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Journal articles

Awwad, S. & Piccardi, M. 2017, 'Prototype-based budget maintenance for tracking in depth videos', Multimedia Tools and Applications, pp. 1-16.
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© 2016 Springer Science+Business Media New YorkThe use of conventional video tracking based on color or gray-level videos often raises concerns about the privacy of the tracked targets. To alleviate this issue, this paper presents a novel tracker that operates solely from depth data. The proposed tracker is designed as an extension of the popular Struck algorithm which leverages the effective framework of structural SVM. The main contributions of our paper are: i) a dedicated depth feature based on local depth patterns, ii) a heuristic for handling view occlusions in depth frames, and iii) a technique for keeping the number of the support vectors within a given “budget” so as to limit computational costs. Experimental results over the challenging Princeton Tracking Benchmark (PTB) dataset report a remarkable accuracy compared to the original Struck tracker and other state-of-the-art trackers using depth and RGB data.

Chen, H., zhang, G., ZHU, D. & lu, J. 2017, 'Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014', Technological Forecasting and Social Change, vol. 119, no. June 2017, pp. 39-52.
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Chen, S.-.L., Wei, F., Qin, P.-.Y., Guo, Y.J. & Chen, X. 2017, 'A Multi-linear Polarization Reconfigurable Unidirectional Patch Antenna', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Chen, X., Qin, P.Y., Guo, Y.J. & Fu, G. 2017, 'Low-profile and wide-beamwidth dual-polarized distributed microstrip antenna', IEEE Access, vol. 5, pp. 2272-2280.
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© 2013 IEEE. A low-profile and wide-beamwidth dual-polarized distributed microstrip antenna is presented in this paper. Four isolated micro patches are proposed as the radiation components and are excited by a compact differential-fed network. The micro patches in two diagonals determine the operating frequency bands of the two polarizations, respectively. By increasing the distances between the micro patches, the beamwidth in E plane can be broadened. Shorting poles between the patches and the ground plane are used to achieve good impedance matching. Compact dual-polarized differential-fed networks are also studied and compared with achieve the best antenna performance. To validate the proposed method, a wide-beamwith dual-polarized distributed microstrip antenna, whose dual polarizations operate at 2 and 2.2 GHz, respectively, is manufactured and measured. The external dimensions of the antenna is 70mm × 10 mm (0.49λ × 0.07λ ). The experimental results agree well with the simulated ones. The 3dB beamwidths in E planes reach 116° and 115°, and the gains are 5.15 and 5.5 dB for two polarizations, respectively. Meanwhile, the cross polarizations are less than -26.2 and -27.8 dB. In addition, the impedance bandwidths of 9.2% and 9.9% for VSWR leq 2 are achieved, and the port isolation is greater than 25.4 dB in the bands.

Chen, Y., Yue, X., Xu, R.Y.D. & Fujita, H. 2017, 'Region scalable active contour model with global constraint', Knowledge-Based Systems, vol. 120, pp. 57-73.
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© 2016Existing Active Contour methods suffer from the deficiencies of initialization sensitivity, slow convergence, and being insufficient in the presence of image noise and inhomogeneity. To address these problems, this paper proposes a region scalable active contour model with global constraint (RSGC). The energy function is formulated by incorporating local and global constraints. The local constraint is a region scalable fitting term that draws upon local region information under controllable scales. The global constraint is constructed through estimating the global intensity distribution of image content. Specifically, the global intensity distribution is approximated with a Gaussian Mixture Model (GMM) and estimated by Expectation Maximization (EM) algorithm as a prior. The segmentation process is implemented through optimizing the improved energy function. Comparing with two other representative models, i.e. region-scalable fitting model (RSF) and active contour model without edges (CV), the proposed RSGC model achieves more efficient, stable and precise results on most testing images under the joint actions of local and global constraints.

Chomsiri, T., He, X.S., Nanda, P. & Tan, Z. 2017, 'Hybrid Tree-rule Firewall for High Speed Data Transmission', IEEE Transactions on Cloud Computing.
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Cooper, C., Franklin, D., Ros, M., Safaei, F. & Abolhasan, M. 2017, 'A Comparative Survey of VANET Clustering Techniques', IEEE Communications Surveys Tutorials, vol. 19, no. 1, pp. 657-681.
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A vehicular ad hoc network (VANET) is a mobile ad hoc network (MANET) in which network nodes are vehicles – most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organised nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, inforomation dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming – the lack of realistic vehicular channel modelling – is identified. The importance of a rigorous and standardised performance evaluation regime utilising realistic vehicular channel models is demonstrated.

Dai, M., Cheng, S. & He, X.S. 2017, 'Hybrid generative–discriminative hash tracking with spatio-temporal contextual cues', Neural Computing and Applications.
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Visual object tracking is of a great application value in video monitoring systems. Recent work on video tracking has taken into account spatial relationship between the targeted object and its background. In this paper, the spatial relationship is combined with the temporal relationship between features on different video frames so that a real-time tracker is designed based on a hash algorithm with spatio-temporal cues. Different from most of the existing work on video tracking, which is regarded as a mechanism for image matching or image classification alone, we propose a hierarchical framework and conduct both matching and classification tasks to generate a coarse-to-fine tracking system. We develop a generative model under a modified particle filter with hash fingerprints for the coarse matching by the maximum a posteriori and a discriminative model for the fine classification by maximizing a confidence map based on a context model. The confidence map reveals the spatio-temporal dynamics of the target. Because hash fingerprint is merely a binary vector and the modified particle filter uses only a small number of particles, our tracker has a low computation cost. By conducting experiments on eight challenging video sequences from a public benchmark, we demonstrate that our tracker outperforms eight state-of-the-art trackers in terms of both accuracy and speed.

Du, J., Pegrum, C.M., Gao, X., Weily, A.R., Zhang, T., Guo, Y.J. & Foley, C.P. 2017, 'Harmonic Mixing Using a HTS Step-Edge Josephson Junction at 0.6 THz Frequency', IEEE Transactions on Applied Superconductivity, vol. 27, no. 4.
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© 2002-2011 IEEE. A high-temperature superconducting (HTS) terahertz (THz) heterodyne mixer based on a thin-film antenna-coupled YBa 2 Cu 3 O 7- x step-edge Josephson junction is presented. The frequency down-conversion from 0.6 THz to an intermediate frequency (IF) of 2 GHz was achieved using high-order harmonic mixing of a local oscillator (LO), thus removing the need to use a second THz source as the LO pumping source. The DC and RF characteristics of the harmonic mixer as well as the relationship of the IF output power versus the harmonic number were experimentally studied and compared with simulated results. Most of our measurements were made at 40 K, but we also observed stable harmonic mixing at 77 K which we believe has not been reported previously in HTS junction mixers.

Du, J., Weily, A.R., Gao, X., Zhang, T., Foley, C.P. & Guo, Y.J. 2017, 'HTS step-edge Josephson junction terahertz harmonic mixer', Superconductor Science and Technology, vol. 30, no. 2.
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© 2016 Federal Australian Crown copyright. A high-temperature superconducting (HTS) terahertz (THz) frequency down-converter or mixer based on a thin-film ring-slot antenna coupled YBa 2 Cu 3 O 7-x (YBCO)/MgO step-edge Josephson junction is reported. The frequency down-conversion was achieved using higher order harmonics of an applied lower frequency (19-40 GHz) local oscillator signal in the Josephson junction mixing with a THz signal of over 600 GHz, producing a 1-3 GHz intermediate frequency signal. Up to 31st order of harmonic mixing was obtained and the mixer operated stably at temperatures up to 77 K. The design details of the antenna, HTS Josephson junction mixer, the matching and isolation circuits, and the DC and RF performance evaluation are described in this paper.

Edwards, D., Cheng, M., Wong, A., Zhang, J. & Wu, Q. 2017, 'Ambassadors of Knowledge Sharing: Co-produced Travel Information Through Tourist-Local Social Media Exchange', International Journal of Contemporary Hospitality Management, vol. 29, no. 2, pp. 690-708.
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Purpose: The aim of this study is to understand the knowledge sharing structure and co-production of trip-related knowledge through online travel forums. Design/methodology/approach: The travel forum threads were collected from TripAdvisor Sydney travel forum for the period from 2010 to 2014, which contains 115,847 threads from 8,346 conversations. The data analytical technique was based on a novel methodological approach - visual analytics including semantic pattern generation and network analysis. Findings: Findings indicate that the knowledge structure is created by community residents who camouflage as local experts, serve as ambassadors of a destination. The knowledge structure presents collective intelligence co-produced by community residents and tourists. Further findings reveal how these community residents associate with each other and form a knowledge repertoire with information covering various travel domain areas. Practical implications: The study offers valuable insights to help destination management organizations and tour operators identify existing and emerging tourism issues to achieve a competitive destination advantage. Originality/value: This study highlights the process of social media mediated travel knowledge co-production. It also discovers how community residents engage in reaching out to tourists by camouflaging as ordinary users.

Fan, X., Xu, R.Y.D., Cao, L. & Song, Y. 2017, 'Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network', IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 589-599.
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Relational model learning is useful for numerous practical applications. Many algorithms have been proposed in recent years to tackle this important yet challenging problem. Existing algorithms utilize only binary directional link data to recover hidden network structures. However, there exists far richer and more meaningful information in other parts of a network which one can (and should) exploit. The attributes associated with each node, for instance, contain crucial information to help practitioners understand the underlying relationships in a network. For this reason, in this paper, we propose two models and their solutions, namely the node-information involved mixed-membership model and the node-information involved latent-feature model, in an effort to systematically incorporate additional node information. To effectively achieve this aim, node information is used to generate individual sticks of a stick-breaking process. In this way, not only can we avoid the need to prespecify the number of communities beforehand, the algorithm also encourages that nodes exhibiting similar information have a higher chance of assigning the same community membership. Substantial efforts have been made toward achieving the appropriateness and efficiency of these models, including the use of conjugate priors. We evaluate our framework and its inference algorithms using real-world data sets, which show the generality and effectiveness of our models in capturing implicit network structures.

Feng, X.I.A.N.G., Wan, W., Richard Yi Da Xu, Chen, H., Li, P. & Sánchez, J.A. 2017, 'A perceptual quality metric for 3D triangle meshes based on spatial pooling', Frontiers of Computer Science.
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Fontugne, R., Abry, P., Fukuda, K., Veitch, D., Cho, K., Borgnat, P. & Wendt, H. 2017, 'Scaling in Internet Traffic: A 14 Year and 3 Day Longitudinal Study, With Multiscale Analyses and Random Projections', IEEE/ACM Transactions on Networking, pp. 1-14.
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Gill, A.Q., Henderson-Sellers, B. & Niazi, M. 2017, 'Scaling for agility: A reference model for hybrid traditional-agile software development methodologies', Information Systems Frontiers: a journal of research and innovation, pp. 1-27.
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Guo, D., Xu, J., Zhang, J., Xu, M., Cui, Y. & He, X. 2017, 'User relationship strength modeling for friend recommendation on Instagram', Neurocomputing, vol. 239, pp. 9-18.
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© 2017 Elsevier B.V.Social strength modeling in the social media community has attracted increasing research interest. Different from Flickr, which has been explored by many researchers, Instagram is more popular for mobile users and is conducive to likes and comments but seldom investigated. On Instagram, a user can post photos/videos, follow other users, comment and like other users' posts. These actions generate diverse forms of data that result in multiple user relationship views. In this paper, we propose a new framework to discover the underlying social relationship strength. User relationship learning under multiple views and the relationship strength modeling are coupled into one process framework. In addition, given the learned relationship strength, a coarse-to-fine method is proposed for friend recommendation. Experiments on friend recommendations for Instagram are presented to show the effectiveness and efficiency of the proposed framework. As exhibited by our experimental results, it can obtain better performance over other related methods. Although our method has been proposed for Instagram, it can be easily extended to any other social media communities.

Hosoe, S., Tuan, H.D. & Nguyen, T.N. 2017, '2D Bilinear programming for robust PID/DD controller design', International Journal of Robust and Nonlinear Control, vol. 27, no. 3, pp. 461-482.
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© 2016 John Wiley & Sons, Ltd.A new design method of PID structured controllers to achieve robust performance is developed. Both robust stabilization and performance conditions are losslessly expressed by bilinear constraints in the proportional-double derivative variable (kP,kDD) and the integral-derivative variable (kI,kD). Therefore, the considered control design can be efficiently solved by alternating optimization between (kP,kDD) and (kI,kD), which is a 2D computationally tractable program. The proposed method works equally efficiently whenever even higher order differential or integral terms are included in PID control to improve its robustness and performance. Numerical examples are provided to show the viability of the proposed development.

Huang, J., Qiu, F., Lin, W., Tang, Z., Lei, D., Yao, M., Chu, Q. & Guo, Y.J. 2017, 'A New Compact and High Gain Circularly-Polarized Slot Antenna Array for Ku Band Mobile Satellite TV Reception', IEEE Access, vol. 5, pp. 6707-6714.
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Huang, S., Zhang, J., Schonfeld, D., Wang, L. & Hua, X.-.S. 2017, 'Two-Stage Friend Recommendation Based on Network Alignment and Series Expansion of Probabilistic Topic Model', IEEE Transactions on Multimedia, vol. 19, no. 6, pp. 1314-1326.
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Huang, T., Huang, M.L., Nguyen, Q., Zhao, L., Huang, W. & Chen, J. 2017, 'A Space-Filling Multidimensional Visualization (SFMDVis) for Exploratory Data Analysis', Information Sciences, vol. 390, pp. 32-53.
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The space-filling visualization model was first invented by Ben Shneiderman [28] for maximizing the utilization of display space in relational data (or graph) visualization, especially for tree visualization. It uses the concept of Enclosure which dismisses the “edges” in the graphic representation that are all too frequently used in traditional node-link based graph visualizations. Therefore, the major issue in graph visualization which is the edge crossing can be naturally solved through the adoption of a space filling approach. However in the past, the space-filling concept has not attracted much attention from researchers in the field of multidimensional visualization. Although the problem of ‘edge crossing’ has also occurred among polylines which are used as the basic visual elements in the parallel coordinates visualization, it is problematic if those ‘edge crossings’ among polylines are not evenly distributed on the display plate as visual clutter will occur. This problem could significantly reduce the human readability in terms of reviewing a particular region of the visualization. In this study, we propose a new Space-Filling Multidimensional Data Visualization (SFMDVis) that for the first-time introduces a space-filling approach into multidimensional data visualization. The main contributions are: (1) achieving the maximization of space utilization in multidimensional visualization (i.e. 100% of the display area is fully used), (2) eliminating visual clutter in SFMDVis through the use of the non-classic geometric primitive and (3) improving the quality of visualization for the visual perception of linear correlations among different variables as well as recognizing data patterns. To evaluate the quality of SFMDVis, we have conducted a usability study to measure the performance of SFMDVis in comparison with parallel coordinates and a scatterplot matrix for finding linear correlations and data patterns. The evaluation results have suggested that the acc...

Huang, X. & Guo, Y.J. 2017, 'Radio Frequency Self-Interference Cancellation With Analog Least Mean-Square Loop', IEEE Transactions on Microwave Theory and Techniques, pp. 1-15.
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Huang, X., Zhang, J., Fan, L., Wu, Q. & Yuan, C. 2017, 'A systematic approach for cross-source point cloud registration by preserving macro and micro structures', IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3261-3276.
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© 2016 IEEE. We propose a systematic approach for registering cross-source point clouds that come from different kinds of sensors. This task is especially challenging due to the presence of significant missing data, large variations in point density, scale difference, large proportion of noise, and outliers. The robustness of the method is attributed to the extraction of macro and micro structures. Macro structure is the overall structure that maintains similar geometric layout in cross-source point clouds. Micro structure is the element (e.g., local segment) being used to build the macro structure. We use graph to organize these structures and convert the registration into graph matching. With a novel proposed descriptor, we conduct the graph matching in a discriminative feature space. The graph matching problem is solved by an improved graph matching solution, which considers global geometrical constraints. Robust cross source registration results are obtained by incorporating graph matching outcome with RANSAC and ICP refinements. Compared with eight state-of-the-art registration algorithms, the proposed method invariably outperforms on Pisa Cathedral and other challenging cases. In order to compare quantitatively, we propose two challenging cross-source data sets and conduct comparative experiments on more than 27 cases, and the results show we obtain much better performance than other methods. The proposed method also shows high accuracy in same-source data sets.

Jan, M., Nanda, P., Usman, M. & He, X. 2017, 'PAWN: A Payload-based mutual Authentication scheme for Wireless Sensor Networks', Concurrency and Computation: Practice and Experience.
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Jan, M.A., Nanda, He, X.S. & Liu, R.P. 2017, 'A Sybil Attack Detection Scheme for a Forest Wildfire Monitoring Application', Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications.
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Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter, etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user’s specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to a wildfire. Our proposed approach has better network lifetime due to efficient sleep–awake scheduling, higher detection rate and low false-negative rate.

Jia, Y., Liu, Y., Guo, Y.J., Li, K. & Gong, S. 2017, 'A dual-patch polarization rotation reflective surface and its application to ultra-wideband RCS reduction', IEEE Transactions on Antennas and Propagation, vol. 65, no. 6, pp. 3291-3295.
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© 2017 IEEE. An ultra-wideband polarization rotation reflective surface (PRRS) with a high polarization conversion ratio (PCR) is proposed, which can reflect a linearly polarized incident wave with 90° polarization rotation. The unit cell of the proposed PRRS consists of a square and L-shaped patches printed on a substrate, which is covered by a superstrate and backed by a metallic ground. The two patches are connected to the ground using two metallic vias, respectively. Compared with the previously reported PRRS, the polarization rotation bandwidth of the proposed PRRS is enhanced from 49% to 97% with a high PCR of 96%. The frequency responses within the operation frequency band are consistent under oblique incident waves. Furthermore, the designed PRRS is applied to the ultra-wideband radar cross-section (RCS) reduction by forming a checkerboard surface. A 10-dB RCS reduction is achieved over an ultrawideband of 98%. To validate the simulation results, a prototype of the checkerboard surface is fabricated and measured. A good agreement between the experimental and simulation results is obtained.

Karmokar, D., Guo, Y., Qin, P.-.Y., Esselle, K. & Bird, T. 2017, 'Forward and Backward Beam Scanning Tri-Band Leaky-Wave Antenna', IEEE Antennas and Wireless Propagation Letters, pp. 1-1.
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Kaur, P., Goyal, M. & Lu, J. 2017, 'A Comparison of Bidding Strategies for Online Auctions Using Fuzzy Reasoning and Negotiation Decision Functions', IEEE Transactions on Fuzzy Systems, vol. 25, no. 2, pp. 425-438.
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© 1993-2012 IEEE. Bidders often feel challenged when looking for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. Bidders face complicated issues for deciding which auction to participate in, whether to bid early or late, and how much to bid. In this paper, we present the design of bidding strategies, which aim to forecast the bid amounts for buyers at a particular moment in time based on their bidding behavior and their valuation of an auctioned item. The agent develops a comprehensive methodology for final price estimation, which designs bidding strategies to address buyers' different bidding behaviors using two approaches: Mamdani method with regression analysis and negotiation decision functions. The experimental results show that the agents who follow fuzzy reasoning with a regression approach outperform other existing agents in most settings in terms of their success rate and expected utility.

Li, B., Sutton, G.J., Hu, B., Liu, R.P. & Chen, S. 2017, 'Modeling and QoS analysis of the IEEE 802.11p broadcast scheme in vehicular ad hoc networks', Journal of Communications and Networks, vol. 19, no. 2, pp. 169-179.
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© 2011 KICS. Quality of service (QoS) and queue management are critical issues for the broadcast scheme of IEEE 802.11p systems in vehicular ad hoc networks (VANETs). However, existing 1-dimensional (1-D) Markov chain models of 802.11p systems are unable to capture the complete QoS performance and queuing behavior due to the lack of an adequate finite buffer model. We present a 2-dimensional (2-D) Markov chain that integrates the broadcast scheme of the 802.11p system and the queuing process into one model. The extra dimension, which models the queue length, allows us to accurately capture the important QoS measures, delay and loss, plus throughput and queue length, for realistic 802.11p systems with finite buffer under finite load. We derive a simplified method to solve the steady state probabilities of the 2-D Markov chain. Our 2-D Markov chain model is the first finite buffer model defined and solved for the broadcast scheme of 802.11p systems. The 2-D model solutions are validated by extensive simulations. Our analyses reveal that the lack of binary exponential backoff and retransmission in the 802.11p system results in poor QoS performance during heavy traffic load, particularly for large VANETs. We demonstrate that our model provides traffic control guidelines to maintain good QoS performance for VANETs.

Li, J., Deng, C., Xu, R.Y.D., Tao, D. & Zhao, B. 2017, 'Robust Object Tracking with Discrete Graph-Based Multiple Experts', IEEE Transactions on Image Processing, vol. 26, no. 6, pp. 2736-2750.
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© 1992-2012 IEEE. Variations of target appearances due to illumination changes, heavy occlusions, and target deformations are the major factors for tracking drift. In this paper, we show that the tracking drift can be effectively corrected by exploiting the relationship between the current tracker and its historical tracker snapshots. Here, a multi-expert framework is established by the current tracker and its historical trained tracker snapshots. The proposed scheme is formulated into a unified discrete graph optimization framework, whose nodes are modeled by the hypotheses of the multiple experts. Furthermore, an exact solution of the discrete graph exists giving the object state estimation at each time step. With the unary and binary compatibility graph scores defined properly, the proposed framework corrects the tracker drift via selecting the best expert hypothesis, which implicitly analyzes the recent performance of the multi-expert by only evaluating graph scores at the current frame. Three base trackers are integrated into the proposed framework to validate its effectiveness. We first integrate the online SVM on a budget algorithm into the framework with significant improvement. Then, the regression correlation filters with hand-crafted features and deep convolutional neural network features are introduced, respectively, to further boost the tracking performance. The proposed three trackers are extensively evaluated on three data sets: TB-50, TB-100, and VOT2015. The experimental results demonstrate the excellent performance of the proposed approaches against the state-of-the-art methods.

Li, J., Meng, Z., Huang, M. & Zhang, K. 2017, 'An interactive visualization approach to the overview of geoscience data', Journal of Visualization, vol. 20, no. 3, pp. 433-451.
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Geoscience observation data refer to the datasets consisting of time series of multiple parameters generated from the sensors at fixed locations. Although a few works have attempted to visualize such data, none of them views these data as a specific type and attempts to show the overview in all the space, time and attribute aspects. It is important for domain experts to select the subsets of interest from huge amounts of observation data according to the high level patterns shown in the overview. We present a novel approach to visualize geoscience observation data in a compact radial view. Our solution consists of three visual elements. A map showing the spatial aspect is in the center of the visualization, while temporal and attribute aspects are seamlessly combined with the spatial information. Our approach is equipped with interactive mechanisms for highlighting the selected features, adjusting the display range, as well as interactively generating a fisheye view. We demonstrate the usability of our approach with three case studies of different domains. Eye tracking records and user feedbacks obtained in a small experiment also prove the effectiveness of our approach.

Li, K., Liu, Y., Jia, Y. & Guo, Y.J. 2017, 'A High Gain and Wideband Low RCS Circularly Polarized Antenna Using Chessboard Polarization Conversion Metasurfaces', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Liu, F., Gong, C., Zhou, T., Fu, K., He, X.S. & Yang, J. 2017, 'Visual Tracking via Nonnegative Multiple Coding', IEEE Transactions on Multimedia.
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It has been extensively observed that an accurate appearance model is critical to achieving satisfactory performance for robust object tracking. Most existing top-ranked methods rely on linear representation over a single dictionary, which brings about improper understanding on the target appearance. To address this problem, in this paper, we propose a novel appearance model named as “Nonnegative Multiple Coding” (NMC) to accurately represent a target. First, a series of local dictionaries are created with different pre-defined numbers of nearest neighbors, and then the contributions of these dictionaries are automatically learned. As a result, this ensemble of dictionaries can comprehensively exploit the appearance information carried by all the constituted dictionaries. Second, the existing methods explicitly impose the nonnegative constraint to coefficient vectors, but in the proposed model, we directly deploy an efficient `2 norm regularization to achieve the similar nonnegative purpose with theoretical guarantees. Moreover, an efficient occlusion detection scheme is designed to alleviate tracking drifts, and it investigates whether negative templates are selected to represent the severely occluded target. Experimental results on two benchmarks demonstrate that our NMC tracker is able to achieve superior performance to state-of-the-art methods.

Liu, W., Chen, X., Yang, J. & Wu, Q. 2017, 'Robust Color Guided Depth Map Restoration', IEEE Transactions on Image Processing, vol. 26, no. 1, pp. 315-327.
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One of the most challenging issues in color guided depth map restoration is the inconsistency between color edges in guidance color images and depth discontinuities on depth maps. This makes the restored depth map suffer from texture copy artifacts and blurring depth discontinuities. To handle this problem, most state-of-the-art methods design complex guidance weight based on guidance color images and heuristically make use of the bicubic interpolation of the input depth map. In this paper, we show that using bicubic interpolated depth map can blur depth discontinuities when the upsampling factor is large and the input depth map contains large holes and heavy noise. In contrast, we propose a robust optimization framework for color guided depth map restoration. By adopting a robust penalty function to model the smoothness term of our model, we show that the proposed method is robust against the inconsistency between color edges and depth discontinuities even when we use simple guidance weight. To the best of our knowledge, we are the first to solve this problem with a principled mathematical formulation rather than previous heuristic weighting schemes. The proposed robust method performs well in suppressing texture copy artifacts. Moreover, it can better preserve sharp depth discontinuities than previous heuristic weighting schemes. Through comprehensive experiments on both simulated data and real data, we show promising performance of the proposed method

Liu, W., Chen, X., Yang, J. & Wu, Q. 2017, 'Variable Bandwidth Weighting for Texture Copy Artifacts Suppression in Guided Depth Upsampling', IEEE Transactions on Circuits and Systems for Video Technology.
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Lu, J., Xuan, J., Zhang, G., Xu, Y.D. & Luo, X. 2017, 'Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 7, pp. 1357-1369.
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Traditional relational topic models provide a successful way to discover the hidden topics from a document network. Many theoretical and practical tasks, such as dimensional reduction, document clustering, and link prediction, could benefit from this revealed knowledge. However, existing relational topic models are based on an assumption that the number of hidden topics is known a priori, which is impractical in many real-world applications. Therefore, in order to relax this assumption, we propose a nonparametric relational topic model using stochastic processes instead of fixed-dimensional probability distributions in this paper. Specifically, each document is assigned a Gamma process, which represents the topic interest of this document. Although this method provides an elegant solution, it brings additional challenges when mathematically modeling the inherent network structure of typical document network, i.e., two spatially closer documents tend to have more similar topics. Furthermore, we require that the topics are shared by all the documents. In order to resolve these challenges, we use a subsampling strategy to assign each document a different Gamma process from the global Gamma process, and the subsampling probabilities of documents are assigned with a Markov Random Field constraint that inherits the document network structure. Through the designed posterior inference algorithm, we can discover the hidden topics and its number simultaneously. Experimental results on both synthetic and real-world network datasets demonstrate the capabilities of learning the hidden topics and, more importantly, the number of topics.

Lv, L., Fan, S., Huang, M., Huang, W. & Yang, G. 2017, 'Golden Rectangle Treemap', Journal of Physics: Conference Series, vol. 787, no. 1, pp. 1-6.
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Treemaps, a visualization method of representing hierarchical data sets, are becoming more and more popular for its efficient and compact displays. Several algorithms have been proposed to create more useful display by controlling the aspect ratios of the rectangles that make up a treemap. In this paper, we introduce a new treemap algorithm, generating layout in which the rectangles are easier to select and hierarchy information is easier to obtain. This algorithm generates rectangles which approximate golden rectangles. To prove the effectiveness of our algorithm, at the end of this paper several analyses on golden rectangle treemap have been done on disk file system.

Mao, M., Lu, J., Zhang, G. & Zhang, J. 2017, 'Multirelational Social Recommendations via Multigraph Ranking', IEEE Transactions on Cybernetics, pp. 1-13.
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Recommender systems aim to identify relevant items for particular users in large-scale online applications. The historical rating data of users is a valuable input resource for many recommendation models such as collaborative filtering (CF), but these models are known to suffer from the rating sparsity problem when the users or items under consideration have insuf- ficient rating records. With the continued growth of online social networks, the increased user-to-user relationships are reported to be helpful and can alleviate the CF rating sparsity problem. Although researchers have developed a range of social networkbased recommender systems, there is no unified model to handle multirelational social networks. To address this challenge, this paper represents different user relationships in a multigraph and develops a multigraph ranking model to identify and recommend the nearest neighbors of particular users in high-order environments. We conduct empirical experiments on two real-world datasets: 1) Epinions and 2) Last.fm, and the comprehensive comparison with other approaches demonstrates that our model improves recommendation performance in terms of both recommendation coverage and accuracy, especially when the rating data are sparse.

Nasir, A.A., Tuan, H.D., Duong, T.Q. & Poor, H.V. 2017, 'Secrecy Rate Beamforming for Multicell Networks with Information and Energy Harvesting', IEEE Transactions on Signal Processing, vol. 65, no. 3, pp. 677-689.
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© 2016 IEEE. Considering a multicell network for the secure wireless information and power transfer, this paper studies the joint design of transmit beamformers at the base stations (BSs) and receive signal splitting ratios at the end users' equipment (UE). The primary concern in this work is the network internal security, where there may be a single multiantenna eavesdropper or there is a risk that any near user may accidentally eavesdrop on the received signal of any far user. The objective is to maximize the minimum secrecy user rate under BS transmit power and UE minimum harvested energy constraints. New path-following algorithms are proposed for computational solutions of these difficult nonconvex optimization problems. Each iteration involves one simple convex quadratic program. Numerical results confirm that the proposed algorithms converge quickly after few iterations having a low computational complexity.

Nasir, A.A., Tuan, H.D., Ngo, D.T., Duong, T.Q. & Vincent Poor, H. 2017, 'Beamforming Design for Wireless Information and Power Transfer Systems: Receive Power-Splitting Versus Transmit Time-Switching', IEEE Transactions on Communications, vol. 65, no. 2, pp. 876-889.
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© 1972-2012 IEEE. Information and energy can be transferred over the same radio-frequency channel. In the power-splitting (PS) mode, they are simultaneously transmitted using the same signal by the base station (BS) and later separated at the user (UE)'s receiver by a power splitter. In the time-switching (TS) mode, they are either transmitted separately in time by the BS or received separately in time by the UE. In this paper, the BS transmit beamformers are jointly designed with either the receive PS ratios or the transmit TS ratios in a multicell network that implements wireless information and power transfer (WIPT). Imposing UE-harvested energy constraints, the design objectives include: 1) maximizing the minimum UE rate under the BS transmit power constraint, and 2) minimizing the maximum BS transmit power under the UE data rate constraint. New iterative algorithms of low computational complexity are proposed to efficiently solve the formulated difficult nonconvex optimization problems, where each iteration either solves one simple convex quadratic program or one simple second-order-cone-program. Simulation results show that these algorithms converge quickly after only a few iterations. Notably, the transmit TS-based WIPT system is not only more easily implemented but outperforms the receive PS-based WIPT system as it better exploits the beamforming design at the transmitter side.

Nghia, N.T., Tuan, H.D., Duong, T.Q. & Poor, H.V. 2017, 'MIMO Beamforming for Secure and Energy-Efficient Wireless Communication', IEEE Signal Processing Letters, vol. 24, no. 2, pp. 236-239.
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© 1994-2012 IEEE. Considering a multiple-user multiple-input multiple-output channel with an eavesdropper, this letter develops a beamformer design to optimize the energy efficiency in terms of secrecy bits per Joule under secrecy quality-of-service constraints. This is a very difficult design problem with no available exact solution techniques. A path-following procedure, which iteratively improves its feasible points by using a simple quadratic program of moderate dimension, is proposed. Under any fixed computational tolerance, the procedure terminates after finitely many iterations, yielding at least a locally optimal solution. Simulation results show the superior performance of the obtained algorithm over other existing methods.

Ni, W., Abolhasan, M., Hagelstein, B., Liu, R.P. & Wang, X. 2017, 'A New Trellis Model for MAC Layer Cooperative Retransmission Protocols', IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3448-3461.
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Pham, T.T., Moore, S.T., Lewis, S.J.G., Nguyen, D.N., Dutkiewicz, E., Fuglevand, A.J., McEwan, A.L. & Leong, P.H.W. 2017, 'Freezing of Gait Detection in Parkinson’s Disease: A Subject-Independent Detector Using Anomaly Scores', IEEE Transactions on Biomedical Engineering.
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Pham, T.T., Nguyen, D.N., Dutkiewicz, E., McEwan, A.L. & Leong, P.H.W. 2017, 'An Anomaly Detection Technique in Wearable Wireless Monitoring Systems for Studies of Gait Freezing in Parkinson’s Disease', International Conference on Information Networking, vol. 17, pp. 41-45.
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Pratama, M., Lu, J., Lughofer, E., Zhang, G. & Er, M.J. 2017, 'Incremental Learning of Concept Drift Using Evolving Type-2 Recurrent Fuzzy Neural Network', IEEE Transactions on Fuzzy Systems, pp. 1-16.
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— the age of online data stream and dynamic environments result in the increasing demand of advanced machine learning techniques to deal with concept drifts in large data streams. Evolving Fuzzy Systems (EFS) are one of recent initiatives from the fuzzy system community to resolve the issue. Existing EFSs are not robust against data uncertainty, temporal system dynamics, and the absence of system order, because vast majority of EFSs are designed in the type-1 feed-forward network architecture. This paper aims to solve the issue of data uncertainty, temporal behaviour, and the absence of system order by developing a novel evolving recurrent fuzzy neural network, called Evolving Type-2 Recurrent Fuzzy Neural Network (eT2RFNN). eT2RFNN is constructed in a new recurrent network architecture, featuring double recurrent layers. The new recurrent network architecture evolves a generalized interval type-2 fuzzy rule, where the rule premise is built upon the interval type-2 multivariate Gaussian function, whereas the rule consequent is crafted by the non-linear wavelet function. The eT2RFNN adopts a holistic concept of evolving systems, where the fuzzy rule can be automatically generated, pruned, merged and recalled in the single pass learning mode. eT2RFNN is capable of coping with the problem of high dimensionality, because it is equipped with online feature selection technology. The efficacy of eT2RFNN was experimentally validated using artificial and real-world data streams and compared with prominent learning algorithms. eT2RFNN produced more reliable predictive accuracy, while retaining lower complexity than its counterparts.

Qin, C., Ni, W., Tian, H. & Liu, R.P. 2017, 'Joint Rate Maximization of Downlink and Uplink in Multiuser MIMO SWIPT Systems', IEEE Access, vol. 5, pp. 3750-3762.
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© 2013 IEEE. Beamforming has the potential to improve the efficiency of simultaneous wireless information and power transfer (SWIPT) systems. Existing beamforming techniques have been focused on the downlink of SWIPT systems. In this paper, we optimize the beamformers and transmit duration to maximize the weighted sum rate of both the downlink and uplink in a multiuser multiple-input multiple-output (MIMO) SWIPT system. Specifically, we formulate and transform the problem into a weighted sum mean square error minimization, conduct difference of convex programming to decouple the downlink and uplink, and convert the problem to quadratic programming (QP), which can be solved iteratively in a centralized fashion. We also decentralize the QP problem using dual decompositions, and reduce the time-complexity without compromising the data rate. Moreover, our algorithms are extended to the case under imperfect channel state information. Confirmed by simulations, the proposed decentralization can dramatically reduce the time-complexity by orders of magnitude. The scalability of the proposed approach can be substantially enhanced to support medium to large networks.

Qin, C., Ni, W., Tian, H., Liu, R.P. & Guo, Y.J. 2017, 'Joint Beamforming and User Selection in Multiuser Collaborative MIMO SWIPT Systems with Non-negligible Circuit Energy Consumption', IEEE Transactions on Vehicular Technology.
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IEEE Multi-antenna beamforming has potential to improve the efficiency of simultaneous wireless information and power transfer (SWIPT). Existing designs are focused on the downlink of multiple-input-single-output under the assumption of single-antenna users and negligible energy consumption in users' circuitry, despite the fact that using multiple antennas on the user side can further improve system efficiency. In this paper, novel multiuser collaborative multiple-input-multiple-output (MIMO) SWIPT systems are studied under the assumption of non-negligible circuit energy consumption. Particularly, we convexify and maximize the uplink sum rate of active users, while maintaining the quality of service (QoS) of their downlink data. The beamformers and durations of both links, and the power splitting factors of individual users are jointly optimized, using semidefinite programming and golden search. Further, the selection of active users is optimized, where all users are assumed to be active in the beginning and those detrimental to the sum-rate maximization are continually deactivated. Evident from simulations, the proposed approaches can eliminate the need for computationally prohibitive combinatorial integer programming at a marginal cost of the sum rate.

Ramezani, F., Lu, J., Taheri, J. & Zomaya, A.Y. 2017, 'A Multi-Objective Load Balancing System for Cloud Environments', The Computer Journal.
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Sheng, Z., Tuan, H.D., Tam, H.H.M., Nguyen, H.H. & Fang, Y. 2017, 'Energy-efficient precoding in multicell networks with full-duplex base stations', EURASIP Journal on Wireless Communications and Networking, vol. 48, pp. 1-13.
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© 2017, The Author(s). This paper considers multi-input multi-output (MIMO) multicell networks, where the base stations (BSs) are full-duplex transceivers, while uplink and downlink users are equipped with multiple antennas and operate in a half-duplex mode. The problem of interest is to design linear precoders for BSs and users to optimize the network’s energy efficiency. Given that the energy efficiency objective is not a ratio of concave and convex functions, the commonly used Dinkelbach-type algorithms are not applicable. We develop a low-complexity path-following algorithm that only invokes one simple convex quadratic program at each iteration, which converges at least to the local optimum. Numerical results demonstrate the performance advantage of our proposed algorithm in terms of energy efficiency.

Shi, S., Ni, W. & Liu, R.P. 2017, 'Performance analysis of XOR two-way relay with finite buffers and instant scheduling', IET Communications, vol. 11, no. 4, pp. 507-513.
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© The Institution of Engineering and Technology 2017. This study investigates the performance of practical wireless exclusive OR (XOR) two-way relay (TWR) system, in which finite buffer, lossy wireless channels and non-negligible signalling overhead are considered. Specifically, the authors develop a new analytical model to explicitly characterise the transmissions of both the end-nodes and the relay. The impact of scheduling on the throughput, queuing delay, power consumption and buffer overflow probability of XOR-TWR is evaluated. Validated by simulations, the model can precisely quantify the performance of XOR-TWR and adequately allocate the relay's buffer adapting to the wireless link qualities and signalling overhead.

Shi, Y., Tuan, H.D. & Apkarian, P. 2017, 'Nonconvex spectral optimization algorithms for reduced-order H∞ LPV-LFT controllers', International Journal of Robust and Nonlinear Control.
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© 2017 John Wiley & Sons, Ltd. A novel sequential semi-definite programming method is developed for optimization subject to rank constraints on matrix-valued nonlinear functions of matrix decision variables, which arise in reduced-order linear parameter varying-linear fractional transformational control synthesis. The global convergence of the method is easily proven without any step size control. An intensive simulation shows the clear advantage of the proposed method over the state-of-the-art nonlinear matrix inequality solvers.

Siyari, P., Krunz & Nguyen, D. 2017, 'Friendly Jamming in a MIMO Wiretap Interference Network: A Non-Convex Game Approach', IEEE Journal on Selected Areas in Communications, vol. PP, no. 99.
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Sutton, G.J., Liu, R. & Guo, Y.J. 2017, 'Harmonising Coexistence of Machine Type Communications with Wi-Fi Data Traffic under Frame-based LBT', IEEE Transactions on Communications, pp. 1-1.
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Tam, H.H.M., Tuan, H.D., Ngo, D.T., Duong, T.Q. & Poor, H.V. 2017, 'Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks with Limited Backhaul Capacity', IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 872-884.
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© 2016 IEEE. In this paper, new strategies are devised for joint load balancing and interference management in the downlink of a heterogeneous network, where small cells are densely deployed within the coverage area of a traditional macrocell. Unlike existing work, the limited backhaul capacity at each base station (BS) is taken into account. Here, users (UEs) cannot be offloaded to any arbitrary BS, but only to ones with sufficient backhaul capacity remaining. Jointly designed with traffic offload, transmit power allocation mitigates the intercell interference to further support the quality of service of each UE. The objective here is either: 1) to maximize the network sum rate subject to minimum throughput requirements at individual UEs, or 2) to maximize the minimum UE throughput. Both formulated problems belong to the difficult class of mixed-integer nonconvex optimization problems. The inherently binary BS-UE association variables are strongly coupled with the transmit power variables, making the problems even more challenging to solve. New iterative algorithms are developed based on an exact penalty method combined with successive convex programming, where the binary BS-UE association problem and the nonconvex power allocation problem are dealt with one at a time. At each iteration of the proposed algorithms, only two simple convex problems need to be solved at the same time scale. It is proven that the algorithms improve the objective functions at each iteration and converge eventually. Numerical results demonstrate the efficiency of the proposed algorithms in both traffic offloading and interference mitigation.

Tong, X., Yang, Y., Zhong, Y., Zhu, X., Lin, J. & Dutkiewicz, E. 2017, 'Design of an On-Chip Highly Sensitive Misalignment Sensor in Silicon Technology', IEEE Sensors Journal, vol. 17, no. 5, pp. 1211-1212.
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© 2016 IEEE. Advanced micromachining technology has made magnificent progress for fabrication of non-planar circuits. Using this technology, circuits and systems can be implemented in a more cost-effective way. Unlike the conventional planar circuit, low-cost and highly sensitive misalignment sensor is required to detect imperfect placement of different micro-devices, which may be of the order of sub-micrometers. Currently, this is hardly to be achieved by using the existing approaches. In this letter, we present a novel sensor design approach utilizing the parasitic capacitance of an integrated coupled-line resonator for misalignment sensing. Due to vertical misalignment between two metal strips, the parasitic capacitance of the sensor varies, which results in a resonance shift from 53 to 68 GHz, while a reasonably strong transmission notch is still maintained. Taking advantage of this principle, misalignment can be effectively detected. To prove the concept, several devices are fabricated in a standard silicon technology. Three samples with the same structure are used to evaluate the reliability, while eight different structures are used to verify the concept. All results are extensively validated through both simulation and measurements.

Tuan, H.D., Ngo, D.T. & Tam, H.H.M. 2017, 'Joint power allocation for MIMO-OFDM full-duplex relaying communications', EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 19, pp. 1-17.
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© 2017, The Author(s). In this paper, we address the problem of joint power allocation in a two-hop MIMO-OFDM network, where two full-duplex users communicate with each other via an amplify-and-forward relay. We consider a general model in which the full-duplex relay can forward the received message in either one-way or two-way mode. Our aim is to maximize the instantaneous end-to-end total throughput, subject to (i) the separate sum-power constraints at individual nodes or (ii) the joint sum-power constraint of the whole network. The formulated problems are large-scale nonconvex optimization problems, for which efficient and optimal solutions are currently not available. Using the successive convex approximation approach, we develop novel iterative algorithms of extremely low complexity which are especially suitable for large-scale computation. In each iteration, a simple closed-form solution is derived for the approximated convex program. The proposed algorithms guarantee to converge to at least a local optimum of the nonconvex problems. Numerical results verify that the devised solutions converge quickly, and that our optimal power allocation schemes significantly improve the throughput of MIMO-OFDM full-duplex one-way/two-way relaying over the conventional half-duplex relaying strategy.

Usman, M., Jan, M.A. & He, X.S. 2017, 'Cryptography-Based Secure Data Storage and Sharing Using HEVC and Public Clouds', Information Sciences, vol. 387, pp. 90-102.
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Mobile devices are widely used for uploading/downloading media files such as audio, video and images to/from the remote servers. These devices have limited resources and are required to offload resource-consuming media processing tasks to the clouds for further processing. Migration of these tasks means that the media services provided by the clouds need to be authentic and trusted by the mobile users. The existing schemes for secure exchange of media files between the mobile devices and the clouds have limitations in terms of memory support, processing load, battery power, and data size. These schemes lack the support for large-sized video files and are not suitable for resource-constrained mobile devices. This paper proposes a secure, lightweight, robust and efficient scheme for data exchange between the mobile users and the media clouds. The proposed scheme considers High Efficiency Video Coding (HEVC) Intra-encoded video streams in unsliced mode as a source for data hiding. Our proposed scheme aims to support real-time processing with power-saving constraint in mind. Advanced Encryption Standard (AES) is used as a base encryption technique by our proposed scheme. The simulation results clearly show that the proposed scheme outperforms AES-256 by decreasing the processing time up to 4.76% and increasing the data size up to 0.72% approximately. The proposed scheme can readily be applied to real-time cloud media streaming.

Wang, H., Nguyen, D., Dutkiewicz, Fang & Mueck 2017, 'Negotiable Auction based on Mixed Graph: A Novel Spectrum Sharing Framework', IEEE Transactions on Cognitive Communications and Networking.
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Wang, Y., Liu, J., Li, Y., Fu, J., Xu, M. & Lu, H. 2017, 'Hierarchically Supervised Deconvolutional Network for Semantic Video Segmentation', Pattern Recognition, pp. 437-445.
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© 2016 Elsevier Ltd.Semantic video segmentation is a challenging task of fine-grained semantic understanding of video data. In this paper, we present a jointly trained deep learning framework to make the best use of spatial and temporal information for semantic video segmentation. Along the spatial dimension, a hierarchically supervised deconvolutional neural network (HDCNN) is proposed to conduct pixel-wise semantic interpretation for single video frames. HDCNN is constructed with convolutional layers in VGG-net and their mirrored deconvolutional structure, where all fully connected layers are removed. And hierarchical classification layers are added to multi-scale deconvolutional features to introduce more contextual information for pixel-wise semantic interpretation. Besides, a coarse-to-fine training strategy is adopted to enhance the performance of foreground object segmentation in videos. Along the temporal dimension, we introduce Transition Layers upon the structure of HDCNN to make the pixel-wise label prediction consist with adjacent pixels across space and time domains. The learning process of the Transition Layers can be implemented as a set of extra convolutional calculations connected with HDCNN. These two parts are jointly trained as a unified deep network in our approach. Thorough evaluations are performed on two challenging video datasets, i.e., CamVid and GATECH. Our approach achieves state-of-the-art performance on both of the two datasets.

Yang, T. 2017, 'Distributed MIMO Broadcasting: Reverse Compute-and-forward and Signal-space Alignment', IEEE Transactions on Wireless Communications, vol. 16, no. 1, pp. 581-593.
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We study a downlink distributed MIMO system where a central unit (CU) broadcasts messages to K' users through K distributed BSs. The CU is connected to the BSs via K independent rate-constrained fronthaul (FH) links. The distributed BSs collectively serve the users through the air. We propose a new network coding based distributed MIMO broadcasting scheme, using reverse compute-and-forward and signal space alignment. At the CU, a network coding generator matrix is employed for pre network coding of the users’ messages. The network coded messages are forwarded to the BSs, where the FH rate-constraint determines the actual number of network-coded messages forwarded to the BSs. At the BSs, linear precoding matrices are designed to create a number of bins, each containing a bunch of spatial streams with aligned signal-spaces. At each user, post physical-layer network coding is employed to compute linear combinations over the NC messages w.r.t. the bins, which reverses the pre network coding and recovers the desired messages. We derive an achievable rate of the proposed scheme based on the existence of NC generator matrix, signal-space alignment precoding matrices and nested lattice codes. Improved rate and degrees of freedom over existing interference alignment and compress-and-forward schemes are shown. Numerical results demonstrate the performance improvement, e.g., by as much as 70% increase in throughput over benchmark schemes.

Yang, T., Yang, L., Guo, J. & Yuan, J. 2017, 'A Non-orthogonal Multiple-Access Scheme Using Reliable Physical-layer Network Coding and Cascade-Computation Decoding', IEEE Transactions on Wireless Communications, vol. 16, no. 3, pp. 1633-1645.
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This paper studies non-orthogonal transmission over a K-user fading multiple access channel. We propose a new reliable physical-layer network coding and cascade-computation decoding scheme. In the proposed scheme, K single-antenna users encode their messages by a same practical channel code and QAM modulation, and transmit simultaneously. The receiver chooses K linear coefficient vectors and computes the associated K layers of finite-field linear message-combinations in a cascade manner. Finally, the K users’ messages are recovered by solving the K linear equations. The proposed can be regarded as a generalized onion peeling. We study the optimal network coding coefficient vectors used in the cascade-computation. Numerical results show that the performance of the proposed approaches that of the iterative maximum a posteriori probability detection and decoding scheme, but without using receiver iteration. This results in considerable complexity reduction, processing delay and easier implementation. Our proposed scheme significantly outperforms the iterative detection and decoding scheme with a single iteration, for example, by 1.7 dB for the two user case. The proposed scheme provides a competitive solution for non-orthogonal multiple access.

Yang, T., Yuan, X. & Sun, Q. 2017, 'A Signal-space Aligned Network Coding Approach to Distributed MIMO', IEEE Transactions on Signal Processing, vol. 65, no. 1, pp. 27-40.
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This paper studies an uplink distributed MIMO (DMIMO) system that consists of K users and K distributed base stations (BSs), where the BSs are connected to a central unit (CU) via independent rate-constrained backhaul (BH) links. We propose a new signal-space aligned network coding scheme. First, a network coding generator matrix is selected subject to certain structural properties. Next, distributed linear precoding is employed by the users to create aligned signal-spaces at the BSs, according to the pattern determined by the network coding generator matrix. For each aligned signal-space at a BS, physical-layer network coding is utilized to compute the corresponding network-coded (NC) messages, where the actual number of NC messages forwarded to the CU is determined by the BH rate-constraint. We derive an achievable rate of the proposed scheme based on the existence of the NC generator matrix and signal-space alignment precoding matrices. For DMIMO with two and three BSs, the achievable rates and degrees of freedom (DoF) are evaluated and shown to outperform existing schemes. For example, for DMIMO with two BSs where each user and BS have N and N antennas, respectively, the proposed scheme achieves a DoF of 2 min (N,N) − 1, if the BH capacity scales like (2 min (N,N) − 1) log SNR. This leads to greater DoF compared to that utilizes the strategy for interference channel, whose DoF is min (N,N ). Numerical results demonstrate the performance advantage of the proposed scheme.

Yao, Y., Zhang, J., Shen, F., Hua, X., Xu, J. & Tang, Z. 2017, 'A new web-supervised method for image dataset constructions', Neurocomputing, vol. 236, pp. 23-31.
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© 2017.The goal of this work is to automatically collect a large number of highly relevant natural images from Internet for given queries. A novel automatic image dataset construction framework is proposed by employing multiple query expansions. In specific, the given queries are first expanded by searching in the Google Books Ngrams Corpora to obtain a richer semantic descriptions, from which the visually non-salient and less relevant expansions are then filtered. After retrieving images from the Internet with filtered expansions, we further filter noisy images by clustering and progressively Convolutional Neural Networks (CNN) based methods. To evaluate the performance of our proposed method for image dataset construction, we build an image dataset with 10 categories. We then run object detections on our image dataset with three other image datasets which were constructed by weak supervised, web supervised and full supervised learning, the experimental results indicated the effectiveness of our method is superior to weak supervised and web supervised state-of-the-art methods. In addition, we do a cross-dataset classification to evaluate the performance of our dataset with two publically available manual labelled dataset STL-10 and CIFAR-10.

Yao, Y., Zhang, J., Shen, F., Hua, X.-.S., Xu, J. & Tang, Z. 2017, 'Exploiting Web Images for Dataset Construction: A Domain Robust Approach', IEEE Transactions on Multimedia, pp. 1-1.
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Zhang, T., Gao, X., Wang, W., Du, J., Pegrum, C. & Guo, Y.J. 2017, 'A 36 GHz HTS MMIC Josephson Mixer—Simulation and Measurement', IEEE Transactions on Applied Superconductivity, vol. 27, no. 4, pp. 1-5.
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Zhang, T., Jia, W., He, X.S. & Yang, J. 2017, 'Discriminative Dictionary Learning with Motion Weber Local Descriptor for Violence Detection', IEEE Transactions on Circuits and Systems for Video Technology, vol. 27, no. 3, pp. 696-709.
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Automatic violence detection from video is a hot topic for many video surveillance applications. However, there has been little success in developing an algorithm that can detect violence in surveillance videos with high performance. In this paper, following our recently proposed idea of motion Weber local descriptor (WLD), we make two major improvements and propose a more effective and efficient algorithm for detecting violence from motion images. First, we propose an improved WLD (IWLD) to better depict low-level image appearance information, and then extend the spatial descriptor IWLD by adding a temporal component to capture local motion information and hence form the motion IWLD. Second, we propose a modified sparse-representation-based classification model to both control the reconstruction error of coding coefficients and minimize the classification error. Based on the proposed sparse model, a class-specific dictionary containing dictionary atoms corresponding to the class labels is learned using class labels of training samples. With this learned dictionary, not only the representation residual but also the representation coefficients become discriminative. A classification scheme integrating the modified sparse model is developed to exploit such discriminative information. The experimental results on three benchmark data sets have demonstrated the superior performance of the proposed approach over the state of the arts.

Zhang, T., Jia, W., Yang, B., Yang, J., He, X. & Zheng, Z. 2017, 'MoWLD: a robust motion image descriptor for violence detection', Multimedia Tools and Applications, vol. 76, no. 1, pp. 1419-1438.
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© 2015 Springer Science+Business Media New York Automatic violence detection from video is a hot topic for many video surveillance applications. However, there has been little success in designing an algorithm that can detect violence in surveillance videos with high performance. Existing methods typically apply the Bag-of-Words (BoW) model on local spatiotemporal descriptors. However, traditional spatiotemporal features are not discriminative enough, and also the BoW model roughly assigns each feature vector to only one visual word and therefore ignores the spatial relationships among the features. To tackle these problems, in this paper we propose a novel Motion Weber Local Descriptor (MoWLD) in the spirit of the well-known WLD and make it a powerful and robust descriptor for motion images. We extend the WLD spatial descriptions by adding a temporal component to the appearance descriptor, which implicitly captures local motion information as well as low-level image appear information. To eliminate redundant and irrelevant features, the non-parametric Kernel Density Estimation (KDE) is employed on the MoWLD descriptor. In order to obtain more discriminative features, we adopt the sparse coding and max pooling scheme to further process the selected MoWLDs. Experimental results on three benchmark datasets have demonstrated the superiority of the proposed approach over the state-of-the-arts.

Zhang, T., Pegrum, C., Du, J. & Guo, Y.J. 2017, 'Simulation and measurement of a Ka-band HTS MMIC Josephson junction mixer', Superconductor Science and Technology, vol. 30, no. 1.
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© 2016 IOP Publishing Ltd. We report modeling and simulation results for a Ka band high-temperature superconducting (HTS) monolithic microwave integrated circuit (MMIC) Josephson junction mixer. A Verilog-A model of a Josephson junction is established and imported into the system simulator to realize a full HTS MMIC circuit simulation containing the HTS passive circuit models. Impedance matching optimization between the junction and passive devices is investigated. Junction DC I-V characteristics, current and local oscillator bias conditions and mixing performance are simulated and compared with the experimental results. Good agreement is obtained between the simulation and measurement results.

Zhang, Y., Chen, H., Lu, J. & Zhang, G. 2017, 'Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016', Knowledge-Based Systems.
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© 2017. The journal Knowledge-based Systems (KnoSys) has been published for over 25 years, during which time its main foci have been extended to a broad range of studies in computer science and artificial intelligence. Answering the questions: "What is the KnoSys community interested in?" and "How does such interest change over time?" are important to both the editorial board and audience of KnoSys. This paper conducts a topic-based bibliometric study to detect and predict the topic changes of KnoSys from 1991 to 2016. A Latent Dirichlet Allocation model is used to profile the hotspots of KnoSys and predict possible future trends from a probabilistic perspective. A model of scientific evolutionary pathways applies a learning-based process to detect the topic changes of KnoSys in sequential time slices. Six main research areas of KnoSys are identified, i.e., expert systems, machine learning, data mining, decision making, optimization, and fuzzy, and the results also indicate that the interest of KnoSys communities in the area of computational intelligence is raised, and the ability to construct practical systems through knowledge use and accurate prediction models is highly emphasized. Such empirical insights can be used as a guide for KnoSys submissions.

Zhang, Y., Qian, Y., Huang, Y., Guo, Y., Zhang, G. & Lu, J. 2017, 'An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation', Scientometrics, vol. 111, no. 3, pp. 1925-1946.
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© 2017, Akadémiai Kiadó, Budapest, Hungary. How to evaluate the value of a patent in technological innovation quantitatively and systematically challenges bibliometrics. Traditional indicator systems and weighting approaches mostly lead to “moderation” results; that is, patents ranked to a top list can have only good-looking values on all indicators rather than distinctive performances in certain individual indicators. Orienting patents authorized by the United States Patent and Trademark Office (USPTO), this paper constructs an entropy-based indicator system to measur e their potential in technological innovation. Shannon’s entropy is introduced to quantitatively weight indicators and a collaborative filtering technique is used to iteratively remove negative patents. What remains is a small set of positive patents with potential in technological innovation as the output. A case study with 28,509 USPTO-authorized patents with Chinese assignees, covering the period from 1976 to 2014, demonstrates the feasibility and reliability of this method.

Zhang, Y., Zhang, G., Zhu, D. & Lu, J. 2017, 'Scientific evolutionary pathways: Identifying and visualizing relationships for scientific topics', Journal of the Association for Information Science and Technology.
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Zhao, Y., Di, H., Zhang, J., Lu, Y., Lv, F. & Li, Y. 2017, 'Region-based Mixture Models for human action recognition in low-resolution videos', Neurocomputing.
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© 2017.State-of-the-art performance in human action recognition is achieved by the use of dense trajectories which are extracted by optical flow algorithms. However, optical flow algorithms are far from perfect in low-resolution (LR) videos. In addition, the spatial and temporal layout of features is a powerful cue for action discrimination. While, most existing methods encode the layout by previously segmenting body parts which is not feasible in LR videos. Addressing the problems, we adopt the Layered Elastic Motion Tracking (LEMT) method to extract a set of long-term motion trajectories and a long-term common shape from each video sequence, where the extracted trajectories are much denser than those of sparse interest points (SIPs); then we present a hybrid feature representation to integrate both of the shape and motion features; and finally we propose a Region-based Mixture Model (RMM) to be utilized for action classification. The RMM encodes the spatial layout of features without any needs of body parts segmentation. Experimental results show that the approach is effective and, more importantly, the approach is more general for LR recognition tasks.

Zhong, Y., Yang, Y., Zhu, X., Dutkiewicz, E., Shum, K.M. & Xue, Q. 2017, 'An On-Chip Bandpass Filter Using a Broadside-Coupled Meander Line Resonator with a Defected-Ground Structure', IEEE Electron Device Letters, vol. 38, no. 5, pp. 626-629.
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© 2017 IEEE. An on-chip bandpass filter (BPF) is designed and fabricated in a 0.13-μm SiGe (Bi)-CMOS technology. This BPF consists of a broadside-coupled meander-line resonator (BCMLR) in conjunction with a defected-ground structure (DGS). By simply grounding a BCMLR, the resonator can be converted into a BPF. Further applying a DGS to this BPF, an additional transmission zero can be generated in the high-frequency band. To understand the fundamentals of this design, an $LC$-equivalent circuit is given for investigation of the transmission zeros and poles. The measured results show that the BPF has a center frequency at 33 GHz with a bandwidth of 18%. The minimum insertion loss is 2.6 dB, while the maximum stopband attenuation is 44 dB. The chip size, excluding the pads, is only 0.038 mm 2 ( 0.126×0.3 mm 2 ).

Zhong, Y., Yang, Y., Zhu, X., Dutkiewicz, E., Zhou, Z. & Jiang, T. 2017, 'Device-Free Sensing for Personnel Detection in a Foliage Environment', IEEE Geoscience and Remote Sensing Letters.
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In this letter, the possibility of using device-free sensing (DFS) technology for personnel detection in a foliage environment is investigated. Although the conventional algorithm that based on statistical properties of the received-signal strength (RSS) for target detection at indoor or open-field environment has come a long way in recent years, it is still questionable if this algorithm is fully functional at outdoor with the changing atmosphere and ground conditions, such as a foliage environment. To answer this question, a variety of the measured data have been taken using different targets in a foliage environment. Applying these data along with support vector machine, the impact on detection accuracy due to different classification algorithms is studied. An algorithm that based on the extraction of the high-order cumulant (HOC) of the signals is presented, while the conventional RSS-based one is used as a benchmark. The measurement results show that the classification accuracy of the HOC-based algorithm is better than the RSS-based one by at least 17%. Moreover, to ensure the reliability of the HOC-based approach, the impact on classification accuracy due to different numbers of training samples and different values of signal-to-noise ratio is extensively verified using experimentally recorded samples. To the best of our knowledge, this is the first time that a DFS-based sensing approach is demonstrated to have a potential to distinguish between human and small-animal targets in a foliage environment.

Zhu, H.L., Chung, K.L., Ding, C., Wei, G., Zhang, C. & Guo, Y.J. 2017, 'Polarization-Rotated Waveguide Antennas for Base-Station Applications', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 1545-1548.
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Zuo, H., Zhang, G., Pedrycz, W., Behbood, V. & Lu, J. 2017, 'Fuzzy Regression Transfer Learning in Takagi-Sugeno Fuzzy Models', IEEE Transactions on Fuzzy Systems, pp. 1-1.
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Data Science is a research field concerned with processes and systems that extract knowledge from massive amounts of data. In some situations, however, data shortage renders existing data-driven methods difficult or even impossible to apply. Transfer learning has recently emerged as a way of exploiting previously acquired knowledge to solve new yet similar problems much more quickly and effectively. In contrast to classical data-driven machine learning methods, transfer learning methods exploit the knowledge accumulated from data in auxiliary domains to facilitate predictive modeling in the current domain. A significant number of transfer learning methods that address classification tasks have been proposed, but studies on transfer learning in the case of regression problems are still scarce. This study focuses on using transfer learning techniques to handle regression problems in a domain that has insufficient training data. We propose an original fuzzy regression transfer learning method, based on fuzzy rules, to address the problem of estimating the value of the target for regression. A Takagi-Sugeno fuzzy regression model is developed to transfer knowledge from a source domain to a target domain. Experimental results using synthetic data and real world datasets demonstrate that the proposed fuzzy regression transfer learning method significantly improves the performance of existing models when tackling regression problems in the target domain.

Zuo, Y., Wu, Q., Zhang, J. & An, P. 2017, 'Explicit Edge Inconsistency Evaluation Model for Color-guided Depth Map Enhancement', IEEE Transactions on Circuits and Systems for Video Technology.
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Color-guided depth enhancement is to refine depth maps according to the assumption that the depth edges and the color edges at the corresponding locations are consistent. In the methods on such low-level vision task, Markov Random Fields (MRF) including its variants is one of major approaches, which has dominated this area for several years. However, the assumption above is not always true. To tackle the problem, the state-of-the-art solutions are to adjust the weighting coefficient inside the smoothness term of MRF model. These methods are lack of explicit evaluation model to quantitatively measure the inconsistency between the depth edge map and the color edge map, so it cannot adaptively control the efforts of the guidance from the color image for depth enhancement leading to various defects such as texture-copy artifacts and blurring depth edges. In this paper, we propose a quantitative measurement on such inconsistency and explicitly embed it into the smoothness term. The proposed method demonstrates the promising experimental results when compared with benchmark and the state-of-the-art methods on Middlebury datasets, ToF-Mark datasets and NYU datasets.

Conferences

Gay, M., Zhu, F., Nguyen, D. & Dutkiewicz 2017, 'Double-Balanced Gilbert Mixer with Current Bleeding for RF Front-End Using 0.13µm SiGe BiCMOS Technology', Proc. of the IEEE 85th Vehicular Technology Conference 2017, IEEE 85th Vehicular Technology Conference 2017, Sydney, Australia.

Guan, D., Ding, C. & Guo, Y.J. 2017, 'A compact multi-beam antenna without beam forming network', ISAP 2016 - International Symposium on Antennas and Propagation, pp. 404-405.
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© 2016 IEICE. A novel approach to design a multi-beam array antenna without a beam forming network (BFN) is presented. The proposed antenna consists of 3×3 microstrip patches that are tightly coupled through microstrip lines. By exciting any one of these patches, the energy can be coupled to all the patches. Nine beams towards different directions are obtained by selecting different feeding ports. The resultant gain varies from 10 dBi to 11 dBi. The scanning ranges of the beams are ±24° and ±45° in the elevation and horizontal directions, respectively. The proposed antenna has a single-layered structure without complex feeding network, which significantly lowers its cost.

Guo, J., Yang, T., Yuan, J. & Zhang, J.A. 2017, 'Linear physical-layer network coding for the fading y-channel without transmitter channel state information', IEEE Vehicular Technology Conference.
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© 2016 IEEE. In this paper, we propose a new linear physical-layer network coding (NC) scheme for the fading Y-channel, assuming that the channel state information (CSI) is not available at transmitters. In this scheme, each user transmits one message to a relay and intends to obtain both other two users' messages. Based on the receiver-side CSI, the relay determines two NC generator vectors for linear network coding, and reconstructs the associated two linear NC codewords. For the case when there is one time-slot in the uplink phase, we present an explicit solution for the generator vectors that minimizes the error probability at a high SNR, and a lower bound of the error performance of the proposed scheme using our optimized generator vectors. Extending to multiple time-slots in the uplink, two typical scenarios are discussed. Numerical results show that the proposed scheme significantly outperforms existing schemes, and match well with our analytical results.

Huynh T, T.B., Vo K, T., Ngo H, S., Dutkiewicz, E. & Nguyen, D. 2016, 'A Local Search Algorithm for Saving Energy Cost in Duty-Cycle Wireless Sensor Network', The 20th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Springer, Canberra, Australia.
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Wireless Sensor Networks (WSNs) have been recently used for various applications. Due to the distributed and (often) unattended nature of the nodes after deployment, the lack of energy and the interruptive process in each sensor are the two major problems of WSN systems. Hence, designing a protocol which not only improves system performance but also lowers sensors’ energy consumption so as to maximize the network lifetime is very much desirable. The network lifetime maximization problem was known to be NP-Hard. This paper addresses the Minimum Energy-Multicasting (MEM) problem in Duty-Cycle Wireless Sensor Networks (DC-WSNs) in which sensors cyclically switch between on/off (wake/sleep) modes. To that end, we propose a local search algorithm and compare its performance with the best algorithm so far called GS-MEM over the four datasets designated for the MEM problem. The experimental results show that our proposed algorithm significantly outperforms GS-MEM in terms of energy cost

Kong, F., Sun, X., Leung, V.C.M., Guo, Y.J., Zhu, Q. & Zhu, H. 2017, 'Queue-aware small cell activation for energy efficiency in two-tier heterogeneous networks', IEEE Wireless Communications and Networking Conference, WCNC.
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© 2017 IEEE. In heterogeneous networks (HetNets), the network energy efficiency is critically determined by the base station (BS) deployment density. In this paper, we consider a BS density optimization problem by turning on only a fraction of micro BSs according to an activation ratio to minimize the network average power consumption per area in a 2- tier HetNet. In contrast to previous studies where a BS is assumed to be transmitting packets all the time, such that the network power consumption monotonically increases as the BS density increases, we assume that each BS can be busy or idle depending on the dynamic packet arrivals. The network power consumption is thus closely related to the average traffic intensity of each tier. With the assumption of universal spectrum reuse, the average traffic intensity of each tier is found to be uniquely determined by a set of fixed-point equations, based on which the network average power consumption per area is characterized. Simulation results demonstrate that the network average power consumption per area can be minimized by properly tuning the activation ratio. It is further revealed that the optimal activation ratio increases as the mean packet arrival rate of each user increases.

Long, S., Yang, T. & Xia, X. 2017, 'Optimized Linear Physical-Layer Network Coding of Full-Rate Full-Diversity in MIMO Two-Way Relay Networks', IEEE ICC 2017, Paris France.
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Mohammadi, M.S., Dutkiewicz, E. & Zhang, Q. 2017, 'Joint source-channel optimization of vector quantization with polar codes', IEEE Vehicular Technology Conference.
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© 2016 IEEE. Joint application of polar channel coding combined with vector quantization lossy source coding is considered in this paper. The existing index assignment schemes in the literature cannot be used with polar codes due to their unique crossover probabilities. We elaborate on this problem and locally optimize index assignments. In addition, we propose an algorithm that jointly optimizes the number of quantization levels and the rate of the polar code in order to achieve minimum end-to-end distortion. It finds the optimal tradeoff between the distortion caused by channel errors and the quantization distortion. We also derive estimates for the crossover probabilities of the polar code which are required in the analysis. Simulation results confirm the effectiveness of the proposed algorithms and the accuracy of the crossover probabilities.

Nguyen, T., Seneviratne, A., Hoang, D. & Nguyen, D. 2017, 'Initial Trust Establishment for Personal Space IoT Systems', Proc. of the 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS): MobiSec 2017, IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS): MobiSec 2017, Atlanta, USA.
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Noman, H., Dutkiewicz, E., Nguyen, D., Mueck, M. & Srikanteswarae, S. 2017, 'The impact on Full Duplex D2D Communication of different LTE Transmission Techniques', IEEE 85th Vehicular Technology Conference: VTC2017-Spring, Sydney, Australia.

Pham, P.G., Huang, M. & Nguyen, Q. 2017, 'Interactive Data Exploration through Multiple Visual Contexts with Different Data Models and Dimensions', Proccdings of 21st International Conference Information Visualisation, 2017 21st International Conference Information Visualisation, IEEE CPS, London, UK, pp. 84-89.
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Visual analytics plays a key role in bringing insights to audiences who are interested and dedicated in data exploration. In the area of relational data, many advanced visualization tools and frameworks are proposed in order to dealing with such data features. However, the majority of those have not greatly considered the whole process from data-model mining to query utilizing on dimensions and data values, which might cause interruption to exploration activities. This paper presents a new interactive exploration framework for relational data analysis through automatic interconnection of data models, data dimensions and data values. The basic idea is to construct a relative and switchable chain of those context representations by integrating our previous techniques on node-link, parallel coordinate and scatterplot graphics. This approach enables users to flexibly make relative queries on desired contexts at any stage of exploration for deep data understanding. The result from a typical case study for the framework demonstration indicates that our approach is able to handle the addressed challenge.

Pham, T., Nguyen, D., Dutkiewicz, E., McEwan, A. & Leong, P. 2017, 'An Anomaly Detection Technique in Wearable Wireless Monitoring Systems for Studies of Gait', 31st International Conference on Information Networking (ICOIN) 2017, Danang, Vietnam.

Pham, T.T., Nguyen, D.N., Dutkiewicz, E., McEwan, A.L. & Leong, P.H.W. 2017, 'Wearable Healthcare Systems: A Single Channel Accelerometer Based Anomaly Detector for Studies of Gait Freezing in Parkinson’s Disease', Proceedings of the IEEE, IEEE conference ICC’17 SAC-6 EH, Institute of Electrical and Electronics Engineers, Paris, France.

Siyari, P., Krunz, M. & Nguyen, D. 2017, 'Joint Transmitter- and Receiver-based Friendly Jamming in a MIMO Wiretap Interference Network', IEEE ICC Conference, Paris, France.

Sohaib, O. & Naderpour, M. 2017, 'Decision Making on Adoption of Cloud Computing in E-Commerce Using Fuzzy TOPSIS', IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), IEEE, Naples, Italy.
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Tam, H.H.M., Tuan, H.D., Nasir, A.A. & Duong, T.Q. 2017, 'Power splitting for MIMO energy harvesting in multi-user networks', Proceedings - 2017 International Conference on Recent Advances in Signal Processing, Telecommunications and Computing, SigTelCom 2016, pp. 217-222.
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© 2017 IEEE. We consider a multicell multi-user multiple-input-multiple-output (MU-MIMO) network and propose the efficient design of precoding matrices for the sum throughput maximization under throughput QoS constraints and energy harvesting (EH) constraints for energy-constrained devices in both downlink (DL) and uplink (UL) transmissions. We employ power splitting (PS) approach at the receiver to ensure practical EH and information decoding (ID). The considered practical problem is quite complex due to highly non-convex objective and constraints. Towards this end, we develop a new path-following algorithm for its solution, which just requires a convex quadratic program at each iteration and promises quick convergence.

Vo, K., Nguyen, D., Ha, K. & Dutkiewicz 2017, 'Real-Time Analysis on Ensemble SVM Scores to Reduce P300-Speller Intensification Time', Prof. of the 39th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC'17), 39th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC'17), Korea.

Vo, K., Nguyen, D., Hoang, H.K. & Dutkiewicz, E. 2017, 'Dynamic Stopping Using eSVM Scores Analysis for Event-Related Potential Brain-Computer Interfaces', 11th International Symposium on Medical Information and Communication Technology (ISMICT), Lisbon, Portugal.

Zhang, J., Cantoni, A., huang, X., guo, Y. & heath, R. 2017, 'Framework for an Innovative Perceptive Mobile Network Using Joint Communication and Sensing', IEEE Vehicular Technology Conference, IEEE VTC Spring, Sydney.
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Zhang, J., cantoni, A., huang, X., guo, Y. & heath, R. 2017, 'Joint Communications and Sensing Using Two Steerable Analog Antenna Arrays', IEEE VTC Spring, IEEE, Sydney.
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Zhu, H.L., Ding, C., Wei, G. & Guo, Y.J. 2017, 'A novel base station antenna based on rectangular waveguide', ISAP 2016 - International Symposium on Antennas and Propagation, pp. 196-197.
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© 2016 IEICE. A novel base station antenna element is proposed. It consists of a surface of parallel strips to rotate the polarization direction and a segment of a rectangular waveguide. The surface is designed on a single-sided substrate, which has the same area as the aperture of the waveguide. In assembling, the non-copper side of the substrate is placed in direct contact with the aperture of the waveguide antenna. To achieve the polarization rotation, the parallel strips on the surface are rotated by 45° with respect to the walls of the waveguide antenna. By adding the surface, the linear polarization direction of the rectangular waveguide antenna is rotated by 45° to comply with the requirements of cellular industry. SMA connector with a conical probe is used as the coaxial-to-waveguide adaptor. Results have shown that the proposed antenna has a fractional impedance bandwidth of 35%, and a stable radiation pattern is also achieved.