured multicore polymer optical fiber (m-MPOF) made of PMMA with air-holes running along the entire length of the fiber. In polymer, refractive index decreases with increasing temperature, a negative thermo-optic coefficient which results in the increase of coupling with increasing temperature thus reducing the beat length and causing a blue shift in transmission nulls, but with increase in temperature the spacing between cores will also increase which results in decreases of coupling and an increases the beat length, so a red shift in transmission nulls –a positive thermal expansion coefficient. In most part of the wavelength the thermo-optic effect dominates the thermal expansion effect, but at a particular wavelength both the effects cancel each other and have a zero change in the Neff with a change in temperature. So, as a result, both these effects get nullified at certain temperature making it a temperature insensitive fiber. Numerical calculations show the fiber is temperature insensitive for a range of 40℃ to 60℃ at a wavelength of 700 nm. The fiber is shown to be sensitive to stress at 700 nm with a sensitivity of 1.6 nm/Pa, which makes the said fiber temperature insensitive stress sensor.

Shen, W, Wu, Y, Yuan, J, Duan, L, Zhang, J & Jia, Y 2019, 'Robust Distracter-Resistive Tracker via Learning a Multi-Component Discriminative Dictionary', IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 7, pp. 2012-2028.
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IEEE Discriminative dictionary learning (DDL) provides an appealing paradigm for appearance modeling in visual tracking. However, most existing DDL based trackers cannot handle drastic appearance changes, especially for scenarios with background cluster and/or similar object interference. One reason is that they often suffer from the loss of subtle visual information which is critical to distinguish an object from distracters. In this paper, we explore the use of deep features extracted from the Convolutional Neural Networks (CNNs) to improve the object representation and propose a robust distracter-resistive tracker via learning a multi-component discriminative dictionary. The proposed method exploits both the intra-class and the interclass visual information to learn shared atoms and the classspecific atoms. By imposing several constraints into the objective function, the learned dictionary is reconstructive, compressive and discriminative, thus can better distinguish an object from the background. In addition, our convolutional features (deep features extracted from CNNs) have structural information for object localization and balance the discriminative power and semantic information of the object. Tracking is carried out within a Bayesian inference framework where a joint decision measure is used to construct the observation model. To alleviate the drift problem, the reliable tracking results obtained online are accumulated to update the dictionary. Both the qualitative and quantitative results on the CVPR2013 benchmark, the VOT2015 dataset and the SPOT dataset demonstrate that our tracker achieves better performance over the state-of-the-art approaches.

Shi, X, Zhu, J, Li, L, Lu, DD-C, Zhang, J & Yang, H 2019, 'Predictive Duty Cycle Control With Reversible Vector Selection for Three-Phase AC/DC Converters', IEEE Transactions on Power Electronics, vol. 34, no. 5, pp. 4868-4882.
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© 2018 IEEE. The conventional predictive duty cycle control (CPDCC) of three-phase full-bridge ac/dc converters selects adjacent nonzero vector pair based on the grid-voltage vector location, then the duration for each vector is calculated. Though the vector selection method is quite simple, it has a significant disadvantage that the values of calculated durations could be frequently less than zero due to nonoptimal vector selection, which results in high current harmonics and power notches. It could be improved with improved predictive duty cycle control (IPDCC) by reselecting the nonzero vector pair when negative duration exists; however, the whole vector selection and calculation procedure are repeated. By theoretical verification that the power variation rates of reversible vector pair are symmetrical with respect to that of zero vector, this paper proposes the reversible predictive duty cycle control (RPDCC) simply by replacing the original vector with its opposite vector and the recalculation of vector duration is eliminated compared with IPDCC. Thus, the calculation effort is almost not increased compared with CPDCC while system performance is significantly improved. The proposed control is theoretically derived and verified with the simulation and experimental results showing that RPDCC has better steady and dynamic performance than CPDCC and IPDCC methods.

Shi, Z, Sun, X, Cai, Y, Yang, Z, Lei, G, Guo, Y & Zhu, J 2019, 'Torque Analysis and Dynamic Performance Improvement of a PMSM for EVs by Skew Angle Optimization', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-5.
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© 2018 IEEE. In this paper, a permanent magnet synchronous machine (PMSM) for electric vehicles (EVs) is studied. Since EVs need to face some low speed road conditions, it is necessary to drive the machine to maintain a stable torque at low speed. The stator skew slot is often adopted to reduce torque ripple; however, it declines the output torque at same time. Besides, the difference between positive rotation performance and negative rotation performance, which caused by the skew slot are often ignored. Through the finite element analysis, the cogging torque and dynamic performance of the PMSM at different skew angle are studied. Moreover, the different influence of slot skew angle on positive and negative rotation performance is studied. Then, the optimum skew angle of the PMSM is studied through comprehensive consideration. Finally, the cogging torque of the prototype is verified to be less than 2 N·m through the experiment.

Siddiqi, MWU, Fedeli, P, Tu, C, Frangi, A & Lee, JE-Y 2019, 'Numerical analysis of anchor loss and thermoelastic damping in piezoelectric AlN-on-Si Lamb wave resonators', Journal of Micromechanics and Microengineering, vol. 29, no. 10, pp. 105013-105013.
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Silwal, S, Taghizadeh, S, Karimi-Ghartemani, M, Hossain, MJ & Davari, M 2019, 'An Enhanced Control System for Single-Phase Inverters Interfaced With Weak and Distorted Grids', IEEE Transactions on Power Electronics, vol. 34, no. 12, pp. 12538-12551.
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© 2019 IEEE. This paper presents an enhanced current controller for improving the performance of a class of single-phase grid-connected inverters operating in weak and distorted grid conditions. An inverter designed to operate at normal (strong or stiff and clean) grid conditions may not perform satisfactorily during weak and distorted grid conditions. One major reason is the interfering dynamics of the synchronization or phase-locked loop (PLL). This paper proposes an enhanced control structure for a popular class of single-phase inverters to address this problem. The proposed idea is to include the PLL state variables into the main inverter controller thereby minimizing the undesirable interactions of the PLL with the other components. A method for optimally designing the controller gains is also proposed. Compared to the conventional one, the proposed controller is shown to have a more robust performance over a substantially wider range of weak and distorted grid conditions. Extensive simulation and experimental results are presented to validate the proposed controls.

Singh, RK, Xu, Y, Wang, R, Hamilton, TJ, Denham, SL & van Schaik, A 2019, 'CAR-Lite: A Multi-Rate Cochlear Model on FPGA for Spike-Based Sound Encoding', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, no. 5, pp. 1805-1817.
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© 2018 IEEE. Filters in cochlear models use different coefficients to break sound into a 2-D time-frequency representation. On digital hardware with a single sampling rate, the number of bits required to represent these coefficients requires substantial computational resources such as memory storage. In this paper, we present a cochlear model operating at multiple sampling rates. As a result, fewer bits are required to represent filter coefficients on hardware as opposed to all the filters operating at a single sampling rate; with a 108-filter cochlear implementation, up to nine times fewer coefficients are needed. We present an implementation of this model in Matlab and on an Altera Cyclone V field-programmable gate array. We also demonstrate the capability of our model to encode sound at various intensity levels and with real-world signals.

Siwakoti, YP, Mahajan, A, Rogers, DJ & Blaabjerg, F 2019, 'A Novel Seven-Level Active Neutral-Point-Clamped Converter With Reduced Active Switching Devices and DC-Link Voltage', IEEE Transactions on Power Electronics, vol. 34, no. 11, pp. 10492-10508.
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© 1986-2012 IEEE. This paper presents a novel seven-level inverter topology for medium-voltage high-power applications. It consists of eight active switches and two inner flying capacitor (FC) units forming a similar structure as in a conventional active neutral-point-clamped (ANPC) inverter. This unique arrangement reduces the number of active and passive components. A simple modulation technique reduces cost and complexity in the control system design without compromising reactive power capability. In addition, compared to major conventional seven-level inverter topologies, such as the neutral point clamped, FC, cascaded H-bridge, and ANPC topologies, the new topology reduces the dc-link voltage requirement by 50%. This recued dc-link voltage makes the new topology appealing for various industrial applications. Experimental results from a 2.2-kVA prototype are presented to support the theoretical analysis presented in this paper. The prototype demonstrates a conversion efficiency of around 97.2% ± 1% for a wide load range.

Siwakoti, YP, Mostaan, A, Abdelhakim, A, Davari, P, Soltani, MN, Khan, MNH, Li, L & Blaabjerg, F 2019, 'High-Voltage Gain Quasi-SEPIC DC–DC Converter', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 2, pp. 1243-1257.
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© 2013 IEEE. This paper proposes a modified coupled-inductor SEPIC dc-dc converter for high-voltage-gain (2< G< 10) applications. It utilizes the same components as the conventional SEPIC converter with an additional diode. The voltage stress on the switch is minimal, which helps the designer to select a low-voltage and low R{mathrm {DS}-mathrm{scriptscriptstyle ON}} MOSFET, resulting in a reduction of cost, conduction, and turn ON losses of the switch. Compared to equivalent topologies with similar voltage-gain expression, the proposed topology uses lower component count to achieve the same or even higher voltage gain. This helps to design a very compact and lightweight converter with higher power density and reliability. Operating performance, steady-state analysis and mathematical derivations of the proposed dc-dc converter have been demonstrated in this paper. Moreover, extension of the circuit for higher gain (G>10) application is also introduced and discussed. Finally, the main features of the proposed converter have been verified through simulation and experimental results of a 400-W laboratory prototype. The efficiency is almost flat over a wide range of load with the highest measured efficiency of 96.2%, and the full-load efficiency is 95.2% at a voltage gain of 10.

Smith, MR, Chai, R, Nguyen, HT, Marcora, SM & Coutts, AJ 2019, 'Comparing the Effects of Three Cognitive Tasks on Indicators of Mental Fatigue', The Journal of Psychology, vol. 153, no. 8, pp. 759-783.
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© 2019, © 2019 Taylor & Francis Group, LLC. This investigation assessed the impact of three cognitively demanding tasks on cognitive performance, subjective, and physiological indicators of mental fatigue. Following familiarization, participants completed four testing sessions, separated by 48 h. During each session, participants watched a 45-min emotionally neutral documentary (control) or completed one of the following computer tasks: Psychomotor Vigilance Task (PVT); AX-Continuous Performance Test (AX-CPT); or Stroop Task. Mental fatigue was assessed before and at regular periods for 60 min following the 45-min treatments. Cognitive performance was assessed using 3-min PVT, and task performance. Subjective assessments were conducted using the Brunel Mood Scale, and visual analog scales (VAS). Physiological indicators of mental fatigue included electroencephalography (EEG), and heart rate variability (HRV). Subjective ratings of mental fatigue increased from pre to 0-min post in all-treatments, but not the documentary (p < 0.05). Subjective fatigue (VAS) remained higher (p < 0.05) than pretreatment values for 20-, 50-, and 60-min following the PVT, Stroop, and AX-CPT respectively. The cognitively demanding tasks had unclear effects on 3-min PVT, EEG, and HRV assessments. Tasks requiring response inhibition appear to induce fatigue for longer durations than a simple vigilance task. Simple VAS appear to be the most practical method for assessing mental fatigue.

Stewart, C, Kianinia, M, Previdi, R, Tran, TT, Aharonovich, I & Bradac, C 2019, 'Quantum emission from localized defects in zinc sulfide', Optics Letters, vol. 44, no. 19, pp. 4873-4873.
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© 2019 Optical Society of America Single-photon sources in solid-state systems are widely explored as fundamental constituents of numerous quantum-based technologies. We report the observation of single-photon emitters in zinc sulfide and present their photo-physical properties via established spectroscopy techniques. The emitter behaves like a three-level system with an intermediate metastable state. It emits at ∼640 nm, and its emission is linearly polarized, with a lifetime of (2.2 ± 0.8) ns. The existence of single-photon sources in zinc sulfide is appealing due to the well-established manufacturing techniques of the material, its versatile technological uses, as well as the availability of many zinc isotopes with potential for designing ad hoc emitter–host pairs with tailored properties.

Subasinghage, K, Gunawardane, K, Kularatna, N & Lie, TT 2019, 'Extending the Supercapacitor-Assisted Low-Dropout Regulator (SCALDO) Technique to a Split-Rail DC–DC Converter Application', IEEE Access, vol. 7, pp. 124034-124047.
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Sun, F, Zhu, H, Zhu, X, Yang, Y & Gomez-Garcia, R 2019, 'Design of On-Chip Millimeter-Wave Bandpass Filters Using Multilayer Patterned-Ground Element in 0.13-$\mu$ m (Bi)-CMOS Technology', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 12, pp. 5159-5170.
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© 1963-2012 IEEE. A novel design methodology for transmission-zero (TZ) generation in on-chip millimeter-wave (mm-wave) bandpass filters (BPFs) based on the original concept of multilayer patterned-ground (MPG) element is presented in this article. Unlike most of prior-art techniques available in the technical literature, this method has two distinct features. First, it is inherently suitable for miniaturized BPF design since the MPG element can be implemented through the layers below the top-metal layer and, thus, without occupying any additional die/chip area. Second, it provides a simple but effective way to produce a TZ at the upper stopband without adversely affecting other BPF performance metrics. To fully understand the operational insight of the engineered approach, a simplified LC-equivalent behavioral circuit model for the MPG element is developed. Using this model, three second-order BPFs based on different circuit configurations are codesigned to further demonstrate the experimental feasibility of the technique. All the filter prototypes are fabricated in a standard 0.13-μ m bipolar complementary metal-oxide-semiconductor [(Bi)-CMOS] technology. The obtained on-wafer measurements show that all fabricated BPF chips have the capability to suppress the second-order harmonic by more than 30 dB, which indicates the effectiveness of the proposed integrated BPF design approach with the MPG element.

Sun, F, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Zhang, X 2019, 'Design of Millimeter-Wave Bandpass Filters With Broad Bandwidth in Si-Based Technology', IEEE Transactions on Electron Devices, vol. 66, no. 3, pp. 1174-1181.
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© 2019 IEEE. In this paper, a novel design approach is proposed for on-chip bandpass filter (BPF) design with improved passband flatness and stopband suppression. The proposed approach simply uses a combination of meander-line structures with metal-insulator-metal (MIM) capacitors. To demonstrate the insight of this approach, a simplified equivalent LC-circuit model is used for theoretical analysis. Using the analyzed results as a guideline along with a full-wave electromagnetic (EM) simulator, two BPFs are designed and implemented in a standard 0.13-μm (Bi)-CMOS technology. The measured results show that good agreements between EM simulated and measured results are achieved. For the first BPF, the return loss is better than 10 dB from 13.5 to 32 GHz, which indicates a fractional bandwidth (FBW) of more than 78%. In addition, the minimum insertion loss of 2.3 dB is achieved within the frequency range from 17 to 27 GHz and the in-band magnitude ripple is less than 0.1 dB. The chip size of this design, excluding the pads, is 0.148 mm 2 . To demonstrate a miniaturized design, a second design example is given. The return loss is better than 10 dB from 17.3 to 35.9 GHz, which indicates an FBW of more than 70%. In addition, the minimum insertion loss of 2.6 dB is achieved within the frequency range from 21.4 to 27.7 GHz and the in-band magnitude ripple is less than 0.1 dB. The chip size of the second design, excluding the pads, is only 0.066 mm 2 .

Sun, H-H, Ding, C, Zhu, H, Jones, B & Guo, YJ 2019, 'Suppression of Cross-Band Scattering in Multiband Antenna Arrays', IEEE Transactions on Antennas and Propagation, vol. 67, no. 4, pp. 2379-2389.
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© 1963-2012 IEEE. This paper presents a novel method of suppressing cross-band scattering in dual-band dual-polarized antenna arrays. The method involves introducing chokes into low-band (LB) elements to suppress high-band (HB) scattering currents. The experimental results show that by inserting LB-pass HB-stop chokes into LB radiators, suppression of induced HB currents on the LB elements is achieved. This greatly reduces the pattern distortion of the HB array caused by the presence of LB elements. The array considered is configured as two columns of HB antennas operating from 1.71 to 2.28 GHz interleaved with a single column of LB antennas operating from 0.82 to 1.0 GHz. The realized array with choked LB element has stable and symmetrical radiation in both HB and LB.

Sun, X, Diao, K, Lei, G, Guo, Y & Zhu, J 2019, 'Study on Segmented-Rotor Switched Reluctance Motors With Different Rotor Pole Numbers for BSG System of Hybrid Electric Vehicles', IEEE Transactions on Vehicular Technology, vol. 68, no. 6, pp. 5537-5547.
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© 1967-2012 IEEE. This paper investigates the design principles and performance optimization for segmented-rotor switched reluctance motors (SRSRMs) with different rotor pole numbers for belt-driven starter generators of hybrid electric vehicles. For the design principles, several constraints are derived for the numbers of stator and rotor poles, the dimensions, and the number of winding turns. Two SRSRMs with 16/10 and 16/14 stator/rotor poles are presented according to these principles. For the performance optimization, the two motors are optimized individually for maximizing the torque. To evaluate the effect of different segmented-rotor numbers, the overall performances of the two SRSRMs are investigated and compared. It is found that the 16/14 SRSRM has higher flux linkage and static torque. The 16/14 SRSRM exhibits higher torque and lower torque ripple at low speed operation, whereas at high speed, the 16/10 SRSRM performs better in terms of torque and power densities. Compared with the 16/14 SRSRM, the 16/10 SRSRM has higher final steady speed under the same startup condition. The 16/10 SRSRM can achieve higher steady speed under starter mode and provide higher generated power under braking mode. Moreover, the 16/10 SRSRM exhibits higher efficiency in the most feasible speed range, especially in high speed range, and it has wider high-efficiency area. Finally, a 16/10 SRSRM is prototyped and tested to validate the simulation results.

Sun, X, Gui, G, Li, Y, Liu, RP & An, Y 2019, 'ResInNet: A Novel Deep Neural Network With Feature Reuse for Internet of Things', IEEE Internet of Things Journal, vol. 6, no. 1, pp. 679-691.
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© 2014 IEEE. Deep neural networks (DNNs) have widely used in various Internet-of-Things (IoT) applications. Pursuing superior performance is always a hot spot in the field of DNN modeling. Recently, feature reuse provides an effective means of achieving favorable nonlinear approximation performance in deep learning. Existing implementations utilizes a multilayer perception (MLP) to act as a functional unit for feature reuse. However, determining connection weight and bias of MLP is a rather intractable problem, since the conventional back-propagation learning approach encounters the limitations of slow convergence and local optimum. To address this issue, this paper develops a novel DNN considering a well-behaved alternative called reservoir computing, i.e., reservoir in network (ResInNet). In this structure, the built-in reservoir has two notable functions. First, it behaves as a bridge between any two restricted Boltzmann machines in the feature learning part of ResInNet, performing a feature abstraction once again. Such reservoir-based feature translation provides excellent starting points for the following nonlinear regression. Second, it serves as a nonlinear approximation, trained by a simple linear regression using the most representative (learned) features. Experimental results over various benchmark datasets show that ResInNet can achieve the superior nonlinear approximation performance in comparison to the baseline models, and produce the excellent dynamic characteristics and memory capacity. Meanwhile, the merits of our approach is further demonstrated in the network traffic prediction related to real-world IoT application.

Sun, X, Hu, C, Zhu, J, Wang, S, Zhou, W, Yang, Z, Lei, G, Li, K, Zhu, B & Guo, Y 2019, 'MPTC for PMSMs of EVs With Multi-Motor Driven System Considering Optimal Energy Allocation', IEEE Transactions on Magnetics, vol. 55, no. 7, pp. 1-6.
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© 1965-2012 IEEE. This paper presents a compound propulsion system with a high-speed permanent-magnet synchronous motor (PMSM) and two in-wheel motors for electric vehicles (EVs). In this paper, the longitudinal dynamic model of EVs is first presented. Then traction distribution ratio \alpha is introduced to express the traction distribution between the front and the rear axles. Moreover, the function of power consumption concerned with the traction distribution ratio \alpha is established. Therefore, the \alpha that minimizes the power consumption function is selected as the optimal traction distribution ratio. To improve the performance of motor controllers, the model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives. Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response. Finally, experimental comparisons and hardware-in-loop (HiL) tests are presented to verify the MPTC method and the proposed energy allocation method, respectively.

Sun, X, Shi, Z, Lei, G, Guo, Y & Zhu, J 2019, 'Analysis and Design Optimization of a Permanent Magnet Synchronous Motor for a Campus Patrol Electric Vehicle', IEEE Transactions on Vehicular Technology, vol. 68, no. 11, pp. 10535-10544.
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© 1967-2012 IEEE. This work presents the analysis, design and optimization of a permanent magnet synchronous motor (PMSM) for an electric vehicle (EV) used for campus patrol with a specific drive cycle. Firstly, based on the collected data like the parameters and speed from a test EV on the campus road, the dynamic calculation of the EV is conducted to decide the rated power and speed range of the drive PMSM. Secondly, according to these requirements, an initial design and some basic design parameters are obtained. Thirdly, optimization process is implemented to improve the performance of the designed PMSM. The permanent magnet (PM) structure, airgap length and stator core geometry are optimized respectively in this step. Different optimization processes are proposed to meet multiple optimization objectives simultaneously. Based on the finite element analysis (FEA) method, it is found that the harmonic of the optimized PMSM is lower than that of the initial design, and the torque ripple is reduced by 24%. The effectiveness of optimization on the core loss and PM eddy loss is validated and the temperature rise is suppressed effectively. Finally, a prototype is fabricated for the optimized PMSM and an experimental platform is developed. The test results verify that the optimized PMSM meets the requirements of the specific campus patrol EV well.

Sun, Y, Yue, H, Zhang, J & Booth, C 2019, 'Minimization of Residential Energy Cost Considering Energy Storage System and EV With Driving Usage Probabilities', IEEE Transactions on Sustainable Energy, vol. 10, no. 4, pp. 1752-1763.
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© 2018 IEEE. Electric vehicle (EV) can be applied to discharge power back to the grid, which is called vehicle-to-grid (V2G) technology. There is a constant debate on whether V2G is an economically viable option due to the high battery degradation cost. In this work, the cost benefit of EV customers participating in V2G has been studied using different feed-in tariffs (FITs). A model is developed for minimization of energy cost for residential users, which includes an EV, a separate energy storage system (ESS), and renewable energy supply. Key factors such as the EV driving usage, the degradation cost of EV and ESS batteries are considered. The EV driving usage is established through a designed survey, from which the probability of vehicle parking and plug in at home, the probabilities of EV under driving and parking outside can be calculated. Comprehensive case studies have been undertaken to investigate the optimization strategies under various scenarios. Two types of electricity tariffs, time-of-use (TOU) and fixed tariffs, are considered. It is revealed that certain threshold levels of FITs are expected to allow users benefit from V2G. Compared with non-optimized operation, the cost saving with the optimized strategy is evident in the case studies.

Sutton, GJ, Zeng, J, Liu, RP, Ni, W, Nguyen, DN, Jayawickrama, BA, Huang, X, Abolhasan, M, Zhang, Z, Dutkiewicz, E & Lv, T 2019, 'Enabling Technologies for Ultra-Reliable and Low Latency Communications: From PHY and MAC Layer Perspectives', IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2488-2524.
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© 1998-2012 IEEE. Future 5th generation networks are expected to enable three key services-enhanced mobile broadband, massive machine type communications and ultra-reliable and low latency communications (URLLC). As per the 3rd generation partnership project URLLC requirements, it is expected that the reliability of one transmission of a 32 byte packet will be at least 99.999% and the latency will be at most 1 ms. This unprecedented level of reliability and latency will yield various new applications, such as smart grids, industrial automation and intelligent transport systems. In this survey we present potential future URLLC applications, and summarize the corresponding reliability and latency requirements. We provide a comprehensive discussion on physical (PHY) and medium access control (MAC) layer techniques that enable URLLC, addressing both licensed and unlicensed bands. This paper evaluates the relevant PHY and MAC techniques for their ability to improve the reliability and reduce the latency. We identify that enabling long-term evolution to coexist in the unlicensed spectrum is also a potential enabler of URLLC in the unlicensed band, and provide numerical evaluations. Lastly, this paper discusses the potential future research directions and challenges in achieving the URLLC requirements.

Taghizadeh, S, Hossain, MJ, Lu, J & Karimi-Ghartemani, M 2019, 'An Enhanced DC-Bus Voltage-Control Loop for Single-Phase Grid-Connected DC/AC Converters', IEEE Transactions on Power Electronics, vol. 34, no. 6, pp. 5819-5829.
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© 1986-2012 IEEE. This paper presents a method to enhance the dc-bus voltage-control loop of a single-phase grid-connected dc/ac converter, which improves its responses in terms of oscillation on its dc-bus voltage as well as its output ac current. Conventionally, the double-frequency (2-f) ripple is reduced by using a large electrolyte capacitor, which increases the cost and size of the system. A state-of-the-art approach is to use a notch filter (NF) to block the 2-f ripple in the voltage-control loop. This can significantly reduce the capacitor size. The existing presentations of this method, however, do not integrate the internal dynamics of the NF into consideration. This paper proposes a new way of implementing the NF, which allows integration of its internal variables into the control loop. The resulted system exhibits enhanced transient responses at both the dc-bus voltage and the output ac current. The proposed method is analyzed in detail and its effectiveness is verified through simulations and experimental results.

Taghizadeh, S, Karimi-Ghartemani, M, Hossain, MJ & Lu, J 2019, 'A Fast and Robust DC-Bus Voltage Control Method for Single-Phase Voltage-Source DC/AC Converters', IEEE Transactions on Power Electronics, vol. 34, no. 9, pp. 9202-9212.
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© 1986-2012 IEEE. This paper presents a fast and robust dc-bus voltage control method for single-phase grid-connected dc/ac converters. The proposed technique precisely estimates the double-frequency (2-f) ripple of a dc-bus voltage and removes it from the voltage-control loop without adding any additional dynamics or oscillations. Conventionally, the 2-f ripple is managed by using large capacitors, which increase the cost and bulkiness of a converter. As a state-of-the-art approach, a notch filter (NF) or a dc-voltage estimator is used to effectively block the 2-f ripple from the voltage-control loop, which can significantly reduce the capacitor size. However, such an approach introduces new dynamics in the control loop, causes additional oscillations on the bus voltage, and increases the settling time of its response. This limits the degrees of freedom of the design to improve the overall system damping. The proposed method in this paper has no adverse impact on the original bus-voltage dynamic response. As a result, the bus-voltage control can be designed with higher speed and robustness and the whole system can operate with a reduced transient at both the bus voltage and the output ac current. The proposed approach is thoroughly analyzed and its effectiveness is validated through simulations and experimental results.

Teng, QF, Cui, HW, Zhu, JG, Guo, YG & Tian, J 2019, 'Current sensorless-based model predictive control for PMSM drive system', Dianji yu Kongzhi Xuebao/Electric Machines and Control, vol. 23, no. 5, pp. 119-128.
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Based on extended state observer (ESO), a novel model predictive torque control (MPTC) strategy was developed for three phase permanent magnet synchronous motor (PMSM) drive system with current sensorless. To achieve high precision control, generally two phase current sensors are indispensable for successful operation of the feedback control. For this purpose, by use of technique of ESO, a new observer for estimating three phase currents and time-varying stator resistance was put forward. Moreover, to reduce torque and flux ripples and improve the performance of the torque and speed, MPTC strategy was employed. The resultant ESO-based MPTC strategy enables PMSM drive system not only to run stably and reliably but also to have satisfactory control performance and strong robustness. The simulation results validate the feasibility and effectiveness of the proposed scheme.

Thomas, D, Shankaran, R, Orgun, M, Hitchens, M & Ni, W 2019, 'Energy-Efficient Military Surveillance: Coverage Meets Connectivity', IEEE Sensors Journal, vol. 19, no. 10, pp. 3902-3911.
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© 2001-2012 IEEE. Sensor networks are increasingly being used in the development and application of military surveillance systems. Small size battery-powered sensor devices are deployed in unattended and hostile environments, such as battlefields to detect any physical intrusion. Energy efficiency, coverage, and connectivity are the three major quality-of-service requirements of such mission critical applications. Energy-efficient communication is required to prolong the network lifetime. Better coverage is required to detect the physical intrusion attempts of all kinds. Similarly, connectivity is necessary to provide mission critical messages to the base station in a timely manner. A scheme that satisfies energy efficiency, coverage, and connectivity requirements is an N-P complete problem. This paper proposes an energy-efficient node scheduling algorithm called EC2 that addresses the problems of energy efficiency, coverage, and connectivity in military surveillance applications using the fuzzy graphs.

Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2019, 'Low-Frequency Metamaterial Absorber Using Space-Filling Curve', Journal of Electronic Materials, vol. 48, no. 10, pp. 6451-6459.
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© 2019, The Minerals, Metals & Materials Society. The extensive use of metamaterials and metamaterial absorbers increases the demand for compact structures in various frequencies. Designing electrically small absorbers for lower frequencies, especially sub-gigahertz applications, is one of the open issues in this field. In this paper, a space filling curve is used to design an absorber operating on low frequencies. The unit cell design is based on a Sierpinski curve with the size of 25×25×1.6mm3 and air-gap of 10 mm. The structure shows 99.9% absorption at 900 MHz on the third step. The system also shows multiple resonances due to its structure. The proposed structure is fabricated and tested and shows a good agreement with simulation results.

Tran, TT, Bradac, C, Solntsev, AS, Toth, M & Aharonovich, I 2019, 'Suppression of spectral diffusion by anti-Stokes excitation of quantum emitters in hexagonal boron nitride', Applied Physics Letters, vol. 115, no. 7, pp. 071102-071102.
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Solid-state quantum emitters are garnering a lot of attention due to their role in scalable quantum photonics. A notable majority of these emitters, however, exhibit spectral diffusion due to local, fluctuating electromagnetic fields. In this work, we demonstrate efficient anti-Stokes (AS) excitation of quantum emitters in hexagonal boron nitride (hBN) and show that the process results in the suppression of a specific mechanism responsible for spectral diffusion of the emitters. We also demonstrate an all-optical gating scheme that exploits Stokes and anti-Stokes excitation to manipulate spectral diffusion so as to switch and lock the emission energy of the photon source. In this scheme, reversible spectral jumps are deliberately enabled by pumping the emitter with high energy (Stokes) excitation; AS excitation is then used to lock the system into a fixed state characterized by a fixed emission energy. Our results provide important insights into the photophysical properties of quantum emitters in hBN and introduce a strategy for controlling the emission wavelength of quantum emitters.

Tran, TT, Regan, B, Ekimov, EA, Mu, Z, Zhou, Y, Gao, W-B, Narang, P, Solntsev, AS, Toth, M, Aharonovich, I & Bradac, C 2019, 'Anti-Stokes excitation of solid-state quantum emitters for nanoscale thermometry', Science Advances, vol. 5, no. 5.
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We demonstrate anti-Stokes excitation of single color centers in diamond for high-sensitivity, nanoscale temperature measurements.

Tuan, HD, Nasir, AA, Nguyen, HH, Duong, TQ & Poor, HV 2019, 'Non-Orthogonal Multiple Access With Improper Gaussian Signaling', IEEE Journal of Selected Topics in Signal Processing, vol. 13, no. 3, pp. 496-507.
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© 2007-2012 IEEE. Improper Gaussian signaling (IGS) helps to improve the throughput of a wireless communication network by taking advantage of the additional degrees of freedom in signal processing at the transmitter. This paper exploits IGS in a general multiuser multi-cell network, which is subject to both intra-cell and inter-cell interference. With IGS under orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), designs of transmit beamforming to maximize the users' minimum throughput subject to transmit power constraints are addressed. Such designs are mathematically formulated as nonconvex optimization problems of structured matrix variables, which cannot be solved by popular techniques such as weighted minimum mean square error or convex relaxation. By exploiting the lowest computational complexity of 2× 2 linear matrix inequalities, lower concave approximations are developed for throughput functions, which are the main ingredients for devising efficient algorithms for finding solution of these difficult optimization problems. Numerical results obtained under practical scenarios reveal that there is an almost two-fold gain in the throughput by employing IGS instead of the conventional proper Gaussian signaling under both OMA and NOMA; and NOMA-IGS offers better throughput compared to that achieved by OMA-IGS.

Tuan, HD, Nasir, AA, Nguyen, M-N & Masood, M 2019, 'Han–Kobayashi Signaling in MIMO Broadcasting', IEEE Communications Letters, vol. 23, no. 5, pp. 855-858.
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IEEE This letter applies Han-Kobayashi (H-K) superposition signaling to a network of a multi-antenna transmitter serving two multi-antenna users. By making the rate of the common message for both users contribute to user individual rate, it shows that H-K superposition signaling clearly outperforms both stateof- the-art orthogonal multiaccess (OMA) and nonorthogonal multiaccess schemes (NOMA) in terms of the worst user rate. More importantly, unlike NOMA, H-K superposition signaling does not require the user channels to be differentiated for efficient implementation.

Tun, EE, Aramvith, S & Miyanaga, Y 2019, 'Fast Coding Unit Encoding Scheme for HEVC Using Genetic Algorithm', IEEE Access, vol. 7, pp. 68010-68021.
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Uddin, MB, Su, SW, Chen, W & Chow, CM 2019, 'Dynamic changes in electroencephalogram spectral power with varying apnea duration in older adults', Journal of Sleep Research, vol. 28, no. 6.
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AbstractSleep apnea elicits brain and physiological changes and its duration varies across the night. This study investigates the changes in the relative powers in electroencephalogram (EEG) frequency bands before and at apnea termination and as a function of apnea duration. The analysis was performed on 30 sleep records (375 apnea events) of older adults diagnosed with sleep apnea. Power spectral analysis centered on two 10‐s EEG epochs, before apnea termination (BAT) and after apnea termination (AAT), for each apnea event. The relative power changes in EEG frequency bands were compared with changes in apnea duration, defined as Short (between 10 and 20 s), Moderate (between 20 and 30 s) and Long (between 30 and 40 s). A significant reduction in EEG relative powers for lower frequency bands of alpha and sigma were observed for the Long compared to the Moderate and Short apnea duration groups at BAT, and reduction in relative theta, alpha and sigma powers for the Long compared to the Moderate and Short groups at AAT. The proportion of apnea events showed a significantly decreased trend with increased apnea duration for non‐rapid eye movement sleep but not rapid eye movement sleep. The proportion of central apnea events decreased with increased apnea duration, but not obstructive episodes. The findings suggest EEG arousal occurred both before and at apnea termination and these transient arousals were associated with a reduction in relative EEG powers of the low‐frequency bands: theta, alpha and sigma. The clinical implication is that these transient EEG arousals, without awakenings, are protective of sleep. Further studies with large datasets and different age groups are recommended.

Usman, M, He, X, Lam, K-M, Xu, M, Bokhari, SMM, Chen, J & Jan, MA 2019, 'Error Concealment for Cloud–Based and Scalable Video Coding of HD Videos', IEEE Transactions on Cloud Computing, vol. 7, no. 4, pp. 975-987.
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IEEE The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bit-rates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.

Vo, TT, Luong, NT & Hoang, D 2019, 'MLAMAN: a novel multi-level authentication model and protocol for preventing wormhole attack in mobile ad hoc network', Wireless Networks, vol. 25, no. 7, pp. 4115-4132.
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Vu, MN, Tran, NH, Tuan, HD, Nguyen, TV & Nguyen, DHN 2019, 'Optimal Signaling Schemes and Capacities of Non-Coherent Correlated MISO Channels Under Per-Antenna Power Constraints', IEEE Transactions on Communications, vol. 67, no. 1, pp. 190-204.
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© 1972-2012 IEEE. This paper investigates the optimal signaling schemes and capacities of non-coherent correlated multiple-input single-output (MISO) channels in fast Rayleigh fading. We consider both channels under per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. For per-antenna power constraint channels, we first establish the convex and compact properties of the feasible sets, and demonstrate the existence of optimal input distribution and the uniqueness of optimal effective magnitude input distribution. By exploiting the solutions of a quadratic optimization problem, we show that the Kuhn-Tucker condition on the optimal inputs can be simplified to a single dimension. As a result, we can apply the Identity Theorem to show the discrete and finite nature of the optimal effective magnitude distribution, with a mass point located at the origin. By using this distribution, we then construct a finite and discrete optimal input vector distribution. The use of this input allows us to determine the capacity gain of MISO over SISO via the phase solutions of a constrained quadratic optimization problem on a sphere, which can be obtained using a proposed penalized optimization algorithm. We also extend the results to MISO channels subject to the joint per-antenna and sum power constraints. Under this consideration, it is shown that not all per-antenna constraints are active. While the finiteness and discreteness of the optimal effective magnitude and the optimal input vector distributions still hold, the optimal phases and the optimal power allocation among the transmit antennas need to be determined simultaneously via a quadratic optimization problem under inequality constraints. These solutions can finally be used to obtain the MISO capacity gain.

Vu, TT, Nguyen, DN, Hoang, DT, Dutkiewicz, E & Nguyen, TV 2019, 'Optimal Energy Efficiency with Delay Constraints for Multi-layer Cooperative Fog Computing Networks'.
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We develop a joint offloading and resource allocation framework for amulti-layer cooperative fog computing network, aiming to minimize the totalenergy consumption of multiple mobile devices subject to their service delayrequirements. The resulting optimization involves both binary (offloadingdecisions) and real variables (resource allocations), making it an NP-hard andcomputationally intractable problem. To tackle it, we first propose an improvedbranch-and-bound algorithm (IBBA) that is implemented in a centralized manner.However, due to the large size of the cooperative fog computing network, thecomputational complexity of the proposed IBBA is relatively high. To speed upthe optimal solution searching as well as to enable its distributedimplementation, we then leverage the unique structure of the underlying problemand the parallel processing at fog nodes. To that end, we propose a distributedframework, namely feasibility finding Benders decomposition (FFBD), thatdecomposes the original problem into a master problem for the offloadingdecision and subproblems for resource allocation. The master problem (MP) isthen equipped with powerful cutting-planes to exploit the fact of resourcelimitation at fog nodes. The subproblems (SP) for resource allocation can findtheir closed-form solutions using our fast solution detection method. These(simpler) subproblems can then be solved in parallel at fog nodes. Thenumerical results show that the FFBD always returns the optimal solution of theproblem with significantly less computation time (e.g., compared with thecentralized IBBA approach). The FFBD with the fast solution detection method,namely FFBD-F, can reduce up to $60\%$ and $90\%$ of computation time,respectively, compared with those of the conventional FFBD, namely FFBD-S, andIBBA.

Wang, S, Liu, C, Wang, Y, Lei, G & Zhu, J 2019, '6σ Robust Multidisciplinary Design Optimization Method for Permanent Magnet Motors with Soft Magnetic Composite Cores', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 34, no. 4, pp. 637-645.
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Soft magnetic composite (SMC) is a new kind of magnetic material, which has been widely used in the design of permanent magnet machines due to its unique electromagnetic characteristic. The cores made by SMC are isotropic magnetically and mechanically with lower eddy current loss, and can be manufactured by molded technology. Therefore, this material is promising for the design of motors with complex structure, such as transverse flux machine and claw pole motor. To improve the application of the motors made by SMC, two main research topics need to be investigated. The first one is the multidisciplinary design optimization, which mainly includes the electromagnetic analysis and thermal analysis. The second one is the robust design optimization, which mainly investigates the manufacturing precision/tolerances in the engineering manufacturing process and their effects on motor's performance. The main aim of this work is to present a Six Sigma (6σ) robust design optimization method for SMC motors under the framework of multidisciplinary design optimization. From the discussion, it can be found that the proposed method can improve the motor's performance while keeping the requirements in term of temperature rise conditions. Compared with traditional deterministic design approach, the new method can improve the reliability of the designed motor significantly, which will benefit the batch production of SMC motors in industry.

Wang, S, Wang, Y, Liu, C, Lei, G, Zhu, J & Guo, Y 2019, 'Comparative Study of Linear Superconductivity Machine With Different Stator and Winding Configurations', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-4.
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© 2002-2011 IEEE. Compared with rotary electrical machines in linear drive applications, linear machines without rotary-linear motion conversion equipment can have higher force density and efficiency. Linear superconductivity machines (LSMs), consisting of high-performance superconducting magnets instead of permanent magnets, can offer very high force density and efficiency compared with other linear machines, such as linear induction machine, linear permanent magnet machine, and so on. In this paper, LSMs with different stators and winding configurations are investigated, specifically LSMs with concentrated or distributed windings, and unilateral or bilateral side stators. The electromagnetic parameters and performance of these LSMs are calculated and compared by using the finite element method, and then, the main difference between various design methods in LSM has been presented.

Wang, W, Hoang, DT, Hu, P, Xiong, Z, Niyato, D, Wang, P, Wen, Y & Kim, DI 2019, 'A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks', IEEE Access, vol. 7, pp. 22328-22370.
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© 2013 IEEE. The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.

Wang, X, Song, B, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Group-Based Susceptible-Infectious-Susceptible Model in Large-Scale Directed Networks', Security and Communication Networks, vol. 2019, pp. 1-9.
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Epidemic models trade the modeling accuracy for complexity reduction. This paper proposes to group vertices in directed graphs based on connectivity and carries out epidemic spread analysis on the group basis, thereby substantially reducing the modeling complexity while preserving the modeling accuracy. A group-based continuous-time Markov SIS model is developed. The adjacency matrix of the network is also collapsed according to the grouping, to evaluate the Jacobian matrix of the group-based continuous-time Markov model. By adopting the mean-field approximation on the groups of nodes and links, the model complexity is significantly reduced as compared with previous topological epidemic models. An epidemic threshold is deduced based on the spectral radius of the collapsed adjacency matrix. The epidemic threshold is proved to be dependent on network structure and interdependent of the network scale. Simulation results validate the analytical epidemic threshold and confirm the asymptotical accuracy of the proposed epidemic model.

Wang, X, Yu, G, Zha, X, Ni, W, Liu, RP, Guo, YJ, Zheng, K & Niu, X 2019, 'Capacity of blockchain based Internet-of-Things: Testbed and analysis', Internet of Things, vol. 8, pp. 100109-100109.
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Wang, X, Zha, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Game Theoretic Suppression of Forged Messages in Online Social Networks', IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-11.
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Wang, X, Zha, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Survey on blockchain for Internet of Things', Computer Communications, vol. 136, pp. 10-29.
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© 2019 Elsevier B.V. The Internet of Things (IoT) is poised to transform human life and unleash enormous economic benefit. However, inadequate data security and trust of current IoT are seriously limiting its adoption. Blockchain, a distributed and tamper-resistant ledger, maintains consistent records of data at different locations, and has the potential to address the data security concern in IoT networks. While providing data security to the IoT, Blockchain also encounters a number of critical challenges inherent in the IoT, such as a huge number of IoT devices, non-homogeneous network structure, limited computing power, low communication bandwidth, and error-prone radio links. This paper presents a comprehensive survey on existing Blockchain technologies with an emphasis on the IoT applications. The Blockchain technologies which can potentially address the critical challenges arising from the IoT and hence suit the IoT applications are identified with potential adaptations and enhancements elaborated on the Blockchain consensus protocols and data structures. Future research directions are collated for effective integration of Blockchain into the IoT networks.

Wang, Y, Lu, J, Liu, C, Lei, G, Guo, Y & Zhu, J 2019, 'Development of a High-Performance Axial Flux PM Machine With SMC Cores for Electric Vehicle Application', IEEE Transactions on Magnetics, vol. 55, no. 7, pp. 1-4.
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© 1965-2012 IEEE. A new axial flux permanent magnet machine (AFPM) with soft magnetic composited (SMC) cores is proposed for electric vehicle (EV) application in this paper. As its windings are wound on the stator ring core, it can be regarded as a toroidally wound internal stator (TORUS) machine. With the adopted SMC material for stator core, this machine has the benefits of 3-D magnetic flux properties. The windings and SMC cores can be designed to form a very compact structure, and thus, the torque density can be improved greatly. To obtain the a good flux concentrating ability, two TORUS machines are designed and analyzed, one is with NdFeB magnet for high-performance EV application and the other is with the cheap ferrite magnet for low-cost application. The 3-D finite-element method is used to analyze the electromagnetic parameter and performance. For performance comparison, a commercial AFPM with yokeless and segmented armature P400 is used.

Wang, Y, Ma, J, Liu, C, Lei, G, Guo, Y & Zhu, J 2019, 'Reduction of Magnet Eddy Current Loss in PMSM by Using Partial Magnet Segment Method', IEEE Transactions on Magnetics, vol. 55, no. 7, pp. 1-5.
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© 1965-2012 IEEE. Compared with traditional induction machine and direct current machine, permanent magnet synchronous machine (PMSM) holds many merits like higher torque ability and efficiency when high magnetic co-energy sintered NdFeB magnet is used. However, for the operation with high frequency, the resulted eddy current loss by the permanent magnet (PM) is very high and this kind of loss can bring the PM with high-temperature rise, making the PM face the risk of irreversible demagnetization. To reduce the PM eddy current loss, complete magnet segmentation is an effective method. However, taking this kind of method will increase manufacturing cost and reduce the mechanical robustness of the PMSM. Thus, a partial magnet segmentation method was proposed in the past. In this paper, a new annular partial segmentation (APS) method is proposed for the reduction of the PM eddy current loss, including single-side APS and double-side APS configurations. Considering that the additional process on the PM will reduce the mechanical robustness of the PM and the electromagnetic performance of machine, both the electromagnetic performance and the mechanical strength of the PM have been analyzed, based on 3-D finite-element method. It can be found that if the proposed new annular partial segmentation (APS) method is adopted, the eddy current loss in the PM can be reduced greatly, while the mechanical robustness of the PM can be guaranteed comparing with the traditional partial magnet segmentation method.

Wang, Y, Shuai, Y, Zhu, Y, Zhang, J & An, P 2019, 'Jointly learning perceptually heterogeneous features for blind 3D video quality assessment', Neurocomputing, vol. 332, pp. 298-304.
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© 2018 Elsevier B.V. 3D videos quality assessment (3D-VQA) is essential to various 3D video processing applications. However, it has not been well investigated on how to make use of perceptual multi-channel video information to improve 3D-VQA under different distortion categories and degrees, especially under asymmetrical distortions. In the paper, we propose a new blind 3D-VQA metric by jointly learning perceptually heterogeneous features. Firstly, a binocular spatio-temporal internal generative mechanism (BST-IGM) is proposed to decompose the views of 3D video into multi-channel videos. Then, we extract perceptually heterogeneous features by proposed multi-channel natural video statistics (MNVS) model, which are characterized 3D video information. Furthermore, a robust AdaBoosting Radial Basis Function (RBF) neural network is utilized to map the features to the overall quality of 3D video. On two benchmark databases, the extensive evaluations demonstrate that the proposed algorithm significantly outperforms several state-of-the-art quality metrics in term of prediction accuracy and robustness.

Wang, Z, Xu, M, Ye, N, Wang, R & Huang, H 2019, 'RF-Focus', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, no. 1, pp. 1-30.
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Capturing RFID tags in the region of interest (ROI) is challenging. Many issues, such as multipath interference, frequency-dependent hardware characteristics and phase periodicity, make RF phase difficult to accurately indicate the tag-to-antenna distance for RFID tag localization. In this paper, we propose a comprehensive solution, called RF-Focus, which fuses RFID and computer vision (CV) techniques to recognize and locate moving RFID-tagged objects within ROI. Firstly, we build a multipath propagation model and propose a dual-antenna solution to minimize the impact of multipath interference on RF phase. Secondly, by extending the multipath model, we estimate phase shifts due to hardware characteristics at different operating frequencies. Thirdly, to minimize the tag position uncertainty due to RF phase periodicity, we leverage CV to extract image regions of being likely to contain ROI RFID-tagged objects, and then associate them with the processed RF phase after the removal of the phase shifts due to multipath interference and hardware characteristics for recognition and localization. Our experiments demonstrate the effectiveness of multipath modelling and hardware-related phase shift estimation. When five RFID-tagged objects are moving in the ROI, RF-Focus achieves the average recognition accuracy of 91.67% and localization accuracy of 94.26% given a false positive rate of 10%.

Wei, Cheng, Lu, Siwakoti & Zhang 2019, 'Multi-Variable Thermal Modeling of Power Devices Considering Mutual Coupling', Applied Sciences, vol. 9, no. 16, pp. 3240-3240.
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In relation to power converter design, power density is increasing while the form factor isdecreasing. This trend generally reduces the rate of the cooling process, which increases the mutualthermal coupling among the surrounding power components. Most of the traditional modelsusually ignore the mutual effects or just focus on the conduction coupling. To deal with these factors,the thermal modeling for a boost converter system has been built to compare the junctiontemperatures (Tj) and the increments under different working conditions in order to consider theconduction coupling. A multi-variable thermal resistances model is proposed in this paper toincorporate the convection thermal coupling into the mutual thermal effects. The couplingresistances, MOSFET to the diode[...]

Wei, F, Yang, Z-J, Qin, P-Y, Guo, YJ, Li, B & Shi, X-W 2019, 'A Balanced-to-Balanced In-Phase Filtering Power Divider With High Selectivity and Isolation', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 2, pp. 683-694.
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© 1963-2012 IEEE. In this paper, a balanced-to-balanced in-phase filtering power divider (FPD) is proposed, which can realize a two-way equal power division with high selectivity and isolation. The design of the proposed FPD is primarily based on microstrip/slotline transition structures and slotline T-junction. A U-type microstrip feed line integrated with a stepped-impedance slotline resonator is adopted at the input and output ports, which makes the differential-mode (DM) responses independent of the common-mode (CM) ones. Meanwhile, superior DM transmission and CM suppression are achieved intrinsically, thereby simplifying the design procedure significantly. By employing slotline resonators loaded with resistors, the isolation between the two output ports can be improved greatly. In addition, a DM passband with a sharp filtering performance is realized by introducing the microstrip stub-loaded resonators (SLRs). By changing the electrical length of the open stub of the SLR, the fractional bandwidth is controllable. In order to verify the feasibility of the proposed design method, two prototype circuits of the proposed FPDs with different bandwidths are fabricated and measured. Good agreement between the simulation and measurement results is observed.

Wei, K, Lu, DD-C, Zhang, C, Siwakoti, YP, Soon, JL & Yao, Q 2019, 'Modeling and Analysis of Thermal Resistances and Thermal Coupling Between Power Devices', IEEE Transactions on Electron Devices, vol. 66, no. 10, pp. 4302-4308.
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© 1963-2012 IEEE. The recent trend in the design of the high-power density power converter generally reduces the rate of the device cooling process. As a result, increased thermal coupling among devices exists. Based on measurements, a thermal coupling resistances network (TCRN) model is proposed in this article. Considering different spacings and current values at a fixed value of case temperature ( T _text c ), the relationships between the case-to-ambient thermal resistance ( R _text ca ) of individual power devices and their thermal coupling resistance ( R _text cp ) to the adjacent device are established. The close correspondence of T _text c from the calculation of the different spacing and experimental results obtained from a thermal coupling measurement platform confirms the established TCRN model and the relationships. Traditional thermal models do not consider the changes of R _text ca and also ignore the effect of thermal coupling among the adjacent devices. Compared with these models, the proposed thermal resistances modeling approach provides a better understanding of the thermal behavior of power devices.

Wei, X, Cheng, M, Luo, R, Xu, L & Zhu, J 2019, 'Model predictive virtual power control of brushless doubly‐fed induction generator for fast and smooth grid synchronisation', IET Renewable Power Generation, vol. 13, no. 16, pp. 3080-3087.
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Wei, X, Cheng, M, Zhu, J, Yang, H & Luo, R 2019, 'Finite-Set Model Predictive Power Control of Brushless Doubly Fed Twin Stator Induction Generator', IEEE Transactions on Power Electronics, vol. 34, no. 3, pp. 2300-2311.
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© 1986-2012 IEEE. This paper presents a finite-set model predictive power control (FS-MPPC) method for the brushless doubly fed twin stator induction generator (BDFTSIG) in variable speed constant frequency generation applications. The FS-MPPC controller is developed in a general reference frame from which all other reference frames can be deduced readily. The invariant feature of the predictive power model in various reference frames contributes to the reference frame-free characteristic of the developed FS-MPPC controller, enabling its application more flexible and universal. Besides, the arduous process of control winding flux estimation is avoided in the FS-MPPC controller by choosing state variables that are easy to be obtained. Moreover, the influence of rotor circuit that has long been neglected in the existing controllers for the brushless doubly fed induction machines is embedded within the predictive power model and inherently considered in the FS-MPPC controller, which contributes to accurate power control of the BDFTSIG. Furthermore, the feasibility and effectiveness of the developed FS-MPPC controller regarding different power levels and grid fault conditions are briefly discussed. Finally, numerical simulations and experimental tests are carried out, which demonstrates the effectiveness of the developed FS-MPPC controller.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Efficient Angle-of-Arrival Estimation of Lens Antenna Arrays for Wireless Information and Power Transfer', IEEE Journal on Selected Areas in Communications, vol. 37, no. 1, pp. 116-130.
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© 1983-2012 IEEE. Antenna design and angle-of-arrival (AoA) estimation are critical to the efficiency of wireless information and power transfer. The AoA estimation is challenging for energy-efficient lens antenna arrays (LAAs), due to discrete sets of fixed discrete Fourier transform (DFT) beams. This paper presents a novel fast and accurate approach for the AoA estimation of LAAs. The key idea is that we prove the two differential outputs of three adjacent lens beams, referred to as 'DFT beam differences (DBDs),' that are the strongest at the two sides of an AoA. They are easy to identify and robust to noises, and their powers are proved to provide an accurate estimate of the AoA. Another important aspect is a new beam synthesis technique which produces different beam widths based on DFT beams and practical 1-bit phase shifts in real time. As a result, the angular region containing the AoA can exponentially narrow down, and the two strongest DBDs can be quickly identified. The proposed approach can operate in coupling with successive interference cancellation to estimate the AoAs of multiple paths. Simulations show that the proposed approach is able to outperform the state of the art by orders of magnitude in terms of accuracy. The power transfer efficiency can be dramatically improved.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Expeditious Estimation of Angle-of-Arrival for Hybrid Butler Matrix Arrays', IEEE Transactions on Wireless Communications, vol. 18, no. 4, pp. 2170-2185.
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© 2002-2012 IEEE. Arrays of Butler matrices provide a promising front-end design for massive MIMO transceivers with low cost and low complexity. However, this advanced design does not necessarily translate to effective applications, unless the angle-of-arrival (AoA) of signals avails to the Butler matrices. This paper presents an efficient approach to the unprecedented AoA estimation for the arrays of Butler matrices. Specifically, we design a new beam synthesis method to recursively narrow down and increasingly focus on the angular region of interest, and hence achieving robust estimation of the phase offset between Butler matrices. With the phase offset canceled in the received signals, we are able to identify the set of critical Butler beams with the dominating effect on the AoA estimation, and estimate the AoA accordingly with minimum signaling. The mean squared error of the proposed estimation is analyzed in the presence of non-negligible noises, with closed-form lower bounds derived. Validated by simulations, the proposed algorithm is able to indistinguishably approach the lower bounds, and significantly outperforms the state-of-the-art developed for discrete antenna arrays by orders of magnitude in terms of accuracy, especially in low signal-to-noise regimes.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Exploiting Spatial-Wideband Effect for Fast AoA Estimation at Lens Antenna Array', IEEE Journal of Selected Topics in Signal Processing, vol. 13, no. 5, pp. 902-917.
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© 2007-2012 IEEE. Energy-efficient, highly integrated lens antenna arrays (LAAs) have found widespread applications in wideband millimeter wave or terahertz communications, localization and tracking, and wireless power transfer. Accurate estimation of angle-of-arrival (AoA) is key to those applications, but has been hindered by a spatial-wideband effect in wideband systems. This paper proposes to exploit (rather than circumventing) the spatial-wideband effect to develop a fast and accurate AoA estimation approach for LAAs. Specifically, we unveil new spatial-frequency patterns based on the spatial-wideband effect, and establish one-to-one mappings between the patterns and the strongest discrete Fourier transform (DFT) beam containing the AoA. With the strongest DFT beam identified, we propose a method to estimate the AoA uniquely and accurately, using only a few training symbols. This is achieved by deriving a new one-to-one mapping between the AoA and the set of DFT beams judiciously selected based on the strongest. In the case that an impinging path is uniformly distributed in [0,2π], simulations show that the proposed algorithm is able to reduce the mean squared error of the AoA estimation by as much as 82.1% while reducing the number of required symbols by 93.2$, as compared to existing techniques. The algorithm can also increase the spectral efficiency by 89% when the average SNR is 20 dB at each antenna of the receiver.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Recent Breakthroughs on Angle-of-Arrival Estimation for Millimeter-Wave High-Speed Railway Communication', IEEE Communications Magazine, vol. 57, no. 9, pp. 57-63.
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© 2019 IEEE. With significantly improved efficiency, largescale hybrid antenna arrays with tens to hundreds of antennas have great potential to support millimeter-wave (mmWave) communication for high-speed railway (HSR) applications. The significant beamforming gains rely on fast and accurate estimation of the angle-of-arrival (AoA), but this can be impeded by the high train speed, the cost/energy oriented design of arrays, and the severe attenuation of mmWave signals. This article reviews these challenges, and discusses the limitations of existing AoA estimation techniques under hybrid antenna array settings. The article further reveals a few recent theoretical breakthroughs that can potentially enable fast and reliable estimation, even based on severely attenuated signals. Under a speed setting of 500 km/h, a performance study is carried out to confirm the significant improvements of estimation accuracy and subsequent beamforming gains as the results of the breakthroughs.

Wu, T, Lu, K, Zhu, J, Lei, G, Guo, Y & Tang, S 2019, 'Calculation of Eddy Current Loss in a Tubular Oscillatory LPMSM Using Computationally Efficient FEA', IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 6200-6209.
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© 2018 IEEE. In some special oscillatory applications, especially those operated at high speeds, the eddy current loss of a linear permanent-magnet (PM) synchronous machine (LPMSM) should be fully considered because the loss might be large and concentrated in PMs during the oscillation period. This paper presents a loss analysis method based on computationally efficient finite-element analysis (CE-FEA) for a 20-Hz oscillatory tubular LPMSM. Since the mover speed varies with time, an equally divided model in 1/4 period is introduced to calculate the average PM eddy current loss. The flux density curves in PMs are calculated at 18 intervals by the CE-FEA, through which the change rate of the magnetic flux density is analyzed, considering both the entering and leaving effects and coil end effects. The calculation results show that the eddy current loss is obviously concentrated in PMs near the two ends of coils. The calculation results at a speed of 3.6 m/s obtained by the CE-FEA and two-dimensional and three-dimensional time-stepping FEAs are compared to validate the accuracy. Finally, the proposed method is validated by the experimental test results on a prototype LPMSM.

Wu, Y, Liu, T, Ling, S, Szymanski, J, Zhang, W & Su, S 2019, 'Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector', Sensors, vol. 19, no. 2, pp. 362-362.
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This paper presents a smart “e-nose” device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we propose a novel artificial-intelligent-based multiple hazard gas detector (MHGD) system that is mounted on a motor vehicle-based robot which can be remotely controlled. First, we optimized the sensor array for the classification of three hazardous gases, including cigarette smoke, inflammable ethanol, and off-flavor from spoiled food, using an e-nose with a mixing chamber. The mixing chamber can prevent the impact of environmental changes. We compared the classification results of all combinations of sensors, and selected the one with the highest accuracy (98.88%) as the optimal sensor array for the MHGD. The optimal sensor array was then mounted on the MHGD to detect and classify the target gases without a mixing chamber but in a controlled environment. Finally, we tested the MHGD under these conditions, and achieved an acceptable accuracy (70.00%).

Xiao, C, Zeng, J, Ni, W, Liu, RP, Su, X & Wang, J 2019, 'Delay Guarantee and Effective Capacity of Downlink NOMA Fading Channels', IEEE Journal of Selected Topics in Signal Processing, vol. 13, no. 3, pp. 508-523.
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© 2007-2012 IEEE. Nonorthogonal multiple access (NOMA) is promising for increasing connectivity and capacity. But there has been little consideration on the quality of service of NOMA; let alone that in generic fading channels. This paper establishes closed-form upper bounds for the delay violation probability of downlink Nakagami-m and Rician NOMA channels, by exploiting stochastic network calculus (SNC). The key challenge addressed is to derive the Mellin transforms of the service processes in the NOMA fading channels. The transforms are proved to be stable, and incorporated into the SNC to provide the closed-form upper bounds of the delay violation probability. The paper also applies the Mellin transforms to develop the closed-form expressions for the effective capacity of the NOMA fading channels, which measures the channel capacity under statistical delay guarantees. By further applying the min-max and max-min rules, two new power allocation algorithms are proposed to optimize the closed-form expressions, which can provide the NOMA users fairness in terms of delay violation probability and effective capacity. Simulation results substantiate the derived upper bounds of the delay violation probabilities, and the effective capacity. The proposed power allocation algorithms are also numerically validated.

Xiao, C, Zeng, J, Ni, W, Su, X, Liu, RP, Lv, T & Wang, J 2019, 'Downlink MIMO-NOMA for Ultra-Reliable Low-Latency Communications', IEEE Journal on Selected Areas in Communications, vol. 37, no. 4, pp. 780-794.
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© 2019 IEEE. With the emergence of the mission-critical Internet of Things applications, ultra-reliable low-latency communications are attracting a lot of attentions. Non-orthogonal multiple access (NOMA) with multiple-input multiple-output (MIMO) is one of the promising candidates to enhance connectivity, reliability, and latency performance of the emerging applications. In this paper, we derive a closed-form upper bound for the delay target violation probability in the downlink MIMO-NOMA, by applying stochastic network calculus to the Mellin transforms of service processes. A key contribution is that we prove that the infinite-length Mellin transforms resulting from the non-negligible interferences of NOMA are Cauchy convergent and can be asymptotically approached by a finite truncated binomial series in the closed form. By exploiting the asymptotically accurate truncated binomial series, another important contribution is that we identify the critical condition for the optimal power allocation of MIMO-NOMA to achieve consistent latency and reliability between the receivers. The condition is employed to minimize the total transmit power, given a latency and reliability requirement of the receivers. It is also used to prove that the minimal total transmit power needs to change linearly with the path losses, to maintain latency and reliability at the receivers. This enables the power allocation for mobile MIMO-NOMA receivers to be effectively tracked. The extensive simulations corroborate the accuracy and effectiveness of the proposed model and the identified critical condition.

Xiao, N, Li, H, Yu, W, Gu, C, Fang, H, Peng, Y, Mao, H, Fang, Y, Ni, W & Yao, M 2019, 'SUMO‐specific protease 2 (SENP2) suppresses keratinocyte migration by targeting NDR1 for de‐SUMOylation', The FASEB Journal, vol. 33, no. 1, pp. 163-174.
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Xu, M, Chen, H, Zhao, Y, Ni, W, Liu, M, Xue, Y, Huo, S, Wu, L, Yang, Z & Yan, Y 2019, 'Ultrathin‐Carbon‐Layer‐Protected PtCu Nanoparticles Encapsulated in Carbon Capsules: A Structure Engineering of the Anode Electrocatalyst for Direct Formic Acid Fuel Cells', Particle & Particle Systems Characterization, vol. 36, no. 7.
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AbstractStructure engineering is an effective strategy to enhance the performance of electrocatalysts for the formic acid oxidation reaction. However, it remains a challenge to prepare a highly active electrocatalyst based on a distinct understanding of its structure‐dependent performance. The design and synthesis of ultrathin‐carbon‐layer‐protected PtCu nanoparticles (NPs) encapsulated in a N‐doped carbon capsule (PtCu@NCC) is reported. This system is fabricated by using Zn‐based metal–organic frameworks as the carbon support source and metal‐containing tannic acid as the protecting shell template. It displays 9.8‐ and 9.6‐fold enhancements in mass activity and specific activity compared to commercial Pt/C. Moreover, a constructed direct formic acid fuel cell using PtCu@NCC as the anodic electrocatalyst delivers a maximum power density of 121 mW cm−2. Significantly, PtCu@NCC exhibits superior structural stability and catalytic durability in both half‐cell and full‐cell tests. A mechanism study reveals that the enhanced activity is partially attributed to facilitated electro‐oxidation kinetics of formic acid in the unique structure of PtCu@NCC, while the excellent durability stems from the “protecting effect” of the in‐situ‐formed ultrathin carbon layer on the surface of the PtCu NPs. This work opens a new avenue for the development of high‐performance electrocatalysts for fuel‐cell applications by offering essential insights into the structure–performance relationship of the materials.

Xu, W, Hu, D, Lei, G & Zhu, J 2019, 'System-level efficiency optimization of a linear induction motor drive system', CES Transactions on Electrical Machines and Systems, vol. 3, no. 3, pp. 285-291.
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Xu, Z, Liu, Y, Li, M & Li, Y 2019, 'Linearly Polarized Shaped Power Pattern Synthesis With Dynamic Range Ratio Control for Arbitrary Antenna Arrays', IEEE Access, vol. 7, pp. 53621-53628.
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© 2013 IEEE. This paper extends the semidefinite relaxation (SDR) method to be capable of synthesizing linearly polarized shaped patterns with accurate control of sidelobe level (SLL), cross-polarization level (XPL), and dynamic range ratio (DRR) of the excitation distribution for arbitrary antenna arrays. In addition, by using the vectorial active element patterns, mutual coupling and platform effect can be also incorporated into the proposed vectorial shaped pattern synthesis. Three examples for synthesizing linearly polarized patterns with different pattern shape requirements and different antenna array geometries have been conducted to check the effectiveness and robustness of the proposed method. Compared to the original vectorial shaped pattern synthesis without DRR control, the proposed method with the DRR control can significantly reduce the obtained DRR which is very useful in many antenna array applications.

Yang, D, Zou, Y, Zhang, J & Li, G 2019, 'C-RPNs: Promoting object detection in real world via a cascade structure of Region Proposal Networks', Neurocomputing, vol. 367, pp. 20-30.
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© 2019 Elsevier B.V. Recently, significant progresses have been made in object detection on common benchmarks (i.e., Pascal VOC). However, object detection in real world is still challenging due to the serious data imbalance. Images in real world are dominated by easy samples like the wide range of background and some easily recognizable objects, for example. Although two-stage detectors like Faster R-CNN achieved big successes in object detection due to the strategy of extracting region proposals by Region Proposal Network, they show their poor adaption in real-world object detection as a result of without considering mining hard samples during extracting region proposals. To address this issue, we propose a Cascade framework of Region Proposal Networks, referred to as C-RPNs, which adopts multiple stages to mine hard samples while extracting region proposals and learn stronger classifiers. Meanwhile, a feature chain and a score chain are proposed to help learning more discriminative representations for proposals. Moreover, a loss function of cascade stages is designed to train cascade classifiers through backpropagation. Our proposed method has been evaluated on Pascal VOC and several challenging datasets like BSBDV 2017, CityPersons, etc. Our method achieves competitive results compared with the current state-of-the-arts and attains all-sided improvements in error analysis, validating its efficacy for detection in real world.

Yang, T, Ding, C & Guo, YJ 2019, 'A Highly Birefringent and Nonlinear AsSe<inline-formula> <tex-math notation='LaTeX'>$_2$</tex-math> </inline-formula>–As<inline-formula> <tex-math notation='LaTeX'>$_2$</tex-math> </inline-formula>S<inline-formula> <tex-math notation='LaTeX'>$_5$</tex-math> </inline-formula> Photonic Crystal Fiber With Two Zero-Dispersion Wavelengths', IEEE Photonics Journal, vol. 11, no. 1, pp. 1-7.
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© 2018 IEEE. A hybrid AsSe2-As2S5 photonic crystal fiber (PCF) with a solid elliptical core is proposed and studied theoretically by the full-vector finite element method. The core and cladding of the PCF are made of AsSe2 and As2S5 glasses, respectively. Simulation results demonstrates that, at the operating wavelength of 1.55 μm, the proposed PCF not only exhibits a very high birefringence of 0.091 but also has large nonlinear coefficients of 147.8 and 78.2 W-1m-1 for the X- A nd Y-polarized (X and Y-pol) modes, respectively. Moreover, it is able to achieve two zero-dispersion wavelengths for both the X-pol (1.52 and 2.19 μm) and Y-pol (1.43 and 2.12 μm) modes. The proposed hybrid PCF exhibits excellent polarization maintaining and the nonlinearity performance, thus, suitable to be used in supercontinuum spectrum generation and polarization maintaining nonlinear signal processing.

Yang, T, Ding, C, Ziolkowski, RW & Guo, YJ 2019, 'A Terahertz (THz) Single-Polarization-Single-Mode (SPSM) Photonic Crystal Fiber (PCF)', Materials, vol. 12, no. 15, pp. 2442-2442.
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This paper presents a novel approach to attain a single-polarization-single-mode (SPSM) photonic crystal fiber (PCF) in the terahertz (THz) regime. An initial circular hole PCF design is modified by introducing asymmetry in the first ring of six air holes in the cladding, i.e., epsilon-near-zero (ENZ) material is introduced into only four of those air holes and the other two remain air-filled but have different diameters. The resulting fundamental X-polarized (XP) and Y-polarized (YP) modes have distinctly different electric field distributions. The asymmetry is arranged so that the YP mode has a much larger amount of the field distributed in the ENZ material than the XP mode. Since the ENZ material is very lossy, the YP mode suffers a much higher loss than the XP mode. Consequently, after a short propagation distance, the loss difference (LD) between the XP and YP modes will be large enough that only the XP mode still realistically exists in the PCF. To further enhance the outcome, gain material is introduced into the core area to increase the LDs between the wanted XP mode and any unwanted higher order (HO) modes, as well as to compensate for the XP mode loss without affecting the LD between the XP and YP modes. The optimized PCF exhibits LDs between the desired XP mode and all other modes greater than 8.0 dB/cm across a wide frequency range of 0.312 THz. Consequently, the reported PCF only needs a length of 2.5 cm to attain an SPSM result, with the unwanted modes being more than 20 dB smaller than the wanted mode over the entire operational band.

Yang, Y, Liu, Y, Ma, X, Li, M, Xu, K-D & Guo, YJ 2019, 'Synthesizing Unequally Spaced Pattern-Reconfigurable Linear Arrays With Minimum Interspacing Control', IEEE Access, vol. 7, pp. 58893-58900.
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© 2013 IEEE. Previously, the alternating convex optimization (ACO) was used to reduce the number of elements in the single-pattern linear array. This work extends the ACO method to synthesize the unequally spaced sparse linear arrays with reconfigurable multiple patterns. In this extended ACO, the minimum interspacing constraint can be easily incorporated in the sparse array synthesis by performing a set of constrained alternating convex optimizations. Three examples for synthesizing sparse linear array with different multiple-pattern requirements are conducted to validate the effectiveness, robustness, and advantages of the proposed method. The synthesis results show that the proposed method can effectively reduce the number of elements in the reconfigurable multiple-pattern linear arrays with good control of the sidelobe levels and minimum interspacing. The comparisons with other methods are also given in the examples.

Yao, X, Wu, Q, Zhang, P & Bao, F 2019, 'Adaptive rational fractal interpolation function for image super-resolution via local fractal analysis', Image and Vision Computing, vol. 82, pp. 39-49.
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© 2019 Elsevier B.V. Image super-resolution aims to generate high-resolution image based on the given low-resolution image and to recover the details of the image. The common approaches include reconstruction-based methods and interpolation-based methods. However, these existing methods show difficulty in processing the regions of an image with complicated texture. To tackle such problems, fractal geometry is applied on image super-resolution, which demonstrates its advantages when describing the complicated details in an image. The common fractal-based method regards the whole image as a single fractal set. That is, it does not distinguish the complexity difference of texture across all regions of an image regardless of smooth regions or texture rich regions. Due to such strong presumption, it causes artificial errors while recovering smooth area and texture blurring at the regions with rich texture. In this paper, the proposed method produces rational fractal interpolation model with various setting at different regions to adapt to the local texture complexity. In order to facilitate such mechanism, the proposed method is able to segment the image region according to its complexity which is determined by its local fractal dimension. Thus, the image super-resolution process is cast to an optimization problem where local fractal dimension in each region is further optimized until the optimization convergence is reached. During the optimization (i.e. super-resolution), the overall image complexity (determined by local fractal dimension) is maintained. Compared with state-of-the-art method, the proposed method shows promising performance according to qualitative evaluation and quantitative evaluation.

Yao, Y, Shen, F, Zhang, J, Liu, L, Tang, Z & Shao, L 2019, 'Extracting Multiple Visual Senses for Web Learning', IEEE Transactions on Multimedia, vol. 21, no. 1, pp. 184-196.
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© 1999-2012 IEEE. Labeled image datasets have played a critical role in high-level image understanding. However, the process of manual labeling is both time consuming and labor intensive. To reduce the dependence on manually labeled data, there have been increasing research efforts on learning visual classifiers by directly exploiting web images. One issue that limits their performance is the problem of polysemy. Existing unsupervised approaches attempt to reduce the influence of visual polysemy by filtering out irrelevant images, but do not directly address polysemy. To this end, in this paper, we present a multimodal framework that solves the problem of polysemy by allowing sense-specific diversity in search results. Specifically, we first discover a list of possible semantic senses from untagged corpora to retrieve sense-specific images. Then, we merge visual similar semantic senses and prune noise by using the retrieved images. Finally, we train one visual classifier for each selected semantic sense and use the learned sense-specific classifiers to distinguish multiple visual senses. Extensive experiments on classifying images into sense-specific categories and reranking search results demonstrate the superiority of our proposed approach.

Ye, J, Yang, X, Xu, M, Chan, PK-S & Ma, C 2019, 'Novel N-Substituted oseltamivir derivatives as potent influenza neuraminidase inhibitors: Design, synthesis, biological evaluation, ADME prediction and molecular docking studies', European Journal of Medicinal Chemistry, vol. 182, pp. 111635-111635.
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Ye, X, Yang, Z, Zhu, J & Guo, Y 2019, 'Modeling and Operation of a Bearingless Fixed-Pole Rotor Induction Motor', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-4.
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© 2002-2011 IEEE. The rotor currents are induced by both suspension force winding magnetic field and torque winding magnetic field in the traditional bearingless induction motors (BIMs). Due to the currents induced by the suspension force winding, there are errors in the generation of radial suspension forces. To address such problems, a novel BIM with fixed-pole rotor, called bearingless fixed-pole rotor induction (BFPRI) motor is proposed. The structure of BFPRI motor is first analyzed and the mathematical models of radial suspension forces are deduced. Based on the finite element analysis, the induced currents and radial suspension forces are also investigated and compared with the traditional BIM. Finally, the prototype motor is built and experimental research is carried out. In this novel motor, only the torque winding magnetic field induces currents in the rotor, which makes the precision of radial suspension forces higher and thereby reduces the complexity of BIM control system. The effectiveness of the proposed BFPRI motor is validated by both simulation and experiments.

Yu, P, Wen, Q, Ni, W, Li, W, Sun, C, Zhang, H & Jin, Z 2019, 'Decentralized, Revocable and Verifiable Attribute-Based Encryption in Hybrid Cloud System', Wireless Personal Communications, vol. 106, no. 2, pp. 719-738.
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Cloud can provide storage space and services for data owners to host their data, where data privacy and confidentiality become critical issues. Ciphertext policy attribute-based encryption (CP-ABE) is one of the most suitable methods to protect data privacy and provide structured access control. In this paper, we propose a multi-authority CP-ABE scheme with a direct attribute revocation mechanism, cause revocation is an inevitable problem in the application process. Under our proposed revocation mechanism, the remaining users need not to update their secret keys when revocation happens. It relies on the matching of public keys’ version and ciphertext’ version. In a cloud storage model, the update of ciphertext is executed by public cloud, which cannot be fully trusted by data owners. In this case, we propose a hybrid CP-ABE cloud storage model aiming at solving the public cloud trust management problem. The data owners can authorize private cloud to verify whether their ciphertexts have been updated to the newest version. In addition, we prove our construction secure in selective-CPA model. Finally, we compare our scheme with similar multi-authority CP-ABE schemes from functionality, communication overhead and computation cost. The simulation results show that our scheme is more efficient than similar works in encryption, decryption and revocation stages.

Yuan, C, Tao, X, Li, N, Ni, W, Liu, RP & Zhang, P 2019, 'Analysis on Secrecy Capacity of Cooperative Non-Orthogonal Multiple Access With Proactive Jamming', IEEE Transactions on Vehicular Technology, vol. 68, no. 3, pp. 2682-2696.
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© 1967-2012 IEEE. This paper analyzes the secrecy capacity of a cooperative relaying system using non-orthogonal multiple access (NOMA). A new cooperative NOMA scheme is proposed, where the source actively sends jamming signals while the relay is forwarding, thereby enhancing the security of intended communication links. Closed-form expressions for the ergodic secrecy rate are derived in the presence of an eavesdropper. Asymptotic approximate expressions for the ergodic secrecy rate are established in high signal-to-noise ratio (SNR) regime, which provides insights on secure NOMA transmission. Numerical results reveal the critical condition, under which NOMA is able to outperform orthogonal multiple access (OMA) in terms of secrecy rate. The proposed NOMA scheme can improve the secrecy rate by about 78.1rm%.

Yuan, D, Lu, Z, Zhang, J & Li, X 2019, 'A hybrid prediction-based microgrid energy management strategy considering demand-side response and data interruption', International Journal of Electrical Power & Energy Systems, vol. 113, pp. 139-153.
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Yuan, W, Wu, N, Guo, Q, Huang, X, Li, Y & Hanzo, L 2019, 'TOA-Based Passive Localization Constructed Over Factor Graphs: A Unified Framework', IEEE Transactions on Communications, vol. 67, no. 10, pp. 6952-6965.
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© 2019 IEEE. Passive localization based on time of arrival (TOA) measurements is investigated, where the transmitted signal is reflected by a passive target and then received at several distributed receivers. After collecting all measurements at receivers, we can determine the target location. The aim of this paper is to provide a unified factor graph-based framework for passive localization in wireless sensor networks based on TOA measurements. Relying on the linearization of range measurements, we construct a Forney-style factor graph model and conceive the corresponding Gaussian message passing algorithm to obtain the target location. It is shown that the factor graph can be readily modified for handling challenging scenarios such as uncertain receiver positions and link failures. Moreover, a distributed localization method based on consensus-aided operation is proposed for a large-scale resource constrained network operating without a fusion center. Furthermore, we derive the Cramér-Rao bound (CRB) to evaluate the performance of the proposed algorithm. Our simulation results verify the efficiency of the proposed unified approach and of its distributed implementation.

Yuan, X, Feng, Z, Ni, W, Wei, Z, Liu, RP & Zhang, JA 2019, 'Secrecy Rate Analysis Against Aerial Eavesdropper', IEEE Transactions on Communications, vol. 67, no. 10, pp. 7027-7042.
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© 2019 IEEE. This paper studies the threat that an aerial eavesdropper can pose to terrestrial wireless communications, from an information-theoretic point of view. The achievable ergodic and the average ϵ-outage secrecy rates with no channel state information at the transmitter (i.e., with no CSIT) are analyzed for a transmitter-receiver pair on the ground, in the presence of an aerial eavesdropper which flies a random trajectory following a smooth turn (ST) mobility model in a three-dimensional (3D) space. The ST mobility model induces a uniform distribution (of the eavesdropper's waypoints) within the considered 3D volume. Closed-form asymptotic approximations of the achievable secrecy rates are derived based on the almost sure convergence and non-trivial mathematical manipulations. Validated by simulations, our analysis is tight and reveals that the ground transmission is particularly vulnerable to aerial eavesdropping which can be carried out in a distance without being noticed. 3D spherical regions are identified, within which the secrecy rates vanish. This sheds useful insights to protect terrestrial wireless networks from aerial eavesdropping.

Zdankowski, P, McGloin, D & Swedlow, JR 2019, 'Full volume super-resolution imaging of thick mitotic spindle using 3D AO STED microscope', Biomedical Optics Express, vol. 10, no. 4, pp. 1999-1999.
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© 2019 Optical Society of America under the terms of the OSA Open Access Publishing. Stimulated emission depletion (STED) nanoscopy is one of a suite of modern optical microscopy techniques capable of bypassing the conventional diffraction limit in fluorescent imaging. STED makes use of a spiral phase mask to enable 2D super-resolution imaging whereas to achieve full volumetric 3D super-resolution an additional bottle-beam phase mask must be applied. The resolution achieved in biological samples 10 μm or thicker is limited by aberrations induced mainly by scattering due to refractive index heterogeneity in the sample. These aberrations impact the fidelity of both types of phase mask, and have limited the application of STED to thicker biological systems. Here we apply an automated adaptive optics solution to correct the performance of both STED masks, enhancing robustness and expanding the capabilities of this nanoscopic technique. Corroboration in terms of successful high-quality imaging of the full volume of a 15μm mitotic spindle with resolution of 50nm x 50nm x 150nm achieved in all three dimensions is presented.

Zeng, J, Lv, T, Liu, RP, Su, X, Beaulieu, NC & Guo, YJ 2019, 'Linear Minimum Error Probability Detection for Massive MU-MIMO With Imperfect CSI in URLLC', IEEE Transactions on Vehicular Technology, vol. 68, no. 11, pp. 11384-11388.
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© 1967-2012 IEEE. It is challenging to realize ultra-reliable and low latency communications (URLLC) under severe shadow fading and imperfect channel state information (CSI). However, reliability can be increased by exploiting space diversity from multiple receive antennas rather than retransmission with limited latency. Massive multi-user multiple-input-multiple-output (MU-MIMO) is studied to enable URLLC with imperfect CSI from least-square channel estimation. The linear minimum error probability (MEP) detector with a given length of pilots (LoP) is derived. Further, the LoP is optimized to minimize the error probability of the uplink with a limited number of channel uses, using the finite blocklength information theory and one-dimensional search methods. Numerical results verify that the proposed linear MEP detection incorporated in massive MU-MIMO improves reliability with limited latency and imperfect CSI.

Zeng, J, Lv, T, Ni, W, Liu, RP, Beaulieu, NC & Guo, YJ 2019, 'Ensuring Max–Min Fairness of UL SIMO-NOMA: A Rate Splitting Approach', IEEE Transactions on Vehicular Technology, vol. 68, no. 11, pp. 11080-11093.
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Zhan, Y, Guo, Y, Zhu, J, Liang, B & Yang, B 2019, 'Comprehensive influences measurement and analysis of power converter low frequency current ripple on PEM fuel cell', International Journal of Hydrogen Energy, vol. 44, no. 59, pp. 31352-31359.
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© 2019 Hydrogen Energy Publications LLC To deeply understand the influences of power converter's low frequency current ripple (LFCR) and harmonics on a proton exchange membrane fuel cell (PEMFC) in its power conditioning system (PCS), a comprehensive measurement and analysis of the influences of LFCR and harmonics on PEMFC's performance and durability is investigated in this paper. Based on an equivalent circuit model of PEMFC stack and a mechanism model for evaluating the LFCR effects on the PEMFC, this paper studies primarily and systematically the comprehensive influences of LFCR and harmonics on PEMFC performances and durability, such as (1) degrading the PEMFC performance, (2) shortening the lifetime of PEMFC, (3) reducing the stack output power, (4) lowing its availability efficiency, (5) producing more heat and raising the PEMFC temperature, (6) consuming more fuel, and (7) decreasing the fuel utilization. Finally, a Horizon 300 W PEMFC stack is implemented and tested.

Zhang, G, Tao, J, Qiu, X & Burnett, I 2019, 'Decentralized Two-Channel Active Noise Control for Single Frequency by Shaping Matrix Eigenvalues', IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 1, pp. 44-52.
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© 2014 IEEE. In an active noise control (ANC) system, computational complexity is one major concern when designing practical control algorithms. For an ANC system with multiple secondary sources and error microphones, one approach to reducing computational complexity is to apply a decentralized control scheme rather than centralized approaches. A decentralized scheme attempts to control a number of small-size ANC subsystems independently. In this paper, we consider the decentralized control of a two-channel ANC system tackling a noise disturbance in the frequency domain, where each channel consists of one secondary source and one error microphone. We propose a decentralized control method that is able to achieve the same noise reduction performance as the centralized controller with guaranteed convergence. The key step in designing the control method is to properly shape the eigenvalues of a matrix that models the two-channel secondary paths for each frequency index.

Zhang, J, Li, L, Dorrell, DG & Guo, Y 2019, 'Modified PI controller with improved steady-state performance and comparison with PR controller on direct matrix converters', Chinese Journal of Electrical Engineering, vol. 5, no. 1, pp. 53-66.
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This paper proposes a modified proportional-integral (PI) controller and compares it with a proportional-resonant (PR) controller. These controllers are tested on a three-phase direct matrix converter (MC). The modified PI controller involves current feedforward together with space vector modulation (SVM) to control the MC output currents. This controller provides extra control flexibility in terms of the current error reduction, and it gives improved steady-state tracking performance. When the coefficient of current feedforward is equal to the load resistor (K = R), the steady-state error is effectively minimized even when regulating sinusoidal variables. The total harmonic distortion is also reduced. In order to comparatively evaluate the modified PI controller, a PR controller is designed and tested. Both the modified PI and PR controllers are implemented in the natural frame (abc) in a straightforward manner. This removes the coordinate transformations that are required in the stationary (αβ) and synchronous (dq) reference frame based control strategies. In addition, both controllers can handle the unbalanced conditions. The experimental and simulation results verify the feasibility and effectiveness of the proposed controllers.

Zhang, J, Li, L, Dorrell, DG, Norambuena, M & Rodriguez, J 2019, 'Predictive Voltage Control of Direct Matrix Converters With Improved Output Voltage for Renewable Distributed Generation', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 296-308.
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© 2013 IEEE. This paper proposes a predictive voltage control strategy for a direct matrix converter used in a renewable energy distributed generation (DG) system. A direct matrix converter with LC filters is controlled in order to work as a stable voltage supply for loads. This is especially relevant for the stand-alone operation of a renewable DG where a stable sinusoidal voltage, with desired amplitude and frequency under various load conditions, is the main control objective. The model predictive control is employed to regulate the matrix converter so that it produces stable sinusoidal voltages for different loads. With predictive control, many other control objectives, e.g., input power factor, common-mode voltage, and switching frequency, can be achieved depending on the application. To reduce the number of required measurements and sensors, this paper utilizes observers and makes the use of the switch matrices. In addition, the voltage transfer ratio can be improved with the proposed strategy. The controller is tested under various conditions including intermittent disturbance, nonlinear loads, and unbalanced loads. The proposed controller is effective, simple, and easy to implement. The simulation and experimental results verify the effectiveness of the proposed scheme and control strategy. This proposed scheme can be potentially used in microgrid applications.

Zhang, J, Norambuena, M, Li, L, Dorrell, D & Rodriguez, J 2019, 'Sequential Model Predictive Control of Three-Phase Direct Matrix Converter', Energies, vol. 12, no. 2, pp. 214-214.
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The matrix converter (MC) is a promising converter that performs the direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful tool for power electronic converters, including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the generalized sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required. Compared with the standard MPC, the computation burden is reduced because only the pre-selected switch states are evaluated in the second and subsequent sequential cost functions. In addition, the prediction model computation for the following cost functions is also reduced. Specifying the priority for control objectives can be achieved. A comparative study with traditional MPC is carried out both in simulation and an experiment. Comparable control performance to the traditional MPC is achieved. This controller is suitable for the MC because of the reduced computational burden. Simulation and experimental results verify the effectiveness of the proposed strategy.

Zhang, J, Wu, Q, Zhang, J, Shen, C, Lu, J & Wu, Q 2019, 'Heritage image annotation via collective knowledge', Pattern Recognition, vol. 93, pp. 204-214.
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© 2019 Elsevier Ltd The automatic image annotation can provide semantic illustrations to understand image contents, and builds a foundation to develop algorithms that can search images within a large database. However, most current methods focus on solving the annotation problem by modeling the image visual content and tag semantic information, which overlooks the additional information, such as scene descriptions and locations. Moreover, the majority of current annotation datasets are visually consistent and only annotated by common visual objects and attributes, which makes the classic methods vulnerable to handle the more diverse image annotation. To address above issues, we propose to annotate images via collective knowledge, that is, we uncover relationships between the image and its neighbors by measuring similarities among metadata and conduct the metric learning to obtain the representations of image contents, we also generate semantic representations for images given collective semantic information from their neighbors. Two representations from different paradigms are embedded together to train an annotation model. We ground our model on the heritage image collection we collected from the library online open data. Annotations on the heritage image collection are not limited to common visual objects, and are highly relevant to historical events, and the diversity of the heritage image content is much larger than the current datasets, which makes it more suitable for this task. Comprehensive experimental results on the benchmark dataset indicate that the proposed model achieves the best performance compared to baselines and state-of-the-art methods.

Zhang, R, Mu, C, Xu, M, Xu, L & Xu, X 2019, 'Facial Component-Landmark Detection With Weakly-Supervised LR-CNN', IEEE Access, vol. 7, pp. 10263-10277.
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Zhang, R, Mu, C, Xu, M, Xu, L, Shi, Q & Wang, J 2019, 'Synthetic IR Image Refinement Using Adversarial Learning With Bidirectional Mappings', IEEE Access, vol. 7, pp. 153734-153750.
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© 2019 IEEE. Collecting a large dataset of real infrared (IR) images is expensive, time-consuming, and even unavailable in some specific scenarios. With recent progress in machine learning, it has become more feasible to replace real IR images with qualified synthetic IR images in learning-based IR systems. However, this alternative may fail to achieve the desired performance, due to the gap between real and synthetic IR images. Inspired by adversarial learning for image-to-image translation, we propose the Synthetic IR Refinement Generative Adversarial Network (SIR-GAN) to narrow this gap. By learning the bidirectional mappings between two unpaired domains, the realism of the simulated IR images generated from the IR Simulator are significantly improved, where the source domain contains a large number of simulated IR images, where the target domain contains a limited quantity of real IR images. Specifically, driven by the idea of transferring infrared characteristic and protect target semantic information simultaneously, we propose a SIR refinement loss to consider an infrared loss and a structure loss further to the adversarial loss and the consistency loss. To further reduce the gap, stabilize training, and avoid artefacts, we modify the proposed algorithm by developing a training strategy, adding the U-net in the generators, using the dilated convolution in the discriminators and invoking the N-Adam acts as the optimizer. Qualitative, quantitative, and ablation study experiments demonstrate the superiority of the proposed approach compared with the state-of-the-art techniques in terms of realism and fidelity. In addition, our refined IR images are evaluated in the context of a feasibility study, where the accuracy of the trained classifier is significantly improved by adding our refined data into a small real-data training set.

Zhang, W, Liu, T, Ye, L, Ueland, M, Forbes, SL & Su, SW 2019, 'A novel data pre-processing method for odour detection and identification system', Sensors and Actuators A: Physical, vol. 287, pp. 113-120.
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© 2018 Elsevier B.V. This paper presents a novel electronic nose (E-nose) data pre-processing method, based on a recently developed non-parametric kernel-based modelling (KBM) approach. The proposed method is tested by an automated odour detection and classification system, named “NOS.E” developed by the NOS.E team in University of Technology Sydney. Experimental results show that when extracting the derivative-related features from signals collected by the NOS.E, the proposed non-parametric KBM odour data pre-processing method achieves more reliable and stable pre-processing results comparing with other pre-processing methods such as wavelet package correlation filter (WPCF), mean filter (MF), polynomial curve fitting (PCF) and locally weighted regression (LWR). Based on these derivative-related features, the NOS.E can achieve a 96.23% accuracy of classification with the popular Support Vector Machine (SVM) classifier.

Zhang, X, Zhang, S, Lin, J, Sun, F, Zhu, X, Yang, Y, Tong, X & Yang, H 2019, 'An Efficient Seismic Data Acquisition Based on Compressed Sensing Architecture With Generative Adversarial Networks', IEEE Access, vol. 7, pp. 105948-105961.
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© 2013 IEEE. Recently, large scale seismic data acquisition has been a critical method for scientific research and industrial production. However, due to the bottleneck on data transmission and the limitation of energy storage, it is hard to conduct large seismic data acquisition in a real-time way. So, in this paper, an efficient seismic data acquisition method, namely, compressed sensing architecture with generative adversarial networks (CSA-GAN), is proposed to tackle the two restrictions of collecting large scale seismic data. In the CSA-GAN, a data collection architecture based on compressed sensing theory is applied to reduce data traffic load of the whole system, as well as balance the data transmission. To make the compressed sensing procedure perform well in both data quality and compression ratio, a kind of generative adversarial networks is designed to learn the recovering map. According to our experiment results, a high data quality (about 30 dB) at the compression ratio of 16 is achieved by the proposed approach, which enables the system to afford 15 times more sensors and reduces the energy cost by means of data collection from N(N + 1)/2 to N2/16. These results show that the CSA-GAN can afford more sensors with the same bandwidth and consume less energy, via improving the efficiency seismic data acquisition.

Zhao, J, Mou, Q, Guo, K, Liu, X, Li, J & Guo, Y 2019, 'Reduction of the Detent Force in a Flux-Switching Permanent Magnet Linear Motor', IEEE Transactions on Energy Conversion, vol. 34, no. 3, pp. 1695-1705.
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IEEE In this paper, the detent force caused by the end effect in a flux-switching permanent magnet linear motor (FSPMLM) with 6 slots and 5 poles is investigated and reduced by two different methods. Firstly, the detent force is diminished by adjusting the position of end teeth of primary side and injecting compensation current into compensation windings wound around the end teeth. Based on the linear relationship between compensation current and compensation force, the proper compensation current is derived and analyzed. Then, to avoid the magnetic coupling between compensation windings and phase windings, a novel compensation module with independent magnet circuit is presented and attached to the primary side of FSPMLM. Thirdly, the two detent force reduction methods are compared with each other, and the compensation module is proved to be more effective. Finally, a prototype of FSPMLM with compensation modules is manufactured and tested to validate the proposed compensation method.

Zhou, W, Sutton, GJ, Andrew Zhang, J, Liu, RP & Pan, S 2019, 'Delay-Guaranteed Admission Control for LAA Coexisting With WiFi', IEEE Wireless Communications Letters, vol. 8, no. 4, pp. 1048-1051.
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© 2012 IEEE. Licensed-assisted-access (LAA) is used to extend the LTE link into the unlicensed band. How to guarantee the quality-of-service (QoS) for LTE devices in the unlicensed band is a challenging problem due to the listen-before-talk contention access in 5-GHz unlicensed bands. In this letter, we quantitatively analyze the medium access control delay for tagged LAA eNBs and propose a delay-guaranteed admission control scheme. We consider the freezing time of busy slots caused by collision or successful transmission, and introduce the exponential backoff mechanism for delay analysis. Validated by simulation results, our method provides important insights into the system admission performance and fairness of access.

Zhu, G, Liu, X, Li, L, Chen, H, Tong, W & Zhu, J 2019, 'Cooling System Design of a High-Speed PMSM Based on a Coupled Fluidic–Thermal Model', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2, pp. 1-5.
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© 2002-2011 IEEE. To avoid overheating of a totally enclosed high-speed permanent magnet synchronous machine (PMSM) with an amorphous alloy core, this paper proposes a hybrid cooling system with both radial and axial vents to maintain the temperature rise below the rated value. The analytical models of cooling ability and frictional loss generated in the rotor ducts are derived in relation to the cooling structure parameters. The sensitivity of each parameter to the cooling effect is researched, and the parameter scopes are then determined. A coupled fluidic-thermal model based on the cell method is developed to predict numerically the temperature distribution to check the effectiveness of the cooling system. By analyzing the influences of the numbers and sizes of the cooling ducts on the efficient cooling air quantity and temperature, the feasible parameters that yield reasonable temperature distribution can be determined. The theoretical results are confirmed by experimental test results on a 15-kW 30 000-r/min PMSM prototype.

Zhu, H & Guo, YJ 2019, 'Wideband Filtering Phase Shifter Using Transversal Signal-Interference Techniques', IEEE Microwave and Wireless Components Letters, vol. 29, no. 4, pp. 252-254.
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© 2001-2012 IEEE. A wideband filtering phase shifter is presented in this letter using transversal signal-interference techniques. The proposed structure creates two signal-propagation paths by introducing extra coupling between two short-ended stubs. Cascaded coupled-line sections and parallel short-ended stubs can generate a constant passband and multiple transmission zeros (TZs) in the stopband and meanwhile provide the arbitrary value of phase shift within the filtering band range. The positions of TZs and phase shift range can be easily controlled. Explicit relations between the objective filtering band and the related parameters are given, and cases with different in-band phase shift values are studied. To validate the design, a prototype is built, simulated, and tested using microstrip lines. The experimental results agree with the predicted ones, demonstrating that the device can realize any given in-band phase shift with a wideband filtering response.

Zhu, H, Cheng, Z & Guo, YJ 2019, 'Design of Wideband In-Phase and Out-of-Phase Power Dividers Using Microstrip-to-Slotline Transitions and Slotline Resonators', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 4, pp. 1412-1424.
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© 2019 IEEE. A new class of in-phase and out-of-phase power dividers with constant equal-ripple frequency response and wide operating bandwidth is presented in this paper. The proposed design is based on microstrip-to-slotline transitions and slotline resonators. A slotted T-junction is adopted to split the power into two parts and obtain wideband isolation between the two output signals at the same time. The characteristic impedance of the transitions and resonators determines the operating bandwidth and in-band magnitude response. By reversing the placement direction of the slotline-to-microstrip transition, the electrical field is reversed, thus resulting in out-of-phase responses between output ports. A thorough analysis of the relations between the structure and the characteristic functions is provided to guide the selection of parameters of the structure in order to meet the design objectives. In the structure, simulation and measurement are conducted to verify the design method. For both in-phase and out-of-phase cases, more than 110% bandwidth has been achieved with excellent matching at all ports and isolation of output signals. Constant in-band ripple is obtained within the operating band of the power dividers, indicating that the proposed design can realise minimal power deviations, which is extremely desired in wireless systems.

Zhu, H, Lin, J-Y & Guo, YJ 2019, 'Filtering Balanced-to-Single-Ended Power Dividers With Wide Range and High Level of Common-Mode Suppression', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 12, pp. 5038-5048.
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© 1963-2012 IEEE. A new design approach for developing balanced-to-single-ended (BTSE) power dividers (PDs) to achieve high-level and wide range of common-mode (CM) suppression and minimum mode-conversion level is presented. The suppression of CM signals and mode conversion is realized by a microstrip-to-slotline transition, which is due to the orthogonality between the electric field of the microstrip line and slotline. Filtering responses are included in the differential-mode transmission performance, and multiple transmission zeros are generated by loading shunted coupled-line stubs. A multimode slotline resonator is used to provide multiple resonances in the passband, and these resonances can be easily controlled so that the operating bandwidth can be varied in a large frequency range. Based on this design approach, several BTSE PDs with different bandwidths are simulated in the EM environment. Prototypes are fabricated and tested to verify the design. The experimental results reveal that 200% fractional bandwidth of CM suppression is obtained. The CM suppression and mode-conversion levels are below-35 dB at all frequencies, which is extremely desired in differential circuits and systems.

Zhu, H, Sun, H, Jones, B, Ding, C & Guo, YJ 2019, 'Wideband Dual-Polarized Multiple Beam-Forming Antenna Arrays', IEEE Transactions on Antennas and Propagation, vol. 67, no. 3, pp. 1590-1604.
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© 1963-2012 IEEE. Wideband multibeam antenna arrays based on three-beam Butler matrices are presented in this paper. The proposed beam-forming arrays are particularly suited to increasing the capacity of 4G long-term evolution (LTE) base stations. Although dual-polarized arrays are widely used in LTE base stations, analog beam-forming arrays have not been realized before, due to the huge challenge of achieving wide operating bandwidth and stable array patterns. To tackle these problems, for the first time, we present a novel wideband multiple beam-forming antenna array based on Butler matrices. The described beam-forming networks produce three beams but the methods are applicable to larger networks. The essential part of the beam-forming array is a wideband three-beam Butler matrix, which comprises quadrature couplers and fixed wideband phase shifters. Wideband quadrature and phase shifters are developed using striplines, which provide the required power levels and phase differences at the outputs. To achieve the correct beamwidth and to obtain the required level of crossover between adjacent beams, beam-forming networks consisting of augmented three-beam Butler matrices using power dividers are presented to expand the number of output ports from three to five or six. Dual-polarized, three-beam antenna arrays with five and six elements covering LTE band are developed. Prototypes comprising beam-forming networks and arrays are tested according to LTE base station specification. The test results show close agreement with the simulation ones and compliance with LTE requirements. The designs presented are applicable to a wide range of wideband multibeam arrays.

Zhu, Q, Coleman, P, Qiu, X, Wu, M, Yang, J & Burnett, I 2019, 'Robust Personal Audio Geometry Optimization in the SVD-Based Modal Domain', IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 3, pp. 610-620.
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© 2014 IEEE. Personal audio generates sound zones in a shared space to provide private and personalized listening experiences with minimized interference between consumers. Regularization has been commonly used to increase the robustness of such systems against potential perturbations in the sound reproduction. However, the performance is limited by the system geometry such as the number and location of the loudspeakers and controlled zones. This paper proposes a geometry optimization method to find the most geometrically robust approach for personal audio amongst all available candidate system placements. The proposed method aims to approach the most 'natural' sound reproduction so that the solo control of the listening zone coincidently accompanies the preferred quiet zone. Being formulated in the SVD-based modal domain, the method is demonstrated by applications in three typical personal audio optimizations, i.e., the acoustic contrast control, the pressure matching, and the planarity control. Simulation results show that the proposed method can obtain the system geometry with better avoidance of 'occlusion,' improved robustness to regularization, and improved broadband equalization.

秀聡, 高, 奎太, 石, 浩永, 丸, 俊之, 田, 紗季, 野, 亮, 岡, Schell, A, Tran, TT, Aharonovich, I & 繁樹, 竹 2019, '六方晶窒化ホウ素中の単一結晶欠陥の双極子方向解析 Analysis of the dipole orientation of single defects in hexagonal boron nitrides', JSAP Annual Meetings Extended Abstracts, pp. 566-566.
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Abdollahi, M, Abolhasan, M, Shariati, N, Lipman, J, Jamalipour, A & Ni, W 1970, 'A Routing Protocol for SDN-based Multi-hop D2D Communications', 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC), IEEE, USA, pp. 895-898.
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© 2019 IEEE. This paper presents a new Multi-hop Device-to-Device (MD2D) routing protocol, referred to as SMDRP (SDN-based Multi-hop D2D Routing Protocol), for SDN-based wireless networks. Our proposed protocol can be considered as a semi-distributed routing protocol, where an SDN controller manages and controls part of the overall MD2D routing functionality to increase scalability while enabling network operators to control and maintain the out-of-band packet forwarding network. This paper also extends prior work on the Hybrid SDN Architecture for Wireless Distributed Networks (HSAW) [1] and is adapted to the framework presented in this paper. In HSAW, since all link state information is flooded by the controller to the nodes, the network will experience scalability problem. In our approach, this problem is overcome by only passing the next hop for each active route to the mobile nodes. To investigate this, we performed a theoretical and simulation studies comparing HSAW with SMDRP. From our result, it can be seen that for larger density populated networks, SMDRP shows better scalability than HSAW. In addition, mobile nodes need less memory and energy for their communications.

Abeywickrama, HV, He, Y, Dutkiewicz, E & Jayawickrama, BA 1970, 'An Adaptive UAV Network for Increased User Coverage and Spectral Efficiency', 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, Marrakesh, Morocco.
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© 2019 IEEE. Unmanned Aerial Vehicles (UAVs) are fast becoming a popular choice in a variety of applications in wireless communication systems. UAV-mounted base stations (UAV-BSs) are an effective and cost-efficient solution for providing wireless connectivity where fixed infrastructure is not available or destroyed. We present a method of using UAV-BSs to provide coverage to mobile users in a fixed area. We propose an algorithm for predicting the user locations based on their mobility data and clustering the predicted locations, so that one UAV-BS would provide coverage to one user cluster. The proposed method, hence is similar to the UAV-BSs following the users to keep them under the coverage region. Simulation results show that the proposed method increases the user coverage by 47%-72% and increases the spectral efficiency by 43%-55% depending on the scenario and in addition, reduces the number of UAV-BSs required to provide coverage.

Abuhilaleh, M, Li, L, Zhu, J & Hossain, MJ 1970, 'Distributed Control and Power Management Strategy for Parallel Bidirectional Power Converters in Hybrid Microgrids', IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society, IEEE, Lisbon, Portugal.
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This paper presents a new approach of distributed coordinated control for multiple interlinking converters (ILCs) to regulate the power flow across the hybrid AC/DC microgrid composed of AC and DC sub-microgrids (SMGs). These SMGs are linked together by multiple parallel ILCs that are operated as bidirectional power converters. The proposed control system not only allows reliable management and control of the power flow between SMGs but also regulates the DC voltage for the DC SMGs as part of the process. One of the key gains of this structure is the mitigation of the circulating current that results from the parallel operation of the converters. Although the circulating current is more present at the AC side, it can also exist on the DC side. At the AC side, this is achieved through the implementation of the d-q-0 axis control strategy. The presented outer control loop is a modified arrangement that could not only ensure accurate power sharing but also suppress the circulating current at the DC side.

Acuna, P, Ghias, A, Aguilera, RP, Lezana, P, Mcgrath, B, Merabet, A & Jayan, V 1970, 'Sequential Phase-Shifted Model Predictive Control for a Five-Level Flying Capacitor Converter', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, Australia, pp. 533-538.
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© 2019 IEEE. This paper extends previous work on the Sequential Phase-Shifted Model Predictive Control (SPS-MPC) strategy into a Single-Phase Five-Level Flying Capacitor Converter (SP-FL-FCC). The use of SPS-MPC in an FL-FCC is not as straightforward as it first seems. Therefore, a sequential average model based on more than one active control input is derived. The proposed SPS-MPC strategy achieves a fixed switching frequency, which is beneficial regarding of semiconductor loss distribution, and also to ensure that a high-bandwidth is achieved that compares favorably to the finite-control-set MPC case. Simulation results of the proposed SPS-MPC strategy validate the current and FC voltages tracking control during the transient and steady-state conditions at a fixed switching frequency.

Afzal, M, Lalbakhsh, A, Koli, NY & EsseIle, KP 1970, 'Antenna Beam Steering by Near-Field Phase Transformation: Comparison between Phase Transforming Printed Metasurfaces and Graded-Dielectric Plates', PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA), 21st International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, SPAIN, Granada, pp. 593-595.
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Afzal, MU, Lalbakhsh, A & Esselle, KP 1970, 'Compact Beam-Steered Resonant-Cavity Antenna Using Near-Field Phase Transformation', 2019 14th Conference on Industrial and Information Systems (ICIIS), 2019 IEEE 14th Conference on Industrial and Information Systems (ICIIS), IEEE.
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Afzal, MU, Lalbakhsh, A, Hayat, T & Esselle, KP 1970, 'Recent Progress on Development of Near-Field Structures for Radio-Frequency Front-End Antennas', 2019 23rd International Conference on Applied Electromagnetics and Communications (ICECOM), 2019 23rd International Conference on Applied Electromagnetics and Communications (ICECOM), IEEE.
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© 2019 IEEE. The theory of near-field phase transformation equips antenna designers with a tool to carry out more accurate electric field transformation, for even geometrically complex radiating structures, within the near-field region. The theory has now been demonstrated with a range of free-standing structures or surfaces, designed using dielectrics or printed planar metasurfaces. The development on the near-field structures can be divided into three phases. The first phase was focused on narrow frequency band for demonstrating the concept. The second phase of the development is to increase the bandwidth of near-field structures that can cover frequency band required for commercial wireless applications. In the third phase, the overall cost of near-field structures is drastically reduced using advanced manufacturing technique such as additive manufacturing. Some of the highlights of the developments in near-field structures include increasing broadside gain of classical resonant-cavity antennas by ~ 9 dB and realization of antenna beam steering in a conical region having an apex angle of 102 °.

Afzal, MU, Lalbakhsh, A, Koli, NY & Esselle, KP 1970, 'Antenna Beam Steering by Near-Field Phase Transformation: Comparison between Phase Transforming Printed Metasurfaces and Graded-Dielectric Plates', 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, pp. 593-595.
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© 2019 IEEE. The antenna beam-steering technique based on near-field phase transformation yields antenna systems that have superior characteristics compared to the traditional methods including both mechanical and electronic. Some of the unique attributes associated with this technology are its totally passive nature, low height profile, and extremely simple operating mechanism. The technology has been used to develop two generations of antenna systems. The first generation was developed using multilayered printed metasurfaces (PMs) and the second generation used graded-dielectric plates (GDPs). In terms of radiation performance, the two antenna systems are nearly identical. The height profile of a GDP based antenna is about one free-space wavelength more than the height of a PM based antenna. PMs can only be manufactured in specialised facilities while with rapid advancements in materials and 3D printing, it may be possible to cheaply develop GDPs.

Aguilera, RP, Acuna, P, Rojas, CA, Konstantinou, G & Pou, J 1970, 'Instantaneous Zero Sequence Voltage for Grid Energy Balancing Under Unbalanced Power Generation', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, pp. 2572-2577.
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An instantaneous zero sequence voltage injection method is presented in this paper. The key novelty of this method lies in the ability to provide instantaneous zero sequence voltage references using stationary abc-framework variables with no numerical iterations and no phase-locked loops. This paper discusses its applicability, especially in the field of large-scale photovoltaic power plants integration, where the efforts are made to achieve grid energy balancing. As an application example, the proposed method is used to find suitable zero sequence voltage references to extract unbalanced power from each phase in star-connected cascaded H-bridge multilevel converters. Under same conditions, the proposed method allows reactive power control, in contrast to traditional approaches that only consider unity power factor operation. Experimental results are provided to verify the effectiveness of the proposed zero sequence voltage injection method.

Alanazi, F, Gay, V & Alturki, R 1970, 'Tag Based Recommendation Systems for Tourism in Saudi Arabia', VISION 2025: EDUCATION EXCELLENCE AND MANAGEMENT OF INNOVATIONS THROUGH SUSTAINABLE ECONOMIC COMPETITIVE ADVANTAGE, 34th International-Business-Information-Management-Association (IBIMA) Conference, INT BUSINESS INFORMATION MANAGEMENT ASSOC-IBIMA, Madrid, SPAIN, pp. 6492-6500.

Aljarajreh, H, Lu, DD-C & Tse, CK 1970, 'Synthesis of Dual-Input Single-Output DC/DC Converters', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, Japan.
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© 2019 IEEE This paper presents a topological study using power flow diagrams to derive all possible basic and non-isolated double-input single-output (DISO) converters. Unlike most reported DISO converters with one bidirectional port, this paper considers up to two bidirectional ports. The paper focuses on providing a general guideline of all power flow combinations and corresponding converter configurations. After eliminating the impractical configurations due to their indirect connection to some ports and their multiple conversion stages, three converter configurations have been identified and corresponding circuit realizations are demonstrated.

Alsmadi, L, Kong, X & Sandrasegaran, K 1970, 'Improve Indoor Positioning Accuracy Using Filtered RSSI and Beacon Weight Approach in iBeacon Network', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Ho Chi Minh City, Vietnam.
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Increasing the location accuracy of the Indoor Positioning System (IPS) is an important research area in localization. Utilizing mobile beacons in IPS environment has made localization more accurate and cost-effective. This paper proposes an Filtered RSSI and Beacon Weight Approach (FRBW) based on improved Received Signal Strength Indicator (RSSI) values using a Kalman filter. This algorithm takes both the distance and improved RSSI measurements between beacon nodes into consideration. Kalman filter applied on the RSSI measurements that eliminate noise of the signal and then applied on FRBW positioning algorithm. The proposed algorithm was applied using eight beacons. The results show that this FRBW approach has better positioning accuracy and minimum location error, and can be applied in IoT applications in smart city.

Alturki, R & Gay, V 1970, 'Augmented and virtual reality in mobile fitness applications: A survey', EAI International Conference on Future Intelligent Vehicular Technologies, EAI International Conference on Future Intelligent Vehicular Technologies, ISLAMABAD, PAKISTAN, pp. 67-75.
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Obesity is a major issue around the world. It is the main reason for several chronic diseases. Obesity can be stopped by encouraging people to do physical activities and making behaviour intervention regarding lifestyle. Mobile fitness apps are emerging because of the unique features that are provided. They are seen as a vital tool to motivate people suffering from obesity to perform physical activities and make behaviour intervention regarding health and fitness. Augmented reality (AR) and virtual reality (VR) technologies have been used successfully in different kinds of mobile apps. This paper presents a systematic review of some of the most recent AG and VR researches in mobile apps. It discusses the main findings of applying both technologies in different fields of mobile apps. Based on this systematic review, a fitness mobile app for obese individuals that consider both AR and VR technology will be developed.

Alturki, R & Gay, V 1970, 'Usability attributes for mobile applications: A systematic review', EAI International Conference on Future Intelligent Vehicular Technologies, EAI International Conference on Future Intelligent Vehicular Technologies, Islamabad, Pakistan, pp. 53-62.
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The usability of mobile applications (apps) is an emerging area of research because of the increasing use of mobile devices around the world. App development is challenging because each application has its own purpose, and each individual user has different needs and expectations from the apps. There are various apps available for each purpose, and the success of the application depends on its usefulness. This paper presents a systematic review of some of the most contemporary apps and highlights their usability attributes. It discusses usability models, frameworks and guidelines outlined in previous research for designing apps with enhanced usability characteristics. Based on this research, comprehensive guidelines for mobile apps’ usability can then be provided.

Al-Zu'bi, MM, Mohan, AS & Ling, SSH 1970, 'Influence of Tissue Anisotropy on Molecular Communication.', EMBC, the 41st International Engineering in Medicine and Biology Conference, IEEE, Germany, pp. 2921-2924.
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Many biological tissues inside the human body exhibit highly anisotropic diffusion properties; for example, tissues of the nervous system and white matter in the brain. Here, we present an improved molecular communication model by introducing the tissue anisotropy to model diffusive molecular channel for nanomachine communications. We present a stochastic particle-based simulation model for molecular communication in three-dimensional (3D) anisotropic diffusive biological microenvironments and validate with analytical expressions. We also derive expressions for peak amplitude and peak time for the received molecular signal. The results demonstrate that the channel impulse response in anisotropic biological media depend significantly on the diffusion tensor as well as on the locations of the nanomachines.

Amin, BMR, Rahman, MS & Hossain, MJ 1970, 'Impact Assessment of Credible Contingency and Cyber Attack on Australian 14-Generator Interconnected Power System', 2019 IEEE Power & Energy Society General Meeting (PESGM), 2019 IEEE Power & Energy Society General Meeting (PESGM), IEEE, Atlanta, GA, USA.
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© 2019 IEEE. This paper analyses the impacts of credible contingency and an event of cyber attack on the dynamic performance of a real large-scale interconnected power grid. Any credible contingency, for example, short circuit fault or unnatural behaviour of protective devices due to cyber intrusion could create catastrophic consequences and even complete blackout to the power systems. In order to protect power systems against cyber events, it is necessary to analyse the impacts of both faults and cyber attacks on the dynamic behaviour of the power system to identify cyber events from credible contingencies. In this paper, a simplified model of an Australian 14-generator interconnected system is considered as a testbed and MATLAB/Simulink Simpowersystems Toolbox is used for the analyses. A real-life incident of faults has considered as case study and an event of a cyber attack on protection relay function is simulated to explore the possible similar impacts on the same page. The systematic analyses of different properties of the system will help to design the detection and counter measure techniques to ensure the system is protected from cyber threats.

Amin, U, Hossain, MJ, Fernandez, E, Mahmud, K & Tiezheng, G 1970, 'A Contract-based Trading Model for Electricity Suppliers in Smart Grids', 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), IEEE, New Delhi, India.
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© 2019 IEEE. This paper proposes an approach to categorize electricity suppliers (ESs) for energy trading between ESs and a single aggregator. A principal-agents game model is developed to model the interactions between an aggregator and different categories of ESs by considering the benefits of both parties. In a proposed game, the aggregator as a principal will purchase a certain amount of power from different-category ESs with the cheapest pricing options available, and at the same time the ESs, acting as agents will maximize their utilities by selling their power to the aggregator instead of feeding the grid at a low rate. The developed optimal contract-based scheme, which can be implemented distributed manner, allows different-category ESs to sell their power at different prices based on their unit production cost to maximize their benefits, and the total cost to the aggregator is minimized. Numerical analysis confirms the effectiveness of the proposed ESs categorizing framework in the development of a contract-based incentive mechanism for energy trading.

Argha, A, Su, SW, Liu, Y & Celler, BG 1970, 'Control Allocation Based Sliding Mode Fault Tolerant Control', 2019 American Control Conference (ACC), 2019 American Control Conference (ACC), IEEE, Philadelphia, PA, USA, pp. 3752-3757.
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© 2019 American Automatic Control Council. This paper describes a novel fault tolerant control using robust sliding mode control strategy. This scheme can also be employed as actuator redundancy management for over-actuated uncertain linear systems. In contrast to many existing methods in the literature that assume the control input matrix is not of full rank such that it can be factorised into two matrices, this scheme can be applied to systems whose control input matrix has full rank. The so-called virtual control, in this scheme, is designed to be robust against uncertainties emanating from visibility of the control allocator to the controller and imperfection in the estimated effectiveness gain. Then using a static real-time control allocator, the obtained virtual control signal is redistributed among remaining (redundant or non-faulty) set of actuators. The proposed scheme is a unified, control allocation-based fault tolerant control which does not need to reconfigure the control system in the case of actuator fault or failure. The effectiveness of the proposed schemes is discussed with a numerical example.

Asari, AR, Guo, Y & Zhu, J 1970, 'Performances of SOMALOY 700 (5P) and SOMALOY 500 Materials under 1-D Alternating Magnetic Flux Density', 2019 International UNIMAS STEM 12th Engineering Conference (EnCon), 2019 International UNIMAS STEM 12th Engineering Conference (EnCon), IEEE, Kuching, Malaysia, pp. 52-58.
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© 2019 IEEE. In high magnetization frequency of the high speed electrical machine, core loss dissipation is a main contributor of the power loss that gives high percentage of loss compared to the other losses. Previously, the engineers has considered SOMALOY 500 as a core of electrical machine but they still aim for the lower loss magnetic material that can offer higher efficiency during the operation of the electrical machines.. There is no standardization for rotational core loss of magnetic material that needs more effort in order to predict the core loss accurately. In this paper, core loss of SOMALOY 700 (5P) is calculated and analyzed to identify the magnetic properties of that material. The magnetic properties of SOMALOY 700 (5P) material are properly measured under alternating magnetic fluxes at 50 Hz, 100 Hz, 500 Hz and 1000 Hz by using 3-D tester. The material characteristics under alternating fluxes are important to estimate the total rotational core loss in the future. LabVIEW and Mathcad software are used for the data acquisition and analysis, respectively. The performances of SOMALOY 700 (5P) are compared to SOMALOY 500 by plotting the core loss curves and hysteresis loops. The finding shows the core loss of both samples is proportional to the squared of magnetic flux density. This study also revealed that the core loss of SOMALOY 700 (5P) and SOMALOY 500 are 6 kg/Watt and 12 kg/Watt when the magnetic field is at 1.5 T. It concludes that the SOMALOY 700 (5P) offers lower core loss compared to the SOMALOY 500 and more suitable to be used in producing high performance of electrical machines. The details of core losses for both SOMALOY materials are important in order to provide the significance information to the real engineers in designing the electrical or electromagnetic machines in the future.

Ashtari, S, Tofigh, F, Abolhasan, M, Lipman, J & Ni, W 1970, 'Efficient Cellular Base Stations Sleep Mode Control Using Image Matching', 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), IEEE, Kuala Lumpur, MALAYSIA.
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© 2019 IEEE. Green cellular network helps to decrease environmental pollution. In contrast, massive connectivity and demand for higher data rate promise the presence of new generation of cellular system (5G) and small cell networks. Hence, expectation on increasing the number of base stations (BSs), which leads to increase in energy usage. One way to improve energy consumption is by shutting down the redundant BSs while sustaining the Quality-of-Service (QoS) for each user. In this paper, we propose a dynamic structural algorithm based on transportation problem, to switch on/off the BSs in cellular networks without compromising its coverage, and maintain the networks load by neighboring cells. We use weighted graphs to translate our problem as a transportation problem and then use linear programming to solve it. The cost of transport, turning a BS into sleep mode, is illustrated as a function of energy usage,coverage area and load on the BSs. Running the propose method consecutively provides the maximum number of BSs whom are at sleep mode. The methodology explained in this paper reduces energy consumption to almost 40%, whereas maintaining all the existing loads in the network.

Ayachit, A, Hasan, SU, Siwakoti, YP, Abdul-Hak, M, Kazimierczuk, MK & Blaabjerg, F 1970, 'Coupled-Inductor Bidirectional DC-DC Converter for EV Charging Applications with Wide Voltage Conversion Ratio and Low Parts Count', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 1174-1179.
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© 2019 IEEE. This paper proposes a new bidirectional dc-dc converter and presents its application for electric-vehicle (EV) charging applications. Using the benefits of a coupled-inductor, the proposed converter exhibits a wide voltage conversion ratio in both buck and boost modes, while using lesser number of components compared to other unidirectional and bidirectional converter counterparts. The steady-state analysis of the converter is presented and the steady-state waveforms are derived. The expressions for the dc voltage and current transfer functions, current and voltage stresses of the semiconductor components, and the design expressions for the converter passive components are derived. Design of a 3.2 kW, 380 V at Low-Voltage (LV) side and 48 V at High-Voltage (HV) side bidirectional converter is shown and verified by simulations. Simulation show efficiencies greater than 95% for both operating modes. A laboratory prototype of a small-scale 300 W bidirectional dc-dc converter with 40 V at LV-side and 300 V at HV-side is considered. The experimental results to support the theoretical predictions are given.

Azizivahed, A, Ghavidel, S, Ghadi, MJ, Li, L & Zhang, J 1970, 'Multi-Objective Energy Management Approach Considering Energy Storages in Distribution Networks with Respect to Voltage Security', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, pp. 661-666.
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© 2019 IEEE. The presence of electrical energy storage (EES) units in distribution systems has potentials to improve the network profiles (e.g. bus voltage and branch current profiles) as well as to reduce operational cost and power losses. This paper presents a novel approach to determine the optimal charging/discharging schedule of EES units in distribution systems by employing multi-objective optimization methods, aiming at reducing operation cost and enhancing radial distribution networks security. In this regard, a voltage stability index (VSI) to improve the radial network security is presented as a separate objective function. In order to assess effectiveness and applicability of the proposed method, it is applied to a 33-bus IEEE standard distribution test system and then the obtained results are compared with existing methodologies.

Azizivahed, A, Lotfi, H, Ghadi, MJ, Ghavidel, S, Li, L & Zhang, J 1970, 'Dynamic Feeder Reconfiguration in Automated Distribution Network Integrated with Renewable Energy Sources with Respect to the Economic Aspect', 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), IEEE, Chengdu, China, pp. 2666-2671.
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© 2019 IEEE. In distribution systems, feeder reconfiguration and capacitor switching can lead to power loss reduction, reliability improvement and keep the voltage within its allowable range. Distribution feeder reconfiguration (DFR) is an optimization problem in distribution systems which is used to improve the distribution network performance by changing the status of switches. In this study, a multi-objective framework is presented for dynamic DFR (DDFR) and capacitor switching (CS) problem in distribution networks over multiple time intervals considering distributed generators, energy storages and solar photovoltaic units. The objective functions in this problem are the operation cost and energy loss. Considering the importance of economic aspects in distribution networks in this study, the effect of demand response program (DRP) is considered to minimize the operation cost in DDFR and CS (DDFRCS) problem. Considering the inherent complexity of the DDFRCS problem, it leads to the presentation of a hybrid evolutionary algorithm to solve the proposed problem. For this purpose, this paper proposes a new hybrid evolutionary algorithm based on a combination of the particle swarm optimization and modified shuffled frog leaping algorithm to solve the multi-objective DDFRCS problem.

Bah, AO, Bird, TS & Qin, P 1970, 'A Low Profile Tightly Coupled Antenna Array with 80° Scanning for Multifunctional Applications', 2019 IEEE International Symposium on Phased Array System & Technology (PAST), 2019 IEEE International Symposium on Phased Array System & Technology (PAST), IEEE, Waltham, MA, USA.
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A wideband wide scanning antenna array for application in multifunctional phased arrays is presented. The dipoles and balun are printed on both sides of a single RT/Duroid™ 6010 substrate with a relative dielectric constant of 10.2. Optimized designs of two thicknesses of a metasurface-based wide angle impedance matching layer are presented, facilitating the highest figure of merit values in phased array antennas. The feed network, composed of meandered impedance transformer and balun sections, are constructed from Klopfenstein tapered microstrip lines. The overall height of the array above the ground plane is 0.087 $\lambda_{\mathrm{L}}$ , where $\lambda_{\mathrm{L}}$ is the wavelength at the lowest frequency of operation. For the single sided metasurface design, scanning to 80° along the E-plane and 55° along the H-plane over a 5.5:1 impedance bandwidth (0.77 GHz-4.2 GHz) was achieved assuming an active VSWR value of 3.1.

Baidya, R, Aguilera, RP, Karamanakos, P, Acuna, P, Rojas, C, Geyer, T & Lu, DD-C 1970, 'Dealing with Suboptimality in Multistep Model Predictive Control for Transient Operations', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 3780-3785.
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© 2019 IEEE. Recently, a computational issue of sphere decoding algorithm (SDA) during transient operation of multistep model predictive control has been addressed in [1] and achieved its real-time implementation in [2] for a medium-voltage electrical drive system. This is achieved by projecting the unconstrained solution onto the convex-hull of the finite control set during transient operation. Therefore, a new initial sphere that guarantees feasibility and includes a significant smaller number of candidate solutions is obtained. This reduces the computation time required to solve the optimization problem. However, the reduction of the computational burden comes at the expense of (mild) suboptimal results [3]. This paper analyses the possibility to obtain a suboptimal solution by the SDA based optimization during transient operation. To deal with this suboptimality issue, this work explores the possibility to enlarge the convex-hull, whose size is by definition tied to the original finite control set. Therefore, in this work, the convex-hull is treated as a SDA initialization parameter during transient operation. As will be demonstrated, enlarging the convex-hull size reduces the possibility to obtain a suboptimal solution during the transient operation retaining, thus, the optimality during the whole converter operation.

Bautista, M, Zhu, H, Zhu, X & Yang, Y 1970, 'Design of Self-Coupling Enhanced Resonator in $0.13-\mu\mathrm{m}$ (Bi)-CMOS Technology', 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT), 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT), IEEE, Guangzhou, China, pp. 1-27.
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© 2019 IEEE. Design of a compact on-chip resonator operating at mm-wave region is presented in this paper. Unlike the previously published ones in the literature, this work is implemented using a planar structure, which requires no broadside coupling. Instead, the resonance is generated through enhanced self-coupling. To further demonstrate the feasibility of using this approach in practice, the designed resonator is fabricated in a standard 0.13- mumathrm{m} (Bi)-CMOS technology. The measured results show that it can generate a notch at 47 GHz with the attenuation better than 28 dB due to the enhanced self-resonant frequency. The chip size, excluding the pads, is only 0.096times 0.294 text{mm}{2}.

Bautista, MG, Zhu, H, Zhu, X, Yang, Y, Sun, Y, Dutkiewicz, E & Zhang, F 1970, 'Millimeter-Wave BPFs Design using Quasi-Lumped Elements in 0.13-μm (Bi)-CMOS Technology', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, Japan.
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© 2019 IEEE A design methodology using quasi-lumped elements for compact millimeter-wave on-chip bandpass filter (BPF) is presented in this work. To implement BPF using this approach, a novel inductor cell is presented first and then using this cell along with metal-insulator-metal (MIM) capacitors, two BPFs are designed. For the purpose of proof-of-concept, all three designs are implemented and fabricated in a standard 0.13-µm (Bi)-CMOS technology. The measurements show that the inductor cell generates a notch at 47 GHz with a chip size of 0.096 × 0.294 mm2 without pads. Moreover, the 1st BPF has the center frequency at 27 GHz with an insertion loss of 2.5 dB and it has one transmission zero at 58 GHz with a peak attenuation of 23 dB. Unlike the 1st design, the 2nd design has two transmission zeros. The center frequency of this BPF is located at 29 GHz with a minimum insertion loss of 3.5 dB. Without the measurement pads, the chip sizes of the two BPFs are 0.076 × 0.296 mm2 and 0.096 × 0.296 mm2, respectively.

Begh, MAW, Liegmann, E, Karamanakos, PP, Mahajan, A, Siwakoti, YP & Kennel, R 1970, 'Indirect Model Predictive Control of a Three-Phase Grid-Connected Siwakoti-H Inverter.', IECON, Annual Conference of the IEEE Industrial Electronics Society, IEEE, Lisbon, Portugal, pp. 411-416.
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The Siwakoti-H flying-capacitor inverter (sFCI) is a potential candidate for photovoltaic applications, specifically for the transformerless grid-connected systems. One of the main challenges in the control of a sFCI is to maintain the flying capacitor voltage within prescribed limits while balancing the voltages on the three flying capacitors. This paper proposes an indirect model predictive control strategy for a three-phase sFCI connected to the grid via an LCL-filter. By linearizing the system model, the nonlinearities introduced due to the dynamics of the flying capacitor are neglected. Moreover, by not directly controlling the switches, but rather manipulating the modulating signal, the optimization problem can be formulated as a quadratic program (QP) and solved in a computationally efficient manner. The explicit solution computed by the controller makes the realtime implementation feasible by employing a carrier-based pulse width modulator (CB-PWM). The presented results illustrate the steady-state and dynamic performance of the controller.

Begum, H, Ali, A & Lee, JE-Y 1970, 'Mass Sensitivity Measurements of a Novel High Q-Factor Disk Resonator for Liquid-Phase Sensing Applications', 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), IEEE.
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Bluff, A & Johnston, A 1970, 'Devising Interactive Theatre', Proceedings of the 2019 on Designing Interactive Systems Conference, DIS '19: Designing Interactive Systems Conference 2019, ACM, San Diego, CA, USA, pp. 279-289.
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© 2019 Copyright held by the owner/author(s). This paper presents a case study of a long-term collaboration between a physical performance company and interactive digital artists. The collaboration has resulted in the creation of five major performance works which have toured internationally over several years. We argue that the interactive systems can be considered a 'material' which changes over time, shaping performer actions and being shaped by them in return. Based on detailed interviews with key stakeholders and our own personal reflections, we have identified several 'trajectories' that have evolved over the duration of each individual production and the entire body of work. These trajectories address a number of perspectives including the way performers interact with the system, the relationship between the dramaturgy and the interaction palette and the way the stakeholders conceive of the interactive system. The evolution of the technology itself has also been examined in terms of aesthetic capability, performance robustness, operational cost and complexity across the entire duration of the collaboration.

Bluff, A & Johnston, A 1970, 'Don’t Panic: Recursive Interactions in a Miniature Metaworld', Proceedings of the 17th International Conference on Virtual-Reality Continuum and its Applications in Industry, VRCAI '19: The 17th International Conference on Virtual-Reality Continuum and its Applications in Industry, ACM, Brisbane, Australia.
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© 2019 Association for Computing Machinery. Metaworld is a new recursive interaction paradigm for virtual reality, where a miniature display (or 3D map) of the virtual world is presented to the user as a miniature model that itself lives inside the virtual world. The miniature model is interactive and every action which occurs on the miniature world similarly occurs to the greater virtual world and vice-versa. We implemented the metaworld concept in the virtual reality application MetaCity, a city designing sandbox where users can reach into a miniature model and move the cars and skyscrapers. Design considerations of how to display and interact with the miniature model are presented, and a technical implementation of the miniature world is described. The metaworld concept was informally and playfully tested in the MetaCity which revealed a number of novel interactions that enable the user to navigate quickly through large spaces, re-scale objects in the world and manipulate the very fabric of the world itself. These interactions are discussed within the context of four major categories-Experiential Planning, Interdimensional Transformations, Power of the Gods and Self Manipulation.

Bonthu, RK, Aguilera, RP, Pham, H, Phung, MD & Ha, QP 1970, 'Energy Cost Optimization in Microgrids Using Model Predictive Control and Mixed Integer Linear Programming', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, Australia, pp. 1113-1118.
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© 2019 IEEE. This paper presents a model predictive control (MPC) approach based on the mixed integer linear programming (MILP) to develop an optimal power management strategy (PMS) for minimizing the electricity bill of commercial buildings in a domestic on-grid system. The optimal PMS is first formulated as a MILP-MPC with time-varying constraints. The constraints are then linearized at each sampling time so that a receding horizon principle can be used to determine the control input applied to the plant and update the model. The time-varying efficiency of power electronic converters is evaluated for each time interval and assumed to be persistent for the prediction time horizon. The numerical results show that the proposed MILP-MPC strategy with variable efficiency is effective in utilizing photovoltaic power generation to save the cost on electricity for buildings.

Bożejko, W, Chaczko, Z, Nadybski, P & Wodecki, M 1970, 'Meta-heuristic Task Scheduling Algorithm for Computing Cluster with 2D Packing Problem Approach', Advances in Intelligent Systems and Computing, International Conference on Dependability and Complex Systems, Springer International Publishing, Brunów, Poland, pp. 74-82.
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© Springer International Publishing AG, part of Springer Nature 2019. In this paper we present a mathematical model and an algorithm for solving a task scheduling problem in computing cluster. The problem is considered as a 2D packing problem. Each multi-node task is treated as a set of separate subtasks with common constrains. For optimization the tabu search metaheuristic algorithm is applied.

Braun, R, Bone, D, Brookes, W, Trede, F & Hadgraft, R 1970, 'Studios in DE and EE at UTS: Structure and Rationale.', ITHET, International Conference on Information Technology Based Higher Education and Training, IEEE, Magdeburg, Germany, pp. 1-6.
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© 2019 IEEE. We describe the Studios we have introduced into our Data and Electronic Engineering programs. We explain the purpose of the Studios, and the structure of activities. We describe the rationale for the significant components. We comment on the success of the components, and lessons learned.

Braun, R, Brookes, W, Hadgraft, R & Chaczko, Z 1970, 'Assessment Design for Studio-Based Learning', Proceedings of the Twenty-First Australasian Computing Education Conference, ACE'19: Twenty-First Australasian Computing Education Conference, ACM, Sydney, Australia, pp. 106-111.
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© 2019 Association for Computing Machinery. Studio-based learning is not new to computing education, however as the ecosystem of available Open Educational Resources (OERs) expands, the capacity and desire for student self-directed learning is growing. However increasing student autonomy in how and when learning takes place creates challenges around assessment. This paper introduces the design of assessment tasks to support studiobased learning at undergraduate level. It describes an example of using learning contracts and portfolio-based assessment for evaluating individual and team performance. The paper presents some initial observations of the approach taken, and its transferability to other areas of the curriculum.

Broomhead, T, Cremean, L, Ridoux, J & Veitch, D 1970, 'Virtualize everything but time', Proceedings of the 9th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2010, pp. 451-464.
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We propose a new timekeeping architecture for virtualized systems, in the context of Xen. Built upon a feed-forward based RADclock synchronization algorithm, it ensures that the clocks in each OS sharing the hardware derive from a single central clock in a resource effective way, and that this clock is both accurate and robust. A key advantage is simple, seamless VM migration with consistent time. In contrast, the current Xen approach for timekeeping behaves very poorly under live migration, posing a major problem for applications such as financial transactions, gaming, and network measurement, which are critically dependent on reliable timekeeping. We also provide a detailed examination of the HPET and Xen Clocksource counters. Results are validated using a hardware-supported testbed.

Cao, Y & Veitch, D 1970, 'Where on Earth Are the Best-50 Time Servers?', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Passive and Active Network Measurement, Springer International Publishing, Chile, pp. 101-115.
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© 2019, Springer Nature Switzerland AG. We present a list of the Best-50 public IPv4 time servers by mining a high-resolution dataset of Stratum-1 servers for Availability, Stratum Constancy, Leap Performance, and Clock Error, broken down by continent. We find that a server with ideal leap performance, high availability, and low stratum variation is often clock error-free, but this is no guarantee. We discuss the relevance and lifetime of our findings, the scalability of our approach, and implications for load balancing and server ranking.

Chaczko, Z, Klempous, R, Rozenblit, J, Chiu, C, Kluwak, K & Smutnicki, C 1970, 'Enabling Design of Middleware for Massive Scale IOT-based Systems', 2019 IEEE 23rd International Conference on Intelligent Engineering Systems (INES), 2019 IEEE 23rd International Conference on Intelligent Engineering Systems (INES), IEEE, Gödöllő, Hungary.
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Recently, the Internet of Things (IoT) technology has rapidly advanced to the stage where it is feasible to discover, locate and identify various smart sensors and devices based on the context, situation, characteristics, and relevancy to query for their data or control actions. Taking things a step further when developing Large Scale Applications requires that two serious issues be overcome. The first issue is to find a solution for data sensing and collection from a massive number of various ubiquitous devices when converging these into the next generation networks. The second important issue is to deal with the “Big Data” that arrive from a very large number of sources. This research emphasizes the need for finding a solution for a large scale data aggregation and delivery. The paper introduces biomimetic design methods for data aggregation in the context of large scale IoT-based systems.

Chaczko, Z, Wajs-Chaczko, P, Tien, D & Haidar, Y 1970, 'Contents', 2019 International Conference on Machine Learning and Cybernetics (ICMLC), 2019 International Conference on Machine Learning and Cybernetics (ICMLC), IEEE, Kobe, Japan.
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Monitoring the presence of micro-plastics in human and animal habitats is fast becoming an important research theme due to a need to preserve healthy ecosystems. Microplastics pollute the environment and can represent a serious threat for biological organisms including the human body, as they can be inadvertently consumed through the food chain. To perceive and understand the level of microplastics pollution threats in the environment there is a need to design and develop reliable methodologies and tools that can detect and classify the different types of microplastics. This paper presents results of our work related to the exploration of methods and techniques useful for detecting suspicious objects in their respective ecosystems captured in hyperspectral images and then classifying these objects with the use of Neural Networks technique.

Chai, R, Tran, Y, Ling, SH, Craig, A & Nguyen, HT 1970, 'Combining ICA Clustering and Power Spectral Density for Feature Extraction of Mental Fatigue of Spinal Cord Injury Patients', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 530-533.
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This paper presents the combination of clustering-based independent component analysis (ICASSO) and power spectral density (PSD) as a features extractor of mental fatigue from spinal cord injury (SCI) patients. Initially, the results show that SCI and abled-bodied groups have no differences in EEG for alert and mental fatigue states. Further, the coefficient determination (R2) is calculated for testing the variation of data alert vs. fatigue on the SCI group, resulting in a lower R2 for proposed combination of ICASSO and PSD method compared to the PSD method only. With the lower R2 values, this shows that the proposed method ICASSO and PSD is able to provide superior distinction for separating fatigue vs. alert data variation. The statistical significance is found across four EEG bands and EEG channels.

Chen, C, Wang, F, Wen, S, Liu, Y, Shan, X & Jin, D 1970, 'Upconversion nanoparticles assisted multi-photon fluorescence saturation microscopy', Nanoscale Imaging, Sensing, and Actuation for Biomedical Applications XVI, Nanoscale Imaging, Sensing, and Actuation for Biomedical Applications XVI, SPIE, San Francisco, CA.
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© 2019 SPIE. Bright and photo-stable luminescent nanoparticles held great potential for bioimaging, long-term molecular tracking. Rare-earth-doped upconversion nanoparticles (UCNPs) have been recently discovered with unique properties for Stimulated Emission Depletion (STED) super-resolution microscopy imaging. However, this system strictly requires optical alignment of concentric excitation and depletion beams, resulting in cost, stability, and complicity of the system. Taking the advantage of intermediate state saturation in UCNPs, emission saturation nanoscopy has been developed as a simplified modality by using a single doughnut excitation beam. In this work, we report that the emission saturation curve of fluorescence probes can modulate the performance of multi-photon emission saturation nanoscopy. With the precise synthesis of UCNPs, we demonstrate the resolution of this new imaging approach can be improved with five parameters, including emission band, activator doping, excitation power, sensitizer doping, core-shell. This approach opens a new strategy to a simple solution for super-resolution imaging and single molecule tracking at low cost, suggesting a large scope for materials science community to improve the performance of emission saturation nanoscopy.

Chen, L, Liu, Y & Guo, YJ 1970, 'Efficient Frequency-invariant Beam Pattern Synthesis With Multiple Space-frequency Nulls', 2019 IEEE International Conference on Computational Electromagnetics (ICCEM), 2019 IEEE International Conference on Computational Electromagnetics (ICCEM), IEEE, Shanghai, China.
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© 2019 IEEE. This paper presents a modified Fourier transform method to synthesize a broadband array with frequency-invariant (FI) mainlobe and multiple space-frequency nulls. In this method, a iterative Fourier transform is used to design multiple optimized reference patterns which have the same mainlobe shape but with different sidelobe or null distributions. These reference patterns are used for describing different radiation requirements in different sub-bands of the whole frequency band. Then, a desired broadband spatial spectral distribution can be obtained by matching it to each reference pattern at each sub-band, and a broadband excitation distribution for generating the desired FI pattern can be efficiently found by performing an inverse fast Fourier transform (IFFT) on the broadband spatial spectral distribution. An example for synthesizing a FI beam pattern with two space-frequency nulls is provided to verify the effectiveness and efficiency of the proposed method.

Chen, S, Aramvith, S & Miyanaga, Y 1970, 'Encoder Control Enhancement in HEVC Based on R-Lambda Coefficient Distribution', 2019 International Symposium on Multimedia and Communication Technology (ISMAC), 2019 International Symposium on Multimedia and Communication Technology (ISMAC), IEEE.
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Chen, S-L, Karmokar, DK, Ziolkowski, RW & Guo, YJ 1970, 'Wide-Angle Wideband Frequency-Independent Beam-Scanning Leaky Wave Antenna', PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA), 21st International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, SPAIN, Granada, pp. 554-557.
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Chen, S-L, Karmokar, DK, Ziolkowski, RW & Guo, YJ 1970, 'Wide-Angle Wideband Frequency-Independent Beam-Scanning Leaky Wave Antenna', 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, Granada, Spain, pp. 554-557.
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© 2019 IEEE. Frequency-independent beam scanning leaky-wave antennas (LWAs) that can operate over a specific frequency band are highly desirable for future wireless systems. A composite right/left-handed (CRLH) LWA is developed in this paper that facilitates these functionalities. It utilizes two groups of varactor diodes to realize the frequency-independent beam scanning capability. The optimized reconfigurable CRLH LWA and its simple DC biasing network achieves a simulated frequency-independent beam that scans over 100° at each frequency point between 4.75 and 5.25 GHz. An antenna prototype was fabricated and tested. The measured results at 5.0 GHz confirm its simulated performance characteristics.

Chen, Y, An, P, Huang, X, Meng, C & Wu, Q 1970, 'Modified Baseline for Light Field Stitching', 2019 IEEE Visual Communications and Image Processing (VCIP), 2019 IEEE Visual Communications and Image Processing (VCIP), IEEE, Australia, pp. 1-4.
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© 2019 IEEE. In traditional 2D image stitching, the baseline method usually means global homography via Direct Linear Transformation (DLT) on inliers. In this paper, a modified baseline method for light field (LF) stitching is proposed to stitch two LFs. The depth map and the center sub-Aperture image (SAI) are used to filter the feature points of the entire LF. The global 4D homography is then calculated by DLT to align all SAIs corresponding to the same angular domain coordinates of two LFs. Finally, the improved Markov Random Field (MRF) energy considering the global LF is used to find the seam of 2D SAIs instead of computational 4D graph cut. Experimental results show that the proposed method can effectively stitch the 4D LFs, and preserve the consistency of the angular and spatial domains of the stitched LF compared with implementing 2D image stitching to the corresponding SAIs. Moreover, the method proposed in this paper can easily extend all advanced 2D image stitching methods to 4D LF, so that the acquired LF can have larger field of view and wider applications.

Cheng, T, Lu, DD-C & Siwakoti, Y 1970, 'Electro-Thermal Modeling of a Boost Converter Considering Device Self-heating', 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), IEEE, Singapore.
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Thermal management is one of the most critical aspects of the design of high power density converters. Recently, significant efforts and progress have been made in developing electro-thermal models for power semiconductor devices as they are very sensitive to temperature changes. Passive components such as inductors and capacitors are also investigated, since they are temperature-dependent. However, most published work focuses on electro-thermal model of a single power device or a module only instead of a whole converter, which is more realistic in terms of converter design. Hence, in this work, a datasheet informed electro-thermal model is proposed for a boost converter. It is achieved by adding additional behavior models to the existing electrical model of each power device to reflect the temperature incurred electrical behavioral change. Loss model and RC network are used to estimate the temperature change. This forms a power loss and temperature feedback loop. The advantages of this work are ease of integration with existing electrical models in the SPICE library, and elimination of the complicated physical properties of the power devices, but fully utilizes the device datasheet information and mathematical method.

Ding, C, Sun, H-H, Jay Guo, Y & Jones, B 1970, 'Enabling the Co-Existence of Multiband Antenna Arrays', 2019 IEEE International Symposium on Phased Array System & Technology (PAST), 2019 IEEE International Symposium on Phased Array System & Technology (PAST), IEEE, Waltham, MA USA.
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This paper identifies a kind of interaction mechanism that has not been well addressed before, the crossband scattering in multi-band antenna arrays. First the crossband scattering effect is demonstrated on an interleaved dual- band base station antenna array section as an example. Then an effective de-scattering method is proposed, which is to insert chokes on low band antennas. The working mechanism and principle of the chokes are also presented in this paper. Finally, this method is applied on the base station antenna array section to demonstrate its effectiveness.

Ding, C, Wang, K & Guo, YJ 1970, 'Building Antennas on Perovskite Solar Cell (PSC) for Hybrid Solar/EM Wireless Energy Harvesting and Transfer', 2018 Asian Wireless Power Transfer Workshop (AWPT), 2018 Asian Wireless Power Transfer Workshop (AWPT), Sendai, Japan.

Dinh, TH, Alsheikh, MA, Gong, S, Niyato, D, Han, Z & Liang, Y-C 1970, 'Defend Jamming Attacks: How to Make Enemies Become Friends', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Waikoloa, HI.
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In this paper, we consider a smart jammer that only attacks the channel if it detects activities of legitimate devices on that channel. To cope with smart jamming attacks, we propose an intelligent deception strategy in which the legitimate device will send fake transmissions to lure the jammer. Then, if the jammer launches attacks to the channel, the legitimate device can either backscatter the jamming signals to transmit data or harvest energy from the jamming signals for future active transmission. In this way, we can not only undermine the attack ability of the jammer, but also leverage jamming attacks as means to enhance system performance. In addition, to find an optimal defense strategy for the legitimate device under uncertainty of wireless environment as well as incomplete information from the jammer, we develop Q-learning and deep Q-learning algorithms based on the Markov decision process. Through simulation results, we demonstrate that our proposed solution is able to not only deal with smart jamming attacks, but also successfully leverage jamming attacks to improve the system performance.

Du, A, Huang, X, Zhang, J, Yao, L & Wu, Q 1970, 'Kpsnet: Keypoint Detection and Feature Extraction for Point Cloud Registration', 2019 IEEE International Conference on Image Processing (ICIP), 2019 IEEE International Conference on Image Processing (ICIP), IEEE, Taipei, Taiwan, pp. 2576-2580.
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© 2019 IEEE. This paper presents the KPSNet, a KeyPoint Siamese Network to simultaneously learn task-desirable keypoint detector and feature extractor. The keypoint detector is optimized to predict a score vector, which signifies the probability of each candidate being a keypoint. The feature extractor is optimized to learn robust features of keypoints by exploiting the correspondence between the keypoints generated from two inputs, respectively. For training, the KPSNet does not require to manually annotate keypoints and local patches pairwise. Instead, we design an alignment module to establish the correspondence between the two inputs and generate positive and negative samples on-the-fly. Therefore, our method can be easily extended to new scenes. We test the proposed method on the open-source benchmark and experiments show the validity of our method.

Duong, TQ, Nguyen, LD, Tuan, HD & Hanzo, L 1970, 'Learning-Aided Realtime Performance Optimisation of Cognitive UAV-Assisted Disaster Communication', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA.
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In this work, we propose efficient optimisation methods for relay-assisted unmanned aerial vehicles (UAVs) in cognitive radio networks (CRNs) to cope with the network destruction in the event of a natural disaster. Our model considers real- time optimisation in embedded UAV-CRN communication involved in recovering wireless communication services. Particularly, by conceiving advanced optimisation techniques and training deep neural networks, our solutions become capable of supporting real-time applications in disaster recovery scenarios. Our algorithms impose low computational complexity, hence, have a low execution time in solving real- time optimisation problems. Numerical results demonstrate the benefits of our approaches proposed for UAV-CRN.

Ebeling, C, Skinner, B & Bluff, A 1970, 'Xploro: Multi-user AR', ACM SIGGRAPH 2019 Appy Hour, SIGGRAPH 2019, SIGGRAPH '19: Special Interest Group on Computer Graphics and Interactive Techniques Conference, ACM, Los Angeles, California.
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© 2019 Copyright Held by the Owner/Author(s). Xploro is an educational game for iOS which combines augmentedreality (AR) technology and spatial computing multi-user game-play mechanics. It was created by the UTS Animal Logic Academy (UTSALA) 2018 cohort to educate children aged 8-12 in a fun and social way. Xploro uses emerging augmented reality technology to create the hide and seek fun of 'Wheres Wally' alongside educational aspects similar to 'Carmen Sandiego'.

Gamal, M, Abolhasan, M, jafarizadeh, S, Lipman, J & Ni, W 1970, 'Mapping and Scheduling of Virtual Network Functions using Multi Objective Optimization Algorithm', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Ho Chi Minh City, Vietnam, pp. 328-333.
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© 2019 IEEE. Within the context of Software-Defined Networking (SDN), the problem of resource allocation for a set of incoming Virtual Network Functions (VNF) service requests has been the focus of many studies. In this paper, a new optimization model has been developed to find the near to optimal mapping and scheduling for the incoming VNF service requests. This model while considering delay, aims to achieve three objectives functions, namely, minimizing the transmission delays occurring in every link, minimizing the processing capacity for every Virtual Machine (VM) and minimizing the processing delay at every VM. The resultant problem is formulated as a multi-objective optimization problem and the developed solution is based on a multi-objective evolutionary algorithm utilizing the decomposition algorithm. Simulation results illustrate that the resulting algorithm is scalable while considering delay and it outperforms the genetic bandwidth link allocation (GA-BA) and genetic non-bandwidth link allocation (GA-NBA) algorithms.

Gamal, M, Jafarizadeh, S, Abolhasan, M, Lipman, J & Ni, W 1970, 'Mapping and Scheduling for Non-Uniform Arrival of Virtual Network Function (VNF) Requests', 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), IEEE, Honolulu, HI, USA.
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© 2019 IEEE. As a new research concept for both academia and industry, there are several challenges faced by the Network Function Virtualization (NFV). One such challenge is to find the optimal mapping and scheduling for the incoming service requests which is the focus of this study. This optimization has been done by maximizing the number of accepted service requests, minimizing the number of bottleneck links and the overall processing time. The resultant problem is formulated as a multi- objective optimization problem, and two novel algorithms based on genetic algorithm have been developed. Through simulations, it has been shown that the developed algorithms can converge to the near to optimal solutions and they are scalable to large networks.

Gao, X, Zhang, T, Du, J & Guo, YJ 1970, 'Ultrasensitive Terahertz High-T_c Superconducting Receivers', 2019 IEEE MTT-S International Wireless Symposium (IWS), 2019 IEEE MTT-S International Wireless Symposium (IWS), IEEE, Guangzhou, PEOPLES R CHINA.
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© 2019 IEEE. This paper reviews our major technical achievement in high-Tc superconducting (HTS) terahertz (THz) receivers or heterodyne mixers in recent years. By virtue of innovative on-chip antenna/circuit designs, accurate device modelling and simulation, and advanced YBa2Cu3O7-x (YBCO) step-edge junction technology, we have successfully developed a series of HTS Josephson THz mixers with superior performance in terms of operating temperature, intermediate-frequency (IF) bandwidth, conversion gain and noise temperature. These mixers serve as promising receiver frontends for THz wireless communication and sensing systems.

Garcia, JA, Sundara, N, Tabor, G, Gay, VC & Leong, TW 1970, 'Solitaire Fitness: Design of an asynchronous exergame for the elderly to enhance cognitive and physical ability', 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH), 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH), IEEE, IEEE, pp. 1-6.
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© 2019 IEEE. The use of exergames has shown positive results in encouraging the elderly to increase their motivation towards physical activity and rehabilitation. These games usually offer playful routines that require players to perform full body movements in order to interact with the game. While this is often well-received by elderly users, this approach has some limitations that can lead to negative effects in the aged cohort. The main one being, that gameplay and exercise must happen concurrently. This, unfortunately, places limitations on the elderly users and limits the range of exercises that can be delivered. Also, prior studies have revealed that while the aged cohort often finds this approach enjoyable, they are more inclined to exercise in more traditional ways. This paper describes the design and development of an asynchronous game, called Solitaire Fitness, where physical exercise and cognitive gameplay do not occur at the same time. The game is designed to enhance both cognitive and physical abilities. It seamlessly links a well-established card game, solitaire, and let the elderly chose the form of exercise they are familiar with and let them exercise at their own pace, allow them to fully immerse in gameplay, and ultimately increase their motivation towards an healthy active lifestyle.

Ghadi, MJ, Li, L, Zhan, J, Chen, L, Huang, Q & Li, C 1970, 'A Review on the Development of Concentrated Solar Power and its Integration in Coal-Fired Power Plants', 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), IEEE, Chengdu, China, pp. 1106-1111.
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© 2019 IEEE. Concentrated solar power (CSP) technology has attracted the attention of researchers worldwide recently, due to falling prices and much lower operating costs. With the capability of providing high-temperature steam and being dispatchable when coupled with thermal storage, CSP systems are becoming promising technologies for increasing the generation efficiency of different types of power plants. This paper provides a review of the worldwide growth of CSP technologies. After providing a summary on current CSP technologies, development of CSP in some countries is reviewed. Then, possible joint-operations of CSP with different types of power plants are examined. Finally, their application on coal-fired power plants (CFPP) in terms of optimal location for integration, and criteria for CSP utilization based on the size of CFPP are investigated. This review study can assist power system planners to reach a deeper vision of CSP potential benefits for hybrid power generation, especially with thermal power plants, as well as a quick overview of successful projects globally.

Ghosh, S & Lee, JE-Y 1970, 'Eleventh Order Lamb Wave Mode Biconvex Piezoelectric Lorentz Force Magnetometer for Scaling Up Responsivity and Bandwidth', 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), IEEE.
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Guo, K & Guo, Y 1970, 'Optimization Design of a Flux Switching Linear Rotary Permanent Magnet Machine', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE, Harbin, China.
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© 2019 IEEE. A flux switching (FS) linear rotary permanent magnet (PM) machine (LRPMM) is presented with dual level FS structure in the paper. The NdFeB PM material magnetized in circumferential direction and Ferrite PM material magnetized in axial direction can produce high poly-magnetic effect, which can improve the torque/thrust density of the machine. In order to obtain the higher torque/thrust, lower torque/thrust ripple, lower cogging torque and detent force, a novel multi-parameter multi-objective optimization method is proposed. Eleven parameters are selected as the optimization parameters, which can be transformed into two virtual parameters by the initial 2-D finite element method analyzed data and coordinate transformation. Then the electromagnetic and structure parameter values are obtained, a prototype is manufactured. Compared with the initial topology, the experimental results confirm that the proposed method is remarkable and effective.

Guo, K, Yu, H, Chai, R, Nguyen, H & Su, SW 1970, 'A Hybrid Physiological Approach of Emotional Reaction Detection Using Combined FCM and SVM Classifier', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 7088-7091.
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© 2019 IEEE. Users' emotional reaction capturing is one of the primary issues for brain computer interface applications. Despite the intuitive feedback provided by the qualitative methods, emotional reactions are expected to be detected and classified quantitatively. Based on the human emotion representation on physiological signal, this paper offers an hybrid approach combining electroencephalogram (EEG) and facial expression together to classify the human emotion. Several advanced signal processing techniques are used to simplify the data and extract the features involving local binary patterns (LBP), Compressed Sensing (CS) and Wavelet Transform (WT). A novel machine learning algorithm, combined Fuzzy Cognitive Maps (FCM) and Support Vector Machine (SVM) are implemented to recognise the feature patterns. The result illustrates a stable emotion classification system with 75.64% accuracy. This design can provide fast and precise emotional feedback, which would further improve the communication between human and computer.

Ha, TV & Hoang, DB 1970, 'Toward an Active Aging Society: An IT Model to Engage the Aging Population', 2019 International Conference on Information Networking (ICOIN), 2019 International Conference on Information Networking (ICOIN), IEEE, Kuala Lumpur, Malaysia.
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Many countries around the world are expecting a growing number of elderly people as the society is aging over time. This shift is expected to create a large impact on our health and social security system. The cost of having an increasing proportion of elderly people is emerging as a challenge for governments, so much that our government is encouraging people to stay in the workforce longer. As a result, the aging population requires a solution that allows them to remain productive and keeping them mentally healthy. Existing solutions rely on the benefits of social networks or service networks to keep them active and improve mental health. However, these solutions fail to allow elderly people to act as a value contributor for the society. This paper proposes the design of a new model that allows elderly people to actively and collaboratively provide value to the society through an assistive platform that integrates a service network with a social network. This model combines the advantages of the social network to connect them and utilize the advantages of the service network to create opportunities for elderly people to offer their skills and knowledge to exchange benefits with other users. The proposed model can be used as a mean to engage seniors to the community, allowing them to generate value for themselves and the community while staying mentally healthy.

Hamilton, TJ, Kavehei, O, Asadnia, M, Kan, A, Wabnitz, A, Luke, R & Gargiulo, GD 1970, 'Towards a Low-Power, Minimally-Invasive Nerve Regeneration', 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), IEEE.
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© 2019 IEEE. In this paper we will explore current advances and the future directions of nerve regeneration implants. We will discuss the challenges of developing implants which can be chronically implanted for long-term nerve regeneration and stimulation. We will also discuss the need for developing such implants to be low-power and minimally invasive. We will compare solutions proposed in the literature as well as develop some criteria which we believe will maximize the success of future implant development.

Hamilton, TJ, Kavehei, O, Asadnia, M, Kan, A, Wabnitz, A, Luke, R & Gargiulo, GD 1970, 'Towards a Low-Power, Minimally-Invasive Nerve Regeneration', 2019 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING RESEARCH & PRACTICE (ICEERP-2019), International Conference on Electrical Engineering Research and Practice (ICEERP) / 5th World Congress of the Global-Circle-for-Scientific-Technological-and-Management-Research (GCSTMR), IEEE, AUSTRALIA, Sydney, pp. 13-16.
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Hassan, W, Gautam, S, Lu, DD-C & Xiao, W 1970, 'Analysis, Design, and Experimental Verification of High Step-up DC-DC Converter to Interface Renewable Energy Sources into DC Nanogrid', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, pp. 1649-1654.
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© 2019 IEEE. This paper proposes a new non-isolated, high step-up DC-DC converter to interface renewable sources into DC microgrid. The topology utilizes the coupled inductor and switched capacitor techniques to achieve high step-up voltage conversion ratio. The leakage energy is directly transferred to output to avoid voltage spikes across the switch. The switching devices have relatively low voltage stresses. In addition, the coupled inductor alleviated the reverse recovery problem of the diode. The key features include high efficiency, low voltage stresses, and low component count and cost. The steady-state analysis and operation of the proposed converter are presented in detail. Finally, a 200 W prototype circuit operating at a switching frequency of 100 kHz is built in the laboratory to verify the performance. The experimental results substantiate the theoretical analysis and show a peak efficiency of 96.90%.

He, Y, Jayawickrama, BA & Dutkiewicz, E 1970, 'Distributed Power Allocation Algorithm for General Authorised Access in Spectrum Access System', 2019 IEEE Wireless Communications and Networking Conference (WCNC), 2019 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, Marrakesh, Morocco.
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© 2019 IEEE. To meet the capacity needs of the next generation wireless communications, U.S. Federal Communications Commission has recently introduced Spectrum Access System. Spectrum is shared between three tiers - Incumbents, Priority Access Licensees (PAL) and General Authorised Access (GAA) Licensees. When the incumbents are absent, PAL and GAA share the spectrum under the constraint that GAA ensure the aggregate interference to PAL is no more than -80 dBm within the PAL protection area. Currently GAA users are required to report their geolocations. However, geolocation is private information that GAA may not be willing to share. We propose a distributed GAA power allocation algorithm that does not require centralised coordination on sharing locations with other GAA users via SAS. We analytically proved the critical point of the interference along the PAL protection area to avoid calculating the interference on every points of the area. We proposed exclusion zone, transitional zone and open zone for GAA users to calculate the self-determined transmit power. Simulation results show that our method meets the interference requirement and achieve more than 90% of capacity approximation to the optimal centralised method, while completely masking the GAA locations.

Hoang, VT, Phung, MD, Dinh, TH, Zhu, Q & Ha, QP 1970, 'Reconfigurable Multi-UAV Formation Using Angle-Encoded PSO', 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), IEEE, Vancouver, BC, Canada, pp. 1670-1675.
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© 2019 IEEE. In this paper, we propose an algorithm for the formation of multiple UAVs used in vision-based inspection of infrastructure. A path planning algorithm is first developed by using a variant of the particle swarm optimisation, named θ-PSO, to generate a feasible path for the overall formation configuration taken into account the constraints for visual inspection. Here, we introduced a cost function that includes various constraints on flight safety and visual inspection. A reconfigurable topology is then added based on the use of intermediate waypoints to allow the formation to avoid collision with obstacles during operation. The planned path and formation are then combined to derive the trajectory and velocity profiles for each UAV. Experiments have been conducted for the task of inspecting a light rail bridge. The results confirmed the validity and effectiveness of the proposed algorithm.

Hu, C, Sun, X, Yang, Z, Lei, G, Guo, Y & Zhu, J 1970, 'A State Feedback Controller for PMSMs Based on Penalty Term Augmented Seeker Optimization Algorithm', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE.
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© 2019 IEEE. This paper presents the design of a state feedback controller (SFC) for permanent-magnet synchronous motor (PMSM) drive. First, two integrals, the integral of rotor speed error and d-axis current error are added into the discretized state space model of PMSM to eliminate steady-state error in speed and id. Then, the seeker optimization algorithm (SOA) is employed to get the parameters of the proposed SFC. Also, in order to avoid overshoots in speed tracking, a penalty term is added to the fitness function. Finally, the SOA based SFC with and without the penalty term are compared in experiments.

Hu, H, Ghosh, S, Siwakoti, Y & Long, T 1970, 'Generalized Multilevel Converter in DC-DC Application', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, pp. 5137-5143.
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© 2019 IEEE. In this paper, a novel non-isolated generalized multilevel DC-DC converter aiming for applications of connecting Low Voltage (LV) DC to Medium Voltage (MV) DC in high power has been presented. The proposed converter can achieve high voltage transfer ratio between LV and MV, and reduced DC inductance and output capacitance requirement by using low voltage power electronic devices with series interleaved switching techniques. The operating rules have been established and the switching states and switching sequences have been analyzed and selected. The design consideration and simulation results are presented for a 2 kW prototype with a voltage transfer ratio of 8. A 2 kW, 4-level converter has been designed and fabricated to validate the proposed converter. Experimental results are reported at 100 V input, 2 kW load.

Huang, H, Liu, Y, Chen, L, Qin, P-Y & Guo, YJ 1970, 'Synthesis of a Dipole Array with Optimally End-fire Directive Pattern', 2019 IEEE International Conference on Computational Electromagnetics (ICCEM), 2019 IEEE International Conference on Computational Electromagnetics (ICCEM), IEEE, Shanghai, China.
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© 2019 IEEE. In this work, a formula is derived for generating optimally directive pattern for an arbitrary antenna array including mutual coupling effect, and it is then applied to design the optimally directive four-element end-fire dipole array. Synthesis results show that the obtained directivity coefficient is about 2dB and 3.5dB higher than those of ordinary and hansen-woodyard four-element end-fire dipole arrays.

Huang, H, Zhang, J, Zhang, J, Wu, Q & Xu, J 1970, 'Compare More Nuanced: Pairwise Alignment Bilinear Network for Few-Shot Fine-Grained Learning', 2019 IEEE International Conference on Multimedia and Expo (ICME), 2019 IEEE International Conference on Multimedia and Expo (ICME), IEEE, Shanghai, China, pp. 91-96.
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© 2019 IEEE. The recognition ability of human beings is developed in a progressive way. Usually, children learn to discriminate various objects from coarse to fine-grained with limited supervision. Inspired by this learning process, we propose a simple yet effective model for the Few-Shot Fine-Grained (FSFG) recognition, which tries to tackle the challenging fine-grained recognition task using meta-learning. The proposed method, named Pairwise Alignment Bilinear Network (PABN), is an end-to-end deep neural network. Unlike traditional deep bilinear networks for fine-grained classification, which adopt the self-bilinear pooling to capture the subtle features of images, the proposed model uses a novel pairwise bilinear pooling to compare the nuanced differences between base images and query images for learning a deep distance metric. In order to match base image features with query image features, we design feature alignment losses before the proposed pairwise bilinear pooling. Experiment results on four fine-grained classification datasets and one generic few-shot dataset demonstrate that the proposed model outperforms both the state-of-the-art few-shot fine-grained and general few-shot methods.

Huang, X 1970, 'Towards Terabit Wireless Communications', 2019 Australian Communications Theory Workshop, 2019 Australian Communications Theory Workshop, Sydney, Australia.

Huang, X, Fan, L, Wu, Q, Zhang, J & Yuan, C 1970, 'Fast Registration for cross-source point clouds by using weak regional affinity and pixel-wise refinement', Proceedings - IEEE International Conference on Multimedia and Expo, IEEE International Conference on Multimedia and Expo, IEEE, Shanghai, China, pp. 1552-1557.
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Many types of 3D acquisition sensors have emerged in recent years and pointcloud has been widely used in many areas. Accurate and fast registration ofcross-source 3D point clouds from different sensors is an emerged researchproblem in computer vision. This problem is extremely challenging becausecross-source point clouds contain a mixture of various variances, such asdensity, partial overlap, large noise and outliers, viewpoint changing. In thispaper, an algorithm is proposed to align cross-source point clouds with bothhigh accuracy and high efficiency. There are two main contributions: firstly,two components, the weak region affinity and pixel-wise refinement, areproposed to maintain the global and local information of 3D point clouds. Then,these two components are integrated into an iterative tensor-based registrationalgorithm to solve the cross-source point cloud registration problem. Weconduct experiments on synthetic cross-source benchmark dataset and realcross-source datasets. Comparison with six state-of-the-art methods, theproposed method obtains both higher efficiency and accuracy.

Huang, X, Zhang, H, Zhang, JA, Guo, YJ, Song, R-L, Xu, X-F, Wang, C-T, Lu, Z & Wu, W 1970, 'Dual Pulse Shaping Transmission with Complementary Nyquist Pulses', 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), IEEE, Honolulu, HI, USA.
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© 2019 IEEE. The concept of complementary Nyquist pulse is introduced in this paper. Making use of a half rate Nyquist pulse and its complementary one, a dual pulse shaping transmission scheme is proposed, which achieves full Nyquist rate transmission with only a half of the sampling rate required by conventional Nyquist pulse shaping. This is essential for realizing high-speed digital communication systems with available and affordable data conversion devices. The condition for cross-symbol interference free transmission with the proposed dual pulse shaping is proved in theory, and two classes of ideal complementary Nyquist pulses are formulated assuming raised-cosine pulse shaping. Simulation results are also presented to demonstrate the improved spectral efficiency with dual pulse shaping and compare other system performance against conventional Nyquist pulse shaping.

Huang, Y, Song, R, Chen, W, Yu, H, Argha, A, Celler, BG & Su, S 1970, 'The effects of different tracking tasks on muscle synergy through visual feedback', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 417-420.
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© 2019 IEEE. By recruiting a modular organization of muscle with relative activities, the arm motion can be indicated by the neural system and generated for performing a variety of motor tasks. In this study, a Non-negative Matrix Factorization with initial estimation is applied to identify and extract primary muscle synergies and their activation patterns from the processed EMG recordings during three multidirectional tracking tasks with visual feedback interaction. The effects of task variety and tracking accuracy by visual feedback on muscle synergies and their activation patterns are explored by statistic analysis. The results showed that only the task variety affected what synergies were indicated by the neural system, but both task variety and visual feedback affected the duration and magnitude of the primary synergies. Thus, for active rehabilitation application, it is advised that if the purpose is to enhance the synergy indication from the neural system, the task completion accuracy should be emphasized, but if the purpose is to expand the motion area, the task variety should be diversified.

Huang, Y, Wu, Q, Xu, J & Zhong, Y 1970, 'Celebrities-ReID: A Benchmark for Clothes Variation in Long-Term Person Re-Identification', 2019 International Joint Conference on Neural Networks (IJCNN), 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, Budapest, Hungary.
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© 2019 IEEE. This paper considers person re-identification (re-ID) in the case of long-time gap (i.e., long-term re-ID) that concentrates on the challenge of clothes variation of each person. We introduce a new dataset, named Celebrities-reID to handle that challenge. Compared with current datasets, the proposed Celebrities-reID dataset is featured in two aspects. First, it contains 590 persons with 10,842 images, and each person does not wear the same clothing twice, making it the largest clothes variation person re-ID dataset to date. Second, a comprehensive evaluation using state of the arts is carried out to verify the feasibility and new challenge exposed by this dataset. In addition, we propose a benchmark approach to the dataset where a two-step fine-tuning strategy on human body parts is introduced to tackle the challenge of clothes variation. In experiments, we evaluate the feasibility and quality of the proposed Celebrities-reID dataset. The experimental results demonstrate that the proposed benchmark approach is not only able to best tackle clothes variation shown in our dataset but also achieves competitive performance on a widely used person re-ID dataset Market1501, which further proves the reliability of the proposed benchmark approach.

Huang, Y, Wu, Q, Xu, J & Zhong, Y 1970, 'SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification', 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, Seoul, South Korea, pp. 9526-9535.
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© 2019 IEEE. Cross-domain person re-identification (re-ID) is challenging due to the bias between training and testing domains. We observe that if backgrounds in the training and testing datasets are very different, it dramatically introduces difficulties to extract robust pedestrian features, and thus compromises the cross-domain person re-ID performance. In this paper, we formulate such problems as a background shift problem. A Suppression of Background Shift Generative Adversarial Network (SBSGAN) is proposed to generate images with suppressed backgrounds. Unlike simply removing backgrounds using binary masks, SBSGAN allows the generator to decide whether pixels should be preserved or suppressed to reduce segmentation errors caused by noisy foreground masks. Additionally, we take ID-related cues, such as vehicles and companions into consideration. With high-quality generated images, a Densely Associated 2-Stream (DA-2S) network is introduced with Inter Stream Densely Connection (ISDC) modules to strengthen the complementarity of the generated data and ID-related cues. The experiments show that the proposed method achieves competitive performance on three re-ID datasets, i.e., Market-1501, DukeMTMC-reID, and CUHK03, under the cross-domain person re-ID scenario.

Ibrahim, IA, Hossain, MJ, Duck, BC & Badar, AQH 1970, 'Parameters Extraction of a Photovoltaic Cell Model Using a Co-evolutionary Heterogeneous Hybrid Algorithm', 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), IEEE, New Delhi, India, pp. 1-6.
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© 2019 IEEE. This paper proposes a new hybrid algorithm with a combination between the wind driven optimization (WDO) algorithm and the differential evolution with integrated mutation per iteration (DEIM) algorithm. The proposed algorithm, a wind driven optimization based on differential evolution with integrated mutation per iteration (WDO-based on DEIM) algorithm, is utilized to extract the unknown parameters in both of a single-diode photovoltaic (PV) cell model and a double-diode PV cell model. To show the effectiveness of the proposed model, its performance is validated internally by comparing the generated current-voltage (I-V) characteristic curves by the proposed algorithm with the actual I-V characteristic curves, and externally with those obtained by the WDO and DEIM algorithms. The results show the superiority of the proposed model. According to the normalized-root-mean-square error (nRMSE), the mean absolute percentage error (MAPE) and the coefficient of determination (R^{2}) of the achieved results, the proposed WDO-based on DEIM algorithm outperforms the aforementioned algorithms. Finally, the average efficiency of the WDO-based on DEIM algorithm is 95.31%, while it is 81.08% for the WDO algorithm and 88.37% for DEIM algorithm in the single-diode PV cell model. While, it is 96.78% based on WDO-based on DEIM algorithm and it is 92.30% for the WDO algorithm and 91.42% for DEIM algorithm in the double-diode PV cell model.

Irfan, S, Dushmantha, T & Michael, H 1970, 'Novel Half-Patch based 1-D Periodic Structure with Better Control over Stop Bandwidth', 2019 IEEE Asia-Pacific Microwave Conference (APMC), 2019 IEEE Asia-Pacific Microwave Conference (APMC), IEEE, SINGAPORE, pp. 1712-1714.
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Islam, M, Mithulananthan, N, Hossain, J & Bhumkittipich, K 1970, 'Short-term Voltage Stability of Distribution Grids With Medium-scale PV Plants due to Asymmetrical Faults', 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), IEEE, Bangkok, Thailand, pp. 130-135.
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© 2019 IEEE. With the increasing penetration of photo-voltaic (PV) units into electrical grids, particularly in distribution networks (DNs), the concern of short-term voltage instability (STVI) are growing in the presence of induction motor (IM) loads. On the event of unsymmetrical faults, STVI issues could be more complicated as the next-generation PV systems would require negative sequence power injection into the grid in conjunction with positive one. Therefore, this paper comprehensively investigates the impact of negative sequence power on the short-term voltage stability (STVS) of DNs. The method of characterizing an unbalanced fault and supplementary controls for PV systems are developed. Different case studies are conducted on a balanced IEEE 4 bus and an unbalanced IEEE 13 bus system by injecting different level of negative sequence power considering with and without peak current limitation of the PV converters. It is observed that STVS is likely to be weakened in case of large negative sequence power penetration, while injecting high positive sequence power can cause excessive voltage swell resulting inverter disconnections. Therefore, both positive and negative sequence powers need to be injected optimally to ensure the system's security following a fault.

Islam, M, Mithulananthan, N, Hossain, MJ & Bhumkittipich, K 1970, 'A New Grid-support Strategy with PV Units to Enhance Short-term Voltage Stability', 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), IEEE, Bangkok, Thailand, pp. 142-147.
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© 2019 IEEE. Modern grid codes demand the integration of voltage support capability with photo-voltaic (PV) generators to ensure a secure and reliable grid operation. On the other hand, short-term voltage instability (STVI) of distribution networks (DNs) is one of the key issues to be addressed due to the rising proportion of induction motor (IM) loads. However, the literature lacks an extensive analysis of short-term voltage stability (STVS) following an unsymmetrical fault in a DN, as well as an effective voltage-support strategy for PV units to improve the STVS while mitigating the excessive voltage swell. Therefore, at first, this paper thoroughly investigates the STVS of a DN subjected to an unbalanced fault. It is perceived that voltage support through conventional methods can increase the risk of STVI and excessive voltage swell. Secondly, a new voltage-support strategy is proposed based on the negative sequence voltage at the point of common coupling (PCC) to improve the STVS and to limit the voltage swell within requirement. The key features of the proposed method are (1) fast and accurate estimation of a network's impedance at PCC is not required, and (2) can be re-designed considering the network behaviors. The proposed method is validated on two IEEE benchmark test systems, and the provided results designate the effectiveness in improving the STVS and alleviating over voltage issues in a DN.

Islam, MR, Helen Lu, H, Hossain, MJ & Li, L 1970, 'Improving Power Quality of Distributed PV-EV Distribution Grid by Mitigating Unbalance', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, Australia, pp. 643-648.
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© 2019 IEEE. Increasing price of fossil fuels and public awareness encouraged many countries to use clean technologies in transport and electricity generation sector. The advent of smart meters can identify unbalance in PV-EV distribution grid which is a great concern for Distribution Service Operators (DSOs). Several researchers have accessed the degree of unbalance and impact of unbalance on distribution grids considering either distributed PV or EVs. Moreover, a few research work has been done for mitigating unbalance till now. This paper measures unbalance due to unequal distribution of loads and sources among three phases and assess the impact of unbalance on power quality of the PV-EV distribution system by considering different PV and EV penetration levels using DigSILENT Power Factory simulation software. An improved method is proposed to mitigate unbalance using Genetic Algorithm by optimizing load distribution among phases. Finally, the efficacy of the proposed method is evaluated considering unequally distributed residential and EV load scenarios, and it is found that the proposed method can reduce a significant amount of unbalance at all the buses of the distribution grid.

Islam, MR, Lu, H, Fang, G, Li, L & Hossain, MJ 1970, 'Optimal Dispatch of Electrical Vehicle and PV Power to Improve the Power Quality of an Unbalanced Distribution Grid', 2019 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS), 2019 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS), IEEE, Shenzhen, China, pp. 258-263.
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© 2019 IEEE. In the smart grid, the distributed generations play an important role to manage the distribution grid. The renewable energy sources such as PV solar, wind, etc. and the Electric Vehicle's Energy Storage are the prominent distributed generation sources. The distributed generation (DG) reduces power loss and improves the voltage profile and reliability of a low voltage (LV) distribution grid. However, optimal placement and sizing of DGs need to be planned properly. Several researchers planned to place single or multiple DGs at the optimum node with an optimal amount of power dispatch assuming balanced distribution grid. But the DGs are connected at all node/buses which require an optimum amount of power dispatch and distribution grids are seldom balance. Moreover, a few research have been conducted for optimizing DG dispatch in an unbalanced distribution grid. This paper proposes a method to improve voltage profile and reduce the total power loss by optimizing the PV and EVs power dispatch in an unbalanced distribution grid. This study will solve the optimization problem using the Differential evolution (DE) optimization algorithm and compares the performance with the Genetic algorithm (GA). Finally, the efficacy of the proposed method is evaluated by applying to an Australian distribution grid. The proposed method reduces 55.72% real power loss of the network. It is also found that the proposed method improves the bus voltage up to 7.65% and increase the bus voltage above 0.95 p.u at all the nodes.

Islam, MR, Lu, H, Hossain, MJ & Li, L 1970, 'Multi-objective Dynamic Phase re-configuration Technique to Mitigate the Unbalance Due to Penetration of Electric Vehicles', 2019 9th International Conference on Power and Energy Systems (ICPES), 2019 9th International Conference on Power and Energy Systems (ICPES), IEEE, Perth, AUSTRALIA.
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Islam, MR, Lu, H, Hossain, MJ & Li, L 1970, 'Reducing Neutral Current of a higher EV Penetrated Unbalanced Distribution Grid', 2019 9th International Conference on Power and Energy Systems (ICPES), 2019 9th International Conference on Power and Energy Systems (ICPES), IEEE, Perth, AUSTRALIA.
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Islam, MR, Lu, HH, Hossain, MJ & Li, L 1970, 'A Comparison of Performance of GA, PSO and Differential Evolution Algorithms for Dynamic Phase Reconfiguration Technology of a Smart Grid', 2019 IEEE Congress on Evolutionary Computation (CEC), 2019 IEEE Congress on Evolutionary Computation (CEC), IEEE, Wellington, New Zealand, pp. 858-865.
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© 2019 IEEE. Increasing penetration of Distributed Generations (Photovoltaic solar energy (PV), Wind energy, and Battery Energy Storage) and PEVs (Plug-in Electric Vehicles) into smart grid induce network imbalance which reduces power quality. The uncertainty of demand-generation requires balancing for mitigating network imbalance. Several researchers have used various optimization methods for mitigating unbalance. Moreover, a few researchers have done comparative studies of optimization methods for mitigating unbalance till now. This paper proposes a method to mitigate unbalance and reduce the total power loss by optimizing load distribution among phases. This paper compares the performance of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms on the application of phase balancing. Finally, the efficacy of these algorithms are evaluated for the proposed unbalance mitigation technique, and it is found that the proposed technique using DE algorithm can reduce a significant amount of unbalance at all the buses of the distribution grid with less computational effort.

Islam, MR, Lu., HH, Hossain, MJ & Li, L 1970, 'Compensating Neutral Current, Voltage Unbalance and Improving Voltage of an Unbalanced Distribution Grid Connected with EV and Renewable Energy Sources', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE, Harbin, China.
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© 2019 IEEE. Coordinating electric vehicle (EV) charging offers several possible solutions, e.g., charging or discharging rate, and schedule time to improve performances of the distribution network. But EV charging or discharging schedule can be affected due to the punctuality of EV users and equipment failures. The growing penetration of EVs is expected to affect the distribution network performances (voltage unbalance, neutral current, and voltage) as well as generation scheduling due to EV uncertainties. Most of the proposed EV charging control strategies improve the network performance ignoring comfortability (change charging or discharging rate) and lack of punctuality of EV users. This paper investigates the impact of EV uncertainty on the imbalance of the network in a higher penetrated distribution grid. A centralized control algorithm is proposed to coordinate EVs and DESs service point of connection (SPOC) among phases to mitigate the network imbalance and improve the voltage. Using the proposed control approach, the candidate DES number is reduced to participate, whereas EV users do not require to participate. Results obtained using the proposed control approach shows that the neutral current reduces 82.98%, voltage unbalance up to 99.08% and improve voltage up to 17.08%.

Jamborsalamati, P, Moghimi, M, Hossain, J & Lu, J 1970, 'Design and Implementation of a Hierarchical Hybrid Communication Platform for Multi-Microgrid Applications', Sustainability in Energy and Buildings 2018 Proceedings of the 10th International Conference in Sustainability on Energy and Buildings (SEB’18), International Conference in Sustainability on Energy and Buildings, Springer International Publishing, Gold Coast, Australia, pp. 199-208.
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© Springer Nature Switzerland AG 2019. This paper presents a hierarchical hybrid communication platform for Multi-Microgrid (MMG) optimization applications. The main purpose of the implemented platform is to attach multiple Microgrids (MGs) to each other by adding an Internet of Things (IoT) gateway to each MG. This enables bi-directional data exchange among the MGs through the IoT gateway for optimal operation of the MGs with respect to each other. Considering the scale of the data acquisition in MMG optimization problems, utilization of a cloud-based platform for extensive data sharing and post-processing of the aggregated data is vital. The proposed platform has adopted Modbus protocol for communications between the devices inside each MG, local controllers, and the MG Central Controller (MGCC). The Message Queue Telemetry Transport (MQTT) protocol is used for data sharing among the MGCCs and HTTP requests for interactions with a cloud server in a hybrid platform. The cloud server has an interface to MATLAB and the hierarchical architecture is implemented in a co-simulation platform with Python and MATLAB. Results show the efficacy of the implemented platform for MMG optimization applications.

Jauregi Unanue, I, Zare Borzeshi, E, Esmaili, N & Piccardi, M 1970, 'ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems', Proceedings of the 2019 Conference of the North, Proceedings of the 2019 Conference of the North, Association for Computational Linguistics, Minneapolis, pp. 430-436.
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Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (ReWE) as a new regularization technique in a system that is jointly trained to predict the next word in the translation (categorical value) and its word embedding (continuous value). Such a joint training allows the proposed system to learn the distributional properties represented by the word embeddings, empirically improving the generalization to unseen sentences. Experiments over three translation datasets have showed a consistent improvement over a strong baseline, ranging between 0.91 and 2.54 BLEU points, and also a marked improvement over a state-of-the-art system.

Ji, LY, Qin, PY, Guo, YJ, Genovesi, S, Zhu, HL & Zong, Y 1970, 'A Reconfigurable Partially Reflective Surface Antenna with Enhanced Beam Steering Capability', 13th European Conference on Antennas and Propagation, EuCAP 2019, European Conference on Antennas and Propagation, IEEE, Krakow, Poland.
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A reconfigurable partially reflective surface (PRS) antenna with improved beam steering capability is proposed in this paper. Compared with our previous paper, the beam-steering angle can be enhanced from ±5° to ±17° with less active elements and a much smaller gain variation. It is realized by employing a compact reconfigurable metasurface as the PRS structure, which is located atop a probe-fed square patch antenna. A prototype antenna operating at 5.5 GHz is fabricated and measured. Good agreement between the simulated and measured results for the input reflection coefficients and radiation patterns is achieved, which validates the feasibility of the design principle.

Karmokar, DK, Bird, TS, Guo, YJ & Esselle, KP 1970, 'A Binary-switch Controlled Periodic Half-width Leaky-wave Antenna for Fixed Frequency Beam Steering near the Endfire Region', 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring), 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring), IEEE, Rome, Italy, pp. 1799-1803.
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© 2019 IEEE. A leaky-wave antenna (LWA) with fixed-frequency beam scanning capabilities is presented in this paper. The main structure is a half-width microstrip LWA (HW-MLWA), and the direction of the main beam at a fixed operating frequency is controlled by using a group of gap capacitors and binary switches. Different binary switching patterns are applied to change the reactance profile of the radiating structure and hence beam scanning at a fixed frequency is achieved in discrete steps. Results from the full-wave simulation demonstrate that the radiating antenna beam can be steered from 38 to 68 in a discrete step at 7 GHz.

Karmokar, DK, Chen, S-L, Qin, P-Y & Guo, YJ 1970, 'Open-Stopband Suppression and Cross-Polarization Reduction of a Substrate Integrated Waveguide Leaky-Wave Antenna', 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), IEEE, New Delhi, INDIA.
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© 2019 URSI. All rights reserved. Most leaky-wave antennas (LWAs) suffer from significant gain degradation when the main beam points towards broadside. This is because an open stopband (OSB) restricts broadside radiation. In this paper, a method to suppress the OSB of a periodic substrate integrated waveguide (SIW) LWA is discussed. By simultaneously introducing a slot and a partially radiating wall in each unit cell the impedance in the OSB region has been matched and hence a continuous beam scan through broadside is achieved. The developed LWA can scan its main beam from 74° continuously to +40° when the frequency varies from 7.45 to 10.55 GHz, with a broadside gain and a level of cross-polarization for the broadside beam of 10.8 dBi and 21.37 dB, respectively.

Kashif, M, Hossain, MJ, Nawazish Ali, SM, Sharma, V & Nizami, MSH 1970, 'Harmonic Identification based on DSC and MAF for Three-phase Shunt Active Power Filter', 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, Nadi, Fiji.
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© 2019 IEEE. Harmonic current identification is very important in control of Active Power Filters. The dq Synchronous Reference Frame (SRF) based reference-current extraction technique has been widely utilized for this purpose. The dynamic performance of reference-current detection is dependent on numerical filters. In this paper, the two most popular filters, Delayed Signal Cancellation (DSC) and Moving Average Filter (MAF) are utilized in the rotating reference frame for both fundamental component identification and selective harmonic identification. A comprehensive comparison of the performance of these two filters is then carried out. Experimental results from digital implementation are provided to substantiate the theoretical analysis and simulation results.

Kashif, M, Hossain, MJ, Sharma, V, Ali, SMN & Khan, A 1970, 'Neutral-point Voltage Control of Three-level NPC Inverter for Three-phase APF based on Zero-sequence Voltage Injection', 2019 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING RESEARCH & PRACTICE (ICEERP-2019), International Conference on Electrical Engineering Research and Practice (ICEERP) / 5th World Congress of the Global-Circle-for-Scientific-Technological-and-Management-Research (GCSTMR), IEEE, AUSTRALIA, Sydney, pp. 77-81.
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Kashif, M, Hossain, MJ, Sharma, V, Nawazish Ali, SM & Khan, A 1970, 'Neutral-point Voltage Control of Three-level NPC Inverter for Three-phase APF based on Zero-sequence Voltage Injection', 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), IEEE, Sydney, Australia.
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© 2019 IEEE. Active Power Filters (APF) have already adopted the three-level inverter topology in medium-voltage and high-power applications for solving power-quality problems. The Neutral-point voltage clamped (NPC) Inverter because of its robustness has become a matured and broadly used topology. It is necessary to maintain the neutral-point voltage at the DC-side as close to zero as possible. The focus of this paper is on the neutral-point voltage control of the three-level NPC inverter based on multicarrier PWM by manipulating the dwell time of small vectors by injecting a zero-sequence voltage into the modulating signal. The effectiveness of the presented method on a three-level NPC inverter is validated via simulation in MATLAB/Simulink. The results confirm the efficacy of the method in maintaining the neutral-point voltage at a minimum value with the desired overall good APF compensation characteristics.

Kekirigoda, A, Hui, K-P, Cheng, Q, Lin, Z, Zhang, JA, Nguyen, DN & Huang, X 1970, 'Massive MIMO for Tactical Ad-hoc Networks in RF Contested Environments', MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM), MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM), IEEE, Norfolk, VA.
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Survivability of wireless communications segments in tactical military networks is an enormous challenge in the present and future defence forces, especially as these networks usually operate in radio frequency (RF) contested environments. Therefore, it is necessary to develop techniques to provide effective and efficient communication in RF contested environments. Massive multiple-input-multiple-output (MIMO) techniques use a large number of antennas enabling higher degrees of freedom that can improve communications network's survivability and efficiency compared to conventional MIMO or single antenna systems. This paper presents a novel massive MIMO communications system which enhances the throughput of the network, reduces the bit-error-rate and mitigates the interference from high powered jammers. Simulation results in contested environments verify the effectiveness of this system.

Khan, MNH, Siwakoti, YP, Li, L & Khan, SA 1970, 'Switched-Capacitor Integrated Single-Phase (2N+1)-Levels Boost Inverter for Grid-Tied Photovoltaic (PV) Applications.', ICIT, IEEE International Conference on Industrial Technology, IEEE, Melbourne, pp. 1655-1660.
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© 2019 IEEE. This paper presents a switched-capacitor integrated (2N+1)-level (N≥2) boost inverter for single-phase photovoltaic (PV) applications. It consists of N modular switching cells, where each cell consists of two switched capacitors and three active switching elements. A boost converter at the front side of the switching cells helps to maintain the capacitor voltage balance during different operation modes. With this arrangement, the inverter is capable to generate 2N+1 output voltage levels, and able to accommodate a wide range of input voltage. Detailed analysis followed by simulation and experimental results of a 5-level inverter as an example is presented to verify the proposed concept. Further, comparison with other multilevel inverter topologies is presented to show the merit of the proposed concept.

Khan, MNH, Siwakoti, YP, Li, L & Suan, FTK 1970, 'Constant Common-Mode Voltage Transformerless Inverter for Grid-Tied Photovoltaic Application', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, pp. 616-621.
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© 2019 IEEE. This paper proposes a new H-bridge clamped transformerless inverter for the grid-connected Photovoltaic (PV) application. The clamping circuit consists of two switches and a full bridge diodes, which can clamp the AC terminal voltage to the DC midpoint during the freewheeling period. As a result, the common mode voltage (CMV) is held constant, which makes it a suitable candidate for the grid-connected PV system. Furthermore, the efficiency of the proposed topology is relatively higher than other topologies. The operating principle of the proposed topology is analyzed in brief. Thermal modeling for the proposed topology has presented for loss calculation. Finally, the theoretical analysis is validated with simulation and experimental results. Validation is carried out using PLECS simulation and experimental results.

Khan, SA, Guo, Y, Chowdhury, N-U-R & Zhu, J 1970, 'A Least Mean Square Algorithm Based Single-Phase Grid Voltage Parameters Estimation Method', 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, Bangladesh.
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© 2019 IEEE. Grid-synchronization may be the most significant task in order to integrate renewable energy sources (RESs) and electric vehicles (EVs) into the power grid. The popular technique for grid synchronization is the power based phase locked loop (PLL). The major challenges that one encounters to design a robust power based PLL is the filter design inside the power based PLL control loop, and estimating the grid voltage parameters under frequency drift conditions. A wide bandwidth should be considered during filter design if a wide range of frequency variations are predicted in the grid voltage. The traditional filters cause a large phase delay if a wide bandwidth is considered during filter design. As a result, it degrades the transient performance of the power based PLL. In order to improve the transient performance of the PLL, this paper adopted a Fourier linear combiner (FLC) filter inside the PLL control loop. Moreover, a feedback loop is used to make the FLC frequency adaptive in order to estimate the grid voltage parameter when grid frequency drift occurs. Simulation and experimental results are provided to verify the proposed technique.

Khan, SA, Guo, Y, Habib Khan, MN, Siwakoti, Y & Zhu, J 1970, 'Model Predictive Control without Weighting Factors for T-type Multilevel Inverters with Magnetic-Link and Series Stacked AC-DC Modules', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 5603-5609.
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© 2019 IEEE. This paper presents a multiport magnetic-link based T-type multilevel inverter topology and associated control scheme. The proposed structure comprises of series stacked AC-DC modules connected to a high-frequency magnetic-link, which boost the input DC-link voltage level significantly, and generates the required dc-link voltages for the multilevel inverter stage. The desired number of the output voltage level can be realized by cascading series stacked AC-DC modules and bidirectional switches. Due to inherent voltage balancing capability of the magnetic-link based structure, this topology does not require any control scheme to balance the series connected capacitors in the DC-bus. Thus, it reduces the control complexity. Moreover, the magnetically isolated structure eliminates the leakage and DC current injection into the grid from DC sources, like photovoltaic (PV) module. The proposed structure has the capability to integrate multiple sources operating with different voltage levels, and consequently, reduces the number of components and control complexity. In this work, multilevel voltage synthesizing, active and reactive power control capability are realized by using the finite control set model predictive control (FCS-MPC) algorithm. A prototype multilevel inverter incorporating three stacked AC-DC modules, designed for seven levels operation has been built and tested to verify the circuit performance and associated control scheme.

Khan, TA, Ling, SH & Mohan, AS 1970, 'Advanced Gravitational Search Algorithm with Modified Exploitation Strategy', 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, Bari, Italy, pp. 1066-1070.
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Gravitational search algorithm (GSA) is a novel technique as compared to other heuristic methods and depends pon the gravitational forces between masses. It showed better performance in terms of convergence but has slow exploitation ability due to the fitness function effect on masses; they are getting heavier after every iteration. Therefore, masses are getting closer to each other and nullify the gravitational forces on each other avoiding them from swiftly exploiting the optimum. In order to solve this problem in this paper, an advanced gravitational search algorithm (AGSA) with modified exploitation strategy is proposed. The reason for the modification is that the agents will reach the optimum point swiftly and the convergence is much faster as compared to the standard and other improved versions of GSA available in the literature. AGSA is also compared with the standard and modified Particle Swarm optimization algorithm in this paper. Five benchmark functions have been implemented to assess the efficiency of the presented algorithm. In addition, a standard, constrained, design problem of a pressure vessel design is also used to examine the efficiency of the proposed technique. Simulation results empirically validated that the presented algorithm has remarkably better results in accordance with convergence and solution stability when compared to the other methods.

Khan, TA, Zain-Ul-Abideen, K & Ling, SH 1970, 'A Hybrid Advanced PSO-Neural Network System', 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), IEEE, Bari, ITALY, pp. 1626-1630.
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In this paper, a combination of Advanced Particle Swarm Optimization (APSO) and Neural Network are presented to compensate the drawbacks of both the techniques and utilize the strong attributes to form a hybrid system called Hybrid Advance Particle Swarm Optimization-Neural Network System (HAPSONNS). APSO is used for the training of the neural network. In the initial phases of the search, PSO has swift convergence for global optimum, but later it suffers from slow convergence around the global optimum position. On the contrary, the gradient method attains prior to convergence around the global optimum point, therefore, attaining better accuracy in terms of convergence. This paper elucidates the usage of APSO applied to feedforward neural network to improve the classification accuracy of the network and also decreases the network training time.

Khan, TA, Zain-Ul-Abideen, K & Ling, SH 1970, 'A Modified Particle Swarm Optimization Algorithm Used for Feature Selection of UCI Biomedical Data Sets', 2019 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), 2019 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), IEEE, Riga, LATVIA.
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Kianinia, M, Bradac, C, Sontheimer, B, Wang, F, Tran, TT, Nguyen, M, Kim, S, Xu, Z-Q, Jin, D, Schell, AW, Lobo, C, Aharanovich, I & Toth, M 1970, 'Enhanced Super-Resolution Imaging of Quantum Emitters in Hexagonal Boron Nitride', 2019 Compound Semiconductor Week (CSW), 2019 Compound Semiconductor Week (CSW), IEEE, Nara, Japan.
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Layered van der Waals materials are emerging as compelling two-dimensional platforms for nanophotonics, polaritonics, valleytronics and spintronics, and have the potential to transform applications in sensing, imaging and quantum information processing. Amongst these, hexagonal boron nitride (hBN) is known to host ultra-bright, room-temperature quantum emitters, whose nature is yet to be fully understood. Here, we present a set of measurements which give unique insight into the photophysical properties and level structure of hBN quantum emitters. Specifically, we report the existence of a class of hBN quantum emitters with a fast-decaying intermediate and a long-lived metastable state accessible from the first excited electronic state. Furthermore, by means of a two-laser repumping scheme, we show an enhanced photoluminescence and emission intensity which can be utilized to realize a new modality of far-field super-resolution imaging. Our findings expand current understanding of quantum emitters in hBN and show new potential ways of harnessing their nonlinear optical properties in sub-diffraction nanoscopy.

Kiran, MR, Farrok, O, Islam, MR & Zhu, J 1970, 'Characterization of the Optimized High Frequency Transformer Using Nanocrystalline and Amorphous Magnetic Materials', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE.
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High frequency transformers (HFTs) suffer from high core loss because of high operating frequencies and low magnetic flux saturation of core materials. Latest soft-magnetic materials having the properties of higher flux density, low core loss at medium or high frequencies and high electrical resistivity greatly contribute to the solution of high core losses of HFTs. In this paper, a toroidal core HFT is optimized using human intervened genetic algorithm, mathematically modeled, and characterized in terms of low core loss, better load-power characteristics, and higher efficiency as well as amorphous and nanocrystalline magnetic materials are compared based on their electromagnetic properties. It is nominated that the characterization will lead significant role in the development of next generation HFTs.

Koli, NY, Afzal, MU, Esselle, KP & Zahidul Islam, M 1970, 'A Radial Line Slot Array Antenna with Improved Radiation Patterns for Satellite Communication', 13th European Conference on Antennas and Propagation, EuCAP 2019, 13th European Conference on Antennas and Propagation (EuCAP), IEEE, Krakow, POLAND.
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In this paper we have investigated aperture field distribution of a radial line slot array (RLSA) antenna to improve the radiation pattern quality. A circularly polarised (CP) RLSA antenna was designed with tapered amplitude distribution. The distribution was obtained by manipulating the slot lengths on the antenna aperture based on a slot coupling analysis. The antenna has achieved a peak directivity of 31.7dBic and a peak gain of 31.3 dBic at 19.3 GHz. A significant improvement has been achieved in reducing side lobe levels. The antenna has demonstrated a side lobe level of -28.8 dB in φ = 0° plane and -32.2 dB in φ = 90° plane at 19.3 GHz.

Koli, NY, Afzal, MU, Esselle, KP & Zahidul Islam, M 1970, 'Analyzing the Coupling from Radiating Slots in a Double-Layered Radial Line Slot Array Antenna', 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, IEEE, pp. 1427-1428.
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© 2019 IEEE. This paper investigates power coupling out of radiating slots in a double-layered circularly polarised radial line slot array (RLSA) antenna. The antenna is composed of three plates which form a folded radial waveguide and supports inward-travelling waves. Top plate of the antenna has radiating slots. The slots are designed to intercept the currents on the radial waveguide and produce a circularly polarised broadside beam. The slot length is varied using coupling factor in order to achieve a uniform aperture distribution. The simulation results show that the antenna has fairly uniform phase distribution in its near field. The far-field result indicates a peak directivity of 26.4 dBic at 20 GHz with a good pattern quality and a side lobe level of-21.8 dB.

Koli, NY, Afzal, MU, Esselle, KP, Matekovits, L & Islam, Z 1970, 'Investigating Small Aperture Radial Line Slot Array Antennas for Medium Gain Communication Links', 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, pp. 613-616.
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This paper investigates the performance of a relatively small aperture circularly polarized (CP) radial line slot array (RLSA) antenna with medium gain for the Ku-band. The antenna is composed of two parallel metal plates which form a parallel-plate waveguide and supports rotationally symmetric transverse electromagnetic (TEM) travelling wave. The top plate consists of radiating slot elements. The slots are arrayed on the aperture in a way to produce a circularly polarised broadside beam. The antenna was designed at the central operating frequency of 11 GHz having a circular aperture with radius of 90 mm. The predicted results indicated that the return magnitude of reflection coefficient is less than -10 dB in a operating frequency band from 10.5 GHz to 11.5 GHz. The antenna has achieved a peak directivity of 22.4 dBic with a peak gain of 22.1 dBic at 11 GHz. The CP-RLSA antenna has a predicted aperture efficiency of 40%, and a total efficiency of 93% at 11 GHz.

Koli, NY, Afzal, MU, Esselle, KP, Matekovits, L & Islam, Z 1970, 'Investigating Small Aperture Radial Line Slot Array Antennas for Medium Gain Communication Links', PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA), 21st International Conference on Electromagnetics in Advanced Applications (ICEAA), IEEE, SPAIN, Granada, pp. 613-616.
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Kong, X, Fang, G, Liu, L & Tran, TP 1970, 'Low Computational Data Fusion Approach Using INS and UWB for UAV Navigation Tasks in GPS-Denied Environments', 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), IEEE, Gold Coast, Australia.
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This paper presents a low computational approach for unmanned aerial vehicles (UAV) navigation in GPS-denied environments. This approach is aiming to reduce computation load for UAV flying mission constraints. Small size, light weight on board hardware are constraints for UAV deployment and flying missions. The on board processor should not be built with high complexity and should consume as little computing as possible. Most existing approaches use Kalman filter, extended Kalman filter, Unscented filter, or particle filter to fuse different types of onboard sensor data to estimate UAV position. We developed a data fusion architecture that does not use these filters. We use an ultra-light-coupling fusion architecture. In this architecture, primary sensor and secondary sensor data are fused. When the secondary sensor is unavailable in most of the time, the UAV navigation uses the output of the primary sensor. When the secondary sensor signal is available, the primary sensor is re-aligned using the secondary sensor signal to bond the errors. In our approach, the primary sensor is Inertial Measurement Unit (IMU), and the secondary sensor inputs are from Ultra-wideband system (UWB). This approach is validated using demonstration of comparison of computing load, and simulation results for accuracy and reliability testing using UAV flying mission scenario.

Lam, SC, Manh Doan, D, Nguyen, QT, Kong, X & Sandrasegaran, K 1970, 'Uplink Performance of Ultra Dense Networks with Power Control', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Ho Chi Minh City, Vietnam, pp. 178-182.
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© 2019 IEEE. In this paper, we study Ultra Dense Networks(UDN) in which the density of BSs is distributed with a density of up to 100 BS/km2. This paper utilizes the stretched path loss model which recently has been introduced as an appropriate model for short communications. We introduces a new approach to control the transmit power of the user in which the user's transmit power depends on the distance between the user and its associated Base Station (BS), signal power attenuation. The user performance metric in terms of average coverage probability is mathematically derived. The analytical results indicates that in the case of utilizing power control, increasing the transmit power and the density of BSs can produce negative impacts on the average coverage probability of the user.

Le, AT, Tran, LC, Huang, X & Guo, YJ 1970, 'Authors', 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), IEEE, Auckland, New Zealand.
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Le, AT, Tran, LC, Huang, X & Guo, YJ 1970, 'Beam-Based Analog Self-Interference Cancellation with Auxiliary Transmit Chains in Full-Duplex MIMO Systems', 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE, Cannes, France, pp. 1-5.
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© 2019 IEEE. Analog domain cancellation has been considered as the most important step to mitigate self-interference (SI) in full-duplex (FD) radios. However, in FD multiple-input multiple-output (MIMO) systems, this method faces a critical issue of complexity since the number of cancellation circuits increases quadratically with the number of antennas. In this paper, we propose a beam-based radio frequency SI cancellation architecture which uses adaptive filters to significantly reduce the complexity. Data symbols for all the beams are up-converted by auxiliary transmit chains to provide reference signals for all adaptive filters. Hence, the number of cancellation circuits becomes proportional to the number of transmit beams which are much smaller than that of transmit antennas. We then show that the interference suppression ratio in this architecture is neither affected by the number of beams nor transmit or receive antennas. Instead, it is decided by the performance of the adaptive filter. Simulations are conducted to confirm the theoretical analyses.

Lee, SS, Lim, CS, Siwakoti, YP, Idris, NRN, Alsofyani, IM & Lee, K-B 1970, 'A New Unity-Gain 5-Level Active Neutral-Point-Clamped (UG-5L-ANPC) Inverter', 2019 IEEE Conference on Energy Conversion (CENCON), 2019 IEEE Conference on Energy Conversion (CENCON), IEEE, Yogyakarta, Indonesia, pp. 213-217.
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© 2019 IEEE. The active neutral-point-clamped (ANPC) inverter is a popular multilevel inverter for various industry applications. In a recent attempt, an improved topology that integrates a flying capacitor to enhance the voltage gain from half to unity has been presented [11]. Retaining the benefit of unity-gain, this paper proposes a new ANPC topology with two improvements. Firstly, the voltage stress of the flying capacitor is reduced by half. Secondly, the charging of the flying capacitor at 0 level is made possible to achieve uniform charging over the power cycle. Comprehensive analysis is presented and experimental results of a prototype are presented for validation. Finally, the extension of the topology with increased number of output voltage levels generation is briefly discussed.

Lee, SS, Shen Lim, C, Siwakoti, YP & Lee, K-B 1970, 'Single-Stage Common-Ground Boost Inverter (S²CGBI) for Solar Photovoltaic Systems', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 4229-4233.
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© 2019 IEEE. This paper presents a new transformerless inverter topology which is termed as a single-stage common-ground boost inverter (S2CGBI) for single-phase solar photovoltaic (PV) systems. The proposed topology provides a common-ground for both the dc source and ac output to eliminate the leakage current induced by the parasitic capacitance of PV cells. Voltage-boosting is made possible with the incorporation of only one inductor, which renders the realization of single-stage power conversion. The proposed pulse width modulation (PWM) technique is capable of charging the inductor with a constant duty-cycle while guaranteeing ac output generation. The operation of the proposed S2CGBI is analyzed. Simulation and experimental results are provided to validate the effectiveness of the proposed topology and modulation scheme.

Li, H, Wang, TQ, Huang, X & Zhang, JA 1970, 'Enhanced AoA Estimation Using Localized Hybrid Dual-Polarized Arrays', 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), IEEE, Honolulu, HI, USA.
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© 2019 IEEE. With balanced system performance, implementation complexity and hardware cost, hybrid antenna array is regarded as an enabling technology for massive multiple-input and multiple-output communication systems in millimeter wave (mmWave) frequencies. Angle-of-arrival (AoA) estimation using a localized hybrid array faces the challenges of the phase ambiguity problem due to its localized nature of array structure and susceptibility to noises. This paper discusses AoA estimation in an mmWave system employing dual-polarized antennas. We propose an enhanced AoA estimation algorithm using a localized hybrid dual-polarized array for a polarized mmWave signal. First, the use of dual-polarized arrays effectively strengthens the calibration of differential signals and resulting signal-to-noise ratio with coherent polarization combining, leading to an enhanced estimate of the phase offset between adjacent subarrays. Second, given the phase offset, an initial AoA estimate can be obtained, which is used to update the phase offset. By employing the updated one, the AoA is re- estimated with improved accuracy. The closed-form mean square error (MSE) lower bounds of AoA estimation are derived and compared with simulated MSEs. The simulation results show that the proposed algorithm in combination with hybrid dual- polarized arrays significantly improves the estimation accuracy compared with the state of the art.

Li, K, Kanhere, SS, Ni, W, Tovar, E & Guizani, M 1970, 'Proactive Eavesdropping via Jamming for Trajectory Tracking of UAVs', 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019 15th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE.
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Li, K, Lu, L, Ni, W, Tovar, E & Guizani, M 1970, 'Cooperative Secret Key Generation for Platoon-Based Vehicular Communications', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE.
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Li, L, Liu, Z, Zhang, J & Zhou, X 1970, 'Learn Image Object Co-segmentation with Multi-scale Feature Fusion', 2019 IEEE Visual Communications and Image Processing (VCIP), 2019 IEEE Visual Communications and Image Processing (VCIP), IEEE, Sydney, Australia.
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© 2019 IEEE. Image object co-segmentation aims to segment common objects in a group of images. This paper proposes a novel neural network, which extracts multi-scale convolutional features at multiple layers via a modified VGG network and fuses them both within and across images as the intra-image and the inter-image features. Then these two kinds of features are further fused at each scale as the multi-scale co-features of common objects, and finally the multi-scale co-features are summed up and upsampled to obtain the co-segmentation results. To simplify the network and reduce the rapidly rising resource cost along with the inputs, the reduced input size, less downsampling and dilation convolution are adopted in the proposed model. Experimental results on the public dataset demonstrate that the proposed model achieves a comparable performance to the state-of-The-Art co-segmentation methods while the computation cost has been effectively reduced.

Li, Q, Wu, Q & Liu, X 1970, 'Multi-scale and Hierarchical Embedding for Polarity Shift Sensitive Sentiment Classification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Artificial Intelligence and Security, Springer International Publishing, New York, NY, USA, pp. 227-238.
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© 2019, Springer Nature Switzerland AG. Appropriate paragraph embedding is critical for sentiment classification. However, the embedding for paragraph with polarity shift is very challenging and insufficiently explored. In this paper, a MUlti-Scale and Hierarchical embedding method, MUSH, is proposed to learn a more accurate paragraph embedding for polarity shift sensitive sentiment classification. MUSH adopts CNN with multi-size filters to reveal multi-scale sentiment atoms and utilizes hierarchical multi-line CNN-RNN structures to simultaneously capture polarity shift in both sentence level and paragraph level. Extensive experiments on four large real-world data sets demonstrate that the MUSH-enabled sentiment classification significantly enhances the accuracy compared with three state-of-the-art and four baseline competitors.

Li, Q, Wu, Q, Zhu, C & Zhang, J 1970, 'Bi-Level Masked Multi-scale CNN-RNN Networks for Short Text Representation', 2019 International Conference on Document Analysis and Recognition (ICDAR), 2019 International Conference on Document Analysis and Recognition (ICDAR), IEEE, Sydney, Australia.
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Representing short text is becoming extremely important for a variety of valuable applications. However, representing short text is critical yet challenging because it involves lots of informal words and typos (i.e. the noise problem) but only a few vocabularies in each text (i.e. the sparsity problem). Most of the existing work on representing short text relies on noise recognition and sparsity expansion. However, the noises in short text are with various forms and changing fast, but, most of the current methods may fail to adaptively recognize the noise. Also, it is hard to explicitly expand a sparse text to a high-quality dense text. In this paper, we tackle the noise and sparsity problems in short text representation by learning multi-grain noise-tolerant patterns and then embedding the most significant patterns in a text as its representation. To achieve this goal, we propose a bi-level multi-scale masked CNN-RNN network to embed the most significant multi-grain noise-tolerant relations among words and characters in a text into a dense vector space. Comprehensive experiments on five large real-world data sets demonstrate our method significantly outperforms the state-of-the-art competitors.

Li, Q, Wu, Q, Zhu, C, Zhang, J & Zhao, W 1970, 'Unsupervised User Behavior Representation for Fraud Review Detection with Cold-Start Problem', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, China, pp. 222-236.
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© Springer Nature Switzerland AG 2019. Detecting fraud review is becoming extremely important in order to provide reliable information in cyberspace, in which, however, handling cold-start problem is a critical and urgent challenge since the case of cold-start fraud review rarely provides sufficient information for further assessing its authenticity. Existing work on detecting cold-start cases relies on the limited contents of the review posted by the user and a traditional classifier to make the decision. However, simply modeling review is not reliable since reviews can be easily manipulated. Also, it is hard to obtain high-quality labeled data for training the classifier. In this paper, we tackle cold-start problems by (1) using a user’s behavior representation rather than review contents to measure authenticity, which further (2) consider user social relations with other existing users when posting reviews. The method is completely (3) unsupervised. Comprehensive experiments on Yelp data sets demonstrate our method significantly outperforms the state-of-the-art methods.

Li, Z, Zhang, J, Wu, Q, Gong, Y, Yi, J & Kirsch, C 1970, 'Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points', Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM, Anchorage AK USA, pp. 2848-2856.
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© 2019 Association for Computing Machinery. Railway points are among the key components of railway infrastructure. As a part of signal equipment, points control the routes of trains at railway junctions, having a significant impact on the reliability, capacity, and punctuality of rail transport. Meanwhile, they are also one of the most fragile parts in railway systems. Points failures cause a large portion of railway incidents. Traditionally, maintenance of points is based on a fixed time interval or raised after the equipment failures. Instead, it would be of great value if we could forecast points' failures and take action beforehand, min-imising any negative effect. To date, most of the existing prediction methods are either lab-based or relying on specially installed sensors which makes them infeasible for large-scale implementation. Besides, they often use data from only one source. We, therefore, explore a new way that integrates multi-source data which are ready to hand to fulfil this task. We conducted our case study based on Sydney Trains rail network which is an extensive network of passenger and freight railways. Unfortunately, the real-world data are usually incomplete due to various reasons, e.g., faults in the database, operational errors or transmission faults. Besides, railway points differ in their locations, types and some other properties, which means it is hard to use a unified model to predict their failures. Aiming at this challenging task, we firstly constructed a dataset from multiple sources and selected key features with the help of domain experts. In this paper, we formulate our prediction task as a multiple kernel learning problem with missing kernels. We present a robust multiple kernel learning algorithm for predicting points failures. Our model takes into account the missing pattern of data as well as the inherent variance on different sets of railway points. Extensive experiments demonstrate the superiority of our algorit...

Li, Z, Zou, Y, Wang, G & Zhang, J 1970, 'Scale-Informed Density Estimation for Dense Crowd Counting', 2019 IEEE Visual Communications and Image Processing (VCIP), 2019 IEEE Visual Communications and Image Processing (VCIP), IEEE, Sydney, Australia.
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© 2019 IEEE. Dense crowd counting (DCC) remains challenging due to the scale variation and occlusion. Several deep learning based DCC methods have achieved the state-of-Arts on public datasets. However, experimental results show that the scale variation is still the main factor to hinder the DCC performance. In this work, we propose a scale-informed dense crowd counting method focusing on handling the negative effect caused by scale variation. More specifically, we propose a method to obtain the scale information of the patch from its GT density maps via estimating the mean value of the Gaussian kernel width and then a scale-classifier is deigned and trained accordingly. Moreover, with the estimated scale information, two sub-nets are dedicatedly deigned to learn the density maps for large-scale head patch and small-scale patch separately. Experimental results validate the performance of our proposed method which achieves the best performance on three dense crowd datasets.

Liao, Q, Wang, D, Holewa, H & Xu, M 1970, 'Squeezed Bilinear Pooling for Fine-Grained Visual Categorization', 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), IEEE, South Korea.
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Lin, S, Kong, X & Liu, L 1970, 'Development of an intelligent UAV path planning approach to minimize the costs in flight distance, time, altitude, and obstacle collision', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Ho Chi Minh City, Vietnam.
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This paper presents a UAV path planning approach to consider flight cost functions. The UAV flight paths are generated using quintic Hermite interpolation. These paths are constant in speed, and the algorithm generates the paths by iteration to ensure the path segments are smooth. We designed a Waypoint-Matrix to store the points of the path. The paths are aimed to reach the defined destination by passing the waypoints and avoiding obstacles. In this approach, we developed flight cost functions to evaluate the paths, and path length, flight time, altitude, and collision. This approach is validated by simulation results.

Lin, Z, Lv, T, Zhang, JA & Liu, RP 1970, '3D Wideband mmWave Localization for 5G Massive MIMO Systems', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA, pp. 1-6.
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© 2019 IEEE. This paper proposes a novel 3D localization method for wideband mmWave massive MIMO systems. A high dimensional linear interpolation (HDLI)-based preprocessing is first proposed to transform the frequency-associated dynamical array response vectors into the common counterparts at the reference frequency. Through this method, the received data in all frequency bands can be processed jointly, and thus the high temporal resolution provided by wideband mmWave systems can be fully exploited for position estimation. To reduce the computational complexity in the process of the parameter estimation, we then present a wideband beamspace (WBS)-based parameter estimation algorithm to estimate the angle and delay in the low-dimensional beamspace. By exploiting the quasi- optical propagation at the mmWave frequencies, a novel positioning scheme is also designed to determine the 3D location of the target. According to our analysis and simulation results, the proposed method is capable of achieving significantly reduced computational complexity, while maintaining high localization accuracy.

Ling, SH, Makgawinata, H, Monsivais, FH, dos Santos Goncalves Lourenco, A, Lyu, J & Chai, R 1970, 'Classification of EEG Motor Imagery Tasks Using Convolution Neural Networks', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 758-761.
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Electroencephalograph (EEG) is a highly nonlinear data and very difficult to be classified. The EEG signal is commonly used in the area of Brain-Computer Interface (BCI). The signal can be used as an operative command for directional movements for a powered wheelchair to assist people with disability in performing the daily activity.In this paper, we aim to classify Electroencephalograph EEG signals extracted from subjects which had been trained to perform four Motoric Imagery (MI) tasks for two classes. The classification will be processed via a Convolutional Neural Network (CNN) utilising all 22 electrodes based on 10-20 system placement. The EEG datasets will be transformed into scaleogram using Continuous Wavelet Transform (CWT) method.We evaluated two different types of image configuration, i.e. layered and stacked input datasets. Our procedure starts from denoising the EEG signals, employing Bump CWT from 8-32 Hz brain wave. Our CNN architecture is based on the Visual Geometry Group (VGG-16) network. Our results show that layered image dataset yields a high accuracy with an average of 68.33% for two classes classification.

Liu, C, Wang, Y, Lei, G, Guo, Y & Zhu, J 1970, 'Comparative Study of Axial Flux Vernier Machine with SMC Cores for Electric Vehicle Application', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE, Harbin, China.
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© 2019 IEEE. Two high performance axial flux Vernier machines (AFVM) with soft magnetic composite (SMC) cores and one of that with silicon steel cores were proposed for electric vehicle application and quantitatively studied in this paper. By using 3D finite element method (FEM), the torque ability and power factor of above three machines have been optimized, and then the main performance are compared. With the combination of spoke magnet rotor structure and 3-D stator structure, the proposed AFVM1 can own the benefit of highest power factor when compared with other machines, and AFVM2 with double rotor configuration and 3D stator structure can have much higher torque ability comparing with the AFVM with silicon steel cores. It can be seen that with the adoption of SMC material the performance of traditional AFVM has been improved greatly.

Liu, C, Wang, Y, Lei, G, Guo, Y & Zhu, J 1970, 'Comparative Study of Axial Flux Vernier Machine with SMC Cores for Electric Vehicle Application', 2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019), 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE, Harbin, PEOPLES R CHINA, pp. 5149-5153.

Liu, J, Chaczko, Z, Braun, R & Gudzbeler, G 1970, 'Collaborative RFID Agent Simulation in Dynamic Environment', 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET), 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET), IEEE, Magdeburg, Germany, Germany, pp. 1-4.
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© 2019 IEEE. This paper discusses the design and implementation process of applying morphogenetic and reflexive agents models into the software architecture of radio frequency identification (RFID) agent simulation environment framework (RMAP), as well as, illustrate the agent internal interaction mechanism, and thus allowing multiple agents to work collaboratively to achieve the same goal at least effort. The RMAP can be extensively used for training of medical professionals, developers, students, first responders, emergency services, etc. The RMAP simulation framework is an attempt to synthesize on technological issues related to RFID based solutions in order to 'train' and 'support' medical practitioners and developers.

Liu, J, Lu, J, Hossain, MJ & Li, H 1970, 'A Commercial Building Based Microgrid Performance Investigation', Sustainability in Energy and Buildings 2018 Proceedings of the 10th International Conference in Sustainability on Energy and Buildings (SEB’18), International Conference in Sustainability on Energy and Buildings, Springer International Publishing, Gold Coast, Australia, pp. 209-217.
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© Springer Nature Switzerland AG 2019. In order to overcome the problems which distributed generations bring to the power system, the microgrid concept is proposed. For the power quality consideration, the introduction of the static synchronous compensators and the active power filters may lead to complexity and extra cost to the system. Therefore, an appropriate control strategy for the microgrid is developed in this paper to combine the power quality improvement function to the interlinking converter. This paper investigated the performance of a commercial building based microgrid system. The proposed control strategy enables the microgrid to achieve the active power, reactive power, and harmonics compensation functions. Different scenarios are carried out through simulation based on the real case data. The simulation results show that the microgrid performs effectively with the grid under different cases.

Liu, Y, Liu, F, Qin, P-Y & Guo, YJ 1970, 'Recent development in nonuniformly spaced array synthesis methods', 2019 IEEE International Symposium on Phased Array System & Technology (PAST), 2019 IEEE International Symposium on Phased Array System & Technology (PAST), IEEE, Waltham, MA, USA,.
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© 2019 IEEE. Synthesis of sparse arrays with reduced number of elements are significant for some applications where the available space, weight and the cost of the antenna system is very limited. In recent years, a variety of advanced techniques have been presented to deal with sparse array synthesis problems in either narrow and wideband cases. This paper presents a brief review of these techniques, and gives rough comparative study on some of sparse array synthesis methods.

Liu, Y, Luo, Q, Li, M & Guo, YJ 1970, 'Thinned Massive Antenna Array for 5G Millimeter-Wave Communications', 13th European Conference on Antennas and Propagation, EuCAP 2019, European Conference on Antennas and Propagation, IEEE, Krakow, Poland.
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massive antenna array is one of the key technologies for 5G millimeter-wave communications. In this paper, a modified iterative FFT is introduced to obtain thinned massive arrays. An example is given for synthesizing a 128-element thinned array with U-slot microstrip antenna working at 27.5-28.5 GHz. Simulated results show that the thinned array has improved beam resolution and sidelobe performance than those for a conventional 128-element array.

Lu, S, Oberst, S, Zhang, G & Luo, Z 1970, 'Period adding bifurcations in dynamic pricing processes', 2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), 2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), IEEE, Shenzhen, China, pp. 71-76.
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Price information enables consumers to anticipate a price and to make purchasing decisions based on their price expectations, which are critical for agents with pricing decisions or price regulations. A company with pricing decisions can aim to optimise the short-term or the long-term revenue, each of which leads to different pricing strategies thereby different price expectations. Two key ingredients play important roles in the choosing of the short-term or the long-term optimisation objectives: the maximal revenue and the robustness of the chosen pricing strategy against market volatility. However the robustness is rarely identified in a volatile market. Here, we investigate the robustness of optimal pricing strategies with the short-term or long-term optimisation objectives through the analysis of nonlinear dynamics of price expectations. Bifurcation diagrams and period diagrams are introduced to compare the change in dynamics of the optomal pricing strategies. Our results highlight that period adding bifurcations occur during the dynamic pricing processes studied. These bifurcations would challenge the robustness of an optimal pricing strategy. The consideration of the long-term revenue allows a company to charge a higher price, which in turn increases the revenue. However, the consideration of the short-term revenue can reduce the occurrence of period adding bifurcations, contributing to a robust pricing strategy. For a company, this strategy is a robust guarantee of optimal revenue in a volatile market; for consumers, this strategy avoids rapid changes in price and reduce their dissatisfaction of price variations.

Luo, Y, Zhang, JA, Huang, S, Pan, J & Huang, X 1970, 'Quantization with Combined Codebook for Hybrid Array using Two-Phase-Shifter Structure', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai, China.
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© 2019 IEEE. We propose a novel joint quantization scheme for hybrid antenna array systems using the two-phase-shifter (2-PS) structure, where two phase shifters are combined to represent one beamforming weight. Conventional quantization using a single phase shifter for each beamforming weight cannot represent the magnitude. We propose a new codebook design that combines the two codebooks of the two phase shifters in the recently proposed 2-PS structure. We also study the scaling problem of the beamforming vector and propose a low-complexity searching algorithm for finding a near-optimal scalar based on element-wise quantization. The mean squared quantization error and signal-to-noise ratio (SNR) degradation are derived analytically. Simulation results validate the accuracy of the analytical results and the effectiveness of the proposed quantization methods.

Luo, Y, Zhang, JA, Ni, W, Pan, J & Huang, X 1970, 'Constrained Multibeam Optimization for Joint Communication and Radio Sensing', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Hawaii, USA.
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Multibeam technology has recently been proposed for joint communication and radio sensing (JCAS) in millimeter wave systems using analog antenna arrays. Generation of the multibeam satisfying both communication and sensing requirements is yet to be developed. In this paper, we develop closed-form solutions for optimizing the coefficient that combines communication and sensing subbeams to generate a multibeam. Our solutions maximize the received signal power for communication, in the cases (1) without constraint on sensing beamforming (BF) waveform, (2) with minimum BF gain constraints on discrete sensing directions, and (3) with a minimum total power constraint on a range of sensing directions. Simulation results are provided and validate the effectiveness of the proposed solutions.

Lyu, J, Ling, SH, Banerjee, S, Zheng, JJY, Lai, K-L, Yang, D, Zheng, Y-P & Su, S 1970, '3D Ultrasound Spine Image Selection Using Convolution Learning-to-Rank Algorithm', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, GERMANY, pp. 4799-4802.
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© 2019 IEEE. 3D Ultrasound imaging has become an important means of scoliosis assessment as it is a real-time, cost-effective and radiation-free imaging technique. However, the coronal images from different depths of a 3D ultrasound image have different imaging definitions. So there is a need to select the coronal image that would give the best image definition. Also, manual selection of coronal images is time-consuming and limited to the discretion and capability of the assessor. Therefore, in this paper, we have developed a convolution learning-to-rank algorithm to select the best ultrasound images automatically using raw ultrasound images. The ranking is done based on the curve angle of the spinal cord. Firstly, we approached the image selection problem as a ranking problem; ranked based on probability of an image to be a good image. Here, we use the RankNet, a pairwise learning-to-rank method, to rank the images automatically. Secondly, we replaced the backbone of the RankNet, which is the traditional artificial neural network (ANN), with convolution neural network (CNN) to improve the feature extracting ability for the successive iterations. The experimental result shows that the proposed convolutional RankNet achieves the perfect accuracy of 100% while conventional DenseNet achieved 35% only. This proves that the convolutional RankNet is more suitable to highlight the best quality of ultrasound image from multiple mediocre ones.

Ma, B, Zheng, J, Lei, G & Zhu, J 1970, 'A Robust Design Optimization Approach for Electromagnetic DevicesConsidering Probability Uncertainties', the 22nd International Conference on the Computation of Electromagnetic Fields, Paris.

Makhdoom, I, Zhou, I, Abolhasan, M, Lipman, J & Ni, W 1970, 'PrivySharing: A Blockchain-based Framework for Integrity and Privacy-preserving Data Sharing in Smart Cities', Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 16th International Conference on Security and Cryptography, SCITEPRESS - Science and Technology Publications, Prague, Czech Republic, pp. 363-371.
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Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present “PrivySharing,” a blockchain-based innovative framework for integrity and privacy-preserving IoT data sharing in a smart city environment. The proposed scheme is distinct from existing technologies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel processes a specific type of data such as health, smart car, smart energy or financial data. Moreover, access to user data within a channel is controlled by embedding access control rules in the smart contracts. In addition, users' data within a channel is further isolated and secured by using private data collection. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution also conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. Lastly, we present a system of reward in the form of a digital token “PrivyCoin” for the users for sharing their data with the stakeholders/third parties.

Malik, N, Nanda, P, He, X & Liu, R 1970, 'Trust and Reputation in Vehicular Networks: A Smart Contract-Based Approach', 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), IEEE, Rotorua, New Zealand, pp. 34-41.
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© 2019 IEEE. Appending digital signatures and certificates to messages guarantee data integrity and ensure non-repudiation, but do not identify greedy authenticated nodes. Trust evolves if some reputable and trusted node verifies the node, data and evaluates the trustworthiness of the node using an accurate metric. But, even if the verifying party is a trusted centralized party, there is opacity and obscurity in computed reputation rating. The trusted party maps it with the node's identity, but how is it evaluated and what inputs derive the reputation rating remains hidden, thus concealment of transparency leads to privacy. Besides, the malevolent nodes might collude together for defamatory actions against reliable nodes, and eventually bad mouth these nodes or praise malicious nodes collaboratively. Thus, we cannot always assume the fairness of the nodes as the rating they give to any node might not be a fair one. In this paper, we propose a smart contract-based approach to update and query the reputation of nodes, stored and maintained by IPFS distributed storage. The use case particularly deals with an emergency scenario, dealing against colluding attacks. Our scheme is implemented using MATLAB simulation. The results show how smart contracts are capable of accurately identifying trustworthy nodes and record the reputation of a node transparently and immutably.

Mau, J, Afshar, S, Hamilton, T, van Schaik, A, Lussana, R, Panella, A, Trumpf, J & Delic, DV 1970, 'Embedded implementation of a random feature detecting network for real-time classification of time-of-flight SPAD array recordings', Laser Radar Technology and Applications XXIV, Laser Radar Technology and Applications XXIV, SPIE.
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© 2019 SPIE. A real time program is implemented to classify different model airplanes imaged using a 32x32 SPAD array camera in time-of-flight mode. The algorithm uses random feature extractors in series with a linear classifier and is implemented on the NVIDIA Jetson TX2 platform, a power efficient embedded computing device. The algorithm is trained by calculating the classification matrix using a simple pseudoinverse operation on collected image data with known corresponding object labels. The implementation in this work uses a combination of serial and parallel processes and is optimized for classifying airplane models imaged by the SPAD and laser system. The performance of different numbers of convolutional filters is tested in real time. The classification accuracy reaches up to 98.7% and the execution time on the TX2 varies between 34.30 and 73.55 ms depending on the number of convolutional filters used. Furthermore, image acquisition and classification use 5.1 W of power on the TX2 board. Along with its small size and low weight, the TX2 platform can be exploited for high-speed operation in applications that require classification of aerial targets where the SPAD imaging system and embedded device are mounted on a UAS.

Mendelson, N, Nikolay, N, Xu, ZQ, Tran, TT, Sadzak, N, Bohm, F, Sontheimer, B, Benson, O, Toth, M & Aharonovich, I 1970, 'Tuning of Quantum Emitters in Hexagonal Boron Nitride', 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings.
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We demonstrate two different techniques to tune quantum emitters in hBN, achieving record tuning magnitudes for a solid state quantum emitter, as well as dynamic and reversible modulation of the emitters through both methods).

Mendelson, N, Nikolay, N, Xu, ZQ, Tran, TT, Sadzak, N, Böhm, F, Sontheimer, B, Benson, O, Toth, M & Aharonovich, I 1970, 'Tuning of quantum emitters in hexagonal boron nitride', Optics InfoBase Conference Papers.
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We demonstrate two different techniques to tune quantum emitters in hBN, achieving record tuning magnitudes for a solid state quantum emitter, as well as dynamic and reversible modulation of the emitters through both methods).

Mendelson, N, Nikolay, N, Xu, Z-Q, Tran, TT, Sadzak, N, Böhm, F, Sontheimer, B, Benson, O, Toth, M & Aharonovich, I 1970, 'Tuning of Quantum Emitters in Hexagonal Boron Nitride', Conference on Lasers and Electro-Optics, CLEO: QELS_Fundamental Science, OSA.
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Mhiesan, H, Mantooth, A & Siwakoti, YP 1970, 'A Fault-Tolerant Hybrid Cascaded H-Bridge Topology', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 6376-6381.
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© 2019 IEEE. This paper presents the fault-tolerant operation for a cascaded H-bridge (CHB) inverter. The added features ensure reliable and robust operation in the event of a fault. The proposed strategy uses an additional cross-coupled CHB (X-CHB) unit in companion with the existing CHB to support the output voltage and ensure continuity of operation in case of an open/short circuit fault. The operation of the proposed X-CHB inverter is described in detail. Simulation and experimental verification of the proposed concept is demonstrated using a seven-level CHB. Both simulation and experimental results validate the fault-tolerant operation of the CHB for a battery energy storage system (BESS) in case of switch faults such as open/short-circuit switch faults or dc-source or battery failure.

Minh, HN, Minh, HH, Dinh, TH, Nguyen, DN, Dutkiewicz, E & The, TT 1970, 'An Efficient Algorithm for the k-Dominating Set Problem on Very Large-Scale Networks', COMPUTATIONAL DATA AND SOCIAL NETWORKS, 8th International Conference on Computational Data and Social Networks (CSoNet), SPRINGER INTERNATIONAL PUBLISHING AG, Ho Chi Minh City, VIETNAM, pp. 74-76.
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Mishra, DK, Jabbari Ghadi, M, Li, L & Zhang, J 1970, 'Proposing a Framework for Resilient Active Distribution Systems using Withstand, Respond, Adapt, and Prevent Element', 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, Nadi, Fiji.
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© 2019 IEEE. The increasing frequency of natural disasters and man-made attacks have increased power outages worldwide. Thus, a resilient infrastructure must be constructed to reduce power system damages which directly impacts on the social and economic lives of people. In this paper, a new framework called withstand, respond, adapt, and prevent (WRAP) is presented to evaluate and improve the resilience of distribution networks following a review on existing studies. This resilience enhancement may happen through microgrid and multi- microgrid development in planning or operation stages. Each element of the WRAP framework is responsible for the improvement of the power system resilience in terms of its own attributes and resilience evaluation index. Furthermore, the WRAP framework is defined on the basis of a flowchart with respect to conditional statements. The WRAP framework can be a helpful solution in measuring the resiliency of the power system in terms of robustness, rapidity, adaptability, and predictability. Finally, a case study considering energy-not- supplied as a resilience evaluation index is presented.

Miyanaga, Y 1970, 'Psychoacoustic Masking Effect for Noise Robust Speech Recognition Robot', 2019 International Symposium on Signals, Circuits and Systems (ISSCS), 2019 International Symposium on Signals, Circuits and Systems (ISSCS), IEEE.
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Mukhtar, NM & Lu, DD-C 1970, 'Comparative Study of Isolated and Symmetrical Bidirectional DC-DC Converters based on Flyback and Forward Topologies', 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), IEEE.
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This paper presents a comparative study of isolated and symmetrical bidirectional dc-dc converters based on flyback and forward topologies. It covers those converters with dissipative and non-dissipative snubbers, active clamped switches and two-switch configuration. The parameters used for this study include conversion efficiency, component count, component stress and gate driving requirements. It is found that some structures produce high circulation current which should be avoided. The study has identified two promising converter structures which eliminate the problems and produce high efficiency with reasonable component count.

Nan, Y, Huang, X & Guo, YJ 1970, 'A Fast Piecewise Constant Doppler Algorithm for Generalized Continuous Wave Synthetic Aperture Radar', 2019 International Radar Conference (RADAR), 2019 International Radar Conference (RADAR), IEEE, Toulon, France.
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The generalized continuous wave synthetic aperture radar (GCW-SAR) adopts one-dimensional data recording without the slow time dimension and hence offers many advantages compared with the conventional SAR system. In this paper, a fast piecewise constant Doppler algorithm is proposed based on further zero-th order approximation on top of the linear approximation of the slant range, leading to a flexible azimuth imaging spacing. Significant reduction of the complexity can be achieved by extending the azimuth imaging spacing and downsampling the received signal in digital domain. Simulation results validate the advantages of the proposed algorithm.

Nayak, A, Mishra, S, Hossain, J & Nizami, MSH 1970, 'Output Feedback Adaptive Control for Inter-area Oscillation Damping Under Power System Uncertainties', 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE.
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© 2019 IEEE. The power system is inherently a complex nonlinear system and experiences continuous changes in operating conditions due to sudden variations in load demand. The increasing integration of renewable power sources in current grids brings new dynamics and increases complexity in developing reliable control strategies. In addition, the variability of renewable generation introduce uncertainty and therefore, an advanced controller is required to ensure the systems stability. The wide area measurement systems (WAMS) has made the remote signal much readily available, thus improving the overall systems observability. With considering the changing systems dynamics, an output feedback model reference adaptive damping controller is designed and implemented in this paper. The results show the controllers effectiveness to handle the parametric and nonparametric uncertainties of the system while obtaining satisfactory damping action on inter-area oscillations.

Ngo, CQ, Chai, R, Nguyen, TV, Jones, TW & Nguyen, HT 1970, 'Nocturnal Hypoglycemia Detection using EEG Spectral Moments under Natural Occurrence Conditions', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 7177-7180.
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This paper is concerned with a study of hypoglycemia under natural occurrence conditions at night time. Five adolescents with type 1 diabetes (T1D) participated in the experiments. Patients' blood glucose profiles were interpolated to estimate the intermediate values. The proposed system used spectral moments of electroencephalogram (EEG) signals from central and occipital areas as features for detecting hypoglycemia. We found that hypoglycemia could be detected non-invasively using EEG spectral moments. During hypoglycemic episodes, theta moments increased significantly (P<; 0.005) whereas beta moments decreased significantly (P<; 0.001). Based on the optimal network architecture associated with the highest log evidence, the proposed optimal Bayesian neural network resulted in a sensitivity of 82% and a specificity of 52%. In addition, the estimated blood glucose profiles showed a significant correlation (P<; 1e-6) with interpolated blood glucose values in the test set.

Ngo, CQ, Chai, R, Nguyen, TV, Jones, TW & Nguyen, HT 1970, 'Nocturnal Hypoglycemia Detection using Optimal Bayesian Algorithm in an EEG Spectral Moments Based System', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 5439-5442.
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This paper presents a hypoglycemia detection system using electroencephalogram (EEG) spectral moments from 8 patients with type 1 diabetes (T1D) at night time. Four channels (C3, C4, O1, and O2) associated with glycemic episodes were analyzed. Spectral moments were applied to EEG signal and its corresponding speed and acceleration. During hypoglycemia, theta moments increased significantly (P<; 0.001) and alpha moments decreased significantly (P<; 0.001). The system used an optimal Bayesian neural network for detecting hypoglycemic episodes. Based on the optimal network architecture with the highest log evidence, the final classification results for the test set were 79% and 51% in sensitivity and specificity, respectively. Essentially, the estimated blood glucose profiles correlated significantly to actual values in the test set (P<; 0.0001). Using error grid analysis, 93% of the estimated values were clinically acceptable.

Ngo, QT, Minh Dang, DN, Le-Trung, Q & Lam, DK 1970, 'A Novel Directional MAC in Restricted Access Window for IEEE 802.11ah Networks', 2019 26th International Conference on Telecommunications (ICT), 2019 26th International Conference on Telecommunications (ICT), IEEE.
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Nguyen, D-A, Bui, D-H, Iacopi, F & Tran, X-T 1970, 'An Efficient Event-driven Neuromorphic Architecture for Deep Spiking Neural Networks', 2019 32nd IEEE International System-on-Chip Conference (SOCC), 2019 32nd IEEE International System-on-Chip Conference (SOCC), IEEE, Singapore, Singapore, pp. 144-149.
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© 2019 IEEE. Deep Neural Networks (DNNs) have been successfully applied to various real-world machine learning applications. However, performing large DNN inference tasks in real-time remains a challenge due to its substantial computational costs. Recently, Spiking Neural Networks (SNNs) have emerged as an alternative way of processing DNN'fs task. Due to its eventbased, data-driven computation, SNN reduces both inference latency and complexity. With efficient conversion methods from traditional DNN, SNN exhibits similar accuracy, while leveraging many state-of-the-art network models and training methods. In this work, an efficient neuromorphic hardware architecture for image recognition task is presented. To preserve accuracy, the analog-to-spiking conversion algorithm is adopted. The system aims to minimize hardware area cost and power consumption, enabling neuromorphic hardware processing in edge devices. Simulation results have shown that, with the MNIST digit recognition task, the system has achieved × 20 reduction in terms of core area cost compared to the state-of-the-art works, with an accuracy of 94.4%, core area of 15 μ m2 at a maximum frequency of 250 MHz.

Nguyen, M, Kim, S, Tran, TT, Kianinia, M, Xu, Z, Wang, D, Yang, A, Aharonovich, I, Toth, M & Odom, T 1970, 'Nanophotonic integration of hexagonal boron nitride (Conference Presentation)', 2D Photonic Materials and Devices II, 2D Photonic Materials and Devices II, SPIE.
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Nguyen, MH, Hà, MH, Hoang, DT, Nguyen, DN, Dutkiewicz, E & Tran, TT 1970, 'An Efficient Algorithm for the k-Dominating Set Problem on Very Large-Scale Networks (Extended Abstract)', Computational Data and Social Networks (LNCS), International Conference on Computational Data and Social Networks, Springer International Publishing, Ho Chi Minh City, Vietnam, pp. 74-76.
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© Springer Nature Switzerland AG 2019. The minimum dominating set problem (MDSP) aims to construct the minimum-size subset $$D \subset V$$ of a graph $$G = (V, E)$$ such that every vertex has at least one neighbor in D. The problem is proved to be NP-hard [5]. In a recent industrial application, we encountered a more general variant of MDSP that extends the neighborhood relationship as follows: a vertex is a k-neighbor of another if there exists a linking path through no more than k edges between them. This problem is called the minimum k-dominating set problem (MkDSP) and the dominating set is denoted as $$D:k$$. The MkDSP can be used to model applications in social networks [2] and design of wireless sensor networks [3]. In our case, a telecommunication company uses the problem model to supervise a large social network up to 17 millions nodes via a dominating subset in which k is set to 3.

Nguyen, N-T, Van Huynh, N, Hoang, DT, Nguyen, DN, Nguyen, N-H, Nguyen, Q-T & Dutkiewicz, E 1970, 'Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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© 2019 IEEE. In this paper, we propose a novel approach to jointly address energy management and network throughput maximization problems for heterogeneous IoT low-power wireless communication networks. In particular, we consider a low-power communication network in which the IoT devices can harvest energy from a dedicated RF energy source to support their transmissions or backscatter the signals of the RF energy source to transmit information to the gateway. Different IoT devices may have dissimilar hardware configurations, and thus they may have various communications types and energy requirements. In addition, the RF energy source may have a limited energy supply source which needs to be minimized. Thus, to maximize the network throughput, we need to jointly optimize energy usage and operation time for the IoT devices under different energy demands and communication constraints. However, this optimization problem is non-convex due to the strong relation between energy supplied by the RF energy source and the IoT communication time, and thus obtaining the optimal solution is intractable. To address this problem, we study the relation between energy supply and communication time, and then transform the non-convex optimization problem to an equivalent convex-optimization problem which can achieve the optimal solution. Through simulation results, we show that our solution can achieve greater network throughputs (up to five times) than those of other conventional methods, e.g., TDMA. In addition, the simulation results also reveal some important information in controlling energy supply and managing low-power IoT devices in heterogeneous wireless communication networks.

Ni, W, Rao, Q & Luo, D 1970, 'Video Human Behaviour Recognition Based on Improved SVM_KNN for Traceability of Planting Industry', Springer International Publishing, pp. 474-482.
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Niwa, K, Zhang, G & Kleijn, WB 1970, 'Fast Edge-consensus Computing Based on Bregman Monotone Operator Splitting', ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, Brighton, UK, pp. 4609-4613.
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© 2019 IEEE. Edge-consensus computing is a framework to optimize a global cost function when distributed nodes observe distinct data sets. The distributed primal-dual method of multipliers (PDMM) and distributed alternating direction method of multipliers (ADMM) find network-global optima for edge-consensus algorithms by exchanging variables rather than data sets among the nodes. Since the distributed PDMM follows traditional Peaceman-Rachford splitting, it has a faster convergence rate than the distributed ADMM. To further speed up the convergence rate, we propose a new edge-consensus computing algorithm based on Bregman Peaceman-Rachford splitting. In traditional Peaceman-Rachford splitting, the variable update is defined based on a Euclidean metric and the convergence rate and is a form of first-order gradient descent. By generalizing the metric to a Bregman divergence and designing the divergence adaptively, our fast edge-consensus computing algorithm corresponds to the Newton or an accelerated gradient descent method. The results of our experiments confirm that the proposed algorithm can significantly improve the convergence rate of edge-consensus computing over state-of-the-art algorithms.

Nizami, MSH, Hossain, MJ, Amin, BMR, Kashif, M, Fernandez, E & Mahmud, K 1970, 'Transactive Energy Trading of Residential Prosumers Using Battery Energy Storage Systems', 2019 IEEE Milan PowerTech, 2019 IEEE Milan PowerTech, IEEE, Milan, Italy.
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© 2019 IEEE. In a transactive energy (TE) framework, prosumers can participate in peer-to-peer (P2P) energy trading with neighbors. TE also allows prosumers to participate in grid services by trading their excess energy or energy consumption flexibility with the grid operators, energy suppliers, and third-party energy companies (e.g., Aggregators). This paper presents a novel bidding strategy for small-scale residential prosumers for energy trading in the day-ahead TE market using the flexibilities of residential battery energy storage systems to maximize the profit from energy trading. The bidding model is formulated as a bi-level optimization problem that determines energy trading bids to maximize profits for the prosumer in the upper level, while the lower-level problem schedules the operation of residential storage units with respect to minimum storage degradation and optimum user comfort. A comprehensive storage model is developed that incorporates the operational constraints and the degradation of storage units when they undergo frequent charge-discharge cycles for the energy trading. The proposed bidding model is evaluated via a case study for a typical Australian prosumer and results indicate the efficacy of the proposed model in terms of profit maximization for the prosumer while satisfying user preferences and constraints related to the operation of the storage units.

Nizami, MSH, Hossain, MJ, Rafique, S, Mahmud, K, Irshad, UB & Town, G 1970, 'A Multi-agent system based residential electric vehicle management system for grid-support service', 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE, Genova, Italy.
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© 2019 IEEE. With a spike in popularity and sales, the electric vehicles (EVs) have revolutionized the transportation industry. As EV technology advances, the EVs are becoming more accessible and affordable. Therefore, a rapid proliferation of light-duty EVs have been noticed in the residential sector. Even though the increased charging demand of EVs is manageable in large-scale, the low-voltage (LV) residential networks might not be capable of managing localized capacity issues of large scale EV integration. Dynamic electricity tariff coupled with demand response and smart charging management can provide grid assistance to some extent. However, uncoordinated charging, if clustered in a residential distribution feeder, can risk grid assets because of overloading and can even jeopardize the reliability of the network by violating voltage constraints. This paper proposes a coordinated residential EV management system for power grid support. Charging and discharging of residential EV batteries are coordinated and optimized to address grid overloading during peak demand periods and voltage constraint violations. The EV management for grid support is formulated as a mixed-integer programming based optimization problem to minimize the inconveniences of EV owner while providing grid assistance. The proposed methodology is evaluated via a case study based on a residential feeder in Sydney, Australia with actual load demand data. The simulation results indicate the efficacy of the proposed EV management method for mitigating grid overloading and maintaining desired bus voltages.

Parajuli, N, Gunawardana, U, Gargiulo, G, Ulloa, DF, Sreenivasan, N, Naik, G, Bifulco, P, Esposito, D, Savino, S, Cesarelli, M & Hamilton, T 1970, 'Electrodeless FSR Linear Envelope Signal for Muscle Contraction Measurement', 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), IEEE.
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Parajuli, N, Ulloa, DF, Sreenivasan, N, Naik, G, Bifulco, P, Esposito, D, Savino, S, Cesarelli, M, Hamilton, T, Gunawardana, U & Gargiulo, G 1970, 'Electrodeless FSR linear envelope signal for muscle contraction measurement', 2019 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING RESEARCH & PRACTICE (ICEERP-2019), International Conference on Electrical Engineering Research and Practice (ICEERP) / 5th World Congress of the Global-Circle-for-Scientific-Technological-and-Management-Research (GCSTMR), IEEE, AUSTRALIA, Sydney, pp. 25-29.
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Paul, AK, Zahid Hassan, M, Islam, MR & Zhu, JG 1970, 'Graphene/Gold Based Photonic Crystal Fiber Plasmonic Temperature Sensor for Electric Vehicle Applications', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE.
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An octagonal photonic crystal fiber (PCF) based surface plasmon resonance (SPR) temperature sensor is proposed where graphene/gold and ethanol are used as a plasmonic material and sensing medium, respectively. The proposed PCF based SPR temperature sensor is numerically simulated by finite element method (FEM) based simulation tool and result is processed by using MATLAB environment. Numerical results indicate that the proposed temperature sensor shows the possible maximum wavelength/temperature sensitivity of 1450 pm/°C for graphene plasmonic and 2500 pm/°C for gold plasmonic, calculated using wavelength interrogation method. It is anticipated that the proposed SPR temperature sensor can be reliably applied to monitor the temperature of battery used for electric vehicles (EVs), transformer oil etc.

Pham, M, Hoang, DB & Chaczko, Z 1970, 'Realization of congestion-aware energy-aware virtual link embedding', 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), IEEE, Auckland, New Zealand.
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Network virtualization is an inherent component of future internets. Network resources are virtualized and provisioned to users on demand. The virtual network embedding entails two processes: node mapping and link mapping. However, efficient and practical solutions to the link mapping problem in software-defined networks (SDN) and data centers are still lacking. This paper proposes a solution to the link mapping (LiM) process that can dynamically interact with the routing protocols of the substrate network to allocate virtual link requests to the underlying substrate links, satisfies optimizing cost, minimizing energy consumption, and avoiding congestion (CEVNE) concurrently. CEVNE LiM is realized as a composite application on top of the SDN controller running the Segment Routing (SR) application. The performance of the CEVNE LiM algorithm is compared with the k-shortest path link mapping algorithm and shows its superior performance in terms of the overall runtime, the average path length, the average node stress, the average link stress, and the overall energy consumption.

Pham, TT & Dutkiewicz, E 1970, 'Quantify Physiologic Interactions Using Network Analysis', Computational Science and Its Applications – ICCSA 2019, International Conference on Computational Science and Its Applications, Springer International Publishing, Saint Petersburg, Russia, pp. 142-151.
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© 2019, Springer Nature Switzerland AG. To better understand the neural interactions amongst human organ systems, this work provides a framework of data analysis to quantify forms of neural signalling. We explore network interactions among the human brain and motor controlling. The main objective of this work is to provoke unique challenges in the emerging Network Physiology field. The proposed method applies network analysis techniques including power coherence for connectivity discovering and correlation measurement for profiling relationships. We used a well-designed dataset of 50 subjects over 14 different scenarios for each individual. We found network models for these interactions and observed informative network behaviours. The information can be used to study impaired communications that can lead to dysfunction of organs or the entire system such as sepsis.

Pham, TT, Takalkar, MA, Xu, M, Hoang, DT, Truong, HA, Dutkiewicz, E & Perry, S 1970, 'Airborne Object Detection Using Hyperspectral Imaging: Deep Learning Review', Computational Science and Its Applications – ICCSA 2019, International Conference on Computational Science and Its Applications, Springer International Publishing, Saint Petersburg, Russia, pp. 306-321.
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Hyperspectral images have been increasingly important in object detection applications especially in remote sensing scenarios. Machine learning algorithms have become emerging tools for hyperspectral image analysis. The high dimensionality of hyperspectral images and the availability of simulated spectral sample libraries make deep learning an appealing approach. This report reviews recent data processing and object detection methods in the area including hand-crafted and automated feature extraction based on deep learning neural networks. The accuracy performances were compared according to existing reports as well as our own experiments (i.e., re-implementing and testing on new datasets). CNN models provided reliable performance of over 97% detection accuracy across a large set of HSI collections. A wide range of data were used: a rural area (Indian Pines data), an urban area (Pavia University), a wetland region (Botswana), an industrial field (Kennedy Space Center), to a farm site (Salinas). Note that, the Botswana set was not reviewed in recent works, thus high accuracy selected methods were newly compared in this work. A plain CNN model was also found to be able to perform comparably to its more complex variants in target detection applications.

Poblete, P, Pereda, J, Nunez, F & Aguilera, RP 1970, 'Distributed Current Control of Cascaded Multilevel Inverters', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, AUSTRALIA, pp. 1509-1514.
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Poostchi, H, Borzeshi, EZ & Piccardi, M 1970, 'BILSTM-CRF for Persian named-entity recognition armanpersonercorpus: The first entity-annotated Persian dataset', LREC 2018 - 11th International Conference on Language Resources and Evaluation, Language Resources and Evaluation Conference, European Language Resources Association (ELRA, Miyazaki, Japan, pp. 4427-4431.
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Named-entity recognition (NER) can still be regarded as work in progress for a number of Asian languages due to the scarcity of annotated corpora. For this reason, with this paper we publicly release an entity-annotated Persian dataset and we present a performing approach for Persian NER based on a deep learning architecture. In addition to the entity-annotated dataset, we release a number of word embeddings (including GloVe, skip-gram, CBOW and Hellinger PCA) trained on a sizable collation of Persian text. The combination of the deep learning architecture (a BiLSTM-CRF) and the pre-trained word embeddings has allowed us to achieve a 77.45% CoNLL F1 score, a result that is more than 12 percentage points higher than the best previous result and interesting in absolute terms.

Poostchimohammadabadi, H & Piccardi, M 1970, 'A multi-constraint structured hinge loss for named-entity recognition', Proceedings of The 17th Annual Workshop of the Australasian Language Technology Association, Annual Workshop of the Australasian Language Technology Association, ACLWEB, Sydney, NSW, Australia, pp. 41-46.
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The negative log-likelihood or cross entropy is the usual training objective of NLP models owing to its versatility and empirical performance. However, training objectives which directly target the performance measure usedto evaluate the task have the potential to lead to higher empirical accuracy. For this reason, in this short paper we propose using a multi-constraint structured hinge loss as the training objective of a contemporary name identity recognition (NER) model. Experimental results over the challenging OntoNotes 5.0 dataset have shown that the proposed objective has been able to achieve an improvement of 0.62 CoNLL score points at a complete parity of testing set-up.

Poursafar, N, Taghizadeh, S & Hossain, MJ 1970, 'An Optimized Power Management System for an Islanded DC Microgrid', 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, Nadi, FIJI.
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Puthal, D, Mohanty, SP, Nanda, P, Kougianos, E & Das, G 1970, 'Proof-of-Authentication for Scalable Blockchain in Resource-Constrained Distributed Systems', 2019 IEEE International Conference on Consumer Electronics (ICCE), 2019 IEEE International Conference on Consumer Electronics (ICCE), IEEE, Las Vegas, NV, USA.
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© 2019 IEEE. Resource -constrained distributed systems such as the Internet of Things (IoT), edge computing and fog computing are deployed for real-time monitoring and evaluation. Current security solutions are problematic when there is a centralized controlling entity. The blockchain provides decentralized security architectures using proof-of-work (PoW). Proof-of-work is an expensive process for IoT and edge computing due to the deployment of resource-constrained devices. This paper presents a novel consensus algorithm called Proof-of-Authentication (PoAh) to replace Proof-of-Work and introduce authentication in such environments to make the blockchain application-specific. This paper implemented the Proof-of-Authentication system to evaluate its sustainability and applicability for the IoT and edge computing. The evaluation process is conducted in both simulation and real-time testbeds to evaluate performance. Finally, the process of Proof-of-Authentication and its integration with blockchain in resource-constrained distributed systems is discussed. Our proposed PoAh, while running in limited computer resources (e.g. single-board computing devices like the Raspberry Pi) has a latency in the order of 3 secs.

Qi, H, Yue, H, Zhang, J & Lo, S 1970, 'Optimal Control of CHP Plant Integrated with Load Management on HVAC System in Microgrid', 2019 IEEE 15th International Conference on Control and Automation (ICCA), 2019 IEEE 15th International Conference on Control and Automation (ICCA), IEEE, Edinburgh, United Kingdom, pp. 1073-1078.
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© 2019 IEEE. Combined heat and power (CHP) is a typical community owned distributed generation solution in microgrid development. In this work, the ratio between the electricity output and the thermal output is controlled, along with the demand side load management, so as to minimize the overall microgrid operational cost. A model is established for the energy cost of a smart building system, which includes factors such as the real time electricity pricing, the capacity and constraints within CHP operation, the operating condition of heating, ventilation, and air - conditioning (HVAC), and the indoors air temperature of the smart building. Efficient CHP operation and HVAC load management under demand response (DR) are determined through optimization. A case study is carried out to examine the effectiveness of the proposed strategy.

Qin, C, Zhang, JA, Huang, X & Guo, YJ 1970, 'Angle-of-Arrival Acquisition and Tracking via Virtual Subarrays in an Analog Array', 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), IEEE, Honolulu, HI, USA.
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© 2019 IEEE. Angle-of-arrival (AoA) estimation is a challenging problem for analog antenna arrays. Typical algorithms use beam scanning and sweeping, which can be time-consuming, and the resolution is limited to the scanning step. In this paper, we propose a virtual-subarray based AoA estimation scheme, which divides an analog array into two virtual subarrays and can obtain a direct AoA estimate from every two temporal measurements. We propose different subarray constructions which lead to different range and accuracy of estimation. We provide detailed beamforming vector designs for these constructions and provide a performance lower bound for the estimator. We also present how to apply the estimator to AoA acquisition and tracking. Simulation results demonstrate that the proposed scheme significantly outperforms existing ones when the signal-to-noise ratio is not very low.

Rafique, S, Hasan Nizami, MS, Bin Irshad, U, Hossain, J & Town, G 1970, 'An aggregator-based-strategy to minimize the cost of energy consumption by optimal utilization of energy resources in an apartment building', 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE, Genova, Italy.
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© 2019 IEEE. Buildings and transport consume two thirds of the total global energy. It is desirable to maximize the use of renewable generation in these sectors, and to optimize the use of that energy by managing diverse sources and loads. This is particularly challenging in high-density residential premises where the space for such infrastructure is limited, and storage can have significant impact on energy utilization and demand. In this paper, we have proposed an aggregator-based-strategy (ABS) to optimally utilize the available energy resources and storage in an apartment building with twenty households, each having an electric vehicle (EV), and an aggregated solar photovoltaic (PV) energy and stationary battery storage (BS) system. The strategy is flexible and can be applied to any building with EVs, solar PV and BS to minimize the cost of energy consumption without compromising the flexibility of energy usage or travel requirements. The model also accounts for the battery capacity degradation and its associated cost to make it more realistic. The model is evaluated using real data and the results show that the strategy not only reduces the cost of energy consumption but also reduces the amount of energy drawn from the grid significantly.

Rafique, S, Nizami, MSH, Irshad, UB, Hossain, MJ & Town, GE 1970, 'A customer-based-strategy to minimize the cost of energy consumption by optimal utilization of energy resources in an apartment building', IOP Conference Series: Earth and Environmental Science, International Conference on Smart Power & Internet Energy Systems, IOP Publishing, Melbourne, Australia, pp. 012018-012018.
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Abstract Global energy consumption in heating and cooling of buildings and in the transport sector together accounts for approximately two-thirds of total energy consumption. Consequently, it is important to maximize the use of renewable generation energy in these sectors, and to optimize the use of that energy by managing diverse sources and loads. This is particularly challenging in high-density residential premises where the space for such infrastructure is limited, and storage can have significant impact on energy utilization and demand. In this paper, we describe a customer-based strategy (CBS) to optimize the usage of the available energy resources in such scenarios. The effectiveness of the strategy was validated for an apartment block of 20 households with photovoltaic generation (PV) and stationary battery storage (BS) systems, each with a vehicle-to-grid (V2G) capable electric vehicle (EV). The modelling used real data for customer demand and included the cost of battery degradation and expected vehicle usage in optimizing resource scheduling. Substantial savings in energy costs were shown to be possible for each customer.

Rahman, M, Ahmed, F & Abdur Rahman, AM 1970, 'Low-Cost Low-Profile Planar Patch Antenna for Ultra-Wideband Applications', 2019 2nd International Conference on Innovation in Engineering and Technology (ICIET), 2019 2nd International Conference on Innovation in Engineering and Technology (ICIET), IEEE.
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Rahman, M, Ahmed, F & Rahman, AMA 1970, 'A Low-Cost WLAN Band Notched Planar Patch Antenna for Ultra-Wideband Applications', 2019 IEEE International Conference on Telecommunications and Photonics (ICTP), 2019 IEEE International Conference on Telecommunications and Photonics (ICTP), IEEE.
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Rahman, ML, Cui, P-F, Zhang, JA, Huang, X, Guo, YJ & Lu, Z 1970, 'Joint Communication and Radar Sensing in 5G Mobile Network by Compressive Sensing', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, pp. 599-604.
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© 2019 IEEE. There is growing interest in integrating communication and radar sensing into one system. However, very limited results are reported on how to realize sensing using complicated mobile signals when joint communication and radar sensing (JCAS) is applied to mobile networks. This paper studies radar sensing using one-dimension (1D) to 3D compressive sensing (CS) techniques, referring to signals compatible with latest fifth generation (5G) new radio (NR) standard. We demonstrate that radio sensing using both downlink and uplink 5G signals can be realized with reasonable performance using these CS techniques, and highlight the respective advantages and disadvantages of these techniques.1

Rippingale, S, Johnston, A & Bluff, A 1970, 'Hybrid animation production and the dream of flight', SIGGRAPH ASIA Art Gallery/Art Papers, SA '19: SIGGRAPH Asia 2019, ACM.
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© 2019 Simon Rippingale, Andrew Johnston and Andrew Bluff. Through a detailed account of a recent practice-based research project - a short animation project called Jasper, this paper explores how a hybrid analogue/digital production approach can generate a unique and engaging visual style - one that sits between the tangible, handcrafted feel of miniatures and the cleanness, fluidity and flexibility of computer-generated animation. The author examines the new creative possibilities and challenges that a hybrid animation production approach presents and also outlines various technical platforms encountered during the production of Jasper, including motion-controlled camera systems, 3D printing, game engines, point cloud scans and augmented reality.

Sahoo, A, Arunan, A, Mahmud, K, Ravishankar, J, Nizami, MSH & Hossain, MJ 1970, 'Teager-Huang based Fault Detection in Inverter-interfaced AC Microgrid', 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), IEEE.
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© 2019 IEEE. The limited fault current tolerance of inverters in AC Microgrids demands the necessity of faster and accurate fault detections. At the point of common coupling, the occurrence of various symmetrical and unsymmetrical faults degrades the performance and robustness of the inverter-interfaced local controllers. To achieve faster fault detection in inverter-based AC microgrid, this paper proposes a combined technique that includes two well-known signal processing techniques such as teager energy operator and Hilbert-Huang transform. The combined principle is called a Teager-Huang technique, which can detect different line faults using the teager energy of the Hilbert-Huang based empirical mode decomposed signals. The fault detection technique is verified by creating faults at the inverter connection point to the grid, using MATLAB/SIMULINK and PLECS.

Saki, M, Abolhasan, M & Lipman, J 1970, 'A Big Sensor Data Offloading Scheme in Rail Networks', 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), IEEE, Kuala Lumpur, Malaysia, Malaysia.
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© 2019 IEEE. In this paper, we propose an offloading scheme to transfer massive stored sensor data from rolling stock to railway data centers. We apply a delayed offloading strategy for non-critical stored data assuming that the critical data has been already separated through an appropriate edge processing task and has been sent via a real-time communication such as cellular networks. We propose train stations as potential and feasible spots for data offloading via available wireless local area networks (WLAN) such as existing WiFi network at stations. Thus, stations will not only be the places of passenger exchange but also data exchange. We develop an analytical model customized for the proposed offloading strategy in rail applications. Then we validate the performance of our model through simulation in various scenarios in Omnet. The simulation results shows an accuracy of %98.67 for the proposed analytical model with reference to the simulation results in Omnetpp. Additionally, by using our proposed scheme, we can theoretically offload up to 5.43 GB per each stopping station.

Samal, PB, Jack Soh, P & Zakaria, Z 1970, 'Compact and Wearable Microstrip-based Textile Antenna with Full Ground Plane Designed for WBAN-UWB 802.15.6 Application', 13th European Conference on Antennas and Propagation, EuCAP 2019.
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The design and evaluation of a microstrip-based textile antenna for the IEEE 802.15.6 Wireless Body Area Network Ultrawideband (WBAN-UWB) application is presented in this paper. This textile antenna is designed with an innovative and compact UWB radiator on top of the overall structure with a full ground plane on its reverse side. The radiator based on a microstrip patch combined with multiple miniaturization methods resulted in a simple topology and a compact size of 39 mm x 42 mm x 3.34 mm to facilitate fabrication using simple tools. Meanwhile, the full ground plane enables the antenna operation in the vicinity of the human body with minimal body coupling and radiation towards it, ensuring operational safety. Besides the mandatory WBAN-UWB low and high band channels, the designed antenna also operated in five other high band channels, exhibiting a total bandwidth of 3.4 GHz.

Sang, L, Xu, M, Qian, S & Wu, X 1970, 'AAANE: Attention-Based Adversarial Autoencoder for Multi-scale Network Embedding', Advances in Knowledge Discovery and Data Mining 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, China, pp. 3-14.
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© Springer Nature Switzerland AG 2019. Network embedding represents nodes in a continuous vector space and preserves structure information from a network. Existing methods usually adopt a “one-size-fits-all” approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scales play different roles in embedding learning. In this paper, we propose an Attention-based Adversarial Autoencoder Network Embedding (AAANE) framework, which promotes the collaboration of different scales and lets them vote for robust representations. The proposed AAANE consists of two components: (1) an attention-based autoencoder that effectively capture the highly non-linear network structure, which can de-emphasize irrelevant scales during training, and (2) an adversarial regularization guides the autoencoder in learning robust representations by matching the posterior distribution of the latent embeddings to a given prior distribution. Experimental results on real-world networks show that the proposed approach outperforms strong baselines.

Saputra, YM, Hoang, DT, Nguyen, DN & Dutkiewicz, E 1970, 'JOCAR: A Jointly Optimal Caching and Routing Framework for Cooperative Edge Caching Networks', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Hawaii.
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We propose a jointly optimal caching and routing framework (JOCAR) for a cooperative mobile edge caching network. This novel network architecture enables mobile edge servers/nodes (MENs) to collaborate in not only caching but also routing contents to users, in order to simultaneously minimize the total content-access delay for all mobile users and reduce the traffic on the backhaul network. To that end, we first formulate an access- delay minimization problem by jointly optimizing the content caching and routing decisions while accounting for various network configurations. Solving this problem requires us to deal with a nested dual optimization due to the strong mutual dependence between content caching and routing decisions. To tackle it, we first transform the nested dual problem to an equivalent mixed-integer nonlinear programming (MINLP) problem. Then, we design a branch-and-bound based algorithm with the interior-point method to find the near-optimal policy for the MINLP problem. Extensive simulations show that JOCAR can reduce the total average delay and increase the cache hit rate for the whole network by more than 40% and by four times, respectively, compared with other conventional policies.

Saputra, YM, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Mueck, MD & Srikanteswara, S 1970, 'Energy Demand Prediction with Federated Learning for Electric Vehicle Networks', 2019 IEEE Global Communications Conference (GLOBECOM), IEEE Global Communications Conference, IEEE, Hawaii.
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In this paper, we propose novel approaches using state-of-the-art machinelearning techniques, aiming at predicting energy demand for electric vehicle(EV) networks. These methods can learn and find the correlation of complexhidden features to improve the prediction accuracy. First, we propose an energydemand learning (EDL)-based prediction solution in which a charging stationprovider (CSP) gathers information from all charging stations (CSs) and thenperforms the EDL algorithm to predict the energy demand for the consideredarea. However, this approach requires frequent data sharing between the CSs andthe CSP, thereby driving communication overhead and privacy issues for the EVsand CSs. To address this problem, we propose a federated energy demand learning(FEDL) approach which allows the CSs sharing their information withoutrevealing real datasets. Specifically, the CSs only need to send their trainedmodels to the CSP for processing. In this case, we can significantly reduce thecommunication overhead and effectively protect data privacy for the EV users.To further improve the effectiveness of the FEDL, we then introduce a novelclustering-based EDL approach for EV networks by grouping the CSs into clustersbefore applying the EDL algorithms. Through experimental results, we show thatour proposed approaches can improve the accuracy of energy demand prediction upto 24.63% and decrease communication overhead by 83.4% compared with otherbaseline machine learning algorithms.

Schell, AW, Takashima, H, Tran, TT, Aharonovich, I & Takeuchi, S 1970, 'Tapered fiber coupling of single defect centers in two-dimensional materials', Optics InfoBase Conference Papers.
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Efficient extraction of photons from quantum emitters is an important prerequisite for the use of such emitters in quantum optical applications such as single photons sources or quantum enhanced sensors. There exist different approached to collect the photons, ranging from nigh numerical aperture microscope objectives over integrated on-chip waveguides and cavities to micro-mirrors. For real-world applications, it is also not enough to just collect the photons with the collection optics, it also needs to be ensured that the photons are channelled into a useful spatial mode, usually in an optical fiber.

Schell, AW, Takashima, H, Tran, TT, Aharonovich, I & Takeuchi, S 1970, 'Tapered Fiber Coupling of Single Defect Centers in Two-Dimensional Materials', 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), IEEE.
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Efficient extraction of photons from quantum emitters is an important prerequisite for the use of such emitters in quantum optical applications such as single photons sources or quantum enhanced sensors. There exist different approached to collect the photons, ranging from nigh numerical aperture microscope objectives over integrated on-chip waveguides and cavities to micro-mirrors. For real-world applications, it is also not enough to just collect the photons with the collection optics, it also needs to be ensured that the photons are channelled into a useful spatial mode, usually in an optical fiber.

Schell, AW, Takashima, H, Tran, TT, Aharonovich, I, Svedendahl, M, Quidant, R & Takeuchi, S 1970, 'Investigation of the Spectroscopic Properties of Single Defects in Hexagonal Boron Nitride', 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), IEEE.
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Among the quantum systems capable of emitting single photons, the class of recently discovered defects in hexagonal boron nitride (hBN) is especially interesting, as these defects offer much desired characteristics such as narrow emission lines and photostability [1]. Like for any new class of quantum emitters, the first challenges to solve are the understanding of their photophysics as well as to find ways to facilitate integration in photonics structures. Here, we will show our investigation of the optical transition in hBN with different methods: Employing excitation with a short laser pulse the emission properties in case of linear and non-linear excitation can be compared [2]. We find clear antibunching signals that prove the single emitter character in both excitation cases. To gain further knowledge, we also obtain saturation curves. From a comparison of one- and two-photon case insights about the level structure of the defects can be obtained. The possibility to perform two-photon excitation makes this single photon emitter an interesting candidate as a biosensor.

Schell, AW, Takashima, H, Tran, TT, Aharonovich, I, Svedendahl, M, Quidant, R & Takeuchi, S 1970, 'Investigation of the spectroscopic properties of single defects in hexagonal boron nitride', Optics InfoBase Conference Papers.
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Among the quantum systems capable of emitting single photons, the class of recently discovered defects in hexagonal boron nitride (hBN) is especially interesting, as these defects offer much desired characteristics such as narrow emission lines and photostability [1]. Like for any new class of quantum emitters, the first challenges to solve are the understanding of their photophysics as well as to find ways to facilitate integration in photonics structures. Here, we will show our investigation of the optical transition in hBN with different methods: Employing excitation with a short laser pulse the emission properties in case of linear and non-linear excitation can be compared [2]. We find clear antibunching signals that prove the single emitter character in both excitation cases. To gain further knowledge, we also obtain saturation curves. From a comparison of one- and two-photon case insights about the level structure of the defects can be obtained. The possibility to perform two-photon excitation makes this single photon emitter an interesting candidate as a biosensor.

Seifollahi, S, Piccardi, M, Borzeshi, EZ & Kruger, B 1970, 'Taxonomy-Augmented Features for Document Clustering', Communications in Computer and Information Science, Australasian Conference on Data Mining, Springer Singapore, Bathurst, NSW, Australia, pp. 241-252.
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© Springer Nature Singapore Pte Ltd. 2019. In document clustering, individual documents are typically represented by feature vectors based on term-frequency or bag-of-word models. However, such feature vectors intrinsically dismiss the order of the words in the document and suffer from very high dimensionality. For these reasons, in this paper we present novel taxonomy-augmented features that enjoy two promising characteristics: (1) they leverage semantic word embeddings to take the word order into account, and (2) they reduce the feature dimensionality to a very manageable size. Our feature extraction approach consists of three main steps: first, we apply a word embedding technique to represent the words in a word embedding space. Second, we partition the word vocabulary into a hierarchy of clusters by using k-means hierarchically. Lastly, the individual documents are projected to the hierarchy and a compact feature vector is extracted. We propose two methods for generating the features: the first uses all the clusters in the hierarchy and results in a feature vector whose dimensionality is equal to the number of the clusters. The second uses a small set of user-defined words and results in an even smaller feature vector whose dimensionality is equal to the size of the set. Numerical experiments on document clustering show that the proposed approach is capable of achieving comparable or even higher accuracy than conventional feature vectors with a much more compact representation.

Shi, Y, Tuan, HD & Savkin, AV 1970, 'Mixed Integer Nonlinear Programming for Joint Coordination of Plug-in Electrical Vehicles Charging and Smart Grid Operations', 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE.
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© 2019 IEEE. The joint coordination of plug-in electric vehicles(PEVs) charging and grid power control is to minimize both PEVs' charging cost and energy generation cost in meeting both PEVs' power demands and power grid operational constraints. A bang-bang PEV charging strategy is adopted to exploit its simple online implementation, which requires computation of a mixed integer nonlinear programming problem (MINP) in binary variables of the PEV charging and continuous variables of the grid voltages. A novel solver for this challenging MINP is proposed. Its efficiency is shown by numerical simulations.

Shi, Z, Zhang, JA, Xu, R & Cheng, Q 1970, 'Deep Learning Networks for Human Activity Recognition with CSI Correlation Feature Extraction', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai, China.
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© 2019 IEEE. Device free WiFi Sensing using channel state information (CSI) has been shown great potentials for human activity recognition (HAR). However, extracting reliable and concise feature signals remains as a challenging problem, especially in a dynamic and complex environment. In this paper, we propose a novel scheme for CSI-based HAR using deep learning network (CH-DLN), with an innovative CSI correlation feature extraction (CCFE) method. The CCFE method pre-processes the signals input to the DLN in two steps. Firstly, it uses a recursive algorithm to reduce non-activity-related information from the signal and hence enhance the activity-dependent signals. Secondly, it computes the correlation over both the time and frequency domain to disclose better signal structure and compress the signal. From such enhanced and compressed signals, we utilize the recurrent neural networking (RNN) to automatically extract deeper features, and then apply the softmax regression algorithm for classifying activities. Through extensive experimental results, our proposed scheme is shown to outperform state-of-the-art methods in recognition accuracy, with much less training time.

Singh, K, Afzal, MU, Bulger, D, Kovaleva, M & Esselle, KP 1970, 'Optimization of Beam-Steering Metasurfaces Using Modified Cross-Entropy Algorithm', 2019 URSI International Symposium on Electromagnetic Theory (EMTS), 2019 URSI International Symposium on Electromagnetic Theory (EMTS), IEEE, San Diego, CA.
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Singh, K, Afzal, MU, Bulger, D, Kovaleva, M & Esselle, KP 1970, 'Optimizing Amplitude Distribution in a Feed Array to Control Side-Lobe Levels of a Beam-Steering Metasurface', 2019 URSI International Symposium on Electromagnetic Theory (EMTS), 2019 URSI International Symposium on Electromagnetic Theory (EMTS), IEEE, San Diego, CA.
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Singh, K, Afzal, MU, Esselle, KP & Kovaleva, M 1970, 'Towards Decreasing Side Lobes Produced by Near-Field Phase Gradient Metasurfaces', 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, IEEE, pp. 1207-1208.
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© 2019 IEEE. When steering or tilting the beam of a planar high-gain antenna using a near-field phase gradient metasurface, undesirable side lobes are often noted. These side lobes can be predicted reasonably well by exciting the metasurface with a normally incident uniform plane wave but direct optimisation of such an electrically large metasurface to reduce strongest undesirable side lobes is computationally very expensive. Here we have applied a more efficient approach to reduce the levels of all side lobes below-20 dB.

Siwakoti, YP, Long, T, Barzegarkhoo, R & Blaabjerg, F 1970, 'A Dual Mode 5-Level Inverter with Wide Input Voltage Range', 2019 IEEE Energy Conversion Congress and Exposition (ECCE), 2019 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Baltimore, MD, USA, pp. 3609-3615.
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© 2019 IEEE. This paper presents a novel dual mode six- switch five-level boost-ANPC inverter (5L-DM-ABNPC) topology with wide input voltage range (400 V - 800 V). It consists of one flying-capacitor and six semiconductor switches forming a similar structure to that of conventional 5L-ANPC or 5L-ABNPC inverter. Depending on the magnitude of the input voltage, the converter can operate in buck or boost mode to produce the same ac voltage out. Further, the number and the size of the active and passive components are also reduced with simple PWM control. Consequently, this make the overall system appealing for various industrial applications. The analysis shows that the proposed topology is suitable for wide range of power conversion applications (for example, rolling mills, fans, pumps, marine appliances, mining, tractions, and most prominently grid-connected renewable energy systems). Simulation and experimental prove the concept of the proposed inverter. The principle of operation and theoretical analysis supported by key simulation and preliminary experimental waveforms are presented.

Soe Naing, HM, Miyanaga, Y, Hidayat, R & Winduratna, B 1970, 'Filterbank Analysis of MFCC Feature Extraction in Robust Children Speech Recognition', 2019 International Symposium on Multimedia and Communication Technology (ISMAC), 2019 International Symposium on Multimedia and Communication Technology (ISMAC), IEEE.
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Son, HH, Pham, CP, Franklin, DR, Walsum, TV & Luu, HM 1970, 'An Evaluation of CNN-based Liver Segmentation Methods using Multi-types of CT Abdominal Images from Multiple Medical Centers.', ISCIT, 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, Ho Chi Minh City, Vietnam, pp. 20-25.
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Automatic segmentation of CT images has recently been applied in several clinical liver applications. Convolutional Neural Networks (CNNs) have shown their effectiveness in medical image segmentation in general and also in liver segmentation. However, liver image quality may vary between medical centers due to differences in the use of CT scanners, protocols, radiation dose, and contrast enhancement. In this paper, we investigate three wells known CNNs, FCN-CRF, DRIU, and V-net, for liver segmentation using data from several medical centers. We perform qualitative evaluation of the CNNs based on Dice score, Hausdorff distance, mean surface distance and false positive rate. The results show that all three CNNs achieved a mean Dice score of over 90% in liver segmentation with typical contrast enhanced CT images of the liver. p-values from paired T-test on Dice score of the three networks using Mayo dataset are larger than 0.05 suggesting that no statistical significant difference in their performance. DRIU performs the best in term of processing time. The results also demonstrate that those CNNs have reduced performance in liver segmentation in the case of low-dose and non-contrast enhanced CT images. In conclusion, these promising results enable further investigation of alternative deep learning based approaches to liver segmentation using CT images.

Song, LZ, Qin, PY & Guo, YJ 1970, 'Conformal Transmitarray and Its Beam Scanning', 2019 International Symposium on Antennas and Propagation, ISAP 2019 - Proceedings, International Symposium on Antennas and Propagation, IEEE, Xi'an, China, pp. 1-3.
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A mechanically beam-scanning conformal transmitarray is developed in this paper. Firstly, a transmitarray element with three layers of identical square ring slots is proposed and its performance for different element thickness is studied. A transmission phase range of 330° with a maximum 3.6 dB loss can be achieved when the thickness is 0.508mm (only 0.04 wavelength at 25GHz). Secondly, a cylindrically conformal transmitarray is designed using the above antenna elements, realizing a 45.3% simulated antenna efficiency. Finally, the above fixed-beam conformal transmitarray is expanded to a beam scanning one. By rotating the feed horn to different positions, the main beam of the array can be switched to ±15°, ±10°, ±5° and 0°, while the whole size of this array is only 2.5 times larger than the fixed beam one. A prototype is fabricated and measured with a stable gain of about 18.7 dBi at all beam angles.

Suarez-Rodriguez, C, He, Y, Jayawickrama, BA & Dutkiewicz, E 1970, 'Low-Overhead Handover-Skipping Technique for 5G Networks.', WCNC, IEEE, pp. 1-6.
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Network densification has been one of the principal causes of performance gain in cellular networks, and 5G networks will not be any different. As cell sizes shrink, handovers become more frequent incurring extra delays that bury all the prospective gains. Mobility in multi-tier dense cellular networks calls for a change in the way it has been traditionally handled in an always-on world, where users take universal data access for granted. Invisible to them, mobile network operators need to provision backhauling to include advanced interference mitigation techniques. In this paper, we propose a spectrum database-aided handover management technique that aims to mitigate the number of disconnections without overloading the backhaul unnecessarily. The proposed technique exploits a spectrum database that stores reception information along with geolocation data, commercially available on any handheld device. Moreover, we have benchmarked several state-of-the-art handover schemes for 5G networks against ours in a realistic urban environment with user mobility trace data. The results highlight that our method can deliver the same downstream traffic with 33% decrease in disconnections when compared to the conventional approach. At the same time, backhaul traffic is reduced up to 68% against our counterparts.

Sun, F, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Xue, Q 1970, 'Design of Ultra-Wideband On-Chip Millimter-Wave Bandpass Filter in 0.13-μm (Bi)-CMOS Technology', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, Japan.
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© 2019 IEEE In this work, an on-chip bandpass filter (BPF) with ultra-wideband, low insertion loss, sharp selectivity and excellent in-band flatness is achieved using a novel design approach based on a quasi-lumped-element method. This approach simply utilizes folded metal strip lines with metal-insulator-metal (MIM) capacitors. To understand the principle of the presented design approach, theoretical analysis is given by means of a simplified equivalent LC-circuit model. Using the analyzed results with a full-wave electromagnetic (EM) simulator to guide the design, a BPF is implemented and fabricated in a standard 0.13-µm (Bi)-CMOS technology. The measurements show that a return loss of better than 10 dB is obtained from 13.5 to 32 GHz. Furthermore, the insertion loss of less than 2.3 dB is achieved with less than 0.1 dB in-band magnitude ripple. The BPF size without measurement pads is only 0.148 mm2 (0.37 × 0.4 mm2).

Sun, F, Zhu, X, Zhu, H, Yang, Y & Gomez-Garcia, R 1970, 'On-Chip Millimeter-Wave Bandpass Filter Design Using Multi-Layer Modified-Ground-Ring Structure', 2019 IEEE MTT-S International Microwave Symposium (IMS), 2019 IEEE/MTT-S International Microwave Symposium - IMS 2019, IEEE, Boston, MA, USA, pp. 853-856.
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© 2019 IEEE. A design approach for compact on-chip bandpass filters (BPFs) is presented in this work. It exploits a novel multi-layer modified-ground-ring structure (ML-MGRS) with additional ground plates that allows to generate a transmission zero for selectivity increase without extra occupied area. A simplified LC-equivalent circuit model is provided to understand the operational principles of this ML-MGRS concept. Moreover, to validate the experimental feasibility of this transmission-zero-creation technique for on-chip BPFs, a millimeter-wave compact BPF is designed and fabricated in a standard 0.13- CMOS technology. The measured results show that the filter exhibits out-of-band power-suppression levels above 40 dB beyond 40 GHz. The center frequency of this filter is 23.5 GHz with a power-insertion-loss level of 3.8 dB, while the input power-matching levels are higher than 10 dB from 19 GHz to 28 GHz. The size of the BPF, excluding the pads, is only 0.06 × 0.284 mm.

Sun, H-H, Ding, C, Zhu, H, Jones, B & Guo, YJ 1970, 'Cross-Band Scattering Suppression for MultiBand Base Station Antenna Arrays', 2019 8th Asia-Pacific Conference on Antennas and Propagation (APCAP), 2019 8th Asia-Pacific Conference on Antennas and Propagation (APCAP), IEEE, pp. 579-580.
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This paper presents a dual-band dual-polarized interleaved base station antenna array unit based on a filtering antenna for cross-band de-scattering. The array is configured as two columns of antenna arrays operating at a higher band from 1.71 GHz to 2.30 GHz interleaved with one column of antenna array operating at a lower band from 0.80 GHz to 0.96 GHz. By inserting low-pass high-stop filters into the low-band dipole arms, a filtering antenna that can efficiently suppress the radiation at the higher band is achieved. On one hand, the obtained filtering antenna has a slightly reduced gain and narrower bandwidth, which is attributed to the filters. On the other hand, the obtained filtering antenna working at the low band has minimum negative effect on the high band antenna performance.

Sun, Y, Yue, H, Zhang, J & Booth, C 1970, 'Minimization of Residential Energy Costs for PV-SWH and PV-T Systems', IFAC-PapersOnLine, IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, Elsevier BV, Brazil, pp. 940-945.
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Photovoltaic (PV) systems transfer solar energy into electric form. PV-T is a hybrid system that converts solar radiation into electrical and thermal energy. For residential users with limited solar panel area, there are two options to achieve economic use of solar energy. One is to install both PV and solar water heater (SWH) systems, called PV-SWH, another one is to apply the PV-T system. In this work, a residential household energy cost model is built up that includes electric vehicle (EV), energy storage system (ESS), and the back-up electricity system in PV-SWH or hybrid PV-T. The model is used to explore operation strategies to minimize user’s energy cost. The case study results suggest that the hybrid PV-T system provides more benefits for the end user from long-term perspective. Compared with typical operation without optimization, the cost saving with the proposed strategy is evident.

Suraweera, N, Li, S, Johnson, M, Collings, IB, Hanly, SV, Ni, W & Hedley, M 1970, 'Passive Target Localization by Asynchronous Self-Locating Receivers in Multipath Environments', 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE.
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Suresh, A, Mak, KL, Benserhir, J, Lee, JE-Y & Rufer, L 1970, 'Air-coupled Ultrasonic Rangefinder with Meter-long Detection Range Based on a Dual-electrode PMUT Fabricated Using a Multi-user MEMS Process', 2019 IEEE SENSORS, 2019 IEEE SENSORS, IEEE.
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Takalkar, MA, Zhang, H & Xu, M 1970, 'Improving Micro-expression Recognition Accuracy Using Twofold Feature Extraction', MultiMedia Modeling (LNCS), International Conference on Multimedia Modeling, Springer International Publishing, Thessaloniki, Greece, pp. 652-664.
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© 2019, Springer Nature Switzerland AG. Micro-expressions are generated involuntarily on a person’s face and are usually a manifestation of repressed feelings of the person. Micro-expressions are characterised by short duration, involuntariness and low intensity. Because of these characteristics, micro-expressions are difficult to perceive and interpret correctly, and they are profoundly challenging to identify and categorise automatically. Previous work for micro-expression recognition has used hand-crafted features like LBP-TOP, Gabor filter, HOG and optical flow. Recent work also has demonstrated the possible use of deep learning for micro-expression recognition. This paper is the first work to explore the use of hand-craft feature descriptor and deep feature descriptor for micro-expression recognition task. The aim is to use the hand-craft and deep learning feature descriptor to extract features and integrate them together to construct a large feature vector to describe a video. Through experiments on CASME, CASME II and CASME+2 databases, we demonstrate our proposed method can achieve promising results for micro-expression recognition accuracy with larger training samples.

Takashima, H, Ishihara, K, Maruya, H, Tashima, T, Schell, AW, Tran, TT, Aharonovich, I & Takeuchi, S 1970, 'Determination of the dipole orientation of a single defect in hexagonal boron nitride using vector beam', Optics InfoBase Conference Papers.
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Solid-state single light emitters are of great interest in photonic and quantum devices, such as bio-sensors, low threshold lasers, and single photon sources. In particular, the defects in hexagonal boron nitrides (hBNs) have recently attracted a lot of attention as novel single light emitters for such devices, owing to their high brightness, high robustness, and a narrow emission linewidth at room temperature. In order to realize those devices, it is important to determine the dipole orientation on the level of single defects. Here, we report on the three-dimensional determination of the orientation of the single defects using a vector beam.

Takashima, H, Ishihara, K, Maruya, H, Tashima, T, Schell, AW, Tran, TT, Aharonovich, I & Takeuchi, S 1970, 'Determination of the Dipole Orientation of a Single Defect in Hexagonal Boron Nitride using Vector Beam', 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), IEEE.
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Solid-state single light emitters are of great interest in photonic and quantum devices, such as bio-sensors, low threshold lasers, and single photon sources. In particular, the defects in hexagonal boron nitrides (hBNs) have recently attracted a lot of attention as novel single light emitters for such devices, owing to their high brightness, high robustness, and a narrow emission linewidth at room temperature. In order to realize those devices, it is important to determine the dipole orientation on the level of single defects. Here, we report on the three-dimensional determination of the orientation of the single defects using a vector beam.

Tao, Q, Luo, X, Wang, H & Xu, R 1970, 'Enhancing Relation Extraction Using Syntactic Indicators and Sentential Contexts', 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), IEEE, USA, pp. 1574-1580.
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© 2019 IEEE. State-of-the-art methods for relation extraction consider the sentential context by modeling the entire sentence. However, syntactic indicators, certain phrases or words like prepositions that are more informative than other words and may be beneficial for identifying semantic relations. Other approaches using fixed text triggers capture such information but ignore the lexical diversity. To leverage both syntactic indicators and sentential contexts, we propose an indicator-aware approach for relation extraction. Firstly, we extract syntactic indicators under the guidance of syntactic knowledge. Then we construct a neural network to incorporate both syntactic indicators and the entire sentences into better relation representations. By this way, the proposed model alleviates the impact of noisy information from entire sentences and breaks the limit of text triggers. Experiments on the SemEval-2010 Task 8 benchmark dataset show that our model significantly outperforms the state-of-the-art methods.

Tayab, UB, Lu, J, Yang, F, Islam, M, Zia, A & Hossain, J 1970, 'Microgrid Energy Management System for Academic Building', 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, Nadi, Fiji.
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© 2019 IEEE. In this paper, an optimal energy management system (EMS) for grid-connected microgrid is proposed. The gridconnected microgrid system comprises of photovoltaic (PV) panel, and battery as an energy storage unit. The optimal EMS is aimed to minimize the total operating cost of grid-connected microgrid for academic building. The feedforward neural network with improved salp swarm alogrithm based on weight factor is used to determine the 24-hours ahead data forecasting of load demand and PV power, while improved salp swarm alogrithm based on weight factor (WSSA) is used to perform the day-ahead optimal scheduling to control the power flow between PV, energy storage unit, load and main grid. The proposed microgrid EMS (MGEMS) is simulated using MATLAB/Simulink. The simulation result shows the effectiveness and validity of presented EMS with academic load.

Tello, AMD & Abolhasan, M 1970, 'SDN Controllers Scalability and Performance Study', 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE, Malaysia.
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Software Defined Networks (SDN) is a networking approach that decouples the intelligent control plane from networking devices and establishes a separate entity called ”controller” that rule the behaviour of the data plane on physical networking devices. Due to the rapid evolution and growth of SDN controllers in the market, this paper aims to present an extensive study on performance and scalability of different open source SDN controllers available in the existing literature. This work covers previous studies and expands them with updated information and official benchmarking methodologies. The study provides a framework based on the standards recommended by the IETF (Internet Engineering Task Force) and it will serve as a guideline to the SDN community to benchmark different SDN controllers.

Tianling Shi, Fei Wang, Hui Guo, Lijun Zhang & Li Li 1970, 'Distributed Generations Interconnection Based on the Clustering Algorithm and Graphy Theory', 8th Renewable Power Generation Conference (RPG 2019), 8th Renewable Power Generation Conference (RPG 2019), Institution of Engineering and Technology, Shanghai, China, pp. 320 (6 pp.)-320 (6 pp.).
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© 2019 Institution of Engineering and Technology. All rights reserved. Because the renewable energy generation has obvious characteristics of spatiotemporal distribution and intermittence, the interconnection of various distributed generations and loads becomes an effective solution to achieve the reliable energy supply. Considering the type and distance of distributed generations, a weight-based clustering algorithm is proposed in this paper to divide the large-scale distributed generation into sub-areas and to further form structured microgrids. Between microgrids, the topology structure is achieved and optimized using the minimum spanning tree algorithm on the basis of clustering centers. In this way, the layout optimization of large-scale distributed energy can be solved. Finally, the effectiveness of the above optimization scheme is verified by simulations, which can provide a novel idea for building an economical and reliable distributed energy interconnection network.

Tran, TT, Regan, B, Ekimov, EA, Mu, Z, Yu, Z, Gao, W, Narang, P, Solntsev, AS, Toth, M, Aharonovich, I & Bradac, C 1970, 'Anti-Stokes Excitation of Solid-State Quantum Emitters for Nanoscale Thermometry', Conference on Lasers and Electro-Optics, CLEO: Science and Innovations, OSA, San Jose, California, United States.
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© 2019 The Author(s) We report the first demonstration of Anti-Stokes excitation on a single solid-state quantum emitter-namely the germanium-vacancy center in diamond and its application as a high-sensitive nanoscale thermal sensor.

Trede, F, Braun, R & Brookes, W 1970, 'Studio-based learning in a first year engineering curriculum: Exploring students' learning experiences and reflections using the rich picture method.', ITHET, International Conference on Information Technology Based Higher Education and Training, IEEE, Magdeburg, Germany, pp. 1-5.
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© 2019 IEEE. We have described engineering students in their first year participating in a 'studio' based experience. We used a rich picture method imbedded in research interviews to explore student's attitudes to, and understandings of their studio experience. Our findings demonstrate that this research method produces an enriched understanding of and deep insights into student experiences in the studio.

Tsutsui, H, Yamada, K, Sudou, A & Miyanaga, Y 1970, 'An Evaluation of Stack Light Indicator Color Detection System Using Web Cameras for Automatic Production Lines', 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), IEEE.
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Tun, EE, Aramvith, S & Miyanaga, Y 1970, 'A Fast CU Depth Estimation Algorithm for HEVC Inter Coding', 2019 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia), 2019 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia), IEEE.
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Tuyen Le, A, Tran, LC, Huang, X & Guo, J 1970, 'Analog Least Mean Square Loops for Self-Interference Cancellation in In-Band Full-Duplex Systems', 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE, pp. 1-1.
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Ullah Siddiqi, MW & Lee, JE-Y 1970, 'Quality Factor Enhancement of AlN-on-Si Lamb Wave Resonators Using a Hybrid of Phononic Crystal Shapes in Anchoring Boundaries', 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), 2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII), IEEE.
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Unanue, IJ, Arratibel, LG, Borzeshi, EZ & Piccardi, M 1970, 'English-Basque statistical and neural machine translation', LREC 2018 - 11th International Conference on Language Resources and Evaluation, Language Resources and Evaluation Conference, European Language Resource Association, Miyazaki, Japan, pp. 880-885.
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Neural Machine Translation (NMT) has attracted increasing attention in the recent years. However, it tends to require very large training corpora which could prove problematic for languages with low resources. For this reason, Statistical Machine Translation (SMT) continues to be a popular approach for low-resource language pairs. In this work, we address English-Basque translation and compare the performance of three contemporary statistical and neural machine translation systems: OpenNMT, Moses SMT and Google Translate. For evaluation, we employ an open-domain and an IT-domain corpora from the WMT16 resources for machine translation. In addition, we release a small dataset (Berriak) of 500 highly-accurate English-Basque translations of complex sentences useful for a thorough testing of the translation systems.

Unanue, IJ, Borzeshi, EZ, Esmaili, N & Piccardi, M 1970, 'ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems', NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference, pp. 430-436.
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Regularization of neural machine translation is still a significant problem,especially in low-resource settings. To mollify this problem, we proposeregressing word embeddings (ReWE) as a new regularization technique in a systemthat is jointly trained to predict the next word in the translation(categorical value) and its word embedding (continuous value). Such a jointtraining allows the proposed system to learn the distributional propertiesrepresented by the word embeddings, empirically improving the generalization tounseen sentences. Experiments over three translation datasets have showed aconsistent improvement over a strong baseline, ranging between 0.91 and 2.54BLEU points, and also a marked improvement over a state-of-the-art system.

Uzair, M, Li, L, Zhu, JG & Eskandari, M 1970, 'A protection scheme for AC microgrids based on multi-agent system combined with machine learning', 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, Nadi, Fiji.
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© 2019 IEEE. Traditional protection schemes at the distribution level designed for unidirectional power flow will be compromised due to bi-directional flow of power with the increased penetration of distributed generation (DG) sources, resulting in miscoordination between protection devices. This paper proposes a new microgrid protection method based on the multi-agent system (MAS) combined with machine learning (ML) for fault detection in autonomous and grid-connected modes, protection coordination and updating relay settings to achieve adaptive protection. MAS framework with various layers and roles of each agent are described in detail. A meshed microgrid model is developed in Simulink to collect fault data for training and testing ML algorithms, while the behaviour of individual agents and interactions between them are validated in AnyLogic simulation software. The simulation results confirmed that the proposed MAS algorithm could provide primary and backup protection in both modes of microgrid.

Van Huynh, N, Hoang, DT, Nguyen, DN & Dutkiewicz, E 1970, 'Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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© 2019 IEEE. Practical and efficient network slicing often faces real-time dynamics of network resources and uncertain customer demands. This work provides an optimal and fast resource slicing solution under such dynamics by leveraging the latest advances in deep learning. Specifically, we first introduce a novel system model which allows the network provider to effectively allocate its combinatorial resources, i.e., spectrum, computing, and storage, to various classes of users. To allocate resources to users while taking into account the dynamic demands of users and resources constraints of the network provider, we employ a semi-Markov decision process framework. To obtain the optimal resource allocation policy for the network provider without requiring environment parameters, e.g., uncertain service time and resource demands, a Q-learning algorithm is adopted. Although this algorithm can maximize the revenue of the network provider, its convergence to the optimal policy is particularly slow, especially for problems with large state/action spaces. To overcome this challenge, we propose a novel approach using an advanced deep Q-learning technique, called deep dueling that can achieve the optimal policy at few thousand times faster than that of the conventional Q-learning algorithm. Simulation results show that our proposed framework can improve the long-term average return of the network provider up to 40% compared with other current approaches.

Vu, L, Cao, VL, Nguyen, QU, Nguyen, DN, Hoang, DT & Dutkiewicz, E 1970, 'Learning Latent Distribution for Distinguishing Network Traffic in Intrusion Detection System', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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© 2019 IEEE. We develop a novel deep learning model, Multi-distributed Variational AutoEncoder (MVAE), for the network intrusion detection. To make the traffic more distinguishable, MVAE introduces the label information of data samples into the Kullback-Leibler (KL) term of the loss function of Variational AutoEncoder (VAE). This label information allows MVAEs to force/partition network data samples into different classes with different regions in the latent feature space. As a result, the network traffic samples are more distinguishable in the new representation space (i.e., the latent feature space of MVAE), thereby improving the accuracy in detecting intrusions. To evaluate the efficiency of the proposed solution, we carry out intensive experiments on two popular network intrusion datasets, i.e., NSL-KDD and UNSW-NB15 under four conventional classifiers including Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). The experimental results demonstrate that our proposed approach can significantly improve the accuracy of intrusion detection algorithms up to 24.6% compared to the original one (using area under the curve metric).

Vu, TT, Nguyen, DN, Hoang, DT & Dutkiewicz, E 1970, 'QoS-Aware Fog Computing Resource Allocation Using Feasibility-Finding Benders Decomposition', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Hawaii.
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We investigate a joint offloading and resource allocation under a multi-layer cooperative fog and cloud computing architecture, aiming to minimize the total energy consumption of mobile devices while meeting users' QoS requirements, e.g., delay, security, and application compatibility. Due to the mutual coupling amongst offloading decision and resource allocation variables, the resulting optimization is a mixed integer non- linear programming problem that is NP-hard. Such problem often requires exponential time to find the optimal solution. In this work, we propose a distributed approach, namely feasibility-finding Benders decomposition (FFBD), that decomposes the original problem into a master problem for the offloading decision and subproblems for resource allocation. These (simpler) subproblems can be solved in parallel at fog nodes, thereby reducing both the complexity and the computational time. The numerical results show that the FFBD always returns the optimal solution of the problem with significantly less computation time (e.g., in comparing with the branch-and-bound method).

Wang, Q, Jia, W, He, X, Lu, Y, Blumenstein, M, Huang, Y & Lyu, S 1970, 'DeepText: Detecting Text from the Wild with Multi-ASPP-Assembled DeepLab', 2019 International Conference on Document Analysis and Recognition (ICDAR), 2019 International Conference on Document Analysis and Recognition (ICDAR), IEEE, Sydney, Australia, pp. 208-213.
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© 2019 IEEE. In this paper, we address the issue of scene text detection in the way of direct regression and successfully adapt an effective semantic segmentation model, DeepLab v3+ [1], for this application. In order to handle texts with arbitrary orientations and sizes and improve the recall of small texts, we propose to extract features of multiple scales by inserting multiple Atrous Spatial Pyramid Pooling (ASPP) layers to the DeepLab after the feature maps with different resolutions. Then, we set multiple auxiliary IoU losses at the decoding stage and make auxiliary connections from the intermediate encoding layers to the decoder to assist network training and enhance the discrimination ability of lower encoding layers. Experiments conducted on the benchmark scene text dataset ICDAR2015 demonstrate the superior performance of our proposed network, named as DeepText, over the state-of-the-art approaches.

Wang, Q, Jia, W, He, X, Lu, Y, Blumenstein, M, Huang, Y & Lyu, S 1970, 'ReELFA: A Scene Text Recognizer with Encoded Location and Focused Attention', 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), IEEE, Australia.
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Wang, S, Wang, Z, Deng, J, Guo, Y & Dorrell, DG 1970, 'The Analysis of a Ferriteless Rectangular Coupler With Reactive Assistive shielding Coils For EV Wireless Charging', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, Australia, pp. 1622-1627.
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© 2019 IEEE. Autonomous driving technology has made significant progress in recent decades. For fully autonomous driving of an electric vehicle, the recharging process should be possible without a manually fixed connection. Wireless charging technology is a promising solution for electric vehicle recharging automation. The wireless transformer/coupler is the key component in electric vehicle wireless charging. The maximum power transfer capability and efficiency are limited by the coupler. To reach the required power level, efficiency and electromagnetic exposure to surrounding area, the coupler should be analyzed. In this paper, a coupler with assistive coils is presented and analyzed. The assistive coils perform as reactive shielding coils as well as flux concentrating coils. Finite element simulation and circuit simulation results are shown.

Wang, X, Yu, P, Yu, G, Zha, X, Ni, W, Liu, RP & Guo, YJ 1970, 'A High-Performance Hybrid Blockchain System for Traceable IoT Applications', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Network and System Security, Springer International Publishing, Sapporo, Japan, pp. 721-728.
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© 2019, Springer Nature Switzerland AG. Blockchain, as an immutable distributed ledger, can be the key to realize secure and trustworthy IoT applications. However, existing blockchains can hardly achieve high-performance and high-security for large-scale IoT applications simultaneously. In this paper, we propose a hyper blockchain architecture combining the security of public blockchains with the efficiency of private blockchains. An IoT anchoring smart contract is proposed to anchor private IoT blockchains into a public blockchain. An IoT device management smart contract is also designed to trace sensory data. A comprehensive analysis reveals that the proposed hybrid blockchain system can achieve the performance of private blockchains and resist tampering.

Watterson, P, Gorrie, C & Herok, G 1970, 'Invited Faculty Abstracts from the International Neuromodulation Society’s 14th World Congress', Neuromodulation: Technology at the Neural Interface, International Neuromodulation Society 14th World Congress, Elsevier BV, Sydney, Australia, pp. e296-e584.
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White, S, Wang, K, Tran, TT, Kianinia, M, Titchener, JG, Graefe, M, Fischbach, S, Rodt, S, Song, JD, Reitzenstein, S, Aharonovich, I, Sukhorukov, AA, Szameit, A & Solntsev, AS 1970, 'Tomography of quantum dots in a non-hermitian photonic chip', AOS Australian Conference on Optical Fibre Technology (ACOFT) and Australian Conference on Optics, Lasers, and Spectroscopy (ACOLS) 2019, AOS Australian Conference on Optical Fibre Technology (ACOFT) and Australian Conference on Optics, Lasers, and Spectroscopy (ACOLS) 2019, SPIE, Melbourne, Australia.
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© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Quantum optical information systems offer the potential for secure communication and fast quantum computation. To fully characterise a quantum optical system one has to use quantum tomography.1 The integration of quantum optics onto photonic chips provides advantages such as miniaturisation and stability, significantly improving quantum tomography using both re-configurable, and more recently, simpler static designs. These on-chip designs have, so far, only used probabilistic single photon sources. Here we are working towards quantum tomography using a true deterministic source-an InGaAs quantum dot.

White, SJU, Wang, K, Tran, TT, Kianinia, M, Titchener, J, Grafe, M, Fischbach, S, Rodt, S, Song, J-D, Reitzenstein, S, Aharonovich, I, Sukhorukov, AA, Szameit, A & Solntsev, AS 1970, 'Tomography of Quantum Dots in a Non-Hermitian Photonic Chip', 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), IEEE, Munich, GERMANY.
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© 2019 IEEE. Quantum optical information systems offer the potential for secure communication and fast quantum computation. To fully characterise a quantum optical system one has to use quantum tomography [1]. Integration of quantum optics onto photonic chips provides advantages such as miniaturisation and stability, and also significantly improves quantum tomography using both re-configurable [2], and more recently, simpler static designs [3,4]. These on-chip designs have, so far, only used probabilistic single photon sources. Here we are working towards quantum tomography using a true deterministic source - a quantum dot. The scheme of the proposed experiment is shown in Fig. 1A. So far we have fabricated and characterised the performance of an InGaAs quantum dot monolithically integrated into a microlens [5], and completed the design, fabrication and classical characterisation of a photonic chip for quantum tomography.

White, SJU, Wang, K, Tran, TT, Kianinia, M, Titchener, J, Gräfe, M, Fischbach, S, Rodt, S, Song, JD, Reitzenstein, S, Aharonovich, I, Sukhorukov, AA, Szameit, A & Solntsev, AS 1970, 'Tomography of quantum dots in a non-Hermitian photonic chip', Optics InfoBase Conference Papers.
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Quantum optical information systems offer the potential for secure communication and fast quantum computation. To fully characterise a quantum optical system one has to use quantum tomography [1]. Integration of quantum optics onto photonic chips provides advantages such as miniaturisation and stability, and also significantly improves quantum tomography using both re-configurable [2], and more recently, simpler static designs [3,4]. These on-chip designs have, so far, only used probabilistic single photon sources. Here we are working towards quantum tomography using a true deterministic source - a quantum dot. The scheme of the proposed experiment is shown in Fig. 1A. So far we have fabricated and characterised the performance of an InGaAs quantum dot monolithically integrated into a microlens [5], and completed the design, fabrication and classical characterisation of a photonic chip for quantum tomography.

Wilson, KJ, Alabd, R, Abolhasan, M, Franklin, DR & Safavi-Naeini, M 1970, 'Localisation of the Lines of Response in a Continuous Cylindrical Shell PET Scanner.', EMBC, IEEE Engineering in Medicine and Biology Conference, IEEE, Berlin, Germany, pp. 4844-4850.
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This work presents a technique for localising the endpoints of the lines of response in a PET scanner based on a continuous cylindrical shell scintillator. The technique is demonstrated by applying it to a simulation of a sensitivity-optimised continuous cylindrical shell PET system using two novel scintillator materials - a transparent ceramic garnet, GLuGAG:Ce, and a LuF$_3$:Ce-polystyrene nanocomposite. Error distributions for the endpoints of the lines of response in the axial, tangential and radial dimension as well as overall endpoint spatial error are calculated for three source positions; the resultant distribution of error in the placement of the lines of response is also estimated.

Wu, J, Yao, L, Huang, Y, Xu, J, Wu, Q & Huang, L 1970, 'Improving Person Re-Identification Performance Using Body Mask Via Cross-Learning Strategy', 2019 IEEE Visual Communications and Image Processing (VCIP), 2019 IEEE Visual Communications and Image Processing (VCIP), IEEE, Sydney, Australia.
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© 2019 IEEE. The task of person re-identification (re-id) is to find the same pedestrian across non-overlapping cameras. Normally, the performance of person re-id can be affected by background clutters. However, existing segmentation algorithms are hard to obtain perfect foreground person images. To effectively leverage the body (foreground) cue, and in the meantime pay attention to discriminative information in the background (e.g., companion or vehicle), we propose to use a cross-learning strategy to take both foreground and other discriminative information into account. In addition, since currently existing foreground segmentation result always involves noise, we use Label Smoothing Regularization (LSR) to strengthen the generalization capability during our learning process. In experiments, we pick up two state-of-The-Art person re-id methods to verify the effectiveness of our proposed cross-learning strategy. Our experiments are carried out on two publicly available person re-id datasets. Obvious performance improvements can be observed on both datasets.

Xie, H-B, Li, C, Xu, RYD & Mengersen, K 1970, 'Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation', Machine Learning, Optimization, and Data Science (LNCS), International Conference on Machine Learning, Optimization, and Data Science, Springer International Publishing, Siena, Italy, pp. 484-495.
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© Springer Nature Switzerland AG 2019. Development of effective and efficient techniques for video analysis is an important research area in machine learning and computer vision. Matrix factorization (MF) is a powerful tool to perform such tasks. In this contribution, we present a hierarchical robust kernelized Bayesian matrix factorization (RKBMF) model to decompose a data set into low rank and sparse components. The RKBMF model automatically infers the parameters and latent variables including the reduced rank using variational Bayesian inference. Moreover, the model integrates the side information of similarity between frames to improve information extraction from the video. We employ RKBMF to extract background and foreground information from a traffic video. Experimental results demonstrate that RKBMF outperforms state-of-the-art approaches for background/foreground separation, particularly where the video is contaminated.

Xie, J, Ma, Z, Zhang, G, Xue, J-H, Tan, Z-H & Guo, J 1970, 'Soft Dropout And Its Variational Bayes Approximation', 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), IEEE, Pittsburgh, PA, USA.
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Soft dropout, a generalization of standard “hard” dropout, is introduced to regularize the parameters in neural networks and prevent overfitting. We replace the “hard” dropout mask following a Bernoulli distribution with the “soft” mask following a beta distribution to drop the hidden nodes in different levels. The soft dropout method can introduce continuous mask coefficients in the interval of [0, 1], rather than only zero and one. Meanwhile, in order to implement the adaptive dropout rate via adaptive distribution parameters, we respectively utilize the half-Gaussian distributed and the half-Laplace distributed variables to approximate the beta distributed masks and apply a variation of variational Bayes optimization called stochastic gradient variational Bayes (SGVB) algorithm to optimize the distribution parameters. In the experiments, compared with the standard soft dropout with fixed dropout rate, the adaptive soft dropout method generally improves the performance. In addition, the proposed soft dropout and its adaptive versions achieve performance improvement compared with the referred methods on both image classification and regression tasks.

Xie, Y, Xu, Z, Gong, S, Xu, J, Hoang, DT & Niyato, D 1970, 'Backscatter-Assisted Hybrid Relaying Strategy for Wireless Powered IoT Communications', 2019 IEEE Global Communications Conference (GLOBECOM), GLOBECOM 2019 - 2019 IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA, pp. 1-6.
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© 2019 IEEE. In this work, we consider multiple energy harvesting relays to assist information transmission from a hybrid access point (HAP) to a distant receiver. The multi-antenna HAP also beamforms RF power to the relays by using a power-splitting protocol. We aim to maximize the throughput by jointly optimizing the HAP's beamforming strategy as well as individual relays' energy harvesting and collaborative beamforming strategies. With dense user devices, the throughput maximization takes account of the direct links from the HAP to the receiver as they are short and contribute considerably to the overall throughput. Moreover, we introduce the concept of hybrid relaying communications which allows the energy harvesting relays to switch between two radio modes. In particular, the relays can operate either in RF communications or backscatter communications, depending on their channel conditions and energy status. This results in a non-convex and combinatorial throughput maximization problem. With the fixed relay mode, we can find a feasible lower performance bound via convex approximation, which further motivates our algorithm design to update the relay mode in an iterative manner. Simulation results verify that the proposed hybrid relaying strategy can achieve significant performance improvement compared to the conventional relaying strategy with all relays operating in the RF communications mode.

Xiong, H, Fu, H, Zhu, J, Liu, J, Luo, X & Qiu, B 1970, 'Design of 3-D Magnetic Field Sensor and Calibration Platform for TMS', 2019 IEEE International Conference on Mechatronics and Automation (ICMA), 2019 IEEE International Conference on Mechatronics and Automation (ICMA), IEEE, Tianjin, China, pp. 1823-1829.
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© 2019 IEEE. In order to build an accurate measurement structure for transcranial magnetic stimulation (TMS) pre-testing, a kind of three - dimensional (3-D) magnetic field sensor and calibration platform are designed in this paper. This measurement structure is made up of 883-D magnetic field sensors. The 3-D magnetic field sensors based on Faraday law of electromagnetic induction are used to accurately measure pulsed magnetic fields generated by the stimulating coil. The coefficients of the sensors are calibrated in a designed 3-D calibration platform. And a series of experiments are carried out to verify the accuracy and stability of the sensors. The results from experiments indicate that the average measurement accuracy of 88 sensors is 1% and sensor performance is stable. In conclusion, this work provides a promising way to avoid direct human experiments and improve the security of TMS.

Xu, Y, Afshar, S, Singh, RK, Wang, R, van Schaik, A & Hamilton, TJ 1970, 'A Binaural Sound Localization System using Deep Convolutional Neural Networks', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, JAPAN.
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Xu, Y, Xu, D, Hong, X, Ouyang, W, Ji, R, Xu, M & Zhao, G 1970, 'Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection', 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, Seoul, Korea.
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Recent saliency models extensively explore to incorporate multi-scale contextual information from Convolutional Neural Networks (CNNs). Besides direct fusion strategies, many approaches introduce message-passing to enhance CNN features or predictions. However, the messages are mainly transmitted in two ways, by feature-to-feature passing, and by prediction-to-prediction passing. In this paper, we add message-passing between features and predictions and propose a deep unified CRF saliency model . We design a novel cascade CRFs architecture with CNN to jointly refine deep features and predictions at each scale and progressively compute a final refined saliency map. We formulate the CRF graphical model that involves message-passing of feature-feature, feature-prediction, and prediction-prediction, from the coarse scale to the finer scale, to update the features and the corresponding predictions. Also, we formulate the mean-field updates for joint end-to-end model training with CNN through back propagation. The proposed deep unified CRF saliency model is evaluated over six datasets and shows highly competitive performance among the state of the arts.

Xu, Z, Ni, W, Li, L-G, Zhang, J-H, Wu, C-M, Li, C-Y & Zhang, Y-H 1970, 'The calculation and realization of the visibility between patches of complex 3D scene based on super-computation', Third International Conference on Photonics and Optical Engineering, The International Conference on Photonics and Optical Engineering, SPIE.
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Yang, T, Ding, C, Ziolkowski, RW & Guo, YJ 1970, 'A THz Single-Polarization-Single-Mode (SPSM) photonic crystal fiber based on epsilon-near-zero material', AOS Australian Conference on Optical Fibre Technology (ACOFT) and Australian Conference on Optics, Lasers, and Spectroscopy (ACOLS) 2019, AOS Australian Conference on Optical Fibre Technology (ACOFT) and Australian Conference on Optics, Lasers, and Spectroscopy (ACOLS) 2019, SPIE, Melbourne, AUSTRALIA.
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© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. To overcome the crosstalk happening between two degenerately fundamental modes of a fiber in Terahertz (THz) regime, a novel photonic crystal fiber (PCF) that yields a wide range of single-polarization-single-mode (SPSM) propagation with large loss differences (LDs) is designed. The method used to realize this SPSM PCF is to deposit an epsilon-near-zero (ENZ) material in four selected air holes in the cladding, which ends up with four ENZ rings. These ENZ rings introduce significant LDs between the wanted (X-polarized) and unwanted (Y-polarized and high order) modes. Extensive simulation results demonstrate that the LDs between the wanted and unwanted modes vary with the thickness of ENZ rings. With a very short length (4 cm) of the proposed PCF, pure SPSM propagation, i.e., the unwanted modes are 20 dB lower than the wanted mode, can be achieved from 1 to 1.2 THz.

Yang, Y & Zhu, X 1970, 'Overview of Millimeter-Wave On-Chip and Off-Chip Bandpass Filter Designs', 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT), 2019 International Conference on Microwave and Millimeter Wave Technology (ICMMT), IEEE, Guangzhou, China, pp. 1-2.
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© 2019 IEEE. In this paper, a brief review of recent advancement in on-chip and off-chip millimeter-wave bandpass filter designs are presented. First, the general background about the two solutions are provided, with a general discussion about their pros and cons. Second, the representative state-of-the-art works are presented. This short paper provides the researchers, in the relative fields, with some guidelines when deciding bandpass filters for a system-on-chip (SoC) solution.

Yang, Y, Hou, Z, Zhu, X, Che, W & Xue, Q 1970, 'A Millimeter-Wave Reconfigurable On-Chip Coupler with Tunable Power-Dividing Ratios', 2019 IEEE MTT-S International Wireless Symposium (IWS), 2019 IEEE MTT-S International Wireless Symposium (IWS), IEEE.
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© 2019 IEEE. This paper presents a millimeter-wave on-chip tunable coupler with tunable power dividing ratios and constant phase responses. Composed by two coupled-lines, two capacitors and two series-connected varactors, the proposed tunable coupler offers wideband frequency responses. Theoretical analysis for wideband operation is provided with design parameters. For demonstration, a millimeter-wave tunable coupler is implemented in a standard 0.13-μm SiGe (Bi) CMOS technology and measured through an on-wafer probing system. From 25 to 31 GHz, the proposed tunable coupler shows a power-dividing ratio tuned from 0 to 5 dB, while maintaining an in-band return loss of better than 10 dB and an output isolation of 20 dB, simultaneously. The phase imbalance is better than ±4° with a measured insertion loss of 1.6 dB across the entire tuning range.

Yang, Y, Zhu, X, Che, W & Xue, Q 1970, 'A Millimeter-Wave On-Chip Bandpass Filter with All-Pole Characteristics', 2019 IEEE MTT-S International Wireless Symposium (IWS), 2019 IEEE MTT-S International Wireless Symposium (IWS), IEEE.
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© 2019 IEEE. This paper presents a millimeter-wave on-chip bandpass filter (BPF) with all-pole characteristics. It is believed to be the first time that an all-pole frequency response has been successfully implemented by using a standard 0.13-μm Silicon-Germanium (SiGe) technology. To further demonstrate the feasibility of using this approach in practice, the designed resonator is fabricated. The measured results show that the BPF has an insertion loss of 2.2 dB at the center frequency of 31 GHz. The return loss is better than 10 dB from 26.5 GHz to 37.5 GHz. In addition, the out-of-band suppression of this filter is superior, which is better than 20 dB beyond 50.6 GHz. The chip size, excluding the pads, is only 0.091 × 0.268 mm2.

Yao, Q, Lu, D & Lei, G 1970, 'Battery Impedance Measurement Using Fast Square Current Perturbation', 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), IEEE, Singapore.
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This paper proposes a simple but accurate battery impedance measurement method. Unlike other complicated and expensive strategies, the proposed method only need a MOSFET and a resistor. A square current perturbation will be generated by the proposed circuitry and a voltage response across the tested battery can be obtained. Bases on the voltage and current signals, Discrete Fourier transform is used to calculate the impedance at fundamental and odd harmonic frequencies. The feasibility of the proposed method has been verified by simulation and experiments. The error of the proposed method is less than 5% at 80% SoC (state of charge) compared with the conventional small AC (alternating current) signal injection method.

Yuan, Y, Kong, X, Fang, G, Liu, L & Khruahong, S 1970, 'Development of Semantic Model of Multi-Level-Building Navigation Using Indoor Ontology and Dijkstra's Algorithm', 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), IEEE, Gold Coast, Australia.
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Location based services (LBS) can be separated into a number of layers: technology layer, application layer, standard layer, and social-ethical layer. This paper presents an ontology development at standard layer. We developed an ontology to identify and classify indoor semantic information to guide the development of LBS applications for multi-level building navigation. This ontology proposed models of multilevel building properties as classes of building, level, zone, link, node, and coordinate. To apply this ontology, we develop an indoor navigation algorithm using the ontology classes and Dijkstra’s algorithm for shortest path in user navigation. A prototype and experiments are implemented to validate this ontology.

Zdankowski, P, Trusiak, M, McGloin, D & Swedlow, JR 1970, 'Quasi-noise-free stimulated emission depletion microscopy imaging of thick samples using adaptive optics and block-matching 3D filtering', Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP), Imaging Systems and Applications, OSA.
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© 2019 The Author(s). We present a novel-method of increasing signal-to-noise-ratio and effective-resolution of STED microscope by combining aberration-correction and image-processing. We imaged 15μm thick mitotic cell and observed in-plane resolution of 118nm without filtering and 70nm with filtering.

Zhang, G, Tao, J & Qiu, X 1970, 'Empirical study of decentralized multi-channel active noise control based on the genetic algorithm', Proceedings of the International Congress on Acoustics, International Congress on Acoustics, International Congress on Acoustics, Aachen, Germany, pp. 6913-6920.
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In an active noise control (ANC) system, computational complexity is one major concern when designing practical control algorithms. One approach to reducing computational complexity is to apply a decentralized control scheme rather than the centralized scheme. The decentralized scheme attempts to control a number of ANC subsystems independently, where for simplicity, one subsystem consists of one loudspeaker and one error microphone. Our recent published article has shown theoretically that a decentralized two-channel ANC system can achieve the same noise reduction performance as the centralized one with guaranteed convergence in the frequency domain. In this work, we attempt to extend the results from two-channel case to N (N>1) channel case. The challenge sits in finding N complex numbers that could properly shape the eigenvalues of an N ´ N matrix for each frequency bin towards guaranteed convergence. Due to the problem complexity, we conduct empirical study by using the genetic algorithm (GA). Simulation results on the channel numbers of 4, 6, and 12 demonstrate that the resulting decentralized ANC controller is also able to achieve the same noise reduction performance as the centralized controller.

Zhang, H, Huang, X & Zhang, JA 1970, 'Comparison of OTFS Diversity Performance over Slow and Fast Fading Channels', 2019 IEEE/CIC International Conference on Communications in China (ICCC), 2019 IEEE/CIC International Conference on Communications in China (ICCC), IEEE, Changchun, China, pp. 828-833.
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© 2019 IEEE. Orthogonal time frequency space (OTFS) modulation shows great performance improvement over high-mobility wireless channels compared with traditional orthogonal frequency division multiplexing (OFDM). In this paper, we first derive the input and output relationship of OTFS signal in the delay-time domain, which shows that OTFS can be regarded as a combination of OFDM and single-carrier frequency-division multiple access (SC-FDMA). We then examine the diversity order of an OTFS system through received signal-to-noise ratio analysis and predict that this modulation technique can potentially achieve full diversity in both delay and Doppler domains. Finally, we simulate the OTFS performance based on 5G tapped-delay-line channel models under both slow and fast fading conditions. Extensive simulation results confirm that OTFS performs significantly better than other modulation techniques in fast fading channels.

Zhang, H, Huang, X, Zhang, JA, Guo, YJ, Song, R, Wang, C, Wu, W, Xu, X & Lu, Z 1970, 'A High-Speed Low-Cost Millimeter Wave System with Dual Pulse Shaping Transmission and Symbol Rate Equalization Techniques', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, Japan.
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© 2019 IEEE A millimeter wave system with commercially available and affordable data conversion devices is presented in this paper for achieving high-speed and low-cost wireless communications. By adopting the proposed dual pulse shaping (DPS) transmission scheme, the system can achieve full Nyquist rate transmission with only half of the sampling rate required by conventional Nyquist pulse shaping. Structures of the DPS transmitter and receiver are described and effective symbol rate equalization techniques suitable for DPS transmission are presented. Simulation results with two sets of practical dual spectral shaping pulses are also provided to compare system performance with the conventional Nyquist pulse shaping system.

Zhang, H, Huang, X, Zhang, T, Zhang, JA & Jay Guo, Y 1970, 'A 30 Gbps Low-Complexity and Real-Time Digital Modem for Wireless Communications at 0.325 THz', 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019 19th International Symposium on Communications and Information Technologies (ISCIT), IEEE, pp. 260-264.
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© 2019 IEEE. A high-speed wideband terahertz (THz) communication system with low-complexity and real-time digital signal processing (DSP) is presented in this paper. The architectures of baseband platform, intermediate frequency (IF) module and radio frequency (RF) frontend are described. For real-time DSP implementation with affordable field programmable gate array (FPGA) device, some effective strategies are discussed to reduce resource usage and ensure that the clock constraints are met. Adopting these strategies, all physical layer DSP modules are implemented in two FPGAs with more than 300 MHz system clock. The experimental test results using the developed real-time digital modem prototype demonstrate the superb performance for THz wireless communications.

Zhang, J, Wu, Q, Zhang, J, Shen, C & Lu, J 1970, 'Mind Your Neighbours: Image Annotation With Metadata Neighbourhood Graph Co-Attention Networks', 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE.
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Zhang, M, Li, H & Su, S 1970, 'High Dimensional Bayesian Optimization via Supervised Dimension Reduction', Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}, International Joint Conferences on Artificial Intelligence Organization, Macao, China, pp. 4292-4298.
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Bayesian optimization (BO) has been broadly applied to computational expensive problems, but it is still challenging to extend BO to high dimensions. Existing works are usually under strict assumption of an additive or a linear embedding structure for objective functions. This paper directly introduces a supervised dimension reduction method, Sliced Inverse Regression (SIR), to high dimensional Bayesian optimization, which could effectively learn the intrinsic sub-structure of objective function during the optimization. Furthermore, a kernel trick is developed to reduce computational complexity and learn nonlinear subset of the unknowing function when applying SIR to extremely high dimensional BO. We present several computational benefits and derive theoretical regret bounds of our algorithm. Extensive experiments on synthetic examples and two real applications demonstrate the superiority of our algorithms for high dimensional Bayesian optimization.

Zhang, P, Wu, Q & Xu, J 1970, 'VN-GAN: Identity-preserved Variation Normalizing GAN for Gait Recognition', 2019 International Joint Conference on Neural Networks (IJCNN), 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, Budapest, Hungary.
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© 2019 IEEE. Gait is recognized as a unique biometric characteristic to identify a walking person remotely across surveillance networks. However, the performance of gait recognition severely suffers challenges from view angle diversity. To address the problem, an identity-preserved Variation Normalizing Generative Adversarial Network (VN-GAN) is proposed for learning purely identity-related representations. It adopts a coarse-to-fine manner which firstly generates initial coarse images by normalizing view to an identical one and then refines the coarse images by injecting identity-related information. In specific, Siamese structure with discriminators for both camera view angles and human identities is utilized to achieve variation normalization and identity preservation of two stages, respectively. In addition to discriminators, reconstruction loss and identity-preserving loss are integrated, which forces the generated images to be the same in view and to be discriminative in identity. This ensures to generate identity-related images in an identical view of good visual effect for gait recognition. Extensive experiments on benchmark datasets demonstrate that the proposed VN-GAN can generate visually interpretable results and achieve promising performance for gait recognition.

Zhang, P, Wu, Q & Xu, J 1970, 'VT-GAN: View Transformation GAN for Gait Recognition Across Views', 2019 International Joint Conference on Neural Networks (IJCNN), 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, Budapest, Hungary.
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© 2019 IEEE. Recognizing gaits without human cooperation is of importance in surveillance and forensics because of the benefits that gait is unique and collected remotely. However, change of camera view angle severely degrades the performance of gait recognition. To address the problem, previous methods usually learn mappings for each pair of views which incurs abundant independently built models. In this paper, we proposed a View Transformation Generative Adversarial Networks (VT-GAN) to achieve view transformation of gaits across two arbitrary views using only one uniform model. In specific, we generated gaits in target view conditioned on input images from any views and the corresponding target view indicator. In addition to the classical discriminator in GAN which makes the generated images look realistic, a view classifier is imposed. This controls the consistency of generated images and conditioned target view indicator and ensures to generate gaits in the specified target view. On the other hand, retaining identity information while performing view transformation is another challenge. To solve the issue, an identity distilling module with triplet loss is integrated, which constrains the generated images inheriting identity information from inputs and yields discriminative feature embeddings. The proposed VT-GAN generates visually promising gaits and achieves promising performances for cross-view gait recognition, which exhibits great effectiveness of the proposed VT-GAN.

Zhang, X, Liu, J, Li, Y, Cui, Q, Tao, X & Liu, RP 1970, 'Blockchain Based Secure Package Delivery via Ridesharing', 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), IEEE.
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© 2019 IEEE. Delivery service via ridesharing is a promising service to share travel costs and improve vehicle occupancy. Existing ridesharing systems require participating vehicles to periodically report individual private information (e.g., identity and location) to a central controller, which is a potential central point of failure, resulting in possible data leakage or tampering in case of controller break down or under attack. In this paper, we propose a Blockchain secured ridesharing delivery system, where the immutability and distributed architecture of the Blockchain can effectively prevent data tampering. However, such tamper-resistance property comes at the cost of a long confirmation delay caused by the consensus process. A Hash-oriented Practical Byzantine Fault Tolerance (PBFT) based consensus algorithm is proposed to improve the Blockchain efficiency and reduce the transaction confirmation delay from 10 minutes to 15 seconds. The Hash-oriented PBFT effectively avoids the double-spending attack and Sybil attack. Security analysis and simulation results demonstrate that the proposed Blockchain secured ridesharing delivery system offers strong security guarantees and satisfies the quality of delivery service in terms of confirmation delay and transaction throughput.

Zhang, Y, Yao, D, Tie, Y, Wang, Y, Zhang, X, Cui, Y, Hao, J, Wu, X, Su, S & Xu, P 1970, 'Identification of Neuromuscular Causal Relationship Between Brain and Muscles in Limb Movement by Using Ensemble Empirical Mode Decomposition based Causal Decomposition', 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, Berlin, Germany, pp. 2667-2670.
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This paper proposes the potential extension of Ensemble Empirical Mode Decomposition based Causal Decomposition (EEMD-CD) to the physiological system. The neural basis of Volitional Motor Control (VMC), resulting in skilled motor behaviors through a connected interaction between limb biomechanical properties and Central Neural System (CNS), has been well documented. Specifically, the Primary Motor Cortex (M1) contributes volitional and goal-directed limb movements in terms of motor planning and motor behavior. The actual applications of causality detection approaches were still dominated by the prediction concept, i.e., Granger Causality (GC). This study concerns clearly some of components of M1 regulating motor properties of upper limbs, and holds the neuroscience finding from which the bi-directional causal interaction in brain and muscles has been concluded. The study performs an experiment by which Electromyography (EMG) of limb muscles and Electroencephalography (EEG) across from prefrontal cortex to M1, were synchronously acquired during wrist extensions. It also provides a valid example of how the casuality can be approached by EEMD-CD and offers a first step in the identification of casual relationship in mutual physiological systems.

Zhang, Y, Zhao, J, Wang, L, Guo, Y, Li, Z & Huang, J 1970, 'Optimization of Two-Dimensional Rotational Single Sheet Tester', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE.
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In order to improve the uniformity of magnetization and excitation efficiency of the two-dimensional rotational single sheet testers (RSST), In this paper, the simulation data of RSST with different shapes of sample are calculated by finite element method (FEM), and the magnetization uniformity of the surface of different shape samples is compared. A stereoscopic structure is designed by selecting Square Rotational Single Sheet Tester (SRSST) as the optimization object. The coupling effect of the orthogonal magnetic circuit and the influence of stray magnetic field between the magnetic poles are reduced by adding the air gap between the magnetic poles and the sample, the same effects can be caused by adding the shields up and down the sample. The sample magnetization uniformity of the SRSST is improved and the excitation power of the SRSST is reduced.

Zhang, Y, Zhao, J, Wang, L, Guo, Y, Li, Z & Huang, J 1970, 'Optimization of Two-Dimensional Rotational Single Sheet Tester', 2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019), 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE, Harbin, PEOPLES R CHINA, pp. 3102-3105.

Zhao, M, Zhang, J, Zhang, C & Zhang, W 1970, 'Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting', 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Long Beach, CA, pp. 12728-12737.
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Zhao, M, Zhang, J, Zhang, C & Zhang, W 1970, 'Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks', COMPUTER VISION - ACCV 2018, PT VI, Asian Conference on Computer Vision, Springer International Publishing, Perth, AUSTRALIA, pp. 247-261.
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High-density object counting in surveillance scenes is challenging mainly due to the drastic variation of object scales. The prevalence of deep learning has largely boosted the object counting accuracy on several benchmark datasets. However, does the global counts really count? Armed with this question we dive into the predicted density map whose summation over the whole regions reports the global counts for more in-depth analysis. We observe that the object density map generated by most existing methods usually lacks of local consistency, i.e., counting errors in local regions exist unexpectedly even though the global count seems to well match with the ground-truth. Towards this problem, in this paper we propose a constrained multi-stage Convolutional Neural Networks (CNNs) to jointly pursue locally consistent density map from two aspects. Different from most existing methods that mainly rely on the multi-column architectures of plain CNNs, we exploit a stacking formulation of plain CNNs. Benefited from the internal multi-stage learning process, the feature map could be repeatedly refined, allowing the density map to approach the ground-truth density distribution. For further refinement of the density map, we also propose a grid loss function. With finer local-region-based supervisions, the underlying model is constrained to generate locally consistent density values to minimize the training errors considering both the global and local counts accuracy. Experiments on two widely-tested object counting benchmarks with overall significant results compared with state-of-the-art methods demonstrate the effectiveness of our approach.

Zhao, S, Qiu, X, Burnett, I, Rigby, M & Lele, A 1970, 'GMAW metal transfer mode identification from welding sound', Australian Acoustical Society Annual Conference, AAS 2018, Australian Acoustical Society, Australian Acoustical Society, Adelaide, Australia,, pp. 482-491.
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Gas Metal Arc Welding (GMAW) is an arc welding process that forms an electric arc between a consumable electrode and the base metal with a shielding gas to protect the arc. In GMAW, there are various metal transfer modes such as the short circuit mode, the globular mode, the spray mode, and the rotational transfer mode, which show different arc stabilities, weld pool penetrations and spatter production. Identifying the metal transfer mode is critical for process monitoring and quality control of GMAW. In this paper, a m ethod for metal transfer mode identification from the welding sound is presented. A recorder mounted on the welder helmet is used to record the sound signals generated by GMAW under different metal transfer modes, which are analysed in both time and frequency domains. New psychoacoustic parameters based on the auditory perception of an expert welder are extracted to distinguish the metal transfer modes. The Gaussian Mixture Model (GMM) is utilised to identify the metal transfer mode from the welding sound signals and a 10-fold cross validation shows 90% recognition accuracy.

Zhao, S, Qiu, X, Burnett, I, Rigby, M & Lele, A 1970, 'Statistical characteristics of gas metal arc welding (GMAW) sound', Proceedings of the International Congress on Acoustics, Internatioanal Congress on Acoustics, EAA, Achen, Germany, pp. 7594-7601.
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Gas Metal Arc Welding (GMAW) is an arc welding process to join two or more metal materials through fusion, where an electric arc is formed between a consumable electrode and the base metal. It has been reported that expert GMAW welders can direct the welding arc type based on the welding sound, and psychoacoustic experiments show that the welding performance is significantly degraded without the acoustic feedback to the welders. In addition, identifying the metal transfer mode based on the welding sound is critical for automatic GMAW process monitoring, quality control and a training pathway for competency. However, the research on the generation and characteristics of the welding sound is still rare. In this paper, the welding sound is measured simultaneously with the welding current at different metal transfer modes to investigate the unique characteristics of welding sound. The welding sound consists of many impulses corresponding to the current leap. The envelope of the impulse responses is estimated based on the sound pressure signal for statistical analysis. It is found that the probability density function of the peak sound pressure, impulse interval and event duration can be well modelled by the Burr distribution. The findings can be used to classify the metal transfer mode from its welding sound.

Zhou, I, Makhdoom, I, Abolhasan, M, Lipman, J & Shariati, N 1970, 'A Blockchain-based File-sharing System for Academic Paper Review', 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE, Australia.
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Zhu, H & Guo, YJ 1970, 'Design of Out-of-phase Filtering Power Dividers Using Flexible Coupling Schemes', 2019 IEEE Asia-Pacific Microwave Conference (APMC), 2019 IEEE Asia-Pacific Microwave Conference (APMC), IEEE, Singapore, Singapore, pp. 1023-1025.
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© 2019 IEEE. This paper presents based on flexible coupling schemes using multiple quarter-wavelength resonators. Microstrip-to-slotline transitions were are used to provide external coupling to the filters. A dual-mode and tri-mode filter are designed. For the dual-mode design, a pair of quarter-wavelength resonators is used with a gap between them providing a suitable coupling coefficient. For the tri-band design, an additional resonator is coupled to the previous quarter-wavelength resonators, leading to a three-pole response within the passband. A microstrip line with a grounded resistor is added at the middle point of two output ports, leading to excellent output matching and isolation between output ports. Two design examples with dual-mode and tri-mode responses are realized with the verification using full-wave simulations.

Zhu, H, Lin, J-Y & Guo, YJ 1970, 'Wideband Filtering Out-of-Phase Power Dividers Using Slotline Resonators and Microstrip-to-Slotline Transitions', 2019 IEEE MTT-S International Microwave Symposium (IMS), 2019 IEEE/MTT-S International Microwave Symposium - IMS 2019, IEEE, Boston, MA, USA, pp. 919-922.
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© 2019 IEEE. Two wideband filtering out-of-phase power dividers are designed and analyzed. The initial design is composed of a quarter-wavelength slotline resonator and two microstrip-to-slotline transitions. Three transmission poles are produced to form the passband. Excellent matching and isolation are achieved using extra matching network. Based on the initial design, a pair of stepped-impedance open stubs are shunted at the output ports to improve the passband selectivity. The designs have been verified through experiment. The tested results show that the proposed devices have achieved 60% operating bandwidth, 1.8 dB insertion loss, 1.2° phase error and excellent in-band matching and isolation.

Zhu, H, Sun, H, Ding, C & Guo, YJ 1970, 'Butler Matrix Based Multi-Beam Base Station Antenna Array', 13th European Conference on Antennas and Propagation, EuCAP 2019, European Conference on Antennas and Propagation, IEEE, Krakow, Poland,.
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In this paper, a three-beam Butler matrix as well as its antenna arrays is presented for cellular base stations. The three-beam Butler matrix is able to generate three beams in the azimuth plane, which can increase the capacity of base stations. Striplines are used for developing the 3 and times; 3 Butler matrix, which is compose of directional couplers and phase shifters. To extend the 3 and times; 3 Butler matrix to a 3 and times; 5 one, unequal power dividers are also require. To verify the beam-forming network, 5-element dual-polarized antenna arrays covering LTE band are developed. Multiple beams are obtained by feeding the antenna array with the augmented 3 and times; 5 Butler matrix. The design is verified by both simulation and experiments.

Zhu, H, Zhu, X, Yang, Y, Sun, Y, Le, VH & Zhang, F 1970, 'Design of Miniaturized On-Chip Bandpass Filters using Inverting-Coupled Structure for Millimter-Wave Applications', 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Sapporo, Japan.
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© 2019 IEEE In this work, a new type of miniaturized on-chip resonator using an inductively-coupled structure is presented. The resonator is constructed by two spiral conductors that are implemented using two different metal layers. Since the two conductors are identical but placed in different rotating pattern, a kind of inductive coupling called inverting coupling will be introduced in addition to the broadside capacitive coupling. To fully understand the working mechanism of the resonator, simplified LC equivalent-circuit models and thorough analysis are provided. To further demonstrate the feasibility of the proposed miniaturized resonator in practice, two bandpass filters, namely a 1st-order and 2nd-order, are designed and fabricated in a standard 0.13-µm (Bi)-CMOS technology. Good agreements between simulation and measurement have obtained, which verify that the presented design approach is suitable for miniaturized on-chip passive design.

Zhu, L, Han, X, Tang, R & Zhu, J 1970, 'Loss Analysis of the Permanent Magnet Motor with an Amorphous Stator Core by Considering the Influences of Manufacturing Processes', 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), IEEE.
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© 2019 IEEE. This paper presents the results of experimental trials carried out on a permanent magnet motor with an amorphous stator core. The magnetization performances and iron loss characteristics of the manufactured amorphous core were measured. Losses of two permanent magnet motors with amorphous core and silicon steel core were calculated and compared by considering the influences of mechanic stresses induced in the amorphous core manufacturing processes. Total losses and efficiencies of the permanent magnet motors were tested and compared. It is demonstrated that the efficiency superiority of the permanent magnet motor with an amorphous core gets weaken as the load ratio increases.

Zhu, Q, Phung, MD & Ha, QP 1970, 'Crack detection using enhanced hierarchical convolutional neural networks', Australasian Conference on Robotics and Automation, ACRA, Australasian Conference on Robotics and Automation, ARAA, Adelaide, Australia, pp. 1-8.
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Unmanned aerial vehicles (UAV) are expected to replace human in hazardous tasks of surface inspection due to their flexibility in operating space and capability of collecting high quality visual data. In this study, we propose enhanced hierarchical convolutional neural networks (HCNN) to detect cracks from image data collected by UAVs. Unlike traditional HCNN, here a set of branch networks is utilised to reduce the obscuration in the down-sampling process. Moreover, the feature preserving blocks combine the current and previous terms from the convolutional blocks to provide input to the loss functions. As a result, the weights of resized images can be reduced to minimise the information loss. Experiments on images of different crack datasets have been carried out to demonstrate the effectiveness of proposed HCNN.

Zhu, Q, Qiu, X, Coleman, P & Burnett, I 1970, 'Reducing number of transfer function measurement in local sound field reproduction using acoustic modeling', Proceedings of the International Congress on Acoustics, International Congress on Acoustics, EAA, Aachen, Germany, pp. 2684-2689.
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Broadband local sound field reproduction over an extended spatial region is a challenging problem when only limited transfer function measurements are available. An approach based on acoustics modeling is proposed in this paper to reduce the required number of transfer function measurements in local sound field reproduction. The proposed method only requires measuring the transfer functions from each source to a few samples over the boundary of the controlled region, and the transfer functions to the samples inside the controlled region are then estimated through efficient acoustic modelling. Simulations demonstrate that the proposed method requires fewer transfer function measurements than existing methods such as the least squares and the spatial harmonic decomposition methods.

Abidi, IH, Mendelson, N, Tran, TT, Tyagi, A, Zhuang, M, Weng, L-T, Ozyilmaz, B, Aharonovich, I, Toth, M & Luo, Z 2019, 'Selective Defect Formation in Hexagonal Boron Nitride'.

Afshar, S, Hamilton, TJ, Davis, L, Schaik, AV & Delic, D 2019, 'Event-based Processing of Single Photon Avalanche Diode Sensors'.

Huang, H, Zhang, J, Zhang, J, Wu, Q & Xu, J 2019, 'Compare More Nuanced:Pairwise Alignment Bilinear Network For Few-shot Fine-grained Learning'.

Liu, L, Jiang, J, Jia, W, Amirgholipour, S, Zeibots, M & He, X 2019, 'DENet: A Universal Network for Counting Crowd with Varying Densities and Scales', arXiv.

Mendelson, N, Doherty, M, Toth, M, Aharonovich, I & Tran, TT 2019, 'Strain Engineering of Quantum Emitters in Hexagonal Boron Nitride'.

Rahman, ML, Zhang, JA, Huang, X, Guo, YJ & Jr, RWH 2019, 'Framework for a Perceptive Mobile Network using Joint Communication and Radar Sensing'.

Tran, TT, Bradac, C, Solntsev, AS, Toth, M & Aharonovich, I 2019, 'Suppression of Spectral Diffusion by Anti-Stokes Excitation of Quantum Emitters in Hexagonal Boron Nitride'.

Unanue, IJ, Borzeshi, EZ & Piccardi, M 2019, 'Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation'.
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In recent years, neural machine translation (NMT) has become the dominant approach in automated translation. However, like many other deep learning approaches, NMT suffers from overfitting when the amount of training data is limited. This is a serious issue for low-resource language pairs and many specialized translation domains that are inherently limited in the amount of available supervised data. For this reason, in this paper we propose regressing word (ReWE) and sentence (ReSE) embeddings at training time as a way to regularize NMT models and improve their generalization. During training, our models are trained to jointly predict categorical (words in the vocabulary) and continuous (word and sentence embeddings) outputs. An extensive set of experiments over four language pairs of variable training set size has showed that ReWE and ReSE can outperform strong state-of-the-art baseline models, with an improvement that is larger for smaller training sets (e.g., up to +5:15 BLEU points in Basque-English translation). Visualizations of the decoder's output space show that the proposed regularizers improve the clustering of unique words, facilitating correct predictions. In a final experiment on unsupervised NMT, we show that ReWE and ReSE are also able to improve the quality of machine translation when no parallel data are available.

Yang, D, Zou, Y, Zhang, J & Li, G 2019, 'C-RPNs: Promoting Object Detection in real world via a Cascade Structure of Region Proposal Networks'.

Zdankowski, P, Trusiak, M, McGloin, D & Swedlow, JR 2019, 'Numerically enhanced adaptive optics-based 3D STED microscopy for deep-tissue super-resolved imaging', Cold Spring Harbor Laboratory.
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AbstractIn stimulated emission depletion (STED) nanoscopy, the major origin of decreased signal-to-noise ratio within images can be attributed to sample photobleaching and strong optical aberrations. This is due to STED utilising both a high power depletion laser (increasing risk of photodamage), while the depletion beam is very sensitive to sample-induced aberrations. Here we demonstrate a custom-built 3D STED microscope with automated aberration correction that is capable of 3D super-resolution imaging through thick, highly aberrating, tissue. We introduce and investigate image denoising by block-matching and collaborative filtering (BM3D) to numerically enhance fine object details otherwise mixed with noise. Numerical denoising provides an increase in the final effective resolution of the STED imaging of 31% using the well-established Fourier ring correlation metric. Experimental validation of the proposed method is achieved through super-resolved 3D imaging of axons in differentiated induced pluripotent stem cells growing under a 80µm thick layer of tissue with lateral and axial resolution of 256nm and 300nm, respectively.

Zhang, G, Niwa, K & Kleijn, WB 2019, 'Rapidly Adapting Moment Estimation'.
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Adaptive gradient methods such as Adam have been shown to be very effective for training deep neural networks (DNNs) by tracking the second moment of gradients to compute the individual learning rates. Differently from existing methods, we make use of the most recent first moment of gradients to compute the individual learning rates per iteration. The motivation behind it is that the dynamic variation of the first moment of gradients may provide useful information to obtain the learning rates. We refer to the new method as the rapidly adapting moment estimation (RAME). The theoretical convergence of deterministic RAME is studied by using an analysis similar to the one used in [1] for Adam. Experimental results for training a number of DNNs show promising performance of RAME w.r.t. the convergence speed and generalization performance compared to the stochastic heavy-ball (SHB) method, Adam, and RMSprop.