Electrical and Electronics Engineering publications abstract of: 02-2018 sorted by title, page: 15

» Rooting for robots at the Winter Olympics
Abstract:
Spectators who get lost in Olympic Plaza in Pyeongchang this month can ask for directions from a nearby guide that speaks four languages. Thirsty patrons who visit Gangneung Media Village can order drinks for delivery. And they can do all of this without talking to another human. South Korea is going big on robotics for the 2018 Winter Olympics, which begin on 9 February. Organizers will deploy about 80 robots at the games to showcase the nation’s leadership in advanced robotics research. Eight companies-with US $1.5 million in sponsorship from the South Korean government-have been working on projects for the games since 2016. The roboticists who built all of these new robots are now preparing to unveil their technology on a world stage.
Autors: Michael Koziol;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 7 - 8
Publisher: IEEE
 
» Row–Column Beam Steering Control of Reflectarray Antennas: Benefits and Drawbacks
Abstract:
This letter proposes a method for controlling single-polarized phase-only reconfigurable reflectarray antennas by rows and columns instead of element-by-element, which enables an important simplification of the control circuitry. First, the fundaments of the method are presented, and then the implications on analog and digital implementations are discussed. Finally, applications beyond beam steering are also addressed. It is shown that this is a promising method for pure beam-steering applications in combination with analog control or with phase quantization with at least two bits. Remarkably, this last result contradicts the existing literature.
Autors: Xavier Artiga;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Feb 2018, volume: 17, issue:2, pages: 271 - 274
Publisher: IEEE
 
» Ruin Time of Uncertain Insurance Risk Process
Abstract:
An insurance risk process usually describes the risk of an insurance company via many criteria, such as ruin index, ruin time, and deficit. So far, the insurance risk process involving random factors has been extensively investigated. As a complement, considering the human uncertainty in running an insurance company, this paper studies an insurance risk process involving human uncertainty. The inverse uncertainty distribution of the uncertain insurance risk process is obtained, and the uncertainty distribution of the ruin time is also derived. Some numerical experiments are performed to illustrate the results.
Autors: Kai Yao;Jian Zhou;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 19 - 28
Publisher: IEEE
 
» Rumor Source Identification in Social Networks with Time-Varying Topology
Abstract:
Identifying rumor sources in social networks plays a critical role in limiting the damage caused by them through the timely quarantine of the sources. However, the temporal variation in the topology of social networks and the ongoing dynamic processes challenge our traditional source identification techniques that are considered in static networks. In this paper, we borrow an idea from criminology and propose a novel method to overcome the challenges. First, we reduce the time-varying networks to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual in traditional techniques, we adopt a reverse dissemination strategy to specify a set of suspects of the real rumor source. This process addresses the scalability issue of source identification problems, and therefore dramatically promotes the efficiency of rumor source identification. Third, to determine the real source from the suspects, we employ a novel microscopic rumor spreading model to calculate the maximum likelihood (ML) for each suspect. The one who can provide the largest ML estimate is considered as the real source. The evaluations are carried out on real social networks with time-varying topology. The experiment results show that our method can reduce percent of the source seeking area in various time-varying social networks. The results further indicate that our method can accurately identify the real source, or an individual who is very close to the real source. To the best of our knowledge, the proposed method is the first that can be used to identify rumor sources in time-varying social networks.
Autors: Jiaojiao Jiang;Sheng Wen;Shui Yu;Yang Xiang;Wanlei Zhou;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Feb 2018, volume: 15, issue:1, pages: 166 - 179
Publisher: IEEE
 
» Safe, Secure Executions at the Network Edge: Coordinating Cloud, Edge, and Fog Computing
Abstract:
System design where cyber-physical applications are securely coordinated from the cloud may simplify the development process. However, all private data are then pushed to these remote “swamps,” and human users lose actual control as compared to when the applications are executed directly on their devices. At the same time, computing at the network edge is still lacking support for such straightforward multidevice development, which is essential for a wide range of dynamic cyber-physical services. This article proposes a novel programming model as well as contributes the associated secure-connectivity framework for leveraging safe coordinated device proximity as an additional degree of freedom between the remote cloud and the safety-critical network edge, especially under uncertain environment constraints. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Autors: Niko Mäkitalo;Aleksandr Ometov;Joona Kannisto;Sergey Andreev;Yevgeni Koucheryavy;Tommi Mikkonen;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 30 - 37
Publisher: IEEE
 
» Sampled-Data Stabilization for Fuzzy Genetic Regulatory Networks with Leakage Delays
Abstract:
This paper deals with the sampled-data stabilization problem for Takagi-Sugeno (T-S) fuzzy genetic regulatory networks with leakage delays. A novel Lyapunov-Krasovskii functional (LKF) is established by the non-uniform division of the delay intervals with triplex and quadruplex integral terms. Using such LKFs for constant and time-varying delay cases, new stability conditions are obtained in the T-S fuzzy framework. Based on this, a new condition for the sampled-data controller design is proposed using a linear matrix inequality representation. A numerical result is provided to show the effectiveness and potential of the developed design method.
Autors: M. Syed Ali;N. Gunasekaran;Choon Ki Ahn;Peng Shi;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Feb 2018, volume: 15, issue:1, pages: 271 - 285
Publisher: IEEE
 
» Satellite-Link Attenuation Measurement Technique for Estimating Rainfall Accumulation
Abstract:
A technique using satellite-link signal attenuation measurements for estimating rainfall accumulation along the link path is evaluated. Power law relationships between attenuation rate and rainfall rate are used to estimate and rainfall accumulation with a satellite link operating at Ku-band (12.3 GHz). Polarimetric radar measurements obtained from a National Weather Service Weather Surveillance Radar—1988 Doppler system near State College, Pennsylvania, are utilized to provide a comparison of rainfall accumulation estimates. A tipping-bucket rain gauge, colocated with the satellite receiver, is also used for comparison. A method based on bit error ratio measurements for the satellite link is used to identify periods of rain during which the rainfall rate is estimated from signal attenuation measurements. The effective rain height used in converting the attenuation rate along the link path into the rainfall rate is estimated from polarimetric radar observations. The Ku-band link is not very sensitive to light rain below 1.5 mm/h. Rainfall accumulation estimates obtained for 11 different days using satellite link attenuation show good comparisons with radar (within 19%) for accumulations greater than 6 mm and not so good (within 43%) for accumulations below 3 mm. The results presented in this paper show that using satellite-link attenuation measurements to estimate rainfall accumulations is a promising technique that requires further testing and refinement.
Autors: C. Hakan Arslan;Kültegin Aydin;Julio V. Urbina;Lars Dyrud;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 681 - 693
Publisher: IEEE
 
» Scaling Projections on Spin-Transfer Torque Magnetic Tunnel Junctions
Abstract:
We investigate scaling of technologically relevant magnetic tunnel junction devices in the trilayer and pentalayer configurations by varying the cross-sectional area along the transverse direction using the nonequilibrium Green’s function spin transport formalism. We study the geometry dependence by considering square and circular cross sections. As the transverse dimension in each case reduces, we demonstrate that the transverse mode energy profile plays a major role in the resistance-area(RA) product. Both types of devices show constant tunnel magnetoresistance at larger cross-sectional areas but achieve ultrahigh magnetoresistance at small cross-sectional areas, while maintaining low RA products. We notice that although the critical switching voltage for switching the magnetization of the free-layer nanomagnet in the trilayer case remains constant at larger areas, it needs more energy to switch at smaller areas. In the pentalayer case, we observe an oscillatory behavior at smaller areas as a result of double barrier tunneling. We also describe how switching characteristics of both kinds of devices are affected by the scaling.
Autors: Debasis Das;Ashwin Tulapurkar;Bhaskaran Muralidharan;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 724 - 732
Publisher: IEEE
 
» Scanning the Issue
Abstract:
Stochastic Geometry Methods for Modeling Automotive Radar Interference
Autors: Petros Ioannou;A. Al-Hourani;R. J. Evans;S. Kandeepan;B. Moran;H. Eltom;N. Polson;V. Sokolov;T. Zhou;C. Tao;S. Salous;L. Liu;W.-Y. Shieh;C.-C. J. Hsu;T.-H. Wang;C.-C. Lu;S. Yan;H.-C. Ko;H.-J. Chen;Y.-J. Gong;E. Chen;X. Zhang;L. M. Ni;J. Zhang;Y. Zhou
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 329 - 332
Publisher: IEEE
 
» Scanning the Literature
Abstract:
Autors: Xiaohua Tian;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 4 - 5
Publisher: IEEE
 
» Scene Classification Based on Two-Stage Deep Feature Fusion
Abstract:
In convolutional neural networks (CNNs), higher layer information is more abstract and more task specific, so people usually concern themselves with fully connected (FC) layer features, believing that lower layer features are less discriminative. However, a few researchers showed that the lower layers also provide very rich and powerful information for image representation. In view of these study findings, in this letter, we attempt to adaptively and explicitly combine the activations from intermediate and FC layers to generate a new CNN with directed acyclic graph topology, which is called the converted CNN. After that, two converted CNNs are integrated together to further improve the classification performance. We validate our proposed two-stage deep feature fusion model over two publicly available remote sensing data sets, and achieve a state-of-the-art performance in scene classification tasks.
Autors: Yishu Liu;Yingbin Liu;Liwang Ding;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 183 - 186
Publisher: IEEE
 
» Scheduling Interrelated Activities Using Insertion-Based Heuristics
Abstract:
The issue of scheduling interrelated activities is important and of particular concern to design managers. One tool that helps us to solve this issue is the design structure matrix (DSM) which can explicitly represent the information dependencies among interrelated activities. Based on the DSM method, this study presents effective approaches for sequencing interrelated activities with the goal of minimizing total feedback length, which is a good approximation for reducing project completion time. First, we prove two new properties of the problem, and develop an insertion-based heuristic. Second, the proposed heuristic is further improved by combing it with simulated annealing and genetic algorithm. Computer experiments show that our approaches outperform existing heuristics, in that with similar settings, our approaches often produces better solutions.
Autors: Jun Lin;Weihao Huang;Yanjun Qian;Xi Zhao;
Appeared in: IEEE Transactions on Engineering Management
Publication date: Feb 2018, volume: 65, issue:1, pages: 113 - 127
Publisher: IEEE
 
» Scheduling of Dual Resource Constrained Lithography Production: Using CP and MIP/CP
Abstract:
A dual resource constrained (DRC) scheduling problem arises at the photolithography area in semiconductor manufacturing wherein reticles are required as an auxiliary resource. Reticles are transferred from one place to another. While this shared resource gives the manufacturer a flexibility, it certainly gives rise to a complex DRC scheduling problem surrounded by jobs, machines, and reticles, restricted by sequence-dependent setup-time and location-dependent reticle transfer-time. This study proposes a constraint programming (CP) approach and investigates methods for improving our initial CP using a hybrid method and variable ordering heuristic. Experiments indicate the variable ordering heuristic brings a significant improvement over a pure CP. Note to Practitioners—There has been yet no successful exact approach that addresses litho scheduling problem, covering jobs, machines, and reticles. This study demonstrates CP is able to find an optimal solution for most of realistic industry-size test problems. In a future smart semiconductor factory, seamlessly orchestrating machines, reticles, and jobs would not be the end state. The next level is to integrate material handling system to this already overcrowded production scheduling problem. The specialized keywords of CP, as demonstrated in this study, will enable practitioners to develop a concise code of integrating vehicles, jobs, machines, and reticles.
Autors: Andy Ham;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 52 - 61
Publisher: IEEE
 
» Scheduling Policies for Wireless Downlink With Correlated Random Connectivity and Multislot Reconfiguration Delay
Abstract:
Stable and minimum delay scheduling of wireless downlinks, with time correlated random connectivity between the base station and each associated user, is an important problem in modern communication systems. We assume that the base station of the wireless downlink dynamically switches between the users to transmit packets to each user. The dynamic switching of the base station incurs a reconfiguration delay. We find that as the reconfiguration delay increases the stability region of the wireless downlink with correlated channel connectivity shrinks to that achieved by time sharing among the users over large time periods. Since existing scheduling policies are designed either for single slot reconfiguration delay and correlated random connectivity, or multislot reconfiguration delay but without correlated connectivity, we propose scheduling policies which explicitly takes into account the correlated channel connectivity and multislot reconfiguration delay and show using simulations that the average delay is reduced compared to existing policies.
Autors: Amit Kumar;Vineeth Bala Sukumaran;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 384 - 387
Publisher: IEEE
 
» Science of Security: Combining Theory and Measurement to Reflect the Observable
Abstract:
What would a “Science of Security” look like? This question has received considerable attention over the past 10 years. No one argues against the desirability of making security research more “scientific.” But how would one would go about that? We argue that making progress on this requires clarifying what “scientific” means in the context of computer security, and that has received too little attention. We pursue this based on a review of literature in the history and Philosophy of Science and a belief that work under the theme “Science of Security” should align with and ideally, benefit from what has been learned over a few hundred years in science. We offer observations and insights, with a view that the security community can benefit from better leveraging past lessons and common practices well-accepted by consensus in the mainstream scientific community—but which appear little recognized in the security community.
Autors: Cormac Herley;P.C. van Oorschot;
Appeared in: IEEE Security & Privacy
Publication date: Feb 2018, volume: 16, issue:1, pages: 12 - 22
Publisher: IEEE
 
» Scientific Workflow Clustering and Recommendation Leveraging Layer Hierarchical Analysis
Abstract:
This article proposes an approach for identifying and recommending scientific workflows for reuse and repurposing. Specifically, a scientific workflow is represented as a layer hierarchy, which specifies hierarchical relations between this workflow, its sub-workflows, and activities. Semantic similarity is calculated between layer hierarchies of workflows. A graph-skeleton based clustering technique is adopted for grouping layer hierarchies into clusters. Barycenters in each cluster are identified, which refer to core workflows in this cluster, for facilitating cluster identification and workflow ranking and recommendation. Experimental evaluation shows that our technique is efficient and accurate on ranking and recommending appropriate clusters and scientific workflows with respect to specific requirements of scientific experiments.
Autors: Zhangbing Zhou;Zehui Cheng;Liang-Jie Zhang;Walid Gaaloul;Ke Ning;
Appeared in: IEEE Transactions on Services Computing
Publication date: Feb 2018, volume: 11, issue:1, pages: 169 - 183
Publisher: IEEE
 
» Secondary Arc Current During DC Auto Reclosing in Multisectional AC/DC Hybrid Lines
Abstract:
In this paper, a contribution to the analysis of electromagnetic ac to dc interactions in complex ac/dc hybrid overhead lines was made. For accurate calculation of such coupling, standard transformations like the symmetrical components cannot be used. Therefore, a method based on adjusted modal decomposition was presented, which allows analysis of untransposed and partly transposed configurations in arbitrary switching states. The method was applied to the case of dc fault clearing using single-pole auto reclosing (dc SPAR), where parallel ac circuits could induce a secondary arc in the dc line. The magnitude of the secondary arc current was examined, which allows evaluating the necessary dead time of the dc SPAR. The influence of parameters like line configuration, load flow, and fault location was discussed. After that, a realistic study case hybrid line was analyzed. In particular, the comparison to secondary arcs in ac lines and the behavior as a function of fault location in the context of changing ac systems and line configurations along the hybrid dc corridor provide new insights into a relevant phenomenon.
Autors: Jakob Schindler;Christian Romeis;Johann Jaeger;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 489 - 496
Publisher: IEEE
 
» Secondary Low-Voltage Circuit Models—How Good is Good Enough?
Abstract:
Utility power distribution system analysis has traditionally been performed considering only the primary or medium-voltage system. Distributed energy resources are increasingly being located on the secondary, or low voltage, side of the distribution transformer, requiring the low-voltage system to be included in the analysis. However, most distribution system models do not include secondary circuits or they are modeled with limited detail. In the absence of the appropriate model data, secondary circuits models commonly rely on simplifications such as single-phase models, constant power factor, etc. This paper highlights the implications of some of these assumptions and provides guidance in terms of how more accurate secondary models are needed. This paper shows that split-phase secondary circuits can be modeled accurately with single-phase equivalents under perfectly balanced conditions. It also shows that assuming constant power factor or using smart meter measurements with practical 15 min, or larger, time granularity can lead to considerable errors in simulated secondary circuit losses or voltages.
Autors: Jouni Peppanen;Celso Rocha;Jason A. Taylor;Roger C. Dugan;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 150 - 159
Publisher: IEEE
 
» Secrecy Rate Maximization With Outage Constraint in Multihop Relaying Networks
Abstract:
In this letter, we study the secure transmission in multihop wireless networks with randomize-and-forward relaying, in the presence of randomly distributed eavesdroppers. By considering adaptive encoder with ON–OFF transmission scheme, we investigate the optimal design of the wiretap code and routing strategies to maximize the secrecy rate while satisfying the secrecy outage probability constraint. We derive the exact expressions for the optimal rate parameters of the wiretap code. Then, the secure routing problem is solved by revising the classical Bellman–Ford algorithm. Simulation results are conducted to verify our analysis.
Autors: Jianping Yao;Yuan Liu;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 304 - 307
Publisher: IEEE
 
» Secure Communications in Three-Step Two-Way Energy Harvesting DF Relaying
Abstract:
Energy harvesting relaying is predicted to play a pivotal role in large-scale energy constrained networks. This letter evaluates the secrecy performance of a system that employs a three-step two-way decode-and-forward relay with the energy harvesting capability. More specifically, we derive a closed-form expression for the eavesdropping probability when the main and wiretap links experience independent shadowed fading. We evaluate the impact of the fading parameters, and the power splitting factor at the relay, on the secrecy performance. Our results indicate that for a small relay reception interval, secrecy can be enhanced by allocating more power for information decoding. Numerical results are provided to validate the derived results.
Autors: Furqan Jameel;Shurjeel Wyne;Zhiguo Ding;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 308 - 311
Publisher: IEEE
 
» Secure Internet of Things Deployment in the Cement Industry: Guidance for Plant Managers
Abstract:
Always-on Internet-connected devices [the so-called Internet of Things (IoT)] have become common tools deployed throughout the cement industry. As plant managers employ more automation technologies, the implementation of more connected devices can lead to information security and personnel safety concerns. IoT devices provide significant value in cost reduction, increased efficiency, and greater visibility for all aspects of the business. Along with the benefits of the IoT infrastructure, there are significant security concerns and challenges present in the deployment of this new technology. Recent implementations of IoT devices have shown a significant gap between actual application and best practices, exposing an organization to risks such as sensitive data exfiltration, malicious attackers, and potential safety issues (including the loss of life). An awareness of these concerns and challenges provides guidance to plant managers for mitigating the security weaknesses contained within connected devices while still reaping the benefits of the IoT infrastructure.
Autors: Patrick McNeil;
Appeared in: IEEE Industry Applications Magazine
Publication date: Feb 2018, volume: 24, issue:1, pages: 14 - 23
Publisher: IEEE
 
» Secure Transmission in Linear Multihop Relaying Networks
Abstract:
This paper studies the design and secrecy performance of linear multihop networks, in the presence of randomly distributed eavesdroppers in a large-scale 2-D space. Depending on whether there is feedback from the receiver to the transmitter, we study two transmission schemes: an ON–OFF transmission (OFT) and a non-ON–OFF transmission (NOFT). In the OFT scheme, transmission is suspended if the instantaneous received signal-to-noise ratio (SNR) falls below a given threshold, whereas, there is no suspension of transmission in the NOFT scheme. We investigate the optimal design of the linear multiple network in terms of the optimal rate parameters of the wiretap code as well as the optimal number of hops. These design parameters are highly interrelated, since more hops reduce the distance of per-hop communication, which completely changes the optimal design of the wiretap coding rates. Despite the analytical difficulty, we are able to characterize the optimal designs and the resulting secure transmission throughput in mathematically tractable forms in the high SNR regime. Our numerical results demonstrate that our analytical results obtained in the high SNR regime are accurate at practical SNR values. Hence, these results provide useful guidelines for designing linear multihop networks with targeted physical layer security performance.
Autors: Jianping Yao;Xiangyun Zhou;Yuan Liu;Suili Feng;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 822 - 834
Publisher: IEEE
 
» Seeds-Based Part Segmentation by Seeds Propagation and Region Convexity Decomposition
Abstract:
Object part segmentation is an important and challenging task in computer vision. The existing supervised part segmentation methods need pixel level training data which leads to a huge workload for the user. In this paper a weakly supervised part segmentation method is proposed which segments part regions from multiple images by only several seeds on an image. Two aspects such as seed propagation among multiple images and part generation from seeds are considered. The first aspect is to generate part seeds in each image in terms of seed propagation which is accomplished by part matching combined with latent object regions. We fuse the local part matching and global shape cosegmentation to avoid the noise propagation. The second aspect is to segment part regions from object regions and part seeds which is formulated as the object shape decomposition model. The shape convexity analysis and seed location are fused to accomplish the decomposition and the final part segmentation. The proposed method is verified on the PASCAL 2010 dataset Bird dataset Cat-Dog dataset and UCF Sports Actions dataset. Experimental results demonstrate the effectiveness of the proposed method with larger intersection over union (IOU) values compared with existing weakly supervised part generation methods.
Autors: Fanman Meng;Hongliang Li;Qingbo Wu;King Ngi Ngan;Jianfei Cai;
Appeared in: IEEE Transactions on Multimedia
Publication date: Feb 2018, volume: 20, issue:2, pages: 310 - 322
Publisher: IEEE
 
» Seismic Waveform Classification and First-Break Picking Using Convolution Neural Networks
Abstract:
Regardless of successful applications of the convolutional neural networks (CNNs) in different fields, its application to seismic waveform classification and first-break (FB) picking has not been explored yet. This letter investigates the application of CNNs for classifying time-space waveforms from seismic shot gathers and picking FBs of both direct wave and refracted wave. We use representative subimage samples with two types of labeled waveform classification to supervise CNNs training. The goal is to obtain the optimal weights and biases in CNNs, which are solved by minimizing the error between predicted and target label classification. The trained CNNs can be utilized to automatically extract a set of time-space attributes or features from any subimage in shot gathers. These attributes are subsequently inputted to the trained fully connected layer of CNNs to output two values between 0 and 1. Based on the two-element outputs, a discriminant score function is defined to provide a single indication for classifying input waveforms. The FB is then located from the calculated score maps by sequentially using a threshold, the first local minimum rule of every trace and a median filter. Finally, we adopt synthetic and real shot data examples to demonstrate the effectiveness of CNNs-based waveform classification and FB picking. The results illustrate that CNN is an efficient automatic data-driven classifier and picker.
Autors: Sanyi Yuan;Jiwei Liu;Shangxu Wang;Tieyi Wang;Peidong Shi;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 272 - 276
Publisher: IEEE
 
» Selected Papers from the 2017 IEEE Symposium on Security and Privacy
Abstract:
For 38 years, the IEEE Symposium on Security and Privacy has been the premier forum for presenting computer security and electronic privacy developments and for bringing together leading researchers and practitioners. We invited authors to submit revised versions of their symposium papers, recast as articles suitable for publication in IEEE Security & Privacy magazine. Specifically, we asked the original authors to revise their papers to speak to the magazine’s audience, which goes beyond the symposium’s traditional academically focused audience to also include policymakers and practitioners.
Autors: Terry Benzel;Sean Peisert;
Appeared in: IEEE Security & Privacy
Publication date: Feb 2018, volume: 16, issue:1, pages: 10 - 11
Publisher: IEEE
 
» Selective Offloading in Mobile Edge Computing for the Green Internet of Things
Abstract:
Mobile edge computing provides the radio access networks with cloud computing capabilities to fulfill the requirements of the Internet of Things services such as high reliability and low latency. Offloading services to edge servers can alleviate the storage and computing limitations and prolong the lifetimes of the IoT devices. However, offloading in MEC faces scalability problems due to the massive number of IoT devices. In this article, we present a new integration architecture of the cloud, MEC, and IoT, and propose a lightweight request and admission framework to resolve the scalability problem. Without coordination among devices, the proposed framework can be operated at the IoT devices and computing servers separately, by encapsulating latency requirements in offloading requests. Then a selective offloading scheme is designed to minimize the energy consumption of devices, where the signaling overhead can be further reduced by enabling the devices to be self-nominated or self-denied for offloading. Simulation results show that our proposed selective offloading scheme can satisfy the latency requirements of different services and reduce the energy consumption of IoT devices.
Autors: Xinchen Lyu;Hui Tian;Li Jiang;Alexey Vinel;Sabita Maharjan;Stein Gjessing;Yan Zhang;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 54 - 60
Publisher: IEEE
 
» Self-Aligning and Self-Calibrating Capacitive Sensor System for Displacement Measurement in Inaccessible Industrial Environments
Abstract:
High-precision positioning often requires high speed and high resolution displacement measurements in order to compensate for the small vibrations of critical components. The displacement sensor must be precise and stable over a long period of time to avoid expensive recalibration. This requires tight mounting tolerances, which are especially difficult to meet in inaccessible environments. The proposed sensor system is based on a capacitive sensor and consists of three subsystems: 1) a mechanical “zoom-in” system that performs self-alignment of the capacitive sensor electrode in order to reduce the mounting tolerances of the sensor; 2) a real-time capacitance-to-digital converter that employs an internal reference and electrical zoom-in technique to effectively reduce the dynamic range of the measured capacitance, thus improving the power efficiency; and 3) a self-calibration circuit that periodically calibrates the internal references to eliminate their drift. In previous publications, the three subsystems have been introduced. This paper shows how the different subsystems can be integrated to achieve optimal performance and presents new repeatability and stability measurement results. The overall system demonstrates a displacement measurement resolution of 65 pm (in terms of capacitance 65 aF) for a measurement time of 20 . Furthermore, the thermal drift of the sensor is within 6 ppm/K, owing to the self-calibration circuit. In measurement mode, the system consumes less than 16 mW.
Autors: Oscar S. van de Ven;Johan G. Vogel;Sha Xia;Jo W. Spronck;Stoyan Nihtianov;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 350 - 358
Publisher: IEEE
 
» Self-Calibrating Transmission-Reflection Technique for Constitutive Parameters Retrieval of Materials
Abstract:
A self-calibrating transmission-reflection method for extraction of electromagnetic properties of materials from waveguide measurements is proposed. It relies on three measurement steps (thru, empty line, and the same line loaded at any position by the sample) to extract electromagnetic properties. When compared with other nonresonant transmission-reflection methods, it has the following features: 1) it does not require application of any calibration method; 2) it does not need any knowledge of the position of the sample within its cell (position invariant); 3) it determines constitutive parameters of the sample; 4) it is noniterative; and 5) it does not involve any sign ambiguity in determination of constitutive parameters. The method was validated and its accuracy was compared with the accuracy of other methods from measured uncalibrated and calibrated scattering parameters of the polyethylene sample with different lengths (3.85 and 7.70 mm). We also applied our method for extraction of electromagnetic properties of a synthesized magnetic sample from its simulated scattering parameters by using the CST Microwave Studio. Following measurements, simulations, and validation, repeatability and uncertainty analyses were performed to access and improve the accuracy of the proposed method.
Autors: Ugur Cem Hasar;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 1081 - 1089
Publisher: IEEE
 
» Self-Holding Magneto-Optical Switch Integrated With Thin-Film Magnet
Abstract:
We demonstrate a novel self-holding function of a magneto-optical waveguide switch. The switching state is flipped by a pulsed current and maintained without any power supply by virtue of the nonvolatility of the thin-film magnet. Extinction ratios up to 15.4 dB were demonstrated. The switch state was controlled by a 1- pulsed electrical current.
Autors: Ken Okazeri;Kenji Muraoka;Yuya Shoji;Shigeki Nakagawa;Nobuhiko Nishiyama;Shigehisa Arai;Tetsuya Mizumoto;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 371 - 374
Publisher: IEEE
 
» Self-Localization Based on Visual Lane Marking Maps: An Accurate Low-Cost Approach for Autonomous Driving
Abstract:
Autonomous driving in public roads requires precise localization within the range of few centimeters. Even the best localization systems based on GNSS cannot always reach this level of precision, especially in an urban environment, where the signal is disturbed by surrounding buildings and artifacts. Recent works have shown the advantage of using maps as a precise, robust, and reliable way of localization. Typical approaches use the set of current readings from the vehicle sensors to estimate its position on the map. The approach presented in this paper exploits a short-range visual lane marking detector and a dead reckoning system to construct a registry of the detected back lane markings corresponding to the last 240 m driven. This information is used to search in the map the most similar section, to determine the vehicle localization in the map reference. Additional filtering is used to obtain a more robust estimation for the localization. The accuracy obtained is sufficiently high to allow autonomous driving in a narrow road. The system uses a low-cost architecture of sensors and the algorithm is light enough to run on low-power embedded architecture.
Autors: Rafael Peixoto Derenzi Vivacqua;Massimo Bertozzi;Pietro Cerri;Felipe Nascimento Martins;Raquel Frizera Vassallo;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 582 - 597
Publisher: IEEE
 
» Self-Reference-Based Hardware Trojan Detection
Abstract:
Outsourcing of the chip product chain makes hardware vulnerable to be attacked. For example, an attacker who has access to hardware fabrication process can alter the genuine hardware with the insertion of concealed hardware elements [hardware Trojan (HT)]. Therefore, microelectronic circuit HT detection becomes a key step of chip production. A self-reference-based power-analysis microelectronic circuit HT detection methodology is proposed in this paper. The detection method is implemented in 90-nm CMOS process. Based on simulation results, our proposed technique can detect HTs with areas that are 0.013% of the host-circuitry. ISCAS benchmarks are used to evaluate efficiency of the developed method.
Autors: Hao Xue;Saiyu Ren;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 2 - 11
Publisher: IEEE
 
» Semantic Segmentation of Aerial Images With Shuffling Convolutional Neural Networks
Abstract:
Semantic segmentation of aerial images refers to assigning one land cover category to each pixel. This is a challenging task due to the great differences in the appearances of ground objects. Many attempts have been made during the past decades. In recent years, convolutional neural networks (CNNs) have been introduced in the remote sensing field, and various solutions have been proposed to realize dense semantic labeling with CNNs. In this letter, we propose shuffling CNNs to realize semantic segmentation of aerial images in a periodic shuffling manner. This approach is a supplement to current methods for semantic segmentation of aerial images. We propose a naive version and a deeper version of this method, and both are adept at detecting small objects. Additionally, we propose a method called field-of-view (FoV) enhancement that can enhance the predictions. This method can be applied to various networks, and our experiments verify its effectiveness. The final results are further improved through an ensemble method that averages the score maps generated by the models at different checkpoints of the same network. We evaluate our models using the ISPRS Vaihingen and Potsdam data sets, and we acquire promising results using these two data sets.
Autors: Kaiqiang Chen;Kun Fu;Menglong Yan;Xin Gao;Xian Sun;Xin Wei;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 173 - 177
Publisher: IEEE
 
» Semantic Slicing of Software Version Histories
Abstract:
Software developers often need to transfer functionality, e.g., a set of commits implementing a new feature or a bug fix, from one branch of a configuration management system to another. That can be a challenging task as the existing configuration management tools lack support for matching high-level, semantic functionality with low-level version histories. The developer thus has to either manually identify the exact set of semantically-related commits implementing the functionality of interest or sequentially port a segment of the change history, “inheriting” additional, unwanted functionality. In this paper, we tackle this problem by providing automated support for identifying the set of semantically-related commits implementing a particular functionality, which is defined by a set of tests. We formally define the semantic slicing problem, provide an algorithm for identifying a set of commits that constitute a slice, and propose techniques to minimize the produced slice. We then instantiate the overall approach, CSlicer, in a specific implementation for Java projects managed in Git and evaluate its correctness and effectiveness on a set of open-source software repositories. We show that it allows to identify subsets of change histories that maintain the functionality of interest but are substantially smaller than the original ones.
Autors: Yi Li;Chenguang Zhu;Julia Rubin;Marsha Chechik;
Appeared in: IEEE Transactions on Software Engineering
Publication date: Feb 2018, volume: 44, issue:2, pages: 182 - 201
Publisher: IEEE
 
» Semiparametric Two-Component Mixture Models When One Component Is Defined Through Linear Constraints
Abstract:
We propose a structure of a semiparametric two-component mixture model when one component is parametric and the other is defined through linear constraints on either its distribution function or its quantile measure. Estimation of a two-component mixture model with an unknown component is very difficult when no particular assumption is made on the structure of the unknown component. A symmetry assumption was used in the literature to simplify the estimation. Such method has the advantage of producing consistent and asymptotically normal estimators, and identifiability of the semiparametric mixture model becomes tractable. Still, existing methods, which estimate a semiparametric mixture model have their limits when the parametric component has unknown parameters or the proportion of the parametric part is either very high or very low. We propose in this paper a method to incorporate a prior linear information about the unknown component in order to better estimate the model when existing estimation methods fail. This linear information is either translated by linear constraints, such as moment-type constraints or L-moments constraints (linear constraints over the quantile). The new method is based on divergences and has a non classical form since the minimization is carried over both arguments of the divergence. The resulting estimators are proved to be consistent and asymptotically normal under standard assumptions. We show that using the Pearson’s divergence our algorithm has a linear complexity when the constraints are moment-type. Simulations on univariate and multivariate mixtures demonstrate the viability and the interest of our novel approach.
Autors: Diaa Al Mohamad;Assia Boumahdaf;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 795 - 830
Publisher: IEEE
 
» Semisupervised Hyperspectral Image Classification Based on Generative Adversarial Networks
Abstract:
Because the collection of ground-truth labels is difficult, expensive, and time-consuming, classifying hyperspectral images (HSIs) with few training samples is a challenging problem. In this letter, we propose a novel semisupervised algorithm for the classification of hyperspectral data by training a customized generative adversarial network (GAN) for hyperspectral data. The GAN constructs an adversarial game between a discriminator and a generator. The generator generates samples that are not distinguishable by the discriminator, and the discriminator determines whether or not a sample is composed of real data. We design a semisupervised framework for HSI data based on a 1-D GAN (HSGAN). This framework enables the automatic extraction of spectral features for HSI classification. When HSGAN is trained using unlabeled hyperspectral data, the generator can generate hyperspectral samples that are similar to the real data, while the discriminator contains the features, which can be used to classify hyperspectral data with only a small number of labeled samples. The performance of the HSGAN is evaluated on the Airborne Visible Infrared Imaging Spectrometer image data, and the results show that the proposed framework achieves very promising results with a small number of labeled samples.
Autors: Ying Zhan;Dan Hu;Yuntao Wang;Xianchuan Yu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 212 - 216
Publisher: IEEE
 
» Sensing Passive Eye Response to Impact Induced Head Acceleration Using MEMS IMUs
Abstract:
The eye may act as a surrogate for the brain in response to head acceleration during an impact. Passive eye movements in a dynamic system are sensed by microelectromechanical systems (MEMS) inertial measurement units (IMU) in this paper. The technique is validated using a three-dimensional printed scaled human skull model and on human volunteers by performing drop-and-impact experiments with ribbon-style flexible printed circuit board IMUs inserted in the eyes and reference IMUs on the heads. Data are captured by a microcontroller unit and processed using data fusion. Displacements are thus estimated and match the measured parameters. Relative accelerations and displacements of the eye to the head are computed indicating the influence of the concussion causing impacts.
Autors: Yuan Meng;Brent Bottenfield;Mark Bolding;Lei Liu;Mark L. Adams;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Publication date: Feb 2018, volume: 12, issue:1, pages: 182 - 191
Publisher: IEEE
 
» Sensitive Photodetection Based on the Surface States of p-Type Silicon
Abstract:
We report a new photodetector based on the surface states of p-type silicon. By combining the application of external fields with laser illumination, the current intensity on the surface of p-type silicon is 578 times larger than that only applied by external fields. Intriguingly, the change of current is closely related to the laser position, and we can detect an obvious current change even if the laser position is more than 1000 away from the electrode. We attribute this to a combined effect: the lateral photovoltaic contribution induced by the surface state of p-type silicon and a sharp increase of photo-excited carriers on the surface due to the change of depletion layer caused by external electric fields. This result provides the possibility for the future use of p-type silicon in the field of photodetection. Due to its sensitivity, simpler structure, and low cost, this kind of the photodetector is expected to be a promising photodetector.
Autors: Bowei Zhou;Zhikai Gan;Anhua Dong;Sipei Wang;Hui Wang;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 236 - 239
Publisher: IEEE
 
» Sensor Choice for Minimum Error Variance Estimation
Abstract:
A Kalman filter is optimal in that the variance of the error is minimized by the estimator. It is shown here, in an infinite-dimensional context, that the solution to an operator Riccati equation minimizes the steady-state error variance. This extends a result previously known for lumped parameter systems to distributed parameter systems. It is shown then that minimizing the trace of the Riccati operator is a reasonable criterion for choosing sensor locations. It is then shown that multiple inaccurate sensors, that is, those with large noise variance, can provide as good an estimate as a single highly accurate (but probably more expensive) sensor. Optimal sensor location is then combined with estimator design. A framework for calculation of the best sensor locations using approximations is established and sensor location as well as choice is investigated with three examples. Simulations indicate that the sensor locations do affect the quality of the estimation and that multiple low-quality sensors can lead to better estimation than a single high-quality sensor.
Autors: Minxin Zhang;Kirsten Morris;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Feb 2018, volume: 63, issue:2, pages: 315 - 330
Publisher: IEEE
 
» Sensor city- A global innovation hub for sensor technology
Abstract:
Sensors and the Internet of Things (IoT) are driving the next wave of technological innovation, transforming lives and growing the economy. By connecting digital devices to the physical world around them, the impact of these emerging technologies on our data-driven society is limitless. The sensor market is growing at over 10% per year, and it is currently worth around US $500 billion globally. The growth in sensors is linked to the increased adoption of the Industrial Internet of Things (IIoT) and Industry 4.0. The fourth industrial revolution technologies, including Big Data, autonomous systems, systems integration and cloud computing, are transforming modern manufacturing by enabling the generation and analysis of digital data that supports the development of smarter products, processes and supply chains. Innovation in this sector is also happening at a very fast pace. Strengthening the link between academia and industry is therefore essential to guarantee that academic research in instrumentation and measurement gets rapidly to the market, and at the same time, innovative ideas from industry get the necessary academic support. This is where Sensor City can help.
Autors: Roberto Ferrero;Elizabeth Beattie;Joanne Phoenix;
Appeared in: IEEE Instrumentation & Measurement Magazine
Publication date: Feb 2018, volume: 21, issue:1, pages: 4 - 16
Publisher: IEEE
 
» Separability-Oriented Subclass Discriminant Analysis
Abstract:
Linear discriminant analysis (LDA) is a classical method for discriminative dimensionality reduction. The original LDA may degrade in its performance for non-Gaussian data, and may be unable to extract sufficient features to satisfactorily explain the data when the number of classes is small. Two prominent extensions to address these problems are subclass discriminant analysis (SDA) and mixture subclass discriminant analysis (MSDA). They divide every class into subclasses and re-define the within-class and between-class scatter matrices on the basis of subclass. In this paper we study the issue of how to obtain subclasses more effectively in order to achieve higher class separation. We observe that there is significant overlap between models of the subclasses, which we hypothesise is undesirable. In order to reduce their overlap we propose an extension of LDA, separability oriented subclass discriminant analysis (SSDA), which employs hierarchical clustering to divide a class into subclasses using a separability oriented criterion, before applying LDA optimisation using re-defined scatter matrices. Extensive experiments have shown that SSDA has better performance than LDA, SDA and MSDA in most cases. Additional experiments have further shown that SSDA can project data into LDA space that has higher class separation than LDA, SDA and MSDA in most cases.
Autors: Huan Wan;Hui Wang;Gongde Guo;Xin Wei;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 409 - 422
Publisher: IEEE
 
» Separately Excited Synchronous Motor With Rotary Transformer for Hybrid Vehicle Application
Abstract:
The cost of rare earth (RE) permanent magnet along with the associated supply volatility have intensified the interests for machine topologies, which eliminate or reduce the RE magnets usage. This paper presents one such design solution, the separately excited synchronous motor (SESM) that eliminates RE magnets, but does not sacrifice the peak torque and power of the motor. The major drawback of such motors is the necessity of brushes to supply the field current. This is especially a challenge for hybrid or electric vehicle applications where the machine is actively cooled with oil inside the transmission. Sealing the brushes from the oil is challenging and would limit the application of such a motor inside a transmission. To overcome this problem, a contactless rotary transformer is designed and implemented for the rotor field excitation. The designed motor is built and tested. The test data show that the designed motor outperforms an equivalent interior permanent magnet (IPM) motor, which is optimized for a hybrid application for both peak torque and power. Better drive system efficiency is measured at high speed compared with the IPM machine, while the latter outperforms (for efficiency) the SESM at low- and medium-speed range.
Autors: Constantin Stancu;Terence Ward;Khwaja M. Rahman;Robert Dawsey;Peter Savagian;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 223 - 232
Publisher: IEEE
 
» Separation of Sources From Single-Channel EEG Signals Using Independent Component Analysis
Abstract:
The electroencephalogram (EEG) signals are often mixed with several sources such as electrooculogram and electromyogram signals. Independent component analysis (ICA) is often used to separate the sources from the multichannel EEG signals. Recently, the use of portable EEG devices has gained much attention due to their low power consumption and the ability to record the EEG signals in home environment. However, these systems are equipped with single or few EEG channels, and hence the direct application of ICA is not possible. In this paper, we proposed an efficient technique to separate the sources from single-channel EEG signals by combining the singular spectrum analysis (SSA) and ICA techniques. In this technique, the single-channel EEG data are first decomposed into multivariate data using SSA. Later, ICA is applied on the multivariate data to extract the source signals. In order to validate the performance of the proposed technique, we carried out the simulation on synthetic and real life EEG signals. In addition, we have also studied the performance of the proposed technique for detecting the seizures. The performance measures of a seizure detection classifier such as receiver operating curve, true positive rate, and false positive rate are obtained and found that the proposed technique exhibits better performance compared with the existing methods.
Autors: Ajay Kumar Maddirala;Rafi Ahamed Shaik;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 382 - 393
Publisher: IEEE
 
» Setting Sail Toward a Bright Future [Presidents' Column]
Abstract:
Presents the President’s message for this issue of the publication.
Autors: Tom Brazil;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 11 - 19
Publisher: IEEE
 
» Shading-Based Surface Detail Recovery Under General Unknown Illumination
Abstract:
Reconstructing the shape of a 3D object from multi-view images under unknown, general illumination is a fundamental problem in computer vision. High quality reconstruction is usually challenging especially when fine detail is needed and the albedo of the object is non-uniform. This paper introduces vertex overall illumination vectors to model the illumination effect and presents a total variation (TV) based approach for recovering surface details using shading and multi-view stereo (MVS). Behind the approach are the two important observations: (1) the illumination over the surface of an object often appears to be piecewise smooth and (2) the recovery of surface orientation is not sufficient for reconstructing the surface, which was often overlooked previously. Thus we propose to use TV to regularize the overall illumination vectors and use visual hull to constrain partial vertices. The reconstruction is formulated as a constrained TV-minimization problem that simultaneously treats the shape and illumination vectors as unknowns. An augmented Lagrangian method is proposed to quickly solve the TV-minimization problem. As a result, our approach is robust, stable and is able to efficiently recover high-quality surface details even when starting with a coarse model obtained using MVS. These advantages are demonstrated by extensive experiments on the state-of-the-art MVS database, which includes challenging objects with varying albedo.
Autors: Di Xu;Qi Duan;Jianmin Zheng;Juyong Zhang;Jianfei Cai;Tat-Jen Cham;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 423 - 436
Publisher: IEEE
 
» Shadow Radiation Iterative Physical Optics Method for High-Frequency Scattering
Abstract:
A shadow-radiation-based fast iterative physical optics (IPO) scheme, for the analysis of the scattering from large complex geometries involving multiple reflection and occlusion effects, is proposed. By employing a “shadow-radiation” mechanism, the scheme alleviates the need for expensive computation and storage of a geometric visibility function. In a nested fashion, shadow radiation iterations are performed for each “bounce” in the conventional multiple reflection IPO scheme. The resulting method makes use of simple field integrals which are all accelerable using a multilevel nonuniform grid-based field evaluation algorithm, with a modification tailored to the scheme’s integral kernels. The proposed scheme is also shown analytically to be a more stable (faster converging) equivalent of existing IPO schemes. The method is studied in terms of accuracy and performance for representative examples and compared with alternative physical optics and numerically exact solution techniques.
Autors: Igor Gershenzon;Yaniv Brick;Amir Boag;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 871 - 883
Publisher: IEEE
 
» Shaped Polar Codes for Higher Order Modulation
Abstract:
A new polar coding scheme for higher order modulation is presented. An encoding method is proposed such that in combination with Gray labeled amplitude shift keying the channel input symbols have a desired non-uniform distribution, resulting in a shaping gain at the receiver compared with the conventional bit-interleaved coded modulation. The proposed scheme mainly affects the encoder, and the complexity increase at the receiver is negligible.
Autors: Onurcan İşcan;Ronald Böhnke;Wen Xu;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 252 - 255
Publisher: IEEE
 
» Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs
Abstract:
Two sets of 0–1 vectors of fixed length form a uniquely decodeable code pair if their Cartesian product is of the same size as their sumset, where the addition is pointwise over integers. For the size of the sumset of such a pair, van Tilborg has given an upper bound in the general case. Urbanke and Li, and later Ordentlich and Shayevitz, have given better bounds in the unbalanced case, that is, when either of the two sets is sufficiently large. Improvements to the latter bounds are presented.
Autors: Per Austrin;Petteri Kaski;Mikko Koivisto;Jesper Nederlof;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1368 - 1373
Publisher: IEEE
 
» SHINE+: A General Framework for Domain-Specific Entity Linking with Heterogeneous Information Networks
Abstract:
Heterogeneous information networks that consist of multi-type, interconnected objects are becoming increasingly popular, such as social media networks and bibliographic networks. The task of linking named entity mentions detected from unstructured Web text with their corresponding entities in a heterogeneous information network is of practical importance for the problem of information network population. This task is challenging due to name ambiguity and limited knowledge existing in the network. Most existing entity linking methods focus on linking entities with Wikipedia and cannot be applied to our task. In this paper, we present SHINE+, a general framework for linking named entitieS in Web free text with a Heterogeneous I nformation NEtwork. We propose a probabilistic linking model, which unifies an entity popularity model with an entity object model. As the entity knowledge contained in the information network is insufficient, we propose a knowledge population algorithm to iteratively enrich the network entity knowledge by leveraging the context information of mentions mapped by the linking model with high confidence, which subsequently boosts the linking performance. Experimental results over two real heterogeneous information networks (i.e., DBLP and IMDb) demonstrate the effectiveness and efficiency of our proposed framework in comparison with the baselines.
Autors: Wei Shen;Jiawei Han;Jianyong Wang;Xiaojie Yuan;Zhenglu Yang;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Feb 2018, volume: 30, issue:2, pages: 353 - 366
Publisher: IEEE
 
» Short-Time and High-Precision Measurement Method for Larmor Frequency of Marine Overhauser Sensor
Abstract:
The measurement accuracy of the Larmor frequency of the Overhauser magnetic sensor directly determines the magnetic accuracy of the Overhauser magnetometer. We propose a multichannel interpolation method for marine magnetic measurements, addressing specifically the deficiencies in traditional measurement methods. The quantization error of the count value of the standard signal is greatly reduced using the delay chain interpolation technique. Also the influence arising from the phase error is weakened through channel expansion. In addition, we also design a test platform and conduct two sets of field contrast tests, the test results showing that the proposed method not only improves the precision of the frequency measurement by about three times but also improves the resolution and lowers the noise level of the system.
Autors: Jian Ge;Xiangyu Qiu;Haobin Dong;Wang Luo;Huan Liu;Zhiwen Yuan;Jun Zhu;Haiyang Zhang;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1442 - 1448
Publisher: IEEE
 
» Signal Processing and Coding Techniques for 2-D Magnetic Recording: An Overview
Abstract:
Two-dimensional magnetic recording (TDMR) is an emerging storage technology that aims to achieve areal densities on the order of 10 Tb/in2, mainly driven by innovative channels engineering with minimal changes to existing head/media designs within a systems framework. Significant additive areal density gains can be achieved by using TDMR over bit patterned media (BPM) and energy-assisted magnetic recording (EAMR). In TDMR, the sectors are inherently 2-D with reduced track pitch and bit widths, leading to severe 2-D intersymbol interference (ISI). This necessitates the development of powerful 2-D signal processing and coding algorithms for mitigating 2-D ISI, timing artifacts, jitter, and electronics noise resulting from irregular media grain positions and read-head electronics. The algorithms have to be eventually realized within a read/write channel architecture as a part of a system-on-chip (SoC) within the disk controller system. In this work, we provide a wide overview of TDMR technology, channel models and capacity, signal processing algorithms (detection and timing recovery), and error-correcting codes attuned to 2-D channels. The innovations and advances described not only make TDMR a promising future technology, but may serve a broader engineering audience as well.
Autors: Shayan Srinivasa Garani;Lara Dolecek;John Barry;Frederic Sala;Bane Vasić;
Appeared in: Proceedings of the IEEE
Publication date: Feb 2018, volume: 106, issue:2, pages: 286 - 318
Publisher: IEEE
 
» Silica Planar Lightwave Circuit Based Integrated 1 $times$ 4 Polarization Beam Splitter Module for Free-Space BB84 Quantum Key Distribution
Abstract:
We have developed an integrated polarization beam splitter (PBS) module with silica planar lightwave circuit technology for use in BB84 quantum key distribution (QKD). The PBS module is designed to operate on four linear polarizations of the horizontal/vertical/diagonal/antidiagonal direction, and shows the minimum polarization extinction ratio of 17.6 dB. When the module is loaded on the free-space BB84 QKD test-bed, quantum bit error rate and sifted key rate are 2.81% and 415 kb/s at clock rate of 100 MHz, respectively.
Autors: Joong-Seon Choe;Heasin Ko;Byung-Seok Choi;Kap-Joong Kim;Chun Ju Youn;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 8
Publisher: IEEE
 
» Silicon Design and Measurement [Book/Software Reviews]
Abstract:
The motivation for his book stems from the complexity of on-wafer measurements and their associated characterization techniques. His intent is to bridge the gap between academic knowledge and real-world silicon design and measurement and also to satisfy the needs of modern RF integrated circuit designers and researchers. Dr. Lourandakis provides a complete and comprehensive guide to performing on-wafer measurements, calibration, and de-embedding of silicon-integrated passive devices. The book opens with an introduction to two basic domains of signal analysis: frequency- and time-domain analysis.
Autors: James Chu;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 114 - 115
Publisher: IEEE
 
» Silver Bullet Talks with Wafaa Mamilli
Abstract:
Gary McGraw talks to Wafaa Mamilli is vice president, chief information security officer (CISO) at Eli Lilly and Company, a pharmaceutical company, where she leads a global enterprise-wide information and product security organization.
Autors: Gary McGraw;
Appeared in: IEEE Security & Privacy
Publication date: Feb 2018, volume: 16, issue:1, pages: 6 - 9
Publisher: IEEE
 
» Simple and Accurate Low SNR Ergodic Capacity Approximations
Abstract:
Some of the existing ergodic capacity approximations for the low signal-to-noise ratio (SNR) region may lack accuracy. To overcome this, we derive two simple yet accurate Padé approximations for the low-SNR ergodic capacity. These approximations utilize the channel moments, which need not be updated for each distinct SNR value. The moments can be derived from the probability density function or from the moment generating function. For instance, we derive the general expressions for the moments of multiple input single output and multiple input multiple output channels. Numerical results demonstrate the superior accuracy of our approximations over some of the existing approximations. Moreover, we demonstrate how our approximations can be efficiently used to analyze several types of wireless links.
Autors: Bitan Banerjee;Ahmad Abu Al Haija;Chintha Tellambura;Himal A. Suraweera;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 356 - 359
Publisher: IEEE
 
» Simple Stabilized Radio-Frequency Transfer With Optical Phase Actuation
Abstract:
We describe and experimentally evaluate a stabilized radio-frequency transfer technique that employs optical phase sensing and optical phase actuation. This technique is achieved by modifying existing optical frequency transfer equipment and also exhibits advantages over previous stabilized radiofrequency transfer techniques in terms of size and complexity. Acousto-optic modulators (AOMs) are used to modulate an optical carrier. Stabilization of frequency fluctuations in the link is achieved by steering the frequency of one of the AOMs. We demonstrate the stabilized transfer of a 160-MHz signal over a 166-km fiber optical link, achieving an Allan deviation of 9.7 × 10-12 at 1 s of integration, and 6.4 × 10-15 at 104 s. This technique was considered for application to the Square Kilometre Array SKA1-low radio telescope.
Autors: David R. Gozzard;Sascha W. Schediwy;Benjamin Courtney-Barrer;Richard Whitaker;Keith Grainge;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:3, pages: 258 - 261
Publisher: IEEE
 
» Simulation of Constrained Musculoskeletal Systems in Task Space
Abstract:
Objective: This paper proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics. Methods: The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the direct marker control and an adaptation of the computed muscle control algorithms for solving the inverse kinematics and muscle redundancy problems, respectively. Results: Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection. Significance: The incorporation of constraints in the derivation unveils an important extension of this framework toward addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy, and most importantly, offers an abstract point of view and control, which can be advantageous toward further integration with high level models of the precommand level. Conclusion: Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.
Autors: Dimitar Stanev;Konstantinos Moustakas;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 307 - 318
Publisher: IEEE
 
» Simulation Study of a Novel Snapback-Free and Low Turn-Off Loss Reverse-Conducting IGBT With Controllable Trench Gate
Abstract:
A novel ultra-fast snapback-free controllable trench gate (CTG) reverse-conducting insulated gate bipolar transistor (RC-IGBT) is proposed and investigated by simulation. It features a CTG in the collector side and a bias voltage () is applied between the CTG and collector electrode. In the forward conduction state with , a high-density hole inversion layer is formed around the CTG. The CTG acts as not only a folded controllable hole injector to enhance the hole injection efficiency, but also an electron barrier to increase the distributed resistance. The CTG RC-IGBT achieves a low on-state voltage drop () and snapback-free with a small cell pitch. In the blocking state with , an electron accumulation layer is formed around the CTG. The electron layer together with the CTG acts as an equivalent N-buffer layer to stop the electric field and support high breakdown voltage. During turn-off, the CTG RC-IGBT behaves like a unipolar device without long tail current because the hole injection is deactivated by properly switching the . Compared with conventional RC-IGBT, the proposed device decreases the and turn-off energy loss () by 34% and 74%, respectively, under the load current of 100 A/cm2 and bus voltage of 600 V.
Autors: Jie Wei;Xiaorong Luo;Linhua Huang;Bo Zhang;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 252 - 255
Publisher: IEEE
 
» Simultaneous Microwave Photonic Analog-to-Digital Conversion and Digital Filtering
Abstract:
We proposed a scheme which can simultaneously realize photonic analog-to-digital conversion (PADC) and digital photonic filtering for microwave signals. A multi-tap optical pulse shaper is adopted in a photonic sampling and electrical quantizing PADC to change its equivalent channel response, which can be designed and flexibly reconfigured as a finite impulse response digital filter. The principle and operation conditions of the proposed scheme are theoretically analyzed. A system employing an optical time division multiplexing (OTDM)-based multi-tap shaper is demonstrated. Filtering features agreeing well with the theoretical and simulation results are experimentally measured by configuring the path attenuations and delays in the OTDM based shaper.
Autors: Sitong Wang;Guiling Wu;Feiran Su;Jianping Chen;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 343 - 346
Publisher: IEEE
 
» Simultaneous Multimodal PC Access for People With Disabilities by Integrating Head Tracking, Speech Recognition, and Tongue Motion
Abstract:
Multimodal Tongue Drive System (mTDS) is a highly integrated wireless assistive technology (AT) in the form of a lightweight wearable headset that utilizes three remaining key control and communication abilities in people with severe physical disabilities, such as tetraplegia, to provide them with effective access to computers: 1) tongue motion for discrete/switch-based control (e.g., clicking), 2) head tracking for proportional control (e.g., mouse pointer movements), and 3) speech recognition for typing, all available simultaneously. The mTDS architecture is presented here with new sensor signal processing algorithm for head tracking. To evaluate the device performance, it was compared against keyboard-and-mouse (KnM) combination, the gold standard in computer input methods, by 15 able-bodied participants, who used both mTDS and KnM to generate and sent an email with randomly selected content, under a 5-minute time constraint. In four repetitions, in the last trial, it took participants only 1.8 times longer to complete the email task, on average, using the mTDS versus KnM at 82.4% typing accuracy. Mean task completion time and typing accuracy improved 24.6% and 18.8% from first to fourth trial using mTDS. Multimodal simultaneous discrete and proportional control input options of mTDS, plus rapid typing, is expected to provide more effective computer access to people with severe physical disabilities.
Autors: M. Nazmus Sahadat;Arish Alreja;Maysam Ghovanloo;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Publication date: Feb 2018, volume: 12, issue:1, pages: 192 - 201
Publisher: IEEE
 
» Sine-Wall Space-Tapered Linear Slot Array Antenna With Low Sidelobe and Second-Order Lobe Levels
Abstract:
A new sine-wall slot array antenna is proposed by using the space-tapered technique to decrease both sidelobe level (SLL) and second-order lobe level (SOLL), simultaneously. In the proposed method, the genetic optimization algorithm is utilized to implement the space-tapered technique and achieve the slots center positions. Then, the waveguide side walls are rippled by sine-form segments to achieve uniform slots excitation needed in the space-tapered technique. Finally, a seven-slot array is designed and fabricated at 9.375 GHz to demonstrate the proposed idea. The proposed slot array achieves 14 dB gain and about 7.5 dB lower SLL as well as 7 dB lower SOLL and compared with the well-known Elliott’s design procedure.
Autors: Ali Pesarakloo;Seyed Hassan Sedighy;Farrokh Hodjatkashani;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 1020 - 1024
Publisher: IEEE
 
» Single-Scan High-Resolution 2-D $J$ -Resolved Spectroscopy in Inhomogeneous Magnetic Fields
Abstract:
Objective: A method is proposed to obtain high-resolution 2-D -resolved nuclear magnetic resonance (NMR) spectra in inhomogeneous magnetic fields. Methods: The proposed experiment enables the acquisition of an entire 2-D spectrum in a single scan by utilizing intermolecular double-quantum coherences and the spatial encoding of NMR observables. Results: Chemical shifts, coupling constants, and multiplet patterns are recovered even when field inhomogeneities are severe enough to completely obscure conventional NMR spectra. After intentional deshimming to yield inhomogeneous magnetic fields, the method was demonstrated on ethyl 3-bromoproprionate in acetone and on a complex mixture of organic compounds. To illustrate the technique's applicability to biological samples with intrinsic magnetic field inhomogeneities arising from macroscopic magnetic susceptibility variations, we performed the experiment on a pig bone marrow sample. Conclusion: Our results show that the new method is a fast and effective tool for studying complex chemical mixtures and biological tissues. Significance: The method could potentially be useful for real-time in vivo NMR studies.
Autors: Kaiyu Wang;Yuqing Huang;Pieter E. S. Smith;Zhiyong Zhang;Shuhui Cai;Zhong Chen;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 440 - 448
Publisher: IEEE
 
» SINR and Throughput of Dense Cellular Networks With Stretched Exponential Path Loss
Abstract:
Distance-based attenuation is a critical aspect of wireless communications. As opposed to the ubiquitous power-law path loss model, this paper proposes a stretched exponential path loss model that is suitable for short-range communication. In this model, the signal power attenuates over a distance as , where and are tunable parameters. Using experimental propagation measurements, we show that the proposed model is accurate for short to moderate distances in the range meters and so is a suitable model for dense and ultradense networks. We integrate this path loss model into a downlink cellular network with base stations modeled by a Poisson point process, and derive expressions for the coverage probability, potential throughput, and area spectral efficiency. Although the most general result for coverage probability has a double integral, several special cases are given, where the coverage probability has a compact or even closed form. We then show that the potential throughput is maximized for a particular BS density and then collapses to zero for high densities, assuming a fixed signal-to-interference-plus-noise ratio (SINR) threshold. We next prove that the area spectral efficiency, which assumes an adaptive SINR threshold, is nondecreasing with the BS density and converges to a constant for high densities.
Autors: Ahmad AlAmmouri;Jeffrey G. Andrews;François Baccelli;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1147 - 1160
Publisher: IEEE
 
» Sitael Hollow Cathodes for Low-Power Hall Effect Thrusters
Abstract:
Low-power Hall effect thrusters (HETs) belong to a class of electric thrusters with an operating power lower than 500 W. The application of this class of HETs is suited for small satellites for telecommunications and Earth observation missions. Sitael is active in this field, through the development of two HETs, HT100, and HT400, belonging to a power class of 100 and 400 W, respectively. HT100 is a permanent-magnet thruster operating in the 100- to 250-W range, providing thrust between 4 and 13 mN, and specific impulse between 900 and 1400 s. HT400 operates in the 350- to 750-W range, providing thrust between 20 and 45 mN, and specific impulse between 1300 and 1700 s. Two cathodes have been developed and tested, referred to as HC1 and HC3, conceived for HT100 and HT400, respectively. Both cathodes are based on Sitael heritage in theoretical modeling and experimental activities for the development of such devices, and rely on lanthanum hexaboride emitters. HC1 is a cathode designed to provide a discharge current in the 0.3–1 A range, operating in steady-state conditions at mass flow rates between 0.08 and 0.5 mg/s of xenon. HC3 was designed for the range 1–3 A of discharge current, with 0.08–0.5 mg/s of mass flow rate. Both HC1 and HC3 have an expected lifetime higher than 104 h, based on the rate of material evaporation from the emitter surface, computed with the aid of a theoretical model developed to guide the cathode design. Experiments were carried out, including preliminary characterization campaigns, of each of the two cathodes and HET-cathode coupling tests. The collected data are presented and discussed with reference to the model predictions, showing a good agreement between theoretical and experimental results.
Autors: Daniela Pedrini;Cosimo Ducci;Tommaso Misuri;Fabrizio Paganucci;Mariano Andrenucci;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Feb 2018, volume: 46, issue:2, pages: 296 - 303
Publisher: IEEE
 
» Slow-Light Effect and Mode Selection of Double Fiber Ring With a Fiber Bragg Grating
Abstract:
A novel slow-light reflector composed of a double-ring resonator with a uniform fiber Bragg grating (FBG) incorporated is proposed in this paper, which can be used as a mirror of narrow-linewidth fiber laser, based on its enlarged group delay, and as a high-sensitivity sensor. Its characteristics are investigated theoretically and experimentally in this paper. Compared with the single fiber ring the amplitude of resonance is modulated, the effective mode spacing is expanded greatly, due to the Vernier effect, giving much better mode selectivity. Mode hopping is believed to be suppressed effectively in applications of narrow-linewidth lasers, and resolution will be enhanced in sensor applications.
Autors: Xiaoqiong Qin;Zujie Fang;Kang Ying;Zhidan Ding;Di Wang;Fang Wei;Fei Yang;Qing Ye;Ronghui Qu;Haiwen Cai;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 9
Publisher: IEEE
 
» Smart Carbon Fiber Transtibial Prosthesis Based on Embedded Fiber Bragg Gratings
Abstract:
This paper presents the utilization of optical fiber Bragg gratings (FBGs) embedded into a carbon fiber reinforced polymer transtibial prosthesis to evaluate the user’s gait, and its own performance. Static mechanical tests were performed to characterize the sensors. Vertically and horizontally positioned FBGs within the structure have been used for load and strain force evaluation during real-time experiments with a candidate at different speeds on a treadmill. For simplicity, one non-amputee candidate performed the experiments using a mechanical adaptation. Distinctive patterns of response of the FBGs located at different points within the prosthetic structure enabled the differentiation between slow and fast motion gait cycle and the force distribution during the tread. This optical instrumentation contributes to the development of a new tool for the evaluation of prosthesis design and amputee patients rehabilitation and to the assessment of the performance of athletes during training or competition.
Autors: José Rodolfo Galvão;Carlos R. Zamarreño;Cicero Martelli;Jean Carlos Cardozo da Silva;Francisco J. Arregui;Ignacio R. Matías;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1520 - 1527
Publisher: IEEE
 
» Social Big-Data-Based Content Dissemination in Internet of Vehicles
Abstract:
By analogy with Internet of things, Internet of vehicles (IoV) that enables ubiquitous information exchange and content sharing among vehicles with little or no human intervention is a key enabler for the intelligent transportation industry. In this paper, we study how to combine both the physical and social layer information for realizing rapid content dissemination in device-to-device vehicle-to-vehicle (D2D-V2V)-based IoV networks. In the physical layer, headway distance of vehicles is modeled as a Wiener process, and the connection probability of D2D-V2V links is estimated by employing the Kolmogorov equation. In the social layer, the social relationship tightness that represents content selection similarities is obtained by Bayesian nonparametric learning based on real-world social big data, which are collected from the largest Chinese microblogging service Sina Weibo and the largest Chinese video-sharing site Youku. Then, a price-rising-based iterative matching algorithm is proposed to solve the formulated joint peer discovery, power control, and channel selection problem under various quality-of-service requirements. Finally, numerical results demonstrate the effectiveness and superiority of the proposed algorithm from the perspectives of weighted sum rate and matching satisfaction gains.
Autors: Zhenyu Zhou;Caixia Gao;Chen Xu;Yan Zhang;Shahid Mumtaz;Jonathan Rodriguez;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 768 - 777
Publisher: IEEE
 
» Social-Aware Movie Recommendation via Multimodal Network Learning
Abstract:
With the rapid development of Internet movie industry social-aware movie recommendation systems (SMRs) have become a popular online web service that provide relevant movie recommendations to users. In this effort many existing movie recommendation approaches learn a user ranking model from user feedback with respect to the movie's content. Unfortunately this approach suffers from the sparsity problem inherent in SMR data. In the present work we address the sparsity problem by learning a multimodal network representation for ranking movie recommendations. We develop a heterogeneous SMR network for movie recommendation that exploits the textual description and movie-poster image of each movie as well as user ratings and social relationships. With this multimodal data we then present a heterogeneous information network learning framework called SMR-multimodal network representation learning (MNRL) for movie recommendation. To learn a ranking metric from the heterogeneous information network we also developed a multimodal neural network model. We evaluated this model on a large-scale dataset from a real world SMR Web site and we find that SMR-MNRL achieves better performance than other state-of-the-art solutions to the problem.
Autors: Zhou Zhao;Qifan Yang;Hanqing Lu;Tim Weninger;Deng Cai;Xiaofei He;Yueting Zhuang;
Appeared in: IEEE Transactions on Multimedia
Publication date: Feb 2018, volume: 20, issue:2, pages: 430 - 440
Publisher: IEEE
 
» Soft-Switched High Voltage Gain Boost-Integrated Flyback Converter Interfaced Single-Phase Grid-Tied Inverter for SPV Integration
Abstract:
A two-stage grid-tied efficient solar photovoltaic (SPV) system with zero voltage switching (ZVS) and zero current switching (ZCS) at the dc–dc converter stage and adaptive synchronization at the inverter stage is proposed. In the first stage, an improved high step-up boost-integrated flyback converter with quasi resonant voltage multiplier cell is proposed. ZVS turn-on of all mosfets and ZCS turn-off of all diodes of resonant voltage multiplier cell results in high efficient power conversion compared with the conventional boost-integrated flyback converters. Small-sized coupled inductor enhances magnetic utilization in this converter. Second stage consists of a single-phase H-bridge grid interfaced inverter with variable band hysteresis current control technique. Amplitude adaptive notch filter is used to extract fundamental unit voltage vector of grid voltage required for estimation of synchronized reference current for hysteresis controller. A 250 W laboratory prototype is developed and experimentally evaluated. Experimental results demonstrate efficient renewable energy conversion at dc–dc converter stage and quality power injection at dc–ac inverter stage of the proposed grid-tied SPV system under changing solar insulation levels.
Autors: Amardeep B. Shitole;Shelas Sathyan;H. M. Suryawanshi;Girish G. Talapur;Pradyumn Chaturvedi;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 482 - 493
Publisher: IEEE
 
» Software Bots
Abstract:
Although the development and widespread adoption of software bots has occurred in just a few years, bots have taken on many diverse tasks and roles. This article discusses current bot technology and presents a practical case study on how to use bots in software engineering.
Autors: Carlene Lebeuf;Margaret-Anne Storey;Alexey Zagalsky;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 18 - 23
Publisher: IEEE
 
» Software Safety and Security Risk Mitigation in Cyber-physical Systems
Abstract:
Cyber-physical systems (CPSs) offer many opportunities but pose many challenges—especially regarding functional safety, cybersecurity, and their interplay, as well as the systems’ impact on society. Consequently, new methods and techniques are needed for CPS development and assurance. The articles in this theme issue aim to help address some of these challenges.
Autors: Miklos Biro;Atif Mashkoor;Johannes Sametinger;Remzi Seker;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 24 - 29
Publisher: IEEE
 
» Solving Leibniz's last puzzle [Resources Geek_Life]
Abstract:
Behind an unmarked door in Hanover, Germany, a bearded young man with stylish glasses and a pierced lip is loading 350-year-old pieces of paper onto glass plates for digitization by a souped-up scanner. These pieces of paper are part of an immense puzzle. If solved, it could give insights into one of the greatest minds of all time: Gottfried Wilhelm Leibniz.
Autors: Michael Dumiak;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 21 - 21
Publisher: IEEE
 
» Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow
Abstract:
This paper presents a new algorithm, termed truncated amplitude flow (TAF), to recover an unknown vector from a system of quadratic equations of the form , where ’s are given random measurement vectors. This problem is known to be NP-hard in general. We prove that as soon as the number of equations is on the order of the number of unknowns, TAF recovers the solution exactly (up to a global unimodular constant) with high probability and complexity growing linearly with both the number of unknowns and the number of equations. Our TAF approach adapts the amplitude-based empirical loss function and proceeds in two stages. In the first stage, we introduce an orthogonality-promoting initialization that can be obtained with a few power iterations. Stage two refines the initial estimate by successive updates of scalable truncated generalized gradient iterations, which are able to handle the rather challenging nonconvex and nonsmooth amplitude-based objective function. In particular, when vectors and ’s are real valued, our gradient truncation rule provably eliminates erroneously estimated signs with high probability to markedly improve upon its untruncated version. Numerical tests using synthetic data and real images demonstrate that our initialization returns more accurate and robust estimates relative to spectral initializations. Furthermore, even under the same initialization, the proposed amplitude-based refinement o- tperforms existing Wirtinger flow variants, corroborating the superior performance of TAF over state-of-the-art algorithms.
Autors: Gang Wang;Georgios B. Giannakis;Yonina C. Eldar;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 773 - 794
Publisher: IEEE
 
» Some Haphazard Thoughts [President's Message]
Abstract:
Presents the President’s message for this issue of the publication.
Autors: Nikhil R. Pal;
Appeared in: IEEE Computational Intelligence Magazine
Publication date: Feb 2018, volume: 13, issue:1, pages: 4 - 6
Publisher: IEEE
 
» Some Results of the Fuzzy Relation Inequalities With Addition–Min Composition
Abstract:
In this paper, some results of the fuzzy relation inequalities with addition–min composition are given. First, the uniqueness of minimal solutions of this system is discussed. Then, the relation between this system and the corresponding equations’ system is introduced. The definition of the critical set is presented, and an algorithm of the critical system is obtained. Finally, an algorithm for the fuzzy relation inequalities is presented.
Autors: Shao-Jun Yang;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 239 - 245
Publisher: IEEE
 
» Source Localization by a Binary Sensor Network in the Presence of Imperfection, Noise, and Outliers
Abstract:
In this paper, source localization by a network of primitive binary sensors under various imperfections are studied. Detailed analysis and mathematical modeling of imperfect binary sensors are presented. Imperfections include sensor failures of two types, drifting, uncertainty, and heterogeneity in binary sensor trigger thresholds, presence of noise, and nonradial symmetry of sensing ranges. Theoretical results, including asymptotical convergence, are established, in particular in the presence of substantial outliers due to sensor failure and large noise. Efficient numerical algorithms are proposed and simulated supporting the theoretical analysis.
Autors: Er-Wei Bai;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Feb 2018, volume: 63, issue:2, pages: 347 - 359
Publisher: IEEE
 
» Space-Time Signal Optimization for SWIPT: Linear Versus Nonlinear Energy Harvesting Model
Abstract:
In simultaneous wireless information and power transfer systems, optimization of transmit signals is critical to system performance. Although the optimization problem can be efficiently solved under a linear energy harvesting model, the obtained solution may not work well in practice, since the energy harvester contains nonlinear elements, such as diodes. On the other hand, while a nonlinear model can be used to capture the dynamics of energy harvesting circuits, it introduces additional complexity at the optimization stage. Specifically, under a nonlinear model, traditional convex optimization is not applicable, since the energy harvesting function is fractional. To address this challenge, this letter first derives an optimal solution for static channels by introducing pseudo-inverse of the nonlinear model. Then, an iterative algorithm that converges to a sub-optimal solution is proposed for time varying channels. With the developed methods, the performance-complexity tradeoff between linear and nonlinear models is illustrated.
Autors: Shuai Wang;Minghua Xia;Yik-Chung Wu;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 408 - 411
Publisher: IEEE
 
» Sparse Large-Scale Nonlinear Dynamical Modeling of Human Hippocampus for Memory Prostheses
Abstract:
In order to build hippocampal prostheses for restoring memory functions, we build sparse multi-input, multi-output (MIMO) nonlinear dynamical models of the human hippocampus. Spike trains are recorded from hippocampal CA3 and CA1 regions of epileptic patients performing a variety of memory-dependent delayed match-to-sample (DMS) tasks. Using CA3 and CA1 spike trains as inputs and outputs respectively, sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear dynamics underlying the CA3-CA1 spike train transformations. These models can accurately predict the CA1 spike trains based on the ongoing CA3 spike trains during multiple memory events, e.g., sample presentation, sample response, match presentation and match response, of the DMS task, and thus will serve as the computational basis of human hippocampal memory prostheses.
Autors: Dong Song;Brian S. Robinson;Robert E. Hampson;Vasilis Z. Marmarelis;Sam A. Deadwyler;Theodore W. Berger;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Feb 2018, volume: 26, issue:2, pages: 272 - 280
Publisher: IEEE
 
» Sparse Orthogonal Circulant Transform Multiplexing for Coherent Optical Fiber Communication
Abstract:
This paper introduces a new multicarrier system, named sparse orthogonal circulant transform multiplexing (S-OCTM), for optical fiber communication. This technique uses an inverse sparse orthogonal circulant transform (S-OCT) matrix, which is simple and contains only two nonzero elements in each column, to multiplex information of different subcarriers. We compared the proposed scheme with conventional orthogonal frequency division multiplexing (OFDM), orthogonal chirp division multiplexing (OCDM), and discrete-Fourier-transform spreading OFDM (DFT-S-OFDM) in a coherent optical communication system. It is shown that S-OCTM, while exhibiting the complexity among the least, avoids the performance disadvantages of all investigated conventional schemes. It is theoretically proved that the S-OCT matrix equalizes the bandwidth limitation effect that degrades the performance of conventional OFDM. It also shows a greatly reduced peak-to-average power ratio and higher tolerance to fiber nonlinearity than OFDM and OCDM. On the other hand, compared to DFT-S-OFDM, S-OCTM shows a better dispersion tolerance under insufficient length of cyclic prefix and is more tolerable to strong optical filtering. The performance advantages and low complexity enable the proposed scheme to be a promising multicarrier solution for optical communications.
Autors: Yukui Yu;Wei Wang;Xing Ouyang;Zhenpeng Wang;Jian Zhao;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 14
Publisher: IEEE
 
» Sparsity of Linear Discrete-Time Optimal Control Problems With $l_1$ Objectives
Abstract:
This paper explores optimal control problems with objectives involving linear discrete-time systems. These problems can be efficiently solved as linear programs. They also have previously been shown to yield sparse solutions, including idle or deadbeat solutions where the input or output is respectively zero along the entire control horizon. The main contribution of this paper is to derive conditions on the problem parameters that specify when idle or deadbeat solutions occur. These results, based on analyzing the dual problem, demonstrate how different types of sparse solutions result from the choice of the problem parameters and, as a consequence, may guide the design of controllers employing objectives.
Autors: Christopher V. Rao;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Feb 2018, volume: 63, issue:2, pages: 513 - 517
Publisher: IEEE
 
» Spatial Electro-Thermal Modeling and Simulation of Power Electronic Modules
Abstract:
In this work, the spatial electro-thermal modeling and simulation of power electronic modules is discussed. It is shown how physical and mathematical modeling techniques can be combined to obtain a compact time-efficient electro-thermal simulation framework for power electronic modules. The accuracy of the modeling framework is demonstrated based on experiments. It can be used for the fast calculation of the temperature distribution of a power module in an electric vehicle over driving cycles. The spatial temperature information allows to effectively estimate the lifetime of the power module.
Autors: Christoph H. van der Broeck;Lukas A. Ruppert;Arne Hinz;Marcus Conrad;Rik W. De Doncker;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 404 - 415
Publisher: IEEE
 
» Spatial Modulation-Assisted Scanning White-Light Interferometry for Noise Suppression
Abstract:
A route of spatial modulation-assisted scanning white-light interferometry with the inhibition of background noises and light source fluctuations for the topography measurement of micro-/nano-structure surface was explored in this letter. The spatial modulation frequency was introduced by tilting the sample at a small angle to separate the noise signals and interference signals in the spatial frequency domain. A band-pass filter and a normalization processing were also applied with the purpose of signal-to-noise-ratio improvement and contrast enhancement. The frequency domain analysis was then enrolled in the elimination of ambiguity for the surface recovery with high-presicion. Both the theoretical analysis and the experiment results reveal the validity of spatial modulation-assisted scanning white-light interferometry and its potentials in high-fidelity measurement of smooth surfaces regardless of external disturbances.
Autors: Qinyuan Deng;Junbo Liu;Yan Tang;Yi Zhou;Yong Yang;Jinlong Li;Song Hu;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 379 - 382
Publisher: IEEE
 
» Spatial Position Measurement System for Surgical Navigation Using 3-D Image Marker-Based Tracking Tools With Compact Volume
Abstract:
We develop a spatial position measurement system using three-dimensional (3-D) image marker-based tracking tools targeted at surgical navigation in minimally invasive surgery. We generate 3-D image markers with spatial information encoded to 2-D images, design tracking tools with the 3-D image markers, and analyze the tracking tools’ theoretical spatial errors, which are primarily limited by the spatial distribution of reconstructed fiducial 3-D markers. A pattern analysis-based positional measurement algorithm is developed to calculate the tool's spatial information using its spatial configuration. Evaluation experiments were conducted to demonstrate the accuracy and effectiveness of the proposed system. Furthermore, surgical navigation feasibility studies were performed. With a patient-image registration algorithm, a navigation interface that shows preoperative medical data and intraoperative information about the tool can intuitively and accurately assist surgeons. The results demonstrate that the proposed tracking tools, which have compact volume and spatial positional information, are of potential use in minimally invasive surgery in a limited space.
Autors: Zhencheng Fan;Guowen Chen;Junchen Wang;Hongen Liao;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 378 - 389
Publisher: IEEE
 
» Spatial Reuse for Coexisting LTE and Wi-Fi Systems in Unlicensed Spectrum
Abstract:
In this paper, we leverage multi-antenna transmit beamforming techniques in order to enable spatial reuse for coexisting LTE and Wi-Fi systems in unlicensed spectrum. For the cellular small cell base stations equipped with multiple transmit antennas and operating in the unlicensed spectrum, some spatial degrees of freedom (DoF)s are dedicated to serving small cell user terminals (SUEs) and others are employed to mitigate interference to the co-existing co-channel Wi-Fi users by applying a linear multi-user precoding technique, such as zero-forcing transmit beamforming (ZFBF). Through careful allocation of spatial DoFs, enhanced spatial reuse of unlicensed spectrum resources can be achieved, thereby improving spectrum efficiency on unlicensed bands. However, due to inherent channel state information (CSI) estimation and feedback errors, ZFBF cannot completely alleviate detrimental co-channel interference effects. After analysing the so-called intra radio technology (intra-RAT) interference among SUEs, i.e., the residual interference caused by imperfect CSI used in ZFBF, and the inter-RAT interference experienced by the Wi-Fi users, we derive the throughput of the co-existing LTE and Wi-Fi systems, respectively. Based on the derived throughput, spatial DoF and power can be optimally allocated to balance the throughput between the small cell and Wi-Fi systems in different scenarios. Our theoretical analysis and proposed schemes are further confirmed with exhaustive numerical simulation results.
Autors: Rui Yin;Geoffrey Ye Li;Amine Maaref;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1187 - 1198
Publisher: IEEE
 
» Spatial Stochastic Vehicle Traffic Modeling for VANETs
Abstract:
Connectivity is a fundamental requirement for vehicular ad hoc networks (VANETs) to secure reliable information dissemination. Connectivity is not guaranteed in the case of traffic sparsity and low market penetration of networked vehicles. Therefore, it is essential to examine the connectivity condition before deploying VANETs. The probabilistic distribution of inter-vehicle spacing plays a crucial role in the study of connectivity. It is quite often in previous studies to assume a priori distribution. This paper has studied this issue analytically and proved a general result as follows. A Poisson vehicle flow of volume enters a road stretch over the period [0, , with the speed of each vehicle sampled from a common probability distribution of the density function ; then, in the steady state, the number of vehicles within any road section [] at any time instant is Poisson distributed with the parameter . This theoretical result is also confirmed with extensive simulation studies.
Autors: Jingqiu Guo;Yong Zhang;Xinyao Chen;Saleh Yousefi;Chenyu Guo;Yibing Wang;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 416 - 425
Publisher: IEEE
 
» Spatially Resolved MR-Compatible Doppler Ultrasound: Proof of Concept for Triggering of Diagnostic Quality Cardiovascular MRI for Function and Flow Quantification at 3T
Abstract:
Objective: We demonstrate the use of a magnetic-resonance (MR)-compatible ultrasound (US) imaging probe using spatially resolved Doppler for diagnostic quality cardiovascular MR imaging (MRI) as an initial step toward hybrid US/MR fetal imaging. Methods: A newly developed technology for a dedicated MR-compatible phased array ultrasound-imaging probe acquired pulsed color Doppler carotid images, which were converted in near-real time to a trigger signal for cardiac cine and flow quantification MRI. Ultrasound and MR data acquired simultaneously were interference free. Conventional electrocardiogram (ECG) and the proposed spatially resolved Doppler triggering were compared in 10 healthy volunteers. A synthetic “false-triggered” image was retrospectively processed using metric optimized gating (MOG). Images were scored by expert readers, and sharpness, cardiac function and aortic flow were quantified. Four-dimensional (4-D) flow (two volunteers) showed feasibility of Doppler triggering over a long acquisition time. Results: Imaging modalities were compatible. US probe positioning was stable and comfortable. Image quality scores and quantified sharpness were statistically equal for Doppler- and ECG-triggering (p ). ECG-, Doppler-triggered, and MOG ejection fractions were equivalent (p ), with false-triggered values significantly lower (p < 0.0005). Aortic flow showed no difference between ECG- and Doppler-triggered and MOG (p > 0.05). 4-D flow quantification gave consistent results between ECG and Doppler triggering. Conclusion: We report interference-free pulsed color Doppler ultrasound du- ing MR data acquisition. Cardiovascular MRI of diagnostic quality was successfully obtained with pulsed color Doppler triggering. Significance: The hardware platform could further enable advanced free-breathing cardiac imaging. Doppler ultrasound triggering is applicable where ECG is compromised due to pathology or interference at higher magnetic fields, and where direct ECG is impossible, i.e., fetal imaging.
Autors: Lindsey Alexandra Crowe;Gibran Manasseh;Aneta Chmielewski;Anne-Lise Hachulla;Daniel Speicher;Andreas Greiser;Hajo Müller;Thomas de Perrot;Jean-Paul Vallée;Rares Salomir;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 294 - 306
Publisher: IEEE
 
» Spatio-Temporal Linkage over Location-Enhanced Services
Abstract:
We are witnessing an enormous growth in the volume of data generated by various online services. An important portion of this data contains geographic references, since many of these services are location-enhanced and thus produce spatio-temporal records of their usage. We postulate that the spatio-temporal usage records belonging to the same real-world entity can be matched across records from different location-enhanced services. Linking spatio-temporal records enables data analysts and service providers to obtain information that they cannot derive by analyzing only one set of usage records. In this paper, we develop a new linkage model that can be used to match entities from two sets of spatio-temporal usage records belonging to two different location-enhanced services. This linkage model is based on the concept of - diversity —that we developed to capture both spatial and temporal aspects of the linkage. To realize this linkage model in practice, we develop a scalable linking algorithm called ST-Link, which makes use of effective spatial and temporal filtering mechanisms that significantly reduce the search space for matching users. Furthermore, ST-Link utilizes sequential scan procedures to avoid random disk access and thus scales to large datasets. We evaluated our work with respect to accuracy and performance using several datasets. Experiments show that ST-Link is effective in practice for performing spatio-temporal linkage and can scale to large datasets.
Autors: Fuat Basık;Buğra Gedik;Çağrı Etemoğlu;Hakan Ferhatosmanoğlu;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Feb 2018, volume: 17, issue:2, pages: 447 - 460
Publisher: IEEE
 
» Species Tree Inference from Gene Splits by Unrooted STAR Methods
Abstract:
The method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a four-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here, we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects to a generalization of the STAR method of Liu, Pearl, and Edwards, and a previous theoretical analysis of it. We further show utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency.
Autors: Elizabeth S. Allman;James H. Degnan;John A. Rhodes;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Feb 2018, volume: 15, issue:1, pages: 337 - 342
Publisher: IEEE
 
» Spectral Clustering of Straight-Line Segments for Roof Plane Extraction From Airborne LiDAR Point Clouds
Abstract:
This letter presents a novel approach to automated extraction of roof planes from airborne light detection and ranging data based on spectral clustering of straight-line segments. The straight-line segments are derived from laser scan lines, and 3-D line geometry analysis is employed to identify coplanar line segments so as to avoid skew lines in plane estimation. Spectral analysis reveals the spectrum of the adjacency matrix formed by the straight-line segments. Spectral clustering is then performed in feature space where the clusters are more prominent, resulting in a more robust extraction of roof planes. The proposed approach has been tested on ISPRS benchmark data sets, with the results showing high quality in terms of completeness, correctness, and geometrical accuracy, thus confirming that the proposed approach can extract roof planes both accurately and efficiently.
Autors: Chunsun Zhang;Yuxiang He;Clive S. Fraser;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 267 - 271
Publisher: IEEE
 
» Spectral Conditions for Stability and Stabilization of Positive Equilibria for a Class of Nonlinear Cooperative Systems
Abstract:
Nonlinear cooperative systems associated to vector fields that are concave or subhomogeneous describe well interconnected dynamics that are of key interest for communication, biological, economical, and neural network applications. For this class of positive systems, we provide conditions that guarantee existence, uniqueness and stability of strictly positive equilibria. These conditions can be formulated directly in terms of the spectral radius of the Jacobian of the system. If control inputs are available, then it is shown how to use state feedback to stabilize an equilibrium point in the interior of the positive orthant.
Autors: Precious Ugo Abara;Francesco Ticozzi;Claudio Altafini;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Feb 2018, volume: 63, issue:2, pages: 402 - 417
Publisher: IEEE
 
» Spectral Unmixing With Multiple Dictionaries
Abstract:
Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral image (HSI) or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels. Many fully automated methods have been proposed in recent years, but little work has been done to allow users to select areas where pure pixels are present manually or using a segmentation algorithm. Additionally, in a nonblind approach, several spectral libraries may be available rather than a single one, with a fixed number (or an upper or lower bound) of endmembers to chose from each. In this letter, we propose a multiple-dictionary constrained low-rank matrix approximation model that addresses these two problems. We propose an algorithm to compute this model, dubbed multiple matching pursuit alternating least squares, and its performance is discussed on both synthetic and real HSIs.
Autors: Jérémy E. Cohen;Nicolas Gillis;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 187 - 191
Publisher: IEEE
 
» Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework
Abstract:
In this paper, we designed an end-to-end spectral–spatial residual network (SSRN) that takes raw 3-D cubes as input data without feature engineering for hyperspectral image classification. In this network, the spectral and spatial residual blocks consecutively learn discriminative features from abundant spectral signatures and spatial contexts in hyperspectral imagery (HSI). The proposed SSRN is a supervised deep learning framework that alleviates the declining-accuracy phenomenon of other deep learning models. Specifically, the residual blocks connect every other 3-D convolutional layer through identity mapping, which facilitates the backpropagation of gradients. Furthermore, we impose batch normalization on every convolutional layer to regularize the learning process and improve the classification performance of trained models. Quantitative and qualitative results demonstrate that the SSRN achieved the state-of-the-art HSI classification accuracy in agricultural, rural–urban, and urban data sets: Indian Pines, Kennedy Space Center, and University of Pavia.
Autors: Zilong Zhong;Jonathan Li;Zhiming Luo;Michael Chapman;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 847 - 858
Publisher: IEEE
 
» Spectrum Allocation for Noncooperative Radar Coexistence
Abstract:
Access to the electromagnetic spectrum is an ever-growing challenge for radar. Future radar will be required to mitigate RF interference from other RF sources, relocate to new frequency bands while maintaining quality of service, and share frequency bands with other RF systems. The spectrum sensing, multioptimization (SS-MO) technique was recently investigated as a possible solution to these challenges. Prior results have indicated significant improvement in the signal-to-interference plus noise ratio at the cost of a high computational complexity. However, the optimization computational cost must be manageable in real time to address the dynamically changing spectral environment. In this paper, a bioinspired filtering technique is investigated to reduce the computational complexity of SS-MO. The proposed technique is analogous to the processing of the thalamus in the human brain in that the number of samples input to SS-MO is significantly decreased, thus, resulting in a reduction in computational complexity. The performance and computational complexity of SS-MO and the proposed technique are investigated. Both techniques are used to process a variety of measured spectral data. The results indicate a significant decrease in computational complexity for the proposed approach while maintaining performance of the SS-MO technique.
Autors: Anthony F. Martone;Kenneth I. Ranney;Kelly Sherbondy;Kyle A. Gallagher;Shannon D. Blunt;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 90 - 105
Publisher: IEEE
 
» Split-and-Merge-Based Block Partitioning for High Efficiency Image Coding
Abstract:
Quadtree-based partitioning (i.e., recursively dividing a picture into square blocks) is one of the most popular partitioning-based image coding schemes because of its computational simplicity and efficient representation of partitioning. However, the rate-distortion performance of quadtree-based partitioning reaches a limit because the dependence between child blocks of different parents is not exploited. In this paper, a new bottom-up-based block partitioning method called split-and-merge is proposed. This method splits an image into multiple square blocks and merges them into nonsquare blocks to exploit the dependence between split blocks. Moreover, a modification of the conventional intra prediction and transform is employed for nonsquare blocks. The experimental results indicate that the proposed method results in an average and maximum bit rate reduction of 3.1% and 8.3%, respectively, relative to High Efficiency Video Coding intra coding.
Autors: Byeong-Doo Choi;Sung-Jea Ko;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Feb 2018, volume: 28, issue:2, pages: 540 - 549
Publisher: IEEE
 
» SRE: Semantic Rules Engine for the Industrial Internet-Of-Things Gateways
Abstract:
The advent of the Internet-of-Things (IoT) paradigm has brought opportunities to solve many real-world problems. Energy management, for example, has attracted huge interest from academia, industries, governments, and regulatory bodies. It involves collecting energy usage data, analyzing it, and optimizing the energy consumption by applying control strategies. However, in industrial environments, performing such optimization is not trivial. The changes in business rules, process control, and customer requirements make it much more challenging. In this paper, a semantic rules engine (SRE) for industrial gateways is presented that allows implementing dynamic and flexible rule-based control strategies. It is simple, expressive, and allows managing rules on-the-fly without causing any service interruption. Additionally, it can handle semantic queries and provide results by inferring additional knowledge from previously defined concepts in ontologies. SRE has been validated and tested on different hardware platforms and in commercial products. Performance evaluations are also presented to validate its conformance to the customer requirements.
Autors: Charbel El Kaed;Imran Khan;Andre Van Den Berg;Hicham Hossayni;Christophe Saint-Marcel;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 715 - 724
Publisher: IEEE
 
» SSDNet: Small-World Super-Dense Device-to-Device Wireless Networks
Abstract:
In this article, we propose a novel networking paradigm called Small-world SSDNet, servicing applications such as public safety, proximity based services, and fog computing based on device-todevice multi-hop wireless communications. The "small-world" feature is determined by the service area, whose size is usually within a community level, and the well known small-world properties existing in SSDNets; the "super-dense" feature comes from the fact that the increased direct communication range and the popularity of 5G and IoT devices jointly result in a large number of devices within a single-hop communication range. This article first formally defines SSDNet. Then the challenges and the opportunities brought by the design and the implementation of the SSDNet protocols and applications are addressed. Finally, the broader discussions on issues relevant to modeling, engineering, and dissemination are provided.
Autors: Wei Cheng;Jiguo Yu;Feng Zhao;Xiuzhen Cheng;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 186 - 192
Publisher: IEEE
 
» Stability Analysis of LCL-Type Grid-Connected Inverter Under Single-Loop Inverter-Side Current Control With Capacitor Voltage Feedforward
Abstract:
When single-loop inverter-side current control is used in the LCL-type inverters, there may be more than one stable region with regard to computation delay in control path. The system is stable if computation delay is small enough, but it, named as the first stable region, may be too narrow to finish the control codes in high-frequency system. On the other hand, the second stable region is highly sensitive to the grid impedance variation and is hardly applicable in weak grids. To deal with the situation, this paper investigates the influence of the capacitor voltage feedforward on the system stability considering flexible computation delay in feedforward path. It is found that the capacitor voltage feedforward is able to suppress the resonance of the LCL filter. However, a new resonance may arise if computation delay is not carefully handled. The influence of computation delay in both forward path and feedforward path on system stability is systematically analyzed. The analytical results show that after applying feedforward control with optimized delay, the system stability is greatly improved and is not sensitive to the grid impedance variation. The simulation and experiment results verify the analytical results.
Autors: Bangyin Liu;Qikang Wei;Changyue Zou;Shanxu Duan;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 691 - 702
Publisher: IEEE
 
» Stability Improvement of a Multimachine Power System Connected With a Large-Scale Hybrid Wind-Photovoltaic Farm Using a Supercapacitor
Abstract:
This paper presents the stability improvement of a multimachine power system connected with a large-scale hybrid wind-photovoltaic (PV) farm using an energy-storage unit based on supercapacitor (SC). The operating characteristics of the hybrid wind-PV farm are simulated by an equivalent aggregated 300-MW wind-turbine generator (WTG) based on permanent-magnet synchronous generator and an equivalent aggregated 75-MW PV array. The WTG and the PV array are connected to a common dc link through a voltage-source converter and a dc/dc boost converter, respectively. The power of the common dc link is transferred to the multimachine power system through a voltage-source inverter, step-up transformers, and a connection line. The SC-based energy-storage unit, which is integrated into the common dc link through a bidirectional dc/dc converter, is employed for smoothing out the power fluctuations due to variations of wind speed and/or solar irradiance. A proportional-integral-derivative (PID)-supplementary damping controller (PID-SDC) is designed for the bidirectional dc/dc converter of the SC to enhance the damping characteristics of the low-frequency oscillations associated with the studied multimachine power system. The root loci of the studied system are examined under wide ranges of wind speed and solar irradiance. The effectiveness of the proposed SC joined with the PID-SDC on improving the performance of the studied system under different disturbance conditions is also demonstrated using time-domain simulations.
Autors: Li Wang;Quang-Son Vo;Anton Victorovich Prokhorov;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 50 - 60
Publisher: IEEE
 
» Stable Adaptive Method to Solve FEM Coupled With Jiles–Atherton Hysteresis Model
Abstract:
The Jiles–Atherton magnetic hysteresis model coupled with time-stepping finite-element analysis is reported to suffer from numerical convergence problems, for example, when simulating electrical machines. In this paper, we describe a source of the numerical difficulties, and present a more stable time integration scheme for the coupled problem. In addition, we introduce the quasi-Newton method to accelerate the solution of the nonlinear field equation. Induction motor simulations verify the robustness of the proposed method.
Autors: Lauri Perkkiö;Brijesh Upadhaya;Antti Hannukainen;Paavo Rasilo;
Appeared in: IEEE Transactions on Magnetics
Publication date: Feb 2018, volume: 54, issue:2, pages: 1 - 8
Publisher: IEEE
 
» Staggered CAP—A New Spectrally Efficient Modulation Format for Optical Communications
Abstract:
In this letter, staggered carrierless amplitude phase (sCAP), a new spectrally efficient modulation format, is proposed for optical transmission. By staggering the in-phase and quadrature components of the CAP modulation, simultaneous transmission of two additional pulse amplitude modulation signals is possible: the first one being baseband and the second one lower sideband. The new modulation format has several advantages: 100% bandwidth efficiency, rectangular-shaped spectrum, minimum tap number shaping filters, minimum requirements for analog-to-digital conversion sampling rate, low peak-to-average power ratio, and capability of bit and power loading. The experimental results in vertical cavity surface emitting laser multimode fiber link indicate that the new format by far outperforms regular CAP.
Autors: Grzegorz Stepniak;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 367 - 370
Publisher: IEEE
 
» Staircase Codes for Secret Sharing With Optimal Communication and Read Overheads
Abstract:
We study the communication efficient secret sharing (CESS) problem. A classical threshold secret sharing scheme encodes a secret into shares given to parties, such that any set of at least , , parties can reconstruct the secret, and any set of at most , , colluding parties cannot obtain any information about the secret. A CESS scheme satisfies the previous properties of threshold secret sharing. Moreover, it allows to reconstruct the secret from any set of , parties by reading and communicating the minimum amount of information. In this paper, we introduce three explicit constructions of CESS codes called Staircase codes. The first construction achieves optimal communication and read costs for a given . The second construction achieves optimal costs universally for all possible values of between and . The third construction, which is the most general, achieves optimal costs universally for all values of in any given set . The introduced Staircase codes can store a secret of maximal size, i.e., equal to shares, and they are all designed over a small finite field , for any prime power . However, Staircase codes may require dividing the secret and the shares into many symbols. We also describe how Staircase codes can be used to construct threshold changeable secret sharing with minimum storage cost, i.e., minimum share size.
Autors: Rawad Bitar;Salim El Rouayheb;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 933 - 943
Publisher: IEEE
 

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