Publications

Acampora, G, Pedrycz, W, Vasilakos, AV & Vitiello, A 2020, Preface.

Alsawwaf, M & Chaczko, Z 2020, 'Multimodal Access Control: A Review of Emerging Mechanisms' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology, Springer, Switzerland, pp. 183-200.
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Accurately identifying and authenticating a human without requiring proximity, yet with high reliability, is crucial for application areas such as surveillance, dynamic authentication, and proof of identity. While a significant research has been conducted in the direction of human authentication, achieving the authentication in an ambient manner, with high reliability, and security is still far from being perfect under the currently deployed methods. This is due to the requirement of a specific posture and approximation to the device in many approved and deployed methods such as fingerprint, facial recognition, and retinal scan. An ambient authentication system is highly dependent on biometric features that can accurately discriminate between one human and another. These biometric features should be insensitive to variation in posture, proximity, and aging. Extraction of a unique feature set that allows a human to be identified smoothly, even without proximity, under varying conditions is one of the main steps needed for an advancement in this field. In this paper, a review of current and emerging mechanism are provided. A proposed method will use a feature set that allows the system to achieve dynamic detection compared to the currently used technologies such as fingerprint, facial recognition and retinal scan. The proposed feature set is made up of a combination of facial minutiae and thermal contours which are extracted from the human face on-the-fly even without the subject coordination.

Alsawwaf, M, Chaczko, Z & Kulbacki, M 2020, 'In Your Face: Person Identification Through Ratios of Distances Between Facial Features', pp. 527-536.
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© 2020, Springer Nature Switzerland AG. These days identification of a person is an integral part of many computer-based solutions. It is a key characteristic for access control, customized services, and a proof of identity. Over the last couple of decades, many new techniques were introduced for how to identify human faces. The purpose of this paper is to introduce yet another innovative approach for face recognition. The human face consists of multiple features that when considered together produces a unique signature that identifies a single person. Building upon this premise, we are studying the identification of faces by producing ratios from the distances between the different features on the face and their locations in an explainable algorithm with the possibility of future inclusion of multiple spectrum and 3D images for data processing and analysis.

Chaczko, Z & Kale, A 2020, 'Learning Classifiers for Multimodal Image Detection' in Klempous, R & Nikodem, J (eds), Asia-Pacific Conference on Computer Assisted and System Engineering, Springer Nature, Cham, Switzerland, pp. 266-280.
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Learning Classifiers are essential analysis tools in today's era due to the rapid expansion in data-intensive applications. Every type of the classifier has own distinct architectural properties which allow to apply them in various application-specific requirements. Here, experimental work is performed to analyse the performance and accuracy of most commonly used learning classifiers applied within the scope of multimodal image classification problem space. The purpose of this study is to investigate the usefulness of the learning-classifiers with the multimodal datasets which are in many cases have the curse of dimensionality and may contain a very high volume of noise. Validation is conducted over multimodal datasets with the proposed classification algorithms operating in a parallel manner. Finally, results are discussed to explore possible ways to apply every learning classifier in multi-modal image classification applications.

Chaczko, Z, Al-Doghman, F & Rakhi Ajayan, A 2020, 'Policy-Based Consensus Data Aggregation for the Internet of Things' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology, Springer Nsture, Cham, Switzerland, pp. 119-130.
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The new trend of the Internet of Things brings a whole breed of opportunities and applications. Within it, a massive amount of data coming from heterogeneous sources travel in a bidirectional way. Data aggregation is one of the most efficient ways to mitigate Big Data. However, using one type of aggregation within a network at all times is not an optimal option. Various network situations require different aggregation functions at different times. We introduce a policy-based data aggregation framework that can handle this issue by referring to a policy when executing the aggregation strategy. An agreement process is used to reach consensus about the aggregation function that is to be applied on the network (or part of it) at a specific time. Participants are to negotiate the policy terms based on the current network status and the nature of the coming requests. The framework represents a promising scope for fully automated IoT.

Chaczko, Z, Chiu, C & Yu, Z 2020, 'Assessment of a Multi-Agent RFID Platform for Industrial Logistic Operations' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology: Intelligent Engineering and Informatics, Springer Nature, Cham, Switzerland, pp. 166-182.
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The paper examines the experimental implementation of multi-agent, omni-dimensional RFID technology for logistical and industrial operations. The aim of the research is to demonstrate the processes taken to test RFID under real-world industrial scenarios using a multi-agent analytical approach. The results obtained demonstrate the level of accuracy for an omni-directional versus agent-based optimized analytical approach, that is essential in conveying the performance in industrial logistic setups. Further work into the positioning and localization of multidimensional RFID inventory scanning for commercial setups is considered for future investigation.

Chaczko, Z, Rakhi Ajayan, A & Al-Doghman, F 2020, 'Tensor Decompositions in Multimodal Big Data: Studying Multiway Behavioral Patterns' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology, Springer Nature, Cham, Switzerland, pp. 1-296.
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Preset day cyber-physical systems (CPS) are the confluence of very large data sets, tight time constraints, and heterogeneous hardware units, ridden with latency and volume constraints, demanding newer analytic perspectives. Their system logistics can be well-defined by the data-streams’ behavioural trends across various modalities, without numerical restrictions, favouring resource-saving over methods of investigating individual component features and operations. The aim of this paper is to demonstrate how behaviour patterns and related anomalies comprehensively define a CPS. Tensor decompositions are hypothesized as the solution in the context of multimodal smart-grid-originated Big Data analysis. Tensorial data representation is demonstrated to capture the complex knowledge encompassed in these data flows. The uniqueness of this approach is highlighted in the modified multiway anomaly patterns models. In addition, higher-order data preparation schemes, design and implementation of tensorial frameworks and experimental-analysis are final outcomes.

Chaczko, Z, Yu, Z & Shi, J 2020, 'Low-Cost Wireless Micro-Electro-Mechanical-SystemsAccelerometers Linear Sensor Model' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology, Springer Nature, Cham, Switzerland, pp. 156-165.
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This chapter introduces a new linear sensor model of low-cost micro-electro-mechanical-systems accelerometers. A modelled algorithm has been developed to reduce different errors for the system. Experiments with Matlab analysis has been displayed in the paper. Transmission of an accelerometer in both cable and wireless has been calculated and displayed from 1500 samples. Linear sensor model has been applied to the experiment results to optimize the accuracy of the accelerometer data. This method is able to be used in different positions of the accelerometer. It is also used to calibrate and align the system before the system operation. Therefore, it is possible that the sensor model can be used to reduce errors in different sensor networks, such as Bluetooth, beacon and ZigBee.

Chaczko, Z, Zhang, W, Christopher, C, Jan, S & Su, S 2020, 'Internet of Things Is Changing Teaching of Technical Subjects at UTS' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology, Springer Nature AG Switzerland, Gewerbestrasse 11, 6330 Cham, Switzerland, pp. 131-296.
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The Internet of Things, involving the connection of intelligent devices (other than standard, already connected products such as computers and smartphones) to the Internet, is in the process of transforming numerous areas of lives. For many years, both academia and industry prepared the background theories and implementations for what is today's IoT, keeping changing and evolving. Students of universities, preparing to be the driving forces of innovation and progress have a very strong interest in IoT and related subjects. Teaching at universities, especially technical ones is strongly affected by the need to give students the required background and show the direction for self-study. In this paper we will provide a literature review to analyze how IoT inspired changes in teaching some technical subjects at the University of Technology Sydney (UTS) by describing, the recently undertaken projects in this area, providing some case studies and drawing conclusions.

More, FJ, Chaczko, Z & Kulbacka, J 2020, 'Early Detection of Coronary Artery Diseases Using Endocrine Markers', pp. 593-601.
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© 2020, Springer Nature Switzerland AG. Cardiovascular diseases including coronary artery disease is the leading cause of death in the well developed and developing countries of the 21st century and has a higher rate of mortality and morbidity. Dysfunction of the pituitary, thyroid, and parathyroid glands caused cardio/cardiovascular diseases including changes in blood pressure, contractility of myocardium - systolic and diastolic myocardial functions, endothelial and dyslipidemia. Dysfunction of thyroid, parathyroid and adrenocorticotropic hormones caused imbalance of endocrine system such as hyper and hypo function, effects on pathophysiology of the cardiovascular system.

Saputra, Y, Dinh, H, Nguyen, D, Dutkiewicz, E & Niyato, D 2020, 'Wireless Edge Caching for Mobile Social Networks' in Vu, T, Chatzinotas, S, Baştuğ, E & Quek, TQS (eds), Wireless Edge CachingModeling, Analysis, and Optimization, Cambridge University Press.

Zhang, W, Chiu, C, Szymanski, J, Chaczko, Z, Su, S & Zhou, J 2020, 'Internet of Things is Changing Teaching of Technical Subjects at UTS' in Klempous, R & Nikodem, J (eds), Smart Innovations in Engineering and Technology: Intelligent Engineering and Informatics, Springer Nature, Cham, Switzerland, pp. 131-143.
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Abbasipour, M, Milimonfared, J, Yazdi, SSH & Rouzbehi, K 2020, 'Power injection model of IDC-PFC for NR-based and technical constrained MT-HVDC grids power flow studies', ELECTRIC POWER SYSTEMS RESEARCH, vol. 182.
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Abeywickrama, HV, He, Y, Dutkiewicz, E, Jayawickrama, BA & Mueck, M 2020, 'A Reinforcement Learning Approach for Fair User Coverage Using UAV Mounted Base Stations Under Energy Constraints', IEEE Open Journal of Vehicular Technology, vol. 1, pp. 67-81.
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Abuhilaleh, M, Li, L & Hossain, MJ 2020, 'Power management and control coordination strategy for autonomous hybrid microgrids', IET Generation, Transmission and Distribution, vol. 14, no. 1, pp. 119-130.
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© The Institution of Engineering and Technology 2019. This study presents an improved power management and control coordination strategy for autonomous hybrid microgrids (MGs). The new strategy aims to reduce the continuous operation of interlinking converters (ILCs) under all load conditions, and thereby avoids the significant power loss on the ILCs that adversely affects the operational feasibility of the hybrid MGs. The hybrid MG considered in this study consists of multiple alternating current and direct current sub-microgrids (SMGs) with different voltage levels. The hierarchal coordination of power management and control strategy for autonomous hybrid MG is introduced and analysed. The designed system includes both the primary and secondary control levels to ensure a seamless and accurate transfer of power among the SMGs. A new technique to ensure the continuous power flow among the SMGs while minimising the continuous operation of the ILCs in the islanded mode is presented with a focus on the secondary control level. Five scenarios of transferring power among SMGs are analysed using MATLAB/Simulink. The results indicate that the system's high level of flexibility in managing the power flow at different control levels can be achieved by the proposed approach.

Afroz, F & Braun, R 2020, 'Energy-efficient MAC protocols for wireless sensor networks: a survey', International Journal of Sensor Networks, vol. 33, no. 3, pp. 150-173.
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Alam, MM, Lu, DC & Siwakoti, Y 2020, 'Small signal analysis of dual input buck converter', International Journal of Smart Grid and Clean Energy, vol. 9, no. 1, pp. 8-16.
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© 2020 by the authors. This paper presents a small signal modelling and voltage-mode control of a pulse-width modulated (PWM) dual-input DC-DC buck converter. The control of multiple switches in a power converter is the main challenge for multipleinput converters addressed in this paper. Using the concept of linearization and perturbation depicted in circuit averaging technique, the closed-loop small signal model for multi-input DC-DC buck converter is derived. The closed loop control to output voltage transfer function is derived. A brief compensator design is introduced for a multi-input buck converter. In order to control the duty cycles of multiple switches and control the output voltage, a new variable is introduced to relate the duty cycles in the closed loop control to output voltage transfer function. The analysis and controller design are simulated in LTSpice.

Alghamdi, K & Braun, R 2020, 'Software Defined Network (SDN) and OpenFlow Protocol in 5G Network', Communications and Network, vol. 12, no. 01, pp. 28-40.
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Alsheikh, MA, Hoang, DT, Niyato, D, Leong, D, Wang, P & Han, Z 2020, 'Optimal Pricing of Internet of Things: A Machine Learning Approach', IEEE Journal on Selected Areas in Communications, vol. 38, no. 4, pp. 669-684.
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© 1983-2012 IEEE. Internet of things (IoT) produces massive data from devices embedded with sensors. The IoT data allows creating profitable services using machine learning. However, previous research does not address the problem of optimal pricing and bundling of machine learning-based IoT services. In this paper, we define the data value and service quality from a machine learning perspective. We present an IoT market model which consists of data vendors selling data to service providers, and service providers offering IoT services to customers. Then, we introduce optimal pricing schemes for the standalone and bundled selling of IoT services. In standalone service sales, the service provider optimizes the size of bought data and service subscription fee to maximize its profit. For service bundles, the subscription fee and data sizes of the grouped IoT services are optimized to maximize the total profit of cooperative service providers. We show that bundling IoT services maximizes the profit of service providers compared to the standalone selling. For profit sharing of bundled services, we apply the concepts of core and Shapley solutions from cooperative game theory as efficient and fair allocations of payoffs among the cooperative service providers in the bundling coalition.

Amjadipour, M, Su, D & Iacopi, F 2020, 'Graphitic-Based Solid-State Supercapacitors: Enabling Redox Reaction by In Situ Electrochemical Treatment', BATTERIES & SUPERCAPS.
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Amjadipour, M, Su, D & Iacopi, F 2020, 'Graphitic‐Based Solid‐State Supercapacitors: Enabling Redox Reaction by In Situ Electrochemical Treatment', Batteries && Supercaps.
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Azizi, N, CheshmehBeigi, HM & Rouzbehi, K 2020, 'Optimal placement of direct current power system stabiliser (DC-PSS) in multi-terminal HVDC grids', IET Generation, Transmission and Distribution, vol. 14, no. 12, pp. 2315-2322.
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© The Institution of Engineering and Technology 2020. This study focuses on the selection of the most effective location of direct current power system stabiliser (DC-PSS) in multi-terminal high-voltage direct current (MT-HVDC) grids that is applied to voltage source converter (VSC) to voltage stability enhancement and oscillation damping. Due to the adverse interaction between having multiple number of DC-PSS, it is necessary to select the best location for installing DC-PSS in MT-HVDC grid. In this study, the participation factor (PF) method is used. This method assists to find which power converters are more sensitive and have a major impact on the instability of the entire system. In this approach, the whole of the system is modelled as a multi-input multi-output (MIMO) dynamic system. PFs related to each power converter are intended by the oscillatory mode sensitivity analysis against the components of the MIMO matrix of the system. The PF analysis determines which VSC station is more participating in the small-signal instability of the system. In order to endorse the efficiency of the proposed method, time-domain MATLAB simulations are conducted in Cigré MT-HVDC grid benchmark.

Azizivahed, A, Arefi, A, Ghavidel Jirsaraie, S, Shafie-khah, M, Li, L, Zhang, J & Catalao, JPS 2020, 'Energy Management Strategy in Dynamic Distribution Network Reconfiguration considering Renewable Energy Resources and Storage', IEEE Transactions on Sustainable Energy, pp. 1-1.
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Azizivahed, A, Razavi, SE, Arefi, A, Jabbari Ghadi, M, Li, L, Zhang, J, Shafie-khah, M & Catalao, JPS 2020, 'Risk-Oriented Multi-Area Economic Dispatch Solution with High Penetration of Wind Power Generation and Compressed Air Energy Storage System', IEEE Transactions on Sustainable Energy, pp. 1-1.
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Baba, AA, Hashmi, RM, Esselle, KP, Attygalle, M & Borg, D 2020, 'A Millimeter-Wave Antenna System for Wideband 2-D Beam Steering', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 5, pp. 3453-3464.
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Barzegarkhoo, R, Siwakoti, YP & Blaabjerg, F 2020, 'A New Switched-Capacitor Five-Level Inverter Suitable for Transformerless Grid-Connected Applications', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 8, pp. 8140-8153.
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Barzegarkhoo, R, Siwakoti, YP, Vosoughi, N & Blaabjerg, F 2020, 'Six-Switch Step-up Common-Grounded Five-Level Inverter with Switched-Capacitor Cell for Transformerless Grid-Tied PV Applications', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Ben, X, Gong, C, Zhang, P, Yan, R, Wu, Q & Meng, W 2020, 'Coupled Bilinear Discriminant Projection for Cross-View Gait Recognition', IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 3, pp. 734-747.
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© 1991-2012 IEEE. A problem that hinders good performance of general gait recognition systems is that the appearance features of gaits are more affected-prone by views than identities, especially when the walking direction of the probe gait is different from the register gait. This problem cannot be solved by traditional projection learning methods because these methods can learn only one projection matrix, and thus for the same subject, it cannot transfer cross-view gait features into similar ones. This paper presents an innovative method to overcome this problem by aligning gait energy images (GEIs) across views with the coupled bilinear discriminant projection (CBDP). Specifically, the CBDP generates the aligned gait matrix features for two views with two sets of bilinear transformation matrices, so that the original GEIs' spatial structure information can be preserved. By iteratively maximizing the ratio of inter-class distance metric to intra-class distance metric, the CBDP can learn the optimal matrix subspace where the GEIs across views are aligned in both horizontal and vertical coordinates. Therefore, the CBDP is also able to avoid the under-sample problem. We also theoretically prove that the upper and lower bounds of the objective function sequence of the CBDP are both monotonically increasing, so the convergence of the CBDP is demonstrated. In the terms of accuracy, the comparative experiments on the CASIA (B) and OU-ISIR gait databases show that our method is superior to the state-of-the-art cross-view gait recognition methods. More impressively, encouraging performance is obtained by our method even in matching a lateral-view gait with a frontal-view gait.

Buchlak, QD, Esmaili, N, Leveque, JC, Farrokhi, F, Bennett, C, Piccardi, M & Sethi, RK 2020, 'Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review', Neurosurgical Review.
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© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Machine learning (ML) involves algorithms learning patterns in large, complex datasets to predict and classify. Algorithms include neural networks (NN), logistic regression (LR), and support vector machines (SVM). ML may generate substantial improvements in neurosurgery. This systematic review assessed the current state of neurosurgical ML applications and the performance of algorithms applied. Our systematic search strategy yielded 6866 results, 70 of which met inclusion criteria. Performance statistics analyzed included area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity. Natural language processing (NLP) was used to model topics across the corpus and to identify keywords within surgical subspecialties. ML applications were heterogeneous. The densest cluster of studies focused on preoperative evaluation, planning, and outcome prediction in spine surgery. The main algorithms applied were NN, LR, and SVM. Input and output features varied widely and were listed to facilitate future research. The accuracy (F(2,19) = 6.56, p < 0.01) and specificity (F(2,16) = 5.57, p < 0.01) of NN, LR, and SVM differed significantly. NN algorithms demonstrated significantly higher accuracy than LR. SVM demonstrated significantly higher specificity than LR. We found no significant difference between NN, LR, and SVM AUC and sensitivity. NLP topic modeling reached maximum coherence at seven topics, which were defined by modeling approach, surgery type, and pathology themes. Keywords captured research foci within surgical domains. ML technology accurately predicts outcomes and facilitates clinical decision-making in neurosurgery. NNs frequently outperformed other algorithms on supervised learning tasks. This study identified gaps in the literature and opportunities for future neurosurgical ML research.

Ca, Y, Tang, W, Li, L, Zhang, B, Zhan, L & Wang, Y 2020, 'Multi-mode adaptive local reactive power control method based on pv inverters in low voltage distribution networks', IET Generation, Transmission and Distribution, vol. 14, no. 4, pp. 542-551.
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© The Institution of Engineering and Technology 2019. Low voltage distribution networks with the high penetration of photovoltaic (PV) units are facing four types of challenges, including over-voltage issues, under-voltage issues, voltage fluctuation issues and high power losses. In order to mitigate the above issues, this study proposes a multi-mode adaptive local reactive power control method based on Q(P) characteristics. A new concept, node virtual injection active power (NVIP), is developed to take the PV active power, load active power and load reactive power as a whole and as the basis to regulate the PV reactive power. Then, an NVIP-based multi-mode local Q(P) framework is proposed to consider the four types of challenges based on four operation modes, respectively, that can be adaptively switched according to the NVIP value and the NVIP variation. In addition, a systematic parameter design for the Q(P) framework is proposed based on an optimisation model to further enhance the effectiveness of the proposed multi-mode control. The simulation results demonstrate the effectiveness of the proposed method in mitigating voltage violations and voltage fluctuations, and improving the power losses and power factor.

Cai, Z, Yang, Y, Tang, X, Li, Z, Zhang, T & Zhu, H 2020, 'Ultra-low phase noise oscillator employing mixed electric and magnetic coupling resonator', MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, vol. 62, no. 5, pp. 1914-1919.
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Canning, J & Ziyani, A 2020, 'Chirping fiber Bragg gratings within additively manufactured polymer packages', OPTICS LETTERS, vol. 45, no. 8, pp. 2235-2238.
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Cao, Y & Veitch, D 2020, 'Toward Trusted Time: Remote Server Vetting and the Misfiring Heart of Internet Timing', IEEE-ACM TRANSACTIONS ON NETWORKING, vol. 28, no. 2, pp. 944-956.
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Chacon, A, James, B, Tran, L, Guatelli, S, Chartier, L, Prokopvich, D, Franklin, DR, Mohammadi, A, Nishikido, F, Iwao, Y, Akamatsu, G, Takyu, S, Tashima, H, Yamaya, T, Parodi, K, Rosenfeld, A & Safavi-Naeini, M 2020, 'Experimental investigation of the characteristics of radioactive beams for heavy ion therapy.', Medical physics.
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PURPOSE:This work has two related objectives. The first is to estimate the relative biological effectiveness of two radioactive heavy ion beams based on experimental measurements, and compare these to the relative biological effectiveness of corresponding stable isotopes to determine whether they are therapeutically equivalent. The second aim is to quantitatively compare the quality of images acquired postirradiation using an in-beam whole-body positron emission tomography scanner for range verification quality assurance. METHODS:The energy deposited by monoenergetic beams of 11 C at 350 MeV/u, 15 O at 250 MeV/u, 12 C at 350 MeV/u, and 16 O at 430 MeV/u was measured using a cruciform transmission ionization chamber in a water phantom at the Heavy Ion Medical Accelerator in Chiba (HIMAC), Japan. Dose-mean lineal energy was measured at various depths along the path of each beam in a water phantom using a silicon-on-insulator mushroom microdosimeter. Using the modified microdosimetric kinetic model, the relative biological effectiveness at 10% survival fraction of the radioactive ion beams was evaluated and compared to that of the corresponding stable ions along the path of the beam. Finally, the postirradiation distributions of positron annihilations resulting from the decay of positron-emitting nuclei were measured for each beam in a gelatin phantom using the in-beam whole-body positron emission tomography scanner at HIMAC. The depth of maximum positron-annihilation density was compared with the depth of maximum dose deposition and the signal-to-background ratios were calculated and compared for images acquired over 5 and 20 min postirradiation of the phantom. RESULTS:In the entrance region, the hboxRBE10 was 1.2 ± 0.1 for both 11 C and 12 C beams, while for 15 O and 16 O it was 1.4 ± 0.1 and 1.3 ± 0.1, respectively. At the Bragg peak, the RBE10 was 2.7 ± 0.4 for 11 C and 2.9 ± 0.4 for 12 C, while for 15 O and 16 O it was 2.7 ± 0.4 and 2.8 ± 0.4, respectively. In ...

Chaczko, Z, Klempous, R, Rozenblit, J, Adegbija, T, Chiu, C, Kluwak, K & Smutnick, C 2020, 'Biomimetic Middleware Design Principles for IoT Infrastructures', Acta Polytechnica Hungarica, vol. 17, no. 5, pp. 135-150.
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Chaczko, Z, Kulbacki, M, Gudzbeler, G, Alsawwaf, M, Thai-Chyzhykau, I & Wajs-Chaczko, P 2020, 'Exploration of Explainable AI in Context of Human-Machine Interface for the Assistive Driving System', Lecture Notes in Artificial Intelligence, vol. Part II, no. 10752.

Challa, S, Das, AK, Gope, P, Kumar, N, Wu, F & Vasilakos, AV 2020, 'Design and analysis of authenticated key agreement scheme in cloud-assisted cyber–physical systems', Future Generation Computer Systems, vol. 108, pp. 1267-1286.
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© 2018 Elsevier B.V. With advancements in engineering and science, the application dimensions of Cyber–Physical System (CPS) are increasing due to their improving efficiency, safety, reliability, usability and autonomy. By providing on-demand access to shared processing resources, cloud computing reduces infrastructure costs. Ensuring quality of service and information privacy and security is important in such environments. In this paper, we design a new authentication scheme related to the cloud-assisted CPS in two directions: (1) authentication between a user and a cloud server, and (2) authentication between a smart meter and a cloud server. In the former situation, any external party (user) can access the information stored in a cloud server provided that the user is legal and has the right to access information. In the later situation, a smart meter and a cloud server authentication is needed for secure communication of data stored in the cloud server. In both cases, both entities first mutually authenticate each other and only after successful authentication with the help of a trusted authority, establish a session key for their future secure communication. The proposed scheme deals with both the cases and provides high security as compared to other related works, which is shown through formal and informal security analysis. In addition, the mutual authentication using the widely-accepted Burrows–Abadi–Needham logic (BAN logic) and also formal security verification using the broadly-used Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool demonstrate further that the scheme is strong in security. Finally, the proposed scheme is shown to be efficient in terms of communication and computation costs as compared to those for other related existing schemes.

Chen, H, Xu, J-X, Kong, Z-H, Chen, W-H & Zhang, XY 2020, 'Broadband High-Efficiency Power Amplifier With Quasi-Elliptic Low-Pass Response', IEEE ACCESS, vol. 8, pp. 52566-52574.
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Chen, J, Zhou, J, Cao, Z, Vasilakos, AV, Dong, X & Choo, KKR 2020, 'Lightweight Privacy-Preserving Training and Evaluation for Discretized Neural Networks', IEEE Internet of Things Journal, vol. 7, no. 4, pp. 2663-2678.
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© 2014 IEEE. Machine learning, particularly the neural network (NN), is extensively exploited in dizzying applications. In order to reduce the burden of computing for resource-constrained clients, a large number of historical private datasets are required to be outsourced to the semi-trusted or malicious cloud for model training and evaluation. To achieve privacy preservation, most of the existing work either exploited the technique of public key fully homomorphic encryption (FHE) resulting in considerable computational cost and ciphertext expansion, or secure multiparty computation (SMC) requiring multiple rounds of interactions between user and cloud. To address these issues, in this article, a lightweight privacy-preserving model training and evaluation scheme LPTE for discretized NNs (DiNNs) is proposed. First, we put forward an efficient single key fully homomorphic data encapsulation mechanism (SFH-DEM) without exploiting public key FHE. Based on SFH-DEM, a series of atomic calculations over the encrypted domain, including multivariate polynomial, nonlinear activation function, gradient function, and maximum operations are devised as building blocks. Furthermore, a lightweight privacy-preserving model training and evaluation scheme LPTE for DiNNs is proposed, which can also be extended to convolutional NN. Finally, we give the formal security proofs for dataset privacy, model training privacy, and model evaluation privacy under the semi-honest environment and implement the experiment on real dataset MNIST for recognizing handwritten numbers in DiNN to demonstrate the high efficiency and accuracy of our proposed LPTE.

Chen, RS, Zhu, L, Lin, JY, Wong, SW, Li, Y, Yang, Y & He, Y 2020, 'Miniaturized Full-Metal Dual-Band Filter Using Dual-Mode Circular Spiral Resonators', IEEE Microwave and Wireless Components Letters, vol. 30, no. 6, pp. 573-576.
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© 2001-2012 IEEE. A miniaturized full-metal dual-band bandpass filter using a dual-mode circular spiral resonator (CSR) in a single metal cavity is proposed. Two spirals are combined together to form a dual-mode resonator, and the transmission zero (TZ) produced by the source-load coupling can separate the two modes and achieve the desired dual-band property. Then, a second-order dual-band filter is designed based on the dual-mode resonator, and each band can be individually synthesized, designed, and tuned to achieve the desired filtering performances. In addition, each band has TZs on both sides of the passband to achieve high selectivity. The size of the second-order dual-band filter is only 0.073\lambda _{0} \times 0.055\lambda _{0} \times 0.015\lambda _{0} calculated at the center frequency of the lower band. Finally, the filter is fabricated and measured, and a good agreement is achieved between the measurement and simulation.

Chen, S-L, Karmokar, DK, Qin, P-Y, Ziolkowski, RW & Guo, YJ 2020, 'Polarization-Reconfigurable Leaky-Wave Antenna With Continuous Beam Scanning Through Broadside', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 1, pp. 121-133.
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Chen, X, Cui, J, Ni, W, Wang, X, Zhu, Y, Zhang, J & Xu, S 2020, 'DFT-s-OFDM: Enabling Flexibility in Frequency Selectivity and Multiuser Diversity for 5G', IEEE Consumer Electronics Magazine.
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IEEE The upcoming fifth-generation (5G) wireless cellular communication systems are expected to provide efficiency and productivity by ushering in flexibility of waveforms and resource allocation. Clustered discrete Fourier transform-spread-orthogonal frequency division multiplexing (DFT-s-OFDM) has been specified as the waveform for 5G, due to its flexibility in the exploitation of frequency selectivity and multiuser diversity. This article discusses the flexibility that clustered DFT-s-OFDM is able to achieve at the physical layer, and the requirements that it needs to comply with at the media access control layer. This article emphasizes on the resource allocation of clustered DFT-s-OFDM that can leverage between the flexibility and compliance requirements, and reveals that clustered DFT-s-OFDM is suited for cells with UEs closely distributed around the base stations. A new enhanced riding peak method which operates on the basis of multiple resolutions is identified to be able to balance the data rate of clustered DFT-s-OFDM and computational complexity.

Chen, X, Tang, M-C, Yi, D & Ziolkowski, RW 2020, 'Wideband, Electrically Small, Near-Field Resonant Parasitic Dipole Antenna With Stable Radiation Performance', IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, vol. 19, no. 5, pp. 826-830.
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Cheng, Q, Nguyen, D, Dutkiewicz, E & Mueck, M 2020, 'Preserving Honest/Dishonest Users' Operational Privacy with Blind Interference Calculation in Spectrum Sharing System', IEEE Transactions on Mobile Computing.
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In this paper, we investigate the operational privacy issue of Incumbent Users (IUs) and honest/dishonest Secondary Users (SUs). For the case of IUs and honest SUs, we propose a privacy-preserving scheme for DSA by leveraging encryption and obfuscation methods (PSEO). To implement PSEO, we introduce an interference calculation scheme that allows users to calculate an interference budget without revealing operational information, referred to as the blind interference calculation scheme (BICS). BICS also reduces the computing overhead of PSEO, compared with FCC's SAS by moving interference budgeting tasks to local users and calculating it in an offline manner. To further save the overhead in calculating the interference map, we introduce a quantization method and optimize the grid sizes of the terrestrial area of interest. Additionally, for the case of IUs and dishonest SUs, we propose a "punishment and forgiveness" (PF) mechanism, which draws support from SUs' reputation scores (RSs) and reputation histories (RHs), to encourage SUs to provide truthful information. Theoretical analysis and extensive simulations show that our proposed PSEO and PF-PSEO schemes can better protect all users' operational privacy under various privacy attacks, yielding higher spectrum utilization with less online overhead, compared with state of the art approaches

Chomsiri, T, He, XS, Nanda, P & Tan, Z 2020, 'Hybrid Tree-rule Firewall for High Speed Data Transmission', IEEE Transactions on Cloud Computing.
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Traditional firewalls employ listed rules in both configuration and process phases to regulate network traffic. However, configuring a firewall with listed rules may create rule conflicts, and slows down the firewall. To overcome this problem, we have proposed a Tree-rule firewall in our previous study. Although the Tree-rule firewall guarantees no conflicts within its rule set and operates faster than traditional firewalls, keeping track of the state of network connections using hashing functions incurs extra computational overhead. In order to reduce this overhead, we propose a hybrid Tree-rule firewall in this paper. This hybrid scheme takes advantages of both Tree-rule firewalls and traditional listed-rule firewalls. The GUIs of our Tree-rule firewalls are utilized to provide a means for users to create conflict-free firewall rules, which are organized in a tree structure and called 'tree rules'. These tree rules are later converted into listed rules that share the merit of being conflict-free. Finally, in decision making, the listed rules are used to verify against packet header information. The rules which have matched with most packets are moved up to the top positions by the core firewall. The mechanism applied in this hybrid scheme can significantly improve the functional speed of a firewall.

Chu, P, Zhang, JA, Wang, X, Fang, G & Wang, D 2020, 'Semi-Persistent Resource Allocation Based on Traffic Prediction for Vehicular Communications', IEEE Transactions on Intelligent Vehicles, pp. 1-1.
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Chu, P, Zhang, JA, Wang, X, Fei, Z, Fang, G & Wang, D 2020, 'Interference Characterization and Power Optimization for Automotive Radar with Directional Antenna', IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 3703-3716.
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© 1967-2012 IEEE. Wide deployment of radar sensors on automotive vehicles can potentially lead to a severe interference problem. Such interference has been characterized without considering directional antenna patterns, which could lead to results significantly larger than the actual ones. In this paper, we study the mean power of effective echo signals and interference, by considering both front- and side- mounted radars equipped with directional antennas. We employ the stochastic geometry method to characterize the randomness of vehicles and hence radars in both two-lane and multi-lane scenarios, and derive closed-form expressions for the mean interference by approximating the radiation pattern by Gaussian waveforms. Simulation results are shown to match the analytical results very well, and insights are obtained for the impact of radar parameters on interference. Based on the interference analysis, we aim to minimize the total transmission power of each vehicle with constraints on the required signal to interference and noise ratio. An optimal solution is obtained based on linear programming techniques and corroborated by simulation results.

Chude-Okonkwo, UAK, Maharaj, BT, Vasilakos, AV & Malekian, R 2020, 'Information-Theoretic Model and Analysis of Molecular Signaling in Targeted Drug Delivery', IEEE Transactions on Nanobioscience, vol. 19, no. 2, pp. 270-284.
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© 2002-2011 IEEE. Targeted drug delivery (TDD) modality promises a smart localization of appropriate dose of therapeutic drugs to the targeted part of the body at reduced system toxicity. To achieve the desired goals of TDD, accurate analysis of the system is important. Recent advances in molecular communication (MC) present prospects to analyzing the TDD process using engineering concepts and tools. Specifically, the MC platform supports the abstraction of TDD process as a communication engineering problem in which the injection and transportation of drug particles in the human body and the delivery to a specific tissue or organ can be analyzed using communication engineering tools. In this paper we stand on the MC platform to present the information-theoretic model and analysis of the TDD systems. We present a modular structure of the TDD system and the probabilistic models of the MC-abstracted modules in an intuitive manner. Simulated results of information-theoretic measures such as the mutual information are employed to analyze the performance of the TDD system. Results indicate that uncertainties in drug injection/release systems, nanoparticles propagation channel and nanoreceiver systems influence the mutual information of the system, which is relative to the system's bioequivalence measure.

Costa, E, Climent, E, Ast, S, Weller, MG, Canning, J & Rurack, K 2020, 'Development of a lateral flow test for rapid pyrethroid detection using antibody-gated indicator-releasing hybrid materials', ANALYST, vol. 145, no. 10, pp. 3490-3494.
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Dai, M, Xiao, G, Cheng, S, Wang, D & He, X 2020, 'Structural correlation filters combined with a Gaussian particle filter for hierarchical visual tracking', Neurocomputing.
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© 2020 Visual tracking is a key problem for many computer vision applications such as human-computer interaction, intelligent medical diagnosis, navigation and traffic control management. Most of the existing tracking methods are mainly based on correlation filters. However, boundary effect, scale estimation and template updating have not been fully resolved. Herein, this paper presents a new hierarchical tracking method combining structural correlation filters with a Gaussian Particle Filter (GPF), named KCF-GPF. Weak KCF classifiers are constructed via a Lukas-Kanade (LK) method and the preliminary target location is presented as a weighted sum of these classifiers. Specially, a facile weight strategy is implemented to estimate the reliability of each weak classifier. On the basis of the preliminary target location, the GPF using features from a Convolutional Neural Network (CNN) is employed to predict the location and scale of a target. Extensive experiments with the OTB-2013 and the OTB-2015 databases demonstrate that the proposed algorithm performs favourably against state-of-the-art trackers.

Dang, D, Hoang, D & Nguyen, D 2020, 'Trust-based Scheduling Framework for Big Data Processing with MapReduce', IEEE Transactions on Services Computing (TSC).
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Security and privacy have become a great concern in cloud computing platforms in which users risk the leakage of their private data. The leakage can happen while the data is at rest (in storage), in processing, or on moving within a cloud or between different cloud infrastructures, e.g., from private to public clouds. This paper focuses on protecting data "in processing". For big data applications, the MapReduce framework has been proven as an efficient solution and has been widely deployed, e.g., in healthcare and business data analysis. In this article, we propose a trust-based framework for MapReduce in big data processing tasks. Specifically, we first quantify and propose to assign the sensitive values for data and trust values for map and reduce slots. We then compute the trust value of each resource employed in the big data processing tasks. Depending on the data's sensitivity level of a task, the task requires a given level of trust (i.e., higher sensitive data requires servers/slots with higher trust level). The MapReduce scheduling problem is then formulated as the maximum weighted matching problem of a bipartite graph that aims to maximize the total trust value over all possible assignments subject to various trust requirement of different tasks. The problem is known to be NP-hard. To tackle it, we observe that within a computing node (VM), slots share the same trust value granted from the secured transformation phase. This helps reduce the number of slot nodes of a weight bipartite graph. Leveraging this fact, we propose an efficient heuristic algorithm that achieves 94.7% of the optimal solution obtained via exhaustive search. Extensive simulations show that the trust-based scheduling scheme provides much higher protection for data sensitivity while ensuring good performance for big data applications.

Dao, N-N, Na, W, Tran, A-T, Nguyen, DN & Cho, S 2020, 'Energy-Efficient Spectrum Sensing for IoT Devices', IEEE Systems Journal, pp. 1-9.
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Dehkordi, SA, Farajzadeh, K, Rezazadeh, J, Farahbakhsh, R, Sandrasegaran, K & Dehkordi, MA 2020, 'A survey on data aggregation techniques in IoT sensor networks', WIRELESS NETWORKS, vol. 26, no. 2, pp. 1243-1263.
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Diao, K, Sun, X, Lei, G, Guo, Y & Zhu, J 2020, 'Multiobjective System Level Optimization Method for Switched Reluctance Motor Drive Systems Using Finite Element Model', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Ding, C, Sun, H-H, Zhu, H & Guo, YJ 2020, 'Achieving Wider Bandwidth with Full-Wavelength Dipoles (FWDs) for 5G Base Stations', IEEE Transactions on Antennas and Propagation, vol. 68, no. 2, pp. 1119-1127.
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Dinh, TH, Phung, MD & Ha, QP 2020, 'Summit Navigator: A Novel Approach for Local Maxima Extraction.', IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.
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This paper presents a novel method, called the Summit Navigator, to effectively extract local maxima of an image histogram for multi-object segmentation of images. After smoothing with a moving average filter, the obtained histogram is analyzed, based on the data density and distribution to find the best observing location. An observability index for each initial peak is proposed to evaluate if it can be considered as dominant by using the calculated observing location. Recursive algorithms are then developed for peak searching and merging to remove any false detection of peaks that are located on one side of each mode. Experimental results demonstrated the advantages of the proposed approach in terms of accuracy and consistency in different reputable datasets.

Dou, Y, Li, Y, Zhang, C, Yue, S & Zhu, J 2020, 'Effects of Uniaxial Stress Along Different Directions on Alternating Magnetic Properties of Silicon Steel Sheets', IEEE TRANSACTIONS ON MAGNETICS, vol. 56, no. 3.
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Du, G, Huang, N, He, H, Lei, G & Zhu, J 2020, 'Parameter Design for a High-Speed Permanent Magnet Machine under Multiphysics Constraints', IEEE Transactions on Energy Conversion, pp. 1-1.
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Du, G, Xu, W, Zhu, J & Huang, N 2020, 'Effects of Design Parameters on the Multiphysics Performance of High-Speed Permanent Magnet Machines', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 5, pp. 3472-3483.
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Du, G, Xu, W, Zhu, J & Huang, N 2020, 'Power loss and thermal analysis for high-power high-speed permanent magnet machines', IEEE Transactions on Industrial Electronics, vol. 67, no. 4, pp. 2722-2733.
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© 1982-2012 IEEE. For high-speed permanent magnet machines (HSPMMs), the permanent magnet (PM) is more likely to suffer irreversible demagnetization because the heat dissipation is serious in the HSPMMs, especially for the high-power machines. This paper focuses on the comprehensive research results on the power loss and thermal characteristic for a high-power HSPMM. First, the power loss at the rated load is investigated by finite-element analysis. Then, the temperature distribution of four cooling schemes is compared by the electromagnetic-thermal iteration calculation. The effect of different parameters on thermal behavior is obtained to reduce rotor temperature, which includes an examination of the axial flow duct, cooling medium, sleeve thickness, and sleeve thermal conductivity. Finally, an improved loss separation method is employed to obtain the loss distribution from the measured total loss, and the comprehensive experiments are implemented based on one HSPMM prototype (800 kW, 15 000 rpm) to verify the related theoretical analysis.

Every, JP, Li, L & Dorrell, DG 2020, 'Köppen-Geiger climate classification adjustment of the BRL diffuse irradiation model for Australian locations', Renewable Energy, vol. 147, pp. 2453-2469.
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© 2019 Elsevier Ltd Numerous mathematical models have been developed to estimate diffuse and direct irradiance components based on global irradiation measurements. The Boland–Ridley–Lauret (BRL) model consists of a single set of parameters for all global locations. There is scope to improve the BRL model to better match local climatic conditions. In this research, the Köppen-Geiger climate classification system is considered to develop a set of adjusted BRL models for Australian conditions. Ground-based and satellite-based irradiation data derived from the Australian Bureau of Meteorology are used to tune and test new BRL models developed at a national level and for each climate zone. Irradiation data are processed through a rigorous quality control procedure before parameter tuning. For ground-based data, a new national model results in an improvement in 96% of statistical indicators over the original BRL model while Köppen-Geiger zone adjusted models show improvement over the new national model in 72% of the statistics. For satellite-based global irradiation estimates, a new national BRL model also results in observed improvements, however, no discernible improvement is observed for Köppen-Geiger zone models.

Fan, K, Bao, Z, Liu, M, Vasilakos, AV & Shi, W 2020, 'Dredas: Decentralized, reliable and efficient remote outsourced data auditing scheme with blockchain smart contract for industrial IoT', Future Generation Computer Systems.
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© 2019 Elsevier B.V. The development of cloud computing and the Internet of things (IOT) attracts more and more enterprises to outsource the data from their Industrial Internet of things (IIOT) to cloud servers in order to save operating costs and improve efficiency. However, in this environment, protecting the security and privacy of data storage is an important challenge for IIOT and cloud server provider (CSP). Data auditing could allow data owner discover malicious behaviors of CSP which destroy their outsourced data. The public auditing authorizes the trusted third part auditor (TPA) to audit the owner's outsourced data and frees owner from regular tasks. However, the public auditing using TPA is considered a centralized auditing, and the TPA is assumed totally honest, but it is difficult to find a reliable auditing organization. In this paper, a novel decentralized auditing smart contract in Ethereum is proposed. By replacing the TPA with a designed smart contract, a decentralized auditing scheme (Dredas) is proposed, where anyone can obtain the auditing result from Ethereum without worrying about semi-honest TPA. Compared with traditional auditing, apart from being able to perform traditional auditing functions, Dredas has three important benefits over previous work. First, the random values of challenge are more secure. Dredas chooses the current blockchain nonce as a random seed to prevent any party forging random values. Secondly, in order to achieve a safe, regular, proactive auditing, the protocol writes the auditing rules into the blockchain, and uses the number blocks on the Ethereum as the security timestamp. Finally, data owner, user and CSP must pay some ether for smart contract as deposit. This way not only inhibits the malicious behavior of these three parties, but also makes it more reasonable in real life. We implement Dredas to show that the computation costs are reasonable and efficient.

Fan, X, Xiang, C, Chen, X, Song, X, Yang, P, Gong, L, Nanda, P & He, X 2020, 'BuildSenSys: Reusing Building Sensing Data for Traffic Prediction with Cross-domain Learning', IEEE Transactions on Mobile Computing.
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With the rapid development of smart cities, smart buildings are generating a massive amount of building sensing data by the equipped sensors. Indeed, building sensing data provides a promising way to enrich a series of data-demanding and cost-expensive urban mobile applications. In this paper, as a preliminary exploration, we study how to reuse building sensing data to predict traffic volume on nearby roads. Compared with existing studies, reusing building sensing data has considerable merits of cost-efficiency and high-reliability. Nevertheless, it is non-trivial to achieve accurate prediction on such cross-domain data with two major challenges. First, relationships between building sensing data and traffic data are not unknown as prior, and the spatio-temporal complexities impose more difficulties to uncover the underlying reasons behind the above relationships. Second, it is even more daunting to accurately predict traffic volume with dynamic building-traffic correlations, which are cross-domain, non-linear, and time-varying. To address the above challenges, we design and implement BuildSenSys, a first-of-its-kind system for nearby traffic volume prediction by reusing building sensing data. Our work consists of two parts, i.e., Correlation Analysis and Cross-domain Learning. First, we conduct a comprehensive building-traffic analysis based on multi-source datasets, disclosing how and why building sensing data is correlated with nearby traffic volume. Second, we propose a novel recurrent neural network for traffic volume prediction based on cross-domain learning with two attention mechanisms. Specifically, a cross-domain attention mechanism captures the building-traffic correlations and adaptively extracts the most relevant building sensing data at each predicting step. Then, a temporal attention mechanism is employed to model the temporal dependencies of data across historical time intervals. The extensive experimental studies demonstrate that BuildSenSys outp...

Fang, Z, Hu, J, Lu, Y & Ni, W 2020, 'Three-User Cooperative NOMA Transmission', IEEE Wireless Communications Letters, vol. 9, no. 4, pp. 465-469.
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© 2012 IEEE. This letter presents a new downlink cooperative non-orthogonal multiple access (NOMA) transmission scheme to serve three users within only two time slots. The scheme involves a base station (BS), two direct-link users and one indirect-link user. The BS sends superposed signals to the two direct-link users which decode and forward the signals to the indirect-link user in an alternating fashion. Closed-form expression is derived for the sum-rate of the proposed scheme and a simple expression of sum-rate is also derived in the high signal-to-noise ratio (SNR) region. In the presence of strong inter-user interference (IUI), the proposed scheme can be applied by having each direct-link user to detect the IUI first and then cancel the IUI to decode the signals destined for the indirect-link user and itself. Simulation results show that the scheme with configurable decoding orders at the users is able to achieve a higher sum-rate than existing orthogonal multiple access (OMA) based alternatives.

Farhood, H, Perry, S, Cheng, E & Kim, J 2020, 'Enhanced 3D Point Cloud from a Light Field Image', Remote Sensing, vol. 12, no. 7, pp. 1-1.
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The importance of three-dimensional (3D) point cloud technologies in the field of agriculture environmental research has increased in recent years. Obtaining dense and accurate 3D reconstructions of plants and urban areas provide useful information for remote sensing. In this paper, we propose a novel strategy for the enhancement of 3D point clouds from a single 4D light field (LF) image. Using a light field camera in this way creates an easy way for obtaining 3D point clouds from one snapshot and enabling diversity in monitoring and modelling applications for remote sensing. Considering an LF image and associated depth map as an input, we first apply histogram equalization and histogram stretching to enhance the separation between depth planes. We then apply multi-modal edge detection by using feature matching and fuzzy logic from the central sub-aperture LF image and the depth map. These two steps of depth map enhancement are significant parts of our novelty for this work. After combing the two previous steps and transforming the point–plane correspondence, we can obtain the 3D point cloud. We tested our method with synthetic and real world image databases. To verify the accuracy of our method, we compared our results with two different state-of-the-art algorithms. The results showed that our method can reliably mitigate noise and had the highest level of detail compared to other existing methods.

Farrok, O, Islam, MR, Muttaqi, KM, Sutanto, D & Zhu, J 2020, 'Design and Optimization of a Novel Dual-Port Linear Generator for Oceanic Wave Energy Conversion', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 5, pp. 3409-3418.
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Farrokhi, F, Buchlak, QD, Sikora, M, Esmaili, N, Marsans, M, McLeod, P, Mark, J, Cox, E, Bennett, C & Carlson, J 2020, 'Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms.', World neurosurgery.
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BACKGROUND:Deep brain stimulation (DBS) surgery is an option for patients experiencing medically resistant neurologic symptoms. DBS complications are rare; finding significant predictors requires a large number of surgeries. Machine learning algorithms may be used to effectively predict these outcomes. The aims of this study were to 1) investigate preoperative clinical risk factors and 2) build machine learning models to predict adverse outcomes. METHODS:This multicenter registry collected clinical and demographic characteristics of patients undergoing DBS surgery (n = 501) and tabulated occurrence of complications. Logistic regression was used to evaluate risk factors. Supervised learning algorithms were trained and validated on 70% and 30%, respectively, of both oversampled and original registry data. Performance was evaluated using area under the receiver operating characteristics curve (AUC), sensitivity, specificity, and accuracy. RESULTS:Logistic regression showed that the risk of complication was related to the operating institution in which the surgery was performed (odds ratio [OR] = 0.44, confidence interval [CI] = 0.25-0.78), body mass index (OR = 0.94, CI = 0.89-0.99), and diabetes (OR = 2.33, CI = 1.18-4.60). Patients with diabetes were almost 3× more likely to return to the operating room (OR = 2.78, CI = 1.31-5.88). Patients with a history of smoking were 4× more likely to experience postoperative infection (OR = 4.20, CI = 1.21-14.61). Supervised learning algorithms demonstrated high discrimination performance when predicting any complication (AUC = 0.86), a complication within 12 months (AUC = 0.91), return to the operating room (AUC = 0.88), and infection (AUC = 0.97). Age, body mass index, procedure side, gender, and a diagnosis of Parkinson disease were influential features. CONCLUSIONS:Multiple significant complication risk factors were identified, and supervised learning algorithms effectively predicted adverse outcomes in DBS surgery.

Fu, L, Lin, P, Vasilakos, AV & Wang, S 2020, 'An overview of recent multi-view clustering', Neurocomputing.
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© 2020 Elsevier B.V. With the widespread deployment of sensors and the Internet-of-Things, multi-view data has become more common and publicly available. Compared to traditional data that describes objects from single perspective, multi-view data is semantically richer, more useful, however more complex. Since traditional clustering algorithms cannot handle such data, multi-view clustering has become a research hotspot. In this paper, we review some of the latest multi-view clustering algorithms, which are reasonably divided into three categories. To evaluate their performance, we perform extensive experiments on seven real-world data sets. Three mainstream metrics are used, including clustering accuracy, normalized mutual information and purity. Based on the experimental results and a large number of literature reading, we also discuss existing problems in current multi-view clustering and point out possible research directions in the future. This research provides some insights for researchers in related fields and may further promote the development of multi-view clustering algorithms.

Gao, X, Zhang, T, Du, J & Guo, YJ 2020, '340 GHz Double-Sideband Mixer Based on Antenna-Coupled High-Temperature Superconducting Josephson Junction', IEEE Transactions on Terahertz Science and Technology, vol. 10, no. 1, pp. 21-31.
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© 2011-2012 IEEE. Wireless communication and sensing are moving from microwave, millimeter-wave into the terahertz (THz) frequency regime to meet the fast growing demand of ultrahigh data-rate communications and super resolution imaging. Faced with severe atmospheric absorption attenuation and the lack of power efficient transmitting source at the higher band, ultrasensitive and cost-effective receiver frontend technology is required for advanced THz wireless systems. To date, the most sensitive heterodyne mixers, the key components of frontend receiver systems, are based on low-temperature superconducting materials that operate at liquid helium (4.2 K) temperature range, requiring expensive and bulky cryogenic cooling systems thus hindering them from commercial applications such as wireless communications and sensing. In this article, we present a 340 GHz double-sideband fundamental mixer based on thin-film antenna-coupled high-temperature superconducting (HTS) Josephson junction that operates at a much higher temperature range attainable with smaller and cheaper cryocoolers. Based on our innovative work in terms of advanced device circuit and on-chip antenna designs, accurate parametric simulation analyses, and Josephson junction parameter optimizations, the reported mixer exhibits a measured noise temperature of 470 and 780 K at operating temperatures of 20 and 40 K respectively at 340 GHz, a performance significantly higher than any HTS THz mixers reported to date.

Gautam, S, Lu, DDC, Xiao, W & Lu, Y 2020, 'Realisation of RPS from electrical home appliances in a smart home energy management system', IET Smart Grid, vol. 3, no. 1, pp. 11-21.
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© 2020 Institution of Engineering and Technology. All rights reserved. With the increasing integration of photovoltaic power generation in the low-voltage distribution network, the grid voltage regulation becomes critical, which demands support from different resources. This study presents the feasibility study of home appliance to be applied for appliance to grid mode of operation. The analysis includes the amendments in topology and control to support the concept of supportive platform provided by smart home and smart grid. Home appliances are then proposed as new distributed reactive sources, which are utilised to resolve the issue of voltage regulation, as well as produce reactive power locally for voltage stability. This study discusses the technical transitions in current home appliance to accommodate auxiliary functionality of grid reactive power support (RPS) and how it can fit in the home energy management system architecture to provide the required RPS.

Gautam, S, Lu, Y, Hassan, W, Xiao, W & Lu, DDC 2020, 'Single phase NTD PLL for fast dynamic response and operational robustness under abnormal grid condition', Electric Power Systems Research, vol. 180.
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© 2019 Elsevier B.V. Non-frequency-dependent transfer delay (NTD) approach is one of the simplest and the fastest solution for single-phase AC systems to achieve phase-locked loops (PLLs). It also exhibits immunity to error in estimated quantities in grid frequency variations. However it is susceptible to grid voltage disturbances, such as DC offset and distortions. This paper proposed an improved NTD scheme to achieve both fast dynamic response and operational robustness against abnormal grid conditions. The solution is based on a digital phase lead compensator (PLC), which is cascaded with the MAF inside the PLL control loop to enhance dynamic response and mitigate disturbance, DC offset, and harmonics. The filtering structure is also designed to be adaptive to grid frequency variations. The effectiveness of the proposed solution is verified via simulation and experimental results.

Ghadi, MJ, Azizivahed, A, Rajabi, A, Ghavidel, S, Li, L, Zhang, J, Shafie-khah, M & Catalao, JPS 2020, 'Day-Ahead Market Participation of an Active Distribution Network Equipped with Small-Scale Compressed Air Energy Storage Systems', IEEE Transactions on Smart Grid, pp. 1-1.
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Ghasemi, M, Davoudkhani, IF, Akbari, E, Rahimnejad, A, Ghavidel, S & Li, L 2020, 'A novel and effective optimization algorithm for global optimization and its engineering applications: Turbulent Flow of Water-based Optimization (TFWO)', Engineering Applications of Artificial Intelligence, vol. 92.
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© 2020 Elsevier Ltd In this study we present a new and effective grouping optimization algorithm (namely, the Turbulent Flow of Water-based Optimization (TFWO)), inspired from a nature search phenomenon, i.e. whirlpools created in turbulent flow of water, for global real-world optimization problems. In the proposed algorithm, the problem of selecting control parameters is eliminated, the convergence power is increased and the algorithm have a fixed structure. The proposed algorithm is used to find the global solutions of real-parameter benchmark functions with different dimensions. Besides, in order to further investigate the effectiveness of TFWO, it was used to solve various types of nonlinear Economic Load Dispatch (ELD) optimization problems in power systems and Reliability–RedundancyAllocation Optimization (RRAO) for the overspeed protection system of a gas turbine, as two real-world engineering optimization problems. The results of TFWO are compared with other algorithms, which provide evidence for efficient performance with superior solution quality of the proposed TFWO algorithm in solving a great range of real-parameter benchmark and real-world engineering problems. Also, the results prove the competitive performance and robustness of TFWO algorithm compared to other state-of-the-art optimization algorithms in this study. The source codes of the TFWO algorithm are publicly available at https://github.com/ebrahimakbary/TFWO.

Ghavidel, S, Ghadi, MJ, Azizivahed, A, Aghaei, J, Li, L & Zhang, J 2020, 'Risk-Constrained Bidding Strategy for a Joint Operation of Wind Power and CAES Aggregators', IEEE Transactions on Sustainable Energy, vol. 11, no. 1, pp. 457-466.
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© 2010-2012 IEEE. This paper proposes a coordinated strategy of a hybrid power plant (HPP), which includes a wind power aggregator and a commercial compressed air energy storage (CAES) aggregator to participate in three electricity markets (day-ahead, intraday, and balancing markets). The CAES aggregator has an extra ability which is called a simple-cycle mode operation that makes it works like a gas turbine when needed, which helps the HPP to economically handle the miscalculations of the wind power and electricity price predictions. The coordinated strategy of the HPP is formulated as a three-stage stochastic optimization problem. To control the financial risks, the conditional value-at-risk model is added to the optimization problem. Moreover, the proposed offering method is capable of submitting both bidding quantity and curves to the day-ahead market. A mixed integer linear programming formulation is written for the problem that can be easily solved by commercially available software such as GAMS. The results that were tested on a realistic-based case study located in Spain show the applicability of the suggested method to increase the joint operation profit and decrease the financial risks.

Gong, Y, Zhang, L, Yu, K & Liu, R 2020, 'Exploring Uplink Achievable Rate for HPO MIMO Through Quasi-Monte Carlo and Variance Reduction Techniques', IEEE ACCESS, vol. 8, pp. 75874-75883.
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Guo, K, Guo, Y & Li, J 2020, 'Decoupling Control Analysis of a Flux Reversal Linear Rotary Permanent Magnet Actuator', Journal of Electrical Engineering and Technology, vol. 15, no. 4, pp. 1693-1704.
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© 2020, The Korean Institute of Electrical Engineers. In order to meet the requirement of industrial production, a control system of a novel flux reversal linear rotary permanent magnet actuator (FR-LRPMA) is developed in this paper, and the electromagnetic and motion decoupled process is analyzed in detail. Firstly, the control equation of FR-LRPMA is derived in the nine phase stator coordinate system and dual dq-axis mover coordinate system. Then the control model of FR-LRPMA is built in MATLAB/Simulink using improved space vector pulse width modulation (SVPWM), and the linear, rotary and spiral motions of the proposed actuator are achieved. Finally, the prototype of the actuator is manufactured, and the experiment platform of FR-LRPMA is set up to measure the cogging torque and linear detent force, validating the simulation results. It is concluded that the control system of FR-LRPMA can be converted into two independent single freedom motors by dual dq transformation. The improved SVPWM is effective in the control system, and the method can be used to solve the electromagnetic and motion decoupling problems.

Hanawal, M, Nguyen, D & Krunz, M 2020, 'Cognitive Networks with In-band Full-duplex Radios: Jamming Attacks and Countermeasures', IEEE Transactions on Cognitive Communications and Networking.
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Although in-band full-duplex (IBFD) radios promise to double the throughput of a wireless link, they are more vulnerable to jamming attacks than their out-of-band full-duplex (OBFD) counterparts. For two communicating OBFD nodes, a jammer needs to attack both the uplink and the downlink channels to completely break the communication link. In contrast, only one common channel needs to be jammed in the case of two IBFD nodes. Even worse, a jammer with self-interference suppression (SIS) capabilities (the underlying technique of IBFD radios) can learn the transmitters’ activity while injecting interference, allowing it to react instantly to the transmitter’s strategies. In this work, we consider a power-constrained IBFD “reactive-sweep” jammer that sweeps through the set of channels by jamming a subset of them simultaneously. We model the interactions between the IBFD radios and the jammer as a stochastic constrained zero-sum Markov game in which nodes adopt the frequency hopping (FH) technique as their strategies to counter jamming attacks. Beside the IBFD transmission-reception (TR) mode, we introduce an additional operation mode, called transmission-detection (TD), in which an IBFD radio transmits and leverages its SIS capability to detect jammers. The aim of the TD mode is to make IBFD radios more cognitive to jamming. The nodes’ optimal defense strategy that guides them when to hop and which operational mode (TD or TR) to use is then established from the equilibrium of the stochastic Markov game. We prove that this optimal policy has a threshold structure, in which IBFD nodes stay on the same channel up to a certain number of time slots before hopping. Simulation results show that our policy significantly improves the throughput of IBFD nodes under jamming attacks.

Hao, Z, Cook, K, Canning, J, Chen, HT & Martelli, C 2020, '3-D printed smart orthotic insoles: Monitoring a person's gait step by step', IEEE Sensors Letters, vol. 4, no. 1.
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© 2017 IEEE. This article reports a 3-D printing intelligent insole gait monitoring system based on an embedded fiber Bragg grating (FBG). The smart insole combines 3-D printing technology and FBG sensors providing high sensitivity and end-point low cost. Results using pressure points measured by four FBGs are sufficient to differentiate foot loads and gait types.

Hasanpour, S, Siwakoti, Y, Mostaan, A & Blaabjerg, F 2020, 'New Semi-Quadratic High Step-Up DC/DC Converter for Renewable Energy Applications', IEEE Transactions on Power Electronics, pp. 1-1.
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Hayat, T, Afzal, MU, Ahmed, F, Zhang, S, Esselle, KP & Vardaxoglou, JYC 2020, 'Low-Cost Ultra-Wideband High-Gain Compact Resonant Cavity Antenna', IEEE Antennas and Wireless Propagation Letters, pp. 1-1.
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He, L, Lu, Z, Geng, L, Zhang, J, Li, X & Guo, X 2020, 'Environmental economic dispatch of integrated regional energy system considering integrated demand response', International Journal of Electrical Power and Energy Systems, vol. 116.
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© 2019 Elsevier Ltd To reduce the emissions of greenhouse gases and air pollutants, various low-emission measures have been taken in the power system, which are gradually intensifying the interdependency among different energy systems. Considering the carbon trading scheme and different air pollutant control technologies, this paper proposes an environmental economic dispatch model for the coordinated operation of an integrated regional energy system, which consists of a regional electricity supply network and a natural gas network, along with district energy hubs. Each energy hub contains a combined heat and power unit, a CO2-capture-based power to gas facility, a heat pump, a gas furnace and different energy storage facilities. To achieve an optimized balance between operational cost and emissions during the environmental economic dispatch of this integrated regional energy system, a price-based integrated demand response program is introduced in the energy hub. Then the proposed model is converted into a mixed-integer linear programming problem to find solutions efficiently. Case studies are carried out to demonstrate the effectiveness of proposed environmental economic dispatch model of the integrated regional energy system.

He, S, Huang, D, Feng, X, Deng, J, Li, J & Zhu, J 2020, 'Transient potential distribution on transformer winding considering the effect of core lamination stack', AIP ADVANCES, vol. 10, no. 1.
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Heidary, A, Radmanesh, H, Bakhshi, A, Samandarpour, S, Rouzbehi, K & Shariati, N 2020, 'A Compound Ferroresonance Overvoltage and Fault Current Limiter for Power System Protection', IET Energy Systems Integration.
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Heidary, A, Radmanesh, H, Naghibi, SH, Samandarpour, S, Rouzbehi, K & Shariati, N 2020, 'Distribution system protection by coordinated fault current limiters', IET Energy Systems Integration, vol. 2, no. 1, pp. 59-65.
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Heidary, A, Radmanesh, H, Rouzbehi, K & CheshmehBeigi, HM 2020, 'A Multifunction High-Temperature Superconductive Power Flow Controller and Fault Current Limiter', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 30, no. 5.
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Heidary, A, Radmanesh, H, Rouzbehi, K, Mehrizi-Sani, A & Gharehpetian, GB 2020, 'Inductive fault current limiters: A review', Electric Power Systems Research, vol. 187, pp. 106499-106499.
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Hlalele, TG, Naidoo, RM, Zhang, J & Bansal, RC 2020, 'Dynamic Economic Dispatch With Maximal Renewable Penetration Under Renewable Obligation', IEEE ACCESS, vol. 8, pp. 38794-38808.
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Hoang, DT, Nguyen, DN, Alsheikh, MA, Gong, S, Dutkiewicz, E, Niyato, D & Han, Z 2020, '"Borrowing Arrows with Thatched Boats": The Art of Defeating Reactive Jammers in IoT Networks', IEEE Wireless Communications Magazine.

Hoang, TM, El Shafie, A, Da Costa, DB, Duong, TQ, Tuan, HD & Marshall, A 2020, 'Security and Energy Harvesting for MIMO-OFDM Networks', IEEE Transactions on Communications.
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IEEE We consider a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) network in which a source node, Alice, communicates with an energy-harvesting destination node, Bob, in the presence of a passive eavesdropper. To secure the wireless transmission, Alice generates a hybrid artificial noise (AN) in both frequency and time domains. Moreover, in order to collect more energy, Bob splits the received signal power of the cyclic prefix of each OFDM block. We then propose two non-convex optimization problems to balance both the need for security and the need for harvesting energy at Bob. While one considers maximizing the secrecy rate, the other approach aims at maximizing the harvested energy. Path-following algorithms of low computational complexity are developed and evaluated. Our numerical results show the gain of our proposed scheme and the effectiveness of our proposed algorithms.

Hoang, VT, Phung, MD, Dinh, TH & Ha, QP 2020, 'System Architecture for Real-Time Surface Inspection Using Multiple UAVs', IEEE Systems Journal, pp. 1-12.
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Hossain, MA, Canning, J & Yu, Z 2020, 'Fluorescence-Based Determination of Olive Oil Quality Using an Endoscopic Smart Mobile Spectrofluorimeter', IEEE SENSORS JOURNAL, vol. 20, no. 8, pp. 4156-4163.
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Hou, S, Ni, W, Zhao, S, Cheng, B, Chen, S & Chen, J 2020, 'Decentralized Real-Time Optimization of Voltage Reconfigurable Cloud Computing Data Center', IEEE Transactions on Green Communications and Networking, vol. 4, no. 2, pp. 577-592.
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© 2017 IEEE. Dynamic Voltage and Frequency Scaling, and Adaptive Body Biasing are increasingly adopted hardware techniques to improve energy efficiency of multi-core servers by adjusting reconfigurable supply and body bias voltages. Existing algorithms cannot fulfill the potential of the techniques because random variations of workload and background traffic can lead to coupling of voltage configurations over time and hinder effective real-time reconfigurations. This paper proposes a new approach which enables multi-core servers to optimize in real-time their configurations under random traffic variations. The approach asymptotically minimizes the time-averaged energy consumption of cloud computing while maintaining platform stability in a fully decentralized fashion. Lyapunov optimization is employed to decouple and separately optimize the voltage configuration, inter- and intra-server offloading schedules among servers and over time. The voltage configuration which is non-convex is proved to increasingly exhibit convexity with growing workloads. The optimality loss from the non-convexity asymptotically diminishes. Simulations show our approach dramatically reduces the power if the cloud is lightly loaded, or converts the power to processing capacity otherwise. Embraced by theoretical breakthroughs, the approach can potentially revolutionize cloud computing.

Hou, S, Ni, W, Zhao, S, Cheng, B, Chen, S & Chen, J 2020, 'Frequency-Reconfigurable Cloud Versus Fog Computing: An Energy-Efficiency Aspect', IEEE Transactions on Green Communications and Networking, vol. 4, no. 1, pp. 221-235.
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© 2017 IEEE. Cloud and fog computing are two emerging Internet-based collaborative technologies for big data analytics. An interesting question arising is whether the two technologies can resonate with significant gains of energy efficiency, especially in the case where advanced cloud platforms with Dynamic Voltage and Frequency Scaling (DVFS) are considered. This paper answers the question by formulating the optimization of a cloud with and without the assistance of fog, and deriving asymptotically optimal distributed solutions for the two cases. We also identify the critical condition under which fog computing helps the cloud to reduce the time-averaged queue lengths. The condition depends on the configurations of the fog, and the configurations of the connections between the fog and cloud. Extensive simulations exhibit good consistency with our analysis of the conditional benefits of fog computing. Evident from experimental datasets, the proposed fog-assisted cloud platform is able to increase the time-averaged energy efficiency by about 32.2%, and decrease the time-averaged queue length by around 37.0%, compared to a fog-coordinated counterpart where fog nodes only dispatch data and do not process the data.

Hu, S, Chen, X, Ni, W, Wang, X & Hossain, E 2020, 'Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey', IEEE Transactions on Green Communications and Networking, vol. 4, no. 2, pp. 461-496.
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© 2017 IEEE. The advancements in smart power grid and the advocation of 'green communications' have inspired the wireless communication networks to harness energy from ambient environments and operate in an energy-efficient manner for economic and ecological benefits. This article presents a contemporary review of recent breakthroughs on the utilization, redistribution, trading and planning of energy harvested in future wireless networks interoperating with smart grids. This article starts with classical models of renewable energy harvesting technologies. We embark on constrained operation and optimization of different energy harvesting wireless systems, such as point-to-point, multipoint-to-point, multipoint-to-multipoint, multi-hop, and multi-cell systems. We also review wireless power and information transfer technologies which provide a special implementation of energy harvesting wireless communications. A significant part of the article is devoted to the redistribution of redundant (unused) energy harvested within cellular networks, the energy planning under dynamic pricing when smart grids are in place, and two-way energy trading between cellular networks and smart grids. Applications of different optimization tools, such as convex optimization, Lagrangian dual-based method, subgradient method, and Lyapunov-based online optimization, are compared. This article also collates the potential applications of energy harvesting techniques in emerging (or upcoming) 5G/B5G communication systems. It is revealed that an effective redistribution and two-way trading of energy can significantly reduce the electricity bills of wireless service providers and decrease the consumption of brown energy. A list of interesting research directions are provided, requiring further investigation.

Hu, Z, Liu, RP, Ni, W, Wen, X, Lu, Z & Dutkiewicz, E 2020, 'Analysis of Clustered Licensed-Assisted Access in Unlicensed Spectrum', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 69, no. 1, pp. 349-360.
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Huang, H, Savkin, AV & Ni, W 2020, 'Energy-efficient 3D navigation of a solar-powered UAV for secure communication in the presence of eavesdroppers and no-fly zones', Energies, vol. 13, no. 6.
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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Unmanned Aerial Vehicles (UAVs) have been regarded as a promising means to reshape future wireless communication systems. In this paper, we consider how to plan the trajectory of a solar-powered UAV under a cloudy condition to secure the communication between the UAV and a target ground node against multiple eavesdroppers. We propose a new 3D UAV trajectory optimization model by taking into account the UAV energy consumption, solar power harvesting, eavesdropping and no-fly zone avoidance. A Rapidly-exploring Random Tree (RRT) method is developed to construct the UAV trajectory. Computer simulations and comparisons with a baseline method demonstrate that the proposed method is able to produce trajectories to ensure the valid wireless communication link with the ground node and prevent eavesdropping.

Huang, L, Yang, Q, Wu, J, Huang, Y, Wu, Q & Xu, J 2020, 'Generated Data With Sparse Regularized Multi-Pseudo Label for Person Re-Identification', IEEE SIGNAL PROCESSING LETTERS, vol. 27, pp. 391-395.
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Huang, M, Liu, A, Xiong, NN, Wang, T & Vasilakos, AV 2020, 'An effective service-oriented networking management architecture for 5G-enabled internet of things', Computer Networks, vol. 173.
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© 2020 The development of a 5G-enabled Internet of Things has led to a dramatic increase in network traffic load, which has presented tremendous challenges to network management. In this paper, a service-oriented network architecture is proposed to support the effective management of 5G-enabled IoT systems. This architecture effectively reduces the traffic load and simplifies network management by introducing a service aggregation and caching (SAaC) scheme. Specifically, SAaC first breaks through the data-centric network architecture by converting data into services. Then, SAaC significantly reduces traffic load and energy consumption by service aggregation. Finally, SAaC introduces service caching, and each content router caches new services locally after aggregating received services so that user requests are handled at the network layer. Experimental results demonstrate that compared with traditional solutions, the SAaC scheme improves the request response time by 20.52%–56.09%, reduces the traffic load by 10.85%–37.67%, and reduces energy consumption by more than 50%.

Huang, W, Hua, W, Chen, F & Zhu, J 2020, 'Enhanced Model Predictive Torque Control of Fault-Tolerant Five-Phase Permanent Magnet Synchronous Motor With Harmonic Restraint and Voltage Preselection', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 8, pp. 6259-6269.
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Huang, W, Hua, W, Chen, F, Hu, M & Zhu, J 2020, 'Model Predictive Torque Control With SVM for Five-Phase PMSM Under Open-Circuit Fault Condition', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 5, pp. 5531-5540.
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Huang, Y, Xu, J, Wu, Q, Zhong, Y, Zhang, P & Zhang, Z 2020, 'Beyond Scalar Neuron: Adopting Vector-Neuron Capsules for Long-Term Person Re-Identification', IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1.
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Ibrahim, IA, Hossain, MJ & Duck, BC 2020, 'An Optimized Offline Random Forests-Based Model for Ultra-Short-Term Prediction of PV Characteristics', IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, vol. 16, no. 1, pp. 202-214.
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Ibrahim, IA, Hossain, MJ, Duck, BC & Fell, CJ 2020, 'An Adaptive Wind-Driven Optimization Algorithm for Extracting the Parameters of a Single-Diode PV Cell Model', IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, vol. 11, no. 2, pp. 1054-1066.
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Ibrahim, IA, Hossain, MJ, Duck, BC & Nadarajah, M 2020, 'An improved wind driven optimization algorithm for parameters identification of a triple-diode photovoltaic cell model', ENERGY CONVERSION AND MANAGEMENT, vol. 213.
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Imran, K, Ullah, K, Khattak, A, Zhang, J, Pal, A, Rafique, MN & Baig, SM 2020, 'Matchmaking model for bilateral trading decisions of load serving entity', ELECTRIC POWER SYSTEMS RESEARCH, vol. 183.
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Imran, K, Zhang, J, Pal, A, Khattak, A, Ullah, K & Baig, SM 2020, 'Bilateral negotiations for electricity market by adaptive agent-tracking strategy', Electric Power Systems Research, vol. 186.
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© 2020 Bilateral transactions hedge both sides against uncertain price and volume risks of day-ahead auction and make up major portions of trading in electricity markets. Peer-to-peer bilateral transactions avoid broker fees but involve challenges of balancing between cooperative and competitive strategies for multi-round negotiations. To solve these challenges, this paper develops novel utility-based and adaptive agent-tracking strategies for bilateral negotiations. Relying on bilateral transaction volume and utility curves determined over a price range during unilateral pre-negotiation, utility-based strategies are developed for generation company (GenCo) agent (load serving entity (LSE) agent) to offer (bid) volumes and prices during multi-round bilateral negotiations. GenCo agent is also equipped with a new adaptive agent-tracking strategy that estimates reservation price of each LSE agent by Bayesian learning and updates the estimates in each round. The adaptive agent-tracking strategy facilitates cooperative yet competitive responses. Integration of new bilateral negotiation strategies with existing day-ahead auction in a renowned agent-based platform also enables combined simulation of the two market types. The case study demonstrates that the adaptive agent-tracking strategy empowers GenCoagents to swing bilateral negotiation results in their favor and yield 7% more payoff than the utility-based strategy, while achieving 100% improvement in frequency of failure of negotiation.

Islam, M, Nadarajah, M & Hossain, MJ 2020, 'A Grid-Support Strategy with PV Units to Boost Short-Term Voltage Stability under Asymmetrical Faults', IEEE Transactions on Power Systems, vol. 35, no. 2, pp. 1120-1131.
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© 1969-2012 IEEE. Modern grid codes demand the integration of voltage support capability with photo-voltaic (PV) generators to ensure a secure operation of power systems. On the other hand, short-term voltage instability (STVI) of distribution networks (DNs) is one of the key issues to be addressed. It can occur due to high proportion of induction motor loads. However, the existing literature lacks a thorough analysis of short-term voltage stability (STVS) of DNs following an asymmetrical fault. Furthermore, an effective voltage-support strategy for PV units, which can improve the STVS while mitigating the excessive voltage swell, is essential for secure operation. Hence, firstly this paper thoroughly investigates the STVS of DNs subjected to asymmetrical faults. 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 point of common coupling (PCC) aimed at mitigating the STVI and regulating the phase voltages within the margins. The key features of the proposed strategy are, fast and accurate estimation of the network's impedance at PCC is not required and it can be easily re-designed considering the network's dynamic behaviors. The efficacy of the proposed method is validated on two IEEE benchmark test systems, and the results demonstrate the effectiveness in improving the STVS and alleviating over voltage issues.

Islam, MR, Lu, H, Islam, MR, Hossain, J & Li, L 2020, 'An IoT- Based Decision Support Tool for Improving the Performance of Smart Grids Connected with Distributed Energy Sources and Electric Vehicles', IEEE Transactions on Industry Applications, pp. 1-1.
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Jafari, M, Malekjamshidi, Z, Zhu, J & Khooban, MH 2020, 'Novel Predictive Fuzzy Logic-Based Energy Management System for Grid-connected and Off-grid Operation of Residential Smart Micro-grids', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 8, no. 2, pp. 1391-1404.
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IEEE In this paper, a novel energy management system with two operating horizons is proposed for a residential micro-grid application. The micro-grid utilises the energies of a photovoltaic (PV), a fuel cell and a battery bank to supply the local loads through a combination of electric and magnetic buses. The proposed micro-grid operates in a large number of grid-connected and off-grid operation modes. The energy management system includes a long-term data prediction unit based on a 2D dynamic programming and a short-term fuzzy controller. The long-term prediction unit is designed to determine the appropriate variation range of the battery state of charge and fuel cell state of hydrogen. The efficiency performance of the micro-grid components, predicted energy generation and demand, energy cost and the system constraints are taken into account. The resultant data then is sent to the short-term fuzzy controller which determines the operation mode of the micro-grid based on the real-time condition of the micro-grid elements. A prototype of the proposed micro-grid including the energy management system is developed, and experimental tests are conducted for three different energy management scenarios. The proposed management technique is validated through energy distribution and cost analysis.

Jafarizadeh, S, Tofigh, F, Lipman, J & Abolhasan, M 2020, 'Optimizing synchronizability in networks of coupled systems', AUTOMATICA, vol. 112.
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Jamborsalamati, P, Hossain, MJ, Taghizadeh, S, Konstantinou, G, Manbachi, M & Dehghanian, P 2020, 'Enhancing Power Grid Resilience Through an IEC61850-Based EV-Assisted Load Restoration', IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, vol. 16, no. 3, pp. 1799-1810.
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Jin, P, Tian, Y, Lu, Y, Guo, Y, Lei, G & Zhu, J 2020, '3-D Analytical Magnetic Field Analysis of the Eddy Current Coupling With Halbach Magnets', IEEE TRANSACTIONS ON MAGNETICS, vol. 56, no. 1.
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Jones, GT, Siwakoti, YP & Rogers, DJ 2020, 'Active Gate Drive to Increase the Power Capacity of Hard-Switched IGBTs', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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Ju, M, Ding, C, Guo, YJ & Zhang, D 2020, 'IDGCP: Image Dehazing Based on Gamma Correction Prior', IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 29, pp. 3104-3118.
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Karami, E, Khalilinia, A, Bali, A & Rouzbehi, K 2020, 'Monte-Carlo-based simulation and investigation of 230 kV transmission lines outage due to lightning', HIGH VOLTAGE, vol. 5, no. 1, pp. 83-91.
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Karmokar, DK & Chen, S-L 2020, 'Slot antenna miniaturization by loading dumbbell-shaped slots and strips, square-shaped loops, and shorting vias', MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, vol. 62, no. 6, pp. 2307-2310.
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Karmokar, DK, Chen, S-L, Thalakotuna, D, Qin, P-Y, Bird, TS & Guo, YJ 2020, 'Continuous Backward-to-Forward Scanning 1-D Slot-Array Leaky-Wave Antenna With Improved Gain', IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, vol. 19, no. 1, pp. 89-93.
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Karmokar, DK, Guo, YJ, Chen, S-L & Bird, TS 2020, 'Composite Right/Left-Handed Leaky-Wave Antennas for Wide-Angle Beam Scanning With Flexibly Chosen Frequency Range', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 1, pp. 100-110.
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Khan, MA, Zhu, Y, Yao, Y, Zhang, P, Agrawal, A & Reece, PJ 2020, 'Impact of metal crystallinity-related morphologies on the sensing performance of plasmonic nanohole arrays', Nanoscale, vol. 12, no. 14, pp. 7577-7585.
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© The Royal Society of Chemistry . Plasmonic nanohole arrays for biosensing applications have attracted tremendous attention because of their flexibility in optical signature design, high multiplexing capabilities, simple optical alignment setup, and high sensitivity. The quality of the metal film, including metal crystallinity and surface roughness, plays an important role in determining the sensing performance because the interaction between free electrons in the metal and incident light is strongly influenced by the metal surface morphology. We systematically investigated the influence of metal crystallinity-related morphologies on the sensing performance of plasmonic nanohole arrays after different metal deposition processes. We utilised several non-destructive nanoscale surface characterisation techniques to perform a quantitative and comparative analysis of the Au quality of the fabricated sensor. We found empirically how the surface roughness and grain sizes influence the permittivity of the Au film and thus the sensitivity of the fabricated sensor. Finally we confirmed that the deposition conditions that provide both low surface roughness and large metal grain sizes improve the sensitivity of the plasmonic sensor.

Khan, MNH, Forouzesh, M, Siwakoti, YP, Li, L & Blaabjerg, F 2020, 'Switched Capacitor Integrated (2n+1)-Level Step-Up Single-Phase Inverter', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 8, pp. 8248-8260.
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Khan, MNH, Forouzesh, M, Siwakoti, YP, Li, L, Kerekes, T & Blaabjerg, F 2020, 'Transformerless Inverter Topologies for Single-Phase Photovoltaic Systems: A Comparative Review', IEEE Journal of Emerging and Selected Topics in Power Electronics.

Khan, MNH, Siwakoti, YP, Li, L & Blaabjerg, F 2020, 'H-Bridge Zero-Voltage Switch Controlled Rectifier (HB-ZVSCR) Transformerless Mid-Point-Clamped Inverter for Photovoltaic Applications', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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A single-phase transformerless mid-point clamped H-bridge zero-voltage switch-controlled rectifier inverter topology is proposed in this paper for photovoltaic (PV) systems to address the issue of common mode (CM) voltage and leakage currents. Apart from the full H-bridge inverter, the proposed voltage clamping circuit consists of two switches and a full-bridge diode which clamps the AC terminal to the DC midpoint (consisting of two DC-link capacitors) during the freewheeling period. As a result, the common mode voltage is held constant which makes it suitable for the grid-connected PV system. The operating principle and CM effect of the proposed topology are analysed and compared with the conventional topologies. This is followed by the thermal analysis and loss calculation, which shows that the proposed circuit is more efficient over the conventional topologies. Validation is carried out using MATLAB-Simulink using the PLECS toolbox followed by a scale down prototype of 1.5 kW. It is shown that the proposed inverter has the 98±1% efficiency over a wide range of loads with a peak efficiency of 98.96%, and the total harmonic distortion of the output current relatively low (≤1.8 %). The leakage current (icm) is measured for different values of parasitic capacitance that reaches a maximum of 16.65 mA for 330 nF capacitor under consideration which is well below the limit set by different safety standards

Khan, SA, Guo, Y, Siwakoti, YP, Lu, DD-C & Zhu, J 2020, 'A Disturbance Rejection-Based Control Strategy for Five-Level T-Type Hybrid Power Converters With Ripple Voltage Estimation Capability', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 9, pp. 7364-7374.
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Khan, SA, Guo, Y, Siwakoti, YP, Lu, DD-C & Zhu, J 2020, 'A Disturbance Rejection-Based Control Strategy for Five-Level T-Type Hybrid Power Converters With Ripple Voltage Estimation Capability.', IEEE Trans. Ind. Electron., vol. 67, pp. 7364-7374.

Kovaleva, M, Bulger, D & Esselle, KP 2020, 'Comparative Study of Optimization Algorithms on the Design of Broadband Antennas', IEEE Journal on Multiscale and Multiphysics Computational Techniques, vol. 5, pp. 89-98.
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Lai, S, Fan, X, Ye, Q, Tan, Z, Zhang, Y, He, X & Nanda, P 2020, 'FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks', IEEE Access, vol. 8, pp. 13516-13526.
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Lalbakhsh, A, Afzal, MU, Esselle, KP & Smith, SL 2020, 'Low-Cost Nonuniform Metallic Lattice for Rectifying Aperture Near-Field of Electromagnetic Bandgap Resonator Antennas', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 5, pp. 3328-3335.
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Lam, SC & Sandrasegaran, K 2020, 'Fractional Frequency Reuse in Multi-tier Networks: Performance Analysis and Optimization', International Journal of Wireless Information Networks, vol. 27, no. 1, pp. 164-183.
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© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Frequency Reuse (FR) is an efficient approach to improve the network performance in a multi-cell cellular network. In this paper, we investigate the performance of heterogeneous networks utilising two well-known frequency reuse algorithms, called Strict FR and Soft FR, with a reuse factor of Δ (Δ> 1). Based on a two-phase operation of the FR algorithm, we develop a new approach to analyse cellular networks based on the Poisson Point Process (PPP) model which successfully demonstrates the impact of the network parameters (such as the number of allocated Resource Blocks (RBs) and bias factor) and FR parameters (such as Base Station (BS) transmit power) on the performance of a user and overall network. Compared to related works, we propose the following novel approaches: (i) we investigate flexible FR networks in which users have connections with the BSs which deliver the highest performance; (ii) the BS observes SINR on the data channel to classify each user into either a Cell-Edge User (CEU) or Cell-Center User (CCU); (iii) the initial state of the network is considered to establish the initial network interference when new users arrive and request connections to the BSs. In the case of a single-tier network, it is proved that our analytical approach is more accurate than previous works. In the case of a two-tier network, the analytical results indicate that compared to the 3GPP model, our proposed model not only reduces up to 40.79% and 3.8% power consumption of a BS on the data channel but also achieves 16.08% and 18.63% higher data rates in the case of Strict FR and Soft FR respectively. Furthermore, the paper presents an approach to find an optimal value of SINR thresholds and bias factor to achieve the maximum network performance.

Le, AT, Tran, LC, Huang, X & Guo, YJ 2020, 'Analog Least Mean Square Loop for Self-Interference Cancellation: A Practical Perspective', SENSORS, vol. 20, no. 1.
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Le, AT, Tran, LC, Huang, X & Guo, YJ 2020, 'Beam-Based Analog Self-Interference Cancellation in Full-Duplex MIMO Systems', IEEE Transactions on Wireless Communications, vol. 19, no. 4, pp. 2460-2471.
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© 2002-2012 IEEE. Self-interference (SI) cancellation for full-duplex (FD) multiple input multiple output (MIMO) systems is challenging due to both hardware and signal processing complexity. In this paper, a beam-based adaptive filter structure with analog least mean square (ALMS) loops is proposed to significantly reduce the complexity of SI cancellation for FD MIMO systems. With this structure, the number of adaptive filters required for SI cancellation scales linearly with the number of transmit beams rather than quadratically with the number of antennas. Furthermore, to avoid additional transmit chains used to up-convert the beam signals to generate reference signals for the ALMS loops, a novel method is proposed to select the optimized reference signals from all transmitted signals. In addition, our stationary analysis shows that the proposed structure for FD MIMO systems outperforms the ALMS loop employed for an FD single input single output system. Simulations are conducted to confirm the theoretical analyses.

Lee, SS, Lim, CS, Siwakoti, YP & Lee, KB 2020, 'Dual-T-Type Five-Level Cascaded Multilevel Inverter with Double Voltage Boosting Gain', IEEE Transactions on Power Electronics, vol. 35, no. 9, pp. 9524-9531.
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© 1986-2012 IEEE. The switched-capacitor-based cascaded multilevel inverters (CMI) have been emerging due to their voltage boosting capability. Unfortunately, they suffer from impulse charging current and nonuniform operation. This article presents a topology termed as dual-T-type five-level CMI to resolve these problems without compromising the desirable voltage boosting characteristic. The main idea is to integrate a half bridge and an inductor to soft charge a capacitor that is connected in series with the dc source. The capacitor enables the voltage gain boosted to two, while the control of eight power switches that constitutes a dual-T structure enables five voltage levels generation. In addition, uniform operation is achieved for cascaded extensions. The operating principle of the proposed topology is analyzed and elaborated. For validation, simulation, and experimental results of a prototype are presented.

Lee, SS, Lim, CS, Siwakoti, YP & Lee, K-B 2020, 'Hybrid 7-Level Boost Active-Neutral-Point-Clamped (H-7L-BANPC) Inverter', IEEE Transactions on Circuits and Systems II: Express Briefs, pp. 1-1.
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Lee, SS, Siwakoti, YP, Lim, CS & Lee, K-B 2020, 'An Improved PWM Technique to Achieve Continuous Input Current in Common-Ground Transformerless Boost Inverter', IEEE Transactions on Circuits and Systems II: Express Briefs, pp. 1-1.
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Lei, G, Bramerdorfer, G, Liu, C, Guo, Y & Zhu, J 2020, 'Robust Design Optimization of Electrical Machines: A Comparative Study and Space Reduction Strategy', IEEE Transactions on Energy Conversion, pp. 1-1.
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Lei, G, Bramerdorfer, G, MA, BO, Guo, Y & Zhu, J 2020, 'Robust Design Optimization of Electrical Machines: Multi-objective Approach', IEEE Transactions on Energy Conversion, pp. 1-1.
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Li, H-Y, Xu, J-X & Zhang, XY 2020, 'Single-to-Balanced and Balanced-to-Balanced Dual-channel Filters Using Multilayer Substrate Integrated Waveguide Cavities', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Li, HY, Xu, JX, Yang, Y & Zhang, XY 2020, 'Novel Switchable Filtering Circuit With Function Reconfigurability Between SPQT Filtering Switch and Four-Way Filtering Power Divider', IEEE Transactions on Microwave Theory and Techniques, vol. 68, no. 3, pp. 867-876.
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© 2019 IEEE. In this article, we propose a circuit model for designing the switchable filtering circuit with reconfigurable functions between a single-pole quad-throw (SPQT) filtering switch (State 1) and a four-way filtering power divider (State 2) without additional switchable impedance matching network (IMN). The proposed circuit model can be utilized as the feeding network of a switchable directive and omni-directional antenna system to eliminate the omni-directional antenna in conventional solutions to reduce the size and cost. It consists of four filter channels with a common port. In State 1, it works as a SPQT filtering switch, where only one channel is turned on to realize good filtering responses and the impedances at the other three channels are adapted to infinity to realize high isolation. The four channels are turned on simultaneously in State 2 to work as a four-way filtering power divider, and the input impedance of the common port is the same as that in State 1. Thus, a switchable IMN is not required for port matching when switching between the two states. Transmission zeros are generated to enhance the skirt selectivity. For verification, the filtering circuit is constructed using high- Q coaxial resonators. Experimental results show excellent performance in both states acting as a SPQT filtering switch and a four-way filtering power divider.

Li, J, Liu, M, Xue, Z, Fan, X & He, X 2020, 'RTVD: A Real-Time Volumetric Detection Scheme for DDoS in the Internet of Things', IEEE ACCESS, vol. 8, pp. 36191-36201.
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Li, Y, Zhu, J, Zhu, L, Li, Y & Lei, G 2020, 'A Dynamic Magnetostriction Model of Grain-Oriented Sheet Steels Based on Becker-Doring Crystal Magnetization Model and Jiles-Atherton Theory of Magnetic Hysteresis', IEEE TRANSACTIONS ON MAGNETICS, vol. 56, no. 3.
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Li, Z, Tang, X, Yang, Y, Lu, D & Cai, Z 2020, 'Three-pole wide-tuning-range balanced frequency-agile bandpass filter with constant absolute bandwidth and 3 transmission zeros', Microwave and Optical Technology Letters.
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© 2020 Wiley Periodicals, Inc. This paper proposes a 3-pole wide-tuning-range, balanced frequency-agile bandpass filter (BAL-FA-BPF) with constant absolute bandwidth (CABW) and 3 transmission zeros (TZs). Under the differential-mode (DM) operation, the cascaded trisection coupling topology with source-load coupling is constructed. Thus, 3 adaptive TZs are generated for the DM responses, which improves the passband selectivity and stopband suppression. Under the common-mode (CM) operation, the short stubs and lumped elements are added at the symmetric plane which effectively improves the CM suppression. Using the advanced matrix synthesis, a demonstrative BAL-FA-BPF is designed with stable CABW and controlled by single-DC-bias. The measured frequency tuning range of the DM passband is 2.0 to 3.0 GHz (40%) and 3 dB-bandwidth is kept at 174 ± 3 MHz (±1.7%). The CM suppression is better than 25 dB.

Lian, J-W, Ban, Y-L, Zhu, H & Guo, YJ 2020, 'Reduced-Sidelobe Multibeam Array Antenna Based on SIW Rotman Lens', IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, vol. 19, no. 1, pp. 188-192.
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Lian, J-W, Ban, Y-L, Zhu, H & Guo, YJ 2020, 'Uniplanar Beam-Forming Network Employing Eight-Port Hybrid Couplers and Crossovers for 2-D Multibeam Array Antennas', IEEE Transactions on Microwave Theory and Techniques, pp. 1-1.
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Liang, Q, Wu, W, Yang, Y, Zhang, R, Peng, Y & Xu, M 2020, 'Multi-Player Tracking for Multi-View Sports Videos with Improved K-Shortest Path Algorithm', APPLIED SCIENCES-BASEL, vol. 10, no. 3.
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Lim, WYB, Luong, NC, Hoang, DT, Jiao, Y, Liang, YC, Yang, Q, Niyato, D & Miao, C 2020, 'Federated Learning in Mobile Edge Networks: A Comprehensive Survey', IEEE Communications Surveys and Tutorials.
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IEEE In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications, e.g., for medical purposes and in vehicular networks. Traditional cloud-based Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, this results in critical issues related to unacceptable latency and communication inefficiency. To this end, Mobile Edge Computing (MEC) has been proposed to bring intelligence closer to the edge, where data is produced. However, conventional enabling technologies for ML at mobile edge networks still require personal data to be shared with external parties, e.g., edge servers. Recently, in light of increasingly stringent data privacy legislations and growing privacy concerns, the concept of Federated Learning (FL) has been introduced. In FL, end devices use their local data to train an ML model required by the server. The end devices then send the model updates rather than raw data to the server for aggregation. FL can serve as an enabling technology in mobile edge networks since it enables the collaborative training of an ML model and also enables DL for mobile edge network optimization. However, in a large-scale and complex mobile edge network, heterogeneous devices with varying constraints are involved. This raises challenges of communication costs, resource allocation, and privacy and security in the implementation of FL at scale. In this survey, we begin with an introduction to the background and fundamentals of FL. Then, we highlight the aforementioned challenges of FL implementation and review existing solutions. Furthermore, we present the applications of FL for mobile edge network optimization. Finally, we discuss the important challenges and future research directions in FL.

Lin, W & Ziolkowski, RW 2020, 'Electrically Small Huygens CP Rectenna With a Driven Loop Element Maximizes Its Wireless Power Transfer Efficiency', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 1, pp. 540-545.
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Liu, C, Zhu, L, He, X & Chen, J 2020, 'Enabling Privacy-Preserving Shortest Distance Queries on Encrypted Graph Data', IEEE Transactions on Dependable and Secure Computing.
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IEEE When coming to perform shortest distance queries on encrypted graph data outsourced in external storage infrastructure such as cloud, a significant challenge is how to compute the shortest distance in an accurate, efficient and secure way. This issue is addressed by a recent work, which makes use of somewhat homomorphic encryption (SWHE) to encrypt distance values output by a 2-hop cover labeling (2HCL) scheme. However, it may import large errors and even yield negative results. Besides, SWHE would be too time-consuming for normal clients. In this paper, we propose GENOA, a novel Graph ENcryption scheme for shOrtest distAnce queries. GENOA employs only efficient symmetric-key primitives while significantly enhances the accuracy compared to the prior work. As a reasonable trade-off, it additionally reveals the order information among queried distance values in the 2HCL index. We theoretically prove the accuracy and security of GENOA under rigorous cryptographic model. Detailed experiments on eight real-world graphs demonstrate that GENOA is efficient and can produce almost exact results.

Liu, F, Liu, Y, Han, F, Ban, Y-L & Guo, YJ 2020, 'Synthesis of Large Unequally Spaced Planar Arrays Utilizing Differential Evolution With New Encoding Mechanism and Cauchy Mutation', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 6, pp. 4406-4416.
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Liu, Y, Li, M, Haupt, RL & Guo, YJ 2020, 'Synthesizing Shaped Power Patterns for Linear and Planar Antenna Arrays Including Mutual Coupling by Refined Joint Rotation/Phase Optimization', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 6, pp. 4648-4657.
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Liu, Y, Wang, F, Lu, H, Fang, G, Wen, S, Chen, C, Shan, X, Xu, X, Zhang, L, Stenzel, M & Jin, D 2020, 'Super-Resolution Mapping of Single Nanoparticles inside Tumor Spheroids', SMALL, vol. 16, no. 6.
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Liu, Y, Yang, Y, Han, F, Liu, QH & Guo, YJ 2020, 'Improved Beam-Scannable Ultra-Wideband Sparse Antenna Arrays by Iterative Convex Optimization Based on Raised Power Series Representation', IEEE Transactions on Antennas and Propagation.
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IEEE A novel method is presented to design beam-scannable ultra-wideband (UWB) sparse arrays. A concept of design frequency is introduced which transforms the beam-scannable UWB array design to the problem of synthesizing a broadside-beam array at single-frequency. The raised power series (RPS) representation with appropriate parameter selection is adopted to generate initial element positions, and then an iterative convex optimization is applied to successively optimize the element positions for further sidelobe level (SLL) reduction. Multiple constraints for controlling the first-order Taylor expansion accuracy, the minimum element spacing and the array aperture are incorporated in the iterative convex optimization to obtain stable and practical synthesis results. Several examples for synthesizing UWB arrays with different frequency bands, beam scanning ranges and element counts, are conducted to validate the effectiveness and advantages of the proposed method. It is shown that the proposed method achieves much lower SLLs than those by the original RPS method for all test cases, and it also significantly outperforms some conventional stochastic optimization methods for large UWB array cases.

Liu, Y, Yang, Y, Wu, P, Ma, X, Li, M, Xu, KD & Guo, YJ 2020, 'Synthesis of Multibeam Sparse Circular-Arc Antenna Arrays Employing Refined Extended Alternating Convex Optimization', IEEE Transactions on Antennas and Propagation.
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IEEE A refined extended alternating convex optimization (REACO) method is presented to synthesize multibeam sparse circular-arc antenna arrays with minimum element spacing control by considering real antenna array structure characteristics. This method consists of initial step and a few refining steps. At the initial step, an initial array with dense elements distributed on a circular-arc is considered, and its array manifold vector is described by rotating a simulated isolated element pattern (IEP) without considering element mutual coupling. The collective excitation coefficient vector (CECV) and its energy bound are introduced for each element, and consequently the common element positions for generating desired multibeam patterns can be found by minimizing the number of active CECVs under multiple constraints. This minimization problem is further formulated as performing a sequence of alternating convex optimization (ACO) in which the CECV and an auxiliary weighting vector are alternately chosen as the optimization variables, so that the mimimum element spacing constraint can be easily dealt with. Once the initial optimization step is finished, a few refining steps are performed in which the element positions and excitations are successively updated in each step by renewing the array manifold vector through rotating the simulated nearby active element patterns (AEPs) of the antenna array obtained at the previous step. In such a way, the mutual coupling can be incorporated into the multibeam sparse array synthesis. An example of synthesizing a sparse circular-arc conformal array with 23 beams covering the space from–63.25° to 63.25° is conducted to validate the effectiveness and advantage of the proposed method.

Liu, Z, Zhang, L, Ni, W & Collings, IB 2020, 'Uncoordinated Pseudonym Changes for Privacy Preserving in Distributed Networks', IEEE Transactions on Mobile Computing, vol. 19, no. 6, pp. 1465-1477.
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© 2002-2012 IEEE. Pseudonyms have been adopted to preserve identity privacy of nodes in distributed networks. Frequent and unlinkable changes of pseudonyms need to be enabled by having at least $k$k nodes change together to confuse potential eavesdroppers. Existing approaches either depend on the coordination from central controllers, or involve interactive signaling between the nodes. This can potentially compromise privacy. This paper proposes a fully uncoordinated approach to change pseudonyms in distributed networks, where each node uses a pseudonym until its expiration and then changes after a random delay. We develop a new model to analyse the time-varying population of changing pseudonyms. Critical conditions are analytically established, under which individual nodes can independently change their pseudonyms while their identity privacy is preserved. The conditions are validated by illustrative examples. Corroborated by simulations, the accuracy of the analytical model improves, as the number of nodes increases. The analysis confirms that, the $k$k-anonymity can be achieved at a negligible throughput loss in the case of large networks.

Lu, Z, Geng, L, Huo, G, Zhao, H, Yao, W, Li, G, Guo, X & Zhang, J 2020, 'A novel hybrid multi-objective bacterial colony chemotaxis algorithm', Soft Computing, vol. 24, pp. 2013-2032.
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© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Abstract: In this article, a novel hybrid multi-objective bacterial colony chemotaxis (HMOBCC) algorithm is proposed to solve multi-objective optimization problems. A mechanism of particle swarm optimization is introduced to multi-objective bacterial colony chemotaxis (MOBCC) algorithm to improve the performance of MOBCC algorithm. Also, three other techniques, including dynamic reverse learning operator, external archive multiplying operator and adaptive diversity maintenance operator, are further applied to improve the diversity and convergence of the algorithm. The proposed algorithm is validated using 12 benchmark problems, and three performance measures are implemented for 5 benchmark problems to compare its performance with existing popular algorithms such as MOBCC, multi-objective bacterial colony chemotaxis based on grid algorithm, non-dominated sorting genetic algorithm (NSGA-II) and multi-objective evolutionary algorithm based on decomposition. The results show that the proposed HMOBCC is very effective against existing algorithms. Graphical abstract: The graphical abstract of this study.[Figure not available: see fulltext.].

Luo, Y, Canning, J, Zhang, J & Peng, GD 2020, 'Toward optical fibre fabrication using 3D printing technology', Optical Fiber Technology, vol. 58.
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© 2020 Elsevier Inc. 3D printing is a disruptive technology that could revolutionise the fabrication of optical fibre by offering greater flexibility and diversity in material and structure designs. This paper reviews the recent research and development of material and fabrication techniques toward 3D printing-based polymer optical fibre (POF) and silica optical fibre (SOF).

Luo, Y, Zhang, JA, Huang, X, Ni, W & Pan, J 2020, 'Multibeam Optimization for Joint Communication and Radio Sensing Using Analog Antenna Arrays', IEEE Transactions on Vehicular Technology, pp. 1-1.
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Lyu, B, Hoang, DT & Yang, Z 2020, 'Backscatter then Forward: A Relaying Scheme for Batteryless IoT Networks', IEEE Wireless Communications Letters.
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IEEE In this paper, we introduce a novel relaying scheme together with a joint energy beamforming (EB) and time allocation optimization to meet requirements about energy efficiency and hardware constraints of batteryless IoT networks. First, we propose an intelligent relaying scheme using RF-powered gateways as relay nodes to deliver information from batteryless IoT devices to a hybrid access point (HAP). The HAP can also transfer energy to the gateways and batteryless devices using EB techniques. The energy from HAP will be then used to supply power for gateways and as a communications means to transmit data for batteryless devices. We then formulate a sum-rate maximization problem by jointly optimizing the EB vectors, time scheduling, and power allocation. Since the optimization problem is non-convex, we exploit EB characteristics for data backscattering and employ variable substitutions and semidefinite relaxation techniques to transform it into a convex one. After that, a low-complexity method is proposed to obtain the optimal solution in a closed-form. Simulation results confirm that the proposed scheme can achieve significant sum-rate gain.

Ma, B, Zheng, J, Lei, G, Zhu, J, Jin, P & Guo, Y 2020, 'Topology Optimization of Ferromagnetic Components in Electrical Machines', IEEE Transactions on Energy Conversion.
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IEEE This paper presents the topology optimization of ferromagnetic components in electrical machines by using the density method. Explicit expressions of machine performance based on the principle of electromechanical energy conversion are derived and incorporated in the finite element model. Because the gradient-based algorithm is employed for efficient optimization, the performance sensitivities with respect to the design variables are derived subsequently. An optimization framework is then proposed to optimize effectively the electrical machine performance, such as the flux linkage, back electromotive force, torque profile including torque density and torque ripples. Two design examples are reported to confirm the feasibility and effectiveness of the presented topology optimization approach. The accuracy of optimal solutions is verified by using the commercial electromagnetic analysis software ANSYS MAXWELL.

Ma, B, Zheng, J, Zhu, J, Wu, J, Lei, G & Guo, Y 2020, 'Robust Design Optimization of Electrical Machines Considering Hybrid Random and Interval Uncertainties', IEEE Transactions on Energy Conversion, pp. 1-1.
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Mahamedi, B, Eskandari, M, Fletcher, JE & Zhu, J 2020, 'Sequence-Based Control Strategy with Current Limiting for the Fault Ride-Through of Inverter-Interfaced Distributed Generators', IEEE Transactions on Sustainable Energy.
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IEEE Three-phase three-leg inverters comprise the majority of inverters that are integrated into power grids. They can develop positive- and negative-sequence components under unbalanced conditions including asymmetrical faults, but not zero sequence. This indicates that a sequence-based control strategy is required for a comprehensive control of inverter currents and voltages, hence positive- and negative-sequence components must be controlled separately with their own dedicated controllers. Given this critical need, a sequence-based control technique for grid-forming and grid-feeding inverter-interfaced distributed generators (IIDG) is proposed. As a necessary part of the fault ride-through (FRT) capability of IIDGs, a current limiter is developed which can limit inverter currents at a pre-defined threshold for both balanced and unbalanced faults/voltage sags. Whilst the current regulators work in the synchronous reference frame with simple PI controllers, the limiter works in natural reference frame and thus treats each phase current separately, which results in current limiting at the threshold for all phases. The advantage of the proposed limiter is that it virtually acts instantaneously such that the inverter current can be limited from the start of the disturbance. The simulation results in MATLAB/SIMULINK reveal promising performance of the proposed control strategy with the proposed current limiting.

Mahmud, K, Rahman, MS, Ravishankar, J, Hossain, MJ & Guerrero, JM 2020, 'Real-Time Load and Ancillary Support for a Remote Island Power System Using Electric Boats', IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 1516-1528.
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© 2005-2012 IEEE. Powering small islands with reliable, affordable, and green electricity is a big challenge due to their dispersed geographical location with limited number of consumers and the heavy dependence on fossil fuels. This paper aims to address this challenge of reducing dependency on fossil fuel generators by providing an easy and feasible solution using available and accessible energy resources. The proposed method utilizes the bidirectional energy transfer mechanism available in electric boats (EBs) to support the consumers' power demand. It proposes a new real-time load-support (RTLS) system with a coordinated control using EBs, community generators, and battery energy storage systems. It analyzes the management of the intermittent source-dependent small-scale grid in real time, under various weather, load, and battery state-of-charge conditions. The RTLS system coordinates the customers' load demand with the available EBs, photovoltaics, and battery storage to provide efficient load support and to regulate the bus voltage and frequency. The efficacy of the proposed system is validated both computationally in a real network and in a laboratory setup. It is found that this novel system can substantially reduce the grid load demand and maintain the power quality under various load/source uncertainties and fault conditions. The system robustness is also evaluated considering undesirable conditions, such as severe three-phase faults and sudden EB disconnections. The performance of the proposed method is compared with that of the day-ahead load management approach to validate its effectiveness under various scenarios.

Mahmud, K, Ravishankar, J, Hossain, MJ & Dong, ZY 2020, 'The Impact of Prediction Errors in the Domestic Peak Power Demand Management', IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, vol. 16, no. 7, pp. 4567-4579.
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Makhdoom, I, Zhou, I, Abolhasan, M, Lipman, J & Ni, W 2020, 'PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities', COMPUTERS & SECURITY, vol. 88.
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Malik, N, Nanda, P, He, X & Liu, RP 2020, 'Vehicular networks with security and trust management solutions: proposed secured message exchange via blockchain technology', Wireless Networks, vol. 26, no. 6, pp. 4207-4226.
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© 2020, Springer Science+Business Media, LLC, part of Springer Nature. In vehicular ad hoc networks (VANET), effective trust establishment with authentication is an important requirement. Trust management among communicating vehicles is significant for secure message transmission; however, very less contributions have been made towards evaluating the trustworthiness of the node. This research work intends to introduce a new trust management system in VANET with two major phases: secured message transmission and node trustability prediction. The security assured message passing is carried out by incorporating the privacy preservation model under the data sanitization process. The key used for the sanitization process is optimally tuned by a new hybrid algorithm termed Sea Lion Explored-Whale Optimization Algorithm, which is the combination of Whale Optimization Algorithm and Sea Lion Optimization Algorithm, respectively. The blockchain technology is assisted to handle the key generated by the nodes. Subsequently, the trustability of the node is evaluated under novel specifics “two-level evaluation process” with a rule-based and machine learning-based evaluation process. Finally, the performance of the proposed model is verified and proved over other conventional methods for certain measures.

Marin, JG, Baba, AA, Hesselbarth, J, Hashmi, RM & Esselle, KP 2020, 'Millimeter-Wave Low-Loss Multifeed Superstrate-Based Antenna', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 5, pp. 3387-3396.
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Metia, S, Ha, QP, Duc, HN & Scorgie, Y 2020, 'Urban air pollution estimation using unscented Kalman filtered inverse modeling with scaled monitoring data', Sustainable Cities and Society, vol. 54.
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© 2019 The increasing rate of urbanization requires effective and reliable techniques for air quality monitoring and control. For this, the Air Pollution Model and Chemical Transport Model (TAPM-CTM) has been developed and used in Australia with emissions inventory data, synoptic data and terrain data used as its input parameters. Since large uncertainties exist in the emissions inventory (EI), further refinements and improvements are required for accurate air quality prediction. This study evaluates the performance of urban air quality forecasting, using TAPM-CTM, and improves accuracy of air pollution estimation by using a two-stage optimization technique to upgrade EI with validation from monitoring data. The first stage is based on statistical analysis for EI correction and the second stage is based on the unscented Kalman filter (UKF) to take into account the spatio-temporal distributions of air pollutant levels utilizing a Matérn covariance function. The predicted nitrogen monoxide (NO) and nitrogen dioxide (NO2) concentrations with a priori emissions are first compared with observations at monitoring stations in the New South Wales (NSW). Ozone (O3) is also considered since at the ground level it represents a major air pollutant affecting human health and the environment. In the second stage, with the improved EI, TAPM-CTM model errors are reduced further by using the UKF to calibrate EI. Results obtained show effectiveness of the proposed technique, which is promising for air quality inverse modeling, an important aspect of air pollution control in smart cities to achieve environmental sustainability.

Mhiesan, H, Wei, Y, Siwakoti, Y & Mantooth, A 2020, 'A Fault-Tolerant Hybrid Cascaded H-Bridge Multilevel Inverter', IEEE Transactions on Power Electronics, pp. 1-1.
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Namadmalan, A, Rouzbehi, K, Manuel Escano, J & Bordons, C 2020, 'Dual-Active Bridge Series Resonant Electric Vehicle Charger: A Self-Tuning Method', ELECTRONICS, vol. 9, no. 2.
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Nan, Y, Huang, X & Guo, YJ 2020, 'A Millimeter-Wave GCW-SAR Based on Deramp-on-Receive and Piecewise Constant Doppler Imaging', IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 1, pp. 680-690.
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© 2019 IEEE. A novel generalized continuous-wave synthetic aperture radar (GCW-SAR) based on deramp-on-receive operating in millimeter-wave frequency is proposed in this article. With deramp-on-receive, the receiver sampling rate is drastically reduced, and the downsampled 1-D raw data can be obtained from the received beat signal. Further adopting piecewise constant Doppler (PCD) imaging in the digital domain, a GCW-SAR image can be easily reconstructed by using the existing frequency-modulated continuous-wave (FMCW) radar system. The effects of deramp-on-receive in PCD imaging are analyzed accordingly. The short wavelength of the millimeter-wave carrier used in the proposed GCW-SAR enables high azimuth resolution as well as a short synthetic aperture, which, in turn, significantly reduces the imaging computational complexity. Simulation and experimental results confirm the advantages of the proposed GCW-SAR.

Nan, Y, Huang, X & Guo, YJ 2020, 'Piecewise Constant Doppler Algorithm: Performance Analysis, Further Simplification and Motion Compensation', IEEE Transactions on Aerospace and Electronic Systems.
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IEEE The piecewise constant Doppler (PCD) algorithm is a novel radar imaging process recently proposed for the generalized continuous wave synthetic aperture radar (GCW-SAR). This paper presents a detailed theoretical analysis on the PCD algorithm's performance and proposes a further complexityreduced PCD algorithm with motion compensation (MOCO) suitable for practical applications. Firstly, the difference between conventional SAR imaging and PCD imaging, i.e., the zeroth order versus the first order slant range approximation, is revealed. Exact ambiguity function expressions of the PCD imaging in range and azimuth directions respectively are then derived. An error function of the PCD imaging as compared with the ideal matched filtering method is further defined and shown to be a function of an image quality factor which can be used to quantify the PCD imaging performance. Finally, a faster and more flexible imaging process, called decimated PCD algorithm, is proposed, by which the image azimuth spacing can be easily extended and hence the computational complexity can be significantly reduced. The decimated PCD implementation incorporated with the MOCO is developed for practical GCWSAR applications and its imaging error lower-bounded by the PCD imaging error function is analyzed accordingly. Simulation and experimental results validate the theoretical analysis of the PCD imaging and show that the decimated PCD algorithm can achieve a high imaging quality at low cost.

Nasir, AA, Tuan, HD, Duong, TQ & Hanzo, L 2020, 'Transmitter-Side Wireless Information- and Power-Transfer in Massive MIMO Systems', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 69, no. 2, pp. 2322-2326.
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Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2020, 'MIMO-OFDM-Based Wireless-Powered Relaying Communication with an Energy Recycling Interface', IEEE Transactions on Communications, vol. 68, no. 2, pp. 811-824.
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© 2019 IEEE. This paper considers wireless-powered relaying multiple-input-multiple-output (MIMO) communication, where all four nodes (information source, energy source, relay, and destination) are equipped with multiple antennas. Orthogonal frequency division multiplexing (OFDM) is applied for information processing to compensate the frequency selectivity of communication channels between the information source and the relay and between the relay and the destination as these nodes are assumed to be located far apart from each. The relay is equipped with a full-duplexing interface for harvesting energy not only from the wireless transmission of the dedicated energy source but also from its own transmission while relaying the source information to the destination. The problem of designing the optimal power allocation over OFDM subcarriers and transmit antennas to maximize the overall spectral efficiency is addressed. Due to a very large number of subcarriers, this design problem poses a large-scale nonconvex optimization problem involving a few thousand variables of power allocation, which is very computationally challenging. A novel path-following algorithm is proposed for computation. Based on the developed closed-form calculation of linear computational complexity at each iteration, the proposed algorithm rapidly converges to an optimal solution. Compared to the best existing solvers, the computational complexity of the proposed algorithm is reduced at least 105 times, making it very efficient and practical for online computation while existing solvers are ineffective. Numerical results for a practical simulation setting show promising results by achieving high spectral efficiency.

Nasir, AA, Tuan, HD, Duong, TQ, Vincent Poor, H & Hanzo, L 2020, 'Hybrid Beamforming for Multi-User Millimeter-Wave Networks', IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 2943-2956.
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© 1967-2012 IEEE. This paper considers hybrid beamforming by combining an analog beamformer with a new regularized zero forcing baseband one, for multi-user millimeter-wave networks under a limited number of radio frequency (RF) chains. Three popular scenarios are examined: i) the number of users is up to the number of RF chains in a single-cell network, ii) the number of users is up to twice the number of RF chains in a single-cell network, and iii) the number of users is up to twice the number of RF chains in each cell of a two-cell network. In the second and third scenarios, we group the users into two categories of cell-center users as well as cell-edge users and serve them in two different time fractions. In the third scenario, we propose to suppress the inter-cell interference by serving the cell-center and cell-edge users in alternate fractional-time slots. In all the three scenarios, we determine the optimal power allocation maximizing the users' minimum rate. Finally, low-complexity path-following algorithms having rapid convergence are developed for the computation of the optimal power. Our simulation results show that the proposed algorithms achieve a clear performance gain over the existing benchmarkers.

Nguyen, HT, Tuan, HD, Duong, TQ, Poor, HV & Hwang, WJ 2020, 'Nonsmooth Optimization Algorithms for Multicast Beamforming in Content-Centric Fog Radio Access Networks', IEEE Transactions on Signal Processing, vol. 68, pp. 1455-1469.
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© 1991-2012 IEEE. This paper considers a content-centric fog radio access network (F-RAN). Its multi-antenna remote radio heads (RRHs) are capable of caching and executing signal processing for content delivery to its users. The fronthaul traffic is thus saved since its baseband processing unit (BBU) needs to transfer only the cache-missed content items to the RRHs via limited-capacity fronthaul links. The problem of beamforming design maximizing the energy efficiency in content delivery subject to the quality-of-content-service constraints in terms of content throughput and fronthaul limited-capacity is addressed. Unlike the user's throughput in user-centric networks, the content throughput in content-centric networks is no longer a differentiable function of the beamforming vectors. The problem is inherently high-dimensional due to the involvement of many beamforming vectors even in simple cases of three RRHs serving three users. Path-following algorithms, which invoke a simple convex quadratic optimization problem to generate a better feasible point, are proposed for computation of this nonsmooth and high-dimensional optimization problem. We also employ generalized zero-forcing beamforming, which forces the multi-content interference to zero or nearly to zero to reduce the problem dimensionality for computational efficiency. Numerical results are provided to demonstrate their computational effectiveness. They also reveal that when the fronthaul traffic becomes more flexible, hard-transfer fronthauling is more energy efficient than soft-transfer fronthauling.

Ni, Z, Zhang, A, Yang, K, Gao, F & An, J 2020, 'Low-complexity Subarray-based RF Precoding for Wideband Multiuser Millimeter Wave Systems', IEEE Transactions on Vehicular Technology, pp. 1-1.
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Ni, Z, Zhang, JA, Yang, K, Gao, F & An, J 2020, 'Estimation of Multiple Angle-of-Arrivals with Localized Hybrid Subarrays for Millimeter Wave Systems', IEEE Transactions on Communications, vol. 68, no. 3, pp. 1897-1910.
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IEEE Angle of Arrival (AoA) estimation with localized hybrid arrays is challenging in millimeter-wave (mmWave) communication systems. Most existing solutions quantize AoAs into limited values with relatively low accuracy. This paper presents a multi-AoA estimation scheme which is capable of estimating multiple AoAs from multiple users with low complexity. Specifically, we design a path filter via combining the received signals for each subarray. Each path filter enables a certain range of AoAs to pass through while suppressing the rest. Then we can use low-complexity cross-correlation operations to obtain continuous AoA estimates. Association of paths to users is further achieved by a follow-up pseudo-random codes based correlation operation. The scheme is first presented for a narrowband system and then extended to wideband with frequency selectivity. We also introduce new metrics and derive the lower bound of mean square error for evaluating the accuracy of AoA estimates, as conventional metrics face difficulties in the presence of multiple closely located AoAs. Extensive simulation results are provided and validate the effectiveness of the proposed multi-AoA estimation scheme.

Nizami, MSH, Hossain, MJ & Fernandez, E 2020, 'Multiagent-Based Transactive Energy Management Systems for Residential Buildings with Distributed Energy Resources', IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 1836-1847.
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© 2005-2012 IEEE. Proper management of building loads and distributed energy resources (DER) can offer grid assistance services in transactive energy (TE) frameworks besides providing cost savings for the consumer. However, most TE models require building loads and DER units to be managed by external entities (e.g., aggregators), and in some cases, consumers need to provide critical information related to their electricity demand and usage, which hampers their privacy. This article introduces a transactive energy management framework for the buildings in a residential neighborhood to address grid overloading and cost optimization of the buildings. The decentralized coordination for the energy management system is realized by using a multiagent system architecture, which provides the consumers with full decision-making authority and preserves their privacy. A new event-triggered transactive market algorithm is developed, where the buildings trade energy to maximize profits, while the regional grid operator procures energy-supply flexibility of active consumers to prevent transformer overloading. A two-stage energy management system is developed for the residential buildings that schedules building loads and DER units in day-ahead stage to minimize cost and inconveniences for the consumer while participating in the real-time transactive market to maximize profits. An optimal bidding model is developed for the buildings that incorporates the degradation of residential storage devices for energy trading. Case studies and analyses with actual Australian building data and electricity tariff structures indicate the efficacy of the proposed methodology for effective mitigation of transformer overloading at a negligible cost compared to transformer replacement cost. Results also indicate that the proposed system can provide 15-20% cost savings for the consumers while minimizing their inconveniences and degradation of storage devices.

Nizami, MSH, Hossain, MJ, Amin, BMR & Fernandez, E 2020, 'A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading', Applied Energy, vol. 261.
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© 2019 Elsevier Ltd Bi-directional electricity trading of demand response (DR) and transactive energy (TE) frameworks allows the traditionally passive end-users of electricity to play an active role in the local power balance of the grid. Appropriate building energy management systems (BEMSs), coupled with an optimized bidding strategy, can provide significant cost savings for prosumers (consumers with on-site power generation and/or storage facility) when they participate in such bi-directional trading. This paper presents a BEMS with an optimization-based scheduling and bidding strategy for small-scale residential prosumers to determine optimal day-ahead energy-quantity bids considering the expected cost of real-time imbalance trading under uncertainty. The proposed scheduling and bidding strategy is formulated as a stochastic bi-level minimization problem that determines the day-ahead energy-quantity bids by minimizing the energy cost in the upper level considering expected cost of uncertainty, whereas a number of lower-level sub-problems ensure optimal operation of building loads and distributed energy resources (DERs) for comfort reservation, minimization of consumers’ inconveniences and degradation of residential storage units. A modified decomposition method is used to reformulate the nonlinear bi-level problem as a mixed-integer linear programming (MILP) problem and solved using ‘of the shelf’ commercial software. The effectiveness of the proposed BEMS model is verified via case studies for a residential prosumer in Sydney, Australia with real measurement data for building energy demand. The efficacy of the proposed method for overall financial savings is also validated by comparing its performance with state-of-the-art day-ahead scheduling strategies. Case studies indicate that the proposed method can provide up to 51% and 22% cost savings compared to inflexible non-optimal scheduling strategies and deterministic optimization-based methods respectively. ...

Pei, T, Li, L, Zhang, J & Hao, X 2020, 'Module block fault locating strategy for large-scale photovoltaic arrays', ENERGY CONVERSION AND MANAGEMENT, vol. 214.
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Pei, T, Zhang, J, Li, L & Hao, X 2020, 'A fault locating method for PV arrays based on improved voltage sensor placement', Solar Energy, vol. 201, pp. 279-297.
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© 2020 International Solar Energy Society Solar photovoltaic (PV) power generation has been widely used because of its environment-friendly advantages. However, operational faults in PV arrays have always been one of the critical factors affecting the PV system's power-generation efficiency and life cycle. This paper proposes a fault locating strategy, which does not need the current sensor in every PV string and can also minimize the number of voltage sensors between strings, to accurately locate the faulty PV modules in a PV array. A variety of faults including open circuit, short circuit, degradation and partial shading faults are considered, and a universal method is proposed in this paper to locate the faulty modules under these faults. In this method, the voltage sensors are deployed through differentiating the parity of the number of strings for the PV array, while the fault locating rules are formulated under each of the afore-mentioned faults, respectively. Compared with existing fault locating methods, the proposed locating technique is shown to be effective in the application to PV arrays with any size and capacity, and it can accurately locate each faulty module for those faults, especially for degradation and partial shading faults. Thus, it is helpful in PV array dynamic reconfiguration and maintenance cost reduction.

Pekka, A, da Silva Cruz, LA, da Silva, EAB, Ebrahimi, T, Freitas, PG, Gilles, A, Oh, K-J, Pagliari, C, Pereira, F, Perra, C, Perry, S, Pinheiro, AMG, Schelkens, P, Seidel, I & Tabus, I 2020, 'JPEG PLENO: STANDARDIZING A CODING FRAMEWORK AND TOOLS FOR PLENOPTIC IMAGING MODALITIES', ITU Journal: ICT Discoveries, vol. 3, no. 1, pp. 1-1.
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JPEG Pleno is an upcoming standard from the ISO/IEC JTC 1/SC 29/WG 1 (JPEG) Committee. It aims to provide a standard framework for coding new imaging modalities derived from representations inspired by the plenoptic function. The image modalities addressed by the current standardization activities are light field, holography, and point clouds, where these image modalities describe different sampled representations of the plenoptic function. The applications that may benefit from these emerging image modalities range from supporting varying capture platforms, interactive content viewing, cultural environments exploration and medical imaging to more immersive browsing with novel special effects and more realistic images. These use cases come with a set of requirements addressed by the JPEG Pleno standard. Main requirements envision high compression efficiency, random access, scalability, error-resilience, low complexity, and metadata support. This paper presents a synopsis of the status of the standardization process and provides technical insights as well as the latest performance evaluation results.

Pham, M, Hoang, DB & Chaczko, Z 2020, 'Congestion-Aware and Energy-Aware Virtual Network Embedding', IEEE/ACM Transactions on Networking, pp. 1-14.
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Poostchi, H & Piccardi, M 2020, 'BiLSTM-SSVM: Training the BiLSTM with a Structured Hinge Loss for Named-Entity Recognition', IEEE Transactions on Big Data, pp. 1-1.
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Pradeepkumar, A, Amjadipour, M, Mishra, N, Liu, C, Fuhrer, MS, Bendavid, A, Isa, F, Zielinski, M, Sirikumara, HI, Jayasekara, T, Gaskill, DK & Iacopi, F 2020, 'p-Type Epitaxial Graphene on Cubic Silicon Carbide on Silicon for Integrated Silicon Technologies', ACS APPLIED NANO MATERIALS, vol. 3, no. 1, pp. 830-841.
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Qadri, YA, Nauman, A, Zikria, YB, Vasilakos, AV & Kim, SW 2020, 'The Future of Healthcare Internet of Things: A Survey of Emerging Technologies', IEEE Communications Surveys and Tutorials, vol. 22, no. 2, pp. 1121-1167.
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© 1998-2012 IEEE. The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop platforms, both at the hardware level as well as the underlying software level. This vision has led to the development of Healthcare IoT (H-IoT) systems. The basic enabling technologies include the communication systems between the sensing nodes and the processors; and the processing algorithms for generating an output from the data collected by the sensors. However, at present, these enabling technologies are also supported by several new technologies. The use of Artificial Intelligence (AI) has transformed the H-IoT systems at almost every level. The fog/edge paradigm is bringing the computing power close to the deployed network and hence mitigating many challenges in the process. While the big data allows handling an enormous amount of data. Additionally, the Software Defined Networks (SDNs) bring flexibility to the system while the blockchains are finding the most novel use cases in H-IoT systems. The Internet of Nano Things (IoNT) and Tactile Internet (TI) are driving the innovation in the H-IoT applications. This paper delves into the ways these technologies are transforming the H-IoT systems and also identifies the future course for improving the Quality of Service (QoS) using these new technologies.

Qin, C, Andrew Zhang, J, Huang, X & Jay Guo, Y 2020, 'Virtual-Subarray-Based Angle-of-Arrival Estimation in Analog Antenna Arrays', IEEE Wireless Communications Letters, vol. 9, no. 2, pp. 194-197.
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© 2012 IEEE. Angle-of-arrival (AoA) estimation is a challenging problem for analog antenna arrays. Typical algorithms are based on beam scanning which can be time-consuming. In this letter, we propose a virtual-subarray based recursive AoA estimation scheme that can get an AoA estimate from every two measurements and recursively improve the performance by updating beamforming weights with soft probability-based information. Simulation results validate the high efficiency of the proposed scheme, demonstrating its superiority for initial AoA estimation in analog arrays.

Qin, C, Zhang, JA, Huang, X, Wu, K & Guo, YJ 2020, 'Fast Angle-of-Arrival Estimation via Virtual Subarrays in Analog Antenna Array', IEEE Transactions on Wireless Communications, pp. 1-1.
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Quang, PH, Metia, S & Manh, DP 2020, 'Sensing Data Fusion for Enhanced Indoor Air Quality Monitoring', IEEE SENSORS JOURNAL, vol. 20, no. 8, pp. 4430-4441.
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Rafi, FHM, Hossain, MJ, Rahman, MS & Taghizadeh, S 2020, 'An overview of unbalance compensation techniques using power electronic converters for active distribution systems with renewable generation', RENEWABLE & SUSTAINABLE ENERGY REVIEWS, vol. 125.
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Rahman, ML, Zhang, JA, Huang, X, Guo, YJ & Heath Jr, RW 2020, 'Framework for a Perceptive Mobile Network using Joint Communication and Radar Sensing', IEEE Transactions on Aerospace and Electronic Systems, pp. 1-1.
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Rahman, MS, Hossain, MJ, Lu, J, Rafi, FHM & Mishra, S 2020, 'A Vehicle-to-Microgrid Framework with Optimization-Incorporated Distributed EV Coordination for a Commercial Neighborhood', IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 1788-1798.
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© 2005-2012 IEEE. In this paper, an improved vehicle-to-microgrid (V2M) framework is proposed for a commercial locality operating as a hybrid ac-dc microgrid, which optimally coordinates electric-vehicle (EV) storages in a distributed manner. An aggregator model is proposed that solves the economic dispatch problem of parked EV storages in a centralized fashion and generates power references in real time for the designed EV storage controllers. Unlike the conventional EV storage controller, the proposed optimization-incorporated distributed EV storage controller can switch from decentralized to distributed control mode or vice versa based on situations and utilizes a sparse vehicle-to-vehicle communication network. The power flow between the ac and dc subgrids is managed by interlinking converters (IC). The IC control structure is augmented by combining voltage-and power-based droop-control schemes in the power control loop. This modification enables simultaneous ac and dc bus voltage regulations. Case studies are carried out to validate the efficacy of the developed framework with a real commercial network and loads. The results exhibit robust performance of the overall system for generation-demand variability, transitions between islanded and grid-tied conditions, and user-preferred EV disconnections and time delay.

Rajabi, A, Eskandari, M, Ghadi, MJ, Li, L, Zhang, J & Siano, P 2020, 'A comparative study of clustering techniques for electrical load pattern segmentation', Renewable and Sustainable Energy Reviews.
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© 2019 Elsevier Ltd Smart meters have been widely deployed in power networks since the last decade. This trend has resulted in an enormous volume of data being collected from the electricity customers. To gain benefits for various stakeholders in power systems, proper data mining techniques, such as clustering, need to be employed to extract the underlying patterns from energy consumptions. In this paper, a comparative study of different techniques for load pattern clustering is carried out. Different parameters of the methods that affect the clustering results are evaluated and the clustering algorithms are compared for two data sets. In addition, the two suitable and commonly used data size reduction techniques and feature definition/extraction methods for load pattern clustering are analysed. Furthermore, the existing studies on clustering of electricity customers are reviewed and the main results are highlighted. Finally, the future trends and major applications of clustering consumption patterns are outlined to inform industry practitioners and academic researchers to optimize smart meter operational use and effectiveness.

Rakhshani, E, Rouzbehi, K, Escano, JM & Torres, J 2020, 'Optimal Linear Control of Modular Multi-Level Converters with a Prescribed Degree of Stability', ELECTRIC POWER COMPONENTS AND SYSTEMS, vol. 48, no. 1-2, pp. 30-41.
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Raza, A, Younis, M, Liu, Y, Altalbe, A, Rouzbehi, K & Abbas, G 2020, 'A Multi-Terminal HVdc Grid Topology Proposal for Offshore Wind Farms', APPLIED SCIENCES-BASEL, vol. 10, no. 5.
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Ren, C, Lyu, X, Ni, W, Tian, H, Song, W & Liu, RP 2020, 'Distributed online optimization of fog computing for internet of things under finite device buffers', IEEE Internet of Things Journal, vol. 7, no. 6, pp. 5434-5448.
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© 2014 IEEE. Lyapunov optimization has shown to be effective for online optimization of fog computing, asymptotically approaching the optimality only achievable offline. However, it is not directly applicable to the Internet of Things, as inexpensive sensors have small buffers and cannot generate sufficient backlogs to activate the optimization. This article proposes an enabling technique for the Lyapunov optimization to operate under finite buffers without loss of asymptotic optimality. This is achieved by optimizing the biases (namely, 'virtual placeholders') of the buffers to create sufficient backlogs. The optimization of the placeholders is proved to be a new three-layer shortest path problem and solved in a distributed manner by extending the Bellman-Ford algorithm. The sizes of the virtual placeholders decline fastest along the shortest paths from the sensors to the data center, thereby preventing unnecessary detours and reducing end-to-end delays. Corroborated by simulations, the proposed approach is able to operate under the conditions the direct application of the Lyapunov optimization fails, and significantly increase the throughput and reduce the delays in other cases.

Romero, E, Valenzuela, VM, Kermany, AR, Sementilli, L, Iacopi, F & Bowen, WP 2020, 'Engineering the Dissipation of Crystalline Micromechanical Resonators', PHYSICAL REVIEW APPLIED, vol. 13, no. 4.
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Saki, M, Abolhasan, M & Lipman, J 2020, 'A Novel Approach for Big Data Classification and Transportation in Rail Networks', IEEE Transactions on Intelligent Transportation Systems, pp. 1-11.
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Santra, SB, Chatterjee, D, Siwakoti, YP & Blaabjerg, F 2020, 'Generalized Switch Current Stress Reduction Technique for Coupled- Inductor based Single Switch High Step-Up Boost Converter', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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Saputra, Y, Dinh, H, Nguyen, D & Dutkiewicz, E 2020, 'A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation', IEEE Transactions on Mobile Computing.
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Mobile edge caching/computing has been emerging as a promising paradigm to provide new services (e.g., ultra-high rate, ultra-reliable, and/or low-latency communications) in future wireless networks. In this paper, we introduce a novel mobile edge caching network architecture that leverages the optimal joint caching-delivering with horizontal cooperation among mobile edge nodes (MENs), namely JOCAD. Under this architecture, MENs cooperate with each other in both caching and delivering contents, aiming to simultaneously minimize the total average delay for the mobile users and mitigate the network traffic on the backhaul link. Extensive simulations demonstrate that the proposed solutions can reduce the total average delay for the whole network up to 40% compared with the most frequency-of-access policy, and up to 25% compared with locally optimal caching policy (i.e., without collaboration). Furthermore, the proposed solutions also increase the cache hit ratio for the network up to 4 times, thereby dramatically reducing the traffic load on the backhaul network.

Sathik, MJ, Bhatnagar, K, Siwakoti, YP, Bassi, HM, Rawa, M, Sandeep, N, Yang, Y & Blaabjerg, F 2020, 'Switched-capacitor multilevel inverter with self-voltage-balancing for high-frequency power distribution system', IET Power Electronics.
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Sayem, ASM, Simorangkir, RBVB, Esselle, KP, Hashmi, RM & Liu, H 2020, 'A Method to Develop Flexible Robust Optically Transparent Unidirectional Antennas Utilizing Pure Water, PDMS and Transparent Conductive Mesh', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Shan, Y, Hu, J, Liu, M, Zhu, J & Guerrero, JM 2020, 'Model Predictive Voltage and Power Control of Islanded PV-Battery Microgrids With Washout-Filter-Based Power Sharing Strategy', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 2, pp. 1227-1238.
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Shi, X, Zhu, J, Li, L & Lu, DD-C 2020, 'Low-Complexity Dual-Vector-Based Predictive Control of Three-Phase PWM Rectifiers Without Duty-Cycle Optimization', IEEE ACCESS, vol. 8, pp. 77049-77059.
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Shi, Y, Hoang, DT, Duong, TQ, Poor, HV & Savkin, A 2020, 'PMU Placement Optimization for Efficient State Estimation in Smart Grid', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 38, no. 1, pp. 71-83.
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Shi, Y, Tuan, HD & Apkarian, P 2020, 'Parameterized bilinear matrix inequality techniques for Script capital H infinity gain-scheduling proportional integral derivative control design', INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL.
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Shi, Z, Pan, Q & Xu, M 2020, 'LSTM-Cubic A * -based auxiliary decision support system in air traffic management', NEUROCOMPUTING, vol. 391, pp. 167-176.

Shi, Z, Sun, X, Lei, G, Yang, Z, Guo, Y & Zhu, J 2020, 'Analysis and Optimization of Radial Force of Permanent-Magnet Synchronous Hub Motors', IEEE TRANSACTIONS ON MAGNETICS, vol. 56, no. 2.
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Singh, K, Afzal, MU, Kovaleva, M & Esselle, KP 2020, 'Controlling the Most Significant Grating Lobes in Two-Dimensional Beam-Steering Systems With Phase-Gradient Metasurfaces', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 3, pp. 1389-1401.
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Song, B, Wang, X, Ni, W, Song, Y, Liu, RP, Jiang, GP & Guo, YJ 2020, 'Reliability Analysis of Large-Scale Adaptive Weighted Networks', IEEE Transactions on Information Forensics and Security, vol. 15, pp. 651-665.
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© 2005-2012 IEEE. Disconnecting impaired or suspicious nodes and rewiring to those reliable, adaptive networks have the potential to inhibit cascading failures, such as DDoS attack and computer virus. The weights of disconnected links, indicating the workload of the links, can be transferred or redistributed to newly connected links to maintain network operations. Distinctively different from existing studies focused on adaptive unweighted networks, this paper presents a new mean-field model to analyze the reliability of adaptive weighted networks against cascading failures. By taking mean-field approximation, we develop a new continuous-time Markov model to capture the propagations of cascading failures and the rewiring actions that individual nodes can take to bypass failed neighbors. We analyze the stability of the model to identify the critical conditions, under which the cascading failures can be eventually inhibited or would proliferate. The conditions are evaluated under different link weight distributions and rewiring strategies. Our model reveals that preferentially disconnecting suspicious peers with high weights can effectively inhibit virus and failures.

Soon, JL, Lu, DDC, Peng, JCH & Xiao, W 2020, 'Reconfigurable Nonisolated DC-DC Converter with Fault-Tolerant Capability', IEEE Transactions on Power Electronics, vol. 35, no. 9, pp. 8934-8943.
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© 1986-2012 IEEE. Malfunction of power semiconductor switches is the dominant cause of failure in power electronic converters. This article proposes a novel dual-switch dc-dc topology for high-reliability applications. The proposed converter is fault tolerant and supports operation under both step-down and step-up modes. The proposed topology can be reconfigured automatically under various switch-fault conditions in order to maintain normal operation. This is enabled by an affine-parametrization-based control design, which minimizes the transient impact of the faults. The reliability performance of the proposed converter is evaluated theoretically using a Markov model, demonstrating its superiority over conventional topologies. Finally, a laboratory prototype is developed and tested to verify the proposed design and control performance under switch faults.

Sornalingam, K, McDonagh, A, Canning, J, Cook, K, Johir, MAH, Zhou, JL & Ahmed, MB 2020, 'Photocatalysis of 17 alpha-ethynylestradiol and estriol in water using engineered immersible optical fibres and light emitting diodes', JOURNAL OF WATER PROCESS ENGINEERING, vol. 33.
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Sun, F, Gomez-Garcia, R, Zhu, X, Zhu, H, Yang, Y & Tong, X 2020, 'Miniaturised millimetre-wave BPF with broad stopband suppression in silicon-germanium technology', IET MICROWAVES ANTENNAS & PROPAGATION, vol. 14, no. 4, pp. 308-313.
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Sun, H-H, Ding, C, Zhu, H & Guo, YJ 2020, 'Dual-Polarized Multi-Resonance Antennas With Broad Bandwidths and Compact Sizes for Base Station Applications', IEEE Open Journal of Antennas and Propagation, vol. 1, pp. 11-19.
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Sun, Q, Ban, YL, Lian, JW, Liu, Y & Nie, Z 2020, 'Millimeter-Wave Multibeam Antenna Based on Folded C-Type SIW', IEEE Transactions on Antennas and Propagation, vol. 68, no. 5, pp. 3465-3476.
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© 1963-2012 IEEE. A millimeter-wave (mm-wave) multibeam array antenna based on folded C-type substrate integrated waveguide (FCSIW) is presented for the first time. The design steps for its two main elements are described, namely an FCSIW Butler matrix (BM) and an FCSIW single-branch slot array antenna. Both of them exhibit a significant miniaturization in comparison with their substrate integrated waveguide (SIW) counterparts, leading to 40% and 33.2% reduction in occupied surface for the BM and the whole multibeam array antenna while maintaining similar performances, respectively. In addition, an optimized transition connection structure from ground coplanar waveguide (GCPW) to FCSIW is designed to facilitate the measurement of the multibeam array antenna. Finally, the FCSIW multibeam array antenna is optimized, manufactured, and measured, which can help verify the feasibility of FCSIW for the miniaturized multibeam array antenna.

Sun, X, Cao, J, Lei, G, Guo, Y & Zhu, J 2020, 'Speed Sensorless Control for Permanent Magnet Synchronous Motors Based on Finite Position Set', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 7, pp. 6089-6100.
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Sun, X, Diao, K, Lei, G, Guo, Y & Zhu, J 2020, 'Real-Time HIL Emulation for a Segmented-Rotor Switched Reluctance Motor Using a New Magnetic Equivalent Circuit', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 4, pp. 3841-3849.
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Sun, X, Diao, K, Yang, Z, Lei, G, Guo, Y & Zhu, J 2020, 'Direct Torque Control Based on a Fast Modeling Method for a Segmented-Rotor Switched Reluctance Motor in HEV Application', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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Sun, X, Hu, C, Lei, G, Guo, Y & Zhu, J 2020, 'State Feedback Control for a PM Hub Motor Based on Gray Wolf Optimization Algorithm', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 1, pp. 1136-1146.
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Sun, X, Hu, C, Lei, G, Yang, Z, Guo, Y & Zhu, J 2020, 'Speed Sensorless Control of SPMSM Drives for EVs with a Binary Search Algorithm-Based Phase-Locked Loop', IEEE Transactions on Vehicular Technology, vol. 69, no. 5, pp. 4968-4978.
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© 1967-2012 IEEE. This article presents a new method to extract accurate rotor position for the speed sensorless control of surface-mounted permanent-magnet synchronous motors (SPMSMs), based on the back electromotive force (EMF) information. The concept of finite control set-model predictive control is employed, and its cost function is related to the back EMF. An optimal voltage vector is selected from several given voltage vectors by comparing their fitness values. Moreover, the position space is divided into four sectors, and the fitness of each sector boundary is calculated and compared. The rotor position is first located in the sector surrounded by two boundaries that minimize the cost function. Then the selected sector is split into two parts, and the binary search algorithm is applied to reduce the sector area to improve the accuracy of position estimation. To overcome the drawback of the back EMF-based sensorless scheme, an I-f startup method is employed to accelerate the motor to the desired speed. An experiment has been carried out to compare the performance of the proposed method and the conventional phase-locked loop (PLL) in terms of steady-state and transient conditions.

Sun, X, Shi, Z, Lei, G, Guo, Y & Zhu, J 2020, 'Multi-objective Design Optimization of an IPMSM Based on Multilevel Strategy', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Sun, X, Wu, M, Lei, G, Guo, Y & Zhu, J 2020, 'An Improved Model Predictive Current Control for PMSM Drives Based on Current Track Circle', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Sun, X, Wu, M, Yang, Z, Lei, G & Guo, Y 2020, 'High-performance control for a permanent-magnet linear synchronous generator using state feedback control scheme plus grey wolf optimisation', IET ELECTRIC POWER APPLICATIONS, vol. 14, no. 5, pp. 771-780.
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Sutton, GJ, Liu, RP & Guo, YJ 2020, 'Coexistence performance and limits of frame-based listen-before-talk', IEEE Transactions on Mobile Computing, vol. 19, no. 5, pp. 1084-1095.
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© 2002-2012 IEEE. Frame-based listen-before-talk (FB-LBT) has been adopted as one of the channel access mechanism for Wi-Fi/LTE coexistence. We aim to explore the limits of FB-LBT by developing theoretical models to characterize the FB-LBT channel access performance under the coexistence of LTE and Wi-Fi. We first derive a steady-state model to calculate the spectrum share occupied by LTE under the assumption that the Wi-Fi transmissions have stationary distributions. The assumption does not hold when the time between two LTE transmissions is short, where the system is dominated by a dynamic phenomenon. A second model is developed that accounts for the dynamics of the Wi-Fi channel access mechanism. Our models, validated by simulation results, accurately calculate the spectrum share occupied by LTE over a range of FB-LBT frame periods and Wi-Fi traffic loads. We obtain upper bounds on the FB-LBT spectrum share when competing with heavy Wi-Fi traffic, which confirm the weakness of FB-LBT. Moreover, we demonstrate that our models can be used to control the FB-LBT spectrum share within a modest range.

Takalkar, MA, Xu, M & Chaczko, Z 2020, 'Manifold feature integration for micro-expression recognition', MULTIMEDIA SYSTEMS.
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Talebian, H, Gani, A, Sookhak, M, Abdelatif, AA, Yousafzai, A, Vasilakos, AV & Yu, FR 2020, 'Optimizing virtual machine placement in IaaS data centers: taxonomy, review and open issues', Cluster Computing.
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. The unprecedented growth of energy consumption in data centers created critical concern in recent years for both the research community and industry. Besides its direct associated cost; high energy consumption also results in a large amount of CO2 emission and incurs extra cooling expenditure. The foremost reason for overly energy consumption is the underutilization of data center resources. In modern data centers, virtualization provides a promising approach to improve the hardware utilization level. Virtual machine placement is a process of mapping a group of virtual machines (VMs) onto a set of physical machines (PMs) in a data center with the aim of maximizing resource utilization and minimizing the total power consumption by PMs. An optimal virtual machine placement algorithm substantially contributes to cutting down the power consumption through assigning the input VMs to a minimum number of PMs and allowing the dispensable PMs to be turned off. However, VM Placement Problem is a complex combinatorial optimization problem and known to be NP-Hard problem. This paper presents an extensive review of virtual machine placement problem along with an overview of different approaches for solving virtual machine placement problem. The aim of this paper is to illuminate challenges and issues for current virtual machine placement techniques. Furthermore, we present a taxonomy of virtual machine placement based on various aspects such as methodology, number of objectives, operation mode, problem objectives, resource demand type and number of clouds. The state-of-the-art VM Placement techniques are classified in single objectives and multi-objective groups and a number of prominent works are reviewed in each group. Eventually, some open issues and future trends are discussed which serve as a platform for future research work in this domain.

Tang, MC, Chen, Y, Chen, X, Mu, D & Ziolkowski, RW 2020, 'Design and Testing of a Simple, Compact Antenna with Reconfigurable Broadside and Monopole-Like Patterns', IEEE Antennas and Wireless Propagation Letters, vol. 19, no. 6, pp. 897-901.
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© 2002-2011 IEEE. A compact antenna with broadside and monopole-like pattern reconfigurability is presented. Its radiating elements are linearly polarized and consists of a magnetic dipole and an electric monopole. A capacitively loaded loop and two rectangular strips, one driven and one parasitic, serve as a magnetic near-field resonant parasitic radiator. The broadside pattern is generated by the magnetic radiator; the electric monopole radiates the monopole-like pattern. A coax-fed structure is developed with only two p-i-n diodes integrated into it that dynamically controls the excitation of either the magnetic or the electric radiator. A prototype was fabricated and tested. The measured results are in reasonable agreement with their simulated ones. The antenna is impedance matched within an overlapping operational fractional bandwidth of 3.8%; the combination of its radiating elements is compact with karad = 0.69. The realized gain value of the broadside pattern at boresight is 7.1 dBi and the null of the monopole-like pattern is over -28 dBi deep. The prototype is an attractive candidate for applications in many space-limited wireless systems that require reconfigurable broadside and monopole-like performance characteristics.

Tang, Q, Yang, J, Jia, W, He, X, Zhang, Q & Liu, H 2020, 'A GMS-Guided Approach for 2D Feature Correspondence Selection', IEEE ACCESS, vol. 8, pp. 36919-36929.
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Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2020, 'Crowd Estimation Using Electromagnetic Wave Power-Level Measurements: A Proof of Concept', IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 784-792.
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Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2020, 'Polarization-Insensitive Metamaterial Absorber for Crowd Estimation Based on Electromagnetic Energy Measurements', IEEE Transactions on Antennas and Propagation, vol. 68, no. 3, pp. 1458-1467.
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© 2020 IEEE. Noninvasive crowd estimation has remained a challenging issue among researchers. Methods such as image analysis and Wi-Fi/Bluetooth probing can always be used to identify and track people. Lately, authors have introduced a noninvasive method for crowd estimation based on ambient RF energy measurements. In this article, a polarization-insensitive multilayer metamaterial absorber is introduced to measure the variation in the available RF energy levels for crowd estimation purposes. The proposed dual-band absorber is designed to absorb and transfer the maximum of the available Wi-Fi energy to a lumped element to enable proper and accurate measurements. To evaluate the design, the proposed structure is fabricated as an array, and its performance is tested, proving perfect absorption at the desired frequencies, 2.4 and 5 GHz.

Tran, T & Ha, QP 2020, 'Semi-automatic control of network systems with non-monotonic Lyapunov function', International Journal of Control.
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© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. A partially decentralised scheme for the semi-automatic control of network systems with stabilising agents is presented in this paper. The semi-automatic control of interconnected systems employing the stabilising agent whose installation is segregated from the associated control algorithm has been presented previously. In this development, the quadratic dissipativity constraint (QDC) associated with a non-negative supply rate is newly introduced for the stabilising agent. The closed-loop system having bounded disturbances is input-to-state stabilised with a non-monotonic Lyapunov function when the QDC is used with model predictive controllers. The effectiveness of the QDC for stabilising agents in the presented partially decentralised architecture is demonstrated via simulation studies of a frequency regulation problem in power systems.

Trede, F, Braun, R & Brookes, W 2020, 'Engineering students’ expectations and perceptions of studio-based learning', European Journal of Engineering Education.
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© 2020, © 2020 SEFI. Studio-based learning is gaining currency in university engineering education programmes. It is widely argued that this practice-oriented, collaborative approach to developing professional, teamwork and interpersonal skills is needed to prepare the future workforce. In this paper, students’ expectations and perceptions of a first-year studio were explored. Data collection included baseline and follow-up interviews. Both included the rich picture method and photo-elicitation. Using critical hermeneutics interpretation, we identified three key themes: teamwork, leadership and reflection. Although studio-based learning was perceived as effortful, slow and at times even frustrating, the move away from didactic lecturing by experts to collaborative learning and building products was welcomed and endorsed by all our participants. The insight gained from this study suggests that more innovative learning and teaching approaches in engineering education may help prepare students for lifelong learning in an uncertain future world of work.

Usman, M, Jan, MA, He, X & Chen, J 2020, 'A Mobile Multimedia Data Collection Scheme for Secured Wireless Multimedia Sensor Networks', IEEE Transactions on Network Science and Engineering.
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IEEE Wireless Multimedia Sensor Networks (WMSNs) produce an enormous amount of big multimedia data. Due to large size, Multimedia Sensor Nodes (MSNs) cannot store generated multimedia data for a long time. In this scenario, mobile sinks can be utilized for data collection. However, due to vulnerable nature of wireless networks, there is a need for an efficient security scheme to authenticate both MSNs and mobile sinks. In this paper, we propose a scheme to protect an underlying WMSN during mobile multimedia data collection. The proposed scheme is a two-layer scheme. At the first layer, all MSNs are distributed into small clusters, where each cluster is represented by a single Cluster Head (CH). At the second layer, all CHs verify identities of mobile sinks before sharing multimedia data. Authentication at both layers ensures a secure data exchange. We evaluate the performance of proposed scheme through extensive simulation results. The simulation results prove that the proposed scheme performs better as compared to existing state-of-the-art approaches in terms of resilience and handshake duration. The proposed scheme is also analyzed in terms of authentication rate, data freshness, and packet delivery ratio, and has shown a better performance.

Usman, M, Jan, MA, He, X & Nanda, P 2020, 'QASEC: A secured data communication scheme for mobile Ad-hoc networks', Future Generation Computer Systems.
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© 2018 Elsevier B.V. Mobile Adhoc NETworks (MANETs) are valuable for various applications due to an efficient, flexible, low-cost and dynamic infrastructure. In these networks, proper utilization of network resources is desirable to maintain Quality of Service (QoS). In multi-hop end-to-end communication, intermediate nodes may eavesdrop on data in transit. As a result, a secured and reliable data delivery from source to destination is required. In this paper, we propose a novel scheme, known as QASEC, to achieve better throughput by securing end-to-end communication in MANETs. The QoS is maintained through an optimal link selection from a queue of available transmission links. The end-to-end communication is secured by authentication. A simple secret-key based symmetric encryption is deployed for interacting nodes. Our proposed QASEC scheme prevents the malicious nodes from data exchange with legitimate intermediate nodes on any established path between the source and the destination. Experimental results show that QASEC performs better in terms of packet-loss rate, jitter and end-to-end delay. Furthermore, QASEC is efficient against various attacks and has a much better performance in terms of associated costs, such as key generation, encryption, and storage and communication.

Usman, M, Jan, MA, Jolfaei, A, Xu, M, He, X & Chen, J 2020, 'A Distributed and Anonymous Data Collection Framework Based on Multilevel Edge Computing Architecture', IEEE Transactions on Industrial Informatics, vol. 16, no. 9, pp. 6114-6123.
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© 2005-2012 IEEE. Industrial Internet of Things applications demand trustworthiness in terms of quality of service (QoS), security, and privacy, to support the smooth transmission of data. To address these challenges, in this article, we propose a distributed and anonymous data collection (DaaC) framework based on a multilevel edge computing architecture. This framework distributes captured data among multiple level-one edge devices (LOEDs) to improve the QoS and minimize packet drop and end-to-end delay. Mobile sinks are used to collect data from LOEDs and upload to cloud servers. Before data collection, the mobile sinks are registered with a level-two edge-device to protect the underlying network. The privacy of mobile sinks is preserved through group-based signed data collection requests. Experimental results show that our proposed framework improves QoS through distributed data transmission. It also helps in protecting the underlying network through a registration scheme and preserves the privacy of mobile sinks through group-based data collection requests.

Vazquez, S, Acuna, P, Aguilera, RP, Pou, J, Leon, JI & Franquelo, LG 2020, 'DC-Link Voltage Balancing Strategy Based on Optimal Switching Sequences Model Predictive Control for Single-Phase H-NPC Converters', IEEE Transactions on Industrial Electronics, pp. 1-1.
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Vu, HD, Nguyen, TV, Nguyen, DN & Nguyen, HT 2020, 'On Design of Protograph LDPC Codes for Large-Scale MIMO Systems', IEEE ACCESS, vol. 8, pp. 46017-46029.
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Vu, L, Nguyen, QU, Nguyen, DN, Hoang, DT & Dutkiewicz, E 2020, 'Deep Transfer Learning for IoT Attack Detection', IEEE Access, pp. 1-1.
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Wang, H, Lian, D, Zhang, Y, Qin, L, He, X, Lin, Y & Lin, X 2020, 'Binarized Graph Neural Network.', CoRR, vol. abs/2004.11147.

Wang, M, Xu, W, Yang, C, Qiu, H & Zhu, J 2020, 'Analytical Calculation of No-Load Magnetic Field in Permanent Magnet Linear Synchronous Motors Based on an Accurate Subdomain Model', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 35, no. 5, pp. 942-953.
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© 2020, Electrical Technology Press Co. Ltd. All right reserved. Accurate calculation of the magnetic field distribution in permanent magnet linear synchronous motor (PMLSM) is required to obtain the parameters and performance, and the establishment of an accurate mathematical model is the key to solving the magnetic field problem. To avoid the limitations of the traditional analytical theory of PMLSM in solving the slot effect on air gap magnetic field, an accurate subdomain model of PMLSM is proposed to obtain the accurate magnetic field distribution. By taking into account the relative magnetic permeability of the permanent magnet (PM), slot depth and mutual influence of all slots on the magnetic field distribution, the Laplace equation of permanent magnet subdomain, airgap subdomain and slot subdomain are established in the scalar magnetic potential. According to the boundary conditions of each subdomain interface, all boundary condition equations are set up based on the Fourier series method, and the equivalent model of end area is established. The scalar magnetic potential and no-load flux density distribution of each subdomain are then solved. The slot and end effects on the spatial distribution of air gap magnetic field are discussed. The accuracy of analytical model is validated by the finite element method (FEM) results.

Wang, Q, Huang, Y, Jia, W, He, X, Blumenstein, M, Lyu, S & Lu, Y 2020, 'FACLSTM: ConvLSTM with focused attention for scene text recognition', Science China Information Sciences, vol. 63, no. 2.
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© 2020, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature. Scene text recognition has recently been widely treated as a sequence-to-sequence prediction problem, where traditional fully-connected-LSTM (FC-LSTM) has played a critical role. Owing to the limitation of FC-LSTM, existing methods have to convert 2-D feature maps into 1-D sequential feature vectors, resulting in severe damages of the valuable spatial and structural information of text images. In this paper, we argue that scene text recognition is essentially a spatiotemporal prediction problem for its 2-D image inputs, and propose a convolution LSTM (ConvLSTM)-based scene text recognizer, namely, FACLSTM, i.e., focused attention ConvLSTM, where the spatial correlation of pixels is fully leveraged when performing sequential prediction with LSTM. Particularly, the attention mechanism is properly incorporated into an efficient ConvLSTM structure via the convolutional operations and additional character center masks are generated to help focus attention on right feature areas. The experimental results on benchmark datasets IIIT5K, SVT and CUTE demonstrate that our proposed FACLSTM performs competitively on the regular, low-resolution and noisy text images, and outperforms the state-of-the-art approaches on the curved text images with large margins.

Wang, S, Ma, J, Liu, C, Wang, Y, Lei, G, Guo, Y & Zhu, J 2020, 'Design and performance analysis of a novel synchronous reluctance machine', International Journal of Applied Electromagnetics and Mechanics, vol. 63, no. 2, pp. 249-265.
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Wang, S, Wang, Y, Liu, C, Lei, G, Zhu, J & Guo, Y 2020, 'Detent Force Minimization of a Tubular Flux-Switching Permanent Magnet Motor Using Un-Equal Width Stator Slots Based on Taguchi Method', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 30, no. 4.
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Wang, X, Zha, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2020, '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, Z, Xu, M, Ye, N, Xiao, F, Ruchuan, WN & Huang, H 2020, 'Computer Vision-assisted 3D Object Localization via COTS RFID Devices and a Monocular Camera', IEEE Transactions on Mobile Computing.
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IEEE In most RFID localization systems, acquiring a reader antenna's position at each sampling time is challenging, especially for those antenna-carrying robot or drone systems with unpredictable trajectories. In this paper, we present RF-MVO that fuses RFID and computer vision for stationary RFID localization in 3D space by attaching a light-weight 2D monocular camera to two reader antennas in parallel. Firstly, the existing monocular visual odometry only recovers a camera/antenna trajectory in the camera view from 2D images. By combining it with RF phase, we design a model to estimate a scale factor for real-world trajectory transformation, along with spatial directions of an RFID tag relative to a virtual antenna array due to the mobility of each antenna. Then we propose a novel RFID localization algorithm that does not require exhaustively searching all possible positions within the pre-specified region. Secondly, to speed up the searching process and improve localization accuracy, we propose a coarse-to-fine optimization algorithm. Thirdly, we introduce the concept of horizontal dilution of precision (HDOP) to measure the confidence level of localization results. Our experiments demonstrate the effectiveness of proposed algorithms and show RF-MVO can achieve 6.23 cm localization error.

Wazid, M, Das, AK, Bhat K, V & Vasilakos, AV 2020, 'LAM-CIoT: Lightweight authentication mechanism in cloud-based IoT environment', Journal of Network and Computer Applications, vol. 150.
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© 2019 Elsevier Ltd Internet of Things (IoT) becomes a new era of the Internet, which consists of several connected physical smart objects (i.e., sensing devices) through the Internet. IoT has different types of applications, such as smart home, wearable devices, smart connected vehicles, industries, and smart cities. Therefore, IoT based applications become the essential parts of our day-to-day life. In a cloud-based IoT environment, cloud platform is used to store the data accessed from the IoT sensors. Such an environment is greatly scalable and it supports real-time event processing which is very important in several scenarios (i.e., IoT sensors based surveillance and monitoring). Since some applications in cloud-based IoT are very critical, the information collected and sent by IoT sensors must not be leaked during the communication. To accord with this, we design a new lightweight authentication mechanism in cloud-based IoT environment, called LAM-CIoT. By using LAM-CIoT, an authenticated user can access the data of IoT sensors remotely. LAM-CIoT applies efficient “one-way cryptographic hash functions” along with “bitwise XOR operations”. In addition, fuzzy extractor mechanism is also employed at the user's end for local biometric verification. LAM-CIoT is methodically analyzed for its security part through the formal security using the broadly-accepted “Real-Or-Random (ROR)” model, formal security verification using the widely-used “Automated Validation of Internet Security Protocols and Applications (AVISPA)” tool as well as the informal security analysis. The performance analysis shows that LAM-CIoT offers better security, and low communication and computation overheads as compared to the closely related authentication schemes. Finally, LAM-CIoT is evaluated using the NS2 network simulator for the measurement of network performance parameters that envisions the impact of LAM-CIoT on the network performance of LAM-CIoT and other schemes.

Wilson, KJ, Alabd, R, Abolhasan, M, Safavi-Naeini, M & Franklin, DR 2020, 'Optimisation of monolithic nanocomposite and transparent ceramic scintillation detectors for positron emission tomography', SCIENTIFIC REPORTS, vol. 10, no. 1.
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Wong, S-W, Lin, J-Y, Yang, Y, Zhu, H, Chen, R-S, Zhu, L & He, Y 2020, 'Cavity Balanced and Unbalanced Diplexer Based on Triple-Mode Resonator', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 6, pp. 4969-4979.
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Wu, K, Ni, W, Zhang, J, Liu, RP & Guo, YJ 2020, 'Refinement of Optimal Interpolation Factor for DFT Interpolated Frequency Estimator', IEEE COMMUNICATIONS LETTERS, vol. 24, no. 4, pp. 782-786.
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Wu, K, Ni, W, Zhang, JA, Liu, RP & Guo, YJ 2020, 'Secrecy Rate Analysis for Millimeter-Wave Lens Antenna Array Transmission', IEEE COMMUNICATIONS LETTERS, vol. 24, no. 2, pp. 272-276.
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Wu, L, Xu, M, Wang, J & Perry, S 2020, 'Recall What You See Continually Using GridLSTM in Image Captioning', IEEE Transactions on Multimedia, vol. 22, no. 3, pp. 808-818.
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The goal of image captioning is to automatically describe an image with a sentence, and the task has attracted research attention from both the computer vision and natural-language processing research communities. The existing encoder–decoder model and its variants, which are the most popular models for image captioning, use the image features in three ways: first, they inject the encoded image features into the decoder only once at the initial step, which does not enable the rich image content to be explored sufficiently while gradually generating a text caption; second, they concatenate the encoded image features with text as extra inputs at every step, which introduces unnecessary noise; and, third, they using an attention mechanism, which increases the computational complexity due to the introduction of extra neural nets to identify the attention regions. Different from the existing methods, in this paper, we propose a novel network, Recall Network, for generating captions that are consistent with the images. The recall network selectively involves the visual features by using a GridLSTM and, thus, is able to recall image contents while generating each word. By importing the visual information as the latent memory along the depth dimension LSTM, the decoder is able to admit the visual features dynamically through the inherent LSTM structure without adding any extra neural nets or parameters. The Recall Network efficiently prevents the decoder from deviating from the original image content. To verify the efficiency of our model, we conducted exhaustive experiments on full and dense image captioning. The experimental results clearly demonstrate that our recall network outperforms the conventional encoder–decoder model by a large margin and that it performs comparably to the state-of-the-art methods.

Wu, T, Feng, Z, Wu, C, Lei, G, Guo, Y, Zhu, J & Wang, X 2020, 'Multiobjective Optimization of a Tubular Coreless LPMSM Based on Adaptive Multiobjective Black Hole Algorithm', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 67, no. 5, pp. 3901-3910.
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Wu, Z, Tang, M-C, Li, M & Ziolkowski, RW 2020, 'Ultralow-Profile, Electrically Small, Pattern-Reconfigurable Metamaterial-Inspired Huygens Dipole Antenna', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 3, pp. 1238-1248.
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Wu, Z, Zhang, C, Alkahtani, M, Hu, Y & Zhang, J 2020, 'Cost Effective Offline Reconfiguration for Large-Scale Non-Uniformly Aging Photovoltaic Arrays Efficiency Enhancement', IEEE Access, vol. 8, pp. 80572-80581.
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© 2013 IEEE. In the past decades, a huge number of large-scale photovoltaic (PV) plants have been constructed all around the world. However, the capital and operational costs can be high, which limits their widespread applications. Because the installed PV modules often operate in harsh environments (i.e. storm, high temperature, dust, hail, etc.), non-uniform aging phenomena of PV modules cannot be avoided and it impacts adversely on the performance of PV plants, especially in the middle and late periods of their service life. This paper develops an offline PV module reconfiguration strategy for the non-uniform aging PV array to mitigate this effect. In order to maximize the economic benefit, electricity price and labor cost are considered in the offline reconfiguration. The Branch-and-Bound based optimization algorithm is proposed to find the highest economic benefit. In order to verify the proposed algorithm, MATLAB software-based modelling and simulation have been performed in four case studies, in which a typical 42kW PV array with 7×20 connection is employed in a testing benchmark, and the manpower cost and electricity price in USA, UK, China and Turkey are considered in the case study. The results demonstrate that the economic benefit from a non-uniformly aged PV array is further enhanced with the proposed reconfiguration method.

Xi, Y, Zheng, J, He, X, Jia, W, Li, H, Xie, Y, Feng, M & Li, X 2020, 'Beyond context: Exploring semantic similarity for small object detection in crowded scenes', Pattern Recognition Letters.
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© 2019 Small object detection in crowded scene aims to find those tiny targets with very limited resolution from crowded scenes. Due to very little information available on tiny objects, it is often not suitable to detect them merely based on the information presented inside their bounding boxes, resulting low accuracy. In this paper, we propose to exploit the semantic similarity among all predicted objects’ candidates to boost the performance of detectors when handling tiny objects. For this purpose, we construct a pairwise constraint to depict such semantic similarity and propose a new framework based on Discriminative Learning and Graph-Cut techniques. Experiments conducted on three widely used benchmark datasets demonstrate the improvement over the state-of-the-art approaches gained by applying this idea.

Xi, Y, Zheng, J, Jia, W, He, X, Li, H, Ren, Z & Lam, K-M 2020, 'See Clearly in the Distance: Representation Learning GAN for Low Resolution Object Recognition', IEEE ACCESS, vol. 8, pp. 53203-53214.
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Xie, H & Veitch, D 2020, 'Nested saturation control of multiple vector integrators and its application to motion control of UAVs', International Journal of Robust and Nonlinear Control, vol. 30, no. 1, pp. 246-265.
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This paper presents two nested input saturation control schemes for a special class of multiple vector integrators with bounded additive disturbances. The considered systems originate from the motion control of rotary‐wing unmanned aerial vehicles (UAVs). The first scheme is based on a feedforward form, which requires state transformation and can be applied to stabilize arbitrary order vector integrator systems. The second scheme is constructed with original state variables using a new approach, applied here to double vector integrator systems. The capability of handling external disturbance using the two schemes is also analyzed. The two schemes are applied to design motion controllers for rotary‐wing UAVs and simulation results are provided to show the performances of two controllers.

Xu, J-X, Zhang, XY, Li, H-Y, Yang, Y, Dutkiewicz, E & Xue, Q 2020, 'Ultracompact Multichannel Bandpass Filter Based on Trimode Dielectric-Loaded Cavities', IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, vol. 68, no. 5, pp. 1668-1677.
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Xu, K-D, Zhang, F, Guo, Y, Ye, L & Liu, Y 2020, 'Spoof Surface Plasmon Polaritons Based on Balanced Coplanar Stripline Waveguides', IEEE PHOTONICS TECHNOLOGY LETTERS, vol. 32, no. 1, pp. 55-58.
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Xu, W, Ebraheem, AK, Liu, Y, Zhu, J, Hussien, MG & Elbabo Mohammed, OM 2020, 'An MRAS Speed Observer Based on Control Winding Flux for Sensorless Control of Stand-Alone BDFIGs', IEEE Transactions on Power Electronics, vol. 35, no. 7, pp. 7271-7281.
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© 1986-2012 IEEE. This article presents a new rotor speed observer for the sensorless control of stand-alone brushless doubly fed induction generators based on the control winding flux model reference adaptive system structure. The observer is incorporated in the control strategy for regulating the terminal voltage magnitude and frequency under the different operating conditions. The capability of the proposed observer and control method is demonstrated by comprehensive simulation results and verified by experiments. As shown, without using physical speed sensors, the sensorless control algorithm incorporating the proposed speed observer can effectively maintain the amplitude and frequency of power winding voltage constant at different rotor speeds and under different conditions of load and machine parameter, e.g., inductance and/or resistance, variations.

Xu, W, Zhang, Y, Du, G, He, M, Zhu, J, Ning, L, Ye, C & Hua, W 2020, 'Design and Analysis of a Hybridly Excited Asymmetric Stator Pole Doubly Salient Machine', IEEE Transactions on Industry Applications, vol. 56, no. 3, pp. 2600-2611.
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© 1972-2012 IEEE. This article presents the design and analysis of a 12/7 (numbers of stator/rotor poles) hybridly excited asymmetric stator pole doubly salient machine (HEASPDSM) with a main focus on the special topology and operational principle by using the analytical and 2-D finite element analysis. A full comparison is conducted on the average torque, torque ripples, no-load back electromotive force and flux regulation capacity under the condition of different structural parameters, which can provide good references to the machine design. A 12/7 HEASPDSM is designed and the main performance indexes are analyzed in detail. Based on the parameters, the performance of 12/7 HEASPDSM is compared with traditional 6/7 doubly salient permanent magnet machine (DSPMM) with the same volume and thermal load. Finally, a prototype of the 12/7 HEASPDSM is manufactured and tested to validate the theoretical analysis. The results fully demonstrate that the HEASPDSM possesses the merits of strong flux regulation capability, higher torque density, and wider constant power speed range benefitted from the dc field winding than the traditional DSPMM.

Xu, X, Veitch, D, Li, Y & Vucetic, B 2020, 'Minimum Cost Reconfigurable Network Template Design with Guaranteed QoS', IEEE Transactions on Communications, vol. 68, no. 2, pp. 1013-1024.
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© 2019 IEEE. Conventional networks are based on layered protocols with intensive cross-layer interactions and complex signal processing at every node, making it difficult to meet the ultra-low latency requirement of mission critical applications in future communication systems. In this paper, we address this issue by proposing the concept of network template, which allows data to flow through it at the transmission symbol level, with minimal node processing. This is achieved by carefully calibrating the inter-connecting links among the nodes and pre-calculating the routing/network coding actions for each node, according to a set of preconfigured flows. In this paper, we focus on the minimum cost network template design to minimize the connections within the template, while ensuring that all the pre-defined configurations are feasible with the guaranteed throughput, latency and reliability. We show that the minimum cost network template design problem is difficult to solve optimally in general. We thus propose an efficient greedy algorithm to find a close-to-optimal solution. Simulation results show that the construction cost of the templates obtained by the proposed algorithm is very close to a lower bound. Furthermore, the construction cost increases only slightly with the number of pre-defined configurations, which confirms the flexibility of the network template design.

Yao, L, Kusakunniran, W, Wu, Q, Zhang, J, Tang, Z & Yang, W 2020, 'Robust gait recognition using hybrid descriptors based on Skeleton Gait Energy Image', Pattern Recognition Letters.
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© 2019 Gait features have been widely applied in human identification. The commonly-used representations for gait recognition can be roughly classified into two categories: model-free features and model-based features. However, due to the view variances and clothes changes, model-free features are sensitive to the appearance changes. For model-based features, there is great difficulty in extracting the underlying models from gait sequences. Based on the confidence maps and the part affinity fields produced by a two-branch multi-stage CNN network, a new model-based representation, Skeleton Gait Energy Image (SGEI), has been proposed in this paper. Another contribution is that a hybrid representation has been produced, which uses SGEI to remedy the deficiency of model-free features, Gait Energy Image (GEI) for instance. The experimental performances indicate that our proposed methods are more robust to the cloth changes, and contribute to increasing the robustness of gait recognition in the unconstrained environments with view variances and clothes changes.

Yao, Y, Zhang, J, Shen, F, Liu, L, Zhu, F, Zhang, D & Shen, HT 2020, 'Towards automatic construction of diverse, high-quality image datasets', IEEE Transactions on Knowledge and Data Engineering, vol. 32, no. 6, pp. 1199-1211.
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© 1989-2012 IEEE. The availability of labeled image datasets has been shown critical for high-level image understanding, which continuously drives the progress of feature designing and models developing. However, constructing labeled image datasets is laborious and monotonous. To eliminate manual annotation, in this work, we propose a novel image dataset construction framework by employing multiple textual queries. We aim at collecting diverse and accurate images for given queries from the Web. Specifically, we formulate noisy textual queries removing and noisy images filtering as a multi-view and multi-instance learning problem separately. Our proposed approach not only improves the accuracy but also enhances the diversity of the selected images. To verify the effectiveness of our proposed approach, we construct an image dataset with 100 categories. The experiments show significant performance gains by using the generated data of our approach on several tasks, such as image classification, cross-dataset generalization, and object detection. The proposed method also consistently outperforms existing weakly supervised and web-supervised approaches.

Yi, JH, Xing, LN, Wang, GG, Dong, J, Vasilakos, AV, Alavi, AH & Wang, L 2020, 'Behavior of crossover operators in NSGA-III for large-scale optimization problems', Information Sciences, vol. 509, pp. 470-487.
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© 2018 Elsevier Inc. Traditional multi-objective optimization evolutionary algorithms (MOEAs) do not usually meet the requirements for online data processing because of their high computational costs. This drawback has resulted in difficulties in the deployment of MOEAs for multi-objective, large-scale optimization problems. Among different evolutionary algorithms, non-dominated sorting genetic algorithm-the third version (NSGA-III) is a fairly new method capable of solving large-scale optimization problems with acceptable computational requirements. In this paper, the performance of three crossover operators of the NSGA-III algorithm is benchmarked using a large-scale optimization problem based on human electroencephalogram (EEG) signal processing. The studied operators are simulated binary (SBX), uniform crossover (UC), and single point (SI) crossovers. Furthermore, enhanced versions of the NSGA-III algorithm are proposed through introducing the concept of Stud and designing several improved crossover operators of SBX, UC, and SI. The performance of the proposed NSGA-III variants is verified on six large-scale optimization problems. Experimental results indicate that the NSGA-III methods with UC and UC-Stud (UCS) outperform the other developed variants.

Yu, G, Wang, X, Yu, K, Ni, W, Zhang, JA & Liu, RP 2020, 'Survey: Sharding in Blockchains', IEEE ACCESS, vol. 8, pp. 14155-14181.
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Yu, G, Zha, X, Wang, X, Ni, W, Yu, K, Yu, P, Zhang, JA, Liu, RP & Guo, YJ 2020, 'Enabling Attribute Revocation for Fine-Grained Access Control in Blockchain-IoT Systems', IEEE Transactions on Engineering Management, pp. 1-18.
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Yu, G, Zha, X, Wang, X, Ni, W, Yu, K, Zhang, JA & Liu, RP 2020, 'A Unified Analytical model for proof-of-X schemes', Computers and Security, vol. 96.
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© 2020 Nakamoto protocol, practically solving the Byzantine Generals Problem, can support a variety of proof-based consensus engines, referred to as Proof-of-X (PoX) in permissionless Blockchains. However, there has been to date in lack of a general approach for each miner to evaluate its steady-state profit against the competitors. This paper presents a Markov model which captures explicitly the weighted resource distribution of PoX schemes in large-scale networks and unifies the analysis of different PoX schemes. The new model leads to the development of three new unified metrics for the evaluation, namely, Resource Sensitivity, System Convergence, and Resource Fairness, accounting for security, stability, and fairness, respectively. The generality and applicability of our model are validated by simulation results, revealing that among typically non-Fairness-oriented PoX schemes (such as Proof-of-Work (PoW) and Proof-of-Stake (PoS)), the strongly restricted coinage-based PoS with a Pareto-distributed resource can offer the best performance on Resource Sensitivity, while Proof-of-Publication (PoP) with normal-distributed resource performs the best on System Convergence. Our simulations also reveal the important role of carefully designed Resource Fairness parameter in balancing Resource Sensitivity and System Convergence and improving the performance compared with other non-Fairness-oriented PoX schemes.

Yu, H, Zhang, T & Jia, W 2020, 'Shared subspace least squares multi-label linear discriminant analysis', Applied Intelligence, vol. 50, no. 3, pp. 939-950.
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© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Multi-label linear discriminant analysis (MLDA) has been explored for multi-label dimension reduction. However, MLDA involves dense matrices eigen-decomposition which is known to be computationally expensive for large-scale problems. In this paper, we show that the formulation of MLDA can be equivalently casted as a least squares problem so as to significantly reduce the computation burden and scale to the data collections with higher dimension. Further, it is also found that appealing regularization techniques can be incorporated into the least-squares model to boost generalization accuracy. Experimental results on several popular multi-label benchmarks not only verify the established equivalence relationship, but also demonstrate the effectiveness and efficiency of our proposed algorithms.

Yuan, J, Mostaan, A, Yang, Y, Siwakoti, YP & Blaabjerg, F 2020, 'A Modified Y-Source DC-DC Converter With High Voltage-Gains and Low Switch Stresses', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 35, no. 8, pp. 7716-7720.
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Yuan, W, Wu, N, Zhang, A, Huang, X, Li, Y & Hanzo, L 2020, 'Iterative Receiver Design for FTN Signaling Aided Sparse Code Multiple Access', IEEE Transactions on Wireless Communications, vol. 19, no. 2, pp. 915-928.
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© 2002-2012 IEEE. The sparse code multiple access (SCMA) is a promising candidate for bandwidth-efficient next generation wireless communications, since it can support more users than the number of resource elements. On the same note, faster-than-Nyquist (FTN) signaling can also be used to improve the spectral efficiency. Hence in this paper, we consider a combined uplink FTN-SCMA system in which the data symbols corresponding to a user are further packed using FTN signaling. As a result, a higher spectral efficiency is achieved at the cost of introducing intentional inter-symbol interference (ISI). To perform joint channel estimation and detection, we design a low complexity iterative receiver based on the factor graph framework. In addition, to reduce the signaling overhead and transmission latency of our SCMA system, we intrinsically amalgamate it with grant-free scheme. Consequently, the active and inactive users should be distinguished. To address this problem, we extend the aforementioned receiver and develop a new algorithm for jointly estimating the channel state information, detecting the user activity and for performs data detection. In order to further reduce the complexity, an energy minimization based approximation is employed for restricting the user state to Gaussian. Finally, a hybrid message passing algorithm is conceived. Our Simulation results show that the FTN-SCMA system relying on the proposed receiver design has a higher throughput than conventional SCMA scheme at a negligible performance loss.

Yuan, X, Feng, Z, Ni, W, Liu, RP, Zhang, JA & Xu, W 2020, 'Secrecy Performance of Terrestrial Radio Links under Collaborative Aerial Eavesdropping', IEEE Transactions on Information Forensics and Security, vol. 15, pp. 604-619.
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© 2005-2012 IEEE. Motivated to understand the increasingly severe threat of unmanned aerial vehicles (UAVs) to the confidentiality of terrestrial radio links, this paper analyzes the ergodic and ϵ-outage secrecy capacities of the links in the presence of multiple cooperative aerial eavesdroppers flying autonomously in three-dimensional (3D) spaces and exploiting selection combining (SC) or maximal ratio combining (MRC). The 'cut-off' density of the eavesdroppers under which the secrecy capacities vanish is identified. By decoupling the analysis of the random trajectories from the random channel fading, closed-form approximations with almost sure convergence to the secrecy capacities are devised. The analysis is extended to study the impact of the oscillator phase noises and finite memories of the aerial eavesdroppers on the secrecy performance of the ground link. Validated by simulations, the cut-off density only depends on the range of the link in the case of SC eavesdropping, while it depends on the flight region of the eavesdroppers in the case of MRC eavesdropping.

Zeng, J, Lv, T, Lin, Z, Liu, RP, Mei, J, Ni, W & Guo, YJ 2020, 'Achieving Ultra-Reliable and Low Latency Communications in IoT by FD-SCMA', IEEE Internet of Things Journal, pp. 1-1.
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Zeng, J, Lv, T, Liu, RP, Su, X, Guo, YJ & Beaulieu, NC 2020, 'Enabling Ultrareliable and Low-Latency Communications Under Shadow Fading by Massive MU-MIMO', IEEE INTERNET OF THINGS JOURNAL, vol. 7, no. 1, pp. 234-246.
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Zhan, W-L, Xu, J-X, Zhao, X-L, Hu, B-J & Zhang, XY 2020, 'Substrate Integrated Waveguide Multi-Channel Filtering Crossover With Extended Channel Number and Controllable Frequencies', IEEE Transactions on Circuits and Systems II: Express Briefs, pp. 1-1.
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Zhang, H & Xu, M 2020, 'Improving the generalization performance of deep networks by dual pattern learning with adversarial adaptation', KNOWLEDGE-BASED SYSTEMS, vol. 200.
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Zhang, H & Xu, M 2020, 'Weakly Supervised Emotion Intensity Prediction for Recognition of Emotions in Images', IEEE Transactions on Multimedia, pp. 1-1.
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Zhang, H, Huang, X, Zhang, JA & Guo, YJ 2020, 'Dual Pulse Shaping Transmission and Equalization for High-Speed Wideband Wireless Communication Systems', IEEE Transactions on Circuits and Systems I: Regular Papers, pp. 1-11.
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Zhang, J, Yang, X, Xie, N, Zhang, X, Vasilakos, AV & Li, W 2020, 'An online auction mechanism for time-varying multidimensional resource allocation in clouds', Future Generation Computer Systems, vol. 111, pp. 27-38.
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© 2020 Elsevier B.V. Multidimensional resource allocation is a hot topic in cloud computing, but current cloud platforms support only fixed resource allocation, that is, the user resource requirements are consistent throughout the usage period, which may cause a waste of resources and reduce the revenue of resource providers. Therefore, time-varying multidimensional resource allocation and the corresponding pricing mechanism represent a new challenge in cloud computing. We address the problem of online time-varying multidimensional resource allocation and pricing in clouds. Specifically, (1) we propose a novel integer programming model for the time-varying multidimensional resource allocation problem and (2) we design a truthful online auction mechanism for resource allocation in a competitive environment. For the resource allocation algorithm, we propose a waiting period strategy and dominant-resource-based strategy to improve the social welfare and resource utilization. Simultaneously, a payment pricing algorithm based on critical value theory is proposed. Finally, we prove that the mechanism is truthful and individual rationality. Compared with existing research, our approach is characterized by high social welfare, high resource utilization and short execution time.

Zhang, P, Li, H, Ha, QP, Yin, ZY & Chen, RP 2020, 'Reinforcement learning based optimizer for improvement of predicting tunneling-induced ground responses', Advanced Engineering Informatics, vol. 45.
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© 2020 Elsevier Ltd Prediction of ground responses is important for improving performance of tunneling. This study proposes a novel reinforcement learning (RL) based optimizer with the integration of deep-Q network (DQN) and particle swarm optimization (PSO). Such optimizer is used to improve the extreme learning machine (ELM) based tunneling-induced settlement prediction model. Herein, DQN-PSO optimizer is used to optimize the weights and biases of ELM. Based on the prescribed states, actions, rewards, rules and objective functions, DQN-PSO optimizer evaluates the rewards of actions at each step, thereby guides particles which action should be conducted and when should take this action. Such hybrid model is applied in a practical tunnel project. Regarding the search of global best weights and biases of ELM, the results indicate the DQN-PSO optimizer obviously outperforms conventional metaheuristic optimization algorithms with higher accuracy and lower computational cost. Meanwhile, this model can identify relationships among influential factors and ground responses through self-practicing. The ultimate model can be expressed with an explicit formulation and used to predict tunneling-induced ground response in real time, facilitating its application in engineering practice.

Zhang, P, Xu, J, Wu, Q, Huang, Y & Zhanga, J 2020, 'Top-Push Constrained Modality-Adaptive Dictionary Learning for Cross-Modality Person Re-Identification', IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1.
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Zhang, R, Wu, L, Yang, Y, Wu, W, Chen, Y & Xu, M 2020, 'Multi-camera multi-player tracking with deep player identification in sports video', PATTERN RECOGNITION, vol. 102.
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Zhang, XY & Xu, J-X 2020, 'Multifunctional Filtering Circuits: 3D Multifunctional Filtering Circuits Based on High-Q Dielectric Resonators and Coaxial Resonators', IEEE MICROWAVE MAGAZINE, vol. 21, no. 3, pp. 50-68.
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Zhang, YQ, Li, X & Vasilakos, AV 2020, 'Spectral Analysis of Epidemic Thresholds of Temporal Networks', IEEE Transactions on Cybernetics, vol. 50, no. 5, pp. 1965-1977.
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© 2013 IEEE. Many complex systems can be modeled as temporal networks with time-evolving connections. The influence of their characteristics on epidemic spreading is analyzed in a susceptible-infected-susceptible epidemic model illustrated by the discrete-time Markov chain approach. We develop the analytical epidemic thresholds in terms of the spectral radius of weighted adjacency matrix by averaging temporal networks, e.g., periodic, nonperiodic Markovian networks, and a special nonperiodic non-Markovian network (the link activation network) in time. We discuss the impacts of statistical characteristics, e.g., bursts and duration heterogeneity, as well as time-reversed characteristic on epidemic thresholds. We confirm the tightness of the proposed epidemic thresholds with numerical simulations on seven artificial and empirical temporal networks and show that the epidemic threshold of our theory is more precise than those of previous studies.

Zhao, J, Zhang, H & Zhang, JA 2020, 'Gaussian kernel adaptive filters with adaptive kernel bandwidth', Signal Processing, vol. 166.
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© 2019 Gaussian kernel adaptive filters (GKAFs) have been successfully applied in functional approximation. The kernel bandwidth for GKAFs not only impacts on the smoothness of function approximation and the locality of training samples, but also affects the convergence rate and testing accuracy. However, in practice, it is hard to predesign an optimal one. In this paper, for practical applications, we propose a novel framework for kernel bandwidth adaptation in sparsification case. In this framework, we consider the latest K kernel bandwidths as free parameters, and sequentially update them using a gradient decent method to minimize the instantaneous squared error. Furthermore, we apply the proposed method to the quantized kernel least mean square (QKLMS) algorithm, and conduct convergence analysis for the algorithm. Extensive simulation results are provided and validate the superiority of our method compared to some state-of-the-art algorithms.

Zhao, J, Zhang, H & Zhang, JA 2020, 'Generalized maximum correntropy algorithm with affine projection for robust filtering under impulsive-noise environments', Signal Processing, vol. 172.
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© 2020 Combining affine projection (AP) with the generalized maximum correntropy (GMC) criterion, we propose a new family of AP-type filtering algorithms, called as APGMC, for system identification under impulsive-noise environments. By optimizing GMC of the a posterior error vector with a ℓ2-norm constraint on the filter weight vector, APGMC avoids the computation of the inversion of the input data matrix. Simulation results validate that APGMC achieves better filtering accuracy and faster convergence rate, compared to state-of-the-art algorithms.

Zhao, J, Zhang, H, Wang, G & Zhang, JA 2020, 'Projected Kernel Least Mean p-Power Algorithm: Convergence Analyses and Modifications', IEEE Transactions on Circuits and Systems I: Regular Papers, pp. 1-14.
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Zheng, D, Zhang, H, Zhang, JA, Zheng, W & Su, SW 2020, 'Stability of asynchronous switched systems with sequence-based average dwell time approaches', Journal of the Franklin Institute, vol. 357, no. 4, pp. 2149-2166.
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© 2019 The Franklin Institute This paper studies the stability problem of asynchronous switched systems and proposes novel sequence-based average dwell time approaches. Both continuous-time and discrete-time systems are considered. The proposed approaches exploit the switching sequences of subsystems which were seldom utilized in the literature. More specifically, our approaches exploit the differences between different switching sequences, including the maximal asynchronous switching time, the energy changing degree at switching times, and the increasing speed of energy functions in asynchronous time intervals. As a result, the proposed approaches can reduce the threshold value of average dwell time significantly. We also propose an approach to counterbalance the increasing of energy functions in asynchronous time intervals by prolonging the preceding rather than subsequent subsystem. Numerical results demonstrate that the proposed approaches can improve the performance significantly in comparison with a well-known method.

Zhou, I, Lipman, J, Abolhasan, M, Shariati, N & Lamb, DW 2020, 'Frost monitoring cyber-physical system: a survey on prediction and active protection methods', IEEE Internet of Things Journal, pp. 1-1.
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Zhu, G, Liu, X, Li, L & Zhu, J 2020, 'A novel nonlinearity marginalization technique for effective solution of induction heating problems by cell method', Journal of Physics D: Applied Physics, vol. 53, no. 24.
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© 2020 IOP Publishing Ltd. The modelling and analysis of induction heating process is a strongly coupled nonlinear electromagnetic-thermodynamic problem. It is of great theoretical and practical significance to develop an effective numerical technique for solving the coupled nonlinear governing equations. This paper presents a mathematical model of the coupled electromagnetic-thermodynamic fields of induction heating problems, taking into account the nonlinearity due to temperature dependent physical properties and the heat sources due to eddy currents. Due to the temperature dependent nonlinearity, the conventional approach to dynamic problems is to reconstruct the global stiffness matrix for each time step, which increases dramatically the computational burden. A new method is proposed in this paper to reduce the computational burden by modifying the mathematical model to marginalize the nonlinearity throughout the calculation domain to the external surfaces. This method can effectively reduce the degree of nonlinearity, and simplify efficaciously the calculation process. The proposed model and method are combined with the algebraically formed cell method to analyze the induction heating process of an aluminum cylindrical billet. The calculation results are validated by the 3D finite element analysis.

Zhu, H, Qin, P-Y & Guo, YJ 2020, 'Single-Ended-to-Balanced Power Divider With Extended Common-Mode Suppression and Its Application to Differential 2 x 4 Butler Matrices', IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, vol. 68, no. 4, pp. 1510-1519.
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Zhu, H, Zhu, X, Yang, Y & Sun, Y 2020, 'Design of miniaturized on-chip bandpass filters using inverting-coupled inductors in (Bi)-CMOS Technology', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 67, no. 2, pp. 647-657.
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© 2004-2012 IEEE. In this work, a new type of miniaturized on-chip resonator using coupled-inductor structure is presented. The impact on resonances of the structure due to the use of non- inverting- and inverting-coupled configuration is extensively investigated. It has been found that using the inverting-coupled structure, a stronger resonance can be generated, which is ideally suitable for device miniaturization. To fully understand the working mechanism of the resonator and use it effectively for bandpass filter (BPF) design, simplified LC equivalent-circuit models and detailed theoretical analysis are provided. To further demonstrate the proposed concept is useful in practice, not only a 1st-order BPF, but also another two 2nd-order BPFs are designed and fabricated in a standard 0.13-μm (Bi)-CMOS technology. All of them are designed to have a centre frequency around 15 GHz. Their physical dimensions are 0.13 × 0.25 mm2, 0.26 × 0.25 mm2, 0.24 × 0.22 mm2, respectively. Good agreements between simulation and measurement have been obtained, which verify that the presented design approach is suitable for miniaturized on-chip passive design.

Zhu, J, Yang, Y, Chu, C, Li, S, Liao, S & Xue, Q 2020, 'Low-Profile Wideband and High-Gain LTCC Patch Antenna Array for 60 GHz Applications', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 4, pp. 3237-3242.
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Zhu, J, Yang, Y, McGloin, D, Rajasekharan Unnithan, R, Li, S, Liao, S & Xue, Q 2020, '3-D Printed Planar Dielectric Linear-to-Circular Polarization Conversion and Beam-Shaping Lenses Using Coding Polarizer', IEEE Transactions on Antennas and Propagation, vol. 68, no. 6, pp. 4332-4343.
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© 1963-2012 IEEE. This article presents a new linear-to-circular polarization conversion coding unit, on which two new kinds of beam-shaping lenses are proposed. First, under periodic boundary conditions, a linear-to-circular polarization conversion coding unit is introduced, which introduces the necessary phase delay by adjusting its geometrical parameters. The phase delay ranges from 0° to 360° and is discretized into 3 bit coding units corresponding to specific delays. Second, by properly arranging the coding units, a high-gain circularly polarized (CP) lens is proposed. The lens achieves linear-to-circular polarization conversion and beam collimation in the transmission mode simultaneously with a planar configuration, which is different from counterparts that place a lens atop of a polarizer. Furthermore, the coding units are used to form Wollaston-prism-like and Rochon-prism-like planar CP beam-shaping lenses, which split the beams with different polarizations into right-and left-handed components. These beams can be controlled independently. Prototypes working at 30 GHz band are designed, fabricated, and measured to verify the idea.

Ziolkowski, RW & Engheta, N 2020, 'Metamaterials: Two Decades Past and Into Their Electromagnetics Future and Beyond', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 68, no. 3, pp. 1232-1237.
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Zuo, Y, Wu, Q, Fang, Y, An, P, Huang, L & Chen, Z 2020, 'Multi-Scale Frequency Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Network', IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 2, pp. 297-306.
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© 1991-2012 IEEE. The depth maps obtained by the consumer-level sensors are always noisy in the low-resolution (LR) domain. Existing methods for the guided depth super-resolution, which are based on the pre-defined local and global models, perform well in general cases (e.g., joint bilateral filter and Markov random field). However, such model-based methods may fail to describe the potential relationship between RGB-D image pairs. To solve this problem, this paper proposes a data-driven approach based on the deep convolutional neural network with global and local residual learning. It progressively upsamples the LR depth map guided by the high-resolution intensity image in multiple scales. A global residual learning is adopted to learn the difference between the ground truth and the coarsely upsampled depth map, and the local residual learning is introduced in each scale-dependent reconstruction sub-network. This scheme can restore the depth structure from coarse to fine via multi-scale frequency synthesis. In addition, batch normalization layers are used to improve the performance of depth map denoising. Our method is evaluated in noise-free and noisy cases. A comprehensive comparison against 17 state-of-the-art methods is carried out. The experimental results show that the proposed method has faster convergence speed as well as improved performances based on the qualitative and quantitative evaluations.

Ahmed, F, Afzal, MU, Hayatt, T & Esselle, KP 2020, 'Low-cost all-metal resonant-cavity antenna for high power applications', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. Low-cost all-metal partially reflecting surface (AM PRS) based resonant-cavity antennas are presented in this paper. The AM PRSs are made by introducing square-shaped slots in a thin metallic sheet having moderate to high reflectivity ranging from -4.12 dB to -1.27 dB. An RCA designed using highly reflecting AM PRS has maximum directivity of 16.54 dBi and low 3dB directivity bandwidth of 9.17% whereas those designed using less reflective AM PRSs have high directivity bandwidth but smaller peak directivity within the operating band.

Amin, BMR, Rahman, MS & Hossain, MJ 2019, 'Impact Assessment of Credible Contingency and Cyber Attack on Australian 14-Generator Interconnected Power System', IEEE Power and Energy Society General Meeting, IEEE Power & Energy Society General Meeting, 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 2019, 'A Contract-based Trading Model for Electricity Suppliers in Smart Grids', 2019 20th International Conference on Intelligent System Application to Power Systems, ISAP 2019, International Conference on Intelligent System Application to Power Systems, 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.

Asari, AR, Guo, Y & Zhu, J 2019, '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 - Proceedings, International UNIMAS STEM Engineering Conference, 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.

Aykin, I & Krunz, M 2020, 'Efficient Beam Sweeping Algorithms and Initial Access Protocols for Millimeter-Wave Networks', IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, pp. 2504-2514.
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Azizivahed, A, Karandeh, R, Cecchi, V, Naderi, E, Li, L & Zhang, J 2020, 'Multi-area dynamic economic dispatch considering water consumption minimization, wind generation, and energy storage system', 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020.
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© 2020 IEEE. This paper introduces a novel, practical model for Multi-Area Dynamic Economic Dispatch (MADED) problem whose primary targets are to minimize both operational cost and water consumption. To make the proposed study more practical, several additional requirements that are inevitable in forthcoming power systems are taken into account including wind power penetration, pumped storage systems, and different interconnected areas. Such a complicated problem needs to be solved by a potent multi-objective optimization tool. In this regard, one of the relatively new optimization approaches, Whale Optimization Algorithm (WOA), is implemented to solve the proposed problem. The obtained optimal solutions on a 40-unit power network illustrate the effectiveness of the proposed approach and reveal a substantial improvement in reducing the operational cost, i.e., more than $30 million is reduced annually.

Bah, AO, Bird, T & Qin, P 2019, '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.

Bai, J, Liu, Y & Liu, QH 2019, 'Fast and accurate antenna array pattern synthesis using iterative FFT via least-square active element pattern expansion (LS-AEPE)', 2019 Photonics and Electromagnetics Research Symposium - Fall, PIERS - Fall 2019 - Proceedings, Photonics & Electromagnetics Research Symposium - Fall, IEEE, Xiamen, China, pp. 2629-2633.
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© 2019 IEEE. A new method incorporating the least-squares active element pattern expansion (LS-AEPE) into the iterative Fourier transform (IFT) procedure is introduced to synthesize the shaped beam pattern for the linear array with the strong scattering environment. The synthesized result, involving the mutual coupling and platform effect, is more accurate than traditional IFT, and the procedure takes very litter time. A 16-element array surrounded with many irregular scatters is given to validate the accuracy and efficiency of the introduced method.

Bautista, M, Zhu, H, Zhu, X & Yang, Y 2019, 'Design of Self-Coupling Enhanced Resonator in 0.13-μm (Bi)-CMOS Technology', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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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}.

Begum, M, Li, L & Zhu, J 2020, 'Distributed secondary control of energy storage units for SoC balancing in AC Microgrid', 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020.
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© 2020 IEEE. This paper introduces a new distributed secondary control (DSC) method for distributed energy storage units (DESUs) in an islanded alternative current (AC) microgrid (MG). Dynamics of distributed storages for the extended time duration are not taken into account in the traditional hierarchical control of MG. Thus, it is challenging to control the DESUs with various levels of stored energy represented by the state of charge (SoC). The storage units can utilise their full power capacity after converging to a common SoC to mitigate the generation and demand variations in the MG. SoC depletion of DESUs with lower initial SoC occurs faster than those with higher initial SoC by using the traditional P-f droop control and then their capacities are no longer accessible. Furthermore, applying the droop control to match the SoC of DESUs causes the deviation of frequency and voltage from their reference values. However, restoration of the MG frequency using the conventional DSCs disrupts the SoC-balancing. The designed DSC can achieve simultaneous frequency/voltage regulation, power sharing and SoC-balancing as well as removing the centralized communication. The proposed method is evaluated in the established Matlab/Simulink model and the results validate the effectiveness of the proposed method.

Chaczko, Z, Klempous, R, Rozenblit, J, Chiu, C, Kluwak, K & Smutnicki, C 2019, 'Enabling Design of Middleware for Massive Scale IoT-based Systems', 2019 IEEE 23rd International Conference on Intelligent Engineering Systems (INES), IEEE International Conference on Intelligent Engineering Systems, 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.

Chen, L, Wang, Y, Liu, Y & Guo, YJ 2019, 'Synthesis of Frequency-invariant Beam Patterns under Accurate Sidelobe Control by Second-order Cone Programming', 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall), Photonics & Electromagnetics Research Symposium - Fall, IEEE, Xiamen, China, pp. 2260-2263.
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It is shown in this work that the FI pattern synthesis can be treated as an optimization problem for minimizing the mainlobe frequency variation. To control both the mainlobe and sidelobe regions, we introduce several constraints imposed on the broadband pattern, called the look-direction constraint, the spatial response variation constraint and the sidelobe constraint, respectively. The whole optimization process needs to perform the SOCP solver. A synthesis of FI pattern with low sidelobe level (SLL) is given to validate the accuracy and effectiveness of the proposed method.

Chen, Y, An, P, Huang, X, Meng, C & Wu, Q 2019, 'Modified baseline for light field stitching', 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, Australia.
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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.

Chen, Z & Zhu, X 2019, 'Integration of mm-wave Antennas on Fan-Out Wafer Level Packaging (FOWLP) for Automotive Radar Applications', 2019 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA), 2019 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA), IEEE, Chengdu, China.
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The integration of mm-wave antennas on fan-out wafer level packaging (FOWLP) for automotive radar applications is presented in this paper. The size of the package is 12 x 15 x 0.45 mm 3 . The package includes seven antenna arrays realized with three redistribution layers (RDL). Three patch antenna arrays are used as transmitting antennas and four patch antenna arrays are used as receiving antennas. The simulation results show that the proposed antenna achieves a 10-dB input impedance bandwidth of 5.5 GHz and a maximal peak realized gain of 9.9 dBi at 77.6 GHz. The angle resolution of the MIMO radar can be improved to 9.6°.

Chen, Z, Zhu, X & Xu, L 2019, 'Integration of mm-wave antennas on fan-out wafer level packaging (FOWLP) for automotive radar applications', Asia-Pacific Microwave Conference Proceedings, APMC, Singapore, pp. 1607-1609.
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© 2019 IEEE. This paper presents the integration of mm-wave antennas on fan-out wafer level packaging (FOWLP) for automotive radar applications. The size of the package is 24x24.5x0.3 mm3, Three microstrip grid array antennas are used as transmitting antennas and four patch sub arrays are used as receiving antennas. The antennas are fed by chip signal which is coupled through a slot in the ground plane. The simulation results show maximal peak realized gain of 14.28 dBi and 11.1 dBi for transmitting and receiving antennas, respectively. The angle resolution of the MIMO radar can be improved to 9.6°.

Cheng, Q, Shi, Z, Nguyen, D & Dutkiewicz, E 2019, 'An OFDM Sensing Algorithm in Full-Duplex Systems with Self-Interference and Carrier Frequency Offset', 2019 IEEE Global Communications Conference (GLOBECOM), IEEE Global Communications Conference, IEEE, Hawaii.
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Full duplex (FD) wireless technology, which enables simultaneous transmission and reception on the same frequency, has shown its great potential for doubling the spectral efficiency as well as spectrum sensing while transmitting in cognitive radio networks (CRNs). However, the self interference (SI) suppression, the underlying technique of FD, is often imperfect, resulting in non-negligible residual SI that severely affects the test statistics of sensing methods. The residual SI thereby significantly deteriorates the spectrum sensing accuracy. In this work, we aim to address this issue by proposing a novel sensing approach in FD systems leveraging the Pilot-Tone (PT) structure of Orthogonal Frequency Division Modulation (OFDM) signals. In comparison with the conventional sensing methods in FD systems, the developed sensing approach holds the advantage in the robustness not only to residual SI but also the carrier frequency offset (CFO). Besides, the proposed sensing method is able to accomplish sensing tasks in low SNR conditions with much lower computational complexity. Numerical simulations results demonstrate that the probability of detection of our proposed approach can be improved up to 34.9%, compared with state- of-the-art sensing methods in FD systems, suffering from residual SI and CFO.

Cheng, Q, Shi, Z, Nguyen, D & Dutkiewicz, E 2020, 'Non-cooperative OFDM Spectrum Sensing Using Deep Learning', IEEE International Conference on Computing, Networking and Communications (ICNC), Hawaii.

Cheng, T, Lu, DD-C & Siwakoti, Y 2019, '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.

Chude-Okonkwo, UAK, Maharaj, BT, Vasilakos, AV & Malekian, R 2019, 'Exploring the impact of ligand residence time on molecular communication system performance', 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings, IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA.
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© 2019 IEEE. Information reception in artificially synthesized molecular communication (MC) systems ideally follows the mechanisms employed by natural nanosystems to communicate. One of such reception mechanism is the so called ligand-receptor binding. Contemporary research in MC has considerably discussed this mechanism; however, the impact of a crucial parameter associated with the ligand-receptor binding action has not been given appropriate attention in the MC literature. This parameter is termed the residence time, and has played very crucial role in defining for instance, the efficacy of drugs in therapeutic processes; hence, it is critical in the performance of MC. In this paper, we employ biophysical approach to model and discuss the influence of the ligand residence time on the performance of MC systems. The performance metrics considered here are the receiver sensitivity and the intersymbol interference. Numerical results that expose the impact of the residence time on these metrics, and the interrelationships between these metrics in MC system, are discussed.

Ding, C, Sun, H, Guo, Y & Jones, B 2019, '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.

Duong, TQ, Nguyen, LD, Tuan, HD & Hanzo, L 2019, 'Learning-Aided Realtime Performance Optimisation of Cognitive UAV-Assisted Disaster Communication', 2019 IEEE Global Communications Conference (GLOBECOM), 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.

Farhood, H, Perry, S, Cheng, E & Kim, J 2020, '3D point cloud reconstruction from a single 4D light field image', Optics, Photonics and Digital Technologies for Imaging Applications VI, Optics, Photonics and Digital Technologies for Imaging Applications VI, SPIE.
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Hassan, W, Hasan, R, Lu, DD-C, Xiao, W & Soon, JL 2019, 'Performance Enhancement of High Step-up DC-DC Converter to Attain High Efficiency and Low Voltage Stress', 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 study proposes a new high voltage gain and high-efficiency dc-dc converter to interface renewable energy resources into dc nanogrid. The proposed topology is formed by a coupled inductor to achieve high voltage gain and low stress on the active switch. The switch voltage stress is significantly low compared to the output voltage. Thus, efficiency is improved by utilizing a low voltage rating MOSFET. Furthermore, the utilization of couple inductor eliminated the reverse recovery losses of diodes. The converter consists of the least number of components that decrease the overall system cost. The steady-state operation and analysis of the proposed converter are discussed comprehensively. The experimental performance is verified by building and testing a prototype in the laboratory. The experimental results prove the consistency with the theoretical analysis. The converter depicts a peak efficiency of 97.10% in the laboratory.

Hayat, T, Afzal, MU, Ahmed, F, Lalbakhsh, A & Esselle, KP 2020, '3D printable lightweight porous superstrate for improved radiation performance of antenna', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. The paper presents a 3D printable porous superstrate (PS) to enhance directive radiation performance of low to medium gain antennas. The PS design process is based on the theory of near-field phase correction. Transmission phase through PS is locally varied by changing sizes of perforations in different sections of the PS. The PS is designed for a resonant cavity antenna (RCA) using acrylonitrile butadiene styrene (ABS) filament. With PS the RCA aperture phase is relatively planar and its directivity in boresight direction is increased by 7.2 dB (14.8 dB to 22 dB) along with 8.2 dB reduction in side-lobe levels (SLL) and 31% increase in aperture efficiency.

Hora, JA, Mayormita, MA, Rebollos, JRC, Zhu, X & Dutkiewicz, E 2019, 'On-chip inductor-less indoor light energy harvester with improved efficiency for WSN/IoT device design', Proceedings of the International Conference on Sensing Technology, ICST, International Conference on Sensing Technology, IEEEE, Sydney, Australia.
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© 2019 IEEE. An on-chip inductor-less indoor light energy harvester circuit block for internet-of-things wireless sensor node device design is implemented in 65nm CMOS process technology. The design of the indoor light energy harvester comprises a bootstrapped ring oscillator, a two-phase non-overlapping clock generator, a tapered buffer, a multi-stage differential-drive CMOS rectifier, a charge controlling circuit and a voltage regulator. The system boosts an input of 500 mV from a photovoltaic cell without using a typical boost converter circuit that employs an inductor element. Hence, a simplified on-chip design charges an external 1.3-V rechargeable battery. The use of a multi-stage differential-drive rectifier eliminates the need for expensive on-chip inductors. A charge control circuit is implemented to maintain the battery voltage and avoid overcharging, thus improving battery life. A low-dropout voltage regulator further regulates the battery voltage to produce a stable dc voltage. The chip core design has a total area of 1342μm×1011μm. The output of the harvesting system is a regulated 0.9 V supply with 1.05 mA current at full load.

Hora, JA, Zhu, X & Dutkiewicz, E 2019, 'Simplified over-temperature protection circuit structure for WSN/IoT device power management', Proceedings of the International Conference on Sensing Technology, ICST, International Conference on Sensing Technology, IEEE, Sydney, Australia,.
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© 2019 IEEE. This paper presents a modified structure of the over-temperature protective circuit integrated into the power management converter design for wireless sensor node devices. The design is focused on realizing a simplified circuit structure that is compatible with standard CMOS technology structure and evaluating the over-temperature threshold to assure needed accuracy. HSPICE simulation using Monte Carlo Analysis for the bandgap voltage reference is used to get a better estimation, process variation, and reliability. The target design temperature threshold is obtained at approximately 150 °C, which is the standard chip testing value at worst temperature consideration. Post-layout simulation of the proposed circuit design structure is carried out using 65nm 1P9M CMOS 1.2V/2.5V logic CMOS technology. And it is co-integrated in the power management circuit design for the system-on-chip wireless sensor node device.

Ian Zhou, Negin.Shariati 2020, 'A Blockchain-based File-sharing System for Academic Paper Review', IEEE International Conference on Signal Processing and Communication Systems, ICSPCS, IEEE, Australia.
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Ibrahim, IA, Hossain, MJ, Duck, BC & Badar, AQH 2019, '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, International Conference on Intelligent System Application to Power Systems, IEEE, New Delhi, India.
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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.

Karmokar, DK, Bird, TS, Guo, YJ & Esselle, KP 2019, 'A Binary-switch Controlled Periodic Half-width Leaky-wave Antenna for Fixed Frequency Beam Steering near the Endfire Region', Progress in Electromagnetics Research Symposium, PhotonIcs & Electromagnetics Research Symposium - 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.

Kashif, M, Hossain, MJ, Nawazish Ali, SM, Sharma, V & Nizami, MSH 2019, 'Harmonic identification based on DSC and MAF for three-phase shunt active power filter', 2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019, Australasian Universities Power Engineering Conference, 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, Nawazish Ali, SM & Khan, A 2019, '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 and Practice, iCEERP 2019, International Conference on Electrical Engineering Research & Practice, 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, KP, Cheng, Q, Lin, Z, Zhang, A, Zhang, JA, Nguyen, D & Huang, X 2019, 'Massive MIMO for Tactical Ad-hoc Networks in RF Contested Environments', MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM), IEEE/AFCEA Military Communications Conference, 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.

Koli, NY, Afzal, MU, Esselle, KP & Islam, MZ 2020, 'Comparison between fully and partially filled dielectric materials on the waveguide of circularly polarised radial line slot array antennas', 2020 International Workshop on Antenna Technology, iWAT 2020.
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© 2020 IEEE. This paper presents an investigation on the waveguide of circularly polarised radial line slot array (RLSA) antennas to improve gain and radiation bandwidth. Two circularly polarised (CP) RLSA antennas were designed with two different waveguide configurations. In the first configuration the waveguide is fully filled with dielectric materials and in the second configuration the waveguide is partially filled with dielectric materials and rest of the waveguide is filled with air. Numerical results of these two CP-RLSA antennas with two different waveguide configurations are presented and compared. Significant improvements have been made in the 3-dB directivity bandwidth and aperture efficiency of the antenna having waveguide partially filled with dielectric material. The 3-dB directivity bandwidth was measured 6.2% and aperture efficiency increased to 55.5%. The CP-RLSA antenna has also achieved a peak directivity of 31.7 dBic and a gain of 31.2 dBic as compared to the directivity 30.1 dBic and gain 29.5 dBic, respectively achieved with the CP-RLSA antenna having waveguide fully filled with dielectric material.

Koli, NY, Afzal, MU, Esselle, KP, Hashmi, RM, Islam, MZ & Shrestha, S 2020, 'A double layer circularly polarised radial line slot array antenna with uniform aperture illumination', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. In this paper, we have designed and investigated a double layer circularly polarised radial line slot array (RLSA) antenna for satellite communication. The antenna is composed of twofold radial waveguide with slots acting as radiating elements on its surface. The radiating slots are arranged in a spiral pattern on the antenna aperture. Every slot has a particular length and position. The slots are oriented in a way to intercept the radial currents on the upper waveguide. The slot lengths were varied to achieve a uniform aperture distribution. The electromagnetic power is fed from center of the lower waveguide. Numerical results show that the antenna is well matched within the operating frequency range. The far-field results indicate a peak directivity of 27 dBi at 20 GHz with a good pattern quality and lower side lobe level of -27.2 dB.

Le, AT, Tran, LC, Huang, X & Guo, YJ 2019, 'Analog Least Mean Square Loop for Self-Interference Cancellation: Implementation and Measurements', 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), International Telecommunication Networks and Applications Conference, IEEE, Auckland, New Zealand.
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Lee, SS, Lim, CS, Siwakoti, YP, Idris, NRN, Alsofyani, IM & Lee, KB 2019, 'A New Unity-Gain 5-Level Active Neutral-Point-Clamped (UG-5L-ANPC) Inverter', CENCON 2019 - 2019 IEEE Conference on Energy Conversion, IEEE Conference on Energy Conversion, 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.

Li, D, Tang, M-C, Wang, Y, Hu, K-Z, Li, M & Ziolkowski, RW 2019, 'Compact, Low-Profile, Planar Filtering Antennas Based on A Novel Coupling Feeding Scheme', 2019 IEEE 6th International Symposium on Electromagnetic Compatibility (ISEMC), 2019 IEEE 6th International Symposium on Electromagnetic Compatibility (ISEMC), IEEE, Nanjing, China.
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The compact, low-profile linearly polarized (LP) and circularly polarized (CP) filtering antennas based on a novel feed scheme are presented. The LP design consists of a patch and an inverted-h-shaped coupling feed probe, which can introduce two radiation nulls at the lower and the upper band edges to realize a quasi-elliptic bandpass filtering response, respectively. This LP design with simple feed structure is also extended to realize the CP function by adding an extra T -shaped feedline operating as a dual-mode resonator, while maintaining the excellent filtering performance and further enhancing the impedance bandwidth. For demonstration, two prototypes of the LP and CP designs were measured. The measured results agree well with the simulated values. In addition, good performance characteristics, i.e., flat passband gain response, excellent roll-off rate, and high out-of-band suppression level, could be well achieved.

Li, HY, Xu, JX, Zhang, XY & Yang, Y 2019, 'Design of Low-Loss Single-Pole Single-Throw and Single-Pole Double-Throw Filtering Switches Using Coaxial Resonators', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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© 2019 IEEE. In this paper, a single-pole single-throw (SPST) filtering switch and a single-pole double-throw (SPDT) filtering switch are designed using coaxial resonators. The ON- and OFF-states are achieved by controlling the PIN diodes embedded in the coaxial filter structures. For the SPST filtering switch, four PIN diodes are all turned off to achieve the ON-state, functioning as same as a conventional four-order coaxial filter, where the cross-coupling is employed to realize high-selectivity filtering responses. When the four PIN diodes are turned on, the SPDT switch works in the OFF-state. Capacitors are connected to the coaxial resonators to change the resonant frequencies of the resonators, thus the passband cannot be formed, resulting in a high isolation between the two ports. For demonstration, a SPST filtering switch is fabricated. Measured results show a low insertion loss of less than 1 dB and a high isolation of better than 60 dB. The excellent performance makes it attractive in wireless systems. Moreover, a SPDT filtering switch is also proposed. Compared with the state-of-the-art works using DR-based resonators, the proposed design shows a more compact size.

Li, L, Liu, Z, Zhang, J & Zhou, X 2019, 'Learn Image Object Co-segmentation with Multi-scale Feature Fusion', 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, IEEE Visual Communications and Image Processing, 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, Z, Zou, Y, Wang, G & Zhang, J 2019, 'Scale-Informed Density Estimation for Dense Crowd Counting', 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, IEEE Visual Communications and Image Processing, 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.

Lian, JW, Ban, YL, Zhu, H & Guo, YJ 2020, 'Uniplanar 2-D butler matrix for multibeam arrays', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. A 2-D Butler matrix (BM) in uniplanar configuration for designing multibeam array antenna (MAA) is proposed using substrate integrated waveguide (SIW) technology. Firstly, a novel topology for building uniplanar 2D BM is proposed, which successfully transforms the traditional 3-D topology to a 2-D (or uniplanar) one. To realize the planarization of basic components, a novel design of eight-port hybrid couplers, is developed to transform four spatially intersected couplers to a planar structure. To address the issue of excessive path intersections, a novel SIW eight-port crossover is proposed to reduce the number of path intersections from 16 to merely 4. Using this proposed 2-D BM, a 2-D MAA with 16 (4 × 4) beams can be realized.

Liao, Q, Wang, D, Holewa, H & Xu, M 2019, '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, W & Ziolkowski, RW 2020, 'A circularly polarized wireless power transfer system for internet-of-things (IoT) applications', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. A circularly polarized (CP) wireless power transfer (WPT) system is demonstrated. It consists of a high directivity, omnidirectional CP (OCP) antenna array and multiple electrically small Huygens CP (HCP) rectennas. The OCP array emits highly directional CP fields over the entire azimuthal plane. It acts as the wireless power source for charging or powering up surrounding IoT sensors. The OCP array is realized by cascading multiple vertical bars and helical loops to form a set of properly phased, collinear array of electric and magnetic dipoles. Wirelessly powered (WP) sensors are facilitated by combining sensors with HCP rectennas, the latter being a seamless integration of an electrically small HCP antenna with highly efficient rectifier circuits. Both systems were tested and achieved their predicted performance characteristics. These WP sensor systems are ideal candidates for wireless internet-of-things (IoT) applications, for example, in the food and agriculture industries, which are amongst the largest enterprises in Australia.

Lin, W & Ziolkowski, RW 2019, 'Development of Omnidirectional CP Antennas and Arrays: Invited', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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© 2019 IEEE. This paper summarizes the design concepts, operating principles, and application examples of advanced omnidirectional circularly polarized (OCP) antennas and arrays. The design of an OCP antenna with a figure eight-shaped pattern is introduced. It is realized by exciting two parallel-oriented electric and magnetic radiators with a 90° phase difference. The diameter of the loop current that generates the magnetic radiator is small, D approx {lambda}/10. As an applications example, a 28 GHz highly compact OCP antenna is reported for 5G Device-to-Device (D2D) communications. The design of an OCP antenna having a conical pattern is also discussed. The conical OCP pattern is realized when both the electric and magnetic radiators are placed above a ground plane. The diameter of the loop current is large, D approx 1 lambda. An example of a low profile and wideband OCP antenna radiating a conical pattern is demonstrated and its reconfigurable version is also discussed. Finally, an OCP array is presented that achieves high broadside directivity. It is based on an innovative method to realize collinear electric and magnetic radiators.

Lin, W & Ziolkowski, RW 2019, 'Internet-of-Things Sensors Wirelessly Powered by Electrically Small Huygens Dipole Rectenna', 2019 International Symposium on Antennas and Propagation, ISAP 2019 - Proceedings, 2019 International Symposium on Antennas and Propagation (ISAP), Xi'an, China, China.
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© 2019 Antenna Branch of Chinese Institute of Electronics. Internet-of-Things (IoT) sensors are expected to be ubiquitous in a future smart and sustainable society. Due to the exponential growth of device numbers, powering IoT devices by far field wireless power transfer (WPT) is becoming a necessary trend. This paper introduces two IoT sensors (light and temperature) that are wirelessly powered by a highly compact and efficient electrically small Huygens dipole rectenna. The entire system seamlessly integrates two subsystems. One is the metamaterial-inspired electrically small Huygens antenna that organically combines capacitively loaded loop (CLL) and Egyptian axe dipole (EAD) radiators together. The other is the sensor-augmented rectifier in which the output DC voltage varies as a function of the sensor impedance. The developed wirelessly powered systems can sense light or temperature levels and, when attached to an alarm, can send a warning signal if a threshold value is exceeded. Their prototypes were fabricated and tested. The measured results agree very well with their simulated values. The prototypes are highly compact and electrically small (ka = 0.73). They represent ideal candidates for many emerging IoT wireless sensor applications.

Lin, W & Ziolkowski, RW 2019, 'Wirelessly powered internet-of-things sensors facilitated by an electrically small egyptian axe dipole rectenna', Asia-Pacific Microwave Conference Proceedings, APMC, IEEE Asia-Pacific Microwave Conference, IEEE, Singapore, Singapore, pp. 891-892.
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© 2019 IEEE. Wirelessly powered Internet-of-Things (IoT) sensors have many unique advantages compared with wire-powered or battery-based sensors. This paper presents two wirelessly powered sensors (light and temperature) facilitated by a highly compact and efficient electrically small rectenna. The IoT sensor is integrated into the rectifier circuit of the rectenna, which converts the captured AC power to DC energy. The output DC voltage of the rectifier is dependent on the variable impedance of the sensor corresponding to different discerned values. Once an acoustic alarm is attached to this sensor-augmented rectenna, a certain amount of the measured parameter (light or temperature level) can activate the alarm. The receiving antenna of the system is a modified version of a metamaterial-inspired electrically small Egyptian axe dipole (EAD) antenna. By meandering the length of the driven element, inductive impedance was achieved to directly match the receiving antenna to the capacitive impedance of the rectifier circuit. Prototypes of the wirelessly powered light and temperature sensors were fabricated and measured. Experimental results successfully demonstrated the light and temperature sensing performance. Both systems are highly compact and very thin (diameter is 0.13 λ0 and thickness is 0.002 λ0) with a ka value equal to 0.47. They are excellent representatives of WPT-driven sensors for the emerging wireless IoT applications.

Lin, Z, Lv, T, Zhang, JA & Liu, RP 2019, '3D wideband mmwave localization for 5G massive MIMO systems', 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings, IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA.
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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.

Liu, Y, Liu, F, Qin, PY & Guo, YJ 2019, 'Recent development in nonuniformly spaced array synthesis methods', IEEE International Symposium on Phased Array Systems and Technology, IEEE International Symposium on Phased Array System & Technology, 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.

Luo, Y, Yan, B, Canning, J, Tafti, G, Wang, S, Wang, W, Tian, Y, Cook, K, Dhasarathan, V & Peng, GD 2019, 'A novel spun photonic crystal fibre with amoeba shape', Asia Communications and Photonics Conference, ACP, Asia Communications and Photonics Conference, IEEE, Chengdu, China.
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Asia Communications and Photonics Conference (ACP) © OSA 2019 A novel spun photonic crystal fibre with Amoeba shape has been fabricated based on asymmetric self-pressurization. Asymmetry growth dynamics with fibre drawing has been investigated.

Luo, Y, Zhang, JA, Ni, W, Pan, J & Huang, X 2019, 'Constrained Multibeam Optimization for Joint Communication and Radio Sensing', 2019 IEEE Global Communications Conference (GLOBECOM), 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.

Luu, V-H, Dao, M-S, Nguyen, TN-T, Perry, S & Zettsu, K 2019, 'Semi-supervised Convolutional Neural Networks for Flood Mapping using Multi-modal Remote Sensing Data', 2019 6th NAFOSTED Conference on Information and Computer Science, Hanoi, Vietnam.
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When floods hit populated areas, quick detection of flooded areas is crucial for initial response by local government, residents, and volunteers. Space-borne polarimetric synthetic aperture radar (PolSAR) is an authoritative data sources for flood mapping since it can be acquired immediately after a disaster even at night time or cloudy weather. Conventionally, a lot of domain-specific heuristic knowledge has been applied for PolSAR flood mapping, but their performance still suffers from confusing pixels caused by irregular reflections of radar waves. Optical images are another data source that can be used to detect flooded areas due to their high spectral correlation with the open water surface. However, they are often affected by day, night, or severe weather conditions (i.e., cloud). This paper presents a convolution neural network (CNN) based multimodal approach utilizing the advantages of both PolSAR and optical images for flood mapping. First, reference training data is retrieved from optical images by manual annotation. Since clouds may appear in the optical image, only areas with a clear view of flooded or non-flooded are annotated. Then, a semisupervised polarimetric-features-aided CNN is utilized for flood mapping using PolSAR data. The proposed model not only can handle the issue of learning with incomplete ground truth but also can leverage a large portion of unlabelled pixels for learning. Moreover, our model takes the advantages of expert knowledge on scattering interpretation to incorporate polarimetric-features as the input. Experiments results are given for the flood event that occurred in Sendai, Japan, on 12th March 2011. The experiments show that our framework can map flooded area with high accuracy (F1 = 96:12) and outperform conventional flood mapping methods.

Mahmud, K, Nizami, MSH, Ravishankar, J, Hossain, MJ & Siano, P 2018, 'Multiple Home-to-Home Energy Transactions for Peak Load Shaving', IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, IEEE International Conference on Environment and Electrical Engineering (EEEIC) / IEEE Industrial and Commercial Power Systems Europe (ICPS Europe), IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Univ Palermo, Palermo, ITALY, pp. 1074-1085.
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Mishra, DK, Jabbari Ghadi, M, Li, L & Zhang, J 2019, 'Proposing a framework for resilient active distribution systems using withstand, respond, adapt, and prevent element', 2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019, Australasian Universities Power Engineering Conference, 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.

Mohamadzade, B, Simorangkir, RBVB, Hashmi, RM & Esselle, KP 2020, 'A Low Profile, UWB Circular Patch Antenna with Monopole-Like Radiation Characteristics', 2020 International Workshop on Antenna Technology (iWAT), 2020 International Workshop on Antenna Technology (iWAT), IEEE.
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Nan, Y, Huang, X & Guo, YJ 2019, 'A Fast Piecewise Constant Doppler Algorithm for Generalized Continuous Wave Synthetic Aperture Radar', 2019 International Radar Conference (RADAR), International Radar Conference, 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.

Nanda, A, Nanda, P, Obaidat, M, He, X & Puthal, D 2019, 'A Novel Multi-Path Anonymous Randomized Key Distribution Scheme for Geo Distributed Networks', IEEE eXpress Conference Publishing, IEEE ComSoc, IEEE GLOBECOM, IEEE, Hilton Waikoloa Village, Hawaii, USA.
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A major concern in distributed networks is the ability to provide acceptable levels of security. This is achieved by using encryption and authentication mechanisms that depend on encryption keys. However, given the ever-expanding nature of the network, it is difficult to keep setting up authorities that can aid the key-exchange process. This paper presents a novel solution to the challenge of exchanging keys of a large, distributed network without the need to set up additional authorities. The key-exchange scheme presented takes advantage of features such as packet anonymity, random selection and a multi-path approach for the exchange process. The paper also discusses the effectiveness of the proposed scheme against various threat scenarios.

Nanda, P, arain, A & Nagar, U 2019, 'Network Packet Breach Detection using Cognitive Techniques', Smart Systems and IoT: Innovations in Computing, Second International Conference on Smart IoT Systems - Innovations in Computing (SSIC-2019), Springer, Jaipur, India.
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Machine learning approach is being extensively used in the area of cybersecurity in recent years developing solutions to protect Internet users. The use of state-based cognitive data and the increased prevalence of data mining has allowed for the amalgamation of statistical concepts with machine learning providing real-time network packet analysis with an aim to detect when an entity has intruded the network. In this paper, the use of mean squares error for packet payload aggregation, coupled with prediction techniques using Bayes and ensemble learning outputs to data clusters provide useful and important insight to generate hybrid solutions to existing data breach problems. The use of dynamic tolerance levels and countering this against the potential for false positives is central to the design of our proposed scheme. We believe that correlations between expected information against the aggregated payloads could provide sufficient level of accuracy, which is sufficient to flag certain packets for further human assessment.

Nguyen, C, Nguyen, D, Dinh, H, Pham, HA, Nguyen, H & Dutkiewicz, E 2020, 'Blockchain and stackelberg game model for roaming fraud prevention and profit maximization', IEEE Wireless Communications and Networking Conference (WCNC), Seoul.

Nguyen, DA, Bui, DH, Iacopi, F & Tran, XT 2019, 'An Efficient Event-driven Neuromorphic Architecture for Deep Spiking Neural Networks', International System on Chip Conference, IEEE International System-on-Chip Conference, 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, H, Dinh, H, Nguyen, D, Dutkiewicz, E & Mueck, M 2020, 'Defeating smart and reactive jammers with unlimited power', f IEEE Wireless Communications and Networking Conference (WCNC),, Seoul.

Nguyen, H, Nguyen, D, Dinh, H, Dutkiewicz, E, Mueck, M & Srikanteswara, S 2020, 'Defeating Jamming Attacks with Ambient Backscatter Communications', IEEE International Conference on Computing, Networking and Communications (ICNC), Hawaii.

Nguyen, HV, Nguyen, V-D, Dobre, OA, Nguyen, D, Dutkiewicz, E & Shin, O 2019, 'A Novel Spectral-Efficient Resource Allocation Approach for NOMA-Based Full-Duplex Systems', 2019 IEEE Global Communications Conference (GLOBECOM), IEEE Global Communications Conference, IEEE, Hawaii.
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This paper investigates the coexistence of non- orthogonal multiple access (NOMA) and full-duplex (FD), where the NOMA successive interference cancellation technique is applied simultaneously to both uplink (UL) and downlink (DL) transmissions in the same time-frequency resource block. Specifically, we jointly optimize the user association (UA) and power control to maximize the overall sum rate, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize the UL users' decoding order and the DL users' clustering, which results in a mixed-integer non- convex problem. For solving this problem, we first relax the binary variables to be continuous, and then propose a low-complexity design based on the combination of the inner convex approximation framework and the penalty method. Numerical results show that the proposed algorithm significantly outperforms the conventional FD-based schemes, FD-NOMA and its half-duplex counterpart with random UA.

Pham, MNT, Chaczko, Z & Hoang, D 2019, 'Realisation of congestion-aware energy-aware virtual link embedding', 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), International Telecommunication Networks and Applications Conference, 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.

Qureshi, S & Braun, R 2019, 'Mininet Topology: Mirror of the Optical Switch Fabric', 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), 2019 29th International Telecommunication Networks and Applications Conference (ITNAC), IEEE, New Zealand.
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Ren, L, Wang, F, Li, L, Liu, X & Zhang, Y 2019, 'Design Optimization of Distributed PV Power Station Based on the Efficiency Modelling and Analysis', 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), 2019 IEEE 4th International Future Energy Electronics Conference (IFEEC), IEEE, Singapore.
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Based on the large amount of data from a 3 MW distributed photovoltaic power station and a module-level experimental platform, the mathematical model of the performance ratio varying with the irradiation is established in this paper. The performance ratio value of the power station is 0.59, which is far below the engineering experience value. Therefore, the inverter efficiency, photovoltaic module efficiency and photovoltaic array efficiency are analyzed individually, and the focus is laid on the loss of performance ratio that caused by the voltage mismatch between the photovoltaic array and the maximum power point tracking of the inverter. In order to improve the performance ratio, the number of modules in series are designed and optimized. The research results are conducive to guide the optimal design of distributed photovoltaic power plants and significantly increase the power generation capacity.

Saputra, Y, Dinh, H, Nguyen, D & Dutkiewicz, E 2019, 'JOCAR: A Jointly Optimal Caching and Routing Framework for Cooperative Edge Caching Networks', 2019 IEEE Global Communications Conference (GLOBECOM), 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, Y, Dinh, H, Nguyen, D, Dutkiewicz, E, Mueck, M & Srikanteswara, S 2019, '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 machine learning techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These methods can learn and find the correlation of complex hidden features to improve the prediction accuracy. First, we propose an energy demand learning (EDL)-based prediction solution in which a charging station provider (CSP) gathers information from all charging stations (CSs) and then performs the EDL algorithm to predict the energy demand for the considered area. However, this approach requires frequent data sharing between the CSs and the CSP, thereby driving communication overhead and privacy issues for the EVs and CSs. To address this problem, we propose a federated energy demand learning (FEDL) approach which allows the CSs sharing their information without revealing real datasets. Specifically, the CSs only need to send their trained models to the CSP for processing. In this case, we can significantly reduce the communication overhead and effectively protect data privacy for the EV users. To further improve the effectiveness of the FEDL, we then introduce a novel clustering- based EDL approach for EV networks by grouping the CSs into clusters before applying the EDL algorithms. Through experimental results, we show that our proposed approaches can improve the accuracy of energy demand prediction up to 24.63% and decrease communication overhead by 83.4% compared with other baseline machine learning algorithms.

Shi, J, Brown, R, Yu, Z, Chu, L, Shi, Q & Xu, Z 2020, 'Tracking of Multiple Moving Objects Using Two Dimensional Beamforming Based on Crossed Array', Springer International Publishing.

Shi, T, Wang, F, Guo, H, Zhang, L & Li, L 2019, 'Distributed generations interconnection based on the clustering algorithm and graphy theory', 8th Renewable Power Generation Conference (RPG 2019), Renewable Power Generation Conference, IEEE, Shanghai, China.
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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.

Tao, Q, Luo, X, Wang, H & Xu, R 2019, 'Enhancing relation extraction using syntactic indicators and sentential contexts', Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 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 2019, 'Microgrid energy management system for academic building', 2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019, Australasian Universities Power Engineering Conference, 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 2019, '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.

Tran, VK, Saputra, Y, Dinh, H, Nguyen, LT, Nguyen, D, Nguyen, H & Dutkiewicz, E 2020, 'Collaborative learning model for cyberattack detection systems in IoT industry 4.0', IEEE Wireless Communications and Networking Conference (WCNC),, Seoul.

Trinh, AVT, Dinh, TMT, Nguyen, QT & Sandrasegaran, K 2020, 'Indoor positioning using BLE iBeacon, smartphone sensors, and distance-based position correction algorithm', Advances in Intelligent Systems and Computing, pp. 1007-1016.
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© Springer Nature Singapore Pte Ltd. 2020. In this paper, we propose a Bluetooth Low Energy (BLE) iBeacon-based localization system, in which we combine two popular positioning methods: Pedestrian Dead Reckoning (PDR) and fingerprinting. As we build the system as an application running on an iPhone, we choose Kalman filter as the fusion algorithm to avoid complex computation. In fingerprinting, a multi-direction-database approach is applied. Finally, in order to reduce the cumulative error of PDR due to smartphone sensors, we propose an algorithm called “Distance-based Position Correction”. The aim of this algorithm is to occasionally correct the estimated position by using the iBeacon nearest to the user. In experiments, our system results in an average error of only 0.63 m.

Uzair, M, Li, L, Zhu, JG & Eskandari, M 2019, 'A protection scheme for AC microgrids based on multi-agent system combined with machine learning', 2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019, Australasian Universities Power Engineering Conference, 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.

Vu, TV, Nguyen, D, Dinh, H & Dutkiewicz, E 2019, 'QoS-Aware Fog Computing Resource Allocation using Feasibility-Finding Benders Decomposition', 2019 IEEE Global Communications Conference (GLOBECOM), 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 2019, 'DeepText: Detecting text from the wild with multi-ASPP-assembled deeplab', Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, International Conference on Document Analysis and Recognition, 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.

Wu, J, Yao, L, Huang, Y, Xu, J, Wu, Q & Huang, L 2019, 'Improving Person Re-Identification Performance Using Body Mask Via Cross-Learning Strategy', 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, IEEE Visual Communications and Image Processing, 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, Y, Xu, Z, Gong, S, Xu, J, Hoang, DT & Niyato, D 2019, 'Backscatter-assisted hybrid relaying strategy for wireless powered IoT communications', 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings, IEEE Global Communications Conference, IEEE, Waikoloa, HI, USA.
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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.

Xu, Y, Xu, D, Hong, X, Ouyang, W, Ji, R, Xu, M & Zhao, G 2019, 'Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection', 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE/CVF International Conference on Computer Vision, 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.

Yang, L, Xu, JX, Zhang, XY & Cao, YF 2019, 'Compact Dual-Band Bandpass Filter Using Overlapped Helical Resonators', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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© 2019 IEEE. In this paper, we propose a compact dual-band bandpass filter using overlapped helical resonators. One helical resonator is placed inside of the other one to generate the two resonant frequencies for the two passbands. Thus, the circuit size of the two overlapped helical resonators is most the same as one resonator, resulting in significant size reduction. The filter topologies at the two operating frequencies are analyzed to obtain the desired filtering responses of the two passbands. Since the two overlapped helical resonators have no influence on the resonant frequencies to each other, the center frequencies of the two passbands can be controlled independently. To validate the proposed ideas, a dual-band bandpass filter is designed and the results are presented.

Yang, T, Ding, C, Ziolkowski, RW & Guo, YJ 2020, 'Achieving a terahertz photonic crystal fiber with enhanced birefrigence', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. A method to achieve a photonic crystal fiber (PCF) with high birefringence for polarization maintenance in short range THz communication systems is introduced in this paper. Rectangular air slots are etched in the core region of the fiber; they make the X-polarized (XP) and Y-polarized (YP) propagation modes have different propagation constants, thus leading to the higher birefringence. In contrast to the widely-used fully-slotted (FS) configuration in which the fiber core is almost fully occupied by air slots, the proposed PCF has a partially-slotted (PS) core. The air slot in the core center is absent; only the dielectric background is present. Comparisons are made between the fully-slotted and partially-slotted PCFs to illustrate that the PS PCF overperforms the FS PCF. After optimization, the PS PCF attains a high birefringence value of 0.069 and a total loss of 0.071 cm-1 at 1.0 THz. Over a broad 0.4 THz working band, from 0.53 to 0.93 THz, the dispersion is within 0.06 ps/THz/cm.

Yang, Y & Hu, Z 2019, 'Advanced Multifunctional Antennas for 5G and Beyond', 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall), 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall), IEEE, Xiamen, China.
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Advanced multifunctional antennas are capable of providing full flexibilities of frequency, polarization and radiation patterns, with possibly steerable beams, to satisfy the desired specifications in modern intelligent systems for applications of 5G communication, wearable systems, Internet of Things (IoT) and future sensing technologies. 5G antennas designed with advanced scalability and new materials are highly expected to cater such emerging applications. Recent advancement in materials and manufacturing techniques has demonstrated new directions of a possible mechanism for diverse future 5G mobile antennas. This paper presents the expected performance of the next generation antennas, the potential design challenges to be tackled, as well as the application scenarios for the future wireless systems. In addition, recent advancement in multifunctional antennas for future communications are also introduced and discussed. For demonstration, microwave lens antennas are presented, which are believed to be the game changer for 5G and beyond.

Yang, Y & Zhu, X 2019, 'Overview of Millimeter-Wave On-Chip and Off-Chip Bandpass Filter Designs', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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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, ZJ, Zhu, X, Che, W & Xue, Q 2019, 'A Millimeter-Wave Reconfigurable On-Chip Coupler With Tunable Power-Dividing Ratios in 0.13-mu m BiCMOS Technology', IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, IEEE NEWCAS Conference, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Munich, GERMANY, pp. 1516-1526.
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Yao, Q, Lu, D & Lei, G 2019, '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.

Zhong, Y, Huang, Y, Dutkiewicz, E, Wu, Q & Jiang, T 2020, 'Differential Evolution FPA-SVM for Target Classification in Foliage Environment Using Device-Free Sensing', Lecture Notes in Electrical Engineering, pp. 553-560.
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© 2020, Springer Nature Singapore Pte Ltd. Target classification in foliage environment is a challenging task in realistic due to the high-clutter background and unsettled weather. To detect a particular target, e.g., human, under such an environment, is an indispensable technique with significant application value. Traditional method such as computer vision techniques is hardly leveraged since the working condition is limited. Therefore, in this paper, we attempt to tackle human detection by using the radio frequency (RF) signal with a device-free sensing. To this end, we propose a differential evolution flower pollination algorithm support vector machine (DEFPA-SVM) approach to detect human among other targets, e.g., iron cupboard and wooden board. This task can be formally described as a target classification problem. In our experiment, the proposed DEFPA-SVM can effectively attain the best performance compared to other classical multi-target classification models and achieve a faster convergent speed than the traditional FPA-SVM.

Zhou, K, Luo, X, Wang, H & Xu, R 2019, 'Multi-task learning for relation extraction', Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, USA, pp. 1480-1487.
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© 2019 IEEE. Distantly supervised relation extraction leverages knowledge bases to label training data automatically. However, distant supervision may introduce incorrect labels, which harm the performance. Many efforts have been devoted to tackling this problem, but most of them treat relation extraction as a simple classification task. As a result, they ignore useful information that comes from related tasks, i.e., dependency parsing and entity type classification. In this paper, we first propose a novel Multi-Task learning framework for Relation Extraction (MTRE). We employ dependency parsing and entity type classification as auxiliary tasks and relation extraction as the target task. We learn these tasks simultaneously from training instances to take advantage of inductive transfer between auxiliary tasks and the target task. Then we construct a hierarchical neural network, which incorporates dependency and entity representations from auxiliary tasks into a more robust relation representation against the noisy labels. The experimental results demonstrate that our model improves the predictive performance substantially over single-task learning baselines.

Zhu, H & Guo, YJ 2020, 'Circularly-polarized differential antenna array fed by single-ended-to-balanced power dividers with high common-mode rejection', 2020 4th Australian Microwave Symposium, AMS 2020.
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© 2020 IEEE. This paper presents a differential feeding network comprising of a new type of single-ended-to-balanced power dividers with high level of common-mode rejection. The single-ended-to-balanced power dividers are built based on slotline-to-microstrip transitions, which are able to provide high commonmode suppression and low differential-mode-to-common-mode conversion levels. A wideband differential circularly-polarized (CP) antenna array is designed fabricated and tested using the differential feeding network. The experimental results verify that the presented differential feeding network can be used in feeding differential CP arrays to achieve high gain, symmetrical patterns and a wide axial ratio bandwidth.

Zhu, H & Guo, YJ 2019, 'Design of out-of-phase filtering power dividers using flexible coupling schemes', Asia-Pacific Microwave Conference Proceedings, APMC, IEEE Asia-Pacific Microwave Conference, 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, J, Yang, Y, Chu, C, Li, S, Liao, S & Xue, Q 2019, 'Mm-Wave Low-Profile Wideband Antenna Array Using Low-temperature Co-fired Ceramics (LTCC) Technique', 2019 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2019 - Proceedings, International Conference on Microwave and Millimeter Wave Technology, IEEE, Guangzhou, China.
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© 2019 IEEE. A low-profile wideband and high gain patch antenna array using low-temperature co-fired ceramics (LTCC) fabrication technique is proposed for 60-GHz applications. Coupled feeding scheme is adopted so that the antenna achieves wide impedance bandwidth that covers the entire 60-GHz license-free band with the height of only 0.384 mm (four tape layers). The shorting pin connecting the upper patch and ground imitates the virtual ac ground plane of differential feeding. This enables the antenna element to achieve good radiation performances including stable gain, symmetrical beam with low cross-polarization, which are comparable to those of the differential-driven patch antenna while the complex differential feeding network is not required. Antenna array prototype is fabricated and measured to verify the idea.

Nguyen, C, Saputra, Y, Nguyen, H, Nguyen, T, Tran, K, Bui, T, Nguyen, D, Dinh, H, Vu, T, Dutkiewicz, E, Chatzinotas, S & Ottersten, B arXiv 2020, Enabling and Emerging Technologies for Social Distancing during Pandemics like COVID-19: A Comprehensive Survey, Sydney.

Barlass, T & Thompson, A 2020, 'Transport for NSW investigating system outage amid 'hacking' fears', The Age.

Tan, S-L 2020, 'Australia targeted in ‘malicious’ cyberattack by state actor, PM Morrison says', South China Morning Post.

Thompson, A 2020, 'NSW government was warned over cyber security weaknesses', The Sydney Morning Herald.