Electrical and Electronics Engineering publications abstract of: 01-2018 sorted by title, page: 11

» Irradiation Testing of Piezoelectric (Aluminum Nitride, Zinc Oxide, and Bismuth Titanate) and Magnetostrictive Sensors (Remendur and Galfenol)
Abstract:
Four piezoelectric transducers with aluminum nitride (AlN), zinc oxide (ZnO), and bismuth titanate (BiTi) as the active elements and two magnetostrictive transducers were fabricated with Remendur and Galfenol as the active elements. The irradiation was for 18 months with an integrated neutron fluence of approximately n/cm2 for MeV, temperatures in excess of 420 °C, and a gamma fluence of gamma/cm2. The sensor performance is explained in the context of the pulse-echo signals. The feasibility of ultrasonic transducers in a nuclear reactor has been established. This opens the door to leave-in-place sensors for in-reactor conditions and materials.
Autors: B. Reinhardt;J. Daw;B. R. Tittmann;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Jan 2018, volume: 65, issue:1, pages: 533 - 538
Publisher: IEEE
 
» Italy launches new IoT network [News]
Abstract:
Telecom Italia, Italy's largest telecommunications provider, is putting the finishing touches on a new wireless network for the Internet of Things that should be available nationwide by the end of January. The Internet of Things (IoT) is a catchall term for many kinds of connected devices-such as sensors, speakers, and cameras-found in cities, factories, and homes. These devices often don't need as much bandwidth as smartphones, but connecting them through existing LTE networks is expensive.
Autors: Amy Nordrum;
Appeared in: IEEE Spectrum
Publication date: Jan 2018, volume: 55, issue:1, pages: 9 - 10
Publisher: IEEE
 
» Iterative Deblending of Simultaneous-Source Seismic Data With Structuring Median Constraint
Abstract:
Simultaneous-source shooting can help reduce the acquisition time cost, but at the expense of introducing strong interference (blending noise) into the acquired seismic data. It has been demonstrated previously that the deblending problem can be considered as an inversion process. In this letter, we propose a new iterative approach to solve this inversion problem. In the proposed approach, a new coherency-promoting constraint, called structuring median filtering (SMF), is proposed and used to regularize the estimated model in each iteration. The SMF processes the signal by the interactions of the input signal and another given small section of signal, namely, the structuring element. The SMF is more robust than other coherency-promoting filtering such as the median filtering and mathematical morphological filtering. Numerical experiments demonstrate that the iterative deblending based on the SMF constraint obtains a better performance and a faster convergence than the low-rank and compressed sensing constraint-based deblending approaches.
Autors: Weilin Huang;Runqiu Wang;Xiangbo Gong;Yangkang Chen;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 58 - 62
Publisher: IEEE
 
» Iterative LMMSE Individual Channel Estimation Over Relay Networks With Multiple Antennas
Abstract:
In this paper, we investigate the individual channel estimation over the three-node one-way relay network, where all the nodes are equipped with multiple antennas. We first examine one simple but representative scenario, where the relay node is equipped with a single antenna. An iterative linear minimum mean-square-error (LMMSE) method, which has fast convergence speed, is proposed to estimate the individual channels. We derive the closed-form least square channel estimator through the matrix unitary diagonalization to provide one good initialization point for the iterative LMMSE estimator. To evaluate the performance of the proposed algorithm, we present two performance lower bounds: Bayesian Cramér lower bound and linear estimation lower bound (LELB). Then, the training block and the relay amplification factor are optimized through minimizing the LELB. After that, our studies are extended to the general case, where all the nodes are equipped with multiple antennas. Finally, numerical results are provided to corroborate our proposed studies.
Autors: Jianpeng Ma;Shun Zhang;Hongyan Li;Nan Zhao;Arumugam Nallanathan;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 423 - 435
Publisher: IEEE
 
» iTTVis: Interactive Visualization of Table Tennis Data
Abstract:
The rapid development of information technology paved the way for the recording of fine-grained data, such as stroke techniques and stroke placements, during a table tennis match. This data recording creates opportunities to analyze and evaluate matches from new perspectives. Nevertheless, the increasingly complex data poses a significant challenge to make sense of and gain insights into. Analysts usually employ tedious and cumbersome methods which are limited to watching videos and reading statistical tables. However, existing sports visualization methods cannot be applied to visualizing table tennis competitions due to different competition rules and particular data attributes. In this work, we collaborate with data analysts to understand and characterize the sophisticated domain problem of analysis of table tennis data. We propose iTTVis, a novel interactive table tennis visualization system, which to our knowledge, is the first visual analysis system for analyzing and exploring table tennis data. iTTVis provides a holistic visualization of an entire match from three main perspectives, namely, time-oriented, statistical, and tactical analyses. The proposed system with several well-coordinated views not only supports correlation identification through statistics and pattern detection of tactics with a score timeline but also allows cross analysis to gain insights. Data analysts have obtained several new insights by using iTTVis. The effectiveness and usability of the proposed system are demonstrated with four case studies.
Autors: Yingcai Wu;Ji Lan;Xinhuan Shu;Chenyang Ji;Kejian Zhao;Jiachen Wang;Hui Zhang;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 709 - 718
Publisher: IEEE
 
» Joint Admission Control and Resource Allocation in Edge Computing for Internet of Things
Abstract:
The IoT is a novel platform for making objects more intelligent by connecting to the Internet. However, mass connections, big data processing, and huge power consumption restrict the development of IoT. In order to address these challenges, this article proposes a novel ECIoT architecture. To further enhance the system performance, radio resource and computational resource management in ECIoT are also investigated. According to the characteristics of the ECIoT, we mainly focus on admission control, computational resource allocation, and power control. To improve the performance of ECIoT, cross-layer dynamic stochastic network optimization is studied to maximize the system utility, based on the Lyapunov stochastic optimization approach. Evaluation results are provided which demonstrate that the proposed resource allocation scheme can improve throughput, reduce end-to-end delay, and also achieve an average throughput and delay trade-off. Finally, the future research topics of resource management in ECIoT are discussed.
Autors: Shichao Li;Ning Zhang;Siyu Lin;Linghe Kong;Ajay Katangur;Muhammad Khurram Khan;Minming Ni;Gang Zhu;
Appeared in: IEEE Network
Publication date: Jan 2018, volume: 32, issue:1, pages: 72 - 79
Publisher: IEEE
 
» Joint Beamforming and Time Switching Design for Secrecy Rate Maximization in Wireless-Powered FD Relay Systems
Abstract:
This paper focuses on the secure transmission of wireless-powered full-duplex (FD) relay systems, where a multiantenna source communicates with a single-antenna destination with the help of a FD relay in the presence of a single-antenna eavesdropper. It is assumed that the FD relay is wireless energy harvesting-enabled, adopting both transmit and receive antennas to harvest energy in a time switching (TS) mode. As the objective of this paper is to maximize the system secrecy rate through jointly designing the energy beamforming vector, the information beamforming vector and the TS coefficient, an optimization problem is formulated. The formulated problem is proved to be nonconvex and the challenge to solve which is to concurrently solve out the three variables. To cope with this difficulty, an iterative algorithm is proposed to convert the formulated optimization problem into three convex subproblems, based on which the closed form solutions for the beamforming vectors are derived and the TS coefficient is obtained. Convergence property of the iterative method is analyzed. Simulations are also done to verify the theoretical derivations in terms of the convergence speed and the secrecy rate. Results reveal that the secrecy rate performance of exploiting transmit antenna together with receive antenna for energy harvesting at the FD relay outperforms only receive antenna case. Moreover, although there exists loopback interference between antennas, the FD relaying can always substantially boost the secrecy rate compared with half-duplex relaying architecture.
Autors: Jingping Qiao;Haixia Zhang;Xiaotian Zhou;Dongfeng Yuan;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 567 - 579
Publisher: IEEE
 
» Joint Discriminative Dictionary and Classifier Learning for ALS Point Cloud Classification
Abstract:
To efficiently recognize on-ground objects in airborne laser scanning (ALS) point clouds, we design a method that jointly learns a discriminative dictionary and a classifier. In the method, the point cloud is segmented into hierarchical point clusters, which are organized by a tree structure. Then, the feature of each point cluster is extracted. The feature of a leaf node is obtained by aggregating the features of all its parent nodes. The feature of the leaf node is called the hierarchical aggregation feature. The hierarchical aggregation features are encoded by sparse coding. We introduce a new label consistency constraint called “discriminative sparse-code error,” and combine it with the reconstruction error, the classification error, and -norm sparsity constraint to form a unified objective function. The objective function is efficiently solved by using the proposed label consistency feature sign method. We obtain an overcomplete discriminative dictionary and an optimal linear classifier. Experiments performed on different ALS point cloud scenes have shown that the hierarchical aggregation features combined with the learned classifier can significantly enhance the classification results, and also demonstrated the superior performance of our method over other techniques in point cloud classification.
Autors: Zhenxin Zhang;Liqiang Zhang;Yumin Tan;Liang Zhang;Fangyu Liu;Ruofei Zhong;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 524 - 538
Publisher: IEEE
 
» Joint Estimation of Carrier Frequency Offset and Channel Impulse Response for Linear Periodic Channels
Abstract:
In many communications scenarios, the channel exhibits periodic characteristics, e.g., power line communications and interference-limited communications. Additionally, certain approximations for mobile radio channels over finite time intervals may result in periodic channel models. In this paper, we study pilot-aided joint estimation of the channel impulse response (CIR) and of the carrier frequency offset (CFO) for linear periodic channels, in which both the CIR and the noise statistics vary periodically in time. We first consider the joint maximum likelihood estimator (JMLE) for the CIR and the CFO, and discuss the practical drawbacks associated with this estimator. When the coefficients of the delay-Doppler spread function of the CIR are approximately sparse, we propose two estimation schemes with higher spectral efficiency and lower computational complexity compared with the JMLE, which are obtained by exploiting both the periodicity and the sparsity of the channel, without requiring a priori knowledge of the sparsity pattern. Finally, we study the design of pilot sequences aimed at improving the estimation performance in sparse periodic channels. Simulation studies corresponding to practical scenarios of the proposed estimators demonstrate that substantial benefits can be obtained by properly accounting for the sparsity and periodicity in the design of estimation schemes.
Autors: Roee Shaked;Nir Shlezinger;Ron Dabora;
Appeared in: IEEE Transactions on Communications
Publication date: Jan 2018, volume: 66, issue:1, pages: 302 - 319
Publisher: IEEE
 
» Joint Estimation of Timing and Carrier Phase Offsets for MSK Signals in Alpha-Stable Noise
Abstract:
Impulsive noise modeled as symmetric -stable () distribution is commonly seen in many practical communication scenarios. In this letter, we focus on the joint timing and carrier phase synchronization of minimum shift keying signals in noise. We first derive the Cramér–Rao lower bound (CRLB) of joint timing and carrier phase offsets estimation. Then, an optimal synchronization training sequence is designed to minimize the CRLB. As the corresponding maximum likelihood estimator is hard to implement in noise, we further propose a pragmatic synchronization parameters estimation algorithm based on explicit myriad cost function and a global optimization method. Extensive simulation results show that our proposed algorithm works well and is robust to the estimation errors of received signal-to-noise ratio and noise parameter.
Autors: Guosheng Yang;Jun Wang;Guoyong Zhang;Qijia Shao;Shaoqian Li;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 89 - 92
Publisher: IEEE
 
» Joint Inversion of Electromagnetic and Seismic Data Based on Structural Constraints Using Variational Born Iteration Method
Abstract:
An efficient 2-D joint full-waveform inversion method for electromagnetic and seismic data in a layered medium background is developed. The joint inversion method based on the integral equation (IE) method is first proposed in this paper. In forward computation, the IE method is employed, which usually has smaller discretized computation domain and less cumulative error compared with the finite-difference method. In addition, fast Fourier transform is used to accelerate the convolution between Green’s functions and induced sources due to the shift invariance property of the layered Green’s functions in the horizontal direction. In the inversion model, the cross-gradient function is incorporated into the cost function of the separate inversion to enforce the structure similarity between electric conductivity and seismic-wave velocity. We use the improved variational Born iteration method and two different iteration strategies to minimize the cost function and reconstruct the contrasts. Several typical models in geophysical applications are used to validate our joint inversion method, and the numerical simulation results show that joint inversion can improve the inversion results when compared with those from the separate inversion.
Autors: Tian Lan;Hai Liu;Na Liu;Jinghe Li;Feng Han;Qing Huo Liu;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 436 - 445
Publisher: IEEE
 
» Joint Latent Dirichlet Allocation for Social Tags
Abstract:
Social tags, serving as a textual source of simple but useful semantic metadata to reflect the user preference or describe the web objects, has been widely used in many applications. However, social tags have several unique characteristics, i.e., sparseness and data coupling (i.e., non-IIDness), which makes existing text analysis methods such as LDA not directly applicable. In this paper, we propose a new generative algorithm for social tag analysis named joint latent Dirichlet allocation, which models the generation of tags based on both the users and the objects, and thus accounts for the coupling relationships among social tags. The model introduces two latent factors that jointly influence tag generation: the user's latent interest factor and the object's latent topic factor, formulated as user-topic distribution matrix and object-topic distribution matrix, respectively. A Gibbs sampling approach is adopted to simultaneously infer the above two matrices as well as a topic-word distribution matrix. Experimental results on four social tagging datasets have shown that our model is able to capture more reasonable topics and achieves better performance than five state-of-the-art topic models in terms of the widely used point-wise mutual information metric. In addition, we analyze the learnt topics showing that our model recovers more themes from social tags while LDA may lead the topic vanishing problems, and demonstrate its advantages in the social recommendation by evaluating the retrieval results with mean reciprocal rank metric. Finally, we explore the joint procedure of our model in depth to show the non-IID characteristic of social tagging process.
Autors: Jiangchao Yao;Yanfeng Wang;Ya Zhang;Jun Sun;Jun Zhou;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 224 - 237
Publisher: IEEE
 
» Joint Magnetic Calibration and Localization Based on Expectation Maximization for Tongue Tracking
Abstract:
Background: Tongue tracking, which helps researchers gain valuable insights into speech mechanism, has many applications in speech therapy and language learning. The wireless localization technique, which involves tracking a small magnetic tracer within the 3-D oral space, provides a low cost and convenient approach to capture tongue kinematics. In practice, this technique requires accurate calibration of three-axial magnetic sensors used in the tracking system. The data-driven calibration depends on the trajectories of magnetic tracer and the ambient noise, which may change across time and space. Methods: In this paper, we model the kinematics of tracer movement and the noisy magnetic measurements in a Bayesian framework, then present a joint calibration and localization (JCL) algorithm based on expectation maximization (EM), where the unscented Rauch–Tung–Striebel smoother is employed for tracer localization and the curvilinear search algorithm is applied for sensor calibration. Results: Based on measurements conducted on our tongue tracking system with a small magnetic tracer (diameter: 6.05 mm, thickness: 1.25 mm, residual induction: 14 800 G), the JCL algorithm achieves averaged root mean square error of 0.45 mm for tracer position estimation and for tracer orientation estimation, which are significantly lower than those of the separate calibration and localization algorithms. Conclusion: These results show that JCL can help improve the localization accuracy of this system. Significance: A potentially high precision tongue tracking method is demonstrated.
Autors: Jun Lu;Zhongtao Yang;Klaus Z. Okkelberg;Maysam Ghovanloo;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Jan 2018, volume: 65, issue:1, pages: 52 - 63
Publisher: IEEE
 
» Joint Prioritized Scheduling and Resource Allocation for OFDMA-Based Wireless Networks
Abstract:
In this paper, we study the joint prioritized link scheduling and resource allocation for OFDMA-based wireless networks, which serve two classes of wireless links, namely, non-prioritized (low-priority) and prioritized (high-priority) links. Our design aims to maximize the number of scheduled non-prioritized links and their sum rate, while guaranteeing the minimum required rates of all active prioritized and non-prioritized links. We present the problem formulation as a single-stage optimization problem, which simultaneously maximizes the number of scheduled non-prioritized links and their sum rate. We propose a monotonic-based optimal approaching (MBOA) algorithm to solve this problem by employing the monotonic global optimization technique and an efficient rounding procedure. We prove that the MBOA algorithm can schedule the maximum number of non-prioritized links with slight and controllable degradation in the minimum required rates of non-prioritized links. For low-complexity design, we propose an iterative convex approximation algorithm, which sequentially performs power allocation and link removal in each iteration. We then describe how the proposed algorithms can be implemented in the standardized LTE-based cellular system. Finally, we conduct numerical studies for device-to-device communications underlaid cellular networks under perfect or imperfect channel state information (CSI). Numerical results demonstrate that the proposed algorithms can be applied to the imperfect CSI scenario with slight degradation in the network performance. Moreover, in the perfect CSI scenario, the proposed algorithms significantly outperform the conventional algorithms both in the number of scheduled non-prioritized links and their sum rate.
Autors: Tuong Duc Hoang;Long Bao Le;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 310 - 323
Publisher: IEEE
 
» Joint Source and Relay Design for MIMO Two-Way Relay Networks With SWIPT
Abstract:
A multiple-input multiple-output two-way amplify-and-forward relay network with energy harvesting is considered in this paper. Under the transmit power constraints at sources and relay, a beamforming design problem is formulated, which minimizes the total mean square error while still guaranteeing sufficient energy harvested at the sources. Since this problem is nonconvex, an alternating optimization method based on generalized singular value decomposition (GSVD) is proposed and the algorithm is proved to be convergent. Moreover, based on the successive convex approximation, an iterative refinement is further designed to improve the solution quality of the GSVD scheme. Numerical results show good performance of the proposed schemes.
Autors: Zhigang Wen;Xiaoqing Liu;Shuangyan Zheng;Wenxia Guo;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 822 - 826
Publisher: IEEE
 
» Joint Statistical Iterative Material Image Reconstruction for Spectral Computed Tomography Using a Semi-Empirical Forward Model
Abstract:
By acquiring tomographic measurements with several distinct photon energy spectra, spectral computed tomography (spectral CT) is able to provide additional material-specific information compared with conventional CT. This information enables the generation of material selective images, which have found various applications in medical imaging. However, material decomposition typically leads to noise amplification and a degradation of the signal-to-noise ratio. This is still a fundamental problem of spectral CT, especially for low-dose medical applications. Inspired by the success for low-dose conventional CT, several statistical iterative reconstruction algorithms for spectral CT have been developed. These algorithms typically rely on detailed knowledge about the spectrum and the detector response. Obtaining this knowledge is often difficult in practice, especially if photon counting detectors are used to acquire the energy specific information. In this paper, a new algorithm for joint statistical iterative material image reconstruction is presented. It relies on a semi-empirical forward model which is tuned by calibration measurements. This strategy allows to model spatially varying properties of the imaging system without requiring detailed prior knowledge of the system parameters. We employ an efficient optimization algorithm based on separable surrogate functions to accelerate convergence and reduce the reconstruction time. Numerical as well as real experiments show that our new algorithm leads to reduced statistical bias and improved image quality compared with projection-based material decomposition followed by analytical or iterative image reconstruction.
Autors: Korbinian Mechlem;Sebastian Ehn;Thorsten Sellerer;Eva Braig;Daniela Münzel;Franz Pfeiffer;Peter B. Noël;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 68 - 80
Publisher: IEEE
 
» Joint Trajectory and Power Optimization for UAV Relay Networks
Abstract:
In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.
Autors: Shuhang Zhang;Hongliang Zhang;Qichen He;Kaigui Bian;Lingyang Song;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 161 - 164
Publisher: IEEE
 
» Joint User Association and Power Allocation for Cell-Free Visible Light Communication Networks
Abstract:
As a complementary technology for conventional radio frequency communication, visible light communication (VLC) is a potential form of the optical wireless communication, which can provide both communication and illumination simultaneously. Since load balancing and power control for interference management are key challenges in the network deployment, we consider a joint user association and power allocation scheme in a cell-free VLC network to improve the system performance. It is mathematically formulated as a non-convex network utility maximization problem in consideration of the user fairness, load balancing, and power control. To tackle this non-convex problem, we divide it into two subproblems (i.e., the user association subproblem and the power allocation subproblem) and solve them with the dual projected gradient algorithm and successive convex approximation algorithm iteratively until a stationary point is found. Simulation results verify that significant gain can be achieved with the proposed scheme compared with the user association schemes without consideration of the power control.
Autors: Rui Jiang;Qi Wang;Harald Haas;Zhaocheng Wang;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 136 - 148
Publisher: IEEE
 
» Joint-Transformation-Based Detection of False Data Injection Attacks in Smart Grid
Abstract:
For reliable operation and control of smart grid, estimating the correct states is of utmost importance to the system operator. With recent incorporation of information technology and advanced metering infrastructure, the futuristic grid is more prone to cyber-threats. The false data injection (FDI) attack is one of the most thoroughly researched cyber-attacks. Intelligently crafted, it can cause false estimation of states, which further seriously affects the entire power system operation. In this paper, we propose joint-transformation-based scheme to detect FDI attacks in real time. The proposed method is built on the dynamics of measurement variations. Kullback–Leibler distance is used to find out the difference between probability distributions obtained from measurement variations. The proposed method is tested using IEEE 14 bus system considering attack on different state variables. The results shows that the proposed scheme detects FDI attacks with high detection probability.
Autors: Sandeep Kumar Singh;Kush Khanna;Ranjan Bose;Bijaya Ketan Panigrahi;Anupam Joshi;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 89 - 97
Publisher: IEEE
 
» Junctionless Nanosheet (3 nm) Poly-Si TFT: Electrical Characteristics and Superior Positive Gate Bias Stress Reliability
Abstract:
In this letter, a junctionless (JL) poly-Si thin-film transistor (TFT) with a 3-nm-thick nanosheet channel is successfully fabricated using the low-temperature atomic level etching process. An inversion-mode (IM) TFT is also prepared for performance comparison and reliability investigation of positive gate bias stress (PGBS). In comparison with the IM-TFT, the JL-TFT exhibits superior PGBS reliability. The origin of the difference in degradation rates between the JL and IM-TFTs is ascribed to the different transport mechanisms and different gate dielectric fields under the same gate over-drive stress. Nanosheet JL-TFTs with a 3-nm channel thickness show excellent S.S (69 mV/decade) and extremely low off-current (1.93 fA). Results indicate that it is a promising candidate for low-power 3-D integrated circuits.
Autors: Jer-Yi Lin;Malkundi Puttaveerappa Vijay Kumar;Tien-Sheng Chao;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 8 - 11
Publisher: IEEE
 
» Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring
Abstract:
Visualizations often appear in multiples, either in a single display (e.g., small multiples, dashboard) or across time or space (e.g., slideshow, set of dashboards). However, existing visualization design guidelines typically focus on single rather than multiple views. Solely following these guidelines can lead to effective yet inconsistent views (e.g., the same field has different axes domains across charts), making interpretation slow and error-prone. Moreover, little is known how consistency balances with other design considerations, making it difficult to incorporate consistency mechanisms in visualization authoring software. We present a wizard-of-oz study in which we observed how Tableau users achieve and sacrifice consistency in an exploration-to-presentation visualization design scenario. We extend (from our prior work) a set of encoding-specific constraints defining consistency across multiple views. Using the constraints as a checklist in our study, we observed cases where participants spontaneously maintained consistent encodings and warned cases where consistency was overlooked. In response to the warnings, participants either revised views for consistency or stated why they thought consistency should be overwritten. We categorize participants' actions and responses as constraint validations and exceptions, depicting the relative importance of consistency and other design considerations under various circumstances (e.g., data cardinality, available encoding resources, chart layout). We discuss automatic consistency checking as a constraint-satisfaction problem and provide design implications for communicating inconsistencies to users.
Autors: Zening Qu;Jessica Hullman;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 468 - 477
Publisher: IEEE
 
» Key Technologies and System Trade-offs for Detection and Localization of Amateur Drones
Abstract:
The use of amateur drones is expected to significantly increase over the upcoming years. However, regulations do not allow such drones to fly over all areas, in addition to typical altitude limitations. As a result, there is an urgent need for amateur drone surveillance solutions. These solutions should include means of accurate detection, classification, and localization of the unwanted drones in a no-fly zone. In this article, we give an overview of promising techniques for modulation classification and signal-strength-based localization of amateur drones by using surveillance drones. By introducing a generic altitude-dependent propagation model, we show how detection and localization performance depend on the altitude of surveillance drones. Particularly, our simulation results show a 25 dB reduction in the minimum detectable power or 10 times coverage enhancement of a surveillance drone by flying at the optimum altitude. Moreover, for a target no-fly zone, the location estimation error of an amateur drone can be remarkably reduced by optimizing the positions of the surveillance drones. Finally, we conclude the article with a general discussion about the future work and possible challenges in aerial surveillance systems.
Autors: Mohammad Mahdi Azari;Hazem Sallouha;Alessandro Chiumento;Sreeraj Rajendran;Evgenii Vinogradov;Sofie Pollin;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 51 - 57
Publisher: IEEE
 
» KID Model-Driven Things-Edge-Cloud Computing Paradigm for Traffic Data as a Service
Abstract:
The development of intelligent traffic systems can benefit from the pervasiveness of IoT technologies. In recent years, increasing numbers of devices are connected to the IoT, and new kinds of heterogeneous data sources have been generated. This leads to traffic systems that exist in extended dimensions of data space. Although cloud computing can provide essential services that reduce the computational load on IoT devices, it has its limitations: high network bandwidth consumption, high latency, and high privacy risks. To alleviate these problems, edge computing has emerged to reduce the computational load for achieving TDaaS in a dynamic way. However, how to drive all edge servers' work and meet data service requirements is still a key issue. To address this challenge, this article proposes a novel three-level transparency-of-traffic-data service framework, that is, a KID-driven TEC computing paradigm. Its aim is to enable edge servers to cooperatively work with a cloud server. A case study is presented to demonstrate the feasibility of the proposed new computing paradigm with associated mechanisms. The performance of the proposed system is also compared to other methods.
Autors: Bowen Du;Runhe Huang;Zhipu Xie;Jianhua Ma;Weifeng Lv;
Appeared in: IEEE Network
Publication date: Jan 2018, volume: 32, issue:1, pages: 34 - 41
Publisher: IEEE
 
» Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Material
Abstract:
Kilohertz electrical stimulation (KES) has enabled a novel new paradigm for spinal cord and peripheral nerve stimulation to treat a variety of neurological diseases. KES can excite or inhibit nerve activity and is used in many clinical devices today. However, the impact of different electrode materials on the efficacy of KES is unknown. We investigated the effect of different electrode materials and their respective charge injection mechanisms on KES nerve block thresholds using 20- and 40-kHz current-controlled sinusoidal KES waveforms. We evaluated the nerve block threshold and the power requirements for achieving an effective KES nerve block. In addition, we evaluated potential effects on the onset duration and recovery of normal conduction after delivery of KES. We found that thresholds and the onset and recovery of KES nerve block are not a function of the electrode material. In contrast, the power dissipation varies among electrode materials and is a function of the materials’ properties at high frequencies. We conclude that materials with a proven track record of chronic stability, both for the tissue and electrode, are suitable for developing KES nerve block therapies.
Autors: Yogi A. Patel;Brian S. Kim;Robert J. Butera;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 11 - 17
Publisher: IEEE
 
» L1-Norm Distance Linear Discriminant Analysis Based on an Effective Iterative Algorithm
Abstract:
Recent works have proposed two L1-norm distance measure-based linear discriminant analysis (LDA) methods, L1-LD and LDA-L1, which aim to promote the robustness of the conventional LDA against outliers. In LDA-L1, a gradient ascending iterative algorithm is applied, which, however, suffers from the choice of stepwise. In L1-LDA, an alternating optimization strategy is proposed to overcome this problem. In this paper, however, we show that due to the use of this strategy, L1-LDA is accompanied with some serious problems that hinder the derivation of the optimal discrimination for data. Then, we propose an effective iterative framework to solve a general L1-norm minimization–maximization (minmax) problem. Based on the framework, we further develop a effective L1-norm distance-based LDA (called L1-ELDA) method. Theoretical insights into the convergence and effectiveness of our algorithm are provided and further verified by extensive experimental results on image databases.
Autors: Qiaolin Ye;Jian Yang;Fan Liu;Chunxia Zhao;Ning Ye;Tongming Yin;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 114 - 129
Publisher: IEEE
 
» Latent-Class Hough Forests for 6 DoF Object Pose Estimation
Abstract:
In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributions at the leaf nodes as latent variables. During testing we infer by iteratively updating these distributions, providing accurate estimation of background clutter and foreground occlusions and, thus, better detection rate. Furthermore, as a by-product, our Latent-Class Hough Forests can provide accurate occlusion aware segmentation masks, even in the multi-instance scenario. In addition to an existing public dataset, which contains only single-instance sequences with large amounts of clutter, we have collected two, more challenging, datasets for multiple-instance detection containing heavy 2D and 3D clutter as well as foreground occlusions. We provide extensive experiments on the various parameters of the framework such as patch size, number of trees and number of iterations to infer class distributions at test time. We also evaluate the Latent-Class Hough Forests on all datasets where we outperform state of the art methods.
Autors: Alykhan Tejani;Rigas Kouskouridas;Andreas Doumanoglou;Danhang Tang;Tae-Kyun Kim;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 119 - 132
Publisher: IEEE
 
» Latent-Data Privacy Preserving With Customized Data Utility for Social Network Data
Abstract:
Social network data can help with obtaining valuable insight into social behaviors and revealing the underlying benefits. New big data technologies are emerging to make it easier to discover meaningful social information from market analysis to counterterrorism. Unfortunately, both diverse social datasets and big data technologies raise stringent privacy concerns. Adversaries can launch inference attacks to predict sensitive latent information, which is unwilling to be published by social users. Therefore, there is a tradeoff between data benefits and privacy concerns. In this paper, we investigate how to optimize the tradeoff between latent-data privacy and customized data utility. We propose a data sanitization strategy that does not greatly reduce the benefits brought by social network data, while sensitive latent information can still be protected. Even considering powerful adversaries with optimal inference attacks, the proposed data sanitization strategy can still preserve both data benefits and social structure, while guaranteeing optimal latent-data privacy. To the best of our knowledge, this is the first work that preserves both data benefits and social structure simultaneously and combats against powerful adversaries.
Autors: Zaobo He;Zhipeng Cai;Jiguo Yu;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 665 - 673
Publisher: IEEE
 
» Layout and Interconnect Optimization for Low-Power and High-Sensitivity Operation of $E$ -Band SiGe HBT Frequency Dividers
Abstract:
A layout and interconnect optimization techniques for low-power and high-sensitivity performance of static frequency dividers in -band is reported. The layout optimization provides optimal transistor placement and identifies critical interconnects, which allows to reduce their parasitics. These measures provide high operation frequency and good sensitivity of the divider without a need of investing additional dc current.
Autors: Aleksey Dyskin;Parisa Harati;Ingmar Kallfass;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 67 - 69
Publisher: IEEE
 
» LDSScanner: Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets
Abstract:
Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the axis and axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS ( axis) and the variation of LTS in structures (the combination of axis and axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.
Autors: Jiazhi Xia;Fenjin Ye;Wei Chen;Yusi Wang;Weifeng Chen;Yuxin Ma;Anthony K.H. Tung;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 236 - 245
Publisher: IEEE
 
» Learning From Cross-Domain Media Streams for Event-of-Interest Discovery
Abstract:
Every day, vast amounts of data are uploaded to various social-sharing websites. Each social-sharing website has its own media dataset. Recently, mining media datasets has shown great potential for our daily lives, e.g., earthquake detection. Generally, different datasets have different characteristics. Combining different datasets is capable of achieving better performance than using any dataset independently, particularly if the datasets can compensate for each other. The resulting performance, however, depends on the fusion method. Effectively combining different datasets is challenging. As a solution to this challenge, this paper presents a generic two-stage framework for events of interest. Specifically, the first stage normalizes the contents of different datasets to make them comparable; then, the second stage combines the normalized contents for a ranked event list using graph-based algorithms. Practically, this paper unifies a flow-based media dataset and a check-in-based media dataset. Based on the precision for the top n events, the experimental results demonstrate that the proposed framework can achieve better performance in finding events associated with sports, local festivals, concerts, and exhibitions compared with a state-of-the-art approach that uses one dataset alone.
Autors: Wen-Yu Lee;Winston H. Hsu;Shin’ichi Satoh;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 142 - 154
Publisher: IEEE
 
» Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
Abstract:
Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Therefore, in this article, we first introduce deep learning for IoTs into the edge computing environment. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. In the performance evaluation, we test the performance of executing multiple deep learning tasks in an edge computing environment with our strategy. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT.
Autors: He Li;Kaoru Ota;Mianxiong Dong;
Appeared in: IEEE Network
Publication date: Jan 2018, volume: 32, issue:1, pages: 96 - 101
Publisher: IEEE
 
» Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging
Abstract:
The integration of compressed sensing and parallel imaging (CS-PI) has shown an increased popularity in recent years to accelerate magnetic resonance (MR) imaging. Among them, calibration-free techniques have presented encouraging performances due to its capability in robustly handling the sensitivity information. Unfortunately, existing calibration-free methods have only explored joint-sparsity with direct analysis transform projections. To further exploit joint-sparsity and improve reconstruction accuracy, this paper proposes to Learn joINt-sparse coDes for caliBration-free parallEl mR imaGing (LINDBERG) by modeling the parallel MR imaging problem as an –– minimization objective with an norm constraining data fidelity, Frobenius norm enforcing sparse representation error and the mixed norm triggering joint sparsity across multichannels. A corresponding algorithm has been developed to alternatively update the sparse representation, sensitivity encoded images and K-space data. Then, the final image is produced as the square root of sum of squares of all channel images. Experimental results on both physical phantom and in vivo data sets show that the proposed method is comparable and even superior to state-of-the-art CS-PI reconstruction approaches. Specifically, LINDBERG has presented strong capability in suppressing noise and artifacts while reconstructing MR images from highly undersampled multichannel measurements.
Autors: Shanshan Wang;Sha Tan;Yuan Gao;Qiegen Liu;Leslie Ying;Taohui Xiao;Yuanyuan Liu;Xin Liu;Hairong Zheng;Dong Liang;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 251 - 261
Publisher: IEEE
 
» Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification
Abstract:
In this paper, we propose a multiscale deep feature learning method for high-resolution satellite image scene classification. Specifically, we first warp the original satellite image into multiple different scales. The images in each scale are employed to train a deep convolutional neural network (DCNN). However, simultaneously training multiple DCNNs is time-consuming. To address this issue, we explore DCNN with spatial pyramid pooling (SPP-net). Since different SPP-nets have the same number of parameters, which share the identical initial values, and only fine-tuning the parameters in fully connected layers ensures the effectiveness of each network, thereby greatly accelerating the training process. Then, the multiscale satellite images are fed into their corresponding SPP-nets, respectively, to extract multiscale deep features. Finally, a multiple kernel learning method is developed to automatically learn the optimal combination of such features. Experiments on two difficult data sets show that the proposed method achieves favorable performance compared with other state-of-the-art methods.
Autors: Qingshan Liu;Renlong Hang;Huihui Song;Zhi Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 117 - 126
Publisher: IEEE
 
» Learning Traversability From Point Clouds in Challenging Scenarios
Abstract:
This paper aims at evaluating the capabilities to detect road traversability in urban and extra-urban scenarios of support vector machine-based classifiers that use local descriptors extracted from point cloud data. The evaluation of the proposed classifiers is carried out by using four different kernels and comparing five point descriptors obtained from geometric and appearance-based features. A comparison among the performance of descriptors individually has demonstrated that the normal vector-based descriptor achieves an accuracy of 88%, outperforming by about 6%–15% all the other considered ones. To further improve the interpretation capabilities, the space of features is augmented by merging the components of each point descriptor, reaching 92% classification accuracy. A set of test scenarios have been acquired during an extensive experimental campaign using an all-terrain vehicle. Tests on real data show high classification performance for road scenarios and rural environments; the generality of the method makes it applicable for different types of mobile robots including, but not limited to, autonomous vehicles.
Autors: Mauro Bellone;Giulio Reina;Luca Caltagirone;Mattias Wahde;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 296 - 305
Publisher: IEEE
 
» Learning-Based Caching in Cloud-Aided Wireless Networks
Abstract:
This letter studies content caching in cloud-aided wireless networks, where small cell base stations with limited storage are connected to the cloud via limited capacity fronthaul links. By formulating a utility (inverse of service delay) maximization problem, we propose a cache update algorithm based on spatio-temporal traffic demands. To account for the large number of contents, we propose a content clustering algorithm to group similar contents. Subsequently, with the aid of regret learning at small cell base stations and the cloud, each base station caches contents based on the learned content popularity subject to its storage constraints. The performance of the proposed caching algorithm is evaluated for sparse and dense environments, while investigating the tradeoff between global and local class popularity. Simulation results show 15% and 40% gains in the proposed method compared to various baselines.
Autors: Syed Tamoor-ul-Hassan;Sumudu Samarakoon;Mehdi Bennis;Matti Latva-aho;Choong Seon Hong;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 137 - 140
Publisher: IEEE
 
» Least Square Error Precoders for Massive MIMO With Signal Constraints: Fundamental Limits
Abstract:
This paper proposes nonlinear least square error (LSE) precoders for multiuser MIMO broadcast channels. The LSE precoders are designed such that the discrete output signals are from a predefined set. This predefined set allows us to model several signal constraints such as peak power constraint, constant envelope, and discrete constellations. We study the large-system performance of these precoders via the replica method from statistical physics, and derive a closed-form expression for the asymptotic distortion. Our results demonstrate that an LSE precoder with the output peak-to-average power ratio of 3 dB can perform similar to the regularized zero forcing (RZF) precoder. As the peak-to-average power ratio reduces to one, the constant envelope precoder is recovered. The investigations show that the performance of the RZF precoder is achieved by a constant envelope precoder with 20% additional transmit antennas. For -phase shift keying constellations, our analysis gives a lower bound on the asymptotic distortion which is tight for moderate antenna-to-user ratios and deviates as the ratio grows. We improve this bound by deriving the replica solution under one-step of replica symmetry breaking. Our numerical investigations for this case show that the bound is tight for antenna-to-user ratios less than 5.
Autors: Mohammad Ali Sedaghat;Ali Bereyhi;Ralf R. Müller;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 667 - 679
Publisher: IEEE
 
» Least Squares Estimation Based SDP Cuts for SOCP Relaxation of AC OPF
Abstract:
It has been known that the second-order conic programming (SOCP) relaxation of an alternating current optimal power flow (ac OPF) problem is a computationally friendly formulation, whereas the semidefinite programming (SDP) relaxation is a theoretically stronger one. This paper presents a method to strengthen the (SOCP) relaxation by generating new cutting planes, i.e., valid inequalities, using SDP relaxation, which remove SOCP solutions that are infeasible to SDP formulation. This new method relies on solving a least square estimation (LSE) problem for every cycle in a cycle basis. General feasibility cutting plane method is also employed for cuts generation. We show that the SDP cuts generated by the LSE method are indeed feasibility cuts. Numerical results show that those new cuts can effectively reduce the search space and lead to a tighter relaxation. The new cuts are comparable to the SDP cuts in [1]. Case studies on systems with several buses to thousands buses have demonstrated the method is also scalable.
Autors: Zhixin Miao;Lingling Fan;Hossein Ghassempour Aghamolki;Bo Zeng;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 241 - 248
Publisher: IEEE
 
» Lessons Learned from Protection and Control Schemes Testing: The Results of Multiple Trials Using IEC 61850 Goose Messaging at an Oil Refinery
Abstract:
Several Trials for Protection and Control Schemes based on the International Electrotechnical Commission (IEC) 61850 standard were recently implemented for the new electrical system at a U.S. oil refinery. IEC 61850, generic object-oriented substation event (GOOSE) messaging, was used for several schemes, including transfer tripping, breaker failure, islanding detection, remote synchronizing, automatic restoration, manual transfer, and load shedding. Site acceptance tests validated the operation of the protection and control schemes. Bench testing was also performed for the load-shedding scheme using a power-system simulator. All of the testing focused on verifying scheme operations during normal operation and failure modes. The experience gained during early project trials influenced the design and testing of subsequent schemes. This article describes the bench and site acceptance testing approaches used and presents example tests along with their relevant results and the lessons learned.
Autors: Jared Mraz;Aaron Cowan;Keith Gray;Kirti S. Shah;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 60 - 70
Publisher: IEEE
 
» Leveraging Accuracy-Uncertainty Tradeoff in SVM to Achieve Highly Accurate Outage Predictions
Abstract:
This letter proposes a three-dimensional Support Vector Machine (SVM) for power grid component outage prediction, and furthermore leverages its accuracy–uncertainty tradeoff to achieve highly accurate results. The model is developed based on three distinct features of component deterioration, distance from the extreme event, and the intensity of the extreme event, and is analytically investigated to exhibit its acceptable performance.
Autors: Rozhin Eskandarpour;Amin Khodaei;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1139 - 1141
Publisher: IEEE
 
» Leveraging Software-Defined Networking for Incident Response in Industrial Control Systems
Abstract:
In the past decade, the security of industrial control systems has emerged as a research priority in order to safeguard our critical infrastructures. A large number of research efforts have focused on intrusion detection in industrial networks; however, few of them discuss what to do after an intrusion has been detected. Because the safety of most of these control systems is time sensitive, we need new research on automatic incident response. This article shows how software-defined networks and network function virtualization can facilitate automatic incident response to a variety of attacks against industrial networks. It also presents a prototype of an incident-response solution that detects and responds automatically to sensor attacks and controller attacks. This work shows the promise that cloud-enabled software-defined networks and virtual infrastructures hold as a way to provide novel defense-in-depth solutions for industrial systems. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Autors: Andrés F. Murillo Piedrahita;Vikram Gaur;Jairo Giraldo;Álvaro A. Cárdenas;Sandra Julieta Rueda;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 44 - 50
Publisher: IEEE
 
» Lidar-Based Gait Analysis and Activity Recognition in a 4D Surveillance System
Abstract:
This paper presents new approaches for gait and activity analysis based on data streams of a rotating multibeam (RMB) Lidar sensor. The proposed algorithms are embedded into an integrated 4D vision and visualization system, which is able to analyze and interactively display real scenarios in natural outdoor environments with walking pedestrians. The main focus of the investigations is gait-based person reidentification during tracking and recognition of specific activity patterns, such as bending, waving, making phone calls, and checking the time looking at wristwatches. The descriptors for training and recognition are observed and extracted from realistic outdoor surveillance scenarios, where multiple pedestrians are walking in the field of interest following possibly intersecting trajectories; thus, the observations might often be affected by occlusions or background noise. Since there is no public database available for such scenarios, we created and published a new Lidar-based outdoor gait and activity data set on our website that contains point cloud sequences of 28 different persons extracted and aggregated from 35-min-long measurements. The presented results confirm that both efficient gait-based identification and activity recognition are achievable in the sparse point clouds of a single RMB Lidar sensor. After extracting the people trajectories, we synthesized a free-viewpoint video, in which moving avatar models follow the trajectories of the observed pedestrians in real time, ensuring that the leg movements of the animated avatars are synchronized with the real gait cycles observed in the Lidar stream.
Autors: Csaba Benedek;Bence Gálai;Balázs Nagy;Zsolt Jankó;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 101 - 113
Publisher: IEEE
 
» Lifetime Estimation of Discrete IGBT Devices Based on Gaussian Process
Abstract:
Discrete package insulated gate bipolar transistor (IGBT) devices are a popular choice for low-power converters. Although IGBT power modules used in high-power applications have recently been studied in the literature, there are major knowledge gaps regarding reliability and lifetime estimation of discrete devices. In this paper, on-state collector–emitter voltage drop variations are characterized for discrete IGBT devices exposed to cyclic thermal stresses. Variations in are carefully identified and classified depending on different aging mechanisms, stress levels, and device structures. A probabilistic framework for remaining useful lifetime (RUL) estimation based on the knowledge obtained by accelerated aging experiments for real-time RUL estimation has been proposed. Specifically, the proposed model uses Gaussian process regression (GPR) for applying a Bayesian inference (BI) on RUL estimation of the device under test. Using BI reduces the uncertainty associated with RUL estimation and leads to more accurate results. This concept is also tested by comparing the classical maximum-likelihood estimation and GPR estimation results with the ones obtained by accelerated aging tests.
Autors: Syed Huzaif Ali;Mehrdad Heydarzadeh;Serkan Dusmez;Xiong Li;Anant S. Kamath;Bilal Akin;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Jan 2018, volume: 54, issue:1, pages: 395 - 403
Publisher: IEEE
 
» Light Field Reconstruction Using Shearlet Transform
Abstract:
In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images (EPI) in shearlet transform domain. The shearlet transform has been specifically modified to handle the straight lines characteristic for EPI. The devised iterative regularization algorithm based on adaptive thresholding provides high-quality reconstruction results for relatively big disparities between neighboring views. The generated densely sampled light field of a given 3D scene is thus suitable for all applications which require light field reconstruction. The proposed algorithm compares favorably against state of the art depth image based rendering techniques and shows superior performance specifically in reconstructing scenes containing semi-transparent objects.
Autors: Suren Vagharshakyan;Robert Bregovic;Atanas Gotchev;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 133 - 147
Publisher: IEEE
 
» Linear Network Coding Over Rings – Part I: Scalar Codes and Commutative Alphabets
Abstract:
Linear network coding over finite fields is a well-studied problem. We consider the more general setting of linear coding for directed acyclic networks with finite commutative ring alphabets. Our results imply that for scalar linear network coding over commutative rings, fields can always be used when the alphabet size is flexible, but other rings may be needed when the alphabet size is fixed. We prove that if a network has a scalar linear solution over some finite commutative ring, then the (unique) smallest such commutative ring is a field. We also show that fixed-size commutative rings are quasi-ordered, such that all the scalar linearly solvable networks over any given ring are also scalar linearly solvable over any higher-ordered ring. We study commutative rings that are maximal with respect to this quasi-order, as they may be considered the best commutative rings of a given size. We prove that a commutative ring is maximal if and only if some network is scalar linearly solvable over the ring, but not over any other commutative ring of the same size. Furthermore, we show that maximal commutative rings are direct products of certain fields specified by the integer partitions of the prime factor multiplicities of the ring’s size. Finally, we prove that there is a unique maximal commutative ring of size if and only if each prime factor of has multiplicity in {1, 2, 3, 4, 6}. As consequences, 1) every finite field is such a maximal ring and 2) for each prime , some network is scalar linearly solvable over a commutative ring of size but not over the field of the same size if and only if .
Autors: Joseph Connelly;Kenneth Zeger;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 274 - 291
Publisher: IEEE
 
» Linear Network Coding Over Rings – Part II: Vector Codes and Non-Commutative Alphabets
Abstract:
In Part I, we studied linear network coding over finite commutative rings and made comparisons to the well-studied case of linear network coding over finite fields. Here, we consider the more general setting of linear network coding over finite (possibly non-commutative) rings and modules. We prove the following results regarding the linear solvability of directed acyclic networks over various finite alphabets. For any network, the following are equivalent: (i) vector linear solvability over some field, (ii) scalar linear solvability over some ring, and (iii) linear solvability over some module. Analogously, the following are equivalent: (a) scalar linear solvability over some field, (b) scalar linear solvability over some commutative ring, and (c) linear solvability over some module whose ring is commutative. Whenever any network is linearly solvable over a module, a smallest such module arises in a vector linear solution for that network over a field. If a network is scalar linearly solvable over some non-commutative ring but not over any commutative ring, then such a non-commutative ring must have size at least 16, and for some networks, this bound is achieved. An infinite family of networks is demonstrated, each of which is scalar linearly solvable over some non-commutative ring but not over any commutative ring. Whenever is prime and , if a network is scalar linearly solvable over some ring of size , then it is also -dimensional vector linearly solvable over the field , but the converse does not necessarily hold. This result is extended to all $kge 1$ when the ring is commutative.
Autors: Joseph Connelly;Kenneth Zeger;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 292 - 308
Publisher: IEEE
 
» Linear Programming Bounds for Entanglement-Assisted Quantum Error-Correcting Codes by Split Weight Enumerators
Abstract:
Linear programming approaches have been applied to derive upper bounds on the size of classical and quantum codes. In this paper, we derive similar results for general quantum codes with entanglement assistance by considering a type of split weight enumerator. After deriving the MacWilliams identities for these enumerators, we are able to prove algebraic linear programming bounds, such as the Singleton bound, the Hamming bound, and the first linear programming bound. Our Singleton bound and Hamming bound are more general than the previous bounds for entanglement-assisted quantum stabilizer codes. In addition, we show that the first linear programming bound improves the Hamming bound when the relative distance is sufficiently large. On the other hand, we obtain additional constraints on the size of Pauli subgroups for quantum codes, which allow us to improve the linear programming bounds on the minimum distance of quantum codes of small length. In particular, we show that there is no or stabilizer code. We also discuss the existence of some entanglement-assisted quantum stabilizer codes with maximal entanglement. As a result, the upper and lower bounds on the minimum distance of maximal-entanglement quantum stabilizer codes with length up to 20 are significantly improved.
Autors: Ching-Yi Lai;Alexei Ashikhmin;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 622 - 639
Publisher: IEEE
 
» Linking Fine-Grained Locations in User Comments
Abstract:
Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon) for users to post comments on. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and tweets, the problem of disambiguating the mentioned entities in user comments has not received much attention. This paper investigates linking fine-grained locations in Foursquare comments. We demonstrate that the focal location, i.e., the location that a comment is posted on, provides rich contexts for the linking task. To exploit such information, we represent the Foursquare data in a graph, which includes locations, comments, and their relations. A probabilistic model named FocalLink is proposed to estimate the probability that a user mentions a location when commenting on a focal location, by following different kinds of relations. Experimental results show that FocalLink is consistently superior under different collective linking settings.
Autors: Jialong Han;Aixin Sun;Gao Cong;Wayne Xin Zhao;Zongcheng Ji;Minh C. Phan;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Jan 2018, volume: 30, issue:1, pages: 59 - 72
Publisher: IEEE
 
» Liquid Dielectric Resonator Antenna With Circular Polarization Reconfigurability
Abstract:
A novel liquid dielectric resonator antenna with circular polarization (CP) reconfigurability is investigated in this communication. The fluidic dielectric for this design is ethyl acetate () which is held by a container fabricated by 3-D printing technology and excited by a single probe. To realize the CP reconfigurability, the container is designed with two zones: left and right zones. Therefore, the proposed antenna can be switched between two different states: when the liquid solution is injected into the left zone, it can realize left hand CP, on the other hand, if the fluidic dielectric is pumped into the right zone, it can obtain right hand CP. Consequently, the CP reconfigurability is obtained by flowing liquid control of the ethyl acetate solution. For demonstration, the proposed antenna is design at 2.4 GHz for RFID application with a broad impedance bandwidth (SWR < 2) of 35.6% which fully cover the wide axial ratio (AR) bandwidth (AR < 3 dB) of 16.3%. Finally, good agreement is achieved between the measurement and simulation.
Autors: Zhe Chen;Hang Wong;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 444 - 449
Publisher: IEEE
 
» LLR-Distribution-Based Non-Uniform Quantization for RBI-MSD Algorithm in MLC Flash Memory
Abstract:
Multi-level cell (MLC) technique has been widely used to improve the storage capacity of NAND flash memory at the price of sacrificing some storage reliability. As a type of excellent error-correction codes, low-density parity-check (LDPC) codes can significantly enhance the performance of flash memory. However, the conventional decoding algorithms for LDPC codes suffer from the drawback of high complexity. To address this problem, we propose a serial reliability-based iterative min-sum decoding (RBI-MSD) algorithm for LDPC-coded MLC flash memory systems to strike a desirable trade-off between the performance and complexity. Furthermore, we conceive a novel log-likelihood-ratio (LLR)-distribution-based non-uniform quantization method for the RBI-MSD algorithm. Unlike conventional quantization methods, the proposed non-uniform quantization method substantially exploits the distribution characteristics of channel initial LLRs in MLC flash memory. Simulation results indicate that the proposed non-uniform quantization method not only exhibits more excellent error performance than the conventional non-uniform and uniform counterparts, but also is applicable to other RBI decoding algorithms.
Autors: Shijie Ouyang;Guojun Han;Yi Fang;Wenjie Liu;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 45 - 48
Publisher: IEEE
 
» Load-Balancing Scheme With Small-Cell Cooperation for Clustered Heterogeneous Cellular Networks
Abstract:
In this paper, a joint user association (UA) scheme with JP-CoMP using a hybrid self-organizing network (SON) is proposed for a practical clustered heterogeneous cellular network (cHCN) to maximize the network-wide proportional fairness among users. The cell range expansion and the enhanced intercell interference coordination have been considered as key items in the long-term evolution-advanced to offload macrocell users to small-cell base stations (sBSs). However, in a cHCN where sBSs are not distributed at random but are clustered instead, the coverage of inner sBSs in a small-cell cluster would be hardly expanded and an increased bias may result in much poor link quality as well as much higher load in outer sBSs. Thus, the load-balancing capability becomes much lower than expected in a cHCN. In order to cope with such a problem, a network architecture and protocol for the cHCN is suggested, and a feasible suboptimal iterative algorithm for determining the joint UA solution of the proposed hybrid SON is provided. It is shown that the proposed hybrid SON scheme with the proposed joint UA solution is very effective in handling the load balancing in a practical cHCN not only improving the performance of the inner sBS users by reducing the intercell interference, especially for intratier offloaded users, but also enabling more aggressive intertier offloading by effectively improving the link quality of cluster edge users without causing an unnecessary resource waste.
Autors: Jin-Bae Park;Kwang Soon Kim;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 633 - 649
Publisher: IEEE
 
» Loading the Third Harmonic: A Linear and Efficient Post-Matching Doherty PA
Abstract:
Among the most exciting parts of the IEEE Microwave Theory and Techniques Society (MTT-S) 2017 International Microwave Symposium (IMS2017) was the "High-Efficiency Power Amplifier" Student Design Competition (SDC) sponsored by Technical Coordinating Committee MTT-5. This competition focuses on RF power amplifiers (PAs) having both high efficiency and linearity. Competitors are required to design, construct, and measure a high-efficiency PA with a specified linearity at a frequency of their choice between 1 and 10 GHz. The winner is determined by a figure of merit (FOM), with other requirements [1] that must also be satisfied:
Autors: Xin Yu Zhou;Wing Shing Chan;Derek Ho;Shao Yong Zheng;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 99 - 105
Publisher: IEEE
 
» Local Gradient Hexa Pattern: A Descriptor for Face Recognition and Retrieval
Abstract:
Local descriptors used in face recognition are robust in a sense that these descriptors perform well in varying pose, illumination, and lighting conditions. The accuracy of these descriptors depends on the precision of mapping the relationship that exists in the local neighborhood of a facial image into microstructures. In this paper, a local gradient hexa pattern is proposed that identifies the relationship among the reference pixel and its neighboring pixels at different distances across different derivative directions. Discriminative information exists in the local neighborhood as well as in different derivative directions. The proposed descriptor effectively transforms these relationships into binary micropatterns discriminating inter-class facial images with optimal precision. The recognition and retrieval performance of the proposed descriptor has been compared with state-of-the-art descriptors, namely, local derivative pattern, local tetra pattern, multiblock local binary pattern, and local vector pattern over the most challenging and benchmark facial image databases, i.e., Cropped Extended Yale B, CMU-PIE, color-FERET, LFW, and Ghallager database. The proposed descriptor has better recognition as well as retrieval rates compared with state-of-the-art descriptors.
Autors: Soumendu Chakraborty;Satish Kumar Singh;Pavan Chakraborty;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 171 - 180
Publisher: IEEE
 
» Local Oscillator Phase-Dependent Linearized Mixer Modeling Based on Large-Signal Vector Measurements
Abstract:
This paper presents a broadband poly-harmonic behavioral model for microwave mixers operating in the linear regime. It is extracted from large-signal vector measurements and predicts the response with respect to an arbitrary local oscillator (LO) phase. The model is capable of estimating the performance of the converted signals and the main mixing products for an intermediate frequency that spans within an a priori defined bandwidth. This paper gives a detailed model analytical treatment along with a discussion of its properties and the description of the characterization method. The model validation is achieved by the characterization of a subharmonic mixer implemented in the hybrid technology that operates with a 2.229-GHz LO, an intermediate frequency bandwidth of 732–754 MHz, and a corresponding radio frequency bandwidth of 5.191–5.211 GHz. Independent experimental validation is achieved by an image rejection mixer composed of two nominally identical mixers, individually characterized by the proposed technique. Validation is concluded with experimental data, demonstrating the model’s capability to deal with a phase-modulated LO signal.
Autors: Alessandro Cidronali;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 81 - 90
Publisher: IEEE
 
» Localization of Multiple Targets With Identical Radar Signatures in Multipath Environments With Correlated Blocking
Abstract:
This paper addresses the problem of localizing an unknown number of targets, all having the same radar signature, by a distributed MIMO radar consisting of single antenna transmitters and receivers that cannot determine directions of departure and arrival. Furthermore, we consider the presence of multipath propagation and the possible (correlated) blocking of the direct paths (going from the transmitter and reflecting off a target to the receiver). In its most general form, this problem can be cast as a Bayesian estimation problem where every multipath component is accounted for. However, when the environment map is unknown, this problem is ill-posed and hence, a tractable approximation is derived where only direct paths are accounted for. In particular, we take into account the correlated blocking by scatterers in the environment which appears as a prior term in the Bayesian estimation framework. A sub-optimal polynomial-time algorithm to solve the Bayesian multi-target localization problem with correlated blocking is proposed and its performance is evaluated using simulations. We found that when correlated blocking is severe, assuming the blocking events to be independent and having constant probability (as was done in previous papers) resulted in poor detection performance, with false alarms more likely to occur than detections.
Autors: Sundar Aditya;Andreas F. Molisch;Naif Rabeah;Hatim Mohammed Behairy;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 606 - 618
Publisher: IEEE
 
» Location-Based Millimeter Wave Multi-Level Beamforming Using Compressive Sensing
Abstract:
In this letter, a novel millimeter wave (mmWave) multi-level beamforming (BF) is proposed. User positioning is used for roughly defining the area within which the mobile station (MS) is properly located. Based on this, a multi-level beam search is conducted using compressive sensing-based channel estimation to find out the transmit/receive beams for establishing the mmWave link. The estimated MS location-uncertainty area is used to determine the number of beams along with the beamwidth required for constructing the sensing matrix used in each beam searching level. Mathematical and simulation analysis confirm the superiority of the proposed BF scheme over the conventional ones in both BF complexity and performance.
Autors: Ahmed Abdelreheem;Ehab Mahmoud Mohamed;Hamada Esmaiel;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 185 - 188
Publisher: IEEE
 
» Longitudinal Study of Automatic Face Recognition
Abstract:
The two underlying premises of automatic face recognition are uniqueness and permanence. This paper investigates the permanence property by addressing the following: Does face recognition ability of state-of-the-art systems degrade with elapsed time between enrolled and query face images? If so, what is the rate of decline w.r.t. the elapsed time? While previous studies have reported degradations in accuracy, no formal statistical analysis of large-scale longitudinal data has been conducted. We conduct such an analysis on two mugshot databases, which are the largest facial aging databases studied to date in terms of number of subjects, images per subject, and elapsed times. Mixed-effects regression models are applied to genuine similarity scores from state-of-the-art COTS face matchers to quantify the population-mean rate of change in genuine scores over time, subject-specific variability, and the influence of age, sex, race, and face image quality. Longitudinal analysis shows that despite decreasing genuine scores, 99% of subjects can still be recognized at 0.01% FAR up to approximately 6 years elapsed time, and that age, sex, and race only marginally influence these trends. The methodology presented here should be periodically repeated to determine age-invariant properties of face recognition as state-of-the-art evolves to better address facial aging.
Autors: Lacey Best-Rowden;Anil K. Jain;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 148 - 162
Publisher: IEEE
 
» Low Complexity Training Methods for Common Mode Aided Cancellation of Intermittent Alien Noise in Downstream VDSL
Abstract:
The adoption of precoding (vectoring) in VDSL2 at the central office has resulted in mitigation of the far-end crosstalk seen at the customer premises equipment (CPE). As a result, alien noise (including repetitive impulse noise) is the new dominant source of impairment for downstream VDSL. At the CPE, an additional common mode (CM) sensor can sense the electromagnetically coupled alien noise signal, which can then be used to cancel the alien noise coupling into the differential mode signal. The intermittent and repetitive nature of the noise sources necessitates that the CM sensor based noise cancellation algorithm be capable of training and adapting during data mode in the presence of the useful data signal, since the presence of alien noise cannot be guaranteed during the modem training phase. In this paper, we propose a novel two-stage frequency domain algorithm based on a per-tone cancellation model for this purpose. The proposed algorithm outperforms previously proposed time domain algorithms in terms of convergence speed in many practical scenarios due to the decision directed nature of the proposed algorithm. We also analyse the theoretical convergence of the algorithm, which is also validated by the simulation experiments.
Autors: Ramanjit Ahuja;Pravesh Biyani;Surendra Prasad;
Appeared in: IEEE Transactions on Communications
Publication date: Jan 2018, volume: 66, issue:1, pages: 290 - 301
Publisher: IEEE
 
» Low PAPR FBMC
Abstract:
Unlike single carrier-frequency division multiple access (SC-FDMA), just combining discrete Fourier transform (DFT) spreading and filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) results in only marginal peak to average power ratio (PAPR) reduction. To utilize the single carrier effect of DFT spreading, a special condition of the coefficients at each subcarrier’s in-phase and quadrature-phase (IQ) channels should be satisfied. As a starting point, we first derive this condition, which we call the identically-time-shifted-multicarrier (ITSM) condition. Then, based on this condition, we propose a new type of FBMC for low PAPR. The main features of the proposed scheme are summarized as follows. First, in order to further enhance the amount of PAPR reduction, we generate the four candidate versions of the DFT-spread and ITSM-conditioned FBMC waveform and select the one with minimum peak power. Even with multiple candidate generation, the major computation parts, such as DFT and IDFT are shared and need to be performed only once, unlike the conventional side information (SI)-based PAPR reduction schemes. Consequently, with a fractional complexity overhead compared with the previous DFT-spread FBMC, the proposed scheme achieves a PAPR reduction comparable to that of SC-FDMA. Second, the proposed scheme transmits only two bit SI per data block consisting of multiple FBMC-OQAM symbols. Hence, the SI overhead is significantly low compared with the usual SI-based schemes, such as selective mapping or partial transmit sequence.
Autors: Dongjun Na;Kwonhue Choi;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 182 - 193
Publisher: IEEE
 
» Low-Complexity Priority-Aware Interference-Avoidance Scheduling for Multi-user Coexisting Wireless Networks
Abstract:
In this paper, the priority-aware interference-avoidance scheduling for multi-user coexisting wireless networks with heterogeneous traffic demands is addressed. Both admission control and throughput maximization for admitted users are studied. These problems are addressed by a proposed sequential solution framework where at each step a large-scale linear program with a large number of variables is required to be solved. To efficiently solve the large-scale program, an accelerated column generation based method is proposed. In the proposed method, an efficient greedy initialization algorithm is first put forward by exploiting the proposed solution structure. After that, both upper and lower bounds on the optimal objective function of each optimization problem are derived, which are used to significantly alleviate the dependence of the whole solution procedure on deriving optimality of problems. Simulation results show that the proposed algorithm can effectively and efficiently handle the coexistence of multiple users with heterogeneous priorities and traffic demands.
Autors: Shiwei Huang;Jun Cai;Hongbin Chen;Feng Zhao;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 112 - 126
Publisher: IEEE
 
» Low-Cost Multimode Patch Antenna for Dual MIMO and Enhanced Localization Use
Abstract:
This communication proposes a simple, low-cost multimode patch antenna combining good multi-in multi-out (MIMO) performance with precise angle of arrival (AoA) estimation. The AoA is based on the monopulse antenna concept; however, unlike in radar applications, the necessity for complex circuitry is replaced by the intrinsic properties of even and odd resonant patch modes. This capability is advantageous for future “Internet of Things” antennas, embedded into low-cost and size-constrained devices. The envelope correlation coefficient, measured in an anechoic chamber, is below 1.5%, ensuring good MIMO performance. An exemplary addition to localization algorithm exploiting antenna properties is demonstrated.
Autors: A. Narbudowicz;Max J. Ammann;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 405 - 408
Publisher: IEEE
 
» Low-Cost Pseudoasynchronous Circuit Design Style With Reduced Exploitable Side Information
Abstract:
Leakage of information through the power supply current has become a major factor in logic design. In this paper, a low cost and simple to employ design methodology dubbed pseudoasynchronous is presented. This design style combines the security advantages of asynchronous circuits with the ease of synchronous circuit design. Randomization and data-dependencies (DD) are utilized to hide information leakage from the current dissipation, and hence making the critical synchronization of power supply current traces hard to do. In addition, randomization and DD are utilized for both time-domain hiding of information leakage during the active region (dynamic currents) and for amplitude-domain hiding of information leakage during the static-region (leakage currents). The main advantages of this new approach are low area cost, reduced signal, and increased noise. Circuit-level analyses show that it is harder to exploit the information leakage from internal signals of the proposed design than from CMOS-based synchronous designs or other forms of time-domain hiding countermeasures.
Autors: Itamar Levi;Alexander Fish;Osnat Keren;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 82 - 95
Publisher: IEEE
 
» Low-Frequency Drain Noise Characterization and TCAD Physical Simulations of GaN HEMTs: Identification and Analysis of Physical Location of Traps
Abstract:
In this letter, an investigation of the low-frequency (LF) drain noise characteristics of the GaN/ AlGaN/GaN HEMT grown on a SiC substrate has been performed. LF drain noise measurements are performed over the frequency range of 20 Hz–1 MHz by varying chuck temperatures ( between 25°C and 100°C. Furthermore, we present the 2-D TCAD physical simulation analysis of this device. TCAD simulation model has been calibrated using the measured device characteristics, and then, using the calibrated model, LF drain noise simulations have been performed. A good match is observed between drain noise measurements and simulation results, and this physically confirms that two acceptor-like traps with apparent activation energies of 0.51 and 0.57 eV, respectively, below the conduction band are located in the GaN buffer.
Autors: Nandha Kumar Subramani;Julien Couvidat;Ahmad Al Hajjar;Jean-Christophe Nallatamby;Raymond Quéré;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 107 - 110
Publisher: IEEE
 
» Low-PAPR Layered/Enhanced ACO-SCFDM for Optical-Wireless Communications
Abstract:
In this letter, we propose layered/enhanced asymmetrically clipped optical single-carrier frequency-division multiplexing (L/E-ACO-SCFDM) for optical-wireless communications. L/E-ACO-SCFDM has a lower computational complexity and peak-to-average power ratio (PAPR) than L/E-ACO orthogonal frequency-division multiplexing (L/E-ACO-OFDM). The computational complexity of the simplified transmitter in L/E-ACO-SCFDM with layers is , which is lower than the computational complexity of in L/E-ACO-OFDM. At a complementary cumulative distribution function of , the PAPR of L/E-ACO-SCFDM is approximately 4.2, 3.4, and 2.7 dB lower than that of L/E-ACO-OFDM for 2, 3, and 4 layers, respectively. The simulation results indicate that L/E-ACO-SCFDM has better performance than L/E-ACO-OFDM under the transmitter nonlinearity and multipath fading.
Autors: Ji Zhou;Qi Wang;Qixiang Cheng;Mengqi Guo;Yueming Lu;Aiying Yang;Yaojun Qiao;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 165 - 168
Publisher: IEEE
 
» Low-Rank Plus Sparse Decomposition and Localized Radon Transform for Ship-Wake Detection in Synthetic Aperture Radar Images
Abstract:
The problem in obtaining stable motion estimation of maritime targets is that sea clutter makes wake structure detection and reconnaissance difficult. This letter presents a complete procedure for the automatic estimation of maritime target motion parameters by evaluating the generated Kelvin waves detected in synthetic aperture radar (SAR) images. The algorithm consists in evaluating a dual-stage low-rank plus sparse decomposition (LRSD) assisted by Radon transform (RT) for clutter reduction, sparse object detection, precise wake inclination estimation, and Kelvin wave spectral analysis. The algorithm is based on the robust principal component analysis (RPCA) implemented by convex programming. The LRSD algorithm permits the extrapolation of sparse objects of interest consisting of the maritime targets and the Kelvin pattern from the unchanging low-rank background. This dual-stage RPCA and RT applied to SAR surveillance permits fast detection and enhanced motion parameter estimation of maritime targets.
Autors: Filippo Biondi;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 117 - 121
Publisher: IEEE
 
» Low-RCS Monopolar Patch Antenna Based on a Dual-Ring Metamaterial Absorber
Abstract:
In this letter, a novel ring-type layout of metamaterial absorber (MA) is investigated for the first time. Three-layer MA unit cell is duplicated along the ring lattices to obtain the proposed dual-ring MA structure, which possesses desirable electromagnetic wave absorbing characteristics. A center-fed circular patch antenna (CPA) coupled with the dual-ring MA is presented to produce a monopole-like radiation pattern and reduce the in-band radar cross section (RCS). MA array acts as an absorber and a radiator simultaneously in this integrated antenna. Both the simulated and measured results demonstrate that compared with the CPA with an annular ring, the in-band RCS of the proposed antenna is dramatically reduced without degradation of antenna radiation performance.
Autors: Junyi Ren;Shuxi Gong;Wen Jiang;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Jan 2018, volume: 17, issue:1, pages: 102 - 105
Publisher: IEEE
 
» LQG Control With Minimum Directed Information: Semidefinite Programming Approach
Abstract:
We consider a discrete-time linear–quadratic–Gaussian (LQG) control problem, in which Massey's directed information from the observed output of the plant to the control input is minimized, while required control performance is attainable. This problem arises in several different contexts, including joint encoder and controller design for data-rate minimization in networked control systems. We show that the optimal control law is a linear–Gaussian randomized policy. We also identify the state-space realization of the optimal policy, which can be synthesized by an efficient algorithm based on semidefinite programming. Our structural result indicates that the filter–controller separation principle from the LQG control theory and the sensor–filter separation principle from the zero-delay rate-distortion theory for Gauss–Markov sources hold simultaneously in the considered problem. A connection to the data-rate theorem for mean-square stability by Nair and Evans is also established.
Autors: Takashi Tanaka;Peyman Mohajerin Esfahani;Sanjoy K. Mitter;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 37 - 52
Publisher: IEEE
 
» LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks
Abstract:
Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden representation of their sequential input. Researchers interested in better understanding these models have studied the changes in hidden state representations over time and noticed some interpretable patterns but also significant noise. In this work, we present LSTMVis, a visual analysis tool for recurrent neural networks with a focus on understanding these hidden state dynamics. The tool allows users to select a hypothesis input range to focus on local state changes, to match these states changes to similar patterns in a large data set, and to align these results with structural annotations from their domain. We show several use cases of the tool for analyzing specific hidden state properties on dataset containing nesting, phrase structure, and chord progressions, and demonstrate how the tool can be used to isolate patterns for further statistical analysis. We characterize the domain, the different stakeholders, and their goals and tasks. Long-term usage data after putting the tool online revealed great interest in the machine learning community.
Autors: Hendrik Strobelt;Sebastian Gehrmann;Hanspeter Pfister;Alexander M. Rush;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 667 - 676
Publisher: IEEE
 
» Machine Learning for Cognitive Network Management
Abstract:
Over the last decade, a significant amount of effort has been invested on architecting agile and adaptive management solutions in support of autonomic, self-managing networks. Autonomic networking calls for automated decisions for management actions. This can be realized through a set of pre-defined network management policies engineered from human expert knowledge. However, engineering sufficiently accurate knowledge considering the high complexity of today's networking environment is a difficult task. This has been a particularly limiting factor in the practical deployment of autonomic systems. ML is a powerful technique for extracting knowledge from data. However, there has been little evidence of its application in realizing practical management solutions for autonomic networks. Recent advances in network softwarization and programmability through SDN and NFV, the proliferation of new sources of data, and the availability of lowcost and seemingly infinite storage and compute resource from the cloud are paving the way for the adoption of ML to realize cognitive network management in support of autonomic networking. This article is intended to stimulate thought and foster discussion on how to defeat the bottlenecks that are limiting the wide deployment of autonomic systems, and the role that ML can play in this regard.
Autors: Sara Ayoubi;Noura Limam;Mohammad A. Salahuddin;Nashid Shahriar;Raouf Boutaba;Felipe Estrada-Solano;Oscar M. Caicedo;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 158 - 165
Publisher: IEEE
 
» Machining-Based Coverage Path Planning for Automated Structural Inspection
Abstract:
The automation of robotically delivered nondestructive evaluation inspection shares many aims with traditional manufacture machining. This paper presents a new hardware and software system for automated thickness mapping of large-scale areas, with multiple obstacles, by employing computer-aided drawing (CAD)/computer-aided manufacturing (CAM)-inspired path planning to implement control of a novel mobile robotic thickness mapping inspection vehicle. A custom postprocessor provides the necessary translation from CAM numeric code through robotic kinematic control to combine and automate the overall process. The generalized steps to implement this approach for any mobile robotic platform are presented herein and applied, in this instance, to a novel thickness mapping crawler. The inspection capabilities of the system were evaluated on an indoor mock-inspection scenario, within a motion tracking cell, to provide quantitative performance figures for positional accuracy. Multiple thickness defects simulating corrosion features on a steel sample plate were combined with obstacles to be avoided during the inspection. A minimum thickness mapping error of 0.21 mm and a mean path error of 4.41 mm were observed for a 2 m2 carbon steel sample of 10-mm nominal thickness. The potential of this automated approach has benefits in terms of repeatability of area coverage, obstacle avoidance, and reduced path overlap, all of which directly lead to increased task efficiency and reduced inspection time of large structural assets.

Note to Practitioners—Current industrial robotic inspection approaches largely consist of a manual control of robotic platform motion to desired points, with the aim of producing a number of straight scans for larger areas, often spaced meters apart. The structures featuring large surface area and multiple obstacles are routinely inspected with such manual approaches, which are both labor intensive and error p- one, and do not guarantee acquisition of full area coverage. The presented system addresses these limitations through a combined hardware and software approach. Core to the operation of the system is a fully wireless, differential drive crawler with integrated active ultrasonic wheel probe, to provide remote thickness mapping. Automation of the path generation algorithms is produced using the commercial CAD/CAM software algorithms, and this paper sets out an adaptable methodology for producing a custom postprocessor to convert the exported G-codes to suitable kinematic commands for mobile robotic platforms. The differential drive crawler is used in this paper to demonstrate the process. This approach has benefits in terms of improved industrial standardization and operational repeatability. The inspection capabilities of the system were documented on an indoor mock-inspection scenario, within a motion tracking cell to provide quantitative performance figures for the approach. Future work is required to integrate the on-board positioning strategies, removing the dependence on global systems, for full automated deployment capability.

Autors: Charles Norman Macleod;Gordon Dobie;Stephen Gareth Pierce;Rahul Summan;Maxim Morozov;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 202 - 213
Publisher: IEEE
 
» MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
Abstract:
Android users are constantly threatened by an increasing number of malicious applications (apps), generically called malware. Malware constitutes a serious threat to user privacy, money, device and file integrity. In this paper we note that, by studying their actions, we can classify malware into a small number of behavioral classes, each of which performs a limited set of misbehaviors that characterize them. These misbehaviors can be defined by monitoring features belonging to different Android levels. In this paper we present MADAM, a novel host-based malware detection system for Android devices which simultaneously analyzes and correlates features at four levels: kernel, application, user and package, to detect and stop malicious behaviors. MADAM has been specifically designed to take into account those behaviors that are characteristics of almost every real malware which can be found in the wild. MADAM detects and effectively blocks more than 96 percent of malicious apps, which come from three large datasets with about 2,800 apps, by exploiting the cooperation of two parallel classifiers and a behavioral signature-based detector. Extensive experiments, which also includes the analysis of a testbed of 9,804 genuine apps, have been conducted to show the low false alarm rate, the negligible performance overhead and limited battery consumption.
Autors: Andrea Saracino;Daniele Sgandurra;Gianluca Dini;Fabio Martinelli;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Jan 2018, volume: 15, issue:1, pages: 83 - 97
Publisher: IEEE
 
» Magic Train: Design of Measurement Methods against Bandwidth Inflation Attacks
Abstract:
Bandwidth measurement is important for many network applications and services, such as peer-to-peer networks, video caching and anonymity services. To win a bandwidth-based competition for some malicious purpose, adversarial Internet hosts may falsely announce a larger network bandwidth. Some preliminary solutions have been proposed to this problem. They can either evade the bandwidth inflation by a consensus view (i.e., opportunistic bandwidth measurements) or detect bandwidth frauds via forgeable tricks (i.e., detection through bandwidth's CDF symmetry). However, smart adversaries can easily remove the forgeable tricks and report an equally larger bandwidth to avoid the consensus analyses. To defend against the smart bandwidth inflation frauds, we design magic train, a new measurement method which combines an unpredictable packet train with estimated round-trip time (RTT) for detection. The inflation behaviors can be detected through highly contradictory bandwidth results calculated using different magic trains or a train's different segments, or large deviation between the estimated RTT and the RTT reported by the train's first packet. Being an uncooperative measurement method, magic train can be easily deployed on the Internet. We have implemented the magic train using RAW socket and LibPcap, and evaluated the implementation in a controlled testbed and the Internet. The results have successfully confirmed the effectiveness of magic train in detecting and preventing smart bandwidth inflation attacks.
Autors: Peng Zhou;Rocky K. C. Chang;Xiaojing Gu;Minrui Fei;Jianying Zhou;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Jan 2018, volume: 15, issue:1, pages: 98 - 111
Publisher: IEEE
 
» Magnetic Particle Imaging for Quantification of Vascular Stenoses: A Phantom Study
Abstract:
Magnetic particle imaging (MPI) is a promising new tomographic imaging method to detect the spatial distribution of superparamagnetic iron-oxide nanoparticles (SPIOs). The aim of this paper was to investigate the potential of MPI to quantify artificial stenoses in vessel phantoms. Custom-made stenosis phantoms (length 40 mm; inner diameter 8 mm) with different degrees of stenosis (0%, 25%, 50%, 75%, and 100%) were scanned in a custom-built MPI scanner (in-plane resolution: ~1–1.5 mm and field of view: 65 29 29 mm3). Phantoms were filled with diluted Feru-carbotran [SPIO agent, 5 mmol (Fe)/l]. Each measurement (overall acquisition time: 20 ms per image, 400 averages) was repeated ten times to assess reproducibility. The MPI signal was used for semi-automatic stenosis quantification. Two stenosis evaluation approaches were compared based on the signal intensity profile alongside the stenosis phantoms. Using a novel multi-step image evaluation approach, MPI allowed for accurate quantification of different stenosis grades. While low grade stenoses were slightly over-estimated, high grade stenoses were slightly underestimated. In particular, the 0%, 25%, and 50% stenosis phantoms revealed a 6.2% ± 0.8, 25.7% ± 1.0, and 48.0% ± 1.5 stenosis, respectively. The higher grade 75% stenosis phantom revealed a 73.3% ± 2.8 and the 100% stenosis phantom a 95.8%± 1.9 stenosis. MPI accu- ately visualized and quantified different stenosis grades in vessel phantoms with high reproducibility demonstrating its great potential for fast and radiation-free preclinical cardiovascular imaging.
Autors: S. Herz;P. Vogel;T. Kampf;M. A. Rückert;S. Veldhoen;V. C. Behr;T. A. Bley;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 61 - 67
Publisher: IEEE
 
» Magnetic Properties of Hexagonal Barium Ferrite Films on Pt(111)/Al2O3(0001) Substrate Based on Optimized Thickness of Pt
Abstract:
In this study, hexagonal barium ferrite thin films have been deposited on Pt(111)/Al2O3(0001) substrates by pulsed laser deposition. The thickness of Pt dependence of crystallographic structure and magnetic properties has been studied. X-ray diffraction θ-2θ reveals the films have a good c-axis orientation perpendicular to the film plane. Furthermore, pole figure analysis discovers that the crystallinity of films is greatly improved by Pt buffer layer and the highest degree of orientation is prepared at 20-nm-thick Pt. It is also observed from scanning electron microscope and atomic force microscopy that the BaM film with 20-nm-thick Pt is formed as hexagonal shaped and has smaller than 2 nm of roughness. Magnetic hysteresis loops show the saturation magnetization (), coercivity (), and uniaxial anisotropy field ( ) are greatly depended on the thickness of Pt buffer layer. Consequently, films with 20-nm Pt buffer layer have the highest of and of 16.7 kOe which are comparable with the theoretical value of BaM bulk.
Autors: Hui Zheng;Mangui Han;Yanhui Wu;Liang Zheng;Wenjing Zhao;Longjiang Deng;Huibin Qin;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 56 - 60
Publisher: IEEE
 
» Management of the ITER Buildings Configuration for the Construction and Installation Phase
Abstract:
The ITER project consists of a wide range of complex systems and interfaces which needs to be configured and controlled over the lifetime of the project with a comprehensive configuration management in place. The different maturities of the systems and their schedule need to be integrated in the overall project schedule in order to allow the project to stay in planned cost and schedule. The interfaces have to be advanced for those systems that are still in conceptual design phase to have sufficient information to advance with the systems facing the manufacturing readiness review (MRR). In order to achieve the project objectives, the structure of the ITER Organization (IO) Central Team (CT) is being adapted toward the ongoing construction phase on site as well as in the domestic agencies (DA) with a streamlined organization. Area manager posts have been created for all buildings, the site and the tokamak machine in order to have a prompt decision-making in design and construction phase following project change requests, system deviation requests, and field change requests. Weekly meetings are held between the IO CT with the DA and their contractors to feed the proposed modifications in the project baseline documentation including the associated cost and schedule impact. In parallel the project is preparing the installation phase of the machine and the plant systems layout in identifying the systems required for the first plasma, but also those which are “captive” and need to be installed during the civil works of the building. The schedule for each building and level has been developed to review the required duration and manpower in each area. As the installation of the systems and components will start at the defined ready for equipment dates for each areas and levels, the co-activities among the contractors have to be agreed.
Autors: Ingo Kuehn;Jean-Jacques Cordier;Christophe Baylard;Miikka Kotamaki;Laurent Patisson;Jens Reich;William Ring;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Jan 2018, volume: 46, issue:1, pages: 194 - 200
Publisher: IEEE
 
» Managing Programmers, with Ron Lichty
Abstract:
Veteran software manager Ron Lichty joins Nate Black to share his insights on managing software engineers. Nate and Ron delve into what about this is hard, how to grow as a manager, and what makes highly performing teams.
Autors: Nate Black;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 117 - 120
Publisher: IEEE
 
» Mapping Glacier Elevations and Their Changes in the Western Qilian Mountains, Northern Tibetan Plateau, by Bistatic InSAR
Abstract:
Accurate measurements of glacier surface topography and their changes play an essential role in various glaciological studies related to glacier dynamics and mass balance. The focus of this study is on mapping glacier digital elevation model (DEM) and elevation changes in the western Qilian Mountains, northern Tibetan Plateau, by synergistically using the TanDEM-X (TDX) bistatic Interferometric Synthetic Aperture Radar (InSAR) data in 2013 and Shuttle Radar Topography Mission (SRTM) DEM in 2000. The first high-resolution and high-precision glacier DEM is derived in this region by a TDX InSAR procedure with a nonlocal (NL) filter. Validated against the Ice, Cloud, and land Elevation Satellite (ICESat) height references, the absolute height error of the TanDEM-X DEM derived with the NL filter and the Goldstein filter with the parameters investigated is, respectively, 1.493 ± 0.747 and 1.857 ± 1.709 m. Further, four combinations of differential phase method (DiffPha) and DEM differencing method (DiffDem) with Goldstein filter and NL filter are applied to estimate glacier elevation changes between 2000 and 2013. The synergistic use of the DiffPha method and the NL filter is superior to other three combinations in terms of uncertainty and noise reduction. Generally, a clear surface thinning can be found in most glacier tongue regions, the maximum value of elevation lowering up to approximately −40 m, whereas a slight thickening is detected in accumulation areas, which are in agreement with the height difference results between GPS measurements and SRTM DEM over Laohugou Glacier No.12. This study demonstrates the potential of the TanDEM-X bistatic InSAR in mapping surface topography and elevation changes of valley glaciers in the Tibetan Plateau.
Autors: Yafei Sun;Liming Jiang;Lin Liu;Qishi Sun;Hansheng Wang;Houtse Hsu;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Jan 2018, volume: 11, issue:1, pages: 68 - 78
Publisher: IEEE
 
» Massive MIMO for Distributed Detection With Transceiver Impairments
Abstract:
This paper investigates an issue of massive MIMO-based distributed detection that considers transceiver hardware impairments at both a massive-antenna fusion center (FC) and multiple single-antenna sensors. First, we derive closed-form expressions of the probability of detection and the probability of false alarm, and show that hardware impairments create finite ceilings on the achievable detection performance. Then, we formulate a constrained optimization problem as sum of linear ratios programming to maximize the detection probability. By exploiting the inherent problem structures, we further develop an algorithm based on the alternating direction method of multipliers. Extensive simulations demonstrate that the nonideal hardware has a fundamental impact on the distributed detection performance. More specifically, in the limit of an infinite number of antennas and infinite sensor reporting power budget, the effects of FC impairment and FC receiver noise vanish, while the sensor impairment dominates the achievable distributed detection performance.
Autors: Guoru Ding;Xiqi Gao;Zhen Xue;Yongpeng Wu;Qingjiang Shi;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 604 - 617
Publisher: IEEE
 
» Massive MIMO Has Unlimited Capacity
Abstract:
The capacity of cellular networks can be improved by the unprecedented array gain and spatial multiplexing offered by Massive MIMO. Since its inception, the coherent interference caused by pilot contamination has been believed to create a finite capacity limit, as the number of antennas goes to infinity. In this paper, we prove that this is incorrect and an artifact from using simplistic channel models and suboptimal precoding/combining schemes. We show that with multicell MMSE precoding/combining and a tiny amount of spatial channel correlation or large-scale fading variations over the array, the capacity increases without bound as the number of antennas increases, even under pilot contamination. More precisely, the result holds when the channel covariance matrices of the contaminating users are asymptotically linearly independent, which is generally the case. If also the diagonals of the covariance matrices are linearly independent, it is sufficient to know these diagonals (and not the full covariance matrices) to achieve an unlimited asymptotic capacity.
Autors: Emil Björnson;Jakob Hoydis;Luca Sanguinetti;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 574 - 590
Publisher: IEEE
 
» Max-Min Fairness Rate Control in Wireless Networks: Optimality and Algorithms by Perron-Frobenius Theory
Abstract:
Rate adaptation and power control are two key resource allocation mechanisms in multiuser wireless networks. In the presence of interference, how do we jointly optimize end-to-end source rates and link powers to achieve weighted max-min rate fairness for all sources in the network? This optimization problem is hard to solve as physical layer link rate functions are nonlinear, nonconvex, and coupled in the transmit powers. We show that the weighted max-min rate fairness problem can, in fact, be decoupled into separate fairness problems for flow rate and power control. For a large class of physical layer link rate functions, we characterize the optimal solution analytically by a nonlinear Perron-Frobenius theory through solving a conditional eigenvalue problem that captures the interaction of multiuser interference. We propose an iterative algorithm to compute the optimal flow rate that converges geometrically fast without any parameter configuration. Numerical results demonstrate that our iterative algorithm is computationally fast for the Shannon capacity, CDMA, and piecewise link rate functions.
Autors: Liang Zheng;Desmond W. H. Cai;Chee Wei Tan;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 127 - 140
Publisher: IEEE
 
» Maximum-Likelihood Frequency and Phasor Estimations for Electric Power Grid Monitoring
Abstract:
In this paper, new frequency and phasor estimators are presented. These estimators are based on the maximum-likelihood technique and exploit the multidimensional nature of electrical signals. To minimize the likelihood function, we present an optimization algorithm based on the Newton–Raphson technique. While the performance of Fourier-based estimators significantly degrades when the window length is not equal to a multiple of the fundamental half-period, the proposed estimators perform well regardless of the window length. Simulation results show that the proposed estimators clearly outperform the discrete-time Fourier transform in terms of total vector error and frequency error whatever the signal-to-noise ratio, harmonic and interharmonic distortion, and off-nominal frequency deviation are. The benefits of the proposed estimators are also illustrated with real power system data obtained from the DOE/EPRI National Database of power system events.
Autors: Zakarya Oubrahim;Vincent Choqueuse;Yassine Amirat;Mohamed El Hachemi Benbouzid;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 167 - 177
Publisher: IEEE
 
» Measurement-Based Dynamic Load Modeling Using the Vector Fitting Technique
Abstract:
Accurate load modeling is essential for power system stability analysis and control. This topic has regained interest, due to the high penetration of new types of loads and the increased availability of measurements in extended power grids. In this paper, an aggregated load model based on measurement data is formulated for dynamic simulations of large power systems. The proposed model employs variable-order transfer functions, enabling the accurate simulation of complex load dynamics. A complete methodology for the automatic derivation of the minimum-required model order is proposed with the model parameters calculated via a robust multisignal identification procedure. For this purpose, the vector fitting method is introduced as a technique for measurement-based load modeling. Several simulations are performed using the NEPLAN software to investigate the accuracy and the generalization capabilities of the proposed model. The model performance is thoroughly compared with other conventional load models, also using measurements recorded on a laboratory-scale microgrid.
Autors: Eleftherios O. Kontis;Theofilos A. Papadopoulos;Andreas I. Chrysochos;Grigoris K. Papagiannis;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 338 - 351
Publisher: IEEE
 
» Mechanical Contact-Less Computational Speed Sensing Approach of PWM Operated PMDC Brushed Motor: A Slotting-Effect and Commutation Phenomenon Incorporated Semi-Analytical Dynamic Model-Based Approach
Abstract:
This brief proposes a mechanical contact-less speed sensing approach for a pulse width modulation (PWM) operated permanent-magnet direct current (PMDC) brushed motor. A recently reported semi-analytical dynamic model which incorporates the space-domain effects, namely slotting-effect and commutation phenomenon, has been taken into consideration to apply the proposed computational speed sensing approach. This speed sensing approach is basically an indirect estimation process and discrete in manner. The proposed method is efficiently applicable at higher range of speed. Zones of estimations with varying load torque and PWM duty cycle are represented with appropriate responses. A simulation of the proposed estimation method is applied over the dynamic semi-analytical model of 24 V, 12 teeth-slots, 100 W PMDC brushed motor, and various responses are represented in this brief.
Autors: Suman Ghosh;Mousam Ghosh;Goutam Kumar Panda;Pradip Kumar Saha;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 81 - 85
Publisher: IEEE
 
» Mechanical Impedance of the Ankle During the Terminal Stance Phase of Walking
Abstract:
Human joint impedance describes the dynamic relationship between perturbation induced change in position and the resulting response torque. Understanding the natural regulation of ankle impedance during locomotion is necessary to discern how humans interact with their environments, and provide a foundation for the design of biomimetic assistive devices and their control systems. This paper estimates ankle impedance during terminal stance phase of walking using a parametric model consisting of stiffness, damping, and inertia. The model accurately described ankle torque, accounting for 90% ± 7.7% of the variance. Stiffness was found to decrease from 3.7 to 2.1 Nm/rad/kg between 75% and 85% stance. Quasi-stiffness—the slope of the ankle’s torque-angle curve—showed a similar decreasing trend but was significantly larger at the onset of terminal stance phase. The damping component of impedance was constant during terminal stance phase, and was increased relative to values previously reported during early and mid-stance phases, indicating an increase in damping in preparation for toe-off. Inertia estimates were consistent with previously reported inertia values for the human ankle. This paper bridges a gap in our understanding of ankle impedance during walking, and provides new insight into how ankle impedance is regulated during regions when substantial mechanical energy is added.
Autors: Amanda L. Shorter;Elliott J. Rouse;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 135 - 143
Publisher: IEEE
 
» Mechanical Technique to Customize a Waveguide-Slot Radiating Performance
Abstract:
A mechanical technique to tune the radiating performance of a waveguide-fed slot is presented. Three metallic tuning screws are introduced through the bottom wall of the feeding waveguide. The field radiated by the slot is mechanically controlled with the insertion length of the tuning screws and a good input matching response is also maintained. One of the tuning screws modifies the slot coupling parameter as well as the phase of the transmitted signal, while the other pair of screws compensates the impedance mismatch introduced by the first one. A five-element traveling-wave (TW) linear array antenna has been designed and manufactured as a proof of concept to validate the performance of the tuning screws. Several improvements such as a main beam steering range of 17°, an enhancement of the antenna efficiency, the mitigation of the undesirable grating lobe appearance typical of TW air-waveguide-fed arrays, as well as the compensation of the mutual coupling effects or manufacturing tolerance errors could be experimentally achieved by using the proposed mechanism based on tuning screws.
Autors: P. Sanchez-Olivares;J. L. Masa-Campos;J. Hernandez-Ortega;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 426 - 431
Publisher: IEEE
 
» MECPASS: Distributed Denial of Service Defense Architecture for Mobile Networks
Abstract:
Distributed denial of service is one of the most critical threats to the availability of Internet services. A botnet with only 0.01 percent of the 50 billion connected devices in the Internet of Things is sufficient to launch a massive DDoS flooding attack that could exhaust resources and interrupt any target. However, the mobility of user equipment and the distinctive characteristics of traffic behavior in mobile networks also limit the detection capabilities of traditional anti-DDoS techniques. In this article, we present a novel collaborative DDoS defense architecture called MECPASS to mitigate the attack traffic from mobile devices. Our design involves two filtering hierarchies. First, filters at edge computing servers (i.e., local nodes) seek to prevent spoofing attacks and anomalous traffic near sources as much as possible. Second, global analyzers located at cloud servers (i.e., central nodes) classify the traffic of the entire monitored network and unveil suspicious behaviors by periodically aggregating data from the local nodes. We have explored the effectiveness of our system on various types of application- layer DDoS attacks in the context of web servers. The simulation results show that MECPASS can effectively defend and clean an Internet service provider core network from the junk traffic of compromised UEs, while maintaining the false-positive rate of its detection engine at less than 1 percent.
Autors: Van Linh Nguyen;Po-Ching Lin;Ren-Hung Hwang;
Appeared in: IEEE Network
Publication date: Jan 2018, volume: 32, issue:1, pages: 118 - 124
Publisher: IEEE
 
» Medical delivery drones take flight in east africa
Abstract:
While Amazon and United Parcel Service pour considerable resources into finding ways of using drones to deliver such things as shoes and dog treats, Zipline has been saving lives in Rwanda since October 2016 with drones that deliver blood. Zipline's autonomous fixedwing drones now form an integral part of Rwanda's medical-supply
Autors: Evan Ackerman;Eliza Strickland;
Appeared in: IEEE Spectrum
Publication date: Jan 2018, volume: 55, issue:1, pages: 34 - 35
Publisher: IEEE
 
» Meetings calendar
Abstract:
Provides a listing of future meetings.
Autors: Davide Fabiani;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Jan 2018, volume: 34, issue:1, pages: 68 - 70
Publisher: IEEE
 
» Megi Typhoon Monitoring by X-Band Synthetic Aperture Radar Measurements
Abstract:
In this study, typhoon monitoring is addressed using X-band synthetic aperture radar (SAR) imagery collected by the German TerraSAR-X mission and the Italian COSMO-SkyMed constellation during the typhoon Megi. Geometrical features, rain rate, and wind speed associated with the typhoon are retrieved by the SAR data set. One of the key benefits of the X-band observations relies in their sensitivity to rain that can be exploited to provide an estimate of geometrical features and rain rate by analyzing attenuation bands present in the SAR data. In addition, wind speed is retrieved using a rain-free model based on two geophysical model functions (GMFs) and experimental results show that the nonlinear relationship between normalized radar cross section and wind speed provided by one of the GMFs can be exploited to provide a rough estimate of high wind speeds.
Autors: Valeria Corcione;Ferdinando Nunziata;Maurizio Migliaccio;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Jan 2018, volume: 43, issue:1, pages: 184 - 194
Publisher: IEEE
 
» MEICAN: Simplifying DCN Life-Cycle Management from End-User and Operator Perspectives in Inter-Domain Environments
Abstract:
National research and education networks (NRENs), such as ESnet, GéANT, and RNP, currently promote the employment of dynamic circuit networks (DCNs) to improve scientific communications beyond the capabilities of today's Internet. In spite of their alleged benefits to materialize user-initiated, ad hoc dedicated end-to-end circuits for high-demanding applications, DCNs also pose important challenges. Two examples are dealing with the end-user's lack of ability or willingness to understand low-level technicalities of virtual circuit establishment, and accommodating NRENs' local policies throughout the life-cycle of DCN. In this article, we seek to improve the usability of DCN services with a focus on the inexperienced end-user and the skilled network operator alike. We introduce MEICAN, a platform to manage the life-cycle of DCN from definition to provisioning of virtual circuits. We also present a case study of inter-domain circuit reservation with mixed manual and automated policy checking, and discuss lessons learned, relevant challenges, and open issues still to be overcome.
Autors: Juliano Araujo Wickboldt;Mauricio Quatrin Guerreiro;Lisandro Zambenedetti Granville;Luciano Paschoal Gaspary;Marcos Felipe Schwarz;Chin Guok;Vangelis Chaniotakis;Andrew Lake;and John MacAuley;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 179 - 187
Publisher: IEEE
 
» Memory-Based Architecture for Multicharacter Aho–Corasick String Matching
Abstract:
The Aho–Corasick (AC) string matching algorithm is commonly used in signature-based intrusion detection and antivirus systems. In this paper, we present a hardware implementation of the AC algorithm that can process multiple characters per cycle. State transitions are implemented using table lookup. Hence, updates to the pattern set do not require hardware reconfiguration. A fundamental issue of multicharacter AC string matching is the transition rules explosion problem. We apply the transition rule reduction strategy such that the number of transition rules can be reduced to less than two rules per state in the finite automaton. The memory cost is further optimized by implementing the rule table as near-minimal perfect hash table. We implement the proposed method on a virtex-7 FPGA for a pattern set with 2200 Snort signatures. The normalized memory cost of our design is 13.75 bytes per character of the pattern set when four characters are processed per cycle, and the FPGA can operate at 216 MHz.
Autors: Xing Wang;Derek Pao;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 143 - 154
Publisher: IEEE
 
» Message from the Editor-in-Chief
Abstract:
Welcome to the January 2018 issue of the IEEE Transactions on Visualization and Computer Graphics (TVCG)! I am pleased to introduce this special issue containing 99 papers presented at IEEE VIS 2017, which includes the Conference on Visual Analytics Science and Technology (IEEE VAST 2017), the IEEE Information Visualization Conference (IEEE InfoVis 2017), and the IEEE Scientific Visualization Conference (IEEE SciVis 2017), held in Phoenix, USA, from the 1st to the 6th of October 2017. These papers, selected from 467 submissions, were recommended for acceptance by the Program Committees of these three conferences, after having undergone a rigorous and competitive two-round review process. The cooperation between TVCG and IEEE VIS has been considerably growing over the years in terms of the number of publications in the TVCG IEEE VIS special issue, and of the size of attendance to IEEE VIS. This special hybrid publication model enables timely dissemination of many high-quality research results from the world’s top visualization conferences to TVCG readership, while improving the overall visibility and quality of IEEE VIS publications through a rigorous journal-style review. Since 2011, the authors of TVCG regular papers have been invited to give an oral presentation of their recent work at IEEE VIS, thus providing a unique opportunity for the VIS audience to keep abreast of high-quality visualization research featured in regular issues of TVCG, and encouraging more TVCG authors to attend IEEE VIS. This closely coupled relation-ship between TVCG and VIS has been leading to a more timely exchange of new ideas, to a rapid dissemination of visualization research via an integrated forum for both publications and presentations, and to further expanding our visualization community.
Autors: Leila De Floriani;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: x - x
Publisher: IEEE
 
» Metal–Insulator Transition of Ge–Sb–Te Superlattice: An Electron Counting Model Study
Abstract:
Ge–Sb–Te superlattice (GST-SL) is a newly emerging electronic material for nonvolatile phase-change memory with ultralow energy cost. However, its switching mechanism is still unclear with intensive debates. In this work, by first-principles calculations and an electron counting model study, we study the possible mechanism of phase change and the accompanying property transition of GST-SL. GST-SL are separated into individual layers by van der Waals gaps. We demonstrate that both the global chemical stoichiometry of the material and the local chemical stoichiometry of individual layer block are required to have an insulating band gap according to an electron counting model analysis. The electrical property can be adjusted by changing the local stoichiometry, such as producing defects around van der Waals gaps. Inspired by a previous experiment, we propose that a stacking-fault motion can spontaneously alter the band gap and results in a metal–insulator transition. This transition may provide a significant change of carrier concentration and indicate an ultralow energy-consumption process with a low energy barrier. The present investigations reveal a picture of electrical transition in GST-SL and may guide us to improve its device performances.
Autors: Nian-Ke Chen;Xian-Bin Li;Xue-Peng Wang;Sheng-Yi Xie;Wei Quan Tian;Shengbai Zhang;Hong-Bo Sun;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 140 - 146
Publisher: IEEE
 
» Micro-Grating Array-Enabled Power Efficiency Improvement for a DMD-Based Optical Switch
Abstract:
Digital micro-mirror device (DMD)-based optical switch can dynamically change the channels reallocation and provide flexibility in optical networking with the advantages of fast time response and scalable port number. However, the DMD as a binary diffraction device has a limited efficiency of 10.1% at the +1st diffraction order. Here we propose and demonstrate a DMD-based optical switch with improved efficiency enabled by a blazed micro-grating array. The blazed micro-grating array is designed and fabricated to diffract and make use of the wasted −1st order beams of the DMD. Using this device, we achieve ~2 dB efficiency improvements for a optical switch with all switching states. We experimentally demonstrate high speed switching of channels carrying 15 and 30 Gb/s ON-OFF keying signals. The micro-grating array has the potential to develop for the DMD-based optical switch with multiple channels.
Autors: Chuanwu Yang;Ting Lei;Xiaocong Yuan;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 145 - 148
Publisher: IEEE
 
» Microbeam Heavy-Ion Single-Event Effect on Xilinx 28-nm System on Chip
Abstract:
Heavy-ion microbeam experiment was performed on Xilinx 28-nm system on chip (SoC) at Beijing Heavy Ion-13 tandem accelerator in the China Institute of Atomic Energy. Five functional blocks of Xilinx Zynq-7020 SoC processing system were irradiated and tested. The distributions of single-event effect (SEE) sensitivity regions and cross sections of on-chip memory (OCM), D-Cache, arithmetic and logic unit (ALU), floating-point unit (FPU), and peripheral were first obtained. The results suggest that the most sensitive block among the five blocks is D-Cache and the least is FPU, and the SEE sensitivities of OCM, ALU, and peripheral are at the same level.
Autors: Weitao Yang;Xuecheng Du;Chaohui He;Shuting Shi;Li Cai;Ning Hui;Gang Guo;Chengliang Huang;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Jan 2018, volume: 65, issue:1, pages: 545 - 549
Publisher: IEEE
 
» Micropatterned Vertical Alignment Liquid Crystal Mode With Dual Threshold Voltages for Improved Off-Axis Gamma Distortion
Abstract:
We proposed an eight-domain vertical alignment (VA) liquid crystal (LC) mode, operated by dual pixel domains of fishbone-structured electrodes for dual threshold (F-DT) voltages in the VA mode, which can improve off-axis gamma distortions without additional electronic circuits and fabrication procedures compared with the conventional multidomain VA modes. In the proposed F-DT VA mode, different threshold voltage levels can be obtained for the main- and subpixel regions by utilizing different field-induced LC reorientations determined by the pixel electrode structures, whose properties are especially enhanced in low-voltage regimes. When the relative area ratio () between the main- and subpixel domains was , these dual threshold properties of the F-DT VA mode improved the off-axis gamma distortion index (GDI) value up to 34.04% at the oblique viewing condition of , compared to the conventional patterned VA (PVA) modes, while maintaining the maximum transmittance level. The proposed pixel electrode design scheme could be applied to further improve the GDI value simply by controlling , where the GDI of the F-DT VA mode was improved by 39.17% and 17.05% at , compared to the conventional PVA and micropatterned VA modes, respectively.
Autors: Young-Chul Shin;Min-Kyu Park;Byeonggon Kim;Jeong Min Bae;Hak-Rin Kim;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 150 - 157
Publisher: IEEE
 
» Microprocessor Optimizations for the Internet of Things: A Survey
Abstract:
The Internet of Things (IoT) refers to a pervasive presence of interconnected and uniquely identifiable physical devices. These devices’ goal is to gather data and drive actions in order to improve productivity, and ultimately reduce or eliminate reliance on human intervention for data acquisition, interpretation, and use. The proliferation of these connected low-power devices will result in a data explosion that will significantly increase data transmission costs with respect to energy consumption and latency. Edge computing reduces these costs by performing computations at the edge nodes, prior to data transmission, to interpret and/or utilize the data. While much research has focused on the IoT’s connected nature and communication challenges, the challenges of IoT embedded computing with respect to device microprocessors has received much less attention. This paper explores IoT applications’ execution characteristics from a microarchitectural perspective and the microarchitectural characteristics that will enable efficient and effective edge computing. To tractably represent a wide variety of next-generation IoT applications, we present a broad IoT application classification methodology based on application functions, to enable quicker workload characterizations for IoT microprocessors. We then survey and discuss potential microarchitectural optimizations and computing paradigms that will enable the design of right-provisioned microprocessors that are efficient, configurable, extensible, and scalable. This paper provides a foundation for the analysis and design of a diverse set of microprocessor architectures for next-generation IoT devices.
Autors: Tosiron Adegbija;Anita Rogacs;Chandrakant Patel;Ann Gordon-Ross;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Jan 2018, volume: 37, issue:1, pages: 7 - 20
Publisher: IEEE
 
» Microstrip-Ridge Gap Waveguide Filter Based on Cavity Resonators With Mushroom Inclusions
Abstract:
In this paper, we propose a novel microstrip-ridge gap waveguide (MS-RGW) filter configuration, which is based on cavity resonators with mushroom inclusions. The resonators are realized as defects in surrounding mushroom-based perfect magnetic conductor (PMC), and thus, the filter configuration does not require additional conductive layers nor rearrangement of the PMC elements. The hosting MS-RGW is fed through transition from SMA to microstrip ridge, enabling simple fabrication and excellent impedance matching in a wide frequency range. To demonstrate the potential of the proposed structure, four narrowband filters have been designed, fabricated, and measured. The filters exhibit excellent in-band characteristics and small dimensions.
Autors: Slobodan Birgermajer;Nikolina Janković;Vasa Radonić;Vesna Crnojević-Bengin;Maurizio Bozzi;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 136 - 146
Publisher: IEEE
 
» Microw(h)att?! Ultralow-Power Six-Port Radar: Realizing Highly Integrated Portable Radar Systems with Good Motion Sensitivity at Relatively Low Cost
Abstract:
Short-range noncontact microwave radar systems have undergone significant development in recent years [1]. Driven by advances in modern monolithic microwave integrated circuitry, printed circuit board (PCB) technologies, and embedded computing, highly integrated portable radar systems with good motion sensitivity can today be realized at relatively low cost. Radar systems have emerged in a variety of new application fields including industrial sensing [2], [3], human vital-sign detection [4], [5], and structural health monitoring [6].
Autors: Fabian Lurz;Fabian Michler;Benedict Scheiner;Robert Weigel;Alexander Koelpin;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 91 - 98
Publisher: IEEE
 
» Microwave Power Transfer With Optimal Number of Rectenna Arrays for Midrange Applications
Abstract:
In this letter, the microwave power transfer (MPT) system with the optimal number of rectenna arrays for midrange applications is proposed, theoretically analyzed, and verified. A retrodirective power transmitter is designed to overcome the degradation by the near-field effect and enhance the power transfer efficiency. The implemented transmitter is composed of 16 1 patch antennas with a spacing, and each of the antennas has a circuit for simultaneously detecting and shifting the phase, and operates at a frequency of 2.45 GHz. To further improve the power transfer efficiency, the parallel dc combining rectenna array is designed since the conventional RF combining rectenna has several problems in the case of midrange. The fabricated rectenna array consists of 8 1 rectennas with a spacing and a dc power management circuit. In addition, the optimal number of rectenna arrays is proposed, considering the size of the receiver. In the experiments, the optimal number of rectennas is 3 when the transfer distance is 1 m. The achieved power transfer efficiency from three-arrayed rectennas is 4.47%, while the efficiency of 5.01% is achieved from eight-arrayed rectennas. Experimental results from the implemented MPT system show good agreement with the proposed theory.
Autors: Seung-Tae Khang;Dong-Jin Lee;In-Jun Hwang;Tae-Dong Yeo;Jong-Won Yu;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Jan 2018, volume: 17, issue:1, pages: 155 - 159
Publisher: IEEE
 
» Microwave-Induced Thermoacoustic Imaging of Subcutaneous Vasculature With Near-Field RF Excitation
Abstract:
Imaging of subcutaneous vasculature is of great interest for biometric security and point-of-care medicine. We investigate the feasibility of microwave-induced thermoacoustic (TA) tomography as a safe, compact, low-power, and cost-effective imaging technique for subcutaneous vasculature by means of application-specific design of near-field, radio frequency (RF) applicators. Using commercial transducers, we demonstrate proof-of-concept TA imaging of synthetic phantoms, plant vasculature, and earthworm blood vessels with only 50 W of peak power, or 42 mW average power, at 300 resolution. The proposed RF applicator design enabled uniform, orientation-independent illumination of vasculature phantoms with only 10% variation. Finally, we show that the benefits of microwave contrast make possible the distinction of actual blood vessels, in an earthworm, from surrounding tissue within a modest receiver dynamic range of 40 dB.
Autors: Miaad S. Aliroteh;Amin Arbabian;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 577 - 588
Publisher: IEEE
 

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