Abbasi, MH, Taki, M, Rajabi, A, Li, L & Zhang, J 2019, 'Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach', APPLIED ENERGY, vol. 239, pp. 1294-1307.
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Abidi, S, Piccardi, M, Tsang, WH & Williams, M-A 2019, 'Well-M³N: A Maximum-Margin Approach to Unsupervised Structured Prediction', IEEE Transactions on Emerging Topics in Computational Intelligence.
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Unsupervised structured prediction is of fundamental importance for the clustering and classification of unannotated structured data. To date, its most common approach still relies on the use of structural probabilistic models and the expectation-maximization (EM) algorithm. Conversely, structural maximum-margin approaches, despite their extensive success in supervised and semi-supervised classification, have not raised equivalent attention in the unsupervised case. For this reason, in this paper we propose a novel approach that extends the maximum-margin Markov networks (M3N) to an unsupervised training framework. The main contributions of our extension are new formulations for the feature map and loss function of M3N that decouple the labels from the measurements and support multiple ground-truth training. Experiments on two challenging segmentation datasets have achieved competitive accuracy and generalization compared to other unsupervised algorithms such as k-means, EM and unsupervised structural SVM, and comparable performance to a contemporary deep learning-based approach.
Acuna, P, Rojas, CA, Baidya, R, Aguilera, RP & Fletcher, JE 2019, 'On the Impact of Transients on Multistep Model Predictive Control for Medium-Voltage Drives', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 34, no. 9, pp. 8342-8355.
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Akgun, B, Krunz, M & Ozan Koyluoglu, O 2019, 'Vulnerabilities of massive MIMO systems to pilot contamination attacks', IEEE Transactions on Information Forensics and Security, vol. 14, no. 5, pp. 1251-1263.
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© 2018 IEEE. We consider a single-cell massive multiple-input multiple-output (MIMO) system in which a base station (BS) with a large number of antennas transmits simultaneously to several single-antenna users. The BS acquires the channel state information (CSI) for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to pilot-contamination (PC) attacks. In our attack model, the attacker aims at minimizing the sum rate of downlink transmissions by contaminating the uplink pilots. We first study these attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the achievable individual secrecy rates under PC attacks and provide an upper bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%.
Al-soeidat, M, Lu, DDC & Zhu, J 2019, 'An Analog BJT-Tuned Maximum Power Point Tracking Technique for PV Systems', IEEE Transactions on Circuits and Systems II: Express Briefs.
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IEEE In this paper, an analog, BJT-tuned voltage reference maximum power point tracking (MPPT) method for photovoltaic (PV) modules is proposed. Conventional fixed voltage reference method is the simplest method for tracking, but it does not obtain good MPPT efficiency because the maximum power point (MPP) voltage changes at different insolation levels. In reality, an approximately linear slope is formed when connecting the MPPs measured from the highest insolation level to the lowest. Utilizing this characteristic, a bipolar junction transistor (BJT), which has a similar electrical property, is used to implement a variable voltage reference that improves the accuracy of the MPP voltage when the insolation changes. The proposed circuit is simple, easy to implement and it can track the maximum power point very quickly without the need for a digital controller or PID controller. Hence, the circuit’s cost and complexity are reduced. Experimental results are given to verify the feasibility of the proposed MPPT method.
Alturki, R & Gay, V 2019, 'The Development of An Arabic Weight Loss App ‘Akser Waznk’', JMIR Formative Research.
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Amiri, M, Tofigh, F, Shariati, N, Lipman, J & Abolhasan, M 2019, 'Miniature tri-wideband Sierpinski-Minkowski fractals metamaterial perfect absorber', IET MICROWAVES ANTENNAS & PROPAGATION, vol. 13, no. 7, pp. 991-996.
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Amjadipour, M, MacLeod, J, Lipton-Duffin, J, Tadich, A, Boeckl, JJ, Iacopi, F & Motta, N 2019, 'Electron effective attenuation length in epitaxial graphene on SiC.', Nanotechnology, vol. 30, no. 2, pp. 025704-025704.
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The inelastic mean free path (IMFP) for carbon-based materials is notoriously challenging to model, and moving from bulk materials to 2D materials may exacerbate this problem, making the accurate measurements of IMFP in 2D carbon materials critical. The overlayer-film method is a common experimental method to estimate IMFP by measuring electron effective attenuation length (EAL). This estimation relies on an assumption that elastic scattering effects are negligible. We report here an experimental measurement of electron EAL in epitaxial graphene on SiC using photoelectron spectroscopy over an electron kinetic energy range of 50-1150 eV. We find a significant effect of the interface between the 2D carbon material and the substrate, indicating that the attenuation length in the so-called 'buffer layer' is smaller than for free-standing graphene. Our results also suggest that the existing models for estimating IMFPs may not adequately capture the physics of electron interactions in 2D materials.
An, L, Cheng, T & Lu, DDC 2019, 'Single-Stage Boost-Integrated Full-Bridge Converter with Simultaneous MPPT, Wide DC Motor Speed Range and Current Ripple Reduction', IEEE Transactions on Industrial Electronics.
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IEEE This paper presents a new approach to controlling and optimizing single-stage boost-integrated full-bridge DC/DC converter for a stand-alone PV-battery powered DC motor system by combining pulse frequency modulation (PFM), pulse width modulation (PWM) and phase angle shift (PAS). Unlike most existing multiport DC/DC converters which aim at regulating the output voltage (first- or second-quadrant operation), the DC motor load requires both voltage and current reversals (four-quadrant operation). The converter is able to perform three tasks simultaneously, namely, maximum power point tracking (MPPT), battery charging/discharging and driving the DC motor at variable speeds including bi-directional and stall motions. To achieve these control objectives, the boost inductor and motor inductance operate in different modes such that pulse-frequency modulation (PFM) and pulse-width modulation (PWM) can be used to achieve MPPT and wide motor voltage range respectively. By properly adjusting the phase angle shift (PAS) of the duty cycles, the capacitor and battery RMS current value can be reduced while the operation of the converter remains unchanged, hence improving the conversion efficiency. Experimental results of a 26W laboratory prototype converter confirmed the proposed design and operation, and efficiency improvement by 2-6%.
Ansari, M, Zhu, H, Shariati, N & Guo, YJ 2019, 'Compact Planar Beamforming Array with End-Fire Radiating Elements for 5G Applications', IEEE Transactions on Antennas and Propagation.
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IEEE In this paper, a compact 4 × 6 Butler matrix (BM) based on microstrip lines is designed and applied to a linear antenna array. The proposed design creates four beams in four different directions within the 27.5 GHz and 28.5 GHz band. One of the advantages of this BM is a reduction in the size of the beamforming network (BFN). In order to attain this objective, the basic microstrip-based 4 × 4 BM is designed, and then modified to a 4 × 6 BM through a dual-substrate structure to avoid crossing lines using microstrip-to-slotline transitions. The BFN is cascaded with a 6-element linear antenna array with end-fire radiating elements. The array can be conveniently integrated into the BFN. The resulting design benefits from low loss characteristics, ease of realization, and low fabrication cost. The array is fabricated and tested, and the experimental results are in good agreement with the simulated ones. The multi-beam antenna size is 5.6λ×4.6λ including feed lines and feed network, while the new BM design is only 3.5λ0 × 1.4λ0, which is almost half as large as the traditional one. The measured radiation patterns show that the beams cover roughly a spatial range of 90° with a peak active gain of 11 dBi.
Armstrong, N, Sutton, GJ & Hibbert, DB 2019, 'Estimating probability density functions using a combined maximum entropy moments and Bayesian method. Theory and numerical examples', Metrologia, vol. 56, no. 1.
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© 2019 BIPM & IOP Publishing Ltd. Estimating the probability density function (pdf) from a limited sample of data is a challenging data analysis problem. Furthermore, determining which pdf best describes the available data involves an extra layer of complexity to the analysis, which if ignored, can have considerable consequences. We propose a combined maximum entropy (MaxEnt) moments and Bayesian model selection method to address this problem. The MaxEnt moments component is used to formulate a set of possible pdf models, each constrained by a different set of moments and parameterised by a set of Lagrangian multipliers. The Bayesian model selection component makes an inference about the most probable model, from the set of MaxEnt moment models. The structure of the prior pdf for the Lagrangian multipliers is determined from an expansion of the free energy functional for each MaxEnt model, and corresponding hyperparameters are calculated empirically. Numerical experiments were used to test the proposed method on samples taken from Gaussian and (more complex) non-Gaussian distributions, over a range of sample sizes. The results clearly demonstrate that the method can discriminate between simple and complex MaxEnt models for sample sizes approximately greater than 60. Our results demonstrate that MaxEnt and Bayesian methods are complementary. More critically, Bayesian inference is necessary when a set of competing MaxEnt models can be derived for a single dataset from a range of assumptions.
Awwad, S, Tarvade, S, Piccardi, M & Gattas, DJ 2019, 'The use of privacy-protected computer vision to measure the quality of healthcare worker hand hygiene', International Journal for Quality in Health Care, vol. 31, no. 1, pp. 36-42.
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(i) To demonstrate the feasibility of automated, direct observation and collection of hand hygiene data, (ii) to develop computer visual methods capable of reporting compliance with moment 1 (the performance of hand hygiene before touching a patient) and (iii) to report the diagnostic accuracy of automated, direct observation of moment 1.Observation of simulated hand hygiene encounters between a healthcare worker and a patient.Computer laboratory in a university.Healthy volunteers.Sensitivity and specificity of automatic detection of the first moment of hand hygiene.We captured video and depth images using a Kinect camera and developed computer visual methods to automatically detect the use of alcohol-based hand rub (ABHR), rubbing together of hands and subsequent contact of the patient by the healthcare worker using depth imagery.We acquired images from 18 different simulated hand hygiene encounters where the healthcare worker complied with the first moment of hand hygiene, and 8 encounters where they did not. The diagnostic accuracy of determining that ABHR was dispensed and that the patient was touched was excellent (sensitivity 100%, specificity 100%). The diagnostic accuracy of determining that the hands were rubbed together after dispensing ABHR was good (sensitivity 83%, specificity 88%).We have demonstrated that it is possible to automate the direct observation of hand hygiene performance in a simulated clinical setting. We used cheap, widely available consumer technology and depth imagery which potentially increases clinical application and decreases privacy concerns.
Azizivahed, A, Arefi, A, Ghavidel Jirsaraie, S, Shafie-khah, M, Li, L, Zhang, J & Catalao, JPS 2019, '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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Bah, AO, Qin, PY, Ziolkowski, RW, Guo, YJ & Bird, TS 2019, 'A Wideband Low-Profile Tightly Coupled Antenna Array with a Very High Figure of Merit', IEEE Transactions on Antennas and Propagation, vol. 67, no. 4, pp. 2332-2343.
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© 1963-2012 IEEE. A wideband, low-profile, tightly coupled antenna array with a simple feed network is presented. The dipole and feed networks in each unit cell are printed on both sides of a single RT/Duroid 6010 substrate with a relative dielectric constant of 10.2. The feed network, composed of meandered impedance transformer and balun sections, is designed based on Klopfenstein tapered microstrip lines. The wide-angle impedance matching is empowered by a novel wideband metasurface superstrate. For the optimum design, scanning to 70° along the E-plane is obtained together with a very high array figure of merit P A = 2.84. The H-plane scan extends to 55°. The broadside impedance bandwidth is 5.5:1 (0.80-4.38) GHz with an active voltage standing-wave ratio value ≤2. The overall height of the array above the ground plane is 0.088λ L, where λ L is the wavelength at the lowest frequency of operation. A prototype was fabricated and tested to confirm the design concepts.
Bautista, MG, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Dutkiewicz, E 2019, 'Compact Millimeter-Wave Bandpass Filters Using Quasi-Lumped Elements in 0.13-um (Bi)-CMOS Technology for 5G Wireless Systems', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 7, pp. 3064-3073.
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© 1963-2012 IEEE. A design methodology for a compact millimeter-wave on-chip bandpass filter (BPF) is presented in this paper. Unlike the previously published works in the literature, the presented method is based on quasi-lumped elements, which consists of a resonator with enhanced self-coupling and metal-insulator-metal capacitors. Thus, this approach provides inherently compact designs comparing with the conventional distributed elements-based ones. To fully understand the insight of the approach, simplified LC-equivalent circuit models are developed. To further demonstrate the feasibility of using this approach in practice, the resonator and two compact BPFs are designed using the presented models. All three designs are fabricated in a standard 0.13- \mu \text{m} (Bi)-CMOS technology. The measured results show that the resonator can generate a notch at 47 GHz with the attenuation better than 28 dB due to the enhanced self-coupling. The chip size, excluding the pads, is only 0.096 \times 0.294 mm2. In addition, using the resonator for BPF designs, the first BPF has one transmission zero at 58 GHz with a peak attenuation of 23 dB. The center frequency of this filter is 27 GHz with an insertion loss of 2.5 dB, while the return loss is better than 10 dB from 26 to 31 GHz. The second BPF has two transmission zeros, and a minimum insertion loss of 3.5 dB is found at 29 GHz, while the return loss is better than 10 dB from 26 GHz to 34 GHz. Also, more than 20-dB stopband attenuation is achieved from dc to 20.5 GHz and from 48 to 67 GHz. The chip sizes of these two BPFs, excluding the pads, are only 0.076\times 0.296 mm2 and 0.096\times 0.296 mm2, respectively.
Ben, X, Gong, C, Zhang, P, Jia, X, Wu, Q & Meng, W 2019, 'Coupled Patch Alignment for Matching Cross-View Gaits', IEEE Transactions on Image Processing, vol. 28, no. 6, pp. 3142-3157.
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© 1992-2012 IEEE. Gait recognition has attracted growing attention in recent years, as the gait of humans has a strong discriminative ability even under low resolution at a distance. Unfortunately, the performance of gait recognition can be largely affected by view change. To address this problem, we propose a coupled patch alignment (CPA) algorithm that effectively matches a pair of gaits across different views. To realize CPA, we first build a certain amount of patches, and each of them is made up of a sample as well as its intra-class and inter-class nearest neighbors. Then, we design an objective function for each patch to balance the cross-view intra-class compactness and the cross-view inter-class separability. Finally, all the local-independent patches are combined to render a unified objective function. Theoretically, we show that the proposed CPA has a close relationship with canonical correlation analysis. Algorithmically, we extend CPA to 'multi-dimensional patch alignment' that can handle an arbitrary number of views. Comprehensive experiments on CASIA(B), USF, and OU-ISIR gait databases firmly demonstrate the effectiveness of our methods over other existing popular methods in terms of cross-view gait recognition.
Ben, X, Gong, C, Zhang, P, Yan, R, Wu, Q & Meng, W 2019, 'Coupled Bilinear Discriminant Projection for Cross-view Gait Recognition', IEEE Transactions on Circuits and Systems for Video Technology.
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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, 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, 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, CBDP can learn the optimal matrix subspace where GEIs across views are aligned in both horizontal and vertical coordinates. Therefore, 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 CBDP are both monotonically increasing, so the convergence of CBDP is demonstrated. In 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, the encouraging performance is obtained by our method even in matching a lateral-view gait with a frontal-view gait.
Bobba, SS & Agrawal, A 2019, 'Author Correction: Ultra-broad Mid-IR Supercontinuum Generation in Single, Bi and Tri Layer Graphene Nano-Plasmonic waveguides pumping at Low Input Peak Powers (Scientific Reports, (2017), 7, 1, (10192), 10.1038/s41598-017-10141-3)', Scientific Reports, vol. 9, no. 1.
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© 2019, The Author(s). In the original version of this Article, Arti Agrawal was listed as corresponding author. Both authors now agree that Swetha S. Bobba should be considered the corresponding author. The PDF and HTML versions of the article have been modified to reflect this change.
Cai, Y, Xu, KD, Ma, Z & Liu, Y 2019, 'Compact bandstop filters using coupled lines and open/short stubs with multiple transmission poles', IET Microwaves, Antennas and Propagation, vol. 13, no. 9, pp. 1368-1372.
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© The Institution of Engineering and Technology 2019 A compact bandstop filter (BSF) using parallel-coupled lines and open stubs with four transmission poles (TPs) is proposed. Through theoretical equation deduction, the positions of these four TPs can be obtained. Good roll-off skirts and stopband suppression characteristics of the BSF can be realised with the help of multiple TPs. To improve transition band roll-off rates, another BSF with five TPs is designed, where a short-circuited T-stub is loaded on the middle of the above BSF circuit structure. For demonstration, two filter examples with centre frequencies at 2 and 1.8 GHz are implemented with generation of four and five TPs, respectively, for theoretically calculated certification. Good agreement between simulated and measured results validates the design method.
Chacon, A, Guatelli, S, Rutherford, H, Bolst, D, Mohammadi, A, Ahmed, A, Nitta, M, Nishikido, F, Iwao, Y, Tashima, H, Yoshida, E, Akamatsu, G, Takyu, S, Kitagawa, A, Hofmann, T, Pinto, M, Franklin, DR, Parodi, K, Yamaya, T, Rosenfeld, A & Safavi-Naeini, M 2019, 'Comparative study of alternative Geant4 hadronic ion inelastic physics models for prediction of positron-emitting radionuclide production in carbon and oxygen ion therapy', PHYSICS IN MEDICINE AND BIOLOGY, vol. 64, no. 15.
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Chacon, A, Safavi-Naeini, M, Bolst, D, Guatelli, S, Franklin, D, Iwao, Y, Akamatsu, G, Tashima, H, Yoshida, E, Nishikido, F, Kitagawa, A, Mohammadi, A, Gregoire, M-C, Yamaya, T & Rosenfeld, A 2019, 'Monte Carlo investigation of the characteristics of radioactive beams for heavy ion therapy', Scientific Reports, vol. 9, no. 1.
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This work presents a simulation study evaluating relative biological effectiveness at 10% survival fraction (RBE10) of several different positron-emitting radionuclides in heavy ion treatment systems, and comparing these to the RBE10s of their non-radioactive counterparts. RBE10 is evaluated as a function of depth for three positron-emitting radioactive ion beams (10C, 11C and 15O) and two stable ion beams (12C and 16O) using the modified microdosimetric kinetic model (MKM) in a heterogeneous skull phantom subject to a rectangular 50 mm × 50 mm × 60 mm spread out Bragg peak. We demonstrate that the RBE10 of the positron-emitting radioactive beams is almost identical to the corresponding stable isotopes. The potential improvement in PET quality assurance image quality which is obtained when using radioactive beams is evaluated by comparing the signal to background ratios of positron annihilations at different intra- and post-irradiation time points. Finally, the incidental dose to the patient resulting from the use of radioactive beams is also quantified and shown to be negligible.
Chen, G, Jin, Z, Liu, Y, Hu, Y, Zhang, J & Qing, X 2019, 'Programmable Topology Derivation of Integrated Three-Port DC-DC Converters with Reduced Switches for Low-Cost Applications', IEEE Transactions on Industrial Electronics.
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IEEE Thanks to the favorable advantage of low cost, integrated three-port dc-dc converters with reduced switches have attracted extensive attention. In order to provide more new topologies, this paper aims to propose a programmable topology derivation method, which effectively simplifies the cumbersome process of the conventional combination method. Instead of the manual connection and examination, the proposed alternative can quickly and rigorously derive multiple viable integrated three-port dc-dc topologies from a great number of possible connections with the aid of computer program. Besides, generalized analysis is also accomplished, with which performance characteristics of all derived converters are simultaneously obtained and then a comprehensive comparison can be easily conducted to select a preferred one for the practical application. Finally, an example specific application with one input and two outputs is given, with topology selection, design and experimental results demonstrated in detail.
Chen, SL, Karmokar, DK, Li, Z, Qin, PY, Ziolkowski, RW & Guo, YJ 2019, 'Circular-polarized substrate-integrated-waveguide leaky-wave antenna with wide-angle and consistent-gain continuous beam scanning', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4418-4428.
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© 2019 IEEE. Circularly polarized (CP) antennas are in high demand for use in future wireless communications. To advance the development of CP substrate-integrated-waveguide (SIW) leaky-wave antennas (LWAs) with the intent to meet this demand, a novel benzene-ring-shaped slot-loaded LWA with partially reflecting wall (PRW) vias is investigated and verified to realize wide-angle continuous beam scanning with consistent gain. The dispersion features of slot-loaded SIW LWAs with PRW vias are theoretically explored using an equivalent circuit model. The CP radiation feature is investigated numerically utilizing the E- A nd H-field distributions of an initial design and its equivalent magnetic currents. The results of these studies are used to demonstrate that improved CP performance over a wide-angle scan range can be attained with a change from a standard slot shape to a benzene-ring-shaped slot. The resulting benzene-ring-shaped slot-loaded CP SIW LWA was optimized, fabricated, and measured. The measured results verify that a CP beam was continuously scanned through a wide angle from backward to forward directions with a consistent gain. The prototype exhibits a continuous 97.1° CP beam scan with a gain variation between 8 and 11.3 dBic when the source frequency is swept from 9.35 to 11.75 GHz.
Chen, X, Kong, X, Xu, M, Sandrasegaran, K & Zheng, J 2019, 'Road Vehicle Detection and Classification Using Magnetic Field Measurement', IEEE ACCESS, vol. 7, pp. 52622-52633.
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Chen, X, Ni, W, Chen, T, Collings, I, Wang, X, Liu, RP & Giannakis, GB 2019, 'Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining', IEEE Transactions on Mobile Computing.
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IEEE Network Function Virtualization (NFV) can cost-efficiently provide network services by running different virtual network functions (VNFs) at different virtual machines (VMs) in a correct order. This can result in strong couplings between the decisions of the VMs on the placement and operations of VNFs. This paper presents a new fully decentralized online approach for optimal placement and operations of VNFs. Building on a new stochastic dual gradient method, our approach decouples the real-time decisions of VMs, asymptotically minimizes the time-average cost of NFV, and stabilizes the backlogs of network services with a cost-backlog tradeoff of [1], for any 0. Our approach can be relaxed into multiple timescales to have VNFs (re)placed at a larger timescale and hence alleviate service interruptions. While proved to preserve the asymptotic optimality, the larger timescale can slow down the optimal placement of VNFs. A learn-and-adapt strategy is further designed to speed the placement up with an improved tradeoff. Numerical results show that the proposed method is able to reduce the time-average cost of NFV by 23% and reduce the queue length (or delay) by 74%, as compared to existing benchmarks.
Chen, Z, Wong, H & Liu, Y 2019, 'A Polarizer Integrated Dielectric Resonator Antenna for Polarization Reconfigurability', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 67, no. 4, pp. 2723-2728.
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Cheng, H, Zhang, J, Wu, Q & An, P 2019, 'A computational model for stereoscopic visual saliency prediction', IEEE Transactions on Multimedia, vol. 21, no. 3, pp. 678-689.
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© 2018 IEEE. Depth information plays an important role in human vision as it provides additional cues that distinguish objects from their backgrounds. This paper explores depth information for analyzing stereoscopic saliency and presents a computational model that predicts stereoscopic visual saliency based on three aspects of human vision: 1) the pop-out effect; 2) comfort zones; and 3) background effects. Through an analysis of these three phenomena, we find that most of the stereoscopic saliency region can be explained. Our model comprises three modules, each describing one aspect of saliency distribution, and a control function that can be used to adjust the three models independently. The relationship between the three models is not mutually exclusive. One, two, or three phenomena may appear in one image. Therefore, to accurately determine which phenomena the image conforms to, we have devised a selection strategy that chooses the appropriate combination of models based on the content of the image. Our approach is implemented within a framework based on the multifeature analysis. The framework considers surrounding regions, color/depth contrast, and points of interest. The selection strategy can improve the performance of the framework. A series of experiments on two recent eye-tracking datasets shows that our proposed method outperforms several state-of-the-art saliency models.
Cheng, Q, Nguyen, D, Dutkiewicz, E & Mueck, M 2019, 'Preserving Honest/Dishonest Users' Operational Privacy with Blind Interference Calculation in Spectrum Sharing System', IEEE Transactions on Mobile Computing (TMC).
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Cheng, Q, Shi, Z, Nguyen, D & Dutkiewicz, E 2019, 'Sensing OFDM Signal: A Deep Learning Approach', IEEE Transactions on Communications (TCOM).
Cheng, Z, Xiong, G, Liu, Y, Zhang, T, Tian, J & Guo, YJ 2019, 'High-efficiency Doherty power amplifier with wide OPBO range for base station systems', IET Microwaves, Antennas and Propagation, vol. 13, no. 7, pp. 926-929.
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© The Institution of Engineering and Technology 2019. A high-efficiency, S-band Doherty power amplifier (DPA) with wide output power back-off (OPBO) range is presented. A novel parasitic capacitance compensation approach is applied at the output of Cree's GaN high-electron-mobility transistor to achieve high saturation efficiency in a wide OPBO range. Specifically, a parallel shorting microstrip line between the transistor output and its match network is adopted to realise parasitic capacitance compensation. The measurement results indicate good Doherty behaviour with 10 dB back-off efficiency of 40.6-44.2% and saturation efficiency of 70.2-73.3% over 2.9-3.3 GHz. When stimulated by a 20-MHz LTE signal with 7.5 dB PAPR, the proposed Doherty amplifier power, combined with digital predistortion, achieved adjacent channel leakage ratios below -47.2 dBc. The DPA demonstrate superior performance in OPBO range and efficiency, which makes it an ideal component for base station communication systems.
Chomsiri, T, He, XS, Nanda, P & Tan, Z 2019, '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, L, Shi, J & Braun, R 2019, 'The equivalent Young's modulus prediction for vacancy defected graphene under shear stress', PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES, vol. 110, pp. 115-122.
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Cui, Q, Gong, Z, Ni, W, Hou, Y, Chen, X, Tao, X & Zhang, P 2019, 'Stochastic Online Learning for Mobile Edge Computing: Learning from Changes', IEEE Communications Magazine, vol. 57, no. 3, pp. 63-69.
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© 1979-2012 IEEE. ML has been increasingly adopted in wireless communications, with popular techniques, such as supervised, unsupervised, and reinforcement learning, applied to traffic classification, channel encoding/ decoding, and cognitive radio. This article discusses a different class of ML technique, stochastic online learning, and its promising applications to MEC. Based on stochastic gradient descent, stochastic online learning learns from the changes of dynamic systems (i.e., the gradient of the Lagrange multipliers) rather than training data, decouples tasks between time slots and edge devices, and asymptotically minimizes the time-averaged operational cost of MEC in a fully distributed fashion with the increase of the learning time. By taking the widely adopted big data analytic framework MapReduce as an example, numerical studies show that the network throughput can increase by eight times through adopting stochastic online learning as compared to existing offline implementations.
Dai, M, Cheng, S, He, X & Wang, D 2019, 'Object tracking in the presence of shaking motions', Neural Computing and Applications, pp. 1-18.
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© 2018 The Natural Computing Applications Forum Visual tracking can be particularly interpreted as a process of searching for targets and optimizing the searching. In this paper, we present a novel tracker framework for tracking shaking targets. We formulate the underlying geometrical relevance between a search scope and a target displacement. A uniform sampling among the search scopes is implemented by sliding windows. To alleviate any possible redundant matching, we propose a double-template structure comprising of initial and previous tracking results. The element-wise similarities between a template and its candidates are calculated by jointly using kernel functions which provide a better outlier rejection property. The STC algorithm is used to improve the tracking results by maximizing a confidence map incorporating temporal and spatial context cues about the tracked targets. For better adaptation to appearance variations, we employ a linear interpolation to update the context prior probability of the STC method. Both qualitative and quantitative evaluations are performed on all sequences that contain shaking motions and are selected from the OTB-50 challenging benchmark. The proposed approach is compared with and outperforms 12 state-of-the-art tracking methods on the selected sequences while running on MATLAB without code optimization. We have also performed further experiments on the whole OTB-50 and VOT 2015 datasets. Although the most of sequences in these two datasets do not contain motion blur that this paper is focusing on, the results of our method are still favorable compared with all of the state-of-the-art approaches.
Dang, C, Zhang, J, Kwong, C-P & Li, L 2019, 'Demand Side Load Management for Big Industrial Energy Users under Blockchain-Based Peer-to-Peer Electricity Market', IEEE Transactions on Smart Grid.
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Dang, D, Hoang, D & Nguyen, D 2019, 'Trust-based Scheduling Framework for Big Data Processing with MapReduce', IEEE Transactions on Services Computing (TSC).
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Dinh, TH, Phung, MD & Ha, QP 2019, 'Summit Navigator: A Novel Approach for Local Maxima Extraction', IEEE Transactions on Image Processing, pp. 1-1.
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Duan, N, Xu, W, Wang, S & Zhu, J 2019, 'Quasi-3-D Cylindrical Coordinate XFEM Model of HTS Cable', IEEE TRANSACTIONS ON MAGNETICS, vol. 55, no. 6.
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Duan, P, Mao, G, Liang, W & Zhang, D 2019, 'A Unified Spatio-Temporal Model for Short-Term Traffic Flow Prediction', IEEE Transactions on Intelligent Transportation Systems.
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IEEE This paper proposes a unified spatio-temporal model for short-term road traffic prediction. The contributions of this paper are as follows. First, we develop a physically intuitive approach to traffic prediction that captures the time-varying spatio-temporal correlation between traffic at different measurement points. The spatio-temporal correlation is affected by the road network topology, time-varying speed, and time-varying trip distribution. Distinctly different from previous black-box approaches to road traffic modeling and prediction, parameters of the proposed approach have physically intuitive meanings which make them readily amendable to suit changing road and traffic conditions. Second, unlike some existing techniques that capture the variation of spatio-temporal correlation by a complete re-design and calibration of the model, the proposed approach uses a unified model that incorporates the physical factors potentially affecting the variation of spatio-temporal correlation into a series of parameters. These parameters are relatively easy to control and adjust when road and traffic conditions change, thereby greatly reducing the computational complexity. Experiments using two sets of real traffic traces demonstrate that the proposed approach has superior accuracy compared with the widely used space-time autoregressive integrated moving average (STARIMA) and the back propagation neural network approaches, and is only marginally inferior to that obtained by constructing multiple STARIMA models for different times of the day, however, with a much reduced computational and implementation complexity.
Eskandari, M & Li, L 2019, 'Microgrid operation improvement by adaptive virtual impedance', IET Renewable Power Generation, vol. 13, no. 2, pp. 296-307.
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© The Institution of Engineering and Technology 2018.. Microgrids (MGs) are regarded as the best solution for optimal integration of the renewable energy sources into power systems. However, novel control strategies should be developed because of the distinct inherent feature of MG components in comparison to conventional power systems. Although the droop-based control method is adopted in the MG to share power among distributed generation units, its dependency to grid parameters makes its implementation not as convenient as that in conventional power systems. Virtual impedance has been proposed as the complementary part of droop control in MGs. In this study, adaptive virtual impedance is designed considering its effects on the system performance in the MG including: (i) decoupling active and reactive power control by making the grid X/R ratio high, (ii) maximum transferable power through the feeder, (iii) stability concern and (iv) precise reactive power sharing in different operating modes as well as smooth transition from connected mode to islanded mode (IM). To this end, a novel method is proposed to determine the reactive power reference of distributed generation (DG) units according to their contribution in reactive power sharing in IM. In addition, simulation in MATLAB/Simulink environment is conducted to assess the performance of the control system.
Eskandari, M, Li, L, Moradi, MH & Siano, P 2019, 'A nodal approach based state-space model of droop-based autonomous networked microgrids', Sustainable Energy, Grids and Networks, vol. 18.
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© 2019 Elsevier Ltd As the requirement of expensive and unreliable high band-width communication infrastructure is obviated, decentralized droop-like control method has been considered for power sharing implementation in autonomous microgrids (MGs). To this end, the power network is regarded as a communication link and voltage variables (magnitude and frequency) as control signals. This, however, reduces the stability margin of islanded MGs due to the interaction of droop controllers through the power network. Lack of inertia of droop-controlled power converters and low X/R ratio of interconnecting power lines intensify this interaction which may lead to the instability of Networked MGs (NMG). On the other hand, the existing parallel-based small signal model of MGs is inadequate to represent this interaction, as the adopted common-based reference frame (RF) is not applicable in islanded NMGs. This issue is investigated in this work in details and, inspired from power flow equations, a local RF is proposed to improve the small-signal model accuracy. Droop controllers are also correlated through the power flow equations to properly model their interaction through the power network. Moreover, the state-space model is developed in a fully decentralized approach which does not rely on any converter for any specific role. Eigenvalue analysis and simulation in MATLAB\SIMULINK platforms are executed to evaluate the effectiveness and accuracy of the proposed model.
Esmaili, N, Norman, BA & Rajgopal, J 2019, 'Exact analysis of (R, s, S) inventory control systems with lost sales and zero lead time', NAVAL RESEARCH LOGISTICS, vol. 66, no. 2, pp. 123-132.
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Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2019, 'Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models (vol 13, e0206274, 2018)', PLOS ONE, vol. 14, no. 4.
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Fan, Y, Lin, X, Liang, W, Tan, G & Nanda, P 2019, 'A secure privacy preserving deduplication scheme for cloud computing', Future Generation Computer Systems, vol. 101, pp. 127-135.
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Farhadian, F, Kashani, MMR, Rezazadeh, J, Farahbakhsh, R & Sandrasegaran, K 2019, 'WITHDRAWN: An efficient IoT cloud energy consumption based on genetic algorithm', Digital Communications and Networks.
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Feng, X, Hormuth, DA & Yankeelov, TE 2019, 'An adjoint-based method for a linear mechanically-coupled tumor model: Application to estimate the spatial variation of murine glioma growth based on diffusion weighted magnetic resonance imaging.', Comput Mech, vol. 63, no. 2, pp. 159-180.
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We present an efficient numerical method to quantify the spatial variation of glioma growth based on subject-specific medical images using a mechanically-coupled tumor model. The method is illustrated in a murine model of glioma in which we consider the tumor as a growing elastic mass that continuously deforms the surrounding healthy-appearing brain tissue. As an inverse parameter identification problem, we quantify the volumetric growth of glioma and the growth component of deformation by fitting the model predicted cell density to the cell density estimated using the diffusion-weighted magnetic resonance imaging (DW-MRI) data. Numerically, we developed an adjoint-based approach to solve the optimization problem. Results on a set of experimentally measured, in vivo rat glioma data indicate good agreement between the fitted and measured tumor area and suggest a wide variation of in-plane glioma growth with the growth-induced Jacobian ranging from 1.0 to 6.0.
Gao, X, Du, J, Zhang, T & Guo, YJ 2019, 'High-T c Superconducting Fourth-Harmonic Mixer Using a Dual-Band Terahertz On-Chip Antenna of High Coupling Efficiency', IEEE Transactions on Terahertz Science and Technology, vol. 9, no. 1, pp. 55-62.
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© 2019 IEEE. This paper presents a dual-band on-chip antenna-coupled high-T c superconducting (HTS) Josephson-junction subterahertz (THz) fourth-harmonic mixer. The antenna utilizes a couple of different structured twin slots to enable the resonant radiations at two frequencies, and integrates a well-designed coplanar waveguide network for achieving good radiation coupling and signal isolation characteristics. The electromagnetic simulations show that coupling efficiencies as high as -4 and -3.5 dB are achieved for the 160- and 640-GHz operating frequency bands, respectively. Based on this dual-band antenna, a 640-GHz HTS fourth-harmonic mixer is developed and characterized in a range of operating temperatures. The mixer exhibits a measured conversion gain of around -18 dB at 20 K and -22 dB at 40 K, respectively. The achieved intermediate frequency bandwidth is larger than 23 GHz. These are the best results reported for HTS harmonic mixers at comparable sub-THz frequency bands to date.
Gay, VC, Garcia, JA & Leong, TW 2019, 'Using Asynchronous Exergames to Encourage an Active Ageing Lifestyle: Solitaire Fitness Study Protocol.', Studies in health technology and informatics, vol. 266, pp. 70-75.
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A healthy and active lifestyle can significantly improve the well-being and quality of life; however, some elderly people struggle to stay motivated and engaged with any form of exercise. The project Elaine (Elderly, AI and New Experiences) addresses this problem by seeking to improve the quality of life of the elderly through exergames. Currently, the project explores a novel approach in the field of health informatics called asynchronous exergaming. This approach, a new trend in games in the health domain, allows the elderly to workout at their own pace, and in their own time, with their physical activity linked asynchronously to a game. This paper presents the study protocol for Solitaire Fitness, a new asynchronous exergame developed by the team. The game aims at increasing the motivation of the elderly to engage in physical exercise whilst helping to maintain their cognitive abilities. It also describes the protocol for the trial. The result of this research has the potential to benefit elderly that need nudging to be motivated to exercise, health care providers treating people with sedentary lifestyles and researchers investigating ways to encourage the elderly to exercise.
Ge, X, Tu, S, Mao, G, Lau, V & Pan, L 2019, 'Cost Efficiency Optimization of 5G Wireless Backhaul Networks', IEEE Transactions on Mobile Computing.
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IEEE The wireless backhaul network provides an attractive solution for the urban deployment of fifth generation (5G) wireless networks that enables future ultra dense small cell networks to meet the everincreasing user demands. Optimal deployment and management of 5G wireless backhaul networks is an interesting and challenging issue. In this paper we propose the optimal gateways deployment and wireless backhaul route schemes to maximize the cost efficiency of 5G wireless backhaul networks. In generally, the changes of gateways deployment and wireless backhaul route are presented in different time scales. Specifically, the number and locations of gateways are optimized in the long time scale of 5G wireless backhaul networks. The wireless backhaul routings are optimized in the short time scale of 5G wireless backhaul networks considering the time-variant over wireless channels. Numerical results show the gateways and wireless backhaul route optimization significantly increases the cost efficiency of 5G wireless backhaul networks. Moreover, the cost efficiency of proposed optimization algorithm is better than that of conventional and most widely used shortest path (SP) and Bellman-Ford (BF) algorithms in 5G wireless backhaul networks.
Geng, J, Ziolkowski, RW, Wang, K, Zhao, X, Zhou, H, Chenhu, G, Liang, X & Jin, R 2019, 'Dual CP Polarization Diversity and Space Diversity Antennas Enabled by a Compact T-Shaped Feed Structure', IEEE Access, vol. 7, pp. 96284-96296.
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© 2013 IEEE. A compact T-shaped feed structure (TFS) is reported that enables the realization of two types of diversity antennas: a polarization diversity antenna (PDA) and a spatial diversity antenna (SDA). Both systems have a high potential for mobile wireless communication applications. The TFS includes four ports and two independent coaxial channels with effective isolation between them all. The PDA is a dual CP omnidirectional antenna. Its optimized prototype achieves measured impedance bandwidths of 16.4% and 15.28% in its LHCP and RHCP states, respectively, and realized gains in both between 4.8 and 6.46 dBic. The inner thin coaxial cable (ITCC) of the TFS directly drives its LHCP subsystem, facilitating its improved omnidirectional performance. This ITCC is also used to directly feed the SDA's low-profile directional planar equiangular spiral antenna and its side port drives its omnidirectional RHCP antenna. Good hemispherical coverage is realized with a measured common impedance bandwidth larger than 14.35% with more than 40-dB isolation between its two ports. The corresponding measured realized gain of the SDA is between 4 and 7.8 dBic. The measured results for both optimized prototypes confirm their simulated performance characteristics.
Ghadi, MJ, Ghavidel, S, Rajabi, A, Azizivahed, A, Li, L & Zhang, J 2019, 'A review on economic and technical operation of active distribution systems', Renewable and Sustainable Energy Reviews, vol. 104, pp. 38-53.
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© 2019 Elsevier Ltd Along with the advent of restructuring in power systems, considerable integration of renewable energy resources has motivated the transition of traditional distribution networks (DNs) toward new active ones. In the meanwhile, rapid technology advances have provided great potentials for future bulk utilization of generation units as well as the energy storage (ES) systems in the distribution section. This paper aims to present a comprehensive review of recent advancements in the operation of active distribution systems (ADSs) from the viewpoint of operational time-hierarchy. To be more specific, this time-hierarchy consists of two stages, and at the first stage of this time-hierarchy, four major economic factors, by which the operation of traditional passive DNs is evolved to new active DNs, are described. Then the second stage of the time-hierarchy refers to technical management and power quality correction of ADSs in terms of static, dynamic and transient periods. In the end, some required modeling and control developments for the optimal operation of ADSs are discussed. As opposed to previous review papers, potential applications of devices in the ADS are investigated considering their operational time-intervals. Since some of the compensating devices, storage units and generating sources may have different applications regarding the time scale of their utilization, this paper considers real scenario system operations in which components of the network are firstly scheduled for the specified period ahead; then their deviations of operating status from reference points are modified during three time-intervals covering static, dynamic and transient periods.
Ghadi, MJ, Rajabi, A, Ghavidel, S, Azizivahed, A, Li, L & Zhang, J 2019, 'From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors', Applied Energy, vol. 253.
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© 2019 Elsevier Ltd Restructuring of power systems along with the integration of renewable energy resources in electricity networks have transformed traditional distribution networks (DNs) into new active distribution systems (ADSs). In addition, rapid advancement of technology has enabled the bulk utilization of power generation units and energy storage (ES) systems in distribution networks. The next step in this trend is to decentralize ADSs to microgrids (MGs). This paper aims to present a review on the recent advancements in the development of ADSs and MGs. In this respect, the regulatory requirements and economic concepts, by which the traditional passive DNs are evolved into ADSs, are categorized and illustrated first. Then, the state-of-the-art of ADS formation is detailed based on the novel standpoint of grid operation factors which are involved in deregulated electricity markets at the distribution level. After presenting highlighted projects of MGs across the world, a similar review approach has been adopted to explain the formation of MGs which play a vital role in the decentralization of ADSs. This survey can provide both policy makers and distribution system planners with new perspectives to establish or participate in day-ahead wholesale markets.
Ghasemi, M, Akbari, E, Rahimnejad, A, Razavi, SE, Ghavidel, S & Li, L 2019, 'Phasor particle swarm optimization: a simple and efficient variant of PSO', Soft Computing.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Particle swarm optimizer is a well-known efficient population and control parameter-based algorithm for global optimization of different problems. This paper focuses on a new and primary sample for PSO, which is named phasor particle swarm optimization (PPSO) and is based on modeling the particle control parameters with a phase angle (θ), inspired from phasor theory in the mathematics. This phase angle (θ) converts PSO algorithm to a self-adaptive, trigonometric, balanced, and nonparametric meta-heuristic algorithm. The performance of PPSO is tested on real-parameter optimization problems including unimodal and multimodal standard test functions and traditional benchmark functions. The optimization results show good and efficient performance of PPSO algorithm in real-parameter global optimization, especially for high-dimensional optimization problems compared with other improved PSO algorithms taken from the literature. The phasor model can be used to expand different types of PSO and other algorithms. The source codes of the PPSO algorithms are publicly available at https://github.com/ebrahimakbary/PPSO.
Ghavidel Jirsaraie, S, Jabbari Ghadi, M, Vahed, AA, Aghaei, J, Li, L & Zhang, J 2019, 'Risk-Constrained Bidding Strategy for a Joint Operation of Wind Power and Compressed Air Energy Storage Aggregators', IEEE Transactions on Sustainable Energy, pp. 1-1.
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Ghavidel, S, Rajabi, A, Ghadi, MJ, Azizivahed, A, Li, L & Zhang, J 2019, 'Risk-constrained demand response and wind energy systems integration to handle stochastic nature and wind power outage', IET Energy Systems Integration, vol. 1, no. 2, pp. 114-120.
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Ghosh, SS, Nathan, KS, Siwakoti, YP & Long, T 2019, 'Dual polarity DC–DC converter integrated grid-tied single-phase transformer less inverter for solar application', The Journal of Engineering, vol. 2019, no. 17, pp. 3962-3966.
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Golsorkhi Esfahani, MS, Shafiee, Q, Lu, DDC & Guerrero, JM 2019, 'Distributed Control of Low-Voltage Resistive AC Microgrids', IEEE Transactions on Energy Conversion.
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IEEE This paper proposes a distributed control strategy for coordination of distributed energy resources (DERs) in low-voltage resistive microgrids. The proposed framework consists of two level structure; primary and secondary control. Unlike the existing distributed control solutions, the proposed method is based upon the practical assumption of resistive network impedance. The primary control level consists of a V-I droop mechanism, where GPS timing is used to synchronize the control agents. A consensus-based distributed secondary control method is introduced to improve the voltage regulation and load sharing accuracy of the V-I droop method. In the proposed approach, the d-axis component of the voltage is altered so as to regulate the average microgrid voltage to the rated value while guarantying proper sharing of active power among the DERs. Additionally, the q-axis component of voltage is adjusted to perform proper current and, accordingly reactive power sharing. The proposed control methodology accounts for the distribution line impedances. It features a plug-and-play environment; prior system knowledge is not required, and an arbitrary DER can enter the microgrid without any need for additional synchronization. An AC microgrid is prototyped to experimentally demonstrate the efficacy of the proposed method.
Gong, R-J, Ban, Y-L, Lian, J-W, Liu, Y & Nie, Z 2019, 'Circularly Polarized Multibeam Antenna Array of ME Dipole Fed by 5 x 6 Butler Matrix', IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, vol. 18, no. 4, pp. 712-716.
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Gong, S, Gao, L, Xu, J, Guo, Y, Hoang, DT & Niyato, D 2019, 'Exploiting Backscatter-Aided Relay Communications with Hybrid Access Model in Device-to-Device Networks', IEEE Transactions on Cognitive Communications and Networking.
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IEEE The backscatter and active RF radios can complement each other and bring potential performance gain. In this paper, we envision a dual-mode radio structure that allows each device to make smart decisions on mode switch between backscatter communications (i.e., the passive mode) or RF communications (i.e., the active mode), according to the channel and energy conditions. The flexibility in mode switching also makes it more complicated for transmission control and network optimization. To exploit the radio diversity gain, we consider a wireless powered device-to-device network of hybrid radios and propose a sum throughput maximization by jointly optimizing energy beamforming and transmission scheduling in two radio modes. We further exploit the user cooperation gain by allowing the passive radios to relay for the active radios. As such, the sum throughput maximization is reformulated into a non-convex. We first present a sub-optimal algorithm based on successive convex approximation, which optimizes the relays’ reflection coefficients by iteratively solving semi-definite programs. We also devise a set of heuristic algorithms with reduced computational complexity, which are shown to significantly improve the sum throughput and amenable for practical implementation.
Guo, K & Guo, Y 2019, 'Key Parameter Design and Analysis of Flux Reversal Linear Rotary Permanent Magnet Actuator', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 29, no. 2.
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Guo, L, Zhu, H & Abbosh, A 2019, 'Phase reconfigurable microwave power divider', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 1, pp. 21-25.
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© 2004-2012 IEEE. A reconfigurable power divider (PD) that can operate either in an in-phase mode or out-of-phase mode is presented. To that end, the novel concept of using tunable phase shifter, which is a reflection-type loaded coupled lines, to emulate an effective variable length transmission line (TL) is utilized. The proposed PD uses a quarter-wavelength TL, a 100 Ω isolation resistor and two tunable phase shifters. The presented theoretical analysis shows that by properly selecting the parameters of the phase shifter, it can be used to approximate the performance of variable length TL. To validate the design, a prototype of dimensions 50 mm × 25 mm is built, using Rogers RO3010 substrate, and tested. The results indicate that the device can operate as an in-phase and out-of-phase by using suitable biasing voltages. Across the band 0.9-1.1 GHz, the device has more than 12 dB return loss at all the ports and more than 15 dB isolation between the two output ports with less than 5° phase deviation for both of the in-phase and out-of-phase states.
Gurjar, DS, Nguyen, HH & Tuan, HD 2019, 'Wireless Information and Power Transfer for IoT Applications in Overlay Cognitive Radio Networks', IEEE Internet of Things Journal.
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IEEE This paper proposes and investigates an overlay spectrum sharing system in conjunction with the simultaneous wireless information and power transfer (SWIPT) to enable communications for the Internet of Things (IoT) applications. Considered is a cooperative cognitive radio network, where two IoT devices (IoDs) exchange their information and also provide relay assistance to a pair of primary users (PUs). Different from most existing works, in this paper, both IoDs can harvest energy from the radio-frequency (RF) signals received from the PUs. By utilizing the harvested energy, they provide relay cooperation to PUs and realize their own communications. For harvesting energy, a time-switching (TS) based approach is adopted at both IoDs. With the proposed scheme, one round of bidirectional information exchange for both primary and IoT systems is performed in four phases, i.e., one energy harvesting (EH) phase and three information processing (IP) phases. Both IoDs rely on the decode-and-forward operation to facilitate relaying, whereas the PUs employ selection combining (SC) technique. For investigating the performance of the considered network, this paper first provides exact expressions of user outage probability (OP) for the primary and IoT systems under Nakagami-m fading. Then, by utilizing the expressions of user OP, the system throughput and energy efficiency are quantified together with the average end-to-end transmission time. Numerical and simulation results are provided to give useful insights into the system behavior and to highlight the impact of various system/channel parameters.
Ha, QP, Yen, L & Balaguer, C 2019, 'Robotic autonomous systems for earthmoving in military applications', Automation in Construction, vol. 107, pp. 102934-102934.
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Haider, N, Ali, A, Suarez-Rodriguez, C & Dutkiewicz, E 2019, 'Optimal Mode Selection for Full-Duplex Enabled D2D Cognitive Networks', IEEE ACCESS, vol. 7, pp. 57298-57311.
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Han, F, Zhuo, J, Liu, N, Liu, Y, Liu, H & Liu, QH 2019, 'Fast solution of electromagnetic scattering for 3-D inhomogeneous anisotropic objects embedded in layered uniaxial media by the BCGS-FFT method', IEEE Transactions on Antennas and Propagation, vol. 67, no. 3, pp. 1748-1759.
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© 1963-2012 IEEE. In this paper, the stabilized biconjugate gradient fast Fourier transform (BCGS-FFT) method is used to solve the electromagnetic scattering problem for 3-D inhomogeneous uniaxial anisotropic objects embedded in a layered uniaxial medium. The optical axis of the background medium is perpendicular to the layer boundaries. However, the optical axis of the scatterer can be rotated through any angles. The electric field integral equation (EFIE) is formulated in the layered uniaxial anisotropic background medium. The volumetric roof-top function is used for the basis function as well as the testing function. The dyadic Green's functions (DGFs) for both the electric field and the magnetic vector potential are used to solve the EFIE, and the results as well as the performance are compared. Several numerical simulations are carried out to validate the accuracy and efficiency of the proposed method. The major new contribution of this paper is to extend the BCGS-FFT method to accommodate the uniaxial anisotropy of the layered background medium. Therefore, the DGFs for the layered uniaxial medium are evaluated before solving the EFIE. In addition, the DGF for the electric field is also used to solve the 3-D scattering problem through BCGS-FFT iterations, which is different from the previous work.
Han, L, Han, XF, Ou, XP & Guo, Y 2019, 'Operating performances analysis of brushless doubly-fed machine using magnetic equivalent circuit', Dianji yu Kongzhi Xuebao/Electric Machines and Control, vol. 23, no. 1, pp. 27-34.
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© 2019, Harbin University of Science and Technology Publication. All right reserved. There are few effective tools to quickly and correctly analyze the operating performances of Brushless Doubly-Fed Machine (BDFM) due to its special structure and complex magnetic field modulation mechanism. Based on the basic concept of Magnetic Equivalent Circuit (MEC), this paper described the method for establishing the MEC model of BDFM with cage rotor, considering the effects of special structure of BDFM, core saturation and rotor revolution. Furthermore, a dynamic MEC model of a prototype with cage rotor was built up and solved by the mesh method. And then, the operating performances of the prototype under different operating conditions were obtained and analyzed. Finally, the results of dynamic MEC model were compared with those of Finite Element Analysis (FEA) and experiment data. The results show that the dynamic MEC model can correctly predict the operating performances of BDFM with cage rotor and is much faster than FEA. This work can broaden the research thought for analyzing the operating performances of BDFM of cage rotor.
Han, L, Zhou, M, Han, S, Jia, W, Sun, C & Fu, C 2019, 'Targeting malware discrimination based on reversed association task', Concurrency Computation.
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©2018 John Wiley & Sons, Ltd. Regarding the current situation that the recognition rate of malware is decreasing, the article points out that the reason for this dilemma is that more and more targeting malware have emerged, which share little or no common feature with traditional malware. The premise of malware recognition judging whether a software is malicious or benign is actually a decision problem. We propose that malware discrimination should resort to the corresponding task or purpose. We first present a formal definition of a task and then provide further classifications of malicious tasks. Based on the decidable theory, we prove that task performed by any software is recursive and determinable. By establishing a mapping from software to task, we prove that software is many-to-one reducible to corresponding tasks. Thus, we demonstrate that software, including malware, is also recursive and can be determined by the corresponding tasks. Finally, we present the discrimination process of our method. Nine real malwares are presented, which were firstly discriminated by our method but at that time could not be identified by Kaspersky, McAfee, Symantec Norton, or Kingsoft Antivirus.
Han, L, Zhou, M, Jia, W, Dalil, Z & Xu, X 2019, 'Intrusion detection model of wireless sensor networks based on game theory and an autoregressive model', Information Sciences, vol. 476, pp. 491-504.
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© 2018 Elsevier Inc. An effective security strategy for Wireless Sensor Networks (WSNs) is imperative to counteract security threats. Meanwhile, energy consumption directly affects the network lifetime of a wireless sensor. Thus, an attempt to exploit a low-consumption Intrusion Detection System (IDS) to detect malicious attacks makes a lot of sense. Existing Intrusion Detection Systems can only detect specific attacks and their network lifetime is short due to their high energy consumption. For the purpose of reducing energy consumption and ensuring high efficiency, this paper proposes an intrusion detection model based on game theory and an autoregressive model. The paper not only improves the autoregressive theory model into a non-cooperative, complete-information, static game model, but also predicts attack pattern reliably. The proposed approach improves on previous approaches in two main ways: (1) it takes energy consumption of the intrusion detection process into account, and (2) it obtains the optimal defense strategy that balances the system's detection efficiency and energy consumption by analyzing the model's mixed Nash equilibrium solution. In the simulation experiment, the running time of the process is regarded as the main indicator of energy consumption of the system. The simulation results show that our proposed IDS not only effectively predicts the attack time and the next targeted cluster based on the game theory, but also reduces energy consumption.
Hanawal, M, Nguyen, D & Krunz, M 2019, 'Cognitive Networks with In-band Full-duplex Radios: Jamming Attacks and Countermeasures', IEEE Transactions on Cognitive Communications and Networking.
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Hassan, W, Lu, DD-C & Xiao, W 2019, 'Single-Switch High Step-Up DC-DC Converter With Low and Steady Switch Voltage Stress', IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 66, no. 12, pp. 9326-9338.
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He, L, Lu, Z, Pan, L, Zhao, H, Li, X & Zhang, J 2019, 'Optimal economic and emission dispatch of a microgrid with a combined heat and power system', Energies, vol. 12, no. 4.
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© 2019 by the authors. With the rapid development of the new concept of energy internet, electric power systems often need to be investigated together with thermal energy systems. Additionally, to reduce pollution from gas emissions, it is very important to study the economic and emission dispatch of integrated electrical and heating systems. Hence, this paper proposes a multi-objective optimization dispatch model for a microgrid (MG) with a combined heat and power (CHP) system. This CHP-based MG system consists of a CHP unit, a wind turbine, a PV system, a fuel cell, an electric boiler, an electric storage, and a heat storage. It can exchange electricity with the distribution network and exchange heat with the district heating network. Minimum economic cost and minimum environmental cost are considered as the two objectives for the operation of this CHP-based MG system. To solve the two objective optimization problem, the multi-objective bacterial colony chemotaxis algorithm is utilized to obtain the Pareto optimal solution set, and the optimal solution is chosen by the Technique for Order of Preference by Similarity to Ideal Solution method. Finally, numerical case studies demonstrate the effectiveness of proposed model and method for the optimal economic and emission dispatch of the CHP-based MG system.
He, T, Zhu, J, Lu, DDC & Zheng, L 2019, 'Modified Model Predictive Control for Bidirectional Four-Quadrant EV Chargers with Extended Set of Voltage Vectors', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 274-281.
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© 2013 IEEE. This paper presents a modified model predictive control (MMPC) for bidirectional power flow control between the electric vehicle (EV) chargers and the main grid. In contrast to the conventional finite control set MPC which selects an optimal switching state from eight possible voltage vectors, the proposed MMPC is based on the application of an optimal voltage vector chosen from an extended set of 20 modulated voltage vectors with a fixed duty ratio. To reduce the computational burden introduced by the increased number of voltage sets, a preselection algorithm is developed for the MMPC method. Six voltage vectors are preselected from the 20 sectors. Due to the increased number of the voltage space vectors, the grid currents and active and reactive power performance can be improved by using the proposed MMPC scheme. Both the conventional and proposed methods are compared through experimental test results of a two-level three-phase off-board EV charger.
Heidary, A, Radmanesh, H, Bakhshi, A, Rouzbehi, K & Pouresmaeil, E 2019, 'A compound current limiter and circuit breaker', Electronics, vol. 8, pp. 1-12.
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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The protection of sensitive loads against voltage drop is a concern for the power system. A fast fault current limiter and circuit breaker can be a solution for rapid voltage recovery of sensitive loads. This paper proposes a compound type of current limiter and circuit breaker (CLCB) which can limit fault current and fast break to adjust voltage sags at the protected buses. In addition, it can act as a circuit breaker to open the faulty line. The proposed CLCB is based on a series L-C resonance, which contains a resonant transformer and a series capacitor bank. Moreover, the CLCB includes two anti-parallel power electronic switches (a diode and an IGBT) connected in series with bus couplers. In order to perform an analysis of CLCB performance, the proposed structure was simulated using MATLAB. In addition, an experimental prototype was built, tested, and the experimental results were reported. Comparisons show that experimental results were in fair agreement with the simulation results and confirm CLCB’s ability to act as a fault current limiter and a circuit breaker.
Heidary, A, Radmanesh, H, Moghim, A, Ghorbanyan, K, Rouzbehi, K, Rodrigues, EMG & Pouresmaeil, E 2019, 'A multi-inductor h bridge fault current limiter', Electronics (Switzerland), vol. 8, no. 7.
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© 2019 by the authors. Current power systems will suffer from increasing pressure as a result of an upsurge in demand and will experience an ever-growing penetration of distributed power generation, which are factors that will contribute to a higher of incidence fault current levels. Fault current limiters (FCLs) are key power electronic devices. They are able to limit the prospective fault current without completely disconnecting in cases in which a fault occurs, for instance, in a power transmission grid. This paper proposes a new type of FCL capable of fault current limiting in two steps. In this way, the FCLs’ power electronic switches experience significantly less stress and their overall performance will significantly increase. The proposed device is essentially a controllable H bridge type fault current limiter (HBFCL) that is comprised of two variable inductances, which operate to reduce current of main switch in the first stage of current limiting. In the next step, the main switch can limit the fault current while it becomes open. Simulation studies are carried out using MATLAB and its prototype setup is built and tested. The comparison of experimental and simulation results indicates that the proposed HBFCL is a promising solution to address protection issues.
Heidary, A, Radmanesh, H, Rouzbehi, K & Pou, J 2019, 'A DC-Reactor-Based Solid-State Fault Current Limiter for HVdc Applications', IEEE TRANSACTIONS ON POWER DELIVERY, vol. 34, no. 2, pp. 720-728.
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Hesamian, MH, Jia, W, He, X & Kennedy, P 2019, 'Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges.', Journal of Digital Imaging, vol. 32, no. 4, pp. 582-596.
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Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.
Hoang, D, Luong, NT & Vo, TT 2019, 'FAPRP: A Machine Learning Approach to Flooding Attacks Prevention Routing Protocol in Mobile Ad Hoc Networks', Wireless Communications and Mobile Computing.
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Hoang, VT, Phung, MD, Dinh, TH & Ha, QP 2019, 'System Architecture for Real-Time Surface Inspection Using Multiple UAVs', IEEE Systems Journal, pp. 1-12.
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Hu, J, Li, Z, Zhu, J & Guerrero, JM 2019, 'Voltage Stabilization A Critical Step Toward High Photovoltaic Penetration', IEEE INDUSTRIAL ELECTRONICS MAGAZINE, vol. 13, no. 2, pp. 17-30.
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Huang, B, Xu, Z, Jia, B & Mao, G 2019, 'An Online Radio Map Update Scheme for WiFi Fingerprint-Based Localization', IEEE INTERNET OF THINGS JOURNAL, vol. 6, no. 4, pp. 6909-6918.
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Huang, L, Kelly, S, Lv, K & Giurco, D 2019, 'A systematic review of empirical methods for modelling sectoral carbon emissions in China', JOURNAL OF CLEANER PRODUCTION, vol. 215, pp. 1382-1401.
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Huang, L, Zhe, T, Wu, J, Wu, Q, Pei, C & Chen, D 2019, 'Robust Inter-Vehicle Distance Estimation Method Based on Monocular Vision', IEEE Access, vol. 7, pp. 46059-46070.
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© 2013 IEEE. Advanced driver assistance systems (ADAS) based on monocular vision are rapidly becoming a popular research subject. In ADAS, inter-vehicle distance estimation from an in-car camera based on monocular vision is critical. At present, related methods based on a monocular vision for measuring the absolute distance of vehicles ahead experience accuracy problems in terms of the ranging result, which is low, and the deviation of the ranging result between different types of vehicles, which is large and easily affected by a change in the attitude angle. To improve the robustness of a distance estimation system, an improved method for estimating the distance of a monocular vision vehicle based on the detection and segmentation of the target vehicle is proposed in this paper to address the vehicle attitude angle problem. The angle regression model (ARN) is used to obtain the attitude angle information of the target vehicle. The dimension estimation network determines the actual dimensions of the target vehicle. Then, a 2D base vector geometric model is designed in accordance with the image analytic geometric principle to accurately recover the back area of the target vehicle. Lastly, area-distance modeling based on the principle of camera projection is performed to estimate distance. The experimental results on the real-world computer vision benchmark, KITTI, indicate that our approach achieves superior performance compared with other existing published methods for different types of vehicles (including front and sideway vehicles).
Huang, X, An, P, Cao, F, Liu, D & Wu, Q 2019, 'Light-field compression using a pair of steps and depth estimation', Optics Express, vol. 27, no. 3, pp. 3557-3573.
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Huang, X, Zhang, JA, Liu, RP, Guo, YJ & Hanzo, L 2019, 'Airplane-Aided Integrated Networking for 6G Wireless: Will It Work?', IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 84-91.
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As demand for wireless connectivity increases, communication technology is moving toward integrating terrestrial networks with space networks. Creating this integrated space and terrestrial network (ISTN) is critically important for industries such as logistics, mining, agriculture, fisheries, and defense. However, a number of significant technological challenges must be overcome for ISTN through low-cost airborne platforms and high-data-rate backbone links.
Huang, Y, Xu, J, Wu, Q, Zheng, Z, Zhang, Z & Zhang, J 2019, 'Multi-pseudo Regularized Label for Generated Data in Person Re-Identification.', IEEE Transactions on Image Processing, vol. 28, no. 3, pp. 1391-1403.
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Sufficient training data normally is required to train deeply learned models. However, due to the expensive manual process for labelling large number of images (i.e., annotation), the amount of available training data (i.e., real data) is always limited. To produce more data for training a deep network, Generative Adversarial Network (GAN) can be used to generate artificial sample data (i.e., generated data). However, the generated data usually does not have annotation labels. To solve this problem, in this paper, we propose a virtual label called Multi-pseudo Regularized Label (MpRL) and assign it to the generated data. With MpRL, the generated data will be used as the supplementary of real training data to train a deep neural network in a semi-supervised learning fashion. To build the corresponding relationship between the real data and generated data, MpRL assigns each generated data a proper virtual label which reflects the likelihood of the affiliation of the generated data to predefined training classes in the real data domain. Unlike the traditional label which usually is a single integral number, the virtual label proposed in this work is a set of weight-based values each individual of which is a number in (0,1] called multi-pseudo label and reflects the degree of relation between each generated data to every pre-defined class of real data. A comprehensive evaluation is carried out by adopting two state-of-the-art convolutional neural networks (CNNs) in our experiments to verify the effectiveness of MpRL. Experiments demonstrate that by assigning MpRL to generated data, we can further improve the person re-ID performance on five re-ID datasets, i.e., Market-1501, DukeMTMC-reID, CUHK03, VIPeR, and CUHK01. The proposed method obtains +6.29%, +6.30%, +5.58%, +5.84%, and +3.48% improvements in rank-1 accuracy over a strong CNN baseline on the five datasets respectively, and outperforms state-of-the-art methods.
Huang, Y, Zhong, Y, Wu, Q, Dutkiewicz, E & Jiang, T 2019, 'Cost-Effective Foliage Penetration Human Detection under Severe Weather Conditions based on Auto-Encoder/Decoder Neural Network', IEEE Internet of Things Journal.
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IEEE Military surveillance events and rescue activities are vital missions for the Internet-of-things. To this end, foliage penetration for human detection plays an important role. However, although the feasibility of that mission has been validated, we observe that it still cannot performs promisingly under severe weather conditions such as rainy, foggy, and snowy days. Therefore, in this paper, experiments are conducted under severe weather conditions based on a proposed deep learning approach. We present an Auto-Encoder/Decoder (Auto-ED) deep neural network that can learn the deep representation and conduct classification task concurrently. Since the property of cost-effective, the device-free sensing (DFS) techniques are used to address human detection in our case. As we pursue the signal-based mission, two components are involved in the proposed Auto-ED approach. First, an encoder is utilized that encode signal-based inputs into higher dimensional tensors by fractionally-strided convolution operations. Then, a decoder is leveraged with convolution operations to extract deep representations and learn the classifier simultaneously. To verify the effectiveness of the proposed approach, we compare it with several machine learning approaches under different weather conditions. Also, a simulation experiment is conducted by adding Additive White Gaussian Noise (AWGN) to the original target signals with different Signal to Noise Ratios (SNRs). Experimental results demonstrate that the proposed approach can best tackle the challenge of human detection under severe weather conditions in the high-clutter foliage environment, which indicates its potential application values in the near future.
Iacopi, F & McIntosh, M 2019, 'Opportunities and perspectives for green chemistry in semiconductor technologies', GREEN CHEMISTRY, vol. 21, no. 12, pp. 3250-3255.
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Islam, MR, Lu, H, Hossain, MJ & Li, L 2019, 'Mitigating unbalance using distributed network reconfiguration techniques in distributed power generation grids with services for electric vehicles: A review', Journal of Cleaner Production, vol. 239.
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© 2019 Elsevier Ltd With rapid movement to combat climate change by reducing greenhouse gases, there is an increasing trend to use more electric vehicles (EVs) and renewable energy sources (RES). With more EVs integration into electricity grid, this raises many challenges for the distribution service operators (DSOs) to integrate such RES-based, distributed generation (DG) and EV-like distributed loads into distribution grids. Effective management of distribution network imbalance is one of the challenges. The distribution network reconfiguration (DNR) techniques are promising to address the issue of imbalance along with other techniques such as the optimal distributed generation placement and allocation (OPDGA) method. This paper presents a systematic and thorough review of DNR techniques for mitigating unbalance of distribution networks, based on papers published in peer-reviewed journals in the last three decades. It puts more focus on how the DNR techniques have been used to manage network imbalance due to distributed loads and DG units. To the best of our knowledge, this is the first attempt to review the research works in the field using DNR techniques to mitigate unbalanced distribution networks. Therefore, this paper will serve as a prime source of the guidance for mitigating network imbalance using the DNR techniques to the new researchers in this field.
Jafari, M, Malekjamshidi, Z & Zhu, J 2019, 'A magnetically coupled multi-port, multi-operation-mode micro-grid with a predictive dynamic programming-based energy management for residential applications', International Journal of Electrical Power & Energy Systems, vol. 104, no. January 2019, pp. 784-796.
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This paper presents the development of a residential micro-grid topology based on a combination of common magnetic and electrical buses. The magnetic bus interfaces two low voltage dc buses linking a PV and a fuel cell to a high voltage dc bus connected to a grid-tied single-phase bidirectional inverter. A battery is used to store the surplus energy of the system and stabilise the dc voltage of the fuel cell bus. A synchronised bus voltage balance (SBVB) technique is used to reduce the conduction losses and increase the soft switching operation range of the converters. To improve the maximum power point tracking (MPPT) performance and system efficiency, appropriate control techniques and compensation blocks are designed. The proposed micro-grid is able to operate in multiple grid-connected and off-grid operation modes according to a predictive 2D dynamic programming-based energy management. A mode selection and transition strategy is developed to select the appropriate operation mode and smooth the mode transition. A detailed study of the micro-grid including steady-state operation, small signal modelling, controller design, and energy management is presented. A prototype of the system is developed, and experimental tests are conducted for an energy management scenario.
Jafari, M, Malekjamshidi, Z & Zhu, J 2019, 'Copper Loss Analysis of a Multi-winding High-frequency Transformer for a Magnetically-coupled Residential Micro-grid', IEEE Transactions on Industry Applications, vol. 55, no. 1, pp. 283-297.
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Improvements in characteristics of magnetic materials and switching devices have provided the feasibility of replacing the electrical buses with high-frequency magnetic links in small-scale micro-grids. This can effectively reduce the number of voltage conversion stages, size and cost of the micro-grid, and isolate the sources and loads. To optimally design the magnetic link, an accurate evaluation of copper loss of the windings considering both the current waveforms and parasitic effects are required. This paper studies the copper loss analysis of a three-winding high-frequency magnetic link for residential micro-grid applications. Due to the non-sinusoidal nature of the voltages and currents, the loss analysis is carried out on a harmonic basis taking into account the variations of phase shift, duty ratio and amplitude of the waveforms. The high-frequency parasitic phenomena including the skin and proximity effects are taken into account. The maximum and minimum copper loss operating conditions of the magnetic link and their dependency on the phase shift angle and the duty ratio of the connected waveforms are studied. A prototype of the micro-grid including the magnetic link is developed to validate the theoretical analysis, evaluate the micro-grid efficiency and perform the loss breakdown.
Jafari, M, Malekjamshidi, Z & Zhu, J 2019, 'Design and development of a multi-winding high-frequency magnetic link for grid integration of residential renewable energy systems', APPLIED ENERGY, vol. 242, pp. 1209-1225.
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Jafari, M, Malekjamshidi, Z, Lu, DDC & Zhu, J 2019, 'Development of a Fuzzy-Logic-Based Energy Management System for a Multi-Port Multi-Operation Mode Residential Smart Micro-grid', IEEE Transactions on Power Electronics.
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IEEE In this paper a grid-tied residential smart micro-grid topology is proposed which integrates energies of a PV, a fuel cell and a battery bank to supply the local loads through a combination of electric and magnetic buses. In contrast to multiple-converter based micro-grids with a common electric bus, using a multi-port converter with a common magnetic bus can effectively reduce the number of voltage conversion stages, size and cost of the micro-grid and isolates the conversion ports. The resultant topology utilizes a centralized system level control which leads to the faster and more flexible energy management. The proposed micro-grid is able to operate in multiple grid-connected and off-grid operation modes. A fuzzy controlled energy management unit is designed to select the appropriate operation mode considering both real-time and long-term-predicted data of the system. A mode transition process is designed to smooth the mode variation by using a state transition diagram and bridging modes. To improve the micro-grid operation performance, appropriate control techniques such as synchronized bus-voltage balance are used. A prototype of the proposed micro-grid is developed and experimentally tested for three different energy management scenarios. Energy distribution and energy cost analysis are performed to validate the proposed control method.
Jafari, M, Malekjamshidi, Z, Zhu, J & Khooban, MH 2019, '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.
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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.
Jan, MA, Usman, M, He, X & Rehman, AU 2019, 'SAMS: A Seamless and Authorized Multimedia Streaming framework for WMSN-based IoMT', IEEE Internet of Things Journal.
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IEEE An Internet of Multimedia Things (IoMT) architecture aims to provide a support for real-time multimedia applications by using wireless multimedia sensor nodes that are deployed for long-term usage. These nodes are capable of capturing both multimedia and non-multimedia data, and form a network known as Wireless Multimedia Sensor Network (WMSN). In a WMSN, the underlying routing protocols need to provide an acceptable level of Quality-of-Service (QoS) support for the multimedia traffic. In this paper, we propose a seamless and authorized multimedia streaming framework (SAMS) for a cluster-based hierarchical WMSN. SAMS uses authentication at different levels to form secured clusters. The formation of these clusters allows only legitimate nodes to transmit captured data to their cluster heads. Each node senses the environment, stores captured data in its buffer, and waits for its turn to transmit to its cluster head. This waiting may result in an excessive packet loss and end-to-end delay for multimedia traffic. To address these issues, a channel allocation approach is proposed for inter-cluster communication. In case of buffer overflow, a member node in one cluster switches to a neighboring cluster head provided that the latter has an available channel for allocation. The experimental results show that SAMS provides an acceptable level of QoS and enhances the security of the underlying network.
Janeczko, C, Martelli, C, Canning, J & Dutra, G 2019, 'Assessment of Orchid Surfaces Using Top-Down Contact Angle Mapping', IEEE Access, vol. 7, pp. 31364-31375.
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© 2013 IEEE. Top-down contact angle (CA) measurements are used to characterize the green leaves and purple flowers of both old and young the Cattleya warneri orchids. The top-down CA allows the characterization of large surfaces away from the leaf edge, avoiding traditional cutting required for side view CA measurement. This allows large area mapping without damaging leaves making the method amenable to fieldwork and useful in environmental diagnostics. Young leaves are found to be hydrophobic whilst old leaves become practically hydrophilic across their entirety, mostly as a result of continued exposure to changes in the environment over time. The flowers are hydrophobic because of their visual and tactile attractor function for pollinating animals and the self-cleaning of dirt and pathogens. Real-time measurement and mapping of CA of surfaces open a new tool to assess the long-term impact of plant aging, pollution, and more of organisms in the field. The method has clear applications elsewhere such as in industrial probing of surfaces and products.
Jiang, S, Li, K & Xu, YDR 2019, 'Relative Pairwise Relationship Constrained Non-negative Matrix Factorisation', IEEE Transactions on Knowledge and Data Engineering.
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IEEE Non-negative Matrix Factorisation (NMF) has been extensively used in machine learning and data analytics applications. Most existing variations of NMF only consider how each row/column vector of factorised matrices should be shaped, and ignore the relationship among pairwise rows or columns. In many cases, such pairwise relationship enables better factorisation, for example, image clustering and recommender systems. In this paper, we propose an algorithm named, Relative Pairwise Relationship constrained Non-negative Matrix Factorisation (RPR-NMF), which places constraints over relative pairwise distances amongst features by imposing penalties in a triplet form. Two distance measures, squared Euclidean distance and Symmetric divergence, are used, and exponential and hinge loss penalties are adopted for the two measures respectively. It is well known that the so-called "multiplicative update rules" result in a much faster convergence than gradient descend for matrix factorisation. However, applying such update rules to RPR-NMF and also proving its convergence is not straightforward. Thus, we use reasonable approximations to relax the complexity brought by the penalties, which are practically verified. Experiments on both synthetic datasets and real datasets demonstrate that our algorithms have advantages on gaining close approximation, satisfying a high proportion of expected constraints, and achieving superior performance compared with other algorithms.
Johnson, B, Chang, L, Afridi, K, Ali, MH, Von Appen, J, Chen, YM, Davoudi, A, Dhople, S, Enslin, JH, Flicker, J, Islam, MR, Koutroulis, E, Kim, KA, Li, Y, Liserre, M, Long, T, Lu, X, Mattavelli, P, Rodriguez, P, Ruan, X, Suntio, T, Wang, H, Xu, D, Xu, W, Yazdani, A, Zeineldin, H & Zhu, J 2019, 'Guest editorial joint special section on power conversion & control in photovoltaic power plants', IEEE Transactions on Energy Conversion, vol. 34, no. 1, pp. 159-160.
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Ju, M, Ding, C, Guo, YJ & Zhang, D 2019, 'Remote Sensing Image Haze Removal Using Gamma-Correction-Based Dehazing Model', IEEE Access, vol. 7, pp. 5250-5261.
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© 2013 IEEE. Haze is evident in most remote sensing (RS) images, particularly for the RS scenes captured in inclement weather, which severely hinders image interpretation. In this paper, two simple yet effective visibility restoration formulas are proposed for RGB-channel RS (RRS) images and multi-spectral RS (MSRS) images, respectively. More specifically, a robust gamma-correction-based dehazing model (RGDM) is first defined, which can better address the non-uniform illumination problem in hazy images. Then, the scene albedo restoration formula (SARF) used for the RRS images is obtained by imposing the existing prior knowledge on this RGDM, which enables us to simultaneously eliminate the interferences of haze and non-uniform illumination. In subsequence, according to Rayleigh's law, an expanded restoration formula (E-SARF) is further developed for MSRS data. Using the proposed E-SARF, the spatially varying haze in each band can be thoroughly removed without using any extra information. The experiments are conducted on the challenging RRS and MSRS images, including images with non-uniform illumination, non-uniform haze distribution, and heavy haze. The results reveal that the SARF and the E-SARF are superior to most other state-of-the-art techniques in terms of both the recover quality and the implementation efficiency.
Ju, M, Ding, C, Zhang, D & Guo, YJ 2019, 'BDPK: Bayesian Dehazing Using Prior Knowledge', IEEE Transactions on Circuits and Systems for Video Technology.
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IEEE Atmospheric scattering model (ASM) has been widely used in hazy image restoration. However, the recovered albedo might deviate from the real scene once the input hazy image cannot fully satisfy the model’s assumptions such as the homogeneous atmosphere and even illumination. In this paper, we break these limitations and redefine a more reliable atmospheric scattering model (RASM) that is extremely adaptable for various practical scenarios. Benefiting from RASM, a simple yet effective Bayesian dehazing algorithm (BDPK) is further proposed based on the prior knowledge. Our strategy is to convert the single image dehazing problem into a maximum a-posteriori probability (MAP) one that can be approximated as an optimization function using the existing priori constraints. To efficiently solve this optimization function, the alternating minimizing technique (AMT) is introduced, which enables us to directly restore the scene albedo. Experiments on a number of challenging images reveal the power of BDPK on removing haze and verify its superiority over several state-of-the-art techniques in terms of quality and efficiency.
Karmokar, DK, Chen, SL, Bird, TS & Guo, YJ 2019, 'Single-Layer Multi-Via Loaded CRLH Leaky-Wave Antennas for Wide-Angle Beam Scanning With Consistent Gain', IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 2, pp. 313-317.
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© 2018 IEEE. Achieving continuous backward-to-forward wide-angle beam scanning with consistent gain by employing composite right/left-handed (CRLH) leaky-wave antennas (LWAs) is reported. For structural and design simplicity, a single-layer one-dimensional structure is considered in which each unit cell consists of a patch shorted centrally to the ground plane. It was found that, when using only one via at the center of a unit cell, a continuous beam scan requires a large-diameter via when all other parameters remain unchanged. To eliminate this limitation while maintaining a single-layer structure, novel unit cells are proposed using multiple vias in each unit cell. An LWA design for continuous beam scan with three vias in each unit cell is investigated, and the results show good performance and design flexibility. A prototype antenna has been realized, and the measured results show that the antenna can scan the radiation beam continuously in a wide range, from -60° to +66° with a consistent gain. The measured gain variation within the scan range is only 2.9 dB, and the 3 dB gain bandwidth is 58.6%.
Khan, AA, Abolhasan, M, Ni, W, Lipman, J & Jamalipour, A 2019, 'A Hybrid-Fuzzy Logic Guided Genetic Algorithm (H-FLGA) Approach for Resource Optimization in 5G VANETs', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 68, no. 7, pp. 6964-6974.
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Khan, MNH, Forouzesh, M, Siwakoti, YP, Li, L, Kerekes, T & Blaabjerg, F 2019, 'Transformerless Inverter Topologies for Single-Phase Photovoltaic Systems: A Comparative Review', IEEE Journal of Emerging and Selected Topics in Power Electronics.
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Khan, SA, Guo, Y & Zhu, J 2019, 'Model Predictive Observer Based Control for Single-Phase Asymmetrical T-Type AC/DC Power Converter', IEEE Transactions on Industry Applications, vol. 55, no. 2, pp. 2033-2044.
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© 1972-2012 IEEE. This paper presents a robust control strategy for the control of single-phase five-level asymmetrical T-type ac/dc power converter. A cascaded control scheme consisting of a finite control set model predictive control (FCS-MPC) with an extended state observer (ESO) is proposed to govern the converter. In this scheme, a proportional integral (PI) controller combined with an ESO-based disturbance observer is employed as an external control loop. This control loop dynamically modifies the active power reference to realize the desired operating point of the system state (converter output voltage). The proposed control system presents a high degree of disturbance rejection capability and robustness against the external disturbances to the converter, whereas the conventional PI control performance suffers in the presence of these disturbances. In this paper, the inner current tracking loop is accomplished by an FCS-MPC algorithm. This algorithm is derived to force the input currents to track the reference values while realizing a user-defined reactive power and maintaining balanced voltages in the series-connected capacitors. Theoretical analysis and the design procedure of the proposed control system are presented. Finally, experimental studies are conducted to verify the effectiveness of the proposed control scheme.
Khan, SA, Islam, MR, Guo, Y & Zhu, J 2019, 'An Amorphous Alloy Magnetic-Bus-Based SiC NPC Converter with Inherent Voltage Balancing for Grid-Connected Renewable Energy Systems', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2.
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© 2002-2011 IEEE. This paper presents an amorphous alloy magnetic-bus-based neutral point clamped (NPC) converter for grid-connected renewable generation systems. In the proposed system, the amorphous alloy high-frequency high-power density multi-winding magnetic bus generates balanced dc supplies for the five-level (5L) NPC converter for high-quality power conversion. Compared to the traditional NPC converter topologies, the proposed magnetic-bus-based architecture does not require any control circuit for voltage balancing of the series connected capacitors. The magnetic bus inherently overcomes galvanic isolation issues and may reduce the size of the boosting inductor. In this paper, a finite control set model predictive control algorithm is derived to control the grid-connected 5L-NPC inverter for multilevel voltage synthesizing, while achieving the user-defined active and reactive power values. To verify the proposed concept, a simulation model is developed and analyzed in MATLAB/Simulink environment. To validate the technology, a scale d-down prototype test platform is developed in the laboratory with silicon carbide switching devices, which achieves high blocking voltage, low power dissipation, high switching frequency, and high-Temperature operation. Based on the simulation and the experimental results, it is expected that the proposed converter will have a great potential for widespread application in renewable generation systems including superconducting generator-based wind turbines.
Khan, SA, Islam, R, Guo, Y & Zhu, J 2019, 'A New Isolated Multi-Port Converter With Multi-Directional Power Flow Capabilities for Smart Electric Vehicle Charging Stations', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 29, no. 2.
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La, HM, Dinh, TH, Pham, NH, Ha, QP & Pham, AQ 2019, 'Automated robotic monitoring and inspection of steel structures and bridges', Robotica, vol. 37, no. 5, pp. 947-967.
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Copyright © Cambridge University Press 2018 This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.
Lam, SC & Sandrasegaran, K 2019, 'A Model Based Poisson Point Process for Downlink Cellular Networks Using Joint Scheduling', Wireless Personal Communications.
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Lan, T, Liu, N, Liu, Y, Han, F & Liu, QH 2019, '2-D electromagnetic scattering and inverse scattering from magnetodielectric objects based on integral equation method', IEEE Transactions on Antennas and Propagation, vol. 67, no. 2, pp. 1346-1351.
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© 1963-2012 IEEE. Efficient 2-D full-waveform forward and inverse electromagnetic scattering solvers are presented in this communication. The combined field volume integral equation (CFVIE) is formulated in a layered medium. Different from the previous work, the mixed-order basis function is adopted in the discretization of the 2-D CFVIE. Meanwhile, the permittivity and permeability are simultaneously reconstructed in the inversion through the variational Born iteration method, which is enhanced with a self-adaptive regularization factor and applied to the multifrequency data. The proposed forward solver is validated by comparisons with the finite-element simulations.
Lashkari, B, Rezazadeh, J, Farahbakhsh, R & Sandrasegaran, K 2019, 'Crowdsourcing and Sensing for Indoor Localization in IoT - a Review', IEEE Sensors Journal, vol. 19, no. 7, pp. 2408-2434.
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IEEE Among the emerging concepts in the context of IoT, crowdsourcing and crowdsensing are known as two critical building blocks on the intersection point of things and humanbased techniques. Although contribution and involvement of people is a key factor in both crowdsensing and crowdsourcing systems which provides reliability and data quality, level of human contribution is what makes crowd-powered systems different. To scrutinize this difference it is considered that user intervention in crowd-based schemes can be either implicit or explicit. Since one of the most important applications of crowdsourcing and crowdsensing systems is providing location services in indoor environments, in this work we study the level of user contribution in available crowd-powered techniques and propose a classification for crowd-powered indoor localization solutions to clarify which crowds-based approach is utilized in each indoor localization solution because in many cases the distinction is not clear and often leads to misconception. Dependency on site survey process is considered as another distinction point in our proposed classification. Hence we consider indoor localization solutions with implicit user participation and latent mobile utilization as crowdsensing indoor localization systems. Respectively, indoor localization solutions with explicit user participation and manifest mobile utilization are classified as crowdsourcing indoor localization systems.
Le, AT, Tran, LC, Huang, X, Jay Guo, Y & Vardaxoglou, JYC 2019, 'Frequency-domain characterization and performance bounds of ALMS loop for RF self-interference cancellation', IEEE Transactions on Communications, vol. 67, no. 1, pp. 682-692.
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© 1972-2012 IEEE. Analog least mean square (ALMS) loop is a promising method to cancel self-interference (SI) in in-band full-duplex (IBFD) systems. In this paper, the steady state analyses of the residual SI powers in both analog and digital domains are firstly derived. The eigenvalue decomposition is then utilized to investigate the frequency domain characteristics of the ALMS loop. Our frequency domain analyses prove that the ALMS loop has an effect of amplifying the frequency components of the residual SI at the edges of the signal spectrum in the analog domain. However, the matched filter in the receiver chain will reduce this effect, resulting in a significant improvement of the interference suppression ratio (ISR). It means that the SI will be significantly suppressed in the digital domain before information data detection. This paper also derives the lower bounds of ISRs given by the ALMS loop in both analog and digital domains. These lower bounds are joint effects of the loop gain, tap delay, number of taps, and transmitted signal properties. The discovered relationship among these parameters allows the flexibility in choosing appropriate parameters when designing the IBFD systems under given constraints.
Le, NT & Hoang, DB 2019, 'A Threat Computation Model using a Markov Chain and Common Vulnerability Scoring System and its Application to Cloud Security', Australian Journal of Telecommunications and the Digital Economy, vol. 7, no. 1, pp. 37-56.
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Copyright © 2019 Securing cyber infrastructures has become critical because they are increasingly exposed to attackers while accommodating a huge number of IoT devices and supporting numerous sophisticated emerging applications. Security metrics are essential for assessing the security risks and making effective decisions concerning system security. Many security metrics rely on mathematical models, but are mainly based on empirical data, qualitative methods, or compliance checking, and this renders the outcome far from satisfactory. Computing the probability of an attack, or more precisely a threat that materialises into an attack, forms an essential basis for a quantitative security metric. This paper proposes a novel approach to compute the probability distribution of cloud security threats based on a Markov chain and Common Vulnerability Scoring System. Moreover, the paper introduces the method to estimate the probability of security attacks. The use of the new security threat model and its computation is demonstrated through their application to estimating the probabilities of cloud threats and types of attacks.
Lei, G, Liu, C, Li, Y, Chen, D, Guo, Y & Zhu, J 2019, 'Robust Design Optimization of a High-Temperature Superconducting Linear Synchronous Motor Based on Taguchi Method', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 29, no. 2.
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Lei, G, Wang, T, Zhu, J & Guo, Y 2019, 'Robust Multiobjective and Multidisciplinary Design Optimization of Electrical Drive Systems', China Electrotechnical Society Transactions on Electrical Machines and Systems, vol. 2, no. 4, pp. 409-416.
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Li, G, Hu, J, Li, Y & Zhu, J 2019, 'An Improved Model Predictive Direct Torque Control Strategy for Reducing Harmonic Currents and Torque Ripples of Five Phase Permanent Magnet Synchronous Motors', IEEE Transactions on Industrial Electronics.
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IEEE Five phase permanent magnet synchronous motors (PMSMs) offer merits of high fault tolerant capability and high torque per rms ampere, and thus, are suitable for applications like aerospace and electric vehicles (EVs). However, the complex machine model causes difficulties in controller design. Besides, having 32 voltage vectors with various effects on currents and torque, the selection of the optimal switching state becomes a challenge to achieve a performance trade-off. This paper proposes an improved model predictive direct torque control (MPDTC) strategy consisting of a quadratic evaluation method (QEM) and a harmonic voltage elimination method (HVEM). In QEM, the preliminary vector is firstly chosen from the vectors of the outer decagon according to a cost function for torque and flux regulation. This preliminary vector, composed of three sets of different amplitudes, is further synthesized according to the error between the actual toque/flux and the references. In this way, the optimal voltage vector can be obtained without significantly increasing the computational burden. In HVEM, by subtracting the harmonics voltage component from the vector determined previously in QEM, the final voltage vector is obtained for mitigating stator harmonic currents. The proposed control strategy is compared with the conventional MPDTC approach. The results confirm the effectiveness of the proposed methods with good steady-state performance while maintaining quick dynamic responses.
Li, H, Wang, TQ & Huang, X 2019, 'Joint Adaptive AoA and Polarization Estimation Using Hybrid Dual-Polarized Antenna Arrays', IEEE Access, vol. 7, pp. 76353-76366.
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© 2013 IEEE. The propagation of a millimeter wave (mmWave) signal is dominated by its line-of-sight component. Therefore, the knowledge of angle-of-arrival and polarization state of the wave is of great importance for its reception at the receiver. In this paper, we estimate these parameters for an information-bearing signal in mmWave systems using hybrid antenna arrays with dual-polarized dipoles. The estimation is studied in the context of both the interleaved and localized arrays. Two blind adaptive algorithms, namely, the joint differential beam tracking and cross-correlation-to-power ratio polarization tracking, and the differential beam and polarization search, are developed, each tailored for an array. It is shown that the use of dual-polarized dipoles in combination with the developed algorithms effectively lead to polarization diversity which significantly enhances the signal-to-noise ratio at the decoder. The simulation results also show that the antennas with dual dipoles provide improved accuracy and convergence rate for the estimations compared with the conventional arrays.
Li, H, Wang, TQ, Huang, X & Guo, YJ 2019, 'Adaptive AoA and Polarization Estimation for Receiving Polarized mmWave Signals', IEEE Wireless Communications Letters.
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IEEE This paper proposes a novel hybrid dual-polarized antenna array which exploits two orthogonally-collocated dipoles to capture the full power of a polarized millimeter wave signal. To maximize the received signal-to-noise ratio (SNR), we study the adaptive angle-of-arrival and polarization state estimation, and develop a differential beam tracking algorithm and a cross-correlation-to-power ratio polarization tracking algorithm for interleaved hybrid dual-polarized arrays. Simulation results verify the superior performance of the proposed algorithms, and confirm the significant improvement of SNR obtained by using the proposed array and algorithms.
Li, H, Wang, TQ, Huang, X, Zhang, JA & Guo, YJ 2019, 'Low-Complexity Multiuser Receiver for Massive Hybrid Array mmWave Communications', IEEE TRANSACTIONS ON COMMUNICATIONS, vol. 67, no. 5, pp. 3512-3524.
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Li, K, Ni, W, Abolhasan, M & Tovar, E 2019, 'Reinforcement Learning for Scheduling Wireless Powered Sensor Communications', IEEE Transactions on Green Communications and Networking, vol. 3, no. 2, pp. 264-274.
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© 2017 IEEE. In a wireless powered sensor network, a base station transfers power to sensors by using wireless power transfer (WPT). Inadequately scheduling WPT and data transmission causes fast battery drainage and data queue overflow of some sensors who could have potentially gained high data reception. In this paper, scheduling WPT and data transmission is formulated as a Markov decision process (MDP) by jointly considering sensors' energy consumption and data queue. In practical scenarios, the prior knowledge about battery level and data queue length in MDP is not available at the base station. We study reinforcement learning at the sensors to find a transmission scheduling strategy, minimizing data packet loss. An optimal scheduling strategy with full-state information is also investigated, assuming that the complete battery level and data queue information are well known by the base station. This presents the lower bound of the data packet loss in wireless powered sensor networks. Numerical results demonstrate that the proposed reinforcement learning scheduling algorithm significantly reduces network packet loss rate by 60%, and increases network goodput by 67%, compared to existing non-MDP greedy approaches. Moreover, comparing the optimal solutions, the performance loss due to the lack of sensors' full-state information is less than 4.6%.
Li, K, Voicu, RC, Kanhere, SS, Ni, W & Tovar, E 2019, 'Energy Efficient Legitimate Wireless Surveillance of UAV Communications', IEEE Transactions on Vehicular Technology, vol. 68, no. 3, pp. 2283-2293.
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© 1967-2012 IEEE. Unmanned aerial vehicles (UAVs) enhance connectivity and accessibility for civilian and military applications. Criminals or terrorists can potentially use UAVs for committing crimes and terrorism, thus endangering public safety. In this paper, we consider that a legitimate UAV is employed to track flight of suspicious UAVs for preventing safety and security threats. To obtain flight information of the suspicious UAVs, the legitimate UAV intentionally jams the suspicious receiver so as to force the suspicious UAV to reduce its data rate, and hence increase the eavesdropping success. An energy-efficient jamming strategy is proposed for the legitimate UAV to maximize the amount of eavesdropped packets. Moreover, a tracking algorithm is developed for the legitimate UAV to track the suspicious flight by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter's signal. A new simulation framework is implemented to combine the complementary features of optimization toolbox with channel modeling (in MATLAB) and discrete event-driven mobility tracking (in NS3). Moreover, numerical results validate the proposed algorithms in terms of packet eavesdropping rate and tracking accuracy of the suspicious UAVs' trajectory.
Li, N, Fu, X, Zhu, J, Lin, M, Yang, G, Kong, Y & Hao, L 2019, 'Hybrid-Excited Series Permanent Magnet Axial Field Flux Switching Memory Machine', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2.
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© 2002-2011 IEEE. This paper presents a novel axial field flux switching memory (AFFSM) machine, which integrates series permanent magnet (SPM) and an additional dc field winding for improving the flux regulation capability. The configuration and the operation principle of the SPM-AFFSM machine are presented. The design considerations for the SPM and the dc field winding are discussed. The voltage regulation capability and torque-speed characteristics of the SPM-AFFSM machine are investigated by 3-D FEA. Finally, a prototype is developed for experimental verification. The measured results verify structural validity and the finite-element predictions.
Li, N, Zhu, J, Lin, M, Yang, G, Kong, Y & Hao, L 2019, 'Analysis of Axial Field Flux-Switching Memory Machine Based on 3-D Magnetic Equivalent Circuit Network Considering Magnetic Hysteresis', IEEE TRANSACTIONS ON MAGNETICS, vol. 55, no. 6.
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Li, W, Liu, BM, Liu, D, Liu, RP, Wang, P, Luo, S & Ni, W 2019, 'Unified Fine-grained Access Control for Personal Health Records in Cloud Computing.', IEEE journal of biomedical and health informatics.
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Attribute-based encryption has been a promising encryption technology to secure personal health records (PHRs) sharing in cloud computing. PHRs consist of the patient data often collected from various sources including hospitals and general practice centres. Different patients' access policies have a common access sub-policy. In this paper, we propose a novel attribute-based encryption scheme for fine-grained and flexible access control to PHRs data in cloud computing. The scheme generates shared information by the common access sub-policy which is based on different patients' access policies. Then the scheme combines the encryption of PHRs from different patients. Therefore, both time consumption of encryption and decryption can be reduced. Medical staff require varying levels of access to PHRs. The proposed scheme can also support multi-privilege access control so that medical staff can access the required level of information while maximizing patient privacy. Through implementation and simulation, we demonstrate that the proposed scheme is efficient in terms of time. Moreover, We prove the security of the proposed scheme based on security of the ciphertext-policy attribute-based encryption scheme.
Li, W, Tang, X & Yang, Y 2019, 'Design and implementation of SIW cavity-backed dual-polarization antenna array with dual high-order modes', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4889-4894.
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© 2019 IEEE. In this communication, a novel approach for high-order modes excitation using substrate-integrated waveguide (SIW) is proposed for the implementation of a dual-polarization cavity-backed slot antenna. The antenna consists of a resonant SIW cavity with eight radiating slots and two separated SIW feeding networks. The vertically linear polarization (VLP) and horizontally linear polarization (HLP) are realized by adopting the TE430 and TE340 modes with different signal schemes. The field distributions and the surface currents of the TE430 and TE340 modes are used to analyze and illuminate the radiation mechanism. To further validate the proposed design, a 2 × 2 polarization-diverse SIW cavity-backed antenna array is fabricated and tested. The measured results show that the impedance bandwidths (S11 <-10 dB) for the two linear-polarization (LP) states are 10.73-10.9 GHz and 10.75-10.83 GHz, respectively, while the 3 dB axial ratio bandwidth for the right-hand circular polarization (RHCP) is 10.75-10.83 GHz. The measured peak gains of the two LP modes and CP mode are 13.4, 12.92, and 12.2 dBi, respectively. The proposed approach demonstrates an effective way of high-order modes (TE430 and TE340 modes) generation in a single SIW cavity, which has significant meaning in polarization-diversity applications.
Li, X, Wang, Z, Zhang, L, Zou, C & Dorrell, DD 2019, 'State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis', JOURNAL OF POWER SOURCES, vol. 410, pp. 106-114.
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Li, Z, Guo, YJ, Chen, SL & Wang, J 2019, 'A Period-Reconfigurable Leaky-Wave Antenna with Fixed-Frequency and Wide-Angle Beam Scanning', IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 3720-3732.
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© 1963-2012 IEEE. A novel fixed-frequency beam-scanning leaky-wave antenna (LWA) based on a period-reconfigurable structure is presented. Operating at 5 GHz, the antenna consists of a slotted substrate integrated waveguide and 54 electrically small patches. Each patch element is etched with two dumbbell-shaped slots, and its operating state can be flexibly controlled by the biasing of the p-i-n diode on a parasitic strip. An ideal array model employing isotropic point sources is used for the analysis on the scanning mechanism, based on which a new method for suppressing the higher order space harmonics is developed. Using this method, the monoharmonic radiation range can be dramatically extended, and a wide-angle beam scanning can be achieved by manipulating the period length of the LWA. An FPGA controlling platform is designed for the electronic control of the antenna. The measured results validate that the proposed antenna achieves good performance of wide-angle scanning (125°) with a peak gain of 11.8 dBi at a fixed frequency.
Li, Z, Zhang, S, Wang, J, Li, Y, Chen, M, Zhang, Z & Guo, YJ 2019, 'A Method of Generating Radiation Null for Periodic Leaky-Wave Antennas', IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 4241-4246.
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© 1963-2012 IEEE. A systematic method for generating a radiation null region in the radiation pattern of periodic leaky-wave antennas (LWAs) is proposed using the theory of effective radiation sections (ERSs). In this method, the aperture field is expanded into spatial harmonics using the mode expansion method, and the ERSs of the harmonics are studied. Based on this, the radiation null region is introduced by suppressing the radiation of the ERSs corresponding to the radiating mode. The proposed method is applied to a periodic-strip LWA. The validity of the proposed method is verified by both simulated and experimental results, showing an obvious radiation null in the prescribed angular range. This method has the advantages of easy calculation and implementation, and has little influence on the gain and beamwidth. It is illustrated that only simple modification to the antenna structure is needed to achieve nulling.
Liang, J, Mondal, AK, Wang, DW & Iacopi, F 2019, 'Graphene-Based Planar Microsupercapacitors: Recent Advances and Future Challenges', Advanced Materials Technologies, vol. 4, no. 1.
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© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim The continuous development of integrated electronics such as maintenance-free biosensors, remote and mobile environmental sensors, wearable personal electronics, nanorobotics etc. and their continued miniaturization has led to an increasing demand for miniaturized energy storage units. Microsupercapacitors with graphene electrodes hold great promise as miniaturized, integrated power sources thanks to their fast charge/discharge rates, superior power performance, and long cycling stability. In addition, planar interdigitated electrodes also have the capability to reduce ion diffusion distances leading to a greatly improved electrochemical performance. Either as standalone power sources or complementing energy harvesting units, it is expected that graphene-based microsupercapacitors will play a key role as miniaturized power sources in electronic microsystems. This review highlights the recent development, challenges, and perspectives in this area, with an emphasis on the link between material and geometry design of planar graphene-based electrodes and their electrochemical performance and integrability.
Liberal, I, Ederra, I & Ziolkowski, RW 2019, 'Grating Lobes in Higher-Order Correlation Functions of Arrays of Quantum Emitters: Directional Photon Bunching Versus Correlated Directions', PHOTONICS, vol. 6, no. 1.
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Lin, JY, Wong, SW, Wu, YM, Yang, Y, Zhu, L & He, Y 2019, 'Three-way multiple-mode cavity filtering crossover for narrowband and broadband applications', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 3, pp. 896-905.
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© 1963-2012 IEEE. In this paper, the design of a cavity crossover with three intersecting channels is presented. The three fundamental modes of a cavity resonator, namely, TE011, TE101, and TM110 modes, are adopted to resonate at each of three channels, respectively. Due to the modal orthogonality of these fundamental modes, high isolation among three channels can be achieved. Two kinds of crossovers, for narrowband and broadband applications, are presented. For the narrowband case, the proposed crossover resonates at 2.91 GHz with the fractional bandwidth of 1.4%. For the broadband case, the proposed crossover resonates at 3 GHz with the fractional bandwidth of 24%. The isolations of both designs reach more than 50 dB. For a proof of concept, the broadband example of the cavity crossover structures is fabricated and measured. A good agreement between the simulated and the measured results verifies the accuracy of the proposed design methodology.
Lin, L, Xu, L, Huang, Y, Xiang, Y & He, X 2019, 'On exploiting priority relation graph for reliable multi-path communication in mobile social networks', Information Sciences, vol. 477, pp. 490-507.
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© 2018 Elsevier Inc. A mobile social network (MSN) consists of certain amount of mobile users with social characteristics, and it provides data delivery concerning social relationships between mobile users. In MSN, ordinary people contact each other more frequently if they have more social features in common. In this paper, we apply a new topology structure–priority relation graph (PRG) to evaluate the data delivery routing in MSN on the system-level. By using the natural order of nodes’ representation, the diameter, the regular degree and the multi-path technology, we determine the priority relation graph-based social feature routing (PRG-SFR) algorithm to find disjointed multi-paths in MSN. Here, the multi-path technology can be exploited for ensuring that, between each pair of sender and receiver, the important information can be delivered through a highly reliable path. Then we calculate the tolerant ability of ‘faults’ and estimate the availability of MSN on the theoretical level. Finally, we analyze the efficiency of PRG-SFR algorithm from the numerical standpoint in terms of fault tolerance, forwarding number, transmission time and delivery rate. Moreover, we make comparisons between PRG-SFR algorithm and certain state-of-the-art technologies.
Lin, W & Ziolkowski, RW 2019, 'Compact, high directivity, omnidirectional circularly polarized antenna array', IEEE Transactions on Antennas and Propagation, vol. 67, no. 7, pp. 4537-4547.
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© 1963-2012 IEEE. A compact omnidirectional circularly polarized (OCP) antenna system is reported, which achieves high directivity and operates with the 2.4 GHz WLAN band. It is formed by cascading several stages of electric (metallic strips) and magnetic (loops) radiators into a highly compact array. Two OCP antenna array designs are developed to demonstrate the approach and their resulting high directivities. First, a four-stage OCP antenna array is presented. It consists of three electric radiators (E-radiators) and four magnetic radiators (M-radiators) arranged in collinear formation. A prototype was realized by mechanically fabricating the folded copper loops. Measurements confirm that this compact cost-effective design generates OCP fields that have a 5.1 dBic peak LHCP realized gain in its horizontal plane. The overlapped impedance and AR bandwidth cover 130 MHz from 2.34 to 2.47 GHz. Second, a six-stage OCP antenna array with helical loops is implemented to further increase the directivity. Its prototype was realized with all-metal 3-D printing technology. Six stages of bar and helical loop radiators form five E-radiators and six M-radiators. This highly compact OCP array achieves a measured maximum realized gain of 7.1 dBic with a 110 MHz operational bandwidth that covers 2.37-2.48 GHz.
Lin, W & Ziolkowski, RW 2019, 'Electrically Small Huygens Antenna-Based Fully-Integrated Wireless Power Transfer and Communication System', IEEE ACCESS, vol. 7, pp. 39762-39769.
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Lin, W & Ziolkowski, RW 2019, 'Wirelessly Powered Light and Temperature Sensors Facilitated by Electrically Small Omnidirectional and Huygens Dipole Antennas.', Sensors, vol. 19, no. 9.
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Wirelessly powered, very compact sensors are highly attractive for many emerging Internet-of-things (IoT) applications; they eliminate the need for on-board short-life and bulky batteries. In this study, two electrically small rectenna-based wirelessly powered light and temperature sensors were developed that operate at 915 MHz in the 902-928-MHz industrial, scientific, and medical (ISM) bands. First, a metamaterial-inspired near-field resonant parasitic (NFRP) Egyptian axe dipole (EAD) antenna was seamlessly integrated with a highly efficient sensor-augmented rectifier without any matching network. It was electrically small and very thin, and its omnidirectional property was ideal for capturing incident AC wireless power from any azimuthal direction and converting it into DC power. Both a photocell as the light sensor and a thermistor as the temperature sensor were demonstrated. The resistive properties of the photocell and thermistor changed the rectifier's output voltage level; an acoustic alarm was activated once a threshold value was attained. Second, an electrically small, low-profile NFRP Huygens antenna was similarly integrated with the same light- and temperature-sensor-augmented rectifiers. Their unidirectional nature was very suitable for surface-mounted wireless power transfer (WPT) applications (i.e., on-body and on-wall sensors). Measurements of the prototypes of both the light- and temperature-sensor-augmented omni- and unidirectional rectenna systems confirmed their predicted performance characteristics.
Lin, W, Ziolkowski, RW & Huang, J 2019, 'Electrically Small, Low-Profile, Highly Efficient, Huygens Dipole Rectennas for Wirelessly Powering Internet-of-Things Devices', IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 3670-3679.
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© 1963-2012 IEEE. Wireless power transfer (WPT) technologies are a major trend in emerging internet-of-things (IoT) applications. Because they negate the need for heavy, bulky batteries and can power multiple elements simultaneously, WPT systems enable very compact ubiquitous IoT wireless devices. However, the realization of high-performance, ultracompact (electrically small) rectennas, i.e., the rectifying antennas that enable midrange and far-field WPT, is challenging. We present the first electrically small ( \textit {ka} < 0.77 ) and low-profile ( 0.04~\lambda -{0} ) linearly (LP) and circularly (CP) polarized WPT rectennas at 915 MHz in the IMS band. They are facilitated by the seamless integration of highly efficient rectifiers, i.e., RF signal to dc power conversion circuits, with electrically small Huygens dipole LP and CP antennas. Their optimized prototypes have cardioid, broadside radiation patterns, and effective capture areas larger than their physical size. Experimental results validate that they achieve an 89% peak ac-to-dc conversion efficiency, effectively confirming that they are ideal candidates for many of the emerging IoT applications.
Liu, C, Wang, S, Wang, Y, Lei, G, Guo, O & Zhu, J 2019, 'Development of a New Flux Switching Transverse Flux Machine with the Ability of Linear Motion', China Electrotechnical Society Transactions on Electrical Machines and Systems, vol. 2, no. 4, pp. 384-391.
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Liu, C, Zhu, L, He, X & Chen, J 2019, '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, L, Amirgholipour, S, Jiang, J, Jia, W, Zeibots, M & He, X 2019, 'Performance-enhancing network pruning for crowd counting', Neurocomputing, vol. 360, pp. 246-253.
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© 2019 The Counting Convolutional Neural Network (CCNN) has been widely used for crowd counting. However, they typically end up with a complicated network model resulting in a challenge for real-time processing. Existing solutions aim to reduce the size of the network model, but unavoidably sacrifice the network accuracy. Different from existing pruning solutions, in this paper, a new pruning strategy is proposed by considering the contributions of various filters to the final result. The filters in the original CCNN model are grouped into positive, negative and irrelevant types. We prune the irrelevant filters of which feature maps contain little information, and the negative filters determined by a mask learned from the training dataset. Our solution improves the results of the counting model without fine-tuning or retraining the pruned model. We demonstrate the advantages of our proposed approach on the problem of crowd counting. Our experimental results on benchmark datasets show that the network model pruned using our approach not only reduces the network size but also improves the counting accuracies by 4% to 17% less MAE than the state of the arts.
Liu, M, Luo, Y, Nanda, P, Yu, S & Zhang, J 2019, 'Efficient solution to the millionaires' problem based on asymmetric commutative encryption scheme', Computational Intelligence, vol. 35, no. 3, pp. 555-576.
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© 2019 Wiley Periodicals, Inc. Secure multiparty computation is an important scheme in cryptography and can be applied in various real-life problems. The first secure multiparty computation problem is the millionaires' problem, and its protocol is an important building block. Because of the less efficiency of public key encryption scheme, most existing solutions based on public key cryptography to this problem are inefficient. Thus, a solution based on the symmetric encryption scheme has been proposed. In this paper, we formally analyse the vulnerability of this solution, and propose a new scheme based on the decisional Diffie-Hellman assumption. Our solution also uses 0-encoding and 1-encoding generated by our modified encoding method to reduce the computation cost. We implement the solution based on symmetric encryption scheme and our protocol. Extensive experiments are conducted to evaluate the efficiency of our solution, and the experimental results show that our solution can be much more efficient and be approximately 8000 times faster than the solution based on symmetric encryption scheme for a 32-bit input and short-term security. Moreover, our solution is also more efficient than the state-of-the-art solution without precomputation and can also compare well with the state-of-the-art protocol while the bit length of private inputs is large enough.
Liu, M, Xue, Z, He, X & Chen, J 2019, 'Cyberthreat-Intelligence Information Sharing', IEEE CONSUMER ELECTRONICS MAGAZINE, vol. 8, no. 3, pp. 17-22.
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Liu, Y, Green, TC, Wu, J, Rouzbehi, K, Raza, A & Xu, D 2019, 'A New Droop Coefficient Design Method for Accurate Power-Sharing in VSC-MTDC Systems', IEEE ACCESS, vol. 7, pp. 47605-47614.
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Liu, Y, Xu, W, Zhu, J & Blaabjerg, F 2019, 'Sensorless Control of Standalone Brushless Doubly Fed Induction Generator Feeding Unbalanced Loads in a Ship Shaft Power Generation System', IEEE Transactions on Industrial Electronics, vol. 66, no. 1, pp. 739-749.
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© 1982-2012 IEEE. The standalone brushless doubly fed induction generator (BDFIG) has demonstrated excellent energy-saving performance in ship shaft power generation applications. As a standalone system, it exhibits unbalanced terminal voltages and poor performance under unbalanced loads. However, the existing control scheme of grid-connected BDFIGs cannot be directly applied to stabilize the amplitude and frequency of terminal voltage when the rotor speed and electrical load vary. This paper presents a new sensorless control scheme for the standalone BDFIG under unbalanced load conditions in the ship shaft power generation system. A second-order generalized integrator-based quadrature signal generator is introduced to realize the rotor speed observer for the standalone BDFIG feeding unbalanced loads. The compensation method of negative-sequence power winding voltage is proposed to eliminate the negative-sequence component of the unbalanced power winding voltage. Comprehensive experiments are carried out on a prototype BDFIG with and without the compensation of negative-sequence power winding voltage. The good performance of the proposed sensorless control scheme is verified by the experimental test results.
Liu, Z, Yang, X, Yang, Y, Wang, K & Mao, G 2019, 'DATS: Dispersive Stable Task Scheduling in Heterogeneous Fog Networks', IEEE Internet of Things Journal.
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IEEE Fog computing has risen as a promising architecture for future Internet of Things (IoT), 5G and embedded artificial intelligence (AI) applications with stringent service delay requirements along the cloud to things continuum. For a typical fog network consisting of heterogeneous fog nodes (FNs) with different computing resources and communication capabilities, how to effectively schedule complex computation tasks to multiple FNs in the neighborhood to achieve minimal service delay is a fundamental challenge. To tackle this problem, a new concept named processing efficiency (PE) is first defined to incorporate computing resources and communication capacities. Further, to minimize service delay in heterogeneous fog networks, a scalable, stable and decentralized algorithm, namely dispersive stable task scheduling (DATS), is proposed and evaluated, which consists of two key components: (i) a PE-based progressive computing resources competition (PCRC) and (ii) a QoE-oriented synchronized task scheduling (STS). Theoretical proofs and simulation results show that the proposed DATS algorithm can achieve effective tradeoff between computing resources and communication capabilities, thus significantly reducing service delay in heterogeneous fog networks.
Lu, Y, Fang, J, Guo, Z & Zhang, J 2019, 'Distributed Transmit Beamforming for UAV to Base Communications', China Communications, vol. 16, no. 1, pp. 15-25.
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Lu, Y, Fang, J, Guo, Z & Zhang, JA 2019, 'Performance characterization and receiver design for random temporal multiple access in non-coordinated networks', China Communications, vol. 16, no. 6, pp. 173-184.
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© 2013 China Institute of Communications. Random access is a well-known multiple access method for uncoordinated communication nodes. Existing work mainly focuses on optimizing iterative access protocols, assuming that packets are corrupted once they are collided, or that feedback is available and can be exploited. In practice, a packet may still be able to be recovered successfully even when collided with other packets. System design and performance analysis under such a situation, particularly when the details of collision are taken into consideration, are less known. In this paper, we provide a framework for analytically evaluating the actual detection performance in a random temporal multiple access system where nodes can only transmit. Explicit expressions are provided for collision probability and signal to interference and noise ratio (SINR) when different numbers of packets are collided. We then discuss and compare two receiver options for the AP, and provide detailed receiver design for the premium one. In particular, we propose a synchronization scheme which can largely reduce the preamble length. We also demonstrate that system performance could be a convex function of preamble length both analytically and via simulation, as well as the forward error correction (FEC) coding rate.
Lu, Z, Geng, L, Huo, G, Zhao, H, Yao, W, Li, G, Guo, X & Zhang, J 2019, 'A novel hybrid multi-objective bacterial colony chemotaxis algorithm', Soft Computing.
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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.].
Lu, Z, Zhao, B, He, L, Zhang, D & Zhang, J 2019, 'Security level classification based on power system partitioning', IET Generation, Transmission and Distribution.
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Lyu, B, Dinh, TH & Yang, Z 2019, 'User Cooperation in Wireless-Powered Backscatter Communication Networks', IEEE WIRELESS COMMUNICATIONS LETTERS, vol. 8, no. 2, pp. 632-635.
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Mahamedi, B, Eskandari, M, Fletcher, JE & Zhu, J 2019, '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.
Makhdoom, I, Abolhasan, M, Abbas, H & Ni, W 2019, 'Blockchain's adoption in IoT: The challenges, and a way forward', Journal of Network and Computer Applications, vol. 125, pp. 251-279.
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The underlying technology of Bitcoin is blockchain, which was initially designed for financial value transfer only. Nonetheless, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as pseudonymous identities, data integrity and authentication, researchers and security analysts around the world are focusing on the blockchain to resolve security and privacy issues of IoT. However, presently, not much work has been done to assess blockchain's viability for IoT and the associated challenges. Hence, to arrive at intelligible conclusions, this paper carries out a systematic study of the peculiarities of the IoT environment including its security and performance requirements and progression in blockchain technologies. We have identified the gaps by mapping the security and performance benefits inferred by the blockchain technologies and some of the blockchain-based IoT applications against the IoT requirements. We also discovered some practical issues involved in the integration of IoT devices with the blockchain. In the end, we propose a way forward to resolve some of the significant challenges to the blockchain's adoption in IoT.
Makhdoom, I, Abolhasan, M, Lipman, J, Liu, RP & Ni, W 2019, 'Anatomy of Threats to The Internet of Things', Communications Surveys and Tutorials, IEEE Communications Society, vol. 21, no. 2, pp. 1636-1675.
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The world is resorting to the Internet of Things (IoT) for ease of control and monitoring of smart devices. The ubiquitous use of IoT ranges from industrial control systems (ICS) to e-Health, e-Commerce, smart cities, supply chain management, smart cars, cyber physical systems (CPS), and a lot more. Such reliance on IoT is resulting in a significant amount of data to be generated, collected, processed, and analyzed. The big data analytics is no doubt beneficial for business development. However, at the same time, numerous threats to the availability and privacy of the user data, message, and device integrity, the vulnerability of IoT devices to malware attacks and the risk of physical compromise of devices pose a significant danger to the sustenance of IoT. This paper thus endeavors to highlight most of the known threats at various layers of the IoT architecture with a focus on the anatomy of malware attacks. We present a detailed attack methodology adopted by some of the most successful malware attacks on IoT, including ICS and CPS. We also deduce an attack strategy of a distributed denial of service attack through IoT botnet followed by requisite security measures. In the end, we propose a composite guideline for the development of an IoT security framework based on industry best practices and also highlight lessons learned, pitfalls and some open research challenges.
Malekjamshidi, Z, Jafari, M, Zhu, J & Xiao, D 2019, 'Bidirectional power flow control with stability analysis of the matrix converter for microgrid applications', INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, vol. 110, pp. 725-736.
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Mostaan, A, Yuan, J, Siwakoti, Y, Esmaeili, S & Blaabjerg, F 2019, 'A Trans-Inverse Coupled-Inductor Semi SEPIC DC/DC Converter with Full Control Range', IEEE Transactions on Power Electronics, pp. 1-1.
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Mukhtar, NM & Lu, DDC 2019, 'A Bidirectional Two-Switch Flyback Converter with Cross-Coupled LCD Snubbers for Minimizing Circulating Current', IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 5948-5957.
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© 1982-2012 IEEE. This paper proposes a novel isolated bidirectional two-switch flyback converter with two integrated non-dissipative inductor-capacitor-diode (LCD) snubbers. In the proposed topology, the main flyback transformer and the LCD snubbers are cross coupled to minimize circulating current that would occur in the non-cross-coupled case, in addition to recycle leakage energy and protect the power transistors. The same current circulation issue also occurs in the bidirectional flyback converter with conventional resistor-capacitor-diode (RCD) snubbers. The main objective of this paper is to illustrate this issue and propose an alternate circuitry to reduce the current circulation and improve the conversion efficiency. The experimental results of a laboratory prototype are reported to verify the design.
Nanda, A, Nanda, P, He, X, Jamdagni, A & Puthal, D 2019, 'A hybrid encryption technique for Secure-GLOR: The adaptive secure routing protocol for dynamic wireless mesh networks', Future Generation Computer Systems.
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As we progress in into a digital era where most aspects of our life depend upon a network of computers,it is essential to focus on digital security. Each component of a network, be it a physical network, virtualnetwork or social network requires security when transmitting data. Hence the dynamic wireless meshnetwork must also deploy high levels of security as found in current legacy networks. This paper presentsa secure Geo-Location Oriented Routing (Secure-GLOR) protocol for wireless mesh networks, whichincorporates a hybrid encryption scheme for its multilevel security framework. The hybrid encryptiontechnique improves the network’s overall performance compared to the basic encryption by using acombination of symmetric key as well as asymmetric key encryption. Using the combination of the twoencryption schemes, the performance of the network can be improved by reducing the transmitted datasize, reduced computational overhead and faster encryption–decryption cycles. In this paper discussedmultiple encryption schemes for both symmetric and asymmetric encryption, compare their performancein various experimental scenarios. Proposed security scheme achieves better performance based on theresults obtained with most viable options for our network model.
Nanda, P, Puthal, D & Mohanty, SP 2019, 'Editorial to the Special Issue on Recent Advances on Trust, Security and Privacy in Computing and Communications', CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE.
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Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2019, 'Improper Gaussian Signaling for Broadcast Interference Networks', IEEE Signal Processing Letters, vol. 26, no. 6, pp. 808-812.
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© 1994-2012 IEEE. For a multi-user multi-cell network, which suffers both intra-cell and inter-cell interference, this letter considers improper Gaussian signaling (IGS) as a means to improve the achievable rate. The problem of interest is designing of improper Gaussian signals' augmented covariance matrices to maximize the users' minimum rate subject to transmit power constraints. This problem is seen as a nonconvex matrix optimization problem, which cannot be solved by conventional techniques, such as weighted minimum mean square error minimization or alternating optimization. A path-following algorithm, which iterates a sequence of improved feasible points, is proposed for its computation. The provided simulation results for three cells serving 18 users show that IGS offers a much better max-min rate compared with that achieved by conventional proper Gaussian signaling. Another problem of maximizing the energy efficiency in IGS is also considered.
Nasir, AA, Tuan, HD, Duong, TQ & Poor, HV 2019, 'UAV-enabled communication using NOMA', IEEE Transactions on Communications, vol. 67, no. 7, pp. 5126-5138.
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© 2019 IEEE. Unmanned aerial vehicles (UAVs) can be deployed as flying base stations (BSs) to leverage the strength of line-of-sight connections and effectively support the coverage and throughput of wireless communication. This paper considers a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA). The max-min rate optimization problem is formulated under total power, total bandwidth, UAV altitude, and antenna beamwidth constraints. The objective of max-min rate optimization is non-convex in all optimization variables, i.e., UAV altitude, transmit antenna beamwidth, power allocation, and bandwidth allocation for multiple users. A path-following algorithm is proposed to solve the formulated problem. Next, orthogonal multiple access (OMA) and dirty paper coding (DPC)-based max-min rate optimization problems are formulated and respective path-following algorithms are developed to solve them. The numerical results show that NOMA outperforms OMA and achieves rates similar to those attained by DPC. In addition, a clear rate gain is observed by jointly optimizing all the parameters rather than optimizing a subset of parameters, which confirms the desirability of their joint optimization.
Nathan, KS, Ghosh, S, Siwakoti, YP & Long, T 2019, 'A New DC-DC Converter for Photovoltaic Systems: Coupled-Inductors Combined Cuk-SEPIC Converter', IEEE Transactions on Energy Conversion.
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IEEE An enhanced DC-DC converter is proposed in this paper, based on the combination of the Cuk and SEPIC converters, which is well-suited for solar photovoltaic (PV) applications. The converter uses only one switch (which is ground-referenced, so simple gate drive circuitry may be used), yet provides dual outputs in the form of a bipolar DC bus. The bipolar output from the DC-DC converter is able to send power to the grid via any inverter with a unipolar or bipolar DC input, and leakage currents can be eliminated if the latter type is used without using lossy DC capacitors in the load current loop. The proposed converter uses integrated magnetics cores to couple the input and output inductors, which significantly reduces the input current ripple and hence greatly improves the power extracted from the solar PV system. The design methodology along with simulation, experimental waveforms, and efficiency measurements of a 4 kW DC-DC converter are presented to prove the concept of the proposed converter. Further, a 1 kW inverter is also developed to demonstrate the converter's grid-connection potential.
Nathan, KS, Ghosh, SS, Tripathi, PR, Siwakoti, YP, Flack, TJ, Li, X & Long, T 2019, 'Benefits of the CI-CCS converter', The Journal of Engineering, vol. 2019, no. 17, pp. 4527-4531.
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Nguyen, CT, Hoang, DT, Nguyen, DN, Niyato, D, Nguyen, HT & Dutkiewicz, E 2019, 'Proof-of-Stake Consensus Mechanisms for Future Blockchain Networks: Fundamentals, Applications and Opportunities', IEEE Access, vol. 7, pp. 85727-85745.
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© 2013 IEEE. The rapid development of blockchain technology and their numerous emerging applications has received huge attention in recent years. The distributed consensus mechanism is the backbone of a blockchain network. It plays a key role in ensuring the network's security, integrity, and performance. Most current blockchain networks have been deploying the proof-of-work consensus mechanisms, in which the consensus is reached through intensive mining processes. However, this mechanism has several limitations, e.g., energy inefficiency, delay, and vulnerable to security threats. To overcome these problems, a new consensus mechanism has been developed recently, namely proof of stake, which enables to achieve the consensus via proving the stake ownership. This mechanism is expected to become a cutting-edge technology for future blockchain networks. This paper is dedicated to investigating proof-of-stake mechanisms, from fundamental knowledge to advanced proof-of-stake-based protocols along with performance analysis, e.g., energy consumption, delay, and security, as well as their promising applications, particularly in the field of Internet of Vehicles. The formation of stake pools and their effects on the network stake distribution are also analyzed and simulated. The results show that the ratio between the block reward and the total network stake has a significant impact on the decentralization of the network. Technical challenges and potential solutions are also discussed.
Nguyen, H, Nguyen, D, Dinh, H & Dutkiewicz, E 2019, 'Jam Me If You Can: Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS.
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Nguyen, HT, Tuan, HD, Duong, TQ, Poor, HV & Hwang, WJ 2019, 'Collaborative Multicast Beamforming for Content Delivery by Cache-Enabled Ultra Dense Networks', IEEE Transactions on Communications, vol. 67, no. 5, pp. 3396-3406.
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© 1972-2012 IEEE. Caching and multicast have surged as effective tools to alleviate the heavy load from the backhaul links while enabling content-centric delivery in communication networks. The main focus of work in this area has been on the cache placements to manage the network delay and backhaul transmission cost. An important issue of optimizing the cost efficiency in content delivery has not been addressed. This paper tackles this issue by proposing collaborative multicast beamforming in cache-enabled ultra-dense networks. The objective is to maximize the cost efficiency, which is defined as the ratio of the content throughput to the sum of power consumption and backhaul cost, in providing quality-of-service for content delivery. Zero-forcing beamforming and generalized zero-forcing beamforming are employed to force the multi-content interference to zero or mitigate it while amplifying the desired signals for users. These problems of collaborative multicast beamforming design are computationally difficult. Path-following algorithms, which invoke a simple convex quadratic program at each iteration, are developed for their solution. Numerical results are provided to demonstrate the computational efficiency of the proposed algorithms and also give insights into the impact of caching on the cost efficiency.
Nguyen, HV, Nguyen, V-D, Dobre, OA, Nguyen, D, Dutkiewicz, E & Shin, O 2019, 'Joint Power Control and User Association for NOMA-Based Full-Duplex Systems', IEEE Transactions on Communications (TCOM).
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Nguyen, LD, Tuan, HD, Duong, TQ & Poor, HV 2019, 'Multi-user regularized zero-forcing beamforming', IEEE Transactions on Signal Processing, vol. 67, no. 11, pp. 2839-2853.
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© 1991-2012 IEEE. Regularized zero-forcing beamforming (RZFB) is an interesting class of linear signal processing problems, which is very attractive for use in large-scale communication networks due its simple visualization as a straightforward extension of the well-accepted zero-forcing beamforming (ZFB). However, unlike ZFB, which is multi-user interference free, RZFB must manage multi-user interference to achieve its high throughput performance. Most existing works focus on the performance analysis of particular RZBF schemes such as the equip-power allocated RZBF under a fixed regularization parameter. This paper is the first work to consider the joint design of power allocation and regularization parameter for RZFB to maximize the worst users' throughput or the quality-of-service awarded energy efficiency under a fixed transmit power constraint. Such designs pose very computationally challenging optimization problems, for which the paper proposes two-stage optimization algorithms of low computational complexity. Their computational and performance efficiencies are substantiated through numerical examples.
Nguyen, MN, Nguyen, LD, Duong, TQ & Tuan, HD 2019, 'Real-time optimal resource allocation for embedded UAV communication systems', IEEE Wireless Communications Letters, vol. 8, no. 1, pp. 225-238.
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© 2012 IEEE. We consider device-to-device (D2D) wireless information and power transfer systems using an unmanned aerial vehicle (UAV) as a relay-assisted node. As the energy capacity and flight time of UAVs is limited, a significant issue in deploying UAV is to manage energy consumption in real-time application, which is proportional to the UAV transmit power. To tackle this important issue, we develop a real-time resource allocation algorithm for maximizing the energy efficiency by jointly optimizing the energy-harvesting time and power control for the considered (D2D) communication embedded with UAV. We demonstrate the effectiveness of the proposed algorithms as running time for solving them can be conducted in milliseconds.
Pou, J, Perez, MA & Aguilera, RP 2019, 'Modular multilevel converters', IEEE Transactions on Industrial Electronics, vol. 66, no. 3, pp. 2204-2206.
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Pu, L, Chen, X, Mao, G, Xie, Q & Xu, J 2019, 'Chimera: An Energy-efficient and Deadline-aware Hybrid Edge Computing Framework for Vehicular Crowdsensing Applications', IEEE Internet of Things Journal.
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IEEE In this paper, we propose Chimera, a novel hybrid edge computing framework, integrated with the emerging edge cloud radio access network, to augment network-wide vehicle resources for future large-scale vehicular crowdsensing applications, by leveraging a multitude of cooperative vehicles and the virtual machine (VM) pool in the edge cloud via the control of the application manager deployed in the edge cloud. We present a comprehensive framework model and formulate a novel multi-vehicle and multi-task offloading problem, aiming at minimizing the energy consumption of network-wide recruited vehicles serving heterogeneous crowdsensing applications, and meanwhile reconciling both application deadline and vehicle incentive. We invoke Lyapunov optimization framework to design TaskSche, an online task scheduling algorithm, which only utilizes the current system information. As the core components of the algorithm, we propose a task workload assignment policy based on graph transformation and a knapsack-based VM pool resource allocation policy. Rigorous theoretical analyses and extensive trace-driven simulations indicate that our framework achieves superior performance (e.g., 20% – 68% energy saving without overstepping application deadlines for network-wide vehicles compared with vehicle local processing) and scales well for a large number of vehicles and applications.
Puthal, D, Ranjan, R, Nanda, A, Nanda, P, Jayaraman, PP & Zomaya, AY 2019, 'Secure authentication and load balancing of distributed edge datacenters', JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, vol. 124, pp. 60-69.
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Qin, C, Ni, W, Tian, H, Lu, L & Liu, RP 2019, 'Radio over Cloud (RoC): Cloud-Assisted Distributed Beamforming for Multi-class Traffic', IEEE Transactions on Mobile Computing.
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IEEE Cloud has yet to be applied to computationally intensive radio signal processing, due to closely coupled computing tasks resulting from interference. This paper presents a new cloud-assisted joint beamforming architecture, where computations are decoupled for individual wireless users and pipelined for cloud execution, using Difference of Convex (DC), l1-norm approximations, and dual decompositions. User-specific tasks are constructed and aligned with the cloud to leverage computation reuses and minimize overhead. The time-complexity is dramatically improved to support networks with tens to hundreds of base stations and users, without compromising the sum rate and quality-of-service. Further, the superiority of DC to the state-of-the-art Weighted Minimum Mean Square Error (WMMSE) in terms of convex relaxation is observed and discussed. Corroborated by simulations, the reason is revealed as WMMSE aggressively increases the data rate at interim stages, hence adversely interacting with l1-norm approximation and reducing the feasible solution regions at later stages.
Qin, P-Y, Song, L-Z & Guo, YJ 2019, 'Beam Steering Conformal Transmitarray Employing Ultra-Thin Triple-Layer Slot Elements', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 67, no. 8, pp. 5390-5398.
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Rahman, MA, Islam, MR, Muttaqi, KM, Guo, Y, Zhu, J, Sutanto, D & Lei, G 2019, 'A Modified Carrier-Based Advanced Modulation Technique for Improved Switching Performance of Magnetic-Linked Medium-Voltage Converters', IEEE Transactions on Industry Applications, vol. 55, no. 2, pp. 2088-2098.
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© 1972-2012 IEEE. The high-frequency magnetic link is gaining popularity due to its lightweight, small volume, and inherent voltage balancing capability. Those features can simplify the utilization of a multilevel converter (MLC) for the integration of renewable energy sources to the grid with compact size and exert economic feasibility. The modulation and control of the MLC are crucial issues, especially for grid-connected applications. To support the grid, the converter may need to operate in an overmodulation (OVM) region for short periods depending upon the loading conditions. This OVM operation of the converter causes increased harmonic losses and adverse effects on the overall system efficiency. On top of that, the size and cost of filtering circuitry become critical to eliminate the unwanted harmonics. In this regard, a modified OVM scheme with phase-disposed carriers for a grid-connected high-frequency magnetic-link-based cascaded H-bridge (CHB) MLC is proposed for the suppression of harmonics and the reduction of converter loss. Furthermore, with the proposed OVM technique, the voltage gain with the modulation index can be increased up to the range which is unlikely to be achieved using the classical ones. Extensive simulations are carried out with a 2.24 MVA permanent magnet synchronous generator based wind energy conversion system, which is connected to the 11 kV ac grid through a high-frequency magnetic-link and a five-level CHB MLC. A scaled down laboratory prototype is implemented to validate the performance of the converter.
Rakhshani, E, Rouzbehi, K, Sanchez, AJ, Cabrera Tobar, A & Pouresmaeil, E 2019, 'Integration of Large Scale PV-Based Generation into Power Systems: A Survey', ENERGIES, vol. 12, no. 8.
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Rao, T, Li, X, Zhang, H & Xu, M 2019, 'Multi-level region-based Convolutional Neural Network for image emotion classification', NEUROCOMPUTING, vol. 333, pp. 429-439.
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Raza, A, Mustafa, A, Rouzbehi, K, Jamil, M, Gilani, SO, Abbas, G, Farooq, U & Shehzad, MN 2019, 'Optimal Power Flow and Unified Control Strategy for Multi-Terminal HVDC Systems', IEEE ACCESS, vol. 7, pp. 92642-92650.
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Ren, C, Lyu, X, Ni, W, Tian, H & Liu, RP 2019, 'Distributed Online Learning of Fog Computing under Nonuniform Device Cardinality', IEEE Internet of Things Journal, vol. 6, no. 1, pp. 1147-1159.
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© 2014 IEEE. Processing data around the point of capture, fog computing can support computationally demanding Internet-of-Things (IoT) services. Distributed online optimization is important given the size of IoT, but challenging due to time variations of random traffic and nonuniform connectivity (or cardinality) of edge servers and IoT devices. This paper presents a distributed online learning approach to asymptotically minimizing the time-average cost of fog computing in the absence of the a-priori knowledge on traffic randomness, for light-weight, and delay-tolerant application scenarios. Stochastic gradient descent is exploited to decouple the optimizations between time slots. A graph matching problem is then formulated for every time slot by decoupling and unifying the nonuniform cardinalities, and solved in a distributed manner by developing a new linear (1/2)-approximation method. We prove that the optimality loss resulting from the distributed approximate graph matching method can be compensated and diminish by increasing the learning time. Corroborated by simulations, the proposed distributed online learning is asymptotically optimal and superior to the state of the art in terms of throughput and energy efficiency.
Ren, C, Lyu, X, Ni, W, Tian, H & Liu, RP 2019, 'Profitable Cooperative Region for Distributed Online Edge Caching', IEEE TRANSACTIONS ON COMMUNICATIONS, vol. 67, no. 7, pp. 4696-4708.
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Rezazadeh, J, Moradi, M, Sandrasegaran, K & Farahbakhsh, R 2019, 'Transmission Power Adjustment Scheme for Mobile Beacon-Assisted Sensor Localization', IEEE Transactions on Industrial Informatics, vol. 15, no. 5, pp. 2859-2869.
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Roselin, AG, Nanda, P, Nepal, S & He, X 2019, 'Testbed Evaluation of Lightweight Authentication Protocol(LAUP) fo r6LoWPAN wireless sensor networks', Concurrency and Computation: Practice and Experience.
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Rouzbehi, K, Baa Wafaa, M & Rakhshani, E 2019, 'An Imperialist Competitive Algorithm-Based Multi-Objective Optimization for Voltage Source Converter High-Voltage Direct Current Stations Control in Multi-Terminal HVDC Grids', Electric Power Components and Systems, vol. 47, no. 4-5, pp. 316-328.
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©, Copyright © Taylor & Francis Group, LLC. This article presents a multi-objective-based imperialist competitive algorithm (ICA) for optimal tuning of voltage source converter (VSC) stations control parameters in multi-terminal high-voltage direct current (MT-HVDC) grid. The key objective here is to enhance the control performance of the MT-HVDC grid VSC-HVDC stations under dynamic situations. As VSC-HVDC stations are non-linear apparatuses of the MT-HVDC grids, conventional methods for the tuning of the control parameters which are commonly based on approximated linear plant models do not reach to optimal results. Therefore, as the main contribution of this research, an effective ICA-based multi-objective optimization technique is adopted for optimal tuning of the VSC-HVDC stations control parameters. The proposed composite objective function in this algorithm consists of both inner and outer loop parameter optimization characteristics. A fuzzification technique is used in this study to normalize all objective functions and to find the optimal solution. To confirm the merits of the presented optimization method, a detailed model of a four-terminal MT-HVDC grid is developed and its transient and steady-state performance in case of classically and ICA tuned have been studied and compared.
Rouzbehi, K, Miranian, A, Escaño, JM, Rakhshani, E, Shariati, N & Pouresmaeil, E 2019, 'A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid', Electronics, vol. 8, no. 5, pp. 493-493.
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This paper develops a data-driven strategy for identification and voltage control for DC-DC power converters. The proposed strategy does not require a pre-defined standard model of the power converters and only relies on power converter measurement data, including sampled output voltage and the duty ratio to identify a valid dynamic model for them over their operating regime. To derive the power converter model from the measurements, a local model network (LMN) is used, which is able to describe converter dynamics through some locally active linear sub-models, individually responsible for representing a particular operating regime of the power converters. Later, a local linear controller is established considering the identified LMN to generate the control signal (i.e., duty ratio) for the power converters. Simulation results for a stand-alone boost converter as well as a bidirectional converter in a test DC microgrid demonstrate merit and satisfactory performance of the proposed data-driven identification and control strategy. Moreover, comparisons to a conventional proportional-integral (PI) controllers demonstrate the merits of the proposed approach.
Sang, L, Xu, M, Qian, S & Wu, X 2019, 'Multi-modal multi-view Bayesian semantic embedding for community question answering', NEUROCOMPUTING, vol. 334, pp. 44-58.
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Saputra, Y, Dinh, H, Nguyen, D & Dutkiewicz, E 2019, 'A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation', IEEE Transactions on Mobile Computing (TMC).
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Saputra, YM, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Kim, DI 2019, 'Distributed Deep Learning at the Edge: A Novel Proactive and Cooperative Caching Framework for Mobile Edge Networks', IEEE Wireless Communications Letters, pp. 1-1.
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Sarker, PC, Islam, MR, Guo, Y, Zhu, J & Lu, HY 2019, 'State-of-The-Art Technologies for Development of High Frequency Transformers with Advanced Magnetic Materials', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2.
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© 2002-2011 IEEE. With the development of advanced soft magnetic materials of high-saturation flux density and low specific core loss and semiconductor power devices, the high-frequency transformer (HFT) has received significant attention in recent years for its widespread emerging applications. The optimal design of high-power-density HFTs for high-performance energy conversion systems is, however, a multiphasic problem that needs special considerations on various aspects such as core material selection, minimization of parasitic components, and thermal management. This paper presents a comprehensive review on advancement of soft magnetic materials for high-power-density magnetic devices and advanced technologies for characterizations and optimal design of HFTs. The future research and development trends are also discussed.
Sattarian, M, Rezazadeh, J, Farahbakhsh, R & Bagheri, A 2019, 'Indoor navigation systems based on data mining techniques in internet of things: a survey', Wireless Networks, vol. 25, no. 3, pp. 1385-1402.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Internet of Things (IoT) is turning into an essential part of daily life, and numerous IoT-based scenarios will be seen in future of modern cities ranging from small indoor situations to huge outdoor environments. In this era, navigation continues to be a crucial element in both outdoor and indoor environments, and many solutions have been provided in both cases. On the other side, recent smart objects have produced a substantial amount of various data which demands sophisticated data mining solutions to cope with them. This paper presents a detailed review of previous studies on using data mining techniques in indoor navigation systems for the loT scenarios. We aim to understand what type of navigation problems exist in different IoT scenarios with a focus on indoor environments and later on we investigate how data mining solutions can provide solutions on those challenges.
Seifollahi, S, Bagirov, A, Zare Borzeshi, E & Piccardi, M 2019, 'A simulated annealing‐based maximum‐margin clustering algorithm', Computational Intelligence, vol. 35, pp. 23-41.
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Maximum‐margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing‐based algorithm that is able to mitigate the issue of local minima in the maximum‐margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k‐means++ and SVM at each step of the annealing process. More precisely, k‐means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.
Shalby, M, Dorrell, D & Walker, P 2019, 'Multi–chamber oscillating water column wave energyconverters and air turbines: A review', International Journal of Energy Research.
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Shen, W, Wu, Y, Yuan, J, Duan, L, Zhang, J & Jia, Y 2019, 'Robust Distracter-Resistive Tracker via Learning a Multi-Component Discriminative Dictionary', IEEE Transactions on Circuits and Systems for Video Technology.
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IEEE Discriminative dictionary learning (DDL) provides an appealing paradigm for appearance modeling in visual tracking. However, most existing DDL based trackers cannot handle drastic appearance changes, especially for scenarios with background cluster and/or similar object interference. One reason is that they often suffer from the loss of subtle visual information which is critical to distinguish an object from distracters. In this paper, we explore the use of deep features extracted from the Convolutional Neural Networks (CNNs) to improve the object representation and propose a robust distracter-resistive tracker via learning a multi-component discriminative dictionary. The proposed method exploits both the intra-class and the interclass visual information to learn shared atoms and the classspecific atoms. By imposing several constraints into the objective function, the learned dictionary is reconstructive, compressive and discriminative, thus can better distinguish an object from the background. In addition, our convolutional features (deep features extracted from CNNs) have structural information for object localization and balance the discriminative power and semantic information of the object. Tracking is carried out within a Bayesian inference framework where a joint decision measure is used to construct the observation model. To alleviate the drift problem, the reliable tracking results obtained online are accumulated to update the dictionary. Both the qualitative and quantitative results on the CVPR2013 benchmark, the VOT2015 dataset and the SPOT dataset demonstrate that our tracker achieves better performance over the state-of-the-art approaches.
Shi, J, Chu, L & Braun, R 2019, 'A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method', International journal of molecular sciences, vol. 20, pp. 2355-2355.
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Shi, T, Tang, MC, Wu, Z, Xu, HX & Ziolkowski, RW 2019, 'Improved signal-to-noise ratio, bandwidth-enhanced electrically small antenna augmented with internal non-foster elements', IEEE Transactions on Antennas and Propagation, vol. 67, no. 4, pp. 2763-2768.
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© 1963-2012 IEEE. Non-Foster technology facilitates the ability to surpass the Chu bandwidth limit associated with electrically small antennas (ESAs). Nonetheless, in addition to challenging stability issues, the enhanced performance can come at the cost of increased noise and resistance losses generated by the active circuit. Consequently, low total efficiency and degraded signal-to-noise ratio (SNR) values can arise. Stability and SNR have dominated most reports to date; little has been discussed with regard to the underlying innovative physics of non-Foster augmented radiators. In this communication, we propose a broad bandwidth non-Foster ESA, emphasizing those aspects. By embedding a non-Foster element into the near-field resonant parasitic element of a metamaterial-inspired antenna, its electrically small size is maintained. On the other hand, a 5-times enhancement of its -10 dB fractional bandwidth (15 times its -3 dB bandwidth) is measured, significantly surpassing its passive Chu limit. Under a good matching, the measurements demonstrate that this non-Foster ESA achieves a 1.05 dBi peak gain and realizes average 5.0 dB SNR and 17 dB gain improvements over its passive counterpart.
Shi, X, Zhu, J, Li, L & Lu, DDC 2019, 'Model-Predictive-Based Duty Cycle Control with Simplified Calculation and Mutual Influence Elimination for AC/DC Converter', IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 1, pp. 504-514.
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© 2013 IEEE. The single-vector-based model-predictive-based direct power control (MPDPC) is commonly used for control of three-phase full-bridge ac/dc converters, but it could only select the best switching vector to be implemented. Due to the limited number of voltage vectors in a two-level three-phase converter, the sampling frequency needs to be high to achieve an acceptable performance. Also, it bears variable switching frequency that causes spread spectrum nature of harmonics. In this paper, a three-vector-based simplified model predictive duty cycle control (SMPDCC) is proposed. The adjacent two nonzero vectors are selected by evaluating the effects of each vector pairs based on the revised cost function. The duration calculation is simplified compared with the conventional predictive duty cycle control (CPDCC) by allocating a control period in reciprocal proportion with the corresponding cost function value of the selected vectors. Besides, the negative duration issue of CPDCC could be completely avoided and the mutual influence elimination ability could be realized. A comparative study with MPDPC and CPDCC has been conducted to verify the superiority of the proposed scheme by the simulation and experimental results. It shows that the SMPDCC has the advantages of lower power ripple, fixed switching frequency, lower total harmonic distortion, and mutual influence elimination ability.
Shi, X, Zhu, J, Li, L, Lu, DDC, Zhang, J & Yang, H 2019, 'Predictive Duty Cycle Control with Reversible Vector Selection for Three-Phase AC/DC Converters', IEEE Transactions on Power Electronics.
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IEEE The conventional predictive duty cycle control (CPDCC) of three-phase full-bridge AC/DC converters selects adjacent non-zero vector pair based on the grid-voltage vector location, then the duration for each vector is calculated. Though the vector selection method is quite simple, it has a significant disadvantage that the values of calculated durations could be frequently less than zero due to non-optimal vector selection, which results in high current harmonics and power notches. It could be improved with improved predictive duty cycle control (IPDCC) by reselecting the non-zero vector pair when negative duration exists, however, the whole vector selection and calculation procedure are repeated. By theoretical verification that the power variation rates of reversible vector pair are symmetrical with respect to that of zero vector, this paper proposes the reversible predictive duty cycle control (RPDCC) simply by replacing the original vector with its opposite vector and the recalculation of vector duration is eliminated compared with IPDCC. Thus the calculation effort is almost not increased compared with CPDCC while system performance is significantly improved. The proposed control is theoretically derived and verified with the simulation and experimental results showing that RPDCC has better steady and dynamic performance than CPDCC and IPDCC methods.
Shi, X, Zhu, J, Lu, D & Li, L 2019, 'Multi-functional model predictive control with mutual influence elimination for three-phase AC/DC converters in energy conversion', Energies, vol. 12, no. 9.
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© 2019 by the authors. Conventional model predictive control (MPC)-based direct power control of the three-phase full-bridge AC/DC converter usually suffers from the parametric coupling between active and reactive powers. A reference change of either the active or reactive power will influence the other, deteriorating the dynamic-state performance. In addition, the steady-state performance affected by one-step-delay arising from computation and communication processes in the digital implementation should be improved in consideration of switching frequency reduction. In combination with the proposed novel mutual influence elimination constraint, this paper proposes the multi-functional MPC for three-phase full-bridge AC/DC converters to improve both the steady and dynamic performances simultaneously. It has various advantages such as one-step-delay compensation, power ripple reduction, and switching frequency reduction for steady-state performance as well as mutual influence elimination for dynamic capability. The simulation and experimental results are obtained to verify the effectiveness of the proposed method.
Shi, Z, Sun, X, Cai, Y, Yang, Z, Lei, G, Guo, Y & Zhu, J 2019, 'Torque Analysis and Dynamic Performance Improvement of a PMSM for EVs by Skew Angle Optimization', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2.
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© 2018 IEEE. In this paper, a permanent magnet synchronous machine (PMSM) for electric vehicles (EVs) is studied. Since EVs need to face some low speed road conditions, it is necessary to drive the machine to maintain a stable torque at low speed. The stator skew slot is often adopted to reduce torque ripple; however, it declines the output torque at same time. Besides, the difference between positive rotation performance and negative rotation performance, which caused by the skew slot are often ignored. Through the finite element analysis, the cogging torque and dynamic performance of the PMSM at different skew angle are studied. Moreover, the different influence of slot skew angle on positive and negative rotation performance is studied. Then, the optimum skew angle of the PMSM is studied through comprehensive consideration. Finally, the cogging torque of the prototype is verified to be less than 2 N·m through the experiment.
Singh, AM & Ha, QP 2019, 'Fast Terminal Sliding Control Application for Second-order Underactuated Systems', International Journal of Control, Automation and Systems, vol. 17, no. 8, pp. 1884-1898.
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© 2019, ICROS, KIEE and Springer. In this paper, we propose a robust and finite-time control method, based on the terminal sliding mode (TSM), for a class of two-degree-of-freedom (2-DOF) underactuated electromechanical systems subject to bounded uncertainties and disturbances. First, the proposed Fast Terminal Sliding Mode (FTSM) method is presented. Then for the underactuated system control, hierarchical sliding surfaces are defined, consisting of two layers. In the first layer, separate FTSM sliding functions are selected for each state of the system. In the second layer, the system sliding manifold is a linear combination of the first layer sliding surfaces. A control law is derived and stability conditions of the nonlinear system are obtained by using the Lyapunov theory. To verify the effectiveness of our proposed method, the developed control technique is applied to control both the swinging load and the cart position of an underactuated gantry crane. Extensive simulation and real-time experiments demonstrate enhanced performance of the system and robustness against parametric variations in comparison to conventional TSM and sliding mode control.
Siwakoti, Y, Mahajan, A, Rogers, D & Blaabjerg, F 2019, 'A Novel Seven-Level Active Neutral Point Clamped Converter with Reduced Active Switching Devices and DC-link Voltage', IEEE Transactions on Power Electronics, pp. 1-1.
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Siwakoti, YP, Mostaan, A, Abdelhakim, A, Davari, P, Soltani, M, Khan, MNH, Li, L & Blaabjerg, F 2019, 'High Voltage Gain Quasi-SEPIC DC-DC Converter', IEEE Journal of Emerging and Selected Topics in Power Electronics.
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IEEE This paper proposes a modified coupled-inductor SEPIC dc-dc converter for high voltage gain (2 < G < 10) applications. It utilizes the same components as the conventional SEPIC converter with an additional diode. The voltage stress on the switch is minimal, which helps the designer to select a low voltage and low RDS-on MOSFET, resulting in a reduction of cost, conduction and turn ON losses of the switch. Compared to equivalent topologies with similar voltage gain expression, the proposed topology uses lower component-count to achieve the same or even higher voltage gain. This helps to design a very compact and lightweight converter with higher power density and reliability. Operating performance, steady-state analysis and mathematical derivations of the proposed dc-dc converter have been demonstrated in the paper. Moreover, extension of the circuit for higher gain (G>10) application is also introduced and discussed. Finally, the main features of the proposed converter have been verified through simulation and experimental results of a 400 W laboratory prototype. The efficiency is almost flat over a wide range of load with the highest measured efficiency of 96.2%, and the full-load efficiency is 95.2% at a voltage gain of 10.
Siyari, P, Krunz, MM & Nguyen, D 2019, 'Distributed Power Control in Single-stream MIMO Wiretap Interference Networks with Full-duplex Jamming Receivers', IEEE Transactions on Signal Processing.
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Song, B, Wang, X, Ni, W, Song, Y, Liu, RP, Jiang, GP & Guo, YJ 2019, 'Reliability Analysis of Large-Scale Adaptive Weighted Networks', IEEE Transactions on Information Forensics and Security.
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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.
Sun, F, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Zhang, X 2019, 'Design of millimeter-wave bandpass filters with broad bandwidth in Si-based technology', IEEE Transactions on Electron Devices, vol. 66, no. 3, pp. 1174-1181.
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© 2019 IEEE. In this paper, a novel design approach is proposed for on-chip bandpass filter (BPF) design with improved passband flatness and stopband suppression. The proposed approach simply uses a combination of meander-line structures with metal-insulator-metal (MIM) capacitors. To demonstrate the insight of this approach, a simplified equivalent LC-circuit model is used for theoretical analysis. Using the analyzed results as a guideline along with a full-wave electromagnetic (EM) simulator, two BPFs are designed and implemented in a standard 0.13-μm (Bi)-CMOS technology. The measured results show that good agreements between EM simulated and measured results are achieved. For the first BPF, the return loss is better than 10 dB from 13.5 to 32 GHz, which indicates a fractional bandwidth (FBW) of more than 78%. In addition, the minimum insertion loss of 2.3 dB is achieved within the frequency range from 17 to 27 GHz and the in-band magnitude ripple is less than 0.1 dB. The chip size of this design, excluding the pads, is 0.148 mm 2 . To demonstrate a miniaturized design, a second design example is given. The return loss is better than 10 dB from 17.3 to 35.9 GHz, which indicates an FBW of more than 70%. In addition, the minimum insertion loss of 2.6 dB is achieved within the frequency range from 21.4 to 27.7 GHz and the in-band magnitude ripple is less than 0.1 dB. The chip size of the second design, excluding the pads, is only 0.066 mm 2 .
Sun, H-H, Ding, C, Zhu, H, Jones, B & Guo, YJ 2019, 'Suppression of Cross-Band Scattering in Multiband Antenna Arrays', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 67, no. 4, pp. 2379-2389.
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Sun, X, Diao, K, Lei, G, Guo, Y & Zhu, J 2019, 'Study on Segmented-Rotor Switched Reluctance Motors With Different Rotor Pole Numbers for BSG System of Hybrid Electric Vehicles', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 68, no. 6, pp. 5537-5547.
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Sun, X, Gui, G, Li, Y, Liu, RP & An, Y 2019, 'ResInNet: A Novel Deep Neural Network with Feature Reuse for Internet of Things', IEEE Internet of Things Journal, vol. 6, no. 1, pp. 679-691.
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© 2014 IEEE. Deep neural networks (DNNs) have widely used in various Internet-of-Things (IoT) applications. Pursuing superior performance is always a hot spot in the field of DNN modeling. Recently, feature reuse provides an effective means of achieving favorable nonlinear approximation performance in deep learning. Existing implementations utilizes a multilayer perception (MLP) to act as a functional unit for feature reuse. However, determining connection weight and bias of MLP is a rather intractable problem, since the conventional back-propagation learning approach encounters the limitations of slow convergence and local optimum. To address this issue, this paper develops a novel DNN considering a well-behaved alternative called reservoir computing, i.e., reservoir in network (ResInNet). In this structure, the built-in reservoir has two notable functions. First, it behaves as a bridge between any two restricted Boltzmann machines in the feature learning part of ResInNet, performing a feature abstraction once again. Such reservoir-based feature translation provides excellent starting points for the following nonlinear regression. Second, it serves as a nonlinear approximation, trained by a simple linear regression using the most representative (learned) features. Experimental results over various benchmark datasets show that ResInNet can achieve the superior nonlinear approximation performance in comparison to the baseline models, and produce the excellent dynamic characteristics and memory capacity. Meanwhile, the merits of our approach is further demonstrated in the network traffic prediction related to real-world IoT application.
Sun, X, Hu, C, Zhu, J, Wang, S, Zhou, W, Yang, Z, Lei, G, Li, K, Zhu, B & Guo, Y 2019, 'MPTC for PMSMs of EVs With Multi-Motor Driven System Considering Optimal Energy Allocation', IEEE TRANSACTIONS ON MAGNETICS, vol. 55, no. 7.
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Sun, Y, Yue, H, Zhang, J & Booth, C 2019, 'Minimisation of residential energy cost considering energy storage system and EV with driving usage probabilities', IEEE Transactions on Sustainable Energy.
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Sutton, G, Liu, RP & Guo, J 2019, 'Coexistence Performance and Limits of Frame-Based Listen-Before-Talk', IEEE Transactions on Mobile Computing, pp. 1-1.
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Sutton, GJ, Zeng, J, Liu, RP, Ni, W, Nguyen, DN, Jayawickrama, BA, Huang, X, Abolhasan, M, Zhang, Z, Dutkiewicz, E & Lv, T 2019, 'Enabling Technologies for Ultra-Reliable and Low Latency Communications: From PHY and MAC Layer Perspectives', IEEE Communications Surveys & Tutorials, pp. 1-1.
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Taghvaie, A, Alijani, A, Adabi, ME, Rezanejad, M, Adabi, J, Rouzbehi, K & Pouresmaeil, E 2019, 'An Asymmetrical Step-Up Multilevel Inverter Based on Switched-Capacitor Network', SUSTAINABILITY, vol. 11, no. 12.
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Taghvaie, A, Alijani, A, Ebrahim Adabi, M, Rezanejad, M, Adabi, J, Rouzbehi, K & Pouresmaeil, E 2019, 'An asymmetrical step-up multilevel inverter based on switched-capacitor network', Sustainability (Switzerland), vol. 11, no. 12.
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© 2019 by the authors. This paper presents a transformerless step-upmultilevel inverter based on a switched-capacitor structure. One of the main contributions of the proposed topology is replacing the separated DC voltage sourcewith capacitorswhich are charged at predetermined time intervals. Therefore, a high-level staircase voltage waveform can be achieved by discharging some of these capacitors on the load. The other contribution of the proposed structure is to eliminate themagnetic elements which traditionally boost the input DC voltage. In addition, asymmetrical or unequal amounts of capacitor voltages create more voltage levels, which enable voltage level increments without increasing the number of semiconductor devices. This paper introduces a self-balanced boost Switched-CapacitorsMultilevel Inverter (SCMLI) which is able to create a nearly sinusoidal voltage waveform with a maximum voltage of up to 45 times that of the input voltage DC source. Higher level output voltage levels are also achievable by extending the circuit topology. After determination of the switching angles and selecting the proper switching states for each level, an offline NLC method is used for modulation, which eases the control implementation. Analysis, simulation and experiments are carried out for a 91-level inverter (45 levels for positive and negative voltages and one for zero voltage) are presented.
Tang, MC, Duan, Y, Wu, Z, Chen, X, Li, M & Ziolkowski, RW 2019, 'Pattern reconfigurable, vertically polarized, low-profile, compact, near-field resonant parasitic antenna', IEEE Transactions on Antennas and Propagation, vol. 67, no. 3, pp. 1467-1475.
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© 1963-2012 IEEE. A vertically polarized, low-profile, compact, near-field resonant parasitic antenna with pattern reconfigurability is demonstrated. The antenna has three dynamic end-fire states facilitated with only three p-i-n diodes. The radiation pattern in each state covers more than 120° in its azimuth plane and, hence, it achieves beam scanning that covers the entire azimuth plane. The antenna height and transverse size are, respectively, only 0.048λ 0 and 0.1λ 02 . Measured results, in good agreement with their simulated values, demonstrate that the antenna exhibits a 11% fractional impedance bandwidth, and a 6.6 dBi peak realized gain in all three of its pattern-reconfigurable states. Stable and high peak realized gain values are realized over its entire operational band surrounding 2.22 GHz.
Tang, M-C, Li, D, Chen, X, Wang, Y, Hu, K & Ziolkowski, RW 2019, 'Compact, Wideband, Planar Filtenna With Reconfigurable Tri-Polarization Diversity', IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, vol. 67, no. 8, pp. 5689-5694.
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Tang, MC, Wu, Z, Shi, T & Ziolkowski, RW 2019, 'Dual-Band, Linearly Polarized, Electrically Small Huygens Dipole Antennas', IEEE Transactions on Antennas and Propagation, vol. 67, no. 1, pp. 37-47.
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© 1963-2012 IEEE. Two electrically small, dual-band Huygens dipole antennas are reported. In both designs, two pairs of magnetic and electric near-field resonant parasitic (NFRP) elements are combined organically within an electrically small, low profile package. The NFRP elements are excited effectively using only one coaxial-fed-driven element. One dual-band Huygens system produces parallel, linearly polarized (LP) fields at its two operating frequencies. The other dual-band system produces two orthogonal LP fields. Additional parasitic elements are introduced to mitigate the mutual coupling effects between the pairs of NFRP elements. The measured values for prototypes of both antennas in the L-band demonstrate their electrically small size (ka< 1) and low profile (∼ 0.03λ0). They also confirm their broadside radiation and polarization performance characteristics, as well as the isolation between each operating frequency. Their fractional bandwidths, peak realized gains, front-to-back ratios, and radiation efficiencies are, respectively, 0.6%, > 2 dBi, > 10 dB, and > 60% at both frequencies. These dual-band systems would provide multifunctional performance in a variety of portable, compact wireless devices.
Teng, QF, Cui, HW, Zhu, JG, Guo, YG & Tian, J 2019, 'Current sensorless-based model predictive control for PMSM drive system', Dianji yu Kongzhi Xuebao/Electric Machines and Control, vol. 23, no. 5, pp. 119-128.
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© 2019, Harbin University of Science and Technology Publication. All right reserved. Based on extended state observer (ESO), a novel model predictive torque control (MPTC) strategy was developed for three phase permanent magnet synchronous motor (PMSM) drive system with current sensorless. To achieve high precision control, generally two phase current sensors are indispensable for successful operation of the feedback control. For this purpose, by use of technique of ESO, a new observer for estimating three phase currents and time-varying stator resistance was put forward. Moreover, to reduce torque and flux ripples and improve the performance of the torque and speed, MPTC strategy was employed. The resultant ESO-based MPTC strategy enables PMSM drive system not only to run stably and reliably but also to have satisfactory control performance and strong robustness. The simulation results validate the feasibility and effectiveness of the proposed scheme.
Thomas, D, Shankaran, R, Orgun, M, Hitchens, M & Ni, W 2019, 'Energy-Efficient Military Surveillance: Coverage Meets Connectivity', IEEE Sensors Journal, vol. 19, no. 10, pp. 3902-3911.
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© 2001-2012 IEEE. Sensor networks are increasingly being used in the development and application of military surveillance systems. Small size battery-powered sensor devices are deployed in unattended and hostile environments, such as battlefields to detect any physical intrusion. Energy efficiency, coverage, and connectivity are the three major quality-of-service requirements of such mission critical applications. Energy-efficient communication is required to prolong the network lifetime. Better coverage is required to detect the physical intrusion attempts of all kinds. Similarly, connectivity is necessary to provide mission critical messages to the base station in a timely manner. A scheme that satisfies energy efficiency, coverage, and connectivity requirements is an N-P complete problem. This paper proposes an energy-efficient node scheduling algorithm called EC2 that addresses the problems of energy efficiency, coverage, and connectivity in military surveillance applications using the fuzzy graphs.
Tian, J, Li, R, Yoo, SH, Poumellec, B, Garcia-Caurel, E, Ossikovski, R, Stchakovsky, M, Eypert, C, Canning, J & Lancry, M 2019, 'Spectral dependence of femtosecond laser induced circular optical properties in silica', OSA Continuum, vol. 2, no. 4, pp. 1233-1242.
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© 2019 Optical Society of America. Transmission Mueller-matrix spectroscopic ellipsometry is applied to study femtosecond laser induced nanogratings in silica glass in a wide spectral range 250-1800 nm. By using differential decomposition of the Mueller matrix, the circular birefringence and dichroism of femtosecond laser irradiated SiO2 are quantified for the first time in the UV and near-IR range. A maximum value of the effective specific rotation of α ~ -860°/mm at 290 nm is found. In the near-IR range, we found a linear and circular dichroism band peaking around 1240 nm, which might be attributed to the formation of anisotropic species like the formation of oriented OH species and Si-O-Si bond.
Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2019, 'Low-Frequency Metamaterial Absorber Using Space-Filling Curve', Journal of Electronic Materials.
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Tuan, HD, Nasir, AA, Nguyen, HH, Duong, TQ & Poor, HV 2019, 'Non-Orthogonal Multiple Access with Improper Gaussian Signaling', IEEE Journal on Selected Topics in Signal Processing, vol. 13, no. 3, pp. 496-507.
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© 2007-2012 IEEE. Improper Gaussian signaling (IGS) helps to improve the throughput of a wireless communication network by taking advantage of the additional degrees of freedom in signal processing at the transmitter. This paper exploits IGS in a general multiuser multi-cell network, which is subject to both intra-cell and inter-cell interference. With IGS under orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), designs of transmit beamforming to maximize the users' minimum throughput subject to transmit power constraints are addressed. Such designs are mathematically formulated as nonconvex optimization problems of structured matrix variables, which cannot be solved by popular techniques such as weighted minimum mean square error or convex relaxation. By exploiting the lowest computational complexity of 2× 2 linear matrix inequalities, lower concave approximations are developed for throughput functions, which are the main ingredients for devising efficient algorithms for finding solution of these difficult optimization problems. Numerical results obtained under practical scenarios reveal that there is an almost two-fold gain in the throughput by employing IGS instead of the conventional proper Gaussian signaling under both OMA and NOMA; and NOMA-IGS offers better throughput compared to that achieved by OMA-IGS.
Tuan, HD, Nasir, AA, Nguyen, MN & Masood, M 2019, 'Han-Kobayashi Signaling in MIMO Broadcasting', IEEE Communications Letters.
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IEEE This letter applies Han-Kobayashi (H-K) superposition signaling to a network of a multi-antenna transmitter serving two multi-antenna users. By making the rate of the common message for both users contribute to user individual rate, it shows that H-K superposition signaling clearly outperforms both stateof- the-art orthogonal multiaccess (OMA) and nonorthogonal multiaccess schemes (NOMA) in terms of the worst user rate. More importantly, unlike NOMA, H-K superposition signaling does not require the user channels to be differentiated for efficient implementation.
Tuan, LA, Ha, Q & Van Trieu, P 2019, 'Observer-Based Nonlinear Robust Control of Floating Container Cranes Subject to Output Hysteresis', Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, vol. 141, no. 11.
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© 2019 by ASME. A container crane mounted on a pontoon is utilized to transfer containers to smaller ships when a large container ship cannot reach the shallow water port. The shipboard container is considered as an underactuated system having complicated kinematic constraints and hysteretic nonlinearities, with only two actuators to conduct simultaneous tasks: tracking the trolley to destination, lifting the container to the desired cable length, and suppressing the axial container oscillations and container swing. Parameter variations, wave-induced motions of the ship, wind disturbance, and nonlinearities remain challenges for control of floating container cranes. To deal with these problems, this study presents the design of two nonlinear robust controllers, taking into account the influence of the output hysteresis, and using velocity feedback from a state observer. Control performance of the proposed controllers is verified in both simulation and experiments. Together with consistently stabilizing outputs, the proposed control approach well rejects hysteresis and disturbance.
Usman, M, He, X, Lam, KKM, Xu, M, Chen, J, Bokhari, SMM & Jan, MA 2019, 'Error Concealment for Cloud-based and Scalable Video Coding of HD Videos', IEEE Transactions on Cloud Computing.
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IEEE The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bit-rates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.
Usman, M, Jan, MA, He, X & Chen, J 2019, '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 & Chen, J 2019, 'P2DCA: A Privacy-Preserving-Based Data Collection and Analysis Framework for IoMT Applications', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 37, no. 6, pp. 1222-1230.
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Usman, M, Jan, MA, He, X & Nanda, P 2019, '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.
Van Huynh, N, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Wang, P 2019, 'Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning', IEEE Transactions on Communications, pp. 1-1.
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Van Huynh, N, Thai Hoang, D, Nguyen, DN & Dutkiewicz, E 2019, 'Optimal and Fast Real-Time Resource Slicing with Deep Dueling Neural Networks', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 37, no. 6, pp. 1455-1470.
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© 1983-2012 IEEE. Effective network slicing requires an infrastructure/network provider to deal with the uncertain demands and real-time dynamics of the network resource requests. Another challenge is the combinatorial optimization of numerous resources, e.g., radio, computing, and storage. This paper develops an optimal and fast real-time resource slicing framework that maximizes the long-term return of the network provider while taking into account the uncertainty of resource demands from tenants. Specifically, we first propose a novel system model that enables the network provider to effectively slice various types of resources to different classes of users under separate virtual slices. We then capture the real-time arrival of slice requests by a semi-Markov decision process. To obtain the optimal resource allocation policy under the dynamics of slicing requests, e.g., uncertain service time and resource demands, a Q-learning algorithm is often adopted in the literature. However, such an algorithm is notorious for its slow convergence, especially for problems with large state/action spaces. This makes Q-learning practically inapplicable to our case, in which multiple resources are simultaneously optimized. To tackle it, we propose a novel network slicing approach with an advanced deep learning architecture, called deep dueling, that attains the optimal average reward much faster than the conventional Q-learning algorithm. This property is especially desirable to cope with the real-time resource requests and the dynamic demands of the users. Extensive simulations show that the proposed framework yields up to 40% higher long-term average return while being few thousand times faster, compared with the state-of-the-art network slicing approaches.
Van Thanh, P, Tran, DT, Nguyen, DC, Duc Anh, N, Nhu Dinh, D, El-Rabaie, S & Sandrasegaran, K 2019, 'Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers', Arabian Journal for Science and Engineering, vol. 44, no. 4, pp. 3329-3342.
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© 2018, King Fahd University of Petroleum & Minerals. Falls represent a major problem for the elderly people aged 60 or above. There are many monitoring systems which are currently available to detect the fall. However, there is a great need to propose a system which is of optimal effectiveness. In this paper, we propose to develop a low-cost fall detection system to precisely detect an event when an elderly person accidentally falls. The fall detection algorithm compares the acceleration with lower fall threshold and upper fall threshold values to accurately detect a fall event. The post-fall recognition module is the combination of posture recognition and vertical velocity estimation that has been added to our proposed method to enhance the performance and accuracy. In case of a fall, our device will transmit the location information to the contacts instantly via SMS and voice call. A smartphone application will ensure that the notifications are delivered to the elderly person’s relatives so that medical attention can be provided with minimal delay. The system was tested by volunteers and achieved 100% sensitivity and accuracy. This was confirmed by testing with public datasets and it also achieved the same percentage in sensitivity and accuracy as in our recorded datasets.
Vincent Poor, H, Shi, Y, Tuan, HD, Savkin, AV & Duong, TQ 2019, 'Model predictive control for smart grids with multiple electric-vehicle charging stations', IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 2127-2136.
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© 2017 IEEE Next-generation power grids will likely enable concurrent service for residences and plug-in electric vehicles (PEVs). While the residence power demand profile is known and thus can be considered inelastic, the PEVs' power demand is only known after random PEV arrivals. PEV charging scheduling aims at minimizing the potential impact of the massive integration of PEVs into power grids to save service costs to customers while power control aims at minimizing the cost of power generation subject to operating constraints and meeting demand. This paper develops a model predictive control-based approach to address joint PEV charging scheduling and power control to minimize both PEV charging cost and energy generation cost in meeting both residence and PEV power demands. Unlike in related works, no assumptions are made about the probability distribution of PEVs' arrivals, knowledge of PEVs' future demand, or unlimited charging capacity of PEVs. The proposed approach is shown to achieve a globally optimal solution. Numerical results for IEEE benchmark power grids serving Tesla model S PEVs show the merit of this approach.
Vu, MN, Tran, NH, Tuan, HD, Nguyen, TV & Nguyen, DHN 2019, 'Optimal signaling schemes and capacities of non-coherent correlated MISO channels under per-antenna power constraints', IEEE Transactions on Communications, vol. 67, no. 1, pp. 190-204.
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© 1972-2012 IEEE. This paper investigates the optimal signaling schemes and capacities of non-coherent correlated multiple-input single-output (MISO) channels in fast Rayleigh fading. We consider both channels under per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. For per-antenna power constraint channels, we first establish the convex and compact properties of the feasible sets, and demonstrate the existence of optimal input distribution and the uniqueness of optimal effective magnitude input distribution. By exploiting the solutions of a quadratic optimization problem, we show that the Kuhn-Tucker condition on the optimal inputs can be simplified to a single dimension. As a result, we can apply the Identity Theorem to show the discrete and finite nature of the optimal effective magnitude distribution, with a mass point located at the origin. By using this distribution, we then construct a finite and discrete optimal input vector distribution. The use of this input allows us to determine the capacity gain of MISO over SISO via the phase solutions of a constrained quadratic optimization problem on a sphere, which can be obtained using a proposed penalized optimization algorithm. We also extend the results to MISO channels subject to the joint per-antenna and sum power constraints. Under this consideration, it is shown that not all per-antenna constraints are active. While the finiteness and discreteness of the optimal effective magnitude and the optimal input vector distributions still hold, the optimal phases and the optimal power allocation among the transmit antennas need to be determined simultaneously via a quadratic optimization problem under inequality constraints. These solutions can finally be used to obtain the MISO capacity gain.
Wang, S & Mao, G 2019, 'Missing Data Estimation for Traffic Volume by Searching an Optimum Closed Cut in Urban Networks', IEEE Transactions on Intelligent Transportation Systems, vol. PP, no. 99.
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Traffic data imputation has drawn significant attention from both academia and industry because traffic data often suffer from data missing problems, caused by temporary deployment of sensors, detector malfunction, and lossy communication systems. To fully exploit the spatial-temporal correlation and road topological information in an urban traffic network, we propose an optimum closed cut (OCC)-based spatio-temporal imputation technique, which is implemented in two stages: a) employing graph theory to search the OCC in the road network, for which the traffic on roads intersected by the closed cut has the maximum correlation with that on the target road while minimizing the number of intersected roads; and b) estimating the missing data on the target road using OCC-based Kriging estimator, incorporating both the road topological information and flow conservation law to improve the estimation accuracy. Experimental results using traffic data collected on real roads indicate that the OCC search algorithm can effectively capture the optimum set of neighboring sensors. An OCC-based estimator can provide more accurate imputation results compared with nearest historical average and correlative k-NN (k-nearest neighbors) methods. The road topological information and flow conservation law can be explored to further improve the estimation performance while reducing the number of sensors involved in the data imputation, hence improving the computational efficiency.
Wang, S, Liu, C, Wang, Y, Lei, G & Zhu, J 2019, '6σ Robust Multidisciplinary Design Optimization Method for Permanent Magnet Motors with Soft Magnetic Composite Cores', Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, vol. 34, no. 4, pp. 637-645.
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© 2019, Electrical Technology Press Co. Ltd. All right reserved. Soft magnetic composite (SMC) is a new kind of magnetic material, which has been widely used in the design of permanent magnet machines due to its unique electromagnetic characteristic. The cores made by SMC are isotropic magnetically and mechanically with lower eddy current loss, and can be manufactured by molded technology. Therefore, this material is promising for the design of motors with complex structure, such as transverse flux machine and claw pole motor. To improve the application of the motors made by SMC, two main research topics need to be investigated. The first one is the multidisciplinary design optimization, which mainly includes the electromagnetic analysis and thermal analysis. The second one is the robust design optimization, which mainly investigates the manufacturing precision/tolerances in the engineering manufacturing process and their effects on motor's performance. The main aim of this work is to present a Six Sigma (6σ) robust design optimization method for SMC motors under the framework of multidisciplinary design optimization. From the discussion, it can be found that the proposed method can improve the motor's performance while keeping the requirements in term of temperature rise conditions. Compared with traditional deterministic design approach, the new method can improve the reliability of the designed motor significantly, which will benefit the batch production of SMC motors in industry.
Wang, S, Mao, G & Zhang, JA 2019, 'Joint Time-of-Arrival Estimation for Coherent UWB Ranging in Multipath Environment With Multi-User Interference', IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 67, no. 14, pp. 3743-3755.
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Wang, S, Wang, Y, Liu, C, Lei, G, Guo, Y & Zhu, J 2019, 'Comparative Study of Linear Superconductivity Machine with Different Stator and Winding Configurations', IEEE Transactions on Applied Superconductivity, vol. 29, no. 2.
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IEEE Compared with rotary electrical machine in linear drive applications, linear machine without rotary-linear motion conversion equipment can have higher force density and efficiency. Linear superconductivity machine (LSM) consists of high performance superconducting magnet instead of permanent magnet can offer very high force density and efficiency compared with other linear machines, such as linear induction machine, linear permanent magnet machine and so on. In this paper, LSM with different stators and winding configurations are investigated, specifically LSMs with concentrated winding or distributed winding and unilateral side stator or bilateral side stator. The electromagnetic parameters and performance of these LSMs are calculated and compared by using the finite element method (FEM), then the main difference of various design methods in LSM have been concluded.
Wang, TQ, Li, H & Huang, X 2019, 'Analysis and Mitigation of Clipping Noise in Layered ACO-OFDM Based Visible Light Communication Systems', IEEE Transactions on Communications.
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IEEE Due to the limited dynamic range of the off-theshelf electrical and optical components, deliberate digital clipping (DDC) is widely applied to optical orthogonal frequency division multiplexing (OFDM) based visible light communication systems. In this paper, we present a theoretical characterization of the layered asymmetrically clipped optical OFDM (ACO-OFDM) signals subject to peak clipping. We decouple a clipped L-layer ACO-OFDM symbol to L single-layer ACO-OFDM symbols, each corresponding to a layer, and show that these symbols are subject to symmetrical peak clippings at random levels. Using the Bussgang’s theorem, the resulting attenuation factors and variances of the additive noise associated with each layer are derived. It is shown that the clipping noise caused by the DDC mainly falls onto the first layer, and its impact is gradually reduced in the subsequent layers. In order to combat the clipping noise, a novel receiver based on decision aided reconstruction is proposed. Simulation results show that the proposed receiver can effectively mitigate the clipping noise, leading to significant improvement of bit error rates over the conventional receiver.
Wang, W, Hoang, DT, Hu, P, Xiong, Z, Niyato, D, Wang, P, Wen, Y & Kim, DI 2019, 'A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks', IEEE Access, vol. 7, pp. 22328-22370.
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© 2013 IEEE. The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.
Wang, X, Song, B, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Group-Based Susceptible-Infectious-Susceptible Model in Large-Scale Directed Networks', SECURITY AND COMMUNICATION NETWORKS.
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Wang, X, Zha, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Game Theoretic Suppression of Forged Messages in Online Social Networks', IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-11.
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Wang, X, Zha, X, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2019, 'Survey on blockchain for Internet of Things', COMPUTER COMMUNICATIONS, vol. 136, pp. 10-29.
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Wang, Y, Lu, J, Liu, C, Lei, G, Guo, Y & Zhu, J 2019, 'Development of a High-Performance Axial Flux PM Machine With SMC Cores for Electric Vehicle Application', IEEE TRANSACTIONS ON MAGNETICS, vol. 55, no. 7.
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Wang, Y, Ma, J, Liu, C, Lei, G, Guo, Y & Zhu, J 2019, 'Reduction of Magnet Eddy Current Loss in PMSM by Using Partial Magnet Segment Method', IEEE TRANSACTIONS ON MAGNETICS, vol. 55, no. 7.
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Wang, Y, Shuai, Y, Zhu, Y, Zhang, J & An, P 2019, 'Jointly learning perceptually heterogeneous features for blind 3D video quality assessment', Neurocomputing, vol. 332, pp. 298-304.
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© 2018 Elsevier B.V. 3D videos quality assessment (3D-VQA) is essential to various 3D video processing applications. However, it has not been well investigated on how to make use of perceptual multi-channel video information to improve 3D-VQA under different distortion categories and degrees, especially under asymmetrical distortions. In the paper, we propose a new blind 3D-VQA metric by jointly learning perceptually heterogeneous features. Firstly, a binocular spatio-temporal internal generative mechanism (BST-IGM) is proposed to decompose the views of 3D video into multi-channel videos. Then, we extract perceptually heterogeneous features by proposed multi-channel natural video statistics (MNVS) model, which are characterized 3D video information. Furthermore, a robust AdaBoosting Radial Basis Function (RBF) neural network is utilized to map the features to the overall quality of 3D video. On two benchmark databases, the extensive evaluations demonstrate that the proposed algorithm significantly outperforms several state-of-the-art quality metrics in term of prediction accuracy and robustness.
Wei, F, Yang, ZJ, Qin, PY, Guo, YJ, Li, B & Shi, XW 2019, 'A Balanced-to-Balanced In-Phase Filtering Power Divider with High Selectivity and Isolation', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 2, pp. 683-694.
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© 1963-2012 IEEE. In this paper, a balanced-to-balanced in-phase filtering power divider (FPD) is proposed, which can realize a two-way equal power division with high selectivity and isolation. The design of the proposed FPD is primarily based on microstrip/slotline transition structures and slotline T-junction. A U-type microstrip feed line integrated with a stepped-impedance slotline resonator is adopted at the input and output ports, which makes the differential-mode (DM) responses independent of the common-mode (CM) ones. Meanwhile, superior DM transmission and CM suppression are achieved intrinsically, thereby simplifying the design procedure significantly. By employing slotline resonators loaded with resistors, the isolation between the two output ports can be improved greatly. In addition, a DM passband with a sharp filtering performance is realized by introducing the microstrip stub-loaded resonators (SLRs). By changing the electrical length of the open stub of the SLR, the fractional bandwidth is controllable. In order to verify the feasibility of the proposed design method, two prototype circuits of the proposed FPDs with different bandwidths are fabricated and measured. Good agreement between the simulation and measurement results is observed.
Wei, K, Cheng, T, Lu, DDC, Siwakoti, YP & Zhang, C 2019, 'Multi-variable thermal modeling of power devices considering mutual coupling', Applied Sciences (Switzerland), vol. 9, no. 16.
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© 2019 by the authors. In relation to power converter design, power density is increasing while the form factor is decreasing. This trend generally reduces the rate of the cooling process, which increases the mutual thermal coupling among the surrounding power components. Most of the traditional models usually ignore the mutual effects or just focus on the conduction coupling. To deal with these factors, the thermal modeling for a boost converter system has been built to compare the junction temperatures (Tj) and the increments under different working conditions in order to consider the conduction coupling. A multi-variable thermal resistances model is proposed in this paper to incorporate the convection thermal coupling into the mutual thermal effects. The coupling resistances, MOSFET to the diode (Rcp-DM ⇀), and the diode to MOSFET (Rcp-DM ⇀) have been calculated and the relationships between coupling resistances and their impact factors (separation distances and working currents) have been discussed. New case temperatures (Tc) obtained by calculation and additional measurements at other separation distances serve to verify the efficacy of the proposed model. This model enhances the current thermal models and provides an effective method to calculate the thermal coupling resistances which can be used to estimate the Tj. As the coupling resistances are distance dependent, the model also helps to optimize and fine-tune the placements of components in high-power density converters.
Wei, X, Cheng, M, Zhu, J, Yang, H & Luo, R 2019, 'Finite-Set Model Predictive Power Control of Brushless Doubly Fed Twin Stator Induction Generator', IEEE Transactions on Power Electronics, vol. 34, no. 3, pp. 2300-2311.
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© 1986-2012 IEEE. This paper presents a finite-set model predictive power control (FS-MPPC) method for the brushless doubly fed twin stator induction generator (BDFTSIG) in variable speed constant frequency generation applications. The FS-MPPC controller is developed in a general reference frame from which all other reference frames can be deduced readily. The invariant feature of the predictive power model in various reference frames contributes to the reference frame-free characteristic of the developed FS-MPPC controller, enabling its application more flexible and universal. Besides, the arduous process of control winding flux estimation is avoided in the FS-MPPC controller by choosing state variables that are easy to be obtained. Moreover, the influence of rotor circuit that has long been neglected in the existing controllers for the brushless doubly fed induction machines is embedded within the predictive power model and inherently considered in the FS-MPPC controller, which contributes to accurate power control of the BDFTSIG. Furthermore, the feasibility and effectiveness of the developed FS-MPPC controller regarding different power levels and grid fault conditions are briefly discussed. Finally, numerical simulations and experimental tests are carried out, which demonstrates the effectiveness of the developed FS-MPPC controller.
Wen, Z, Tang, MC & Ziolkowski, RW 2019, 'Band- And frequency-reconfigurable circularly polarised filtenna for cognitive radio applications', IET Microwaves, Antennas and Propagation, vol. 13, no. 7, pp. 1003-1008.
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© The Institution of Engineering and Technology 2019. A band- and frequency-reconfigurable circularly polarised (CP) filtenna that exhibits good selectivity and out-of-band rejection in both its wideband and continuously tunable narrowband states is reported for cognitive radio (CR) applications. The filtenna provides two switchable operational states: A wideband state from 2.52 to 3.53 GHz for sensing and a tunable state of narrowband states from 2.44 to 3.19 GHz for communications. The corresponding 3-dB axial ratio bandwidths completely overlap these impedance bandwidths. A single PIN diode is utilised to switch between these two operational states to achieve the band-reconfigurable performance. Two varactor diodes are employed to realise the frequency-reconfigurable performance by facilitating a continuous shift of the narrowband states over the operational communication frequencies.
Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Efficient angle-of-arrival estimation of lens antenna arrays for wireless information and power transfer', IEEE Journal on Selected Areas in Communications, vol. 37, no. 1, pp. 116-130.
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© 1983-2012 IEEE. Antenna design and angle-of-arrival (AoA) estimation are critical to the efficiency of wireless information and power transfer. The AoA estimation is challenging for energy-efficient lens antenna arrays (LAAs), due to discrete sets of fixed discrete Fourier transform (DFT) beams. This paper presents a novel fast and accurate approach for the AoA estimation of LAAs. The key idea is that we prove the two differential outputs of three adjacent lens beams, referred to as 'DFT beam differences (DBDs),' that are the strongest at the two sides of an AoA. They are easy to identify and robust to noises, and their powers are proved to provide an accurate estimate of the AoA. Another important aspect is a new beam synthesis technique which produces different beam widths based on DFT beams and practical 1-bit phase shifts in real time. As a result, the angular region containing the AoA can exponentially narrow down, and the two strongest DBDs can be quickly identified. The proposed approach can operate in coupling with successive interference cancellation to estimate the AoAs of multiple paths. Simulations show that the proposed approach is able to outperform the state of the art by orders of magnitude in terms of accuracy. The power transfer efficiency can be dramatically improved.
Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2019, 'Expeditious estimation of angle-of-arrival for hybrid butler matrix arrays', IEEE Transactions on Wireless Communications, vol. 18, no. 4, pp. 2170-2185.
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© 2002-2012 IEEE. Arrays of Butler matrices provide a promising front-end design for massive MIMO transceivers with low cost and low complexity. However, this advanced design does not necessarily translate to effective applications, unless the angle-of-arrival (AoA) of signals avails to the Butler matrices. This paper presents an efficient approach to the unprecedented AoA estimation for the arrays of Butler matrices. Specifically, we design a new beam synthesis method to recursively narrow down and increasingly focus on the angular region of interest, and hence achieving robust estimation of the phase offset between Butler matrices. With the phase offset canceled in the received signals, we are able to identify the set of critical Butler beams with the dominating effect on the AoA estimation, and estimate the AoA accordingly with minimum signaling. The mean squared error of the proposed estimation is analyzed in the presence of non-negligible noises, with closed-form lower bounds derived. Validated by simulations, the proposed algorithm is able to indistinguishably approach the lower bounds, and significantly outperforms the state-of-the-art developed for discrete antenna arrays by orders of magnitude in terms of accuracy, especially in low signal-to-noise regimes.
Wu, T, Lu, K, Zhu, J, Lei, G, Guo, Y & Tang, S 2019, 'Calculation of Eddy Current Loss in a Tubular Oscillatory LPMSM Using Computationally Efficient FEA', IEEE Transactions on Industrial Electronics.
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IEEE In some special oscillatory applications, especially those operated at high speeds, the eddy current loss of linear permanent magnet (PM) synchronous machine (LPMSM) should be fully considered because the loss might be large and concentrated in PMs during the oscillation period. This paper presents a loss analysis method based on computationally efficient finite element analysis (CE-FEA) for a 20 Hz oscillatory tubular LPMSM. Since the mover speed varies with time, an equally-divided model in 1/4 period is introduced to calculate the average PM eddy current loss. The flux density curves in PMs are calculated at 18 intervals by the CE-FEA, through which the change rate of magnetic flux density is analyzed, considering both the entering and leaving effects and coil end effects. The calculation results show that the eddy current loss is obviously concentrated in PMs near the two ends of coils. The calculation results at a speed of 3.6 m/s obtained by the CE-FEA and 2D&3D time-stepping FEAs are compared to validate the accuracy. Finally, the proposed method is validated by the experimental test results on a prototype LPMSM.
Wu, Y, Liu, T, Ling, SH, Szymanski, J, Zhang, W & Su, SW 2019, 'Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector.', Sensors, vol. 19, no. 2.
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This paper presents a smart "e-nose" device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we propose a novel artificial-intelligent-based multiple hazard gas detector (MHGD) system that is mounted on a motor vehicle-based robot which can be remotely controlled. First, we optimized the sensor array for the classification of three hazardous gases, including cigarette smoke, inflammable ethanol, and off-flavor from spoiled food, using an e-nose with a mixing chamber. The mixing chamber can prevent the impact of environmental changes. We compared the classification results of all combinations of sensors, and selected the one with the highest accuracy (98.88%) as the optimal sensor array for the MHGD. The optimal sensor array was then mounted on the MHGD to detect and classify the target gases without a mixing chamber but in a controlled environment. Finally, we tested the MHGD under these conditions, and achieved an acceptable accuracy (70.00%).
Xi, Y, Zheng, J, He, X, Jia, W, Li, H, Xie, Y, Feng, M & Li, X 2019, '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.
Xiao, C, Zeng, J, Ni, W, Liu, RP, Su, X & Wang, J 2019, 'Delay Guarantee and Effective Capacity of Downlink NOMA Fading Channels', IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, vol. 13, no. 3, pp. 508-523.
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Xiao, C, Zeng, J, Ni, W, Su, X, Liu, RP, Lv, T & Wang, J 2019, 'Downlink MIMO-NOMA for Ultra-Reliable Low-Latency Communications', IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 37, no. 4, pp. 780-794.
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Xiao, Y, Krunz, M & Shu, T 2019, 'Multi-Operator Networking Sharing for Massive IoT', IEEE COMMUNICATIONS MAGAZINE, vol. 57, no. 4, pp. 96-101.
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Xu, JX, Li, HY, Zhang, XY, Yang, Y, Xue, Q & Dutkiewicz, E 2019, 'Compact Dual-Channel Balanced Filter and Balun Filter Based on Quad-Mode Dielectric Resonator', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 2, pp. 494-504.
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© 1963-2012 IEEE. In this paper, we propose a method for designing a dual-channel balanced filter and a dual-channel balun filter based on the quad-mode dielectric resonator (DR) for the first time. By sharing one common quad-mode DR, two balanced filters or two balun filters are integrated as one single-cavity configuration, featuring compact size and high integration. A cylindrical DR with two short ends is investigated to construct the quad-mode DR. By properly arranging input and output feeding probes, two modes of the DR are only excited by the feeding probes of one channel and the other two modes are excited by that of the other channel. Accordingly, signals cannot be transmitted between the two channels, resulting in high isolation. Moreover, the required out-of-phase characteristics of the balanced and balun filters can be obtained by the inherent electromagnetic field properties of the DR without adding additional circuits, featuring a simple structure. For demonstration, a dual-channel balanced filter and a dual-channel balun filter are designed and fabricated, showing excellent balanced or balun filter performance of each channel as well as high isolation between the two channels. As compared to the other reported DR balanced and balun filters, the proposed designs exhibit a significant size reduction, which are attractive in wireless systems.
Xu, K-D, Li, D & Liu, Y 2019, 'High-Selectivity Wideband Bandpass Filter Using Simple Coupled Lines With Multiple Transmission Poles and Zeros', IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS, vol. 29, no. 2, pp. 107-109.
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Xu, K-D, Xu, H & Liu, Y 2019, 'Low-Profile Filtering End-Fire Antenna Integrated With Compact Bandstop Filtering Element for High Selectivity', IEEE ACCESS, vol. 7, pp. 8398-8403.
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Xu, W, Dian, R, Liu, Y, Hu, D & Zhu, J 2019, 'Robust Flux Estimation Method for Linear Induction Motors Based on Improved Extended State Observers', IEEE Transactions on Power Electronics, vol. 34, no. 5, pp. 4628-4640.
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IEEE Flux estimation is of great importance for high performance linear induction motor (LIM) drives. However, due to the end effects of LIMs, the mutual inductance and secondary resistance are seriously varied with the operation condition changing, and the flux estimation suffers from these LIM parameter variations. To alleviate the influence of these parameter variations, this paper proposes a new flux estimation algorithm based on two improved extended state observers (ESOs) with expanded bandwidth for observing disturbances. One of them is specially designed to observe the ac disturbance at certain frequency. Taking advantage of the improved ESOs, the robustness of the flux observer to parameter deviations can be significantly strengthened, and the vector control strategy based on this new flux observer can achieve better dynamic performance. Lastly, the effectiveness of the proposed method is validated by both simulation and experimental results on an LIM prototype.
Xu, W, Zou, J, Liu, Y & Zhu, J 2019, 'Weighting Factorless Model Predictive Thrust Control for Linear Induction Machine', IEEE TRANSACTIONS ON POWER ELECTRONICS, vol. 34, no. 10, pp. 9916-9928.
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Xu, Z, Liu, Y, Li, M & Li, Y 2019, 'Linearly Polarized Shaped Power Pattern Synthesis With Dynamic Range Ratio Control for Arbitrary Antenna Arrays', IEEE ACCESS, vol. 7, pp. 53621-53628.
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Yan, S-P, Zhao, M-H, Ban, Y-L, Lian, J-W & Nie, Z 2019, 'Dual-Layer SIW Multibeam Pillbox Antenna With Reduced Sidelobe Level', IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, vol. 18, no. 3, pp. 541-545.
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Yang, J, Ding, M, Mao, G & Lin, Z 2019, 'Interference Management in In-band D2D Underlaid Cellular Networks', IEEE Transactions on Cognitive Communications and Networking.
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IEEE Recently, it has been standardized by the 3rd Generation Partnership Project (3GPP) roessler that device-to-device (D2D) communications should use uplink resources when coexisting with conventional cellular communications. With uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we address the critical issue of interference management in the network considering a practical path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions. To reduce the severe interference caused by active D2D links, we consider a mode selection scheme based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Furthermore, we analyze the performance in terms of the coverage probability and the area spectral efficiency (ASE) for both the cellular network and the D2D one. Analytical results are obtained and the accuracy of the proposed analytical framework is validated through Monte Carlo simulations. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications in cellular networks and we find an optimum mode selection threshold β to maximize the total ASE in the network. This insight is expected to provide a design guideline for D2D mode selections.
Yang, J, Ding, M, Mao, G, Lin, Z & Ge, X 2019, 'Analysis of Underlaid D2D-Enhanced Cellular Networks: Interference Management and Proportional Fair Scheduler', IEEE Access, vol. 7, pp. 35755-35768.
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© 2013 IEEE. Device-to-device (D2D) communications have been proposed as a promising technology to improve network capacity and user experiences in the future mobile networks such as heterogeneous networks with densely deployed small cells, but it has not yet been fully incorporated into the existing cellular networks. Interference management is one of the critical issues when D2D communications using uplink resources and coexisting with conventional cellular communications, especially in the ultra-dense networks (UNDs). In this paper, we address the critical issue of interference management by a mode selection method, which is based on the maximum received signal strength (MRSS) for each D2D transmitter (TU). To analyze the capacity of a more practical D2D-enhanced network, we consider that the typical user is no longer a random user, i.e., random user selection by a round-robin (RR) scheduler, as assumed in most studies in the literature. Instead, a cellular user with the maximum proportional fair (PF) metric is chosen by its serving base station as the typical user, which is referred to as the PF scheduler in the cellular tier. Furthermore, we theoretically study the performance in terms of the coverage probability and the area spectral efficiency (ASE) for both the cellular network and the D2D one with the consideration of the PF scheduler in UDNs. Analytical results are obtained, and the accuracy of the proposed analytical framework is validated through Monte Carlo simulations. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and the PF scheduler in cellular networks, and we find an optimum mode selection threshold β to maximize the total ASE in the network.
Yang, J, Ding, M, Mao, G, Lin, Z, Zhang, D-G & Luan, TH 2019, 'Optimal Base Station Antenna Downtilt in Downlink Cellular Networks', IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, vol. 18, no. 3, pp. 1779-1791.
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Yang, T, Ding, C & Guo, Y 2019, 'A Highly Birefringent and Nonlinear AsSe2-As2S5 Photonic Crystal Fiber with Two Zero-Dispersion Wavelengths', IEEE Photonics Journal, vol. 11, no. 1.
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OAPA A hybrid AsSe$_{2}$-As$_{2}$S$_{5}$ photonic crystal fiber (PCF) with a solid elliptical core is proposed and studied theoretically by full-vector finite element method (FEM). The core and cladding of the PCF are made of AsSe$_{2}$ and As$_{2}$S$_{5}$ glasses, respectively. Simulation results demonstrates that, at the operating wavelength of 1.55 μm, the proposed PCF not only exhibits a very high birefringence of 0.091 but also has large nonlinear coefficients of 147.8 and 78.2 W$^{-1}$m$^{-1}$ for the X- and Y-polarized (X- and Y-pol) modes, respectively. Moreover, it is able to achieve two zero-dispersion wavelengths (ZDWs) for both the X-pol (1.52 and 2.19 μm) and Y-pol (1.43 and 2.12 μm) modes. The proposed hybrid PCF exhibits excellent polarization maintaining and nonlinearity performance, thus suitable to be used in supercontinuum spectrum generation and polarization maintaining nonlinear signal processing.
Yang, T, Ding, C, Ziolkowski, RW & Guo, YJ 2019, 'A Terahertz (THz) Single-Polarization-Single-Mode (SPSM) Photonic Crystal Fiber (PCF).', Materials, vol. 12, no. 15.
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This paper presents a novel approach to attain a single-polarization-single-mode (SPSM) photonic crystal fiber (PCF) in the terahertz (THz) regime. An initial circular hole PCF design is modified by introducing asymmetry in the first ring of six air holes in the cladding, i.e., epsilon-near-zero (ENZ) material is introduced into only four of those air holes and the other two remain air-filled but have different diameters. The resulting fundamental X-polarized (XP) and Y-polarized (YP) modes have distinctly different electric field distributions. The asymmetry is arranged so that the YP mode has a much larger amount of the field distributed in the ENZ material than the XP mode. Since the ENZ material is very lossy, the YP mode suffers a much higher loss than the XP mode. Consequently, after a short propagation distance, the loss difference (LD) between the XP and YP modes will be large enough that only the XP mode still realistically exists in the PCF. To further enhance the outcome, gain material is introduced into the core area to increase the LDs between the wanted XP mode and any unwanted higher order (HO) modes, as well as to compensate for the XP mode loss without affecting the LD between the XP and YP modes. The optimized PCF exhibits LDs between the desired XP mode and all other modes greater than 8.0 dB/cm across a wide frequency range of 0.312 THz. Consequently, the reported PCF only needs a length of 2.5 cm to attain an SPSM result, with the unwanted modes being more than 20 dB smaller than the wanted mode over the entire operational band.
Yang, Y, Liu, Y, Ma, X, Li, M, Xu, K-D & Guo, YJ 2019, 'Synthesizing Unequally Spaced Pattern-Reconfigurable Linear Arrays With Minimum Interspacing Control', IEEE ACCESS, vol. 7, pp. 58893-58900.
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Yao, L, Kusakunniran, W, Wu, Q, Zhang, J, Tang, Z & Yang, W 2019, '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, X, Wu, Q, Zhang, P & Bao, F 2019, 'Adaptive rational fractal interpolation function for image super-resolution via local fractal analysis', Image and Vision Computing, vol. 82, pp. 39-49.
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© 2019 Elsevier B.V. Image super-resolution aims to generate high-resolution image based on the given low-resolution image and to recover the details of the image. The common approaches include reconstruction-based methods and interpolation-based methods. However, these existing methods show difficulty in processing the regions of an image with complicated texture. To tackle such problems, fractal geometry is applied on image super-resolution, which demonstrates its advantages when describing the complicated details in an image. The common fractal-based method regards the whole image as a single fractal set. That is, it does not distinguish the complexity difference of texture across all regions of an image regardless of smooth regions or texture rich regions. Due to such strong presumption, it causes artificial errors while recovering smooth area and texture blurring at the regions with rich texture. In this paper, the proposed method produces rational fractal interpolation model with various setting at different regions to adapt to the local texture complexity. In order to facilitate such mechanism, the proposed method is able to segment the image region according to its complexity which is determined by its local fractal dimension. Thus, the image super-resolution process is cast to an optimization problem where local fractal dimension in each region is further optimized until the optimization convergence is reached. During the optimization (i.e. super-resolution), the overall image complexity (determined by local fractal dimension) is maintained. Compared with state-of-the-art method, the proposed method shows promising performance according to qualitative evaluation and quantitative evaluation.
Yao, Y, Shen, F, Zhang, J, Liu, L, Tang, Z & Shao, L 2019, 'Extracting Multiple Visual Senses for Web Learning', IEEE Transactions on Multimedia, vol. 21, no. 1, pp. 184-196.
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© 1999-2012 IEEE. Labeled image datasets have played a critical role in high-level image understanding. However, the process of manual labeling is both time consuming and labor intensive. To reduce the dependence on manually labeled data, there have been increasing research efforts on learning visual classifiers by directly exploiting web images. One issue that limits their performance is the problem of polysemy. Existing unsupervised approaches attempt to reduce the influence of visual polysemy by filtering out irrelevant images, but do not directly address polysemy. To this end, in this paper, we present a multimodal framework that solves the problem of polysemy by allowing sense-specific diversity in search results. Specifically, we first discover a list of possible semantic senses from untagged corpora to retrieve sense-specific images. Then, we merge visual similar semantic senses and prune noise by using the retrieved images. Finally, we train one visual classifier for each selected semantic sense and use the learned sense-specific classifiers to distinguish multiple visual senses. Extensive experiments on classifying images into sense-specific categories and reranking search results demonstrate the superiority of our proposed approach.
Yao, Y, Shen, F, Zhang, J, Liu, L, Tang, Z & Shao, L 2019, 'Extracting Privileged Information for Enhancing Classifier Learning', IEEE Transactions on Image Processing, vol. 28, no. 1, pp. 436-450.
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© 1992-2012 IEEE. The accuracy of data-driven learning approaches is often unsatisfactory when the training data is inadequate either in quantity or quality. Manually labeled privileged information (PI), e.g., attributes, tags or properties, is usually incorporated to improve classifier learning. However, the process of manually labeling is time-consuming and labor-intensive. Moreover, due to the limitations of personal knowledge, manually labeled PI may not be rich enough. To address these issues, we propose to enhance classifier learning by exploring PI from untagged corpora, which can effectively eliminate the dependency on manually labeled data and obtain much richer PI. In detail, we treat each selected PI as a subcategory and learn one classifier for each subcategory independently. The classifiers for all subcategories are integrated together to form a more powerful category classifier. Particularly, we propose a novel instance-level multi-instance learning model to simultaneously select a subset of training images from each subcategory and learn the optimal SVM classifiers based on the selected images. Extensive experiments on four benchmark data sets demonstrate the superiority of our proposed approach.
Yazdi, SSH, Milimonfared, J, Fathi, SH, Rouzbehi, K & Rakhshani, E 2019, 'Analytical modeling and inertia estimation of VSG-controlled Type 4 WTGs: Power system frequency response investigation', INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, vol. 107, pp. 446-461.
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Ye, X, Yang, Z, Zhu, J & Guo, Y 2019, 'Modeling and Operation of a Bearingless Fixed-Pole Rotor Induction Motor', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 29, no. 2.
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Yuan, C, Tao, X, Li, N, Ni, W, Liu, RP & Zhang, P 2019, 'Analysis on Secrecy Capacity of Cooperative Non-Orthogonal Multiple Access With Proactive Jamming', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 68, no. 3, pp. 2682-2696.
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Yuan, D, Lu, Z, Zhang, J & Li, X 2019, 'A hybrid prediction-based microgrid energy management strategy considering demand-side response and data interruption', INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, vol. 113, pp. 139-153.
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Zhang, A, Huang, X, Guo, YJ, Yuan, J & Heath, RW 2019, 'Multibeam for Joint Communication and Sensing Using Steerable Analog Antenna Arrays', IEEE Transactions on Vehicular Technology.
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IEEE Beamforming has great potential for joint communication and sensing (JCAS), which is becoming a demanding feature on many emerging platforms such as unmanned aerial vehicles and smart cars. Although beamforming has been extensively studied for communication and radar sensing respectively, its application in the joint system is not straightforward due to different beamforming requirements by communication and sensing. In this paper, we propose a novel multibeam framework using steerable analog antenna arrays, which allows seamless integration of communication and sensing. Different to conventional JCAS schemes that support JCAS using a single beam, our framework is based on the key innovation of multibeam technology: providing fixed subbeam for communication and packet-varying scanning subbeam for sensing, simultaneously from a single transmitting array. We provide a system architecture and protocols for the proposed framework, complying well with modern packet communication systems with multicarrier modulation. We also propose low-complexity and effective multibeam design and generation methods, which offer great flexibility in meeting different communication and sensing requirements. We further develop sensing parameter estimation algorithms using conventional digital Fourier transform and 1D compressive sensing techniques, matching well with the multibeam framework. Simulation results are provided and validate the effectiveness of our proposed framework, beamforming design methods and the sensing algorithms.
Zhang, D, Ge, H, Zhang, T, Cui, YY, Liu, X & Mao, G 2019, 'New Multi-Hop Clustering Algorithm for Vehicular Ad Hoc Networks', IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 4, pp. 1517-1530.
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IEEE As a hierarchical network architecture, the cluster architecture can improve the routing performance greatly for vehicular ad hoc networks (VANETs) by grouping the vehicle nodes. However, the existing clustering algorithms only consider the mobility of a vehicle when selecting the cluster head. The rapid mobility of vehicles makes the link between nodes less reliable in cluster. A slight change in the speed of cluster head nodes has a great influence on the cluster members and even causes the cluster head to switch frequently. These problems make the traditional clustering algorithms perform poorly in the stability and reliability of the VANET. A novel passive multi-hop clustering algorithm (PMC) is proposed to solve these problems in this paper. The PMC algorithm is based on the idea of a multi-hop clustering algorithm that ensures the coverage and stability of cluster. In the cluster head selection phase, a priority-based neighbor-following strategy is proposed to select the optimal neighbor nodes to join the same cluster. This strategy makes the inter-cluster nodes have high reliability and stability. By ensuring the stability of the cluster members and selecting the most stable node as the cluster head in the N-hop range, the stability of the clustering is greatly improved. In the cluster maintenance phase, by introducing the cluster merging mechanism, the reliability and robustness of the cluster are further improved. In order to validate the performance of the PMC algorithm, we do many detailed comparison experiments with the algorithms of N-HOP, VMaSC, and DMCNF in the NS2 environment.
Zhang, J, Li, L, Dorrell, D, Norambuena, M & Rodriguez, J 2019, 'Predictive Voltage Control of Direct Matrix Converters with Improved Output Voltage for Renewable Distributed Generation', IEEE Journal of Emerging and Selected Topics in Power Electronics.
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This paper proposes a predictive voltage control strategy for a direct matrix converter used in a renewable energy distributed generation (DG) system. A direct matrix converter with LC filters is controlled in order to work as a stable voltage supply for loads. This is especially relevant for the stand-alone operation of a renewable DG where a stable sinusoidal voltage, with desired amplitude and frequency under various load conditions, is the main control objective. Model predictive control is employed to regulate the matrix converter so that it produces stable sinusoidal voltages for different loads. With predictive control, many other control objectives, e.g., input power factor, common-mode voltage and switching frequency, can be achieved depending on the application. To reduce the number of required measurements and sensors, this work utilizes observers and makes use of the switch matrices. In addition, the voltage transfer ratio can be improved with the proposed strategy. The controller is tested under various conditions including intermittent disturbance, non-linear loads and unbalanced loads. The proposed controller is effective, simple, and easy to implement. Simulation and experimental results verify the effectiveness of the proposed scheme and control strategy. This proposed scheme can be potentially used in microgrid applications.
Zhang, J, Norambuena, M, Li, L, Dorrell, D & Rodriguez, J 2019, 'Sequential Model Predictive Control of Three-Phase Direct Matrix Converter', ENERGIES, vol. 12, no. 2.
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Zhang, J, Wu, Q, Zhang, J, Shen, C, Lu, J & Wu, Q 2019, 'Heritage image annotation via collective knowledge', Pattern Recognition, vol. 93, pp. 204-214.
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© 2019 Elsevier Ltd The automatic image annotation can provide semantic illustrations to understand image contents, and builds a foundation to develop algorithms that can search images within a large database. However, most current methods focus on solving the annotation problem by modeling the image visual content and tag semantic information, which overlooks the additional information, such as scene descriptions and locations. Moreover, the majority of current annotation datasets are visually consistent and only annotated by common visual objects and attributes, which makes the classic methods vulnerable to handle the more diverse image annotation. To address above issues, we propose to annotate images via collective knowledge, that is, we uncover relationships between the image and its neighbors by measuring similarities among metadata and conduct the metric learning to obtain the representations of image contents, we also generate semantic representations for images given collective semantic information from their neighbors. Two representations from different paradigms are embedded together to train an annotation model. We ground our model on the heritage image collection we collected from the library online open data. Annotations on the heritage image collection are not limited to common visual objects, and are highly relevant to historical events, and the diversity of the heritage image content is much larger than the current datasets, which makes it more suitable for this task. Comprehensive experimental results on the benchmark dataset indicate that the proposed model achieves the best performance compared to baselines and state-of-the-art methods.
Zhang, R, Chengpo, M, Min, X, Lixin, X & Xiaofeng, X 2019, 'Facial Component-Landmark Detection with Weakly-supervised LR-CNN', IEEE Access, no. 2169-3536.
Zhang, T, Bao, JF, Zeng, RZ, Yang, Y, Bao, LL, Bao, FH, Zhang, Y & Qin, F 2019, 'Long lifecycle MEMS double-clamped beam based on low stress graphene compound film', Sensors and Actuators, A: Physical, vol. 288, pp. 39-46.
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© 2019 Elsevier B.V. Graphene based three-layer compound film on the silicon substrate is formed by gold deposition of electron beam evaporation (EBE) and graphene transfer. Processed with different high temperature annealing in nitrogen, the film with residual tensile stress of 52.58 MPa at 500 ℃ can be achieved by using an X-ray diffraction (XRD) method. Based on this low stress film, a series of long lifecycle MEMS double-clamped beams (DCBs) are fabricated by the standard MEMS manufacturing technology. The achieved beam can be turned on/off for up to 100 million times at the pull-in voltage of 30 V, which is compatible with the conventional, complementary metal-oxide-semiconductor (CMOS) circuit requirements.
Zhang, W, Liu, T, Ye, L, Ueland, M, Forbes, SL & Su, SW 2019, 'A novel data pre-processing method for odour detection and identification system', Sensors and Actuators, A: Physical, vol. 287, pp. 113-120.
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© 2018 Elsevier B.V. This paper presents a novel electronic nose (E-nose) data pre-processing method, based on a recently developed non-parametric kernel-based modelling (KBM) approach. The proposed method is tested by an automated odour detection and classification system, named “NOS.E” developed by the NOS.E team in University of Technology Sydney. Experimental results show that when extracting the derivative-related features from signals collected by the NOS.E, the proposed non-parametric KBM odour data pre-processing method achieves more reliable and stable pre-processing results comparing with other pre-processing methods such as wavelet package correlation filter (WPCF), mean filter (MF), polynomial curve fitting (PCF) and locally weighted regression (LWR). Based on these derivative-related features, the NOS.E can achieve a 96.23% accuracy of classification with the popular Support Vector Machine (SVM) classifier.
Zhang, X, Lv, T, Ren, Y, Ni, W, Beaulieu, NC & Guo, YJ 2019, 'Economical Caching for Scalable Videos in Cache-Enabled Heterogeneous Networks', IEEE Journal on Selected Areas in Communications, vol. 37, no. 7, pp. 1608-1621.
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© 1983-2012 IEEE. We develop the optimal economical caching schemes in cache-enabled heterogeneous networks, while delivering multimedia video services with personalized viewing qualities to mobile users. By applying scalable video coding (SVC), each video file to be requested is divided into one base layer (BL) and several enhancement layers (ELs). In order to assign different transmission tasks, the serving small-cell base stations (SBSs) are grouped into K clusters. The SBSs are able to cache and cooperatively transmit BL and EL contents to the user. We analytically derive expressions for successful transmission probability and ergodic service rate, and then the closed-form expression for EConomical Efficiency (ECE) is obtained. In order to enhance the ECE performance, we formulate the ECE optimization problems for two cases. In the first case, with equal cache size equipped at each SBS, the layer caching indicator is determined. Since this problem is NP-hard, after the l-{0} -norm approximation, the discrete optimization variables are relaxed to be continuous, and this relaxed problem is convex. Next, based on the optimal solution derived from the relaxed problem, we devise a greedy-strategy based heuristic algorithm to achieve the near-optimal layer caching indicators. In the second case, the cache size for each SBS, the layer size, and the layer caching indicator are jointly optimized. This problem is a mixed integer programming problem, which is more challenging. To effectively solve this problem, the original ECE maximization problem is divided into two subproblems. These two subproblems are iteratively solved until the original optimization problem is convergent. Numerical results verify the correctness of the theoretical derivations. Additionally, compared to the most popular layer placement strategy, the performance superiority of the proposed SVC-based caching schemes is testified.
Zhao, J, Mou, Q, Guo, K, Liu, X, Li, J & Guo, Y 2019, 'Reduction of the Detent Force in a Flux-Switching Permanent Magnet Linear Motor', IEEE Transactions on Energy Conversion.
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IEEE In this paper, the detent force caused by the end effect in a flux-switching permanent magnet linear motor (FSPMLM) with 6 slots and 5 poles is investigated and reduced by two different methods. Firstly, the detent force is diminished by adjusting the position of end teeth of primary side and injecting compensation current into compensation windings wound around the end teeth. Based on the linear relationship between compensation current and compensation force, the proper compensation current is derived and analyzed. Then, to avoid the magnetic coupling between compensation windings and phase windings, a novel compensation module with independent magnet circuit is presented and attached to the primary side of FSPMLM. Thirdly, the two detent force reduction methods are compared with each other, and the compensation module is proved to be more effective. Finally, a prototype of FSPMLM with compensation modules is manufactured and tested to validate the proposed compensation method.
Zheng, D, Zhang, H, Zhang, JA & Li, Y 2019, 'Consensus of the Second-order Multi-agent Systems under Asynchronous Switching with a Controller Fault', INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, vol. 17, no. 1, pp. 136-144.
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Zheng, G, Yang, W, Valli, C, Shankaran, R, Abbas, H, Zhang, G, Fang, G, Chaudhry, J & Qiao, L 2019, 'Fingerprint Access Control for Wireless Insulin Pump Systems Using Cancelable Delaunay Triangulations', IEEE Access, vol. 7, pp. 75629-75641.
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© 2013 IEEE. An insulin pump is a small wearable medical gadget which can mimic the way a healthy pancreas functions by providing continuous subcutaneous insulin infusion for the patient. However, in the current products, the access to the pump is not securely controlled, rendering the pump insecure to harmful or even lethal attacks, such as those that lead to the privacy breach of the patient and the delivery of abnormal dosage of insulin to the patient. In a conventional symmetric key-based security solution, how to distribute and manage the key is quite challenging, since the patient bearing an insulin pump may visit any hospital or clinic to receive treatment from any qualified doctor. In order to prevent malicious access to the pump, in this paper, we propose a Fingerprint-based Insulin Pump security (FIPsec) scheme which requires an entity to first pass the fingerprint authentication process before it is allowed to access the insulin pump. With this scheme, the request from an adversary to access the pump will be blocked thereby protecting the pump from the possibility of being subjected to serious attacks during the post-request period. In the scheme, a cancelable Delaunay triangle-based fingerprint matching algorithm is proposed for the insulin pump, which has capabilities to resist against nonlinear fingerprint image distortion and the influence of missing or spurious minutiae. In order to evaluate the performance of the proposed fingerprint matching algorithm, we perform comprehensive experiments on FVC2002 DB1 and DB2 fingerprint databases. The results show that the FIPsec scheme can achieve a reasonably low equal error rate and thus becomes a viable solution to thwarting unauthorized access to the insulin pump.
Zhou, W, Sutton, GJ, Andrew Zhang, J, Liu, RP & Pan, S 2019, 'Delay-Guaranteed Admission Control for LAA Coexisting with WiFi', IEEE Wireless Communications Letters, vol. 8, no. 4, pp. 1048-1051.
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© 2012 IEEE. Licensed-assisted-access (LAA) is used to extend the LTE link into the unlicensed band. How to guarantee the quality-of-service (QoS) for LTE devices in the unlicensed band is a challenging problem due to the listen-before-talk contention access in 5-GHz unlicensed bands. In this letter, we quantitatively analyze the medium access control delay for tagged LAA eNBs and propose a delay-guaranteed admission control scheme. We consider the freezing time of busy slots caused by collision or successful transmission, and introduce the exponential backoff mechanism for delay analysis. Validated by simulation results, our method provides important insights into the system admission performance and fairness of access.
Zhu, G, Liu, X, Li, L, Chen, H, Tong, W & Zhu, J 2019, 'Cooling System Design of a High-Speed PMSM Based on a Coupled Fluidic-Thermal Model', IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, vol. 29, no. 2.
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Zhu, H & Guo, YJ 2019, 'Wideband Filtering Phase Shifter Using Transversal Signal-Interference Techniques', IEEE Microwave and Wireless Components Letters, vol. 29, no. 4, pp. 252-254.
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© 2001-2012 IEEE. A wideband filtering phase shifter is presented in this letter using transversal signal-interference techniques. The proposed structure creates two signal-propagation paths by introducing extra coupling between two short-ended stubs. Cascaded coupled-line sections and parallel short-ended stubs can generate a constant passband and multiple transmission zeros (TZs) in the stopband and meanwhile provide the arbitrary value of phase shift within the filtering band range. The positions of TZs and phase shift range can be easily controlled. Explicit relations between the objective filtering band and the related parameters are given, and cases with different in-band phase shift values are studied. To validate the design, a prototype is built, simulated, and tested using microstrip lines. The experimental results agree with the predicted ones, demonstrating that the device can realize any given in-band phase shift with a wideband filtering response.
Zhu, H, Cheng, Z & Guo, YJ 2019, 'Design of wideband in-phase and out-of-phase power dividers using microstrip-to-slotline transitions and slotline resonators', IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 4, pp. 1412-1424.
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© 2019 IEEE. A new class of in-phase and out-of-phase power dividers with constant equal-ripple frequency response and wide operating bandwidth is presented in this paper. The proposed design is based on microstrip-to-slotline transitions and slotline resonators. A slotted T-junction is adopted to split the power into two parts and obtain wideband isolation between the two output signals at the same time. The characteristic impedance of the transitions and resonators determines the operating bandwidth and in-band magnitude response. By reversing the placement direction of the slotline-to-microstrip transition, the electrical field is reversed, thus resulting in out-of-phase responses between output ports. A thorough analysis of the relations between the structure and the characteristic functions is provided to guide the selection of parameters of the structure in order to meet the design objectives. In the structure, simulation and measurement are conducted to verify the design method. For both in-phase and out-of-phase cases, more than 110% bandwidth has been achieved with excellent matching at all ports and isolation of output signals. Constant in-band ripple is obtained within the operating band of the power dividers, indicating that the proposed design can realise minimal power deviations, which is extremely desired in wireless systems.
Zhu, H, Sun, HH, Jones, B, Ding, C & Guo, YJ 2019, 'Wideband Dual-Polarized Multiple Beam-Forming Antenna Arrays', IEEE Transactions on Antennas and Propagation.
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IEEE Wideband multi-beam antenna arrays based on three-beam Butler matrices are presented in this paper. The proposed beam-forming arrays are particularly suited to increasing the capacity of 4G long-term evolution (LTE) base stations. Although dual-polarized arrays are widely used in LTE base stations, analogue beam-forming arrays have not been realized before, due to the huge challenge of achieving wide operating bandwidth and stable array patterns. To tackle these problems, for the first time, we present a novel wideband multiple beam-forming antenna array based on Butler matrices. The described beam-forming networks produce three beams but the methods are applicable to larger networks. The essential part of the beam-forming array is a wideband three-beam Butler matrix, which comprises quadrature couplers and fixed wideband phase shifters. Wideband quadrature and phase shifters are developed using striplines, which provide the required power levels and phase differences at the outputs. To achieve the correct beamwidth and to obtain the required level of crossover between adjacent beams, beam-forming networks consisting of augmented three-beam Butler matrices using power dividers are presented to expand the number of output ports from three to five or six. Dual-polarized, three-beam antenna arrays with five and six elements covering LTE band are developed. Prototypes comprising beam-forming networks and arrays are tested according to LTE base station specification. The test results show close agreement with the simulation ones and compliance with LTE requirements. The designs presented are applicable to a wide range of wideband multi-beam arrays.
Zhu, J, Yang, Y, Li, S, Liao, S & Xue, Q 2019, 'Single-ended-fed high-gain LTCC planar aperture antenna for 60 GHz antenna-in-package applications', IEEE Transactions on Antennas and Propagation, vol. 67, no. 8, pp. 5154-5162.
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© 1963-2012 IEEE. This paper presents new single-ended-fed planar aperture antennas (SPAAs) using low-temperature co-fired ceramics (LTCC) process technology. The SPAA element is proposed first, which not only inherits the merits of the aperture antennas including high gain and wide bandwidth but also exhibits advantages of low profile and compact size. The aperture is excited by a cross-shaped patch, and a loop-shaped balun structure placed below the patch is introduced to convert the single-ended signal into differential one to drive the patch. In this way, the energy can propagate on the patch in a traveling waveform and illuminate the aperture with uniform E-field distributions. Therefore, the antenna achieves good electrical and radiation performances, which are comparable to its balanced-fed counterparts, while processing a simplified structure. Measured results demonstrate that the impedance bandwidth of the antenna covers the 60 GHz license-free band (57-64 GHz), and the maximum gain can reach 11.5 dBi with a cavity area of only about 27 mm2. Furthermore, the element is successfully extended to a 4 × 4 element array using a substrate-integrated-waveguide based feeding network to further increase the gain up to 20.4 dBi. The measured results show that the impedance bandwidth of the array is from 57.5 to 65.7 GHz and the radiation performances are very stable over the operating frequency band.
Zuo, Y, Wu, Q, Fang, Y, An, P, Huang, L & Chen, Z 2019, 'Multi-scale Frequency Reconstruction for Guided Depth Map Super-resolution via Deep Residual Network', IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1.
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Abbasipour, M, Milimonfared, J, Yazdi, SSH & Rouzbehi, K 2019, 'Static Modeling of the IDC-PFC to Solve DC Power Flow Equations of MT-HVDC Grids Employing the Newton-Raphson Method', 2019 10TH INTERNATIONAL POWER ELECTRONICS, DRIVE SYSTEMS AND TECHNOLOGIES CONFERENCE (PEDSTC), 10th International Power Electronics, Drive Systems and Technologies Conference (PEDSTC), IEEE, Shiraz Univ, Shiraz, IRAN, pp. 450-457.
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Abdollahi, M, Abolhasan, M, Shariati, N, Lipman, J, Jamalipour, A & Ni, W 2019, 'A Routing Protocol for SDN-based Multi-hop D2D Communications', 2019 16th IEEE Annual Consumer Communications and Networking Conference, CCNC 2019, EEE Annual Consumer Communications & Networking Conference, IEEE, USA, pp. 895-898.
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© 2019 IEEE. This paper presents a new Multi-hop Device-to-Device (MD2D) routing protocol, referred to as SMDRP (SDN-based Multi-hop D2D Routing Protocol), for SDN-based wireless networks. Our proposed protocol can be considered as a semi-distributed routing protocol, where an SDN controller manages and controls part of the overall MD2D routing functionality to increase scalability while enabling network operators to control and maintain the out-of-band packet forwarding network. This paper also extends prior work on the Hybrid SDN Architecture for Wireless Distributed Networks (HSAW) [1] and is adapted to the framework presented in this paper. In HSAW, since all link state information is flooded by the controller to the nodes, the network will experience scalability problem. In our approach, this problem is overcome by only passing the next hop for each active route to the mobile nodes. To investigate this, we performed a theoretical and simulation studies comparing HSAW with SMDRP. From our result, it can be seen that for larger density populated networks, SMDRP shows better scalability than HSAW. In addition, mobile nodes need less memory and energy for their communications.
Abeywickrama, HV, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Empirical Power Consumption Model for UAVs', 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), IEEE Vehicular Technology Conference, IEEE, Chicago, IL, USA, USA, pp. 1-5.
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Unmanned Aerial Vehicles (UAV) are gaining popularity in a range of areas and are already being used for a wide variety of purposes. While UAVs have many desirable features, limited battery lifetime is identified as a key restriction in UAV applications. Typical UAVs being electric devices, powered by on-board batteries, this constrain has limited their capabilities to a considerable extent. Thus planning UAV missions in an energy efficient manner is of utmost importance. To achieve this, for prediction of power consumption, it is necessary to have a reliable power consumption model. In this paper, we present a consistent and complete power consumption model for UAVs based on empirical studies of battery usage for various UAV activities. The power consumption model presented in this paper can be readily used for energy efficient UAV mission planning.
Abuhilaleh, M, Li, L, Zhu, J & Hossain, J 2018, 'Distributed Control and Power Management Strategy for an Autonomous Hybrid Microgrid with Multiple Sub-Microgrids', IEEE Xplore Digital Library, The Australasian Universities Power Engineering Conference (AUPEC), New Zealand.
Acuna, P, Aguilera, RP, McGrath, B, Lezana, P, Ghias, A & Pou, J 2018, 'Sequential Phase-Shifted Model Predictive Control for a Single-Phase Five-Level H-bridge Flying Capacitor Converter', 2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT), Asian Conference on Energy, Power and Transportation Electrification, IEEE, Singapore, Singapore, pp. 1-8.
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This paper proposes a sequential Phase-Shifted Model Predictive Control (PS-MPC) strategy for a single-phase five-level H-bridge flying capacitor converter. The optimal control problem is formulated to regulate the output current and both of the internal floating capacitor voltages. The proposed sequential PS-MPC strategy achieves a fixed switching frequency, which is beneficial in terms semiconductor loss distribution, and also to ensure that a high-bandwidth is achieved that compares favorably to the finite-control-set MPC (FCS-MPC) case. Simulation results of the proposed sequential PS-MPC strategy, providing current tracking control for a passive load, are presented to verify the transient and steady-state performance that can be achieved.
Acuna, P, Ghias, A, Aguilera, RP, Lezana, P, McGrath, B, Merabet, A & Jayan, V 2019, 'Sequential phase-shifted model predictive control for a five-level flying capacitor converter', Proceedings of the IEEE International Conference on Industrial Technology, pp. 533-538.
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© 2019 IEEE. This paper extends previous work on the Sequential Phase-Shifted Model Predictive Control (SPS-MPC) strategy into a Single-Phase Five-Level Flying Capacitor Converter (SP-FL-FCC). The use of SPS-MPC in an FL-FCC is not as straightforward as it first seems. Therefore, a sequential average model based on more than one active control input is derived. The proposed SPS-MPC strategy achieves a fixed switching frequency, which is beneficial regarding of semiconductor loss distribution, and also to ensure that a high-bandwidth is achieved that compares favorably to the finite-control-set MPC case. Simulation results of the proposed SPS-MPC strategy validate the current and FC voltages tracking control during the transient and steady-state conditions at a fixed switching frequency.
Ajayan, AR, Al-Doghman, F & Chaczko, Z 2018, 'Visualizing Multimodal Big Data Anomaly Patterns in Higher-Order Feature Spaces', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, NSW, Australia, pp. 1-9.
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The world today, as we know it, is profuse with information about humans and objects. Datasets generated by cyber-physical systems are orders of magnitude larger than their current information processing capabilities. Tapping into these big data flows to uncover much deeper perceptions into the functioning, operational logic and smartness levels attainable has been investigated for quite a while. Knowledge Discovery & Representation capabilities across mutiple modalities holds much scope in this direction, with regards to their information holding potential. This paper investigates the applicability of an arithmetic tool Tensor Decompositions and Factorizations in this scenario. Higher order datasets are decomposed for Anomaly Pattern capture which encases intelligence along multiple modes of data flow. Preliminary investigations based on data derived from Smart Grid Smart City Project are compliant with our hypothesis. The results proved that Abnormal patterns detected in decomposed Tensor factors encompass deep information energy content from Big Data as efficiently as other Pattern Extraction and Knowledge Discovery frameworks, while salvaging time and resources.
Akter, N, Phu, J, Perry, S, Fletcher, J, Kalloniatis, M & Roy, M 1970, 'Analysis of OCT Images to Optimize Glaucoma Diagnosis', Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP), Imaging Systems and Applications, OSA.
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Al-Doghman, F, Chaczko, Z & Brookes, W 2018, 'Adaptive Consensus-based Aggregation for Edge Computing', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia.
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The swift expansion in employing IoT and the tendency to apply its application have encompassed a wide range of fields in our life. The heterogeneity and the massive amount of data produced from IoT require adaptive collection and transmission processes that function closed to front-end to mitigate these issues. In this paper, We introduced a method
of aggregating IoT data in a consensus way using Bayesian analysis and Markov Chain techniques. The aim is to enhance the quality of data traveling within IoT framework.
Aljarajreh, H, Lu, DDC & Tse, CK 2019, 'Synthesis of dual-input single-output DC/DC converters', Proceedings - IEEE International Symposium on Circuits and Systems.
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© 2019 IEEE This paper presents a topological study using power flow diagrams to derive all possible basic and non-isolated double-input single-output (DISO) converters. Unlike most reported DISO converters with one bidirectional port, this paper considers up to two bidirectional ports. The paper focuses on providing a general guideline of all power flow combinations and corresponding converter configurations. After eliminating the impractical configurations due to their indirect connection to some ports and their multiple conversion stages, three converter configurations have been identified and corresponding circuit realizations are demonstrated.
Ashtari, S, Tofigh, F, Abolhasan, M, Lipman, J & Ni, W 2019, 'Efficient cellular base stations sleep mode control using image matching', IEEE Vehicular Technology Conference.
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© 2019 IEEE. Green cellular network helps to decrease environmental pollution. In contrast, massive connectivity and demand for higher data rate promise the presence of new generation of cellular system (5G) and small cell networks. Hence, expectation on increasing the number of base stations (BSs), which leads to increase in energy usage. One way to improve energy consumption is by shutting down the redundant BSs while sustaining the Quality-of-Service (QoS) for each user. In this paper, we propose a dynamic structural algorithm based on transportation problem, to switch on/off the BSs in cellular networks without compromising its coverage, and maintain the networks load by neighboring cells. We use weighted graphs to translate our problem as a transportation problem and then use linear programming to solve it. The cost of transport, turning a BS into sleep mode, is illustrated as a function of energy usage,coverage area and load on the BSs. Running the propose method consecutively provides the maximum number of BSs whom are at sleep mode. The methodology explained in this paper reduces energy consumption to almost 40%, whereas maintaining all the existing loads in the network.
Aykin, I, Akgun, B & Krunz, M 2019, 'Smartlink: Exploiting Channel Clustering Effects for Reliable Millimeter Wave Communications', IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2019), IEEE Conference on Computer Communications (IEEE INFOCOM), IEEE, Paris, FRANCE, pp. 1117-1125.
Basnet, S, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Fairness Aware Resource Allocation for Average Capacity Maximisation in General Authorized Access User', 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), IEEE Vehicular Technology Conference, IEEE, Chicago, IL, USA, USA, pp. 1-5.
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Spectrum Access System (SAS) is a three-tier spectrum sharing framework proposed for 3.5 GHz by Federal Communication Commission (FCC) in the United States. General Authorized Access (GAA) users in SAS do not have an assigned channel and can opportunistically access the Priority Access Licensee (PAL) channel satisfying the interference constraint proposed by FCC. Coexistence among GAA users in SAS is a key problem to be solved to enhance the system capacity to meet the increasing traffic demand. In this work, we propose a method for fair and efficient spectrum utilisation for GAA users. To achieve the fairness among GAA users equal interference budget allocation scheme is proposed for each set of GAA users that can hear each other. Our proposed method decide the optimal channel switching schedule that maximises the average capacity of GAA users while satisfying the interference constraint at PAL protection area. This work jointly considers the fairness between GAA users and the average capacity maximisation of GAA network. Simulation result justifies the performance of our proposed method for average capacity maximisation of GAA users and fairness between GAA users by comparing with existing works.
Basnet, S, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Transmit Power Allocation for General Authorized Access in Spectrum Access System Using Carrier Sensing Range', IEEE Vehicular Technology Conference, 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), IEEE, Chicago, IL, USA, USA, pp. 1-5.
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The optimal use of spectrum is a key focus for all regulatory bodies. Federal Communications Commission has introduced Spectrum Access System (SAS) to maximise the spectrum utilisation in the US 3.5 GHz band. SAS is a three-tier spectrum sharing framework where Citizen Broadband Radio Service (CBRS) devices can access the channel when it is not used by Incumbent Access users. CBRS consists of Priority Access Licensee (PAL) and General Authorized Access (GAA). In this paper, we consider the problem of optimum transmit power allocation for GAA users using a carrier sensing range i.e. maximum distance a user can be sensed while guaranteeing the interference to PAL from GAA users is below the threshold. We use carrier sensing range to find the sets of GAA users that cannot transmit at the same time and adjust the interference budget of transmitting GAA users. We present an algorithm for transmit power allocation for GAA users in the SAS. The proposed algorithm uses the transmission characteristics and location information provided by Citizen Broadband Radio Service Devices to SAS to maximise the peak capacity of GAA users ensuring the interference constraint to PAL. Simulation results show that the proposed algorithm significantly increases the peak capacity of GAA users by considering the carrier sensing range and adjusted interference budget.
Bautista, MG, Zhu, H, Zhu, X, Yang, Y, Sun, Y, Dutkiewicz, E & Zhang, F 2019, 'Millimeter-wave BPFs design using quasi-lumped elements in 0.13-µm (Bi)-CMOS technology', Proceedings - IEEE International Symposium on Circuits and Systems.
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© 2019 IEEE A design methodology using quasi-lumped elements for compact millimeter-wave on-chip bandpass filter (BPF) is presented in this work. To implement BPF using this approach, a novel inductor cell is presented first and then using this cell along with metal-insulator-metal (MIM) capacitors, two BPFs are designed. For the purpose of proof-of-concept, all three designs are implemented and fabricated in a standard 0.13-µm (Bi)-CMOS technology. The measurements show that the inductor cell generates a notch at 47 GHz with a chip size of 0.096 × 0.294 mm2 without pads. Moreover, the 1st BPF has the center frequency at 27 GHz with an insertion loss of 2.5 dB and it has one transmission zero at 58 GHz with a peak attenuation of 23 dB. Unlike the 1st design, the 2nd design has two transmission zeros. The center frequency of this BPF is located at 29 GHz with a minimum insertion loss of 3.5 dB. Without the measurement pads, the chip sizes of the two BPFs are 0.076 × 0.296 mm2 and 0.096 × 0.296 mm2, respectively.
Bożejko, W, Chaczko, Z, Nadybski, P & Wodecki, M 2019, 'Meta-heuristic task scheduling algorithm for computing cluster with 2D packing problem approach', Advances in Intelligent Systems and Computing, pp. 74-82.
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© Springer International Publishing AG, part of Springer Nature 2019. In this paper we present a mathematical model and an algorithm for solving a task scheduling problem in computing cluster. The problem is considered as a 2D packing problem. Each multi-node task is treated as a set of separate subtasks with common constrains. For optimization the tabu search metaheuristic algorithm is applied.
Braun, R, Brookes, W, Hadgraft, R & Chaczko, Z 2019, 'Assessment Design for Studio-Based Learning', Proceedings of the Twenty-First Australasian Computing Education Conference, Australasian Computing Education Conference, ACM, Sydney, Australia, pp. 106-111.
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Cai, Z, Tang, X, Li, Z, Zhang, T, Liu, Y & Yang, Y 2019, 'A Low Phase Noise Differential Oscillator Employing Stub-Loaded Nested Split-Ring Resonator Inspired Balanced Bandpass Filter', IEEE MTT-S International Microwave Symposium Digest, pp. 967-970.
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© 2019 IEEE. This paper presents a low phase noise differential oscillator by employing a balanced feedback bandpass filter (BPF) designed with the proposed stub-loaded nested split-ring resonator (SLNSRR). The proposed balanced BPF functions as a frequency stabilization element in its feedback loop. Taking advantage of the balanced structure, a high group delay is obtained by introducing a transition zero near the upper passband of feedback loop filter. The proposed differential oscillator can present a differential output with low phase noise performance. For proof of the concept, a 2 GHz differential oscillator has been designed, fabricated and measured. The measured results show that the 180o out-of-phase differential signals are obtained with almost the same peak-peak voltage among two channels. The output power is 9.18 dBm when oscillates at 2.004 GHz with the second harmonic suppression of 40.63 dB. The measured phase noise is -126.72 dBc/Hz at 100 kHz frequency offset. The figure-of-merit (FOM) at 100 kHz is -196.19 dBc/Hz. The phase noise performance of proposed differential oscillator is one of the best among open literatures.
Cao, Y & Veitch, D 2019, 'Where on Earth Are the Best-50 Time Servers?', Passive and Active Measurement 20th International Conference, PAM 2019, Puerto Varas, Chile, March 27–29, 2019, Proceedings, International Conference on Passive and Active Network Measurement, Spronger, Chile, pp. 101-115.
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© 2019, Springer Nature Switzerland AG. We present a list of the Best-50 public IPv4 time servers by mining a high-resolution dataset of Stratum-1 servers for Availability, Stratum Constancy, Leap Performance, and Clock Error, broken down by continent. We find that a server with ideal leap performance, high availability, and low stratum variation is often clock error-free, but this is no guarantee. We discuss the relevance and lifetime of our findings, the scalability of our approach, and implications for load balancing and server ranking.
Chemalamarri, VD, Braun, R, Lipman, J & Abolhasan, M 2018, 'A Multi-agent Controller to enable Cognition in Software Defined Networks', 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), International Telecommunication Networks and Applications Conference, IEEE, Sydney, Australia, pp. 52-56.
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Current SDN controllers are not cognitive. We propose a new architecture for an SDN controller to enable intelligence. The proposed new architecture is based on Multi-agent systems. As a prototype, we have built a MAS-SDN controller using the GOAL agent programming language. We highlight the motivation behind the new architecture, describe the architecture and provide some initial results
Chen, L, Liu, Y & Guo, YJ 2019, 'Efficient Frequency-invariant Beam Pattern Synthesis with Multiple Space-frequency Nulls', 2019 IEEE International Conference on Computational Electromagnetics, ICCEM 2019 - Proceedings.
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© 2019 IEEE. This paper presents a modified Fourier transform method to synthesize a broadband array with frequency-invariant (FI) mainlobe and multiple space-frequency nulls. In this method, a iterative Fourier transform is used to design multiple optimized reference patterns which have the same mainlobe shape but with different sidelobe or null distributions. These reference patterns are used for describing different radiation requirements in different sub-bands of the whole frequency band. Then, a desired broadband spatial spectral distribution can be obtained by matching it to each reference pattern at each sub-band, and a broadband excitation distribution for generating the desired FI pattern can be efficiently found by performing an inverse fast Fourier transform (IFFT) on the broadband spatial spectral distribution. An example for synthesizing a FI beam pattern with two space-frequency nulls is provided to verify the effectiveness and efficiency of the proposed method.
Cheng, Q, Shi, Z, Nguyen, D & Dutkiewicz, E 2019, 'An OFDM Sensing Algorithm in Full-Duplex Systems with Self-Interference and Carrier Frequency Offset', IEEE Global Communications Conference (GLOBECOM), Hawaii.
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Chu, P, Zhang, JA, Wang, X, Fang, G & Wang, D 2019, 'Semi-persistent v2x resource allocation with traffic prediction in two-tier cellular networks', IEEE Vehicular Technology Conference.
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© 2019 IEEE. In a dense urban area, conventional cellular V2X communications require frequent and heavy resource allocation, which can lead to processing congestion and large delay. In this paper, we propose a semi- persistent resource allocation scheme using the least minimum mean square error (LMMSE) traffic prediction in a two-tier network. The two-tier network architecture includes a central macro base station (MBS) and multiple roadside units (RSU). In the proposed scheme, the MBS pre-allocates persistent resource to RSUs based on predicted traffic, and then allocate dynamic resource upon real-time requests from vehicles through RSUs. We formulate an optimization problem for minimizing the total bandwidth under latency constraints and provide an optimal solution to the problem. Simulation is conducted for both artificially generated and real-world data, and the results validate the effectiveness of the proposed semi- persistent scheme.
Cui, P, Zhang, J, Lu, W, Guo, Y & Zhu, H 2018, 'Sparse Channel Modelling Using Multi-measurement Vector Compressive Sensing', IEEE Global Communications Conference, Abu Dahbi, UAE.
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Cui, P, Zhang, J, Lu, W-J, Guo, Y & Zhu, H 2019, 'Influence of Human Body on Massive MIMO Indoor Channels', Kuala Lumpur, Malaysia.
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Cui, P, Zhang, J, Lu, W-J, Guo, YJ & Zhu, H 2019, 'Influence of Human Body on Massive MIMO Indoor Channels', Kuala Lumpur, Malaysia.
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Ding, C, Wang, K & Guo, YJ 2018, 'Building Antennas on Perovskite Solar Cell (PSC) for Hybrid Solar/EM Wireless Energy Harvesting and Transfer', 2018 Asian Wireless Power Transfer Workshop (AWPT), Sendai, Japan.
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Ding, T, Ding, M & Mao, G 2019, 'MAC Layer performance analysis of dense small cell networks with full duplex', 2018 24th Asia-Pacific Conference on Communications, APCC 2018, pp. 145-149.
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© 2018 IEEE. The study of full duplex (FD) is important because it has been identified as one of the candidate technologies for the 5th-generation (5G) networks. Small cell networks (SCNs) are envisioned to embrace the FD transmission technology in order to increase the spectral efficiency of wireless systems. In this paper, for the first time, we consider FD communications in a realistic small cell networks (SCN) scenario, where base stations (BSs) can select FD or half-duplex (HD) mode according to the real-time downlink (DL)/uplink (UL) traffic. We present analytical results on the probabilities of BS mode selection, which match the simulation results well.
Dinh, H, Niyato, D, Wang, P, Domenico, AD & Strinati, EC 2018, 'Optimal Cross Slice Orchestration for 5G Mobile Services', IEEE Vehicular Technology Conference, IEEE, Chicago, IL, USA, USA.
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5G mobile networks encompass the capabilities of hosting a variety of
services such as mobile social networks, multimedia delivery, healthcare,
transportation, and public safety. Therefore, the major challenge in designing
the 5G networks is how to support different types of users and applications
with different quality-of-service requirements under a single physical network
infrastructure. Recently, network slicing has been introduced as a promising
solution to address this challenge. Network slicing allows programmable network
instances which match the service requirements by using network virtualization
technologies. However, how to efficiently allocate resources across network
slices has not been well studied in the literature. Therefore, in this paper,
we first introduce a model for orchestrating network slices based on the
service requirements and available resources. Then, we propose a Markov
decision process framework to formulate and determine the optimal policy that
manages cross-slice admission control and resource allocation for the 5G
networks. Through simulation results, we show that the proposed framework and
solution are efficient not only in providing slice-as-a-service based on the
service requirements, but also in maximizing the provider's revenue.
dos Santos, AP & Chaczko, Z 2018, 'Blockchain: Status-Quo, Enablers and Inhibitors', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia.
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Blockchain has been evolving and gaining new heights over the years. The shift in the perspective is allowing new user cases beyond the cryptocurrency space. Cryptocurrencies are digital assets supported by the complexities of cryptography, game theory and peer-to-peer networks. Blockchain became a popular platform for decentralized applications, as well as a valuable tool for start-ups seeking fundraising. The aim of this research paper is to review and assess the status quo for each branch of use cases, and then analyze the enabling and inhibiting factors influencing the adoption of blockchain. These findings permit a broader comprehension over the concepts backing blockchain. It will help new users to establish strategies, develop solutions and encourage the employment of blockchain technology.
Ganjkhani, M, Badakhshan, S, Azizivahed, A, Li, L, Chen, L & Huang, Q 2019, 'Optimized water consumption considering power plants efficiency in power system generation', Proceedings of the IEEE International Conference on Industrial Technology, pp. 673-678.
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© 2019 IEEE. In order to generate adequate electricity energy, conventional power plants utilize dramatic volume of water resources. Different methods such as replacing cutting-edge technologies of facilities have been proposed to diminish water consumption in this industry. Most of the approaches are considered as medium or long-term solution which requires substantial investment costs. Meanwhile, because of the process and technology, natural gas-fired power plants need less water among conventional power plants. Therefore, shifting unit commitment planning toward these power plants would aid to save water consumption. Nevertheless, overlooking combined cycle power plants can perform negative impact on power plant efficiency, and it may increase power generation cost. This paper aims to investigate multi-objective optimization problem to minimize water consumption by maximizing the power generation efficiency. Hence, this method contemplates economic dispatch by selecting more efficient and less water required power plants. The proposed model is examined on an IEEE 24-bus test system to address the results, and it is compared with the conventional economic dispatch problem to clarify the impact of the proposed approach. According to the results, some relevant conclusions are drawn.
Gay, D, Betz, RE, Dorrell, D & Knight, A 2017, 'Brushless Doubly Fed Reluctance Machine Testing for Parameter Determination', IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 20th IEEE International Conference on Electrical Machines and Systems (ICEMS), IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Sydney, AUSTRALIA, pp. 2611-2619.
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Gorski, T, Bednarski, J & Chaczko, Z 2018, 'Blockchain-based renewable energy exchange management system', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia, Australia, pp. 1-6.
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The paper presents the concept of renewable energy
management system. The idea behind the system is to exploit
the potential of renewable energy generation sources so as
to provide additional energy services and participation in a
competitive energy market. These actions can significantly affect
the shortening of the period of return on investment of individual
customer in renewable energy sources. The paper contains a
concept of Electricity Consumption and Supply Management
System (ECSM) with application of blockchain technology.
ECSM provides functionality to monitor and record continuously
information about inbound and outbound energy to/from power
grid. Except monitoring inbound and outbound energy, solution
will provide the possibility to manage in automatic and manual
way when energy should be sent to energy grid. Information
about inbound/outbound energy will be part of smart contract
which will be confirmed and stored in every node.
Ha, T & Hoang, D 2019, 'Toward an Active Aging Society an IT Model to Engage the Aging Population', Kuala Lumpur, Malaysia.
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Many countries around the world are expecting a growing number of elderly people as the society is aging over time. This shift is expected to create a large impact on our health and social security system. The cost of having an increasing proportion of elderly people is emerging as a challenge for governments, so much that our government is encouraging people to stay in the workforce longer. As a result, the aging population requires a solution that allows them to remain productive and keeping them mentally healthy. Existing solutions rely on the benefits of social networks or service networks to keep them active and improve mental health. However, these solutions fail to allow elderly people to act as a value contributor for the society. This paper proposes the design of a new model that allows elderly people to actively and collaboratively provide value to the society through an assistive platform that integrates a service network with a social network. This model combines the advantages of the social network to connect them and utilize the advantages of the service network to create opportunities for elderly people to offer their skills and knowledge to exchange benefits with other users. The proposed model can be used as a mean to engage seniors to the community, allowing them to generate value for themselves and the community while staying mentally healthy.
Hakim, G & Braun, R 2019, 'Agent based modeling of a flange climb derailment', 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings.
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© 2018 IEEE. We report on the development of an Agent Based Model of a train derailment incident, considering a number of factors including friction and flange angle. We describe the background and objectives, and use the Rushall derailment as a Case Study. We use the NetLogo modeling environment to build our model. We describe the workings of the model. Two scenarios involving frequency of maintenance are tested using the model. We observe unexpected (emergent) results in one case.
Hesamian, MH, Jia, W, He, X & Kennedy, PJ 2019, 'Atrous Convolution for Binary Semantic Segmentation of Lung Nodule', ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 1015-1019.
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© 2019 IEEE. Accurately estimating the size of tumours and reproducing their boundaries from lung CT images provides crucial information for early diagnosis, staging and evaluating patients response to cancer therapy. This paper presents an advanced solution to segment lung nodules from CT images by employing a deep residual network structure with Atrous convolution. The Atrous convolution increases the field of view of the filters and helps to improve classification accuracy. Moreover, in order to address the significant class imbalance issue between the nodule pixels and background non-nodule pixels, a weighted loss function is proposed. We evaluate our proposed solution on the widely adopted benchmark dataset LIDC. A promising result of an average DCS of 81.24% is achieved, outperforming the state of the arts. This demonstrates the effectiveness and importance of applying the Atrous convolution and weighted loss for such problems.
Hirzallah, M, Xiao, Y & Krunz, M 2018, 'On Modeling and Optimizing LTE/Wi-Fi Coexistence with Prioritized Traffic Classes', 2018 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2018, IEEE International Symposium on Dynamic Spectrum Access Networks, IEEE, Seoul, South Korea.
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© 2018 IEEE. The dramatic growth in demand for mobile data service has prompted mobile network operators (MNOs) to explore new spectrum resources in unlicensed bands. MNOs have been recently allowed to extend LTE-based service called LTE-LAA over 5 GHz U-NII bands, currently occupied by Wi-Fi. To support applications with diverse QoS requirements, both LTE and Wi-Fi technologies introduce multiple priority classes with different channel contention parameters for accessing unlicensed bands. How these different priority classes affect the interplay between coexisting LTE and Wi-Fi technologies is still relatively under explored. In this paper, we develop a simple and efficient framework that helps MNOs assess the fair coexistence between MNOs and Wi-Fi operators with prioritized channel access under multi-channel setting. We derive an approximated close-form solution for each MNO to pre-evaluate the probability of successful transmission (PST), average contention delay, and average throughput when adopting different priority classes to serve different traffics. MNOs and Wi-Fi operators can fit our model using measurements collected offline and/or online, and use it to further optimize their systems' throughput and latency. Our results reveal that PSTs computed with our approximated closed-form model approach those collected from system-level simulations with around 95% accuracy under scenarios of dense network deployment density and high traffic intensity.
Hoang, D & Le, NT 2018, 'Security threat probability computation using Markov Chain and Vulnerability Scoring System', 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), International Telecommunication Networks and Applications Conference, Sydney, Australia.
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Hoang, D & Nguyen, TMC 2018, 'S-MANAGE Protocol for Software-Define IoT', International Telecommunication Networks and Applications Conference, IEEE, Sydney, Australia.
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Hoang, VT, Phung, MD, Dinh, TH & Ha, Q 2018, 'Angle-Encoded Swarm Optimization for UAV Formation Path Planning', 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), International Conference on Intelligent Robots and Systems, IEEE, Madrid, Spain.
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This paper presents a novel and feasible path planning technique for a group of unmanned aerial vehicles (DAVs) conducting surface inspection of infrastructure. The ultimate goal is to minimise the travel distance of DAVs while simultaneously avoid obstacles, and maintain altitude constraints as well as the shape of the UAV formation. A multiple-objective optimisation algorithm, called the Angle-encoded Particle Swarm Optimization (θ- PSO) algorithm, is proposed to accelerate the swarm convergence with angular velocity and position being used for the location of particles. The whole formation is modelled as a virtual rigid body and controlled to maintain a desired geometric shape among the paths created while the centroid of the group follows a pre-determined trajectory. Based on the testbed of 3DR Solo drones equipped with a proprietary Mission Planner, and the Internet-of- Things (loT) for multi-directional transmission and reception of data between the DAV s, extensive experiments have been conducted for triangular formation maintenance along a monorail bridge. The results obtained confirm the feasibility and effectiveness of the proposed approach.
Hora, JA, Piandong, DL, Empas, PEG, Gerasta, OJL, Zhu, X & Dutkiewicz, E 2018, 'A CMOS implemented transimpedance amplifier design for optical communications', 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018, International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management, Baguio City, Philippines.
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© 2018 IEEE. A transimpedance amplifier for optical communication system is presented in this study. The design includes a regulated cascode and an interleaving active feedback to improve the bandwidth of the transimpedance amplifier. Multiple gain stages are also employed to greatly improve the output voltage. This is implemented in 32 nm CMOS technology using Custom Designer from Synopsys. The circuit is designed to compete with existing transimpedance amplifiers implemented in other technologies in the field of optical communications. The transimpedance amplifier design in this study has a gain of 54 dB and a bandwidth of 9.39 GHz. The layout measures 0.0011mm2 in area and the total power dissipated is 2.94 mW.
Huang, H, Liu, Y, Chen, L, Qin, PY & Guo, YJ 2019, 'Synthesis of a Dipole Array with Optimally End-fire Directive Pattern', 2019 IEEE International Conference on Computational Electromagnetics, ICCEM 2019 - Proceedings.
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© 2019 IEEE. In this work, a formula is derived for generating optimally directive pattern for an arbitrary antenna array including mutual coupling effect, and it is then applied to design the optimally directive four-element end-fire dipole array. Synthesis results show that the obtained directivity coefficient is about 2dB and 3.5dB higher than those of ordinary and hansen-woodyard four-element end-fire dipole arrays.
Huang, H, Xu, J, Zhang, J, Wu, Q & Kirsch, C 2018, 'Railway Infrastructure Defects Recognition using Fine-grained Deep Convolutional Neural Networks', 2018 Digital Image Computing: Techniques and Applications (DICTA), Digital Image Computing: Techniques and Applications, IEEE, Canberra, Australia.
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Huang, H, Zheng, J, Zhang, J, Wu, Q & Xu, J 2019, 'Compare more nuanced: Pairwise alignment bilinear network for few-shot fine-grained learning', Proceedings - IEEE International Conference on Multimedia and Expo, pp. 91-96.
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© 2019 IEEE. The recognition ability of human beings is developed in a progressive way. Usually, children learn to discriminate various objects from coarse to fine-grained with limited supervision. Inspired by this learning process, we propose a simple yet effective model for the Few-Shot Fine-Grained (FSFG) recognition, which tries to tackle the challenging fine-grained recognition task using meta-learning. The proposed method, named Pairwise Alignment Bilinear Network (PABN), is an end-to-end deep neural network. Unlike traditional deep bilinear networks for fine-grained classification, which adopt the self-bilinear pooling to capture the subtle features of images, the proposed model uses a novel pairwise bilinear pooling to compare the nuanced differences between base images and query images for learning a deep distance metric. In order to match base image features with query image features, we design feature alignment losses before the proposed pairwise bilinear pooling. Experiment results on four fine-grained classification datasets and one generic few-shot dataset demonstrate that the proposed model outperforms both the state-of-the-art few-shot fine-grained and general few-shot methods.
Huynh, HD, Sandrasegaran, K & Lam, SC 2019, 'Modelling and Simulation of Handover in Light Fidelity (Li-Fi) Network', IEEE Region 10 Annual International Conference, Proceedings/TENCON, pp. 1307-1312.
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© 2018 IEEE. The demand of a faster and more secure wireless communication system leads to the development of a new and innovated network in future. Light Fidelity (Li-Fi) is being researched to provide a better wireless network communication. In this communication technology, light from Light Emitting Diodes (LEDs) has been used for data transmission. The purpose of this research work is to investigate the performance of handover algorithms in a Li-Fi network. Two handover algorithms are Closest Access Point (AP) (CAP) and Maximum Channel Gain (MCG). MATLAB simulation results are presented to evaluate those two types of handover algorithms and to show the impacts of UE's rotation and movement on handover performance.
Imani, MH, Yousefpour, K, Andani, MT & Ghadi, MJ 2019, 'Effect of Changes in Incentives and Penalties on Interruptible/Curtailable Demand Response Program in Microgrid Operation', 2019 IEEE TEXAS POWER AND ENERGY CONFERENCE (TPEC), IEEE Texas Power and Energy Conference (TPEC), IEEE, Texas A&M Univ, College Station, TX.
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Islam, MR, Helen Lu, H, Hossain, MJ & Li, L 2019, 'Improving Power Quality of Distributed PV-EV Distribution Grid by Mitigating Unbalance', 2019 IEEE International Conference on Industrial Technology (ICIT), 2019 IEEE International Conference on Industrial Technology (ICIT), IEEE, Melbourne, Australia.
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Islam, MR, Lu, H, Fang, G, Li, L & Hossain, MJ 2019, 'Optimal Dispatch of Electrical Vehicle and PV Power to Improve the Power Quality of an Unbalanced Distribution Grid', 2019 Proceedings of International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS), 2019 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS), IEEE, Shenzhen, China.
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Islam, MR, Lu, HH, Hossain, MJ & Li, L 2019, 'A Comparison of Performance of GA, PSO and Differential Evolution Algorithms for Dynamic Phase Reconfiguration Technology of a Smart Grid', 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, pp. 858-865.
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© 2019 IEEE. Increasing penetration of Distributed Generations (Photovoltaic solar energy (PV), Wind energy, and Battery Energy Storage) and PEVs (Plug-in Electric Vehicles) into smart grid induce network imbalance which reduces power quality. The uncertainty of demand-generation requires balancing for mitigating network imbalance. Several researchers have used various optimization methods for mitigating unbalance. Moreover, a few researchers have done comparative studies of optimization methods for mitigating unbalance till now. This paper proposes a method to mitigate unbalance and reduce the total power loss by optimizing load distribution among phases. This paper compares the performance of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms on the application of phase balancing. Finally, the efficacy of these algorithms are evaluated for the proposed unbalance mitigation technique, and it is found that the proposed technique using DE algorithm can reduce a significant amount of unbalance at all the buses of the distribution grid with less computational effort.
Ji, LY, Qin, PY, Guo, YJ, Genovesi, S, Zhu, HL & Zong, Y 2019, 'A Reconfigurable Partially Reflective Surface Antenna with Enhanced Beam Steering Capability', 13th European Conference on Antennas and Propagation, EuCAP 2019.
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© 2019 European Association on Antennas and Propagation. A reconfigurable partially reflective surface (PRS) antenna with improved beam steering capability is proposed in this paper. Compared with our previous paper, the beam-steering angle can be enhanced from ±5° to ±17° with less active elements and a much smaller gain variation. It is realized by employing a compact reconfigurable metasurface as the PRS structure, which is located atop a probe-fed square patch antenna. A prototype antenna operating at 5.5 GHz is fabricated and measured. Good agreement between the simulated and measured results for the input reflection coefficients and radiation patterns is achieved, which validates the feasibility of the design principle.
Karmokar, DK, Chen, SL & Guo, YJ 2019, 'Novel Continuous Beam Scanning Leaky-Wave Antennas Using 1-D Mushroom Structure', ISAP 2018 - 2018 International Symposium on Antennas and Propagation.
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© 2018 KIEES. Novel continuous backward-to-forward beam-scanning leaky-wave antennas (LWAs) are designed using a 1-D mushroom structure. An effective method is proposed to suppress the bandgap of a mushroom structure. A smooth transition between the backward and forward leaky modes is achievable by choosing a suitable value of the via inductance, and hence the antenna has design flexibility. The study starts from an equivalent circuit of a unit cell and is verified through simulation and measurement. The measured results confirm a continuous 126° beam scan, starting from -60°, with less than 3 dB gain variation. Moreover, the measured 3dB gain bandwidth is over 58%, which is better than most of the reported LWAs.
Karmokar, DK, Chen, SL, Qin, PY & Guo, YJ 2019, 'Open-stopband suppression and cross-polarization reduction of a substrate integrated waveguide leaky-wave antenna', 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019.
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© 2019 URSI. All rights reserved. Most leaky-wave antennas (LWAs) suffer from significant gain degradation when the main beam points towards broadside. This is because an open stopband (OSB) restricts broadside radiation. In this paper, a method to suppress the OSB of a periodic substrate integrated waveguide (SIW) LWA is discussed. By simultaneously introducing a slot and a partially radiating wall in each unit cell the impedance in the OSB region has been matched and hence a continuous beam scan through broadside is achieved. The developed LWA can scan its main beam from 74° continuously to +40° when the frequency varies from 7.45 to 10.55 GHz, with a broadside gain and a level of cross-polarization for the broadside beam of 10.8 dBi and 21.37 dB, respectively.
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', IEEE/AFCEA Military Communications Conference (MILCOM), Norfolk, VA.
Kempegowda, SM & Chaczko, Z 2018, 'Essential Skill of Enterprise Architect Practitioners for Digital Era', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia, pp. 1-5.
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The technology landscape has evolved from
Mainframe to Digital platform. In this paper, we are proposing
the skills that are essential for an Enterprise Architect to be
successful in the Digital Era.
Kempegowda, SM & Chaczko, Z 2018, 'The optimum number of Principles ideal for Enterprise Architecture practice', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia, pp. 1-4.
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Every organization defines Principles for Enterprise Architecture (EA) practice. As there is no set standard, the principles identified exceeds the recommended number 20 by TOGAF. More the number of Principles defined it will be ignored by the Enterprise Architects instead referring for their decision making. In this paper, we identify the ideal number of principles that will motivate Architects to refer to perform their task
Khan, MNH, Forouzesh, M, Li, L, Siwakoti, Y, Kerekes, T & Blaabjerg, F 2018, 'A Classification of Single-Phase Transformerless Inverter Topologies for Photovoltaic Applications', IEEE Region Ten Symposium, IEEE, Sydney, Australia.
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Khan, MNH, Forouzesh, M, Siwakoti, Y & Li, L 2018, 'Single-Phase Switched-Capacitor Integrated-Boost Five-level Inverter', 2018 IEEE Region 10 Symposium, Sydney, pp. 25-29.
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Khan, MNH, Forouzesh, M, Siwakoti, YP & Li, L 2019, 'Novel High Efficiency H-Bridge Transformerless Inverter for Grid-Connected Single-Phase Photovoltaic Systems', 2018 IEEE Region 10 Symposium, Tensymp 2018, pp. 95-99.
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© 2018 IEEE. This paper proposes a new H-bridge type transformerless inverter for grid-connected photovoltaic (PV) application. The proposed H-bridge zero voltage switch controlled rectifier (HB-ZVSCR) inverter uses additional switches and diodes at the AC side with voltage clamping feature to the DC midpoint. Main characteristics of the proposed inverter are the high conversion efficiency and low leakage current, which make it a suitable candidate for grid-connected PV applications. The analysis and operating principles of the proposed inverter are discussed in details. This theoretical findings has been simulated using PLECS software to verify the common mode voltage (CMV) and leakage current behaviors and the results are compared with similar existing midpoint voltage clamping inverter topologies (i.e. HB-ZVR and HB-ZVR-D). Furthermore, power loss and efficiency of the proposed inverter have been evaluated and compared with existing topologies.
Khan, MNH, Li, L, Siwakoti, Y & Khan, S 2019, 'Switched-Capacitor Integrated Single-Phase (2N+1)-Levels Boost Inverter for Grid-Tied Photovoltaic (PV) Applications', melbourne.
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Khan, MNH, Siwakoti, Y, Li, L & Forouzesh, M 2018, 'Novel High Efficiency H-Bridge Transformerless Inverter for Grid-Connected Single-Phase Photovoltaic Systems', 2018 IEEE Region Ten Symposium (Tensymp), Sydney.
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Khan, MNH, Siwakoti, YP, Li, L & Forouzesh, M 2019, 'Single-Phase Switched-Capacitor Integrated-Boost Five-level Inverter', 2018 IEEE Region 10 Symposium, Tensymp 2018, pp. 25-29.
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© 2018 IEEE. This paper proposes a novel five-level single-phase inverter topology. The inverter uses eight power switches, two capacitors, one inductor, one diode, and a small LC filter at the output. Compared to other multilevel inverters, the proposed inverter can achieve up to 400% more output voltage for the same DC link voltage. As a result, it requires the only of the conventional multilevel inverter topology. The operational states are discussed in brief with the theoretical explanation. A comparison table is illustrated to show the importance of proposed topology compared with existing topologies. The key simulation waveforms are presented, and the preliminary experimental results are carried out for the proposed topology to verify the simulation and theoretical analysis.
Khan, SA, Guo, Y, Chowdhury, NUR & Zhu, J 2019, 'A Least Mean Square Algorithm Based Single-Phase Grid Voltage Parameters Estimation Method', 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019, International Conference on Electrical, Computer and Communication Engineering, Bangladesh.
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© 2019 IEEE. Grid-synchronization may be the most significant task in order to integrate renewable energy sources (RESs) and electric vehicles (EVs) into the power grid. The popular technique for grid synchronization is the power based phase locked loop (PLL). The major challenges that one encounters to design a robust power based PLL is the filter design inside the power based PLL control loop, and estimating the grid voltage parameters under frequency drift conditions. A wide bandwidth should be considered during filter design if a wide range of frequency variations are predicted in the grid voltage. The traditional filters cause a large phase delay if a wide bandwidth is considered during filter design. As a result, it degrades the transient performance of the power based PLL. In order to improve the transient performance of the PLL, this paper adopted a Fourier linear combiner (FLC) filter inside the PLL control loop. Moreover, a feedback loop is used to make the FLC frequency adaptive in order to estimate the grid voltage parameter when grid frequency drift occurs. Simulation and experimental results are provided to verify the proposed technique.
Khawaldeh, HA, Aljarajreh, H, Al-Soeidat, M, Lu, DDC & Li, L 2018, 'Performance investigation of a PV emulator using current source and diode string', 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings, International Conference on Systems Engineering, IEEE, Sydney, Australia, Australia, pp. 1-5.
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© 2018 IEEE. Energy emulator is a specific t ype o f p ower electronic system to mimic the electrical behavior of an energy source and facilitate the testing of energy system. This paper presents a study of a photovoltaic (PV) emulator which is formed by a current source, a diode string and some resistors. It is constructed according to the one-diode photovoltaic model. Unlike the previous study, this paper focuses on using the model equations to design the circuit parameters of the emulator to mimic a selected PV panel and evaluate the circuit performance from both electrical and thermal perspectives. A laboratory experimental setup is built and tested to verify the design. The emulator is power efficient a t t he m aximum p ower p oint. The highest power dissipation of the circuit occurs at the open-circuit voltage operating point.
Lam, SC, Danh Huynh, H, Nguyen, QT & Sandrasegaran, K 2019, 'Strict Frequency Reuse in Ultra Dense Networks', IEEE Region 10 Annual International Conference, Proceedings/TENCON, pp. 1027-1032.
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© 2018 IEEE. In this paper, the Ultra Dense Network (UDN) using Strict Frequency Reuse (FR) is modelled according to the 3GPP recommendations. The recent developed stretch path loss model is utilised to replace the traditional one. The user performance expressions in terms of user classification probability and average coverage probability are derived in Rayleigh fading environment. Throughout the analytical results, which are verified by Monte Carlo simulation, the new findings are presented such as in deep fading environment, the received signal strength at the user keeps constant when the transmit power of Base Station (BS) varies; when the density of BSs increases, the Cell-Center User (CCU) performance reduces continuously while Cell-Edge User (CEU) performance fluctuates.
Le, AT, Nan, Y, Tran, LC, Huang, X, Guo, YJ & Vardaxoglou, JCY 2018, 'Analog Least Mean Square Loop for Self-Interference Cancellation in Generalized Continuous Wave SAR', In Proceedings of the IEEE 88th Vehicular Technology Conference, IEEE Vehicular Technology Conference, IEEE, Chicago, US, pp. 1-5.
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Generalized continuous wave synthetic aperture radar (GCW-SAR) is a promising new imaging radar system since it applies the full-duplex (FD) transmission technique to achieve continuous signaling in order to overcome several fundamental limitations of the conventional pulsed SARs. As in any FD wireless communication system, self-interference (SI) is also a key problem which can impact on the GCW-SAR system. In this paper, the analog least mean square (ALMS) loop in the radio frequency domain is adopted to cancel the SI for a GCW-SAR system with periodic chirp signaling. The average residual SI power after the ALMS loop is analyzed theoretically by a stationary analysis. It is found that the ALMS loop not only works with random signals in general FD communication systems, but also works well with the periodic signal in GCW-SAR systems. Simulation results show that over 45 dB SI cancellation can be achieved by the ALMS loop which ensures the proper operation of the GCW-SAR system.
Le, AT, Tran, LC, Huang, X & Guo, YJ 2019, 'Beam-Based Analog Self-Interference Cancellation with Auxiliary Transmit Chains in Full-Duplex MIMO Systems', The IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, IEEE, Cannes, France, pp. 1-5.
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Li, H, Wang, Q, Huang, X & Guo, YJ 2018, 'Matrix Normalization Based ZF Hybrid Precoded Multi-User MIMO mmWave Systems with Massive Array', IEEE Vehicular Technology Conference, IEEE, Chicago, USA.
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Li, H, Wang, S, Zhang, N & Zhu, J 2019, 'Multiscale Modeling of Magnetic Distribution in a Magnetic Core of High-frequency Transformer', 2018 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2018.
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© 2018 ACES. The multiscale finite element method (MsFEM) combined with conventional finite element method (FEM) is proposed to solve static magnetic field in the ribbon magnetic core. Firstly, a simple 2-dimensional electrostatic problem is used to introduce the MsFEM part. The results are compared to analytical method, as well as conventional FEM. Then, an example of magneto static problem is considered for a ribbon magnetic core built sheet by sheet. Conventional FEM and MsFEM are used to compute the magneto-static field by adopting scalar magnetic potential. Both magnetic potential and magnetic flux density on a certain path are compared. It is shown that the results obtained by MsFEM agrees well with the one from conventional FEM. Moreover, MsFEM combined with FEM is potentially a general strategy for multiscale modeling of ribbon magnetic cores, which can effectively reduce the computational cost.
Li, Q, Chen, Y, Cui, Q, Gu, Y & Mao, G 2019, 'Effective capacity analysis of multiuser ultra-dense networks with cell DTx', 2018 24th Asia-Pacific Conference on Communications, APCC 2018, pp. 21-27.
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© 2018 IEEE. Cell discontinuous transmission (Cell DTx) improves network performance because it help mitigate inter-cell interference. However, the relationship between this technology and network performance has been little studied. The aim of this work is to understand the impact of Cell DTx on users' quality of service (QoS) performance of multiuser ultra-dense networks (UDNs). We extend the traditional one-dimensional effective capacity model and develop a new multidimensional framework for UDNs with Cell DTx, which can be applied to different scheduling policies. Under the round-robin and the max-C/I scheduling examples, computer simulation shows that the analytical and simulation results are in good agreement and thus validate the accuracy of our proposed framework.
Li, Q, Wu, Q, Zhu, C, Zhang, J & Zhao, W 2019, 'Unsupervised User Behavior Representation for Fraud Review Detection with Cold-Start Problem', Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, China, pp. 222-236.
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Liao, Q, Xu, M, Wang, D & Holewa, H 2018, 'Fine-Grained Categorization by Deep Part-Collaboration Convolution Net', 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018, Digital Image Computing: Techniques and Applications (DICTA), Australia.
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© 2018 IEEE. In part-based categorization context, the ability to learn representative feature from quantitative tiny object parts is of similar importance as to exactly localize the parts. We propose a new deep net structure for fine-grained categorization that follows the taxonomy workflow, which makes it interpretable and understandable for humans. By training customized sub-nets on each manually annotated parts, we increased the state-of-the-art part-based classification accuracy for general fine-grained CUB-200-2011 dataset by 2.1%. Our study shows the proposed method can produce more activation to discriminate detail part difference while maintaining high computing performance by applying a set of strategies to optimize the deep net structure.
Liberal, I, Ederra, I & Ziolkowski, RW 2019, 'Designing the bandwidth of single-photon sources with classical antenna techniques', 2019 13TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 13th European Conference on Antennas and Propagation (EuCAP), IEEE, Krakow, POLAND.
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Lin, JY, Wong, SW, Yang, Y & Zhu, L 2019, 'Cavity Balanced-to-Unbalanced Magic-T with Filtering Response', IEEE MTT-S International Microwave Symposium Digest, pp. 444-447.
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© 2019 IEEE. In this paper, a design of balanced-to-unbalanced magic-T with filtering response is proposed for the first time. The function of the proposed magic-T is composed of an in-phase balanced-to-unbalanced power divider and an out-of-phase balanced-to-unbalanced power divider. Three fundamental modes, namely, TE011, TE101, and TM110, of the triple-mode resonators (TMRs) are excited to provide the odd- and even-symmetric field distributions so that in-phase and out-of-phase responses can be achieved. It is noteworthy that the common-mode suppression can be achieved at the balanced ports, while high isolation is achieved at the single-end ports. To verify the concept, the proposed balanced-to-unbalanced magic-T structure is fabricated and measured. Good matching between simulated and measured results shows the validity and accuracy of the proposed design methodology.
Lin, W & Ziolkowski, RW 2018, 'Dual-Functional Electrically Small Huygens Antenna System', ISAP 2018 - 2018 International Symposium on Antennas and Propagation, International Symposium on Antennas and Propagation, IEEE, South Korea.
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© 2018 KIEES. A dual-functional electrically small Huygens antenna system is introduced for wireless power transfer (WPT) and communication applications at 915 MHz. This dual-functional system is facilitated by using two orthogonally-oriented electrically small Huygens linearly polarized (HLP) dipole subsystems. Each HLP antenna consists of two metamaterial-inspired near field resonant parasitic (NFRP) elements, i.e., the capacitive loaded loop (CLL) and the Egyptian axe dipole (EAD). A rectifier circuit is integrated with one of the HLP antennas to facilitate its function as a rectenna for WPT applications. The other HLP antenna serves the communication applications. Due to the large isolation (> 30 dB) between these two HLP subsystems, their functionalities are independent. A successfully fabricated and measured prototype demonstrates that this highly-integrated dual-functional antenna system has excellent performance characteristics. It is electrically-small (ka < 0.77) and produces unidirectional Huygens (cardioid) broadside realized gain patterns with broad beamwidths. It has a high AC to DC conversion efficiency. The antenna system is an excellent, practical candidate for wireless Internet-of-Things (IoT) applications.
Lin, W & Ziolkowski, RW 2019, 'Electrically Small, Highly Efficient, Huygens Circularly Polarized Rectenna for Wireless Power Transfer Applications', 13th European Conference on Antennas and Propagation, EuCAP 2019, European Conference on Antennas and Propagation, IEEE, Krakow, Poland.
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© 2019 European Association on Antennas and Propagation. This paper introduces the first realized electrically small, highly efficient, Huygens circularly polarized (HCP) rectenna for wireless power transfer applications. It is designed to operate at the 915 MHz in the corresponding ISM band. It is realized through the seamless integration of an electrically small HCP antenna and a highly efficient rectifier circuit. The electrically small HCP antenna consists of four electrically small near-field resonant parasitic (NFRP) elements: two Egyptian axe dipoles (EADs) and two capacitively loaded loops (CLLs). The rectifier is a full-wave rectifying circuit based on HSMS286C diodes. It is integrated with the HCP antenna on its bottom layer via a coplanar stripline (CPS) without occupying any additional space. A HCP rectenna prototype was successfully fabricated and tested. It is electrically small (ka < 0.77) with a radius R = λ0 / 8 and a height H = λ0 / 25. Excellent CP radiation absorption capacity is observed. The measured peak AC to DC conversion efficiency reaches 82%. Being electrically small and highly efficient, the reported HCP rectenna is an ideal candidate for wirelessly powering internet-of-things (IoT) devices in many emerging IoT applications.
Liu, F, Liu, Y, Guo, YJ & Liu, QH 2018, 'Synthesis of Rotated Sparse Linear Dipole Array with Shaped Power Pattern', 2018 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2018, International Applied Computational Electromagnetics Society Symposium - China, IEEE, Beijing, China.
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© 2018 ACES. A new shaped pattern synthesis method is presented in which element rotations, positions and phases are co-optimized to produce a shaped beam pattern for a sparse dipole array. Compared with conventional shaped pattern synthesis using excitation amplitude and phase optimization, the proposed method can not only reduce the number of elements But also avoid the usage of unequal power dividers. A synthesis example is provided to verify the performance of the proposed method.
Liu, Y, Luo, Q, Li, M & Guo, YJ 2019, 'Thinned Massive Antenna Array for 5G Millimeter-Wave Communications', 2019 13TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 13th European Conference on Antennas and Propagation (EuCAP), IEEE, Krakow, POLAND.
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Luo, Q, Liu, Y, Liu, F, Ren, Y & Guo, YJ 2018, 'Fast Synthesis Algorithm for Uniformly Spaced Circular Array with Low Sidelobe Pattern', 2018 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2018, International Applied Computational Electromagnetics Society Symposium - China, IEEE, Beijing, China.
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© 2018 ACES. In this paper, a highly efficient approach is proposed to synthesize the low sidelobe pattern of uniformly spaced circular array. The proposed approach can be generalized to deal with the pattern synthesis for the circular array with directional elements. Numerical examples are given to verify the effectiveness and advantage of this approach.
Luo, Y, Zhang, JA, Huang, S, Pan, J & Huang, X 2019, 'Quantization with Combined Codebook for Hybrid Array using Two-Phase-Shifter Structure', IEEE International Conference on Communications.
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© 2019 IEEE. We propose a novel joint quantization scheme for hybrid antenna array systems using the two-phase-shifter (2-PS) structure, where two phase shifters are combined to represent one beamforming weight. Conventional quantization using a single phase shifter for each beamforming weight cannot represent the magnitude. We propose a new codebook design that combines the two codebooks of the two phase shifters in the recently proposed 2-PS structure. We also study the scaling problem of the beamforming vector and propose a low-complexity searching algorithm for finding a near-optimal scalar based on element-wise quantization. The mean squared quantization error and signal-to-noise ratio (SNR) degradation are derived analytically. Simulation results validate the accuracy of the analytical results and the effectiveness of the proposed quantization methods.
Ma, B, Zheng, J, Lei, G & Zhu, J 2019, 'A Robust Design Optimization Approach for Electromagnetic DevicesConsidering Probability Uncertainties', the 22nd International Conference on the Computation of Electromagnetic Fields, Paris.
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Men, X, Wu, G, Guo, Y, Zhu, Z & Gao, J 2019, 'Development of an advanced motor control system for electric vehicles', SAE Technical Papers.
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© 2019 SAE International. All Rights Reserved. Electric vehicles are considered as one of the most popular way to decrease the consumption of petroleum resources and reduce environmental pollutions. Motor control system is one of the most important part of electric vehicles. It includes power supply module, IGBT driver, digital signal processing (DSP) controller, protection adjustment module, and resolver to digital convertor. To implement the control strategies on motor control system, a lot of practical aspects need to be taken into accounts. It includes setup of the initial excitation current, consistency of current between motor and program code, over-modulation, field weakening control, current protection, and so on. In this paper, an induction motor control system for electric vehicles is developed based on DSP. The control strategy is based on the field-oriented control (FOC) and space vector pulse width modulation (SVPWM). Speed calculation, over-modulation, field weakening control, PI controller, and fault diagnosis are also applied in this DSP algorithm. As an industry product running on a real electric bus with a 100kW induction motor, communication with vehicle control unit (VCU) by CAN bus, control system safety and PC software designed for lab experiments are also discussed. This paper focused on how to develop the advanced motor control system for electric vehicles for industrial application. The steady-state and transient performances of this motor control system are analyzed by both test-bench experiments and road experiments. Its performance is satisfactory when applied to the real electric vehicle.
Mohammed, F, He, X, Chen, J & Lin, Y 2019, 'A Novel Model for Classification of Parkinson’s Disease: AccuratelyIdentifying Patients for Surgical Therapy', HICSS, Hawaii International Conference on System Sciences, USA, pp. 3741-3750.
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Parkinson’s disease (PD) is a neurodegenerative disorder and a global health problem that has no curative therapies. Surgery is a well-established therapy for controlling symptoms of advanced PD patients. This paper proposes a streamlined model to classify PD and to identify appropriate patients for surgical therapy. The data was gathered from the
Parkinson’s Progressive Markers Initiative consisting of 1080 subjects. Multilayer Perceptron (MLP), Decision trees, Support Vector Machine and Na¨ıve Bayes are used as classifiers. MLP achieves the highest accuracy as compared to other three classifiers. The dataset used in our experiments is from the Parkinson Progressive Markers Initiative. With feature selection, it is observed that the same classification accuracy is achieved with 60% of the attributes as that using all attributes. It
is demonstrated that our classification model for PD patients produces the most accurate results and achieves the highest accuracy of 98.13%
More, FJ & Chaczko, Z 2018, 'Non-invasive Methods in the Detection of Coronary Artery Disease', 2018 26th International Conference on Systems Engineering (ICSEng), International Conference on Systems Engineering, IEEE, Sydney, Australia, pp. 1-5.
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Coronary Artery Disease (CAD) is the prime causal factor in cardiovascular disease in the 21st century throughout the world. In Australia, CAD related diseases result in 12% morbidity and mortality rate. This paper summarizes the non-invasive methods of diagnosis of CAD. The association between medical science and biomedical engineering has led to the development of non-invasive methods of diagnosis of CAD. The use of new technology that exploits IoT and Body Area Networks using wearable sensor devices over the patient’s body and medical experts to diagnose CAD. Progression of clinical assessment, diagnosis, and evaluation of CAD have been achieved in the last decade. The current treatment plan for CAD focused on clinical prevention, surgical or a combination of both depending on the severity of disease. The analysis of coronary artery disease, chest pain, and various things involved in the assessment of patient’s history with relieving factors such as risk stratification and non-invasive tests used in diagnosis of CAD.
Mukhtar, NM & Lu, DDC 2018, 'An Isolated Bidirectional Forward Converter with Integrated Output Inductor-Transformer Structure', 2018 IEEE 4th Southern Power Electronics Conference (SPEC 2018), IEEE 4th Southern Power Electronics Conference, IEEE, Singapore, pp. 137-143.
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© 2018 IEEE. An isolated bidirectional forward DC/DC converter is presented. The proposed converter is formed by combining two identical two-switch forward converters through a shared transformer. The transformer also integrates the function of the output inductors on both sides into a single magnetic structure. The proposed topology offers low voltage stress on the power switches due to the voltage clamp and recycling of leakage energy to the source. The main goal of this paper is to show the operation principle and capability of the proposed topology as a bidirectional converter with less switching stress and reduce component count. Finally, a hardware prototype is built and tested to validate the theoretical analysis in the continuous conduction mode (CCM).
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', IEEE Global Communications Conference (GLOBECOM), Hawaii.
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Nguyen, N-T, Van Huynh, N, Hoang, DT, Nguyen, DN, Nguyen, N-H, Nguyen, Q-T & Dutkiewicz, E 2019, 'Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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Ni, Z, Zhang, JA, Yang, K, Gao, F & Gao, Z 2018, 'Codebook Based Minimum Subspace Distortion Hybrid Precoding for Millimeter Wave Systems', IEEE Globecom Workshops, Abu Dhabi, United Arab Emirates.
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Perry, S, Pinheiro, A, Dumic, E & da Silva Cruz, LA 2019, 'Study of Subjective and Objective Quality Evaluation of 3D Point Cloud Data by the JPEG Committee', Image Quality and System Performance XVI, IS&T, Burlingame, CA, USA, pp. 312-1-312-1.
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The SC29/WG1 (JPEG) Committee within ISO/IEC is currently working on developing standards for the storage, compression and transmission of 3D point cloud information. To support the creation of these standards, the committee has created a database of 3D point clouds representing various quality levels and use-cases and examined a range of 2D and 3D objective quality measures. The examined quality measures are correlated with subjective judgments for a number of compression levels. In this paper we describe the database created, tests performed and key observations on the problems of 3D point cloud quality assessment.
Pham, T, Takalkar, M, Xu, M, Hoang, DT, Truong, HA, Dutkiewicz, E & Perry, S 2019, 'Airborne Object Detection Using Hyperspectral Imaging: Deep Learning Review', The 19th International Conference on Computational Science and Its Applications, Springer, Saint Petersburg, Russia, pp. 306-321.
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Hyperspectral images have been increasingly important in object detection applications especially in remote sensing scenarios. Machine learning algorithms have become emerging tools for hyperspectral image analysis. The high dimensionality of hyperspectral images and the availability of simulated spectral sample libraries make deep learning an appealing approach. This report reviews recent data processing and
object detection methods in the area including hand-crafted and automated feature extraction based on deep learning neural networks. The accuracy performances were compared according to existing reports as well as our own experiments (i.e., re-implementing and testing on new datasets). CNN models provided reliable performance of over 97% detection accuracy across a large set of HSI collections. A wide range of
data were used: a rural area (Indian Pines data), an urban area (Pavia University), a wetland region (Botswana), an industrial field (Kennedy Space Center), to a farm site (Salinas). Note that, the Botswana
set was not reviewed in recent works, thus high accuracy selected methods were newly compared in this work. A plain CNN model was also found to be able to perform comparably to its more complex variants
in target detection applications.
Pham, TT & Dutkiewicz, E 2019, 'Quantify Physiologic Interactions Using Network Analysis', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 142-151.
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© 2019, Springer Nature Switzerland AG. To better understand the neural interactions amongst human organ systems, this work provides a framework of data analysis to quantify forms of neural signalling. We explore network interactions among the human brain and motor controlling. The main objective of this work is to provoke unique challenges in the emerging Network Physiology field. The proposed method applies network analysis techniques including power coherence for connectivity discovering and correlation measurement for profiling relationships. We used a well-designed dataset of 50 subjects over 14 different scenarios for each individual. We found network models for these interactions and observed informative network behaviours. The information can be used to study impaired communications that can lead to dysfunction of organs or the entire system such as sepsis.
Poblete, P, Pereda, J, Nunez, F & Aguilera, RP 2019, 'Distributed current control of cascaded multilevel inverters', Proceedings of the IEEE International Conference on Industrial Technology, pp. 1509-1514.
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© 2019 IEEE. Multilevel inverters are widely used in the medium voltage energy market. Among them, the Cascaded H-Bridge (CHB) and Modular Multilevel Inverter (MMC) stand out for their modular hardware, which allows the easy replacement of their modules in the case of failures. Normally, these converters are operated with centralized control schemes, which require a large processing capacity, multiple digital outputs and wires for the switching signals of the transistors. The use of a centralized controller reduces the modularity of the system and generates difficulties as the number of inverters connected in series (cells) increases. In this work, a distributed control strategy for CHB converters is proposed, allowing each cell to have an independent local controller, which increases the modularity of the multilevel converter without deteriorating the performance of the system. Extensive simulations are carried out, showing the advantages and disadvantages of the proposed distributed control strategy offers when compared to a PI current controller on dq axes and Shifted PWM. The proposed control scheme is also tested under fault conditions and is finally applied in a Field Oriented Control (FOC) of a permanent magnet synchronous machine (PMSM), in order to evaluate its performance in electrical drives applications.
Puthal, D, Mohanty, SP, Nanda, P, Kougianos, E & Das, G 2019, 'Proof-of-Authentication for Scalable Blockchain in Resource-Constrained Distributed Systems', 2019 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), IEEE International Conference on Consumer Electronics (ICCE), IEEE, Las Vegas, NV.
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Qureshi, S & Braun, R 2019, 'Dynamic light path establishment in switch fabric using openFlow', 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings.
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© 2018 IEEE. In today's optical networks, Light paths are established through Network Management System and Element Management System, which is a manual and cumbersome process. Paths are computed and pre-setup according to the known traffic d emands, a nd p rovisioning a ny new service takes time. Several efforts have recently been made to make the path establishment process dynamic, including the Software Defined N etworking a pproach. H owever all of this work has assumed fully interconnected fabrics of the network devices which is generally not the case. The task of end to end path establishment between network elements and through fabric are interrelated, and this task remains incomplete, without consideration of the switch's limitations. This work highlights for the first time the issue of path establishment dynamically through a switch fabric. The paper briefly e xplains t he p roblem a nd s uggests an SDN based solution using the OpenFlow protocol. This work contributes a represention of the basic framework which will be required to make the complete path setup process dynamic. The paper also includes an operational description.
Saki, M, Abolhasan, M & Lipman, J 2019, 'A big sensor data offloading scheme in rail networks', IEEE Vehicular Technology Conference, IEEE Vehicular Technology Conference, IEEE, Kuala Lumpur, Malaysia, Malaysia.
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© 2019 IEEE. In this paper, we propose an offloading scheme to transfer massive stored sensor data from rolling stock to railway data centers. We apply a delayed offloading strategy for non-critical stored data assuming that the critical data has been already separated through an appropriate edge processing task and has been sent via a real-time communication such as cellular networks. We propose train stations as potential and feasible spots for data offloading via available wireless local area networks (WLAN) such as existing WiFi network at stations. Thus, stations will not only be the places of passenger exchange but also data exchange. We develop an analytical model customized for the proposed offloading strategy in rail applications. Then we validate the performance of our model through simulation in various scenarios in Omnet. The simulation results shows an accuracy of %98.67 for the proposed analytical model with reference to the simulation results in Omnetpp. Additionally, by using our proposed scheme, we can theoretically offload up to 5.43 GB per each stopping station.
Salah, AA, Dorrell, DG & Guo, Y 2017, 'A Review of the Monitoring and Damping Unbalanced Magnetic Pull in Induction Machines Due to Rotor Eccentricity', IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 20th IEEE International Conference on Electrical Machines and Systems (ICEMS), IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Sydney, AUSTRALIA, pp. 2569-2580.
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Salama, AM, Li, M, Lazos, L, Xiao, Y & Krunz, M 2018, 'On the Privacy and Utility Tradeoff in Database-Assisted Dynamic Spectrum Access', 2018 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2018, IEEE International Symposium on Dynamic Spectrum Access Networks, IEEE, Seoul, South Korea.
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© 2018 IEEE. In dynamic spectrum access, commercially-operated database servers are often used to assist the opportunistic users (OUs) to query and access spectrum vacancies of incumbent users (IUs). The query and answer process in such DSA architectures introduce significant privacy concerns for potential leakage of the sensitive operational details of the IUs, especially their locations. Existing privacy-preserving mechanisms such as location cloaking or spatial obfuscation can be used to hide IUs' locations. They however cannot guarantee the interference from all surrounding access-allowed OUs staying under a given limit. In addition, the spectrum utilization (i.e., transmission opportunities) of OUs should also be considered in the design of mechanisms. The complex three-way tradeoff among privacy, interference and utility has not been systematically studied in the literature. In this paper, we first endeavor to tackle this challenge, by introducing a privacy zone within the exclusion zone. In the privacy zone the IU's location is indistinguishable, while the exclusion zone guarantees the interference limit within the privacy zone. Under two variants of the system model (either known OU locations or probabilistic locations with known density), we formulate and solve corresponding optimization problems to find the optimal tradeoff of one versus the other two objectives. Simulation results with real-world maps/parameters show that the IU's privacy increases with decreasing OUs' utility given a fixed allowable interference for the IUs.
Sang, L, Xu, M, Qian, S & Wu, X 2019, 'AAANE: Attention-based adversarial autoencoder for multi-scale network embedding', Advances in Knowledge Discovery and Data Mining 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, China, pp. 3-14.
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© Springer Nature Switzerland AG 2019. Network embedding represents nodes in a continuous vector space and preserves structure information from a network. Existing methods usually adopt a one-size-fits-all approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scales play different roles in embedding learning. In this paper, we propose an Attention-based Adversarial Autoencoder Network Embedding (AAANE) framework, which promotes the collaboration of different scales and lets them vote for robust representations. The proposed AAANE consists of two components: (1) an attention-based autoencoder that effectively capture the highly non-linear network structure, which can de-emphasize irrelevant scales during training, and (2) an adversarial regularization guides the autoencoder in learning robust representations by matching the posterior distribution of the latent embeddings to a given prior distribution. Experimental results on real-world networks show that the proposed approach outperforms strong baselines.
Saputra, Y, Dinh, H, Nguyen, D & Dutkiewicz, E 2019, 'JOCAR: A Jointly Optimal Caching and Routing Framework for Cooperative Edge Caching Networks', IEEE Global Communications Conference (GLOBECOM), Hawaii.
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Saputra, Y, Dinh, H, Nguyen, D, Dutkiewicz, E, Mueck, M & Srikanteswara, S 2019, 'Energy Demand Prediction with Federated Learning for Electric Vehicle Networks', IEEE Global Communications Conference (GLOBECOM), Hawaii.
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Seifollahi, S, Piccardi, M, Borzeshi, EZ & Kruger, B 2019, 'Taxonomy-augmented features for document clustering', Communications in Computer and Information Science, pp. 241-252.
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© Springer Nature Singapore Pte Ltd. 2019. In document clustering, individual documents are typically represented by feature vectors based on term-frequency or bag-of-word models. However, such feature vectors intrinsically dismiss the order of the words in the document and suffer from very high dimensionality. For these reasons, in this paper we present novel taxonomy-augmented features that enjoy two promising characteristics: (1) they leverage semantic word embeddings to take the word order into account, and (2) they reduce the feature dimensionality to a very manageable size. Our feature extraction approach consists of three main steps: first, we apply a word embedding technique to represent the words in a word embedding space. Second, we partition the word vocabulary into a hierarchy of clusters by using k-means hierarchically. Lastly, the individual documents are projected to the hierarchy and a compact feature vector is extracted. We propose two methods for generating the features: the first uses all the clusters in the hierarchy and results in a feature vector whose dimensionality is equal to the number of the clusters. The second uses a small set of user-defined words and results in an even smaller feature vector whose dimensionality is equal to the size of the set. Numerical experiments on document clustering show that the proposed approach is capable of achieving comparable or even higher accuracy than conventional feature vectors with a much more compact representation.
Shen, J, Wang, Y & Zhang, J 2018, 'Memory optimized Deep Dense Network for Image Super-resolution', Digital Image Computing: Techniques and Applications, IEEE, Canberra, Australia.
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CNN methods for image super-resolution consume a large number of training-time memory, due to the feature size will not decrease as the network goes deeper. To reduce the memory consumption during training, we propose a memory optimized deep dense network for image super-resolution. We first reduce redundant features learning, by rationally designing the skip connection and dense connection in the network. Then we adopt share memory allocations to store concatenated features and Batch Normalization intermediate feature maps. The memory optimized network consumes less memory than normal dense network. We also evaluate our proposed architecture on highly competitive super-resolution benchmark datasets. Our deep dense network outperforms some existing methods, and requires relatively less computation.
Shen, J, Zhang, J & Wang, Y 2018, 'Deep Bi-Dense Networks for Image Super-Resolution', Digital Image Computing: Techniques and Applications, Canberra.
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Shi, Z, Zhang, JA, Xu, R & Cheng, Q 2019, 'Deep Learning Networks for Human Activity Recognition with CSI Correlation Feature Extraction', IEEE International Conference on Communications.
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© 2019 IEEE. Device free WiFi Sensing using channel state information (CSI) has been shown great potentials for human activity recognition (HAR). However, extracting reliable and concise feature signals remains as a challenging problem, especially in a dynamic and complex environment. In this paper, we propose a novel scheme for CSI-based HAR using deep learning network (CH-DLN), with an innovative CSI correlation feature extraction (CCFE) method. The CCFE method pre-processes the signals input to the DLN in two steps. Firstly, it uses a recursive algorithm to reduce non-activity-related information from the signal and hence enhance the activity-dependent signals. Secondly, it computes the correlation over both the time and frequency domain to disclose better signal structure and compress the signal. From such enhanced and compressed signals, we utilize the recurrent neural networking (RNN) to automatically extract deeper features, and then apply the softmax regression algorithm for classifying activities. Through extensive experimental results, our proposed scheme is shown to outperform state-of-the-art methods in recognition accuracy, with much less training time.
Shi, Z, Zhang, JA, Xu, Y & Fang, G 2018, 'Human Activity Recognition Using Deep Learning Networks with Enhanced Channel State information', IEEE Globecom Workshops, IEEE, Abu Dhabi, United Arab Emirates.
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Siwakoti, YP, Mahajan, A & Liese, S 2018, 'Active utilization of a full DC-Link voltage in multilevel converter', INTELEC, International Telecommunications Energy Conference (Proceedings), International Telecommunications Energy Conference, Italy.
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© 2018 IEEE. Multilevel inverter technology has emerged recently as a very important alternative in the area of high-power medium-voltage energy conversion. Multilevel inverter reduces the inductors and filters size, whilst improving the output power quality. However, the main drawback of the multi-level inverter topologies is that they utilizes only ≤ 50% of the input dc-bus voltage, i.e. they require two times the peak of ac output voltage. For example, the nominal input voltage of the NPC, ANPC and Flying Capacitor is 800 V dc . This high dc-link voltage not only requires higher voltage components (both active and passive) but also prompts to use an additional front-end boost dc-dc converter. Considering these aspects, this paper presents a novel technique to extend the input dc-bus voltage utilization in any conventional multilevel inverter from ≤ 50% to ≤ 100%. The novel technique utilizes an additional T-type module (consist of four active switches), which is inserted just before the two dc-link capacitor forming a new grounding point. The novel method not only reduces the input voltage requirement and voltage stress, but also increases the output voltage levels of the inverter. In general, this technique can be implemented to any multilevel inverter. An example of implementation of 5L inverter from the conventional 3-Level T-type inverter is discussed and validated. Measurement results shows that the new Dual T-type inverter has a flat efficiency « 99 % over a wide range of load.
Sun, F, Zhu, H, Zhu, X, Yang, Y, Sun, Y & Xue, Q 2019, 'Design of ultra-wideband on-chip millimter-wave bandpass filter in 0.13-µm (Bi)-CMOS technology', Proceedings - IEEE International Symposium on Circuits and Systems.
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© 2019 IEEE In this work, an on-chip bandpass filter (BPF) with ultra-wideband, low insertion loss, sharp selectivity and excellent in-band flatness is achieved using a novel design approach based on a quasi-lumped-element method. This approach simply utilizes folded metal strip lines with metal-insulator-metal (MIM) capacitors. To understand the principle of the presented design approach, theoretical analysis is given by means of a simplified equivalent LC-circuit model. Using the analyzed results with a full-wave electromagnetic (EM) simulator to guide the design, a BPF is implemented and fabricated in a standard 0.13-µm (Bi)-CMOS technology. The measurements show that a return loss of better than 10 dB is obtained from 13.5 to 32 GHz. Furthermore, the insertion loss of less than 2.3 dB is achieved with less than 0.1 dB in-band magnitude ripple. The BPF size without measurement pads is only 0.148 mm2 (0.37 × 0.4 mm2).
Sun, F, Zhu, X, Zhu, H, Yang, Y & Gomez-Garcia, R 2019, 'On-Chip Millimeter-Wave Bandpass Filter Design Using Multi-Layer Modified-Ground-Ring Structure', IEEE MTT-S International Microwave Symposium Digest, pp. 853-856.
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© 2019 IEEE. A design approach for compact on-chip bandpass filters (BPFs) is presented in this work. It exploits a novel multi-layer modified-ground-ring structure (ML-MGRS) with additional ground plates that allows to generate a transmission zero for selectivity increase without extra occupied area. A simplified LC-equivalent circuit model is provided to understand the operational principles of this ML-MGRS concept. Moreover, to validate the experimental feasibility of this transmission-zero-creation technique for on-chip BPFs, a millimeter-wave compact BPF is designed and fabricated in a standard 0.13- CMOS technology. The measured results show that the filter exhibits out-of-band power-suppression levels above 40 dB beyond 40 GHz. The center frequency of this filter is 23.5 GHz with a power-insertion-loss level of 3.8 dB, while the input power-matching levels are higher than 10 dB from 19 GHz to 28 GHz. The size of the BPF, excluding the pads, is only 0.06 × 0.284 mm.
Sun, Y, Yue, H, Zhang, J & Booth, C 2019, 'Minimisation of Residential Energy Costs for PV-SWH and PV-T Systems', 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, Brazil.
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Takalkar, MA, Zhang, H & Xu, M 2019, 'Improving Micro-expression Recognition Accuracy Using Twofold Feature Extraction', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 652-664.
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© 2019, Springer Nature Switzerland AG. Micro-expressions are generated involuntarily on a person’s face and are usually a manifestation of repressed feelings of the person. Micro-expressions are characterised by short duration, involuntariness and low intensity. Because of these characteristics, micro-expressions are difficult to perceive and interpret correctly, and they are profoundly challenging to identify and categorise automatically. Previous work for micro-expression recognition has used hand-crafted features like LBP-TOP, Gabor filter, HOG and optical flow. Recent work also has demonstrated the possible use of deep learning for micro-expression recognition. This paper is the first work to explore the use of hand-craft feature descriptor and deep feature descriptor for micro-expression recognition task. The aim is to use the hand-craft and deep learning feature descriptor to extract features and integrate them together to construct a large feature vector to describe a video. Through experiments on CASME, CASME II and CASME+2 databases, we demonstrate our proposed method can achieve promising results for micro-expression recognition accuracy with larger training samples.
Tang, MC & Ziolkowski, RW 2019, 'Multifunctional Huygens Dipole Antennas', 13th European Conference on Antennas and Propagation, EuCAP 2019, European Conference on Antennas and Propagation, IEEE, Krakow, Poland.
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© 2019 European Association on Antennas and Propagation. Two electrically small, multifunctional Huygens dipole antennas that operate in the L-band are reviewed briefly. In both designs, two pairs of magnetic and electric near-field resonant parasitic (NFRP) elements are combined. Egyptian axe dipoles (EADs) generate the electric dipoles; capacitively loaded loops (CLLs) generate the magnetic dipoles. These NFPR elements are excited with coax-fed driven dipole elements. Both systems are low profile and radiate cardioid patterns pointed in the broadside direction. One Huygens antenna is a dual linearly polarized (dual-LP) system. The other one produces parallel, LP fields at two operating frequencies (dual-band LP).
Tofigh, F, Mao, G, Lipman, J & Abolhasan, M 2018, 'Crowd Density Mapping Based on Wi-Fi Measurements on Train Platforms', 2018 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS), International Conference on Signal Processing and Communication Systems, IEEE, Cairns, Australia.
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Crowd distribution is a challenging issue in the management and design levels. This paper provides a passive method to derive the crowd density distribution using Wi-Fi measurements on a real scenario. Six WiFi access points (AP) are deployed in the platform 2/3 of Redfern station, Sydney to monitor the platform for a week. Based on the probability maps that are built using RSSI measurements and prior knowledge, the crowd distribution is calculated on the platform and its results are compared with distributions acquired from CCTV images. Final density heat maps are in good agreement with the acquired results from CCTV cameras.
Uzair, M, Li, L & Zhu, J 2018, 'Identifying line-to-ground faulted phase in low and medium voltage AC microgrid using principal component analysis and supervised machine-learning', Australasian Universities Power Engineering Conference 2018, IEEE Xplore, Auckland.
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A supervised machine-learning based approach for faulted phase identification in bolted, low- and high-impedance line-to-ground faults using principal component analysis for feature extraction from multiple input signals is presented in this paper. DIgSILENT PowerFactory is used for simulating the underlying microgrid to obtain fault related data, while MATLAB is used for machine learning application. A 15-fold cross validation is applied to the training data set for evaluation of different machine learning models and the results show supreme performance compared to previous methods.
Van Huynh, N, Hoang, DT, Nguyen, DN & Dutkiewicz, E 2019, 'Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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Vo, A & Eryk Dutkiewicz 2018, 'Optimal Length-Constrained Segmentation and Subject-Adaptive Learning for Real-time Arrhythmia Detection', IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, Washington, DC, USA.
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Vu, L, Cao, VL, Nguyen, QU, Nguyen, DN, Hoang, DT & Dutkiewicz, E 2019, 'Learning Latent Distribution for Distinguishing Network Traffic in Intrusion Detection System', ICC 2019 - 2019 IEEE International Conference on Communications (ICC), ICC 2019 - 2019 IEEE International Conference on Communications (ICC), IEEE, Shanghai.
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Vu, TV, Nguyen, D, Dinh, H & Dutkiewicz, E 2019, 'QoS-Aware Fog Computing Resource Allocation using Feasibility-Finding Benders Decomposition', IEEE Global Communications Conference (GLOBECOM), Hawaii.
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Wang, S, Wang, Z, Deng, J, Guo, Y & Dorrell, DG 2019, 'The analysis of a ferriteless rectangular coupler with reactive assistive shielding coils for ev wireless charging', Proceedings of the IEEE International Conference on Industrial Technology, pp. 1622-1627.
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© 2019 IEEE. Autonomous driving technology has made significant progress in recent decades. For fully autonomous driving of an electric vehicle, the recharging process should be possible without a manually fixed connection. Wireless charging technology is a promising solution for electric vehicle recharging automation. The wireless transformer/coupler is the key component in electric vehicle wireless charging. The maximum power transfer capability and efficiency are limited by the coupler. To reach the required power level, efficiency and electromagnetic exposure to surrounding area, the coupler should be analyzed. In this paper, a coupler with assistive coils is presented and analyzed. The assistive coils perform as reactive shielding coils as well as flux concentrating coils. Finite element simulation and circuit simulation results are shown.
Wang, X, Zha, X, Yu, G, Ni, W, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2018, 'Attack and Defence of Ethereum Remote APIs', 2018 IEEE Globecom Workshops, GC Wkshps 2018 - Proceedings, IEEE Globecom Workshops, IEEE, Abu Dhabi, United Arab Emirates, United Arab Emirates.
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© 2018 IEEE. Ethereum, as the first Turing-complete blockchain platform, provides various application program interfaces for developers. Although blockchain has highly improved security, faulty configuration and usage can result in serious vulnerabilities. In this paper, we focus on the security vulnerabilities of the official Go-version Ethereum client (geth). The vulnerabilities are because of the insecure API design and the specific Ethereum wallet mechanism. We demonstrate attacks exploiting these vulnerabilities in an Ethereum testbed. The vulnerabilities are confirmed by the scanning results on the public Internet. Finally, corresponding countermeasures against attacks are provided to enhance the security of the Ethereum platform.
Watterson, P, Gorrie, C & Herok, G 2019, 'HUMAN TRIAL OF MEDIAN NERVE ACTIVATION BY HIGH SPEED ROTATION OF A BIPOLE MAGNET CONFIGURATION', International Neuromodulation Society 14th World Congress, Sydney, Australia.
Webb, BA & Ziolkowski, RW 2018, 'Enabling Transmission Through Reentry Plasmas: Simulation of Plasma-SRR Layered Materials', 2018 6TH IEEE INTERNATIONAL CONFERENCE ON WIRELESS FOR SPACE AND EXTREME ENVIRONMENTS (WISEE), IEEE International Conference on Wireless for Space and Extreme Environments, IEEE, Huntsville, AL, pp. 101-103.
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Wilson, K, Alabd, R, Safavi-Naeini, M, Abolhasan, M & Franklin, D 2019, 'Localisation of the Lines of Response in a Continuous Cylindrical Shell PET Scanner', IEEE Engineering in Medicine and Biology Conference, Berlin, Germany.
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This work presents a technique for localising the endpoints of the lines of response in a PET scanner based on a continuous cylindrical shell scintillator. The technique is demonstrated by applying it to a simulation of a sensitivity-optimised continuous cylindrical shell PET system using two novel scintillator materials - a transparent ceramic garnet, GLuGAG:Ce, and a LuF$_3$:Ce-polystyrene nanocomposite. Error distributions for the endpoints of the lines of response in the axial, tangential and radial dimension as well as overall endpoint spatial error are calculated for three source positions; the resultant distribution of error in the placement of the lines of response is also estimated.
Yan, B, Zhao, Q, Zhang, JA, Li, Y & Wang, Z 2019, 'Convergence acceleration for multiobjective sparse reconstruction via knowledge transfer', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 475-487.
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© Springer Nature Switzerland AG 2019. Multiobjective sparse reconstruction (MOSR) methods can potentially obtain superior reconstruction performance. However, they suffer from high computational cost, especially in high-dimensional reconstruction. Furthermore, they are generally implemented independently without reusing prior knowledge from past experiences, leading to unnecessary computational consumption due to the re-exploration of similar search spaces. To address these problems, we propose a sparse-constraint knowledge transfer operator to accelerate the convergence of MOSR solvers by reusing the knowledge from past problem-solving experiences. Firstly, we introduce the deep nonlinear feature coding method to extract the feature mapping between the search of the current problem and a previously solved MOSR problem. Through this mapping, we learn a set of knowledge-induced solutions which contain the search experience of the past problem. Thereafter, we develop and apply a sparse-constraint strategy to refine these learned solutions to guarantee their sparse characteristics. Finally, we inject the refined solutions into the iteration of the current problem to facilitate the convergence. To validate the efficiency of the proposed operator, comprehensive studies on extensive simulated signal reconstruction are conducted.
Yang, J, Ding, M, Mao, G & Luan, TH 2019, 'Interference management in underlay in-band D2D-enhanced cellular networks : (Invited Paper)', 2018 24th Asia-Pacific Conference on Communications, APCC 2018, pp. 62-67.
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© 2018 IEEE. Recently, it has been standardized by the 3rd Generation Partnership Project (3GPP) [1] that device-to-device (D2D) communications should use uplink resources when coexisting with conventional cellular communications. With uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we consider a D2D mode selection criterion based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Specifically, a UE will operate in a cellular mode, if its received signal strength from the strongest base station (BS) is larger than a threshold β; otherwise, it will operate in a D2D mode. Furthermore, in our study, cellular UEs, D2D transmit UEs and D2D receiver UEs constitute the entire UE set, which is a more practical assumption than dropping more UEs for D2D reception only in existing works. The coverage probability and the area spectral efficiency (ASE) are derived for both the cellular network and the D2D one. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and provide guidelines for selecting the parameters for network operations.
Yang, Y, Xu, M, Wu, W, Zhang, R & Peng, Y 2018, '3D Multiview Basketball Players Detection and Localization Based on Probabilistic Occupancy', 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018, Digital Image Computing: Techniques and Applications, IEEE, Australia, pp. 267-274.
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© 2018 IEEE. This paper addresses the issue of 3D multiview basketball players detection and localization. Existing methods for this problem typically take background subtraction as input, which limits the accuracy of localization and the performance of further object tracking. Moreover, the performance of background subtraction based methods is heavily impacted by the occlusions in crowded scenes. In this paper, we propose an innovative method which jointly implements deep learning based player detection and occupancy probability based player localization. What's more, a new Bayesian model of the localization algorithms is developed, which uses foreground information from fisheye cameras to setup meaningful initialization values in the first step of iteration, in order to not only eliminate ambiguous detection, but also accelerate computational processes. Experimental results on real basketball game data demonstrate that our methods significantly improve the performance compared with current methods, by eliminating missed and false detection, as well as increasing probabilities of positive results.
Yao, L, Kusakunniran, W, Wu, Q, Zhang, J & Tang, Z 2018, 'Robust CNN-based Gait Verification and Identification using Skeleton Gait Energy Image', 2018 Digital Image Computing: Techniques and Applications (DICTA), Digital Image Computing: Techniques and Applications, IEEE, Canberra, Australia.
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Ye, P, Wang, Y, Xia, Y, An, P & Zhang, J 2019, 'Enhanced saliency prediction via free energy principle', Communications in Computer and Information Science, pp. 31-44.
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© Springer Nature Singapore Pte Ltd 2019. Saliency prediction can be treated as the activity of human brain. Most saliency prediction methods employ features to determine the contrast of an image area relative to its surroundings. However, only few studies have investigated how human brain activities affect saliency prediction. In this paper, we propose an enhanced saliency prediction model via free energy principle. A new AR-RTV model, which combines the relative total variation (RTV) structure extractor with autoregressive (AR) operator, is firstly utilized to decompose an original image into the predictable component and the surprise component. Then, we adopt the local entropy of ‘surprise’ map and the gradient magnitude (GM) map to estimate the component saliency maps-sub-saliency respectively. Finally, inspired by visual error sensitivity, a saliency augment operator is designed to enhance the final saliency combined two sub-saliency maps. Experimental results on two benchmark databases demonstrate the superior performance of the proposed method compared to eleven state-of-the-art algorithms.
Zhang, H, Huang, X, Zhang, JA, Jay Guo, Y, Song, RL, Wang, CT, Wu, W, Xu, XF & Lu, Z 2019, 'A high-speed low-cost millimeter wave system with dual pulse shaping transmission and symbol rate equalization techniques', Proceedings - IEEE International Symposium on Circuits and Systems, IEEE International Symposium on Circuits and Systems, Sapporo, Japan.
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© 2019 IEEE A millimeter wave system with commercially available and affordable data conversion devices is presented in this paper for achieving high-speed and low-cost wireless communications. By adopting the proposed dual pulse shaping (DPS) transmission scheme, the system can achieve full Nyquist rate transmission with only half of the sampling rate required by conventional Nyquist pulse shaping. Structures of the DPS transmitter and receiver are described and effective symbol rate equalization techniques suitable for DPS transmission are presented. Simulation results with two sets of practical dual spectral shaping pulses are also provided to compare system performance with the conventional Nyquist pulse shaping system.
Zhang, L, Xu, J, Zhang, J & Gong, Y 2018, 'Information Enhancement for Travelogues via a Hybrid Clustering Model', Digital Image Computing: Techniques and Applications, IEEE, Canberra, ACT, Australia, pp. 1-8.
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Zhang, T, Gong, C, Jia, W, Song, X, Sun, J & Wu, X 2019, 'Supervised image classification with self-paced regularization', IEEE International Conference on Data Mining Workshops, ICDMW, pp. 411-414.
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© 2018 IEEE. In this paper, we present a new scheme for image classification that is robust to samples noises. The proposed scheme depicts a novel sparse classification model with self-paced learning mechanism. First, inspired by the outstanding performance of curriculum learning, we integrate the idea of self-paced learning into supervised class-specific dictionary learning to select appropriate training samples. Secondly, we design a novel sparse representation model associated with self-paced learning regularization, which employs locally linear reconstruction to improve the accuracy of the classifier and exploit the manifold structure of data. By using the designed model, a classification scheme integrating self-paced learning is proposed to exploit more discriminative image information. The experimental results on two typical datasets indicate that our constructed model achieves the competitive performance when compared with the state-of-the-art methods.
Zhang, Z, Wu, Q, Wang, Y & Chen, F 2018, 'Size-Invariant Attention Accuracy Metric for Image Captioning with High-Resolution Residual Attention', 2018 Digital Image Computing: Techniques and Applications (DICTA), Digital Image Computing: Techniques and Applications, IEEE, Canberra, Australia.
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Zhu, H & Jay Guo, Y 2018, 'Modified wideband tandem couplers with arbitrary coupling coefficient and its implementation in beam-forming networks', Asia-Pacific Microwave Conference Proceedings, APMC, Asia-Pacific Microwave Conference, Kyoto, Japan, pp. 542-544.
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© 2018 IEICE This paper presents a wideband quadrature coupler using a modified Tandem structure with two stages of cascaded coupled-lines. The proposed design is built in the stripline configuration, which can achieve wide operating bandwidth and excellent matching as well as high isolation across the whole band range. The proposed design with coupling coefficient of 3-dB and 1.77-dB is applied in the design of a wideband beam-forming network for wideband applications. Experimental result has been carried out, verifying that the design approach is useful for wideband applications.
Zhu, H, Cao, Y, Ding, C, Wei, G & Guo, YJ 2018, 'Main Beam Manipulation of Patch Antenna Using Non-Uniform Meta-Surface', International Symposium on Antennas and Propagation (ISAP), 2018 International Symposium on Antennas and Propagation (ISAP), Busan, South Korea.
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Zhu, H, Lin, JY & Guo, YJ 2019, 'Wideband Filtering Out-of-Phase Power Dividers Using Slotline Resonators and Microstrip-to-Slotline Transitions', IEEE MTT-S International Microwave Symposium Digest, pp. 919-922.
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© 2019 IEEE. Two wideband filtering out-of-phase power dividers are designed and analyzed. The initial design is composed of a quarter-wavelength slotline resonator and two microstrip-to-slotline transitions. Three transmission poles are produced to form the passband. Excellent matching and isolation are achieved using extra matching network. Based on the initial design, a pair of stepped-impedance open stubs are shunted at the output ports to improve the passband selectivity. The designs have been verified through experiment. The tested results show that the proposed devices have achieved 60% operating bandwidth, 1.8 dB insertion loss, 1.2° phase error and excellent in-band matching and isolation.
Zhu, H, Sun, H, Ding, C & Guo, YJ 2019, 'Butler Matrix Based Multi-Beam Base Station Antenna Array', 13th European Conference on Antennas and Propagation, EuCAP 2019.
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© 2019 European Association on Antennas and Propagation. In this paper, a three-beam Butler matrix as well as its antenna arrays is presented for cellular base stations. The three-beam Butler matrix is able to generate three beams in the azimuth plane, which can increase the capacity of base stations. Striplines are used for developing the 3 and times; 3 Butler matrix, which is compose of directional couplers and phase shifters. To extend the 3 and times; 3 Butler matrix to a 3 and times; 5 one, unequal power dividers are also require. To verify the beam-forming network, 5-element dual-polarized antenna arrays covering LTE band are developed. Multiple beams are obtained by feeding the antenna array with the augmented 3 and times; 5 Butler matrix. The design is verified by both simulation and experiments.
Zhu, H, Zhu, X, Yang, Y, Sun, Y, Le, VH & Zhang, F 2019, 'Design of miniaturized on-chip bandpass filters using inverting-coupled structure for millimter-wave applications', Proceedings - IEEE International Symposium on Circuits and Systems.
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© 2019 IEEE In this work, a new type of miniaturized on-chip resonator using an inductively-coupled structure is presented. The resonator is constructed by two spiral conductors that are implemented using two different metal layers. Since the two conductors are identical but placed in different rotating pattern, a kind of inductive coupling called inverting coupling will be introduced in addition to the broadside capacitive coupling. To fully understand the working mechanism of the resonator, simplified LC equivalent-circuit models and thorough analysis are provided. To further demonstrate the feasibility of the proposed miniaturized resonator in practice, two bandpass filters, namely a 1st-order and 2nd-order, are designed and fabricated in a standard 0.13-µm (Bi)-CMOS technology. Good agreements between simulation and measurement have obtained, which verify that the presented design approach is suitable for miniaturized on-chip passive design.
Zhu, J, Chu, C, Deng, L, Yang, Y & Li, S 2019, 'Mm-wave high gain substrate integrated cavity excited patch antenna array', Asia-Pacific Microwave Conference Proceedings, APMC, pp. 591-593.
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© 2018 IEICE A wideband and high gain cavity-backed 4x4 patch antenna array is proposed in this paper. Each patch antenna element of the array is enclosed by a rectangular cavity and differentially-fed by the slot underneath. Taking advantages of the higher-order substrate integrated cavity excitation, the elements of the array are efficiently fed with the same amplitude and phase in a simplified feeding mechanism instead of the conventional bulky and lossy power-splitter-based feeding network. Measured results show the antenna bandwidth is from 56 to 63.1-GHz (16.1%) with the peak gain reaching 21.4 dBi. The radiation patterns of the array are very stable over the entire frequency band and the cross-polarizations are as low as -30 dB. These good characteristics demonstrate that the proposed array can be a good candidate for the future 60-GHz communication system applications.
Ziolkowski, RW 2018, 'Metamaterial-inspired Electrically Small Platforms: Enhanced Directivity Properties', 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings, IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, Boston, MA, USA, pp. 873-874.
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© 2018 IEEE. A variety of near-field resonant parasitic (NFRP) antennas have been developed as electrically small platforms to realize high directivity. These include compact arrays and Huygens dipole and multipole radiating systems. A brief review of these developments and their scattering equivalents will be presented.