Electrical and Electronics Engineering publications abstract of: 10-2017 sorted by title, page: 6

» Complete Electrical Arc Hazard Classification System and Its Application
Abstract:
The standard for electrical safety in the workplace, National Fire Protection Association 70E, and relevant Occupational Safety and Health Act electrical safety standards evolved in the U.S. over the past 40 years to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. This leaves a substantial gap in the management of other types of electrical hazards including battery banks, dc power systems, capacitor banks, and solar power systems. Although many of these systems are fed by 50/60-Hz energy, we find substantial use of electrical energy, and the use of capacitors, inductors, batteries, solar, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz ac power. At the IEEE Electrical Safety Workshop in 2009, we presented a comprehensive approach to classifying the electrical shock hazards of all types of electricity, including various waveforms and various types of sources of electrical energy. That paper introduced a new comprehensive electrical shock hazard classification system that used a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards with a focus on the shock hazard. That paper was based on research conducted over the past 100 years and on decades of experience. This paper continues the effort in understanding and managing all forms of injury from all forms of electricity with the introduction of a comprehensive approach to classifying all forms of injury from the electrical arc, including thermal, blast pressure, hearing, radiation, and shrapnel injury. The general term “arc” is divided into the arc, arc flash, and arc blast as a first subdivision of type of source of injury. Then, the parameters of voltage, short-circuit current, energy, waveform, gap distance, gap geom- try, enclosure geometry, and time are used to choose various approaches to analysis. Recent efforts to understand, model, and estimate injury for these types of systems are reviewed. Most of the focus to understand and predict injury for dc, capacitor, solar, and RF arc hazards has been only in the past 10 years. A comprehensive approach to analyzing all forms of injury from all forms of electrical arcs is presented.
Autors: Lloyd B. Gordon;Kyle D. Carr;Nicole Graham;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 5078 - 5087
Publisher: IEEE
 
» Completion Time Analysis of Wafer Lots in Single-Armed Cluster Tools With Parallel Processing Modules
Abstract:
We analyze the completion time of wafer lots in single-armed cluster tools with parallel processing modules (PMs) by considering the lot switching operation. To effectively assign wafer lots and dispatch overhead hoist transports (OHTs) to manufacturing tools, it is crucial to obtain the completion time of wafer lots. However, estimating the completion time is not straightforward, due to the concurrent processing of two consecutive wafer lots during lot switching operation, which often increases wafer sojourn times in PMs. In this paper, we derive closed-form expressions of the completion time of wafer lots in single-armed cluster tools with parallel PMs. We assume that the robot unloads wafers in the order of their loading sequence. We then experimentally show that the formulas derived can be used even when processing time variation exists or another robot task sequence, which is of first-in first-out (FIFO), is assumed.

Note to Practitioners—Due to the larger wafer size and circuit width reduction, cluster tools often perform the lot switching operation with each pair of consecutive wafer lots. In addition, since most tools are operated with parallel chambers, concurrent processing with two different wafer lots occurs frequently. Such transient periods in operating tools make it hard to estimate the completion time of wafer lots. In this paper, we derive closed-form expressions to obtain the completion time of wafer lots in single-armed cluster tools with parallel chambers. We further show that the formulas can be used with processing time variation or the FIFO rule. With the formulas, OHTs can be sent just-in-time to tools to load or unload wafer cassettes, and wafer lots can be assigned while minimizing the transient periods. In addition, the estimated completion time can be utilized in the planning and scheduling of wafer fabrication processes.

Autors: Jun-Ho Lee;Hyun-Jung Kim;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Oct 2017, volume: 14, issue:4, pages: 1622 - 1633
Publisher: IEEE
 
» Complexity Reduction by Modified Scale-Space Construction in SIFT Generation Optimized for a Mobile GPU
Abstract:
Scale-invariant feature transform (SIFT) is one of the most widely used local features for computer vision in mobile devices. A mobile graphic processing unit (GPU) is often used to run computer-vision applications using SIFT features, but the performance in such a case is not powerful enough to generate SIFT features in real time. This paper proposes an efficient scheme to optimize the SIFT algorithm for a mobile GPU. It analyzes the conventional scale-space construction step in the SIFT generation, finding that reducing the size of the Gaussian filter and the scale-space image leads to a significant speedup with only a slight degradation of the quality of the features. Based on this observation, the SIFT algorithm is modified and implemented for real-time execution. Additional optimization techniques are employed for a further speedup by efficiently utilizing both the CPU and the GPU in a mobile processor. The proposed SIFT generation scheme achieves a processing speed of 28.30 frames/s for an image with a resolution of running on a Galaxy S5 LTE-A device, thereby gaining a speedup by the factors of 114.78 and 4.53 over CPU- and GPU-only implementations, respectively.
Autors: Chulhee Lee;Chae Eun Rhee;Hyuk-Jae Lee;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Oct 2017, volume: 27, issue:10, pages: 2246 - 2259
Publisher: IEEE
 
» Complexity Reduction for the Optimization of Linear Precoders Over Random MIMO Channels
Abstract:
Precoder optimization with full channel state information for finite alphabet signals over multiple-input multiple-output random channels is investigated in this paper. The precoder is represented by a product of power allocation matrix and constellation-forming matrix. There was an optimal algorithm introduced in the literature to globally maximize the channel mutual information by iteratively optimizing these two matrices. However, the computational complexity of the optimal algorithm is painfully high, especially when it is used with the high-order modulation and the high-data stream number. In this paper, we propose a novel sub-optimal low-complexity precoding algorithm and compare it with the optimal one. The new algorithm proceeds in two steps. First, the constellation-forming matrix is fixed in order to maximize the minimum Euclidean distance between the received symbols, which ensures high channel mutual information. Then, given the constellation-forming matrix, an iterative algorithm searches for the power allocation matrix that maximizes the channel mutual information. Since optimizing only one matrix instead of two, the new algorithm not only achieves a lower computational complexity but also avoids the use of initial values, which must be carefully selected for each channel and signal-to-noise ratio for fast convergence. Another advantage of the new algorithm is that the resulting precoder has a fixed form of received constellation thanks to the fixed constellation-forming matrix. This allows us to optimize the symbol mapping on the received constellation. Simulation results show that the proposed low-complexity precoder achieves error-rate performance that is close to performance of the optimal one when the conventional mapping is used. In addition, the new precoder used with optimized mapping at received constellation shows significant error-rate performance improvement.
Autors: Nhat-Quang Nhan;Philippe Rostaing;Karine Amis;Ludovic Collin;Emanuel Radoi;
Appeared in: IEEE Transactions on Communications
Publication date: Oct 2017, volume: 65, issue:10, pages: 4205 - 4217
Publisher: IEEE
 
» Composability Verification of Multi-Service Workflows in a Policy-Driven Cloud Computing Environment
Abstract:
The emergence of cloud computing infrastructure and Semantic Web technologies has created unprecedented opportunities for composing large-scale business processes and workflow-based applications that span multiple organizational domains. A key challenge related to composition of such multi-organizational business processes and workflows is posed by the security and access control policies of the underlying organizational domains. In this paper, we propose a framework for verifying secure composability of distributed workflows in an autonomous multi-domain environment. The objective of workflow composability verification is to ensure that all the users or processes executing the designated workflow tasks conform to the time-dependent security policy specifications of all collaborating domains. A key aspect of such verification is to determine the time-dependent schedulability of distributed workflows, assumed to be invoked on a recurrent basis. We use a two-step approach for verifying secure workflow composability. In the first step, a distributed workflow is decomposed into domain-specific projected workflows and is verified for conformance with the respective domain's security and access control policy. In the second step, the cross-domain dependencies amongst the workflow tasks performed by different collaborating domains are verified.
Autors: Basit Shafiq;Sameera Ghayyur;Ammar Masood;Zahid Pervaiz;Abdulrahman Almutairi;Farrukh Khan;Arif Ghafoor;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Oct 2017, volume: 14, issue:5, pages: 478 - 493
Publisher: IEEE
 
» Compression-Based Compressed Sensing
Abstract:
Modern compression codes exploit signals’ complex structures to encode them very efficiently. On the other hand, compressed sensing algorithms recover “structured” signals from their under-determined set of linear measurements. Currently, there is a noticeable gap between the types of structures used in the area of compressed sensing and those employed by state-of-the-art compression codes. Recent results in the literature on deterministic signals aim at bridging this gap through devising compressed sensing decoders that employ compression codes. This paper focuses on structured stochastic processes and studies application of lossy compression codes to compressed sensing of such signals. The performance of the formerly proposed compressible signal pursuit (CSP) optimization is studied in this stochastic setting. It is proved that in the low-distortion regime, as the blocklength grows to infinity, the CSP optimization reliably and robustly recovers instances of a stationary process from its random linear measurements as long as is slightly more than times the rate-distortion dimension (RDD) of the source. It is also shown that under some regularity conditions, the RDD of a stationary process is equal to its information dimension. This connection establishes the optimality of CSP at least for memoryless stationary sources, which have known fundamental limits. Finally, it is shown that CSP combined by a family of universal variable-length fixed-distortion compression codes yields a family of universal compressed sensing recovery algorithms.
Autors: Farideh E. Rezagah;Shirin Jalali;Elza Erkip;H. Vincent Poor;
Appeared in: IEEE Transactions on Information Theory
Publication date: Oct 2017, volume: 63, issue:10, pages: 6735 - 6752
Publisher: IEEE
 
» Compressive Sensing as Applied to Inverse Problems for Imaging: Theory, Applications, Current Trends, and Open Challenges.
Abstract:
Compressive sensing (CS) is currently one the most active research fields in information engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound theory behind such a paradigm have motivated a great interest in developing and applying CS to many domains, including inverse scattering. Unfortunately, electromagnetic imaging problems have some unique theoretical features that prevent a straightforward exploitation of CS tools. Therefore, suitable CS-based strategies must be considered in such a framework.
Autors: Giacomo Oliveri;Marco Salucci;Nicola Anselmi;Andrea Massa;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Oct 2017, volume: 59, issue:5, pages: 34 - 46
Publisher: IEEE
 
» Compressive Sensing Techniques for mm-Wave Nondestructive Testing of Composite Panels
Abstract:
This paper presents imaging results from measurements of an industrially manufactured composite test panel, utilizing two introduced algorithms for data postprocessing. The system employs a planar near-field scanning setup for characterizing defects in composite panels in the 50–67-GHz band, and can be considered as a complementary diagnostic tool for nondestructive testing purposes. The introduced algorithms are based on the reconstruction of the illuminating source at the transmitter, enabling a separation of the sampled signal with respect to the location of its potential sources, the scatterers within the device under test or the transmitter. For the second algorithm, an -minimization problem formulation is introduced that enables compressive sensing techniques to be adapted for image retrieval. The algorithms are benchmarked against a more conventional imaging technique, based on the Fourier transform, and it is seen that the complete imaging system provides increased dynamic range, improved resolution, and reduced measurement time by removal of a reference measurement. Moreover, the system provides stable image quality over a range of frequencies.
Autors: Jakob Helander;Andreas Ericsson;Mats Gustafsson;Torleif Martin;Daniel Sjöberg;Christer Larsson;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Oct 2017, volume: 65, issue:10, pages: 5523 - 5531
Publisher: IEEE
 
» Computable Delay Margins for Adaptive Systems With State Variables Accessible
Abstract:
Robust adaptive control of plants whose state variables are accessible in the presence of an input time delay is established in this paper. It is shown that a standard model reference adaptive controller modified with projection ensures global boundedness of the overall adaptive system for a range of nonzero delays. The upper bound of such delays, that is, the delay margin, is explicitly defined and can be computed a priori.
Autors: Heather S. Hussain;Yildiray Yildiz;Megumi Matsutani;Anuradha M. Annaswamy;Eugene Lavretsky;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5039 - 5054
Publisher: IEEE
 
» Concealment of Chaos Time-Delay Signature Through Phase-Conjugate Feedback and Chaos Optical Injection
Abstract:
In this paper, we numerically demonstrate that the concealment of time-delay signature (TDS) can be readily achieved via the combined mechanism of phase-conjugate feedback (PCF) and chaotic optical injection. To show the potential advantages of the proposed scheme, its counterpart, i.e., a slave semiconductor laser (SSL) subjected to chaotic optical injection from a master semiconductor laser (MSL) with conventional optical feedback (COF) is studied in parallel. In particular, we consider a fair situation where the MSL in both PCF and COF shows a comparable peak value in the autocorrelation function computed from the intensity time series. Our simulations uncover that combining the mechanism of PCF and chaotic optical injection is beneficial for TDS concealment in the SSL. To better understand this, the effects of some control parameters including injection and feedback are comparably studied. The results further prove that, as the injection or feedback parameters are varied, the proposed PCF-system always exhibits weaker autocorrelation around the feedback delay value when compared to the COF-system. In the meantime, the former system allows for larger bandwidth and, thus, paves way for important applications to secure communication and random-number generation.
Autors: Penghua Mu;Wei Pan;Lianshan Yan;Bin Luo;Xihua Zou;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 8
Publisher: IEEE
 
» Concise Planning and Filtering: Hardness and Algorithms
Abstract:
Motivated by circumstances with severe computational resource limits (e.g., settings with strong constraints on memory or communication), this paper addresses the problem of concisely representing and processing information for estimation and planning tasks. In this paper, conciseness is a measure of explicit representational complexity: for filtering, we are concerned with maintaining as little state as possible to perform a given task; for the planning case, we wish to generate the plan graph (or policy graph) with the fewest vertices that is correct and also complete. We present hardness results showing that both filtering and planning are NP-hard to perform in an optimally concise way, and that the related decision problems are NP-complete. We also describe algorithms for filter reduction and concise planning, for which these hardness results justify the potentially suboptimal output. The filter-reduction algorithm accepts as input an arbitrary combinatorial filter, expressed as a transition graph, and outputs an equivalent filter that uses fewer I-states to complete the same filtering task. The planning algorithm, using the filter-reduction algorithm as a subroutine, generates concise plans for planning problems that may involve both nondeterminism and partial observability. Both algorithms are governed by parameters that encode tradeoffs between computational efficiency and solution quality. We describe implementation of both algorithms and present a series of experiments evaluating their effectiveness.
Autors: Jason M. O’Kane;Dylan A. Shell;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Oct 2017, volume: 14, issue:4, pages: 1666 - 1681
Publisher: IEEE
 
» Concurrent Control of Mobility and Communication in Multirobot Systems
Abstract:
We develop a hybrid system architecture that enables a team of mobile robots to complete a task in a complex environment by self-organizing into a multihop ad hoc network and solving the concurrent communication and mobility problem. The proposed system consists of a two-layer feedback loop. An outer loop performs infrequent global coordination and a local inner loop determines motion and communication variables. This system provides the lightweight coordination and responsiveness of decentralized systems while avoiding local minima. This allows a team to complete a task in complex environments while maintaining desired end-to-end data rates. The behavior of the system is evaluated in experiments that demonstrate: 1) successful task completion in complex environments; 2) achievement of equal or greater end-to-end data rates as compared to a centralized system; and 3) robustness to unexpected events such as motion restriction.
Autors: James Stephan;Jonathan Fink;Vijay Kumar;Alejandro Ribeiro;
Appeared in: IEEE Transactions on Robotics
Publication date: Oct 2017, volume: 33, issue:5, pages: 1248 - 1254
Publisher: IEEE
 
» Condition and Strategy Analysis for Assembly Based on Attractive Region in Environment
Abstract:
Automatic assembly with high precision is an essential step in robotic manipulation. It is still a difficult problem due to various complicated requirements, such as less contact force, irregular shapes of the parts, sensing information understanding in complex environment, etc. In the previous work, the concept of attractive region in environment (ARIE) was proposed, which helps to achieve high-precision manipulation with low-precision systems by using the constraints formed by the environment. In this paper, the general relation between the physical space and the configuration space for the robotic assembly system will be analyzed, the strategies of using ARIE to achieve high-precision peg-hole assembly will be provided, and furthermore, practical examples for industrial applications will be given, which further illustrates the usefulness of the concept.
Autors: Rui Li;Hong Qiao;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Oct 2017, volume: 22, issue:5, pages: 2218 - 2228
Publisher: IEEE
 
» Conditions for Almost Global Attractivity of a Synchronous Generator Connected to an Infinite Bus
Abstract:
Conditions for existence and global attractivity of the equilibria of a realistic model of a synchronous generator with constant field current connected to an infinite bus are derived. First, necessary and sufficient conditions for existence and uniqueness of equilibrium points are provided. Then, sufficient conditions for local asymptotic stability and almost global attractivity of one of these equilibria are given. The analysis is carried out by employing a new Lyapunov-like function to establish convergence of bounded trajectories, while the latter is proven using the powerful theoretical framework of cell structures pioneered by Leonov and Noldus. The efficiency of the derived sufficient conditions is illustrated via extensive numerical experiments based on two benchmark examples taken from the literature.
Autors: Nikita Barabanov;Johannes Schiffer;Romeo Ortega;Denis Efimov;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 4905 - 4916
Publisher: IEEE
 
» Conductor Surface Conditions Effects on the Ion-Flow Field of Long-Term Operating Conductors of the HVDC Transmission Line
Abstract:
The influence of conductor surface conditions of new and aged conductors on ground-level resultant electric field and ion current density is analyzed in this paper. The surface roughness and morphology of conductors are measured and analyzed by 3-D phase shift Micro-Xam (MicroXAM-3D) and scanning electron microscopy. Calculations are made using the upstream finite-element-finite difference method for the corona cage model to obtain the influence of surface conditions on the ion-flow field, consequently, changing the resulting electric field and ion current density. An indoor corona cage platform is build up to check the impact of surface conditions on the ground-level resultant electric field and ion current density in the laboratory. Considering the aging characteristics of the conductor surface, a typical ±800 kV ultra-high voltage direct current transmission line is analyzed. The calculated results show that compared with the new conductor, the electric field and ion current density of the long-term operation conductors increase very significantly.
Autors: Yong Yi;Chuyan Zhang;Liming Wang;Zhengying Chen;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Oct 2017, volume: 32, issue:5, pages: 2171 - 2178
Publisher: IEEE
 
» Conformational Space Sampling Method Using Multi-Subpopulation Differential Evolution for De novo Protein Structure Prediction
Abstract:
Protein structure prediction can be considered as a multimodal optimization problem for sampling the protein conformational space associated with an extremely complex energy landscape. To address this problem, a conformational space sampling method using multi-subpopulation differential evolution, MDE, is proposed. MDE first devotes to generate given numbers of concerned modal under the ultrafast shape recognition-based modal identification protocol, which regards each individual as one modal at beginning. Then, differential evolution is used for keeping the preserved modal survival in the evolution process. Meanwhile, a local descent direction used to sample along with is constructed based on the abstract convex underestimate technique for modal enhancement, which could enhance the ability of sampling in the region with lower energy. Through the sampling process of evolution, several certain clusters contain a series of conformations in proportion to the energy score will be obtained. Representative conformations in the generated clusters can be directly picked out as decoy conformations for further refinement with no extra clustering operation needs. A total of 20 target proteins are tested, in which ten target proteins are tested for comparison with Rosetta and three evolutionary algorithms, and ten easy/hard target proteins in CASP 11 are tested for further verifying the effectiveness of MDE. Test results show strong sampling ability that MDE holds, and near-native conformations can be effectively obtained.
Autors: Xiao-Hu Hao;Gui-Jun Zhang;Xiao-Gen Zhou;
Appeared in: IEEE Transactions on NanoBioscience
Publication date: Oct 2017, volume: 16, issue:7, pages: 618 - 633
Publisher: IEEE
 
» Congestion Control for Background Data Transfers With Minimal Delay Impact
Abstract:
Congestion control protocols for background data are commonly conceived and designed to emulate low priority traffic, which yields to transmission control protocol (TCP) flows. In the presence of even a few very long TCP flows, this behavior can cause bandwidth starvation, and hence, the accumulation of large numbers of background data flows for prolonged periods of time, which may ultimately have an adverse effect on the download delays of delay-sensitive TCP flows. In this paper, we look at the fundamental problem of designing congestion control protocols for background traffic with the minimum impact on short TCP flows while achieving a certain desired average throughput over time. The corresponding optimal policy under various assumptions on the available information is obtained analytically. We give tight bounds of the distance between TCP-based background transfer protocols and the optimal policy, and identify the range of system parameters for which more sophisticated congestion control makes a noticeable difference. Based on these results, we propose an access control algorithm for systems where control on aggregates of background flows can be exercised, as in file servers. Simulations of simple network topologies suggest that this type of access control performs better than protocols emulating low priority over a wide range of parameters.
Autors: Costas A. Courcoubetis;Antonis Dimakis;Michalis Kanakakis;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Oct 2017, volume: 25, issue:5, pages: 2743 - 2758
Publisher: IEEE
 
» Congestion Control for Web Real-Time Communication
Abstract:
Applications requiring real-time communication (RTC) between Internet peers are ever increasing. RTC requires not only congestion control but also minimization of queuing delays to provide interactivity. It is known that the well-established transmission control protocol congestion control is not suitable for RTC due to its retransmissions and in-order delivery mechanisms, which induce significant latency. In this paper, we propose a novel congestion control algorithm for RTC, which is based on the main idea of estimating—using a Kalman Filter—the end-to-end one-way delay variation which is experienced by packets traveling from a sender to a destination. This estimate is compared with a dynamic threshold and drives the dynamics of a controller located at the receiver, which aims at maintaining queuing delays low, while a loss-based controller located at the sender acts when losses are detected. The proposed congestion control algorithm has been adopted by Google Chrome. Extensive experimental evaluations have shown that the algorithm contains queuing delays while providing intra and inter protocol fairness along with full link utilization.
Autors: Gaetano Carlucci;Luca De Cicco;Stefan Holmer;Saverio Mascolo;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Oct 2017, volume: 25, issue:5, pages: 2629 - 2642
Publisher: IEEE
 
» Consensus With Output Saturations
Abstract:
This paper considers a standard consensus algorithm under output saturations. In this case, the global consensus cannot be realized due to the existence of stable equilibrium points that do not belong to the consensus manifold. Therefore, this paper investigates necessary and sufficient initial conditions for the achievement of consensus that characterize an exact domain of attraction. Specifically, this paper considers single-integrator agents with both fixed and time-varying undirected graphs. Then, we show that the consensus will be achieved if and only if the average of the initial states is within the minimum saturation level.
Autors: Young-Hun Lim;Hyo-Sung Ahn;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5388 - 5395
Publisher: IEEE
 
» Considering Backhaul [Book\Software Reviews]
Abstract:
This book offers a comprehensive guide to the subject of microwave backhaul. Design information on this subject is sparse, and it is not easy to collect and interpret. This fact was the driving force behind the creation of this book, which focuses on the electronics of backhaul and describes in detail all the subsystems responsible for transforming the information signal that comes from baseband processing into an electromagnetic wave traveling through the air. Electronics for Microwave Backhaul presents an overview of the evolution of the electronics for microwave radios, from their initial development to present implementations and future trends. The authors have stayed abreast of current real-world industry products and present many real-world solutions to the design issues.
Autors: James Chu;
Appeared in: IEEE Microwave Magazine
Publication date: Oct 2017, volume: 18, issue:6, pages: 125 - 126
Publisher: IEEE
 
» Constrained Dynamic Systems: Generalized Modeling and State Estimation
Abstract:
Due to physical laws or mathematical properties the states of some dynamic systems satisfy certain constraints, and taking advantage of such constraints generally will produce more accurate system models. This paper is concerned with dynamic modeling and state estimation of equality constrained systems. First, an effective framework for constrained dynamic modeling is proposed by which equality constraints and an original dynamics are optimally fused. In particular, modeling of linear and quadratic equality constrained dynamic systems is systematically investigated. Meanwhile, the effects of the original dynamics on the constructed dynamic model are analyzed. Next, properties of the constrained state estimation are presented, and in particular, the constrained minimum mean square error (CMMSE) estimator is proposed and its differences from the conventional constrained estimators are illustrated. Finally, the proposed modeling is assessed on benchmark scenarios of road-confined vehicle tracking. Simulation results demonstrate that the proposed CMMSE estimator outperforms the conventional constrained ones.
Autors: Linfeng Xu;X. Rong Li;Yan Liang;Zhansheng Duan;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Oct 2017, volume: 53, issue:5, pages: 2594 - 2609
Publisher: IEEE
 
» Constructions of Binary Sequence Pairs of Period $3p$ With Optimal Three-Level Correlation
Abstract:
In this letter, we present a new generalized cyclotomic method over based on the Chinese remainder theorem and the cyclotomic classes of order 2. Two new families of binary sequence pairs of period with optimal three-level correlation values are constructed by utilizing these new generalized cyclotomic classes, where is an odd prime. All the constructed binary sequence pairs have optimal correlation values {−3, 1} or {−1, 3}.
Autors: Xiumin Shen;Yanguo Jia;Xiaofei Song;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2150 - 2153
Publisher: IEEE
 
» Contact Force Monitoring and Its Application in Vacuum Circuit Breakers
Abstract:
Condition monitoring of circuit-breaker (CB) operating mechanisms is one the most important aspects of predictive maintenance. This paper proposes a contact force monitoring scheme for 10 ~ 35-kV vacuum CB. With specially designed force sensors and a signal-processing method, we can accurately find the instants of contact touch and separation. With the indirectly measured contact touch-and-separation instants, we can measure the opening speed, closing speed, and open gap over the travel of each phase. The accuracy of our online monitoring scheme is compared with the conventional offline methods that can directly obtain the instants of contact touch and separation by measuring the connectivity of the contacts. The results show that the accuracy of the scheme proposed in this paper is satisfactory and it can meet the engineering requirements of online condition monitoring of CBs. By introducing a set of new force sensors, some additional information that is useful for overall condition assessment of CB operating mechanism can also be extracted; this will help us to find new ways to improve our CB condition monitoring systems.
Autors: Jianzhong Tang;Shisong Lu;Jingwei Xie;Zhengmin Cheng;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Oct 2017, volume: 32, issue:5, pages: 2154 - 2161
Publisher: IEEE
 
» Contactless Current Measurement for Enclosed Multiconductor Systems Based on Sensor Array
Abstract:
How to measure ac currents in a bundle of inaccessible, enclosed conductors has been a challenging problem but with many potential applications. This paper presents a method to solve the problem using an array of magnetic field sensors. The proposed method consists of two novel ideas. The first idea is to use an off-site calibration method to establish sensor parameters including sensing position and angle, which provides more accurate sensor parameter estimation than their nominal values. The second idea is to “measure” (i.e., calculate) conductor currents and positions based on the sensed magnetic fields and preestablished sensor parameters. This process is simplified since the sensor information is obtained by the first idea. Both calibration and measurement tasks are formulated as nonlinear least square problems and solved efficiently. The proposed method is demonstrated for the cases involving ideal three-conductor system and practical residential service cable enclosed in a plastic conduit. The method has the potential for contactless current measurement of Romex cables and overhead distribution lines.
Autors: Guangchao Geng;Juncheng Wang;Kun-Long Chen;Wilsun Xu;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Oct 2017, volume: 66, issue:10, pages: 2627 - 2637
Publisher: IEEE
 
» Content Placement for Wireless Cooperative Caching Helpers: A Tradeoff Between Cooperative Gain and Content Diversity Gain
Abstract:
Depending on what and how caching helpers cache content in their finite storage, the caching helpers can offer either a content diversity gain by serving diverse content or a cooperative gain by jointly transmitting the same content. This paper identifies a tradeoff between the content diversity gain and the cooperative gain according to content placements and proposes a probabilistic content placement to optimally balance the tradeoff. Using stochastic geometry, we quantify this tradeoff by deriving the cache hit rate and the rate coverage probability. To efficiently control the tradeoff, we determine the near-optimal caching probabilities that maximize the average content delivery success probability with the cooperative caching helpers. Our analysis and numerical results reveal that our proposed content placement outperforms the conventional caching schemes, such as caching with uniform probabilities, caching the most popular contents, and caching the content maximizing the cache hit, in terms of the average content delivery success probability.
Autors: Seong Ho Chae;Tony Q. S. Quek;Wan Choi;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6795 - 6807
Publisher: IEEE
 
» Context-Aware Architecture for Probabilistic Voting-based Filtering Scheme in Sensor Networks
Abstract:
Wireless sensor networks are widely deployed and implicitly characterized by stringent energy and computation constraints. Sensor nodes are vulnerable to false positive and false negative attacks that inject false data through compromised nodes. Such attacks cause false alarms with energy drain and information loss. Although several en-route filtering schemes have been designed to detect the attacks, they focus on saving energy through early filtering or continuous delivery of data in accordance with verification records; they cannot exclude compromised nodes. In this paper, we propose a scheme that effectively identifies the compromised nodes and copes with new attacks using a context-aware architecture. In addition, the proposed scheme improves the security strength and energy efficiency of the network. Simulation results validate that the proposed scheme provides energy savings of up to 45 percent and allows fewer attack successes than the existing scheme.
Autors: Su Man Nam;Tae Ho Cho;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Oct 2017, volume: 16, issue:10, pages: 2751 - 2763
Publisher: IEEE
 
» Continuous and Singular Micromagnetic Configurations
Abstract:
Up to the present time [1965], only magnetic configurations that are continuous in the micromagnetic sense have been described in the literature. The consequences of this continuity restriction on possible types of magnetization reversal processes have received no attention. These consequences are discussed here. It is also shown that micromagnetic discontinuities are allowed theoretically. In particular, a micromagnetically singular point may exist that is the zero-dimensional analog of the two-dimensional wall and the one-dimensional Bloch or Néel line of magnetic domain theory.
Autors: Ernst Feldtkeller;
Appeared in: IEEE Transactions on Magnetics
Publication date: Oct 2017, volume: 53, issue:10, pages: 1 - 8
Publisher: IEEE
 
» Control and Emulation of Small Wind Turbines Using Torque Estimators
Abstract:
Soft-stall control of small wind turbines is a method to protect the generation system and/or load from excessive wind speeds and wind gusts without discontinuing power generation. Soft-stall can be activated due to an excess of the power and/or torque/current. This paper proposes a method to improve the existing soft-stall methods for over torque/current protection using a turbine torque estimator. In addition, this paper also proposes two methods to emulate the wind turbine inertia without communications between the load drive (wind turbine emulator) and the generation system controller. This will allow the evaluation of the proposed methods in working conditions.
Autors: Juan M. Guerrero;Carlos Lumbreras;David Díaz Reigosa;Pablo Garcia;Fernando Briz;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4863 - 4876
Publisher: IEEE
 
» Control Design for Disturbance Rejection in the Presence of Uncertain Delays
Abstract:
This paper is concerned with control of processes with uncertain delays for disturbance rejection. The effect of the uncertain delays on the stability is studied. First, the method to compute the maximum uncertain delay that a given controller can tolerate is described. Second, in the case of PI/PID controller, all of the admissible controller parameters stabilizing a system with uncertain but bounded delays are determined. Meanwhile, we propose a simple method to construct the parameter space satisfying a given robustness index for the nominal model. In the admissible regions satisfying various objectives, the global optimum controller is achieved for disturbance rejection in the presence of uncertain delay. As a result, the MIGO ( -constrained Integral Gain Optimization) method is revisited in the case of uncertain delay, and the rule of selecting the value of maximum sensitivity function is proposed in terms of the bound on the uncertain delay. Two simulation examples and an experiment are given to demonstrate the effectiveness and advantage of the proposed method.
Autors: Qibing Jin;Qie Liu;Biao Huang;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Oct 2017, volume: 14, issue:4, pages: 1570 - 1581
Publisher: IEEE
 
» Control Method of Double Inverter Fed Wound Machine for Minimizing Copper Loss in Maximized Operating Area
Abstract:
A double inverter fed wound machine (DFWM) needs two inverters on the rotor as well as the stator side. This scheme gives more freedom to operation of an electric machine and improves the output power capability and the efficiency, but its control method becomes more complex because the number of control variables and the operating constraints increase. This paper deals with a control method of DFWM for minimizing the copper loss in maximized operating area. The possible operation area considering all constraints of currents, voltages, and flux is analyzed on the stator currents plane to maximize the operating area. For the minimum copper loss operation in the operating area, different modes are defined and the optimal currents are determined in each mode. Also, the optimal current selection algorithm is proposed to achieve the torque control using the optimal currents. The simulation and experimental results about wound machines are presented to show the feasibility of the proposed control method.
Autors: Yongsu Han;Jung-Ik Ha;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 7700 - 7710
Publisher: IEEE
 
» Control of a City Road Network: Distributed Exact Verification of Traffic Safety
Abstract:
A least-restrictive supervisor for vehicle collision avoidance is a control algorithm that can detect an unsafe maneuver by a set of human-driven or autonomous vehicles, intervening with a corrective action only when needed to avoid a collision. It can help prevent collisions, and facilitate coexistence of autonomous and human-driven vehicles. Such an algorithm is based on a formal verification problem which, unfortunately, is known to be NP-hard in many cases of interest, for instance at traffic intersections. Here, we propose a strategy to dynamically decompose the formal verification problem of a large road network, exploiting vehicle dynamics and the constraints induced by road topology to separate nonconflicting vehicles. We split the global problem into smaller and treatable subproblems, while still allowing to compute an exact solution. We illustrate our results on three different scenarios.
Autors: Alessandro Colombo;Gabriel Rodrigues de Campos;Fabio Della Rossa;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 4933 - 4948
Publisher: IEEE
 
» Control of Buffer-Induced Current Collapse in AlGaN/GaN HEMTs Using SiNx Deposition
Abstract:
The stoichiometry of low-pressure chemical vapor deposition SiNx surface passivation is shown to change vertical conductivity at the top of the epitaxial stack in GaN-on-Si power high-electron mobility transistors (HEMTs). This changes the charge stored in the carbon-doped GaN layer during high-voltage operation, and allows direct control of buffer-related current collapse in HEMTs. Substrate bias ramps are used to identify the changes in C:GaN charge trapping and vertical leakage. Channel length dependence indicates a lateral conductivity in the C:GaN with a localized increase in vertical conductivity under the ohmic contacts. An optimum SiNx recipe is identified which simultaneously delivers low current collapse and low drain leakage.
Autors: William M. Waller;Mark Gajda;Saurabh Pandey;Johan J. T. M. Donkers;David Calton;Jeroen Croon;Jan Šonský;Michael J. Uren;Martin Kuball;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4044 - 4049
Publisher: IEEE
 
» Control of Junction Temperature and Its Rate of Change at Thermal Boundaries via Precise Loss Manipulation
Abstract:
To optimize the lifetime of switching power semiconductors, this paper presents a methodology to control power device junction temperature and its change during power cycles at thermal boundaries. This paper proposes a supervisory state machine to interrupt nominal system-level control only when temperature bounds are exceeded, and coordinates smooth transitions as and approach their respective boundaries. To ensure that thermal states are regulated via precise and independent modulation of conduction and switching loss elements, decoupling methods are proposed. Also proposed is a control law that closes a control loop on the rate of change state , and introduces active thermal capacitance and conductance into the closed-loop thermal system dynamics. Experimental evaluation of the proposed system illustrates well damped and responses, and gradual adjustment of the manipulated inputs switching frequency and duty ratio. Finally, comparison with a current limit-based regulation method illustrates how the proposed system allows power converters to push harder against their thermal limits.
Autors: Timothy Allen Polom;Boru Wang;Robert D. Lorenz;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4796 - 4806
Publisher: IEEE
 
» Control Scheme for Open-Ended Induction Motor Drives With a Floating Capacitor Bridge Over a Wide Speed Range
Abstract:
An electric drive for high-speed applications is analyzed in this paper. The drive consists of a dual two-level inverter with a floating bridge, fed by a single voltage source, and a three-phase induction motor with open-ended stator windings. The floating bridge compensates the reactive power of the motor, so that the main inverter operates at unity power factor and fully exploits its current capability. The constant power speed range of the motor can be significantly extended depending on the dc-link voltage of the floating inverter. The details of the control system are examined and the feasibility of an electric drive is experimentally assessed.
Autors: Michele Mengoni;Albino Amerise;Luca Zarri;Angelo Tani;Giovanni Serra;Domenico Casadei;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4504 - 4514
Publisher: IEEE
 
» Control Strategy for a Modified Cascade Multilevel Inverter With Dual DC Source for Enhanced Drivetrain Operation
Abstract:
This paper presents a new control strategy for a modified cascade multilevel inverter used in drivetrain operations. The proposed inverter is a three-phase bridge with its dc link fed by a dc source (battery), and each phase series-connected to an H-bridge fed with a floating dc source (ultracapacitor). To exploit the potentials of the inverter for enhanced drivetrain performance, a sophisticated yet efficient modulation method is proposed to optimize energy transfer between the dc sources and with the load (induction motor) during typical operations, and to minimize switching losses and harmonics distortion. Detailed analysis of the proposed control method is presented, which is supported by experimental verifications.
Autors: Maciej S. Bendyk;Patrick Chi-Kwong Luk;Mohammed H. Alkhafaji;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4655 - 4664
Publisher: IEEE
 
» Controllability of Multiagent Networks With Antagonistic Interactions
Abstract:
This paper addresses the controllability of a class of antagonistic multiagent networks with both positive and negative edges. All the agents of the multiagent network run a consensus algorithm using a signed Laplacian. Based on the generalized equitable partition, we propose a graph-theoretic characterization of an upper bound on the controllable subspace. Then, we provide a necessary condition for the controllability of the system and give an algorithm to compute the partition. Furthermore, we prove that for a structurally balanced network, the controllability is equivalent to that of the corresponding all-positive network, if the leaders are chosen from the same vertex set. Several examples are given to illustrate these results.
Autors: Chao Sun;Guoqiang Hu;Lihua Xie;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5457 - 5462
Publisher: IEEE
 
» Controllable Rotations of Spiraling Elliptic Beams in Anisotropic Linear Media
Abstract:
We study the rotation properties of spiraling elliptic beams in the anisotropy media. Based on the Collins formula, we obtain the exact analytical solution of the spiraling elliptic beams carrying the orbital angular momentum (OAM) to the paraxial wave equation. It is found that the rotation property is closely relevant to the OAM, which can be controlled by the linear anisotropy of media. For an anisotropic media such as the uniaxial crystal, the rotation velocity of spiraling elliptic beams at the output can be controlled only by changing the direction of the optic axis of the uniaxial crystal. Depending on the anisotropy parameter, two rotation modes are predicted for the spiraling elliptic beam. For small anisotropy parameter, the rotation direction of the spiraling elliptic beam is inverted at a certain propagation distance. When the anisotropy parameter is large enough, the invertion of the rotation direction disappears. The results are potentially useful in controlling the optical beams.
Autors: Guo Liang;Tingjian Jia;Zhanmei Ren;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 8
Publisher: IEEE
 
» Controllable Unidirectional Emission With Double-Resonant Plasmonic Antenna
Abstract:
A double-resonant metal–insulator–metal (MIM) optical antenna is theoretically proposed to control the emission directivity of a dipolar emitter. The nanoantenna consists of an in-plane side-by-side assembling metallic nanobar dimer on the top and a metallic nanoplate on the bottom, separated by a dielectric spacer. Unidirectional and enhanced emission of the emitter is wavelength dependent. It is controllable by changing the phase differences of constituting elements of the antenna, induced by the double magnetic resonances at different wavelengths. The results can be potentially used in near-field sample detection, solar cell, and single-photon source.
Autors: Fei Liu;Shengyin Ye;Kailiang Zhang;Guangjun Ren;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 10
Publisher: IEEE
 
» Controlled Kink Effect in a Novel High-Voltage LDMOS Transistor by Creating Local Minimum in Energy Band Diagram
Abstract:
A new technique to control the kink effect in the high-voltage lateral double-diffused MOSFET (LDMOS) is presented in this paper. This technique produces a local minimum in the band diagram of the proposed structure, which causes the lower barrier height for the holes from the channel to the source region. So, the produced excess holes during the impact ionization process in the channel are reduced significantly. We have called the proposed structure as local minimum energy band LDMOS (LMEB-LDMOS) transistor. The LMEB-LDMOS structure contains modified source and drain regions. The modified source region creates a local minimum in the energy band diagram for absorbing the excess holes, and the modified drain region causes high breakdown voltage (462 V) and low specific on-resistance (. Also, the drift region with lower doping density than drain is deleted in LMEB-LDMOS transistor. The simulation with 2-D ATLAS simulator shows that the proposed structure improves the device performance.
Autors: Mahsa Mehrad;Meysam Zareiee;Ali A. Orouji;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4213 - 4218
Publisher: IEEE
 
» Controlled Voltage Breakdown in Disconnector Contact System for VFTO Mitigation in Gas-Insulated Switchgear (GIS)
Abstract:
Several methods have been proposed and investigated so far on mitigation of very fast transient overvoltages (VFTO) in gas-insulated switchgear (GIS). The state-of-the-art methods are primarily based on dissipation of the energy associated with electromagnetic waves that the VFTO originate from and are composed of. Present paper reports on an alternative concept of VFTO mitigation based on the principle of controlling voltage conditions preceding voltage breakdown in SF6 gas that leads to VFTO generation. The paper introduces different control algorithms and shows how the algorithms can limit VFTO maximum value and total number of voltage breakdowns during operation of the GIS disconnector. The concept is applied for mitigation of VFTO in ultra-high voltage GIS. As the study case, an 1100 kV test set-up is used as recently reported for Wuhan (China) GIS station, with the disconnector characteristics obtained from 1100 kV development tests.
Autors: Marcin Szewczyk;Maciej Kuniewski;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Oct 2017, volume: 32, issue:5, pages: 2360 - 2366
Publisher: IEEE
 
» Convergence Rate of Distributed ADMM Over Networks
Abstract:
We propose a new distributed algorithm based on alternating direction method of multipliers (ADMM) to minimize sum of locally known convex functions using communication over a network. This optimization problem emerges in many applications in distributed machine learning and statistical estimation. Our algorithm allows for a general choice of the communication weight matrix, which is used to combine the iterates at different nodes. We show that when functions are convex, both the objective function values and the feasibility violation converge with rate , where is the number of iterations. We then show that when functions are strongly convex and have Lipschitz continuous gradients, the sequence generated by our algorithm converges linearly to the optimal solution. In particular, an -optimal solution can be computed with iterations, where is the condition number of the problem. Our analysis highlights the effect of network and communication weights on the convergence rate through degrees of the nodes, the smallest nonzero eigenvalue, and operator norm of the communication matrix.
Autors: Ali Makhdoumi;Asuman Ozdaglar;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5082 - 5095
Publisher: IEEE
 
» Convex Distributed Controller Synthesis for Interconnected Heterogeneous Subsystems Via Virtual Normal Interconnection Matrices
Abstract:
Based on a previously introduced framework for distributed controller synthesis, in this note a novel transformation of interconnection matrices is proposed that enables to consider arbitrary, time-varying and directed interaction topologies. It represents any interconnection as a virtual interconnection matrix that has the property of being normal, i.e., that guarantees the existence of a unitary diagonalizing transformation, which admits to decompose the synthesis problem in terms of the entire interconnected system into problems of subsystem scale, which can then be solved by standard convex multiplier-based gain-scheduling synthesis methods with complexity in the order of a single subsystem. When compared with a method from the literature, the method shows superior performance in both a numerical example and the leader-follower formation control problem of nonlinear quadrocopter models.
Autors: C. Hoffmann;H. Werner;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5337 - 5342
Publisher: IEEE
 
» Cooperative Modulation Classification for Multipath Fading Channels via Expectation-Maximization
Abstract:
In this paper, we investigate the cooperative modulation classification problem under multipath scenarios with blind channel information. Multipath channels cause severe degradation on the modulation classification performance, which has not yet been thoroughly solved in the existing literature. To address this issue, a likelihood-based classifier using the expectation-maximization algorithm is proposed, which is capable of finding the maximum likelihood estimates of unknown parameters in a tractable way. Furthermore, to evaluate the upper bound performance of the proposed algorithm, the Cramér–Rao lower bounds of the joint estimates of unknown parameters are derived. Extensive simulations show that the classification performance of the proposed algorithm with good initialization scheme is close to the performance upper bound in the high signal-to-noise ratio region. The results also demonstrate that the proposed algorithm provides significant performance improvement in the multipath channels compared with conventional approaches.
Autors: Jingwen Zhang;Danijela Cabric;Fanggang Wang;Zhangdui Zhong;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6698 - 6711
Publisher: IEEE
 
» Cooperative Raman Spectroscopy for Real-Time In Vivo Nano-Biosensing
Abstract:
In the last few decades, the development of miniature biological sensors that can detect and measure different phenomena at the nanoscale has led to transformative disease diagnosis and treatment techniques. Among others, biofunctional Raman nanoparticles have been utilized in vitro and in vivo for multiplexed diagnosis and detection of different biological agents. However, existing solutions require the use of bulky lasers to excite the nanoparticles and similarly bulky and expensive spectrometers to measure the scattered Raman signals, which limit the practicality and applications of this nano-biosensing technique. In addition, due to the high path loss of the intra-body environment, the received signals are usually very weak, which hampers the accuracy of the measurements. In this paper, the concept of cooperative Raman spectrum reconstruction for real-time in vivo nano-biosensing is presented for the first time. The fundamental idea is to replace the single excitation and measurement points (i.e., the laser and the spectrometer, respectively) by a network of interconnected nano-devices that can simultaneously excite and measure nano-biosensing particles. More specifically, in the proposed system, a large number of nanosensors jointly and distributively collect the Raman response of nano-biofunctional nanoparticles (NBPs) travelling through the blood vessels. This paper presents a detailed description of the sensing system and, more importantly, proves its feasibility, by utilizing the accurate models of optical signal propagation in intra-body environment and low-complexity estimation algorithms. The numerical results show that with a certain density of NBPs, the reconstructed Raman spectrum can be recovered and utilized to accurately extract the targeting intra-body information.
Autors: Hongzhi Guo;Josep Miquel Jornet;Qiaoqiang Gan;Zhi Sun;
Appeared in: IEEE Transactions on NanoBioscience
Publication date: Oct 2017, volume: 16, issue:7, pages: 571 - 584
Publisher: IEEE
 
» Coprime Factors Model Reduction of Spatially Distributed LTV Systems Over Arbitrary Graphs
Abstract:
This technical note is on the model reduction of distributed systems formed by discrete-time, linear time-varying, heterogeneous subsystems interconnected over arbitrary directed graphs and subjected to communication latency. We give two procedures to construct a strongly stable coprime factorization for a strongly stabilizable and strongly detectable system. One of the procedures ensures the contractiveness of the resulting factorization. Then, we apply the structure-preserving balanced truncation method for distributed systems. We illustrate the proposed methods through an example.
Autors: Dany Abou Jaoude;Mazen Farhood;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5254 - 5261
Publisher: IEEE
 
» Copula-Based Joint Statistical Model for Polarimetric Features and Its Application in PolSAR Image Classification
Abstract:
Polarimetric features are essential to polarimetric synthetic aperture radar (PolSAR) image classification for their better physical understanding of terrain targets. The designed classifiers often achieve better performance via feature combination. However, the simply combination of polarimetric features cannot fully represent the information in PolSAR data, and the statistics of polarimetric features are not extensively studied. In this paper, we propose a joint statistical model for polarimetric features derived from the covariance matrix. The model is based on copula for multivariate distribution modeling and alpha-stable distribution for marginal probability density function estimations. We denote such model by CoAS. The proposed model has several advantages. First, the model is designed for real-valued polarimetric features, which avoids the complex matrix operations associated with the covariance and coherency matrices. Second, these features consist of amplitudes, correlation magnitudes, and phase differences between polarization channels. They efficiently encode information in PolSAR data, which lends itself to interpretability of results in the PolSAR context. Third, the CoAS model takes advantage of both copula and the alpha-stable distribution, which makes it general and flexible to construct the joint statistical model accounting for dependence between features. Finally, a supervised Markovian classification scheme based on the proposed CoAS model is presented. The classification results on several PolSAR data sets validate the efficacy of CoAS in PolSAR image modeling and classification. The proposed CoAS-based classifiers yield superior performance, especially in building areas. The overall accuracies are higher by 5%–10%, compared with other benchmark statistical model-based classification techniques.
Autors: Hao Dong;Xin Xu;Haigang Sui;Feng Xu;Junyi Liu;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5777 - 5789
Publisher: IEEE
 
» Core Regulation of Long Period Grating Based on Ring-Core Hollow Fiber and the Application of Temperature Sensing
Abstract:
We propose a novel long-period grating (LPG) based on a ring-core hollow fiber (RCHF) filled with functional liquid as a tunable material. The RCHF structure is simple. The effective refractive index tuning characteristics of the liquid-filled RCHF-LPG are investigated. The RCHF-LPG functions as a tunable device filling with a functional liquid. The temperature sensitivities of three RCHF-LPG samples filled with dimethylacetamide (DMA) or DMA–glycerin mixtures are measured. The results show that the sample with high-RI liquid has higher sensitivity to temperature variation. The maximum linear sensitivity of the temperature can reach −618 pm/°C.
Autors: Bin Dai;Xiang Shen;Jinyan Li;Nengli Dai;Luyun Yang;Xiongwei Hu;Yibo Wang;Yehui Liu;Jinggang Peng;Haiqing Li;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 6
Publisher: IEEE
 
» Correction to “The Generalized Stochastic Likelihood Decoder: Random Coding and Expurgated Bounds” [Aug 17 5039-5051]
Abstract:
The purpose of this paper is to handle a gap that was found in the proof of Theorem 2 in the paper “The generalized stochastic likelihood decoder: random coding and expurgated bounds.”
Autors: Neri Merhav;
Appeared in: IEEE Transactions on Information Theory
Publication date: Oct 2017, volume: 63, issue:10, pages: 6827 - 6829
Publisher: IEEE
 
» Corrections to "JANUS-Based Services for Operationally Relevant Underwater Applications" [ IEEE J. Ocean. Eng., 2017, DOI: 10.1109/JOE.2017.2722018]
Abstract:
Presents corrections to the paper, “JANUS-based services for operationally relevant underwater applications,” (Petroccia, R., et al), IEEE J. Ocean. Eng., Jul. 2017.
Autors: R. Petroccia;J. Alves;G. Zappa;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 1162 - 1162
Publisher: IEEE
 
» Corrections to “JANUS-Based Services for Operationally Relevant Underwater Applications” [ IEEE J. Ocean. Eng., 2017, DOI: 10.1109/JOE.2017.2722018]
Abstract:
Autors: R. Petroccia;J. Alves;G. Zappa;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 1162 - 1162
Publisher: IEEE
 
» Corrections to “Density of Traps at the Insulator/III-N Interface of GaN Heterostructure Field-Effect Transistors Obtained by Gated Hall Measurements”
Abstract:
In the above paper [1], equation 5 should read

Equation 6 should read

Autors: Shlomo Mehari;Arkady Gavrilov;Moshe Eizenberg;Dan Ritter;
Appeared in: IEEE Electron Device Letters
Publication date: Oct 2017, volume: 38, issue:10, pages: 1504 - 1504
Publisher: IEEE
 
» Corrections to “On-Chip Investigation of Phase Noise in Monolithically Integrated Gain-Switched Lasers”
Abstract:
In the above letter equations (2) and (6) are incorrect due to an additional present within the bracketed term.
Autors: Justin K. Alexander;Padraic E. Morrissey;Ludovic Caro;Mohamad Dernaika;Niall P. Kelly;Frank H. Peters;
Appeared in: IEEE Photonics Technology Letters
Publication date: Oct 2017, volume: 29, issue:20, pages: 1755 - 1755
Publisher: IEEE
 
» Correlated Random Bit Generation Using Chaotic Semiconductor Lasers Under Unidirectional Optical Injection
Abstract:
Correlated random bit generation is investigated using three optically injected chaotic semiconductor lasers. Based on a rate-equation model, a continuous-wave injection first perturbs a common laser into chaos. The common laser then optically injects a pair of response lasers through a public channel unidirectionally. The two response lasers of identical parameters are synchronized. Their chaotic emissions are digitized in yielding correlated random bit streams. As the scheme advantageously involves no feedback loops, the output bits contain no undesirable time-delay information artifacts. Security is ensured as the response lasers produce bits that cannot be extracted using the information in the public channel alone. Output bit streams are generated at a tunable rate of up to about 2 Gbps with randomness verified by a test suite of the National Institute of Standards and Technology. The streams are correlated with a low bit error ratio of less than 4, which is sensitive to parameter mismatch between the response lasers.
Autors: Xiao-Zhou Li;Song-Sui Li;Sze-Chun Chan;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 11
Publisher: IEEE
 
» Correlation of Gate Capacitance with Drive Current and Transconductance in Negative Capacitance Ge PFETs
Abstract:
Correlation of gate capacitance with drive current and transconductance in negative capacitance (NC) Ge pFETs is first investigated. Hysteresis-free NC Ge pFETs integrated with 4.5-nm HZO achieving the improved and over the control devices are fabricated. A peak in the versus gate voltage curve is demonstrated in the NC Ge pFET, indicating the NC effect induced by HZO film. It is observed that and of the NC transistors are enhanced as the peak gets increased. This is attributed to the fact that, as the device operates in the NC region, both and internal gate voltage amplification are proportional to /(), where and are the NC of HZO and the MOS capacitance of the device, respectively.
Autors: Jing Li;Jiuren Zhou;Genquan Han;Yan Liu;Yue Peng;Jincheng Zhang;Qing-Qing Sun;David Wei Zhang;Yue Hao;
Appeared in: IEEE Electron Device Letters
Publication date: Oct 2017, volume: 38, issue:10, pages: 1500 - 1503
Publisher: IEEE
 
» Cost Effective Laser Structuration of Optical Waveguides on Thin Glass Interposer
Abstract:
In order to enhance electro–optical system-in-package capabilities for silicon photonics, a cost effective fabrication process for optical waveguides integration on thin glass substrate interposer is demonstrated. First, a femtosecond laser ablation coupled with a hydrofluoric acid etching is developed to create microgrooves at the glass surface. Second, a dry film lamination followed by chemical mechanical planarization is achieved to define surface optical waveguides by filling the microchannels. Physical characterizations of the fabricated waveguides are performed using optical and scanning electron microscopy. Finally, optical mode profile and loss characterizations confirm the optical functionality of waveguides which prove to be multimodal at 1550 nm.
Autors: Jean-Marc Boucaud;Folly-Eli Ayi-Yovo;Quentin Hivin;Matthieu Berthomé;Cédric Durand;Frédéric Gianesello;Davide Bucci;Guillaume Ducournau;Jean-François Robillard;Jean-Emmanuel Broquin;Emmanuel Dubois;
Appeared in: Journal of Lightwave Technology
Publication date: Oct 2017, volume: 35, issue:20, pages: 4445 - 4450
Publisher: IEEE
 
» Coupled Parametric Effects on Magnetic Fields of Eddy-Current Induced in Non-Ferrous Metal Plate for Simultaneous Estimation of Geometrical Parameters and Electrical Conductivity
Abstract:
Illustrated with a magnetic field based eddy-current (EC) sensor which utilizes an anisotropic magneto-resistive sensor to directly measure the magnetic flux density (MFD) generated by the EC induced in a non-ferrous metal plate, this paper presents a material-independent method for multi-objective estimation of the plate geometrical parameters and/or electrical conductivity using frequency response analysis. The model, which agrees well with a 2-D axis-symmetric finite-element analysis, relates the measured (EC-generated) MFD to three dimensionless parameters (skin depth, plate thickness, and sensor-plate distance) normalized relative to a specified coil design. Data in the material-independent model that provides the basis to investigate the parametric effects on measured MFD can be regrouped in 2-D maps for simultaneously measuring any two of the three parameters. Experimental measurements were conducted on three different materials (Aluminum, Titanium, and Titanium alloy) with different thicknesses and sensor-plate distances between 1 and 5 mm operating in the frequency range from 100 Hz to 42.8 kHz. Experimental results show that the maximum difference between the analytically computed and experimental data is in the order of 5%, and demonstrate that the method has the capability of simultaneously measuring two unknowns out of three geometrical and/or material properties using a material-independent 2-D map.
Autors: Kok-Meng Lee;Chun-Yeon Lin;Bingjie Hao;Min Li;
Appeared in: IEEE Transactions on Magnetics
Publication date: Oct 2017, volume: 53, issue:10, pages: 1 - 9
Publisher: IEEE
 
» Coupling Characteristics of Selective-Infiltration-Based Locally Tapered Photonic Crystal Fiber
Abstract:
We have proposed and experimentally demonstrated a novel compound structure based on selectively infiltrating of a local tapered photonic crystal fiber (TPCF). Theoretical and experimental investigations indicate that tapering photonic crystal fiber (PCF) can change the material refractive index (RI) of silica core, and the RI change can be revealed and proved to influence the effective RI curve of the PCF core mode, which results in the shifting of the phase matching point. Moreover, strong coupling can occur in the infiltrated TPCF due to the increased overlap integral of the involved coupled modes. As application, the proposed configuration based on TPCF has huge potential use in microfluidic, RI, and dual-parameter sensing with high sensitivity, such as ultrahigh strain sensitivity of –139.78 nm/N (–167.74 pm/μϵ).
Autors: Hu Liang;Zhi Wang;Yange Liu;Hongye Li;Hongwei Zhang;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 7
Publisher: IEEE
 
» Coupling Matrix Synthesis of Microwave Differentiators
Abstract:
This letter presents a new design of microwave differentiators using coupled-resonator network. It is synthesized using coupling matrix techniques in the low-pass domain and subsequently transformed and implemented in the bandpass domain. Two numerical examples and one experimental validation are provided to illustrate the approach, which finally validates the proposed approach.
Autors: Qingfeng Zhang;Fen Xia;Ge Zhang;Yifan Chen;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Oct 2017, volume: 27, issue:10, pages: 879 - 881
Publisher: IEEE
 
» Coupling Quality [Enigmas, etc.]
Abstract:
Various puzzles, games, humorous definitions, or mathematical that should engage the interest of readers.
Autors: Takashi Ohira;
Appeared in: IEEE Microwave Magazine
Publication date: Oct 2017, volume: 18, issue:6, pages: 154 - 154
Publisher: IEEE
 
» Covariance Matrix Estimation for Broadband Underwater Noise
Abstract:
In this paper, a technique is presented for frequency-smoothing the sample covariance matrix observed at the output of a set of elements or beams so as to obtain a frequency-smoothed estimate of the broadband noise covariance matrix due to underwater noise. The smoothing technique is based on a linear model that is derived through analysis of the delay-domain cross covariance of the ambient noise observed by a pair of beams or omnidirectional hydrophones. A simple and robust least squares fitting algorithm allows for extraction of a frequency-smoothed broadband noise covariance estimate even in the presence of narrowband energy. Simulated passive sonar examples demonstrate the validity and utility of the estimate. Possible applications include adaptive beamforming and measuring the vertical/horizontal directionality of diffuse broadband ambient noise sources such as wind and rain.
Autors: Ryan J. Pirkl;Jason M. Aughenbaugh;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 936 - 947
Publisher: IEEE
 
» Coverage in Heterogeneous Downlink Millimeter Wave Cellular Networks
Abstract:
In this paper, we provide an analytical framework to analyze heterogeneous downlink millimeter-wave (mm-wave) cellular networks consisting of tiers of randomly located base stations (BSs), where each tier operates in an mm-wave frequency band. Signal-to-interference-plus-noise ratio (SINR) coverage probability is derived for the entire network using tools from stochastic geometry. The distinguishing features of mm-wave communications, such as directional beamforming, and having different path loss laws for line-of-sight and non-line-of-sight links are incorporated into the coverage analysis by assuming averaged biased-received power association and Nakagami fading. By using the noise-limited assumption for mm-wave networks, a simpler expression requiring the computation of only one numerical integral for coverage probability is obtained. Also, the effect of beamforming alignment errors on the coverage probability analysis is investigated to get insight on the performance in practical scenarios. Downlink rate coverage probability is derived as well to get more insights on the performance of the network. Moreover, the effect of deploying low-power smaller cells and the impact of biasing factor on energy efficiency is analyzed. Finally, a hybrid cellular network operating in both mm-wave and -wave frequency bands is addressed.
Autors: Esma Turgut;M. Cenk Gursoy;
Appeared in: IEEE Transactions on Communications
Publication date: Oct 2017, volume: 65, issue:10, pages: 4463 - 4477
Publisher: IEEE
 
» Cross-Entropy Method for Electromagnetic Optimization With Constraints and Mixed Variables
Abstract:
An elegant and simple approach is presented for electromagnetic (EM) optimizations, especially when mixed variables and/or constraints are involved. In mixed-variable optimization, some variables are continuous (can take any value within a range) and others are discrete (can take only values from a database). An example constraint is when the total length of a device under optimization is specified. Our approach can handle such optimization problems and is based on an abstract probabilistic evolutionary optimization algorithm, called the cross-entropy (CE) method. We believe that this is the first application of CE with full-wave EM simulations. A quick performance benchmarking on two test functions was performed to compare convergence of CE and two other established optimization algorithms. Then, the advantages of the CE method when simultaneously optimizing a mix of discrete and continuous variables and imposing geometric constraints are illustrated. Finally, six resonant cavity antennas (RCAs) were optimized, and one was prototyped and tested to verify predicted results. This one-layer-superstrate RCA prototype has a measured peak directivity of 17.6 dBi with a 3 dB directivity bandwidth of 51% and lower sidelobes, outperforming all such prototypes in the literature.
Autors: Maria Kovaleva;David Bulger;Basit Ali Zeb;Karu P. Esselle;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Oct 2017, volume: 65, issue:10, pages: 5532 - 5540
Publisher: IEEE
 
» Crosstalk Analysis of Heterogeneous Multicore Fibers Using Coupled-Mode Theory
Abstract:
Intercore crosstalk of heterogeneous multicore fiber is investigated based on coupled-mode theory. Random twisting model is used for estimating the crosstalk. The crosstalk of two kinds of fibers: triangular lattice 30-core fiber with four kinds of cores and square lattice 32-core fiber with two kinds of cores is investigated both theoretically and experimentally. Unlike previous study, measured crosstalk for all the combinations of cores for both fibers is in good agreement with calculated values with single correlation length, showing the validity of the theoretical model used here.
Autors: Takeshi Fujisawa;Yoshimichi Amma;Yusuke Sasaki;Shoichiro Matsuo;Kazuhiko Aikawa;Kunimasa Saitoh;Masanori Koshiba;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 8
Publisher: IEEE
 
» Crowdsourcing Sensing to Smartphones: A Randomized Auction Approach
Abstract:
Crowdsourcing to mobile users has emerged as a compelling paradigm for collecting sensing data over a vast area for various monitoring applications. It is of paramount importance for such crowdsourcing paradigm to provide effective incentive mechanisms. State-of-the-art auction mechanisms for crowdsourcing to mobile users are typically deterministic in the sense that for a given sensing job from a crowdsourcer, only a small set of smartphones are selected to perform sensing tasks and the rest are not selected. One apparent disadvantage of such deterministic auction mechanisms is that the diversity with respect to the sensing job is reduced. As a consequence, the quality of the collected sensing data is also decreased. This is due to failure to exploit the intrinsic advantage of the large set of diverse mobile users in a mobile crowdsourcing network. In this paper, we propose a randomized combinatorial auction mechanism for the social cost minimization problem, which is proven to be NP-hard. We design an approximate task allocation algorithm that is near optimal with polynomial-time complexity and use it as a building block to construct the whole randomized auction mechanism. Compared with deterministic auction mechanisms, the proposed randomized auction mechanism increases the diversity in contributing users for a given sensing job. We carry out both solid theoretical analysis and extensive numerical studies and show that our randomized auction mechanism achieves approximate truthfulness, individual rationality, and high computational efficiency.
Autors: Juan Li;Yanmin Zhu;Yiqun Hua;Jiadi Yu;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Oct 2017, volume: 16, issue:10, pages: 2764 - 2777
Publisher: IEEE
 
» Cryptanalysis of Controlled Bidirectional Quantum Secure Direct Communication Network Using Classical XOR Operation and Quantum Entanglement
Abstract:
The multi-user controlled bidirectional quantum secure direct communication network protocol based on classical EXCLUSIVE-OR operation and quantum entanglement is analyzed. It is shown that this protocol has the information leakage problem, that is, one half of the information the users transmit is leaked out unconsciously. Furthermore, it is also weak against the intercept-measure-resend attack and the Controlled-Not operation attack from an outside adversary, and the different initial state attack from the controller.
Autors: Zhihao Liu;Hanwu Chen;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2202 - 2205
Publisher: IEEE
 
» Cumulation of High-Current Electron Beams: Theory and Experiment
Abstract:
High-power electron beam cumulation in a relativistic vacuum diode with a ring-type cathode is considered. The term “electron beam cumulation” here means electron beam self-focusing accompanied with multifold beam current density increase on the beam axis compared to the average current density in the cathode-anode gap. Space-charge repulsion of electrons emitted by the explosive-emission plasma on the inner edge of the cathode is shown to be the origin of this cumulation mechanism. Current density in the vicinity of beam axis is evaluated for different cathode inner diameter values both numerically and experimentally. Cathode with eccentric apertures of different diameters is studied experimentally.
Autors: Sergei Anishchenko;Vladimir Baryshevsky;Nikolai Belous;Alexandra Gurinovich;Elizaveta Gurinovich;Evgeny Gurnevich;Pavel Molchanov;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Oct 2017, volume: 45, issue:10, pages: 2739 - 2743
Publisher: IEEE
 
» Cumulative Dual Foreground Differences for Illegally Parked Vehicles Detection
Abstract:
Illegally parked vehicles on the urban road may create a traffic flow problem as well as a potential traffic accident, such as crashing between parked and other vehicles. Thus, the intelligent traffic monitoring system should be able to prevent this situation by integrating an illegally parked vehicle detection module. However, implementing such a module becomes more challenging due to road environments, such as weather conditions, occlusion, and illumination changing. Hence, this work addresses a method to implement an illegally parked vehicle detection based on the cumulative dual foreground differences from the short- and long-term background models, temporal analysis, vehicle detector, and tracking. The extensive experiments were conducted using both iLIDS and our proposed datasets to evaluate the effectiveness of the proposed method by comparing with other methods. The results showed that the method is effective in detecting illegally parked vehicles and can be considered as part of the intelligent traffic monitoring system.
Autors: Wahyono;Kang-Hyun Jo;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2464 - 2473
Publisher: IEEE
 
» Current Noise Cancellation for Bearing Fault Diagnosis Using Time Shifting
Abstract:
The stator current of a typical induction motor involves the supply fundamental and its harmonics existing before and after the presence of a bearing defect, and much of the information they contain is not related to the bearing defect. In this sense, they are basically noise to bearing fault diagnosis problem. This paper develops a current noise cancellation method using time shifting. Current residue is obtained by adding digital current signal to its own sample-delayed representation as an antinoise component. The amount of the sample delay is only dependent upon the supply frequency and the sampling rate. This amount is set to eliminate the supply fundamental and its odd multiple harmonics. After obtaining the current residue, through the spectral analysis of the envelope of the current residue, the characteristic fault frequencies for a defective bearing can be revealed. To show the superiority, the developed method is experimentally compared with three of the current-based methods in the literature. Experimental results for the defects in the outer raceway, the inner raceway, and the ball of a bearing verify the merits and effectiveness of the developed method.
Autors: Fardin Dalvand;Satar Dalvand;Fatemeh Sharafi;Michael Pecht;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 8138 - 8147
Publisher: IEEE
 
» Current-Detection-Independent Dead-Time Compensation Method Based on Terminal Voltage A/D Conversion for PWM VSI
Abstract:
Dead-time insertion increases noise and torque pulsation in motors under open-loop constant V/f control, and it results in instability in motors under sensorless field-orientated control or direct torque control at low speed, degrading performance of motor drive systems. In order to overcome the drawback of dead-time insertion, a novel current-detection-independent dead-time compensation technique based on terminal voltage A/D conversion is proposed in this paper. Both current polarity and compensation time can be extracted from the sampled terminal voltage. Experiments on an induction motor rated at 210 V, 2.2 kW demonstrated the proposed technique can significantly improve the performance of the fixed compensation, online compensation, and even the feedback compensation method. The proposed scheme does not rely on current sensors, and thus can be applied to both open-loop and closed-loop motor drive systems. When combined with the fixed compensation method, the performance of the proposed technique is even comparable with the feedback compensation method within a large frequency range, making it very attractive for open-loop constant V/f drives where current sensors are not available.
Autors: Gang Liu;Dafang Wang;Yi Jin;Miaoran Wang;Peng Zhang;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 7689 - 7699
Publisher: IEEE
 
» Current-Feed Single-Switch Forward Resonant DC Transformer (DCX) With Secondary Diode-Clamping
Abstract:
A simple current-feed single-switch forward resonant converter with secondary diode-clamping is proposed for low-power high-density bus converter applications in this paper. The quasi-zero-voltage-switching turn-on and quasi-zero-current-switching (ZCS) turn-off for switch are both achieved. Due to the quasi-ZCS turn-off , the high voltage spike in traditional single forward converter with a reset winding is much reduced. A small diode connected to the output capacitor is utilized to clamp the voltage stress of the switches. The operating principle of the proposed converter is analyzed and a MHz 66 W 24 V-to-12 V prototype with all Si devices is built up. Experimental results show good soft-switching features, and the prototype achieves 95.3% peak efficiency with 270 W/in3 power density.
Autors: Wei Qin;Xinke Wu;Junming Zhang;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 7790 - 7799
Publisher: IEEE
 
» CUTE Mote, A Customizable and Trustable End-Device for the Internet of Things
Abstract:
The ubiquitous connectivity of the low-end devices in the Internet of Things (IoT) brings new challenges over the traditional wireless sensor networks’ architectures. Such challenges require not only security and privacy-related features, but also solutions to handle the ever-growing amount of data transferred over the network. However, performing such tasks on resource constrained devices is not straightforward. The need for energy-efficient devices, while preserving their performance and security capabilities, requires new solutions at the architectural level of the wireless device. This paper proposes a heterogeneous architecture that targets low-end and resource constrained IoT devices, combining a hardcore microcontroller unit (MCU) and a reconfigurable computing unit (RCU) with an IEEE 802.15.4 radio transceiver. The MCU hosts an embedded operating system with an IoT-enabled network stack, and exploits the available field-programmable gate array technology to implement the RCU and to deploy customized sensing- and network-related accelerators, offloading heavy, and/or complex software tasks to dedicated hardware blocks. The customizable and trustable end-device mote was implemented using the proposed architecture and the achieved results demonstrates the benefits, both in terms of performance and energy, of accelerating network-related tasks in always-connected resource constrained IoT devices.
Autors: Tiago Gomes;Filipe Salgado;Adriano Tavares;Jorge Cabral;
Appeared in: IEEE Sensors Journal
Publication date: Oct 2017, volume: 17, issue:20, pages: 6816 - 6824
Publisher: IEEE
 
» CVaR-Constrained Optimal Bidding of Electric Vehicle Aggregators in Day-Ahead and Real-Time Markets
Abstract:
An electric vehicle aggregator (EVA) that manages geographically dispersed electric vehicles offers an opportunity for the demand side to participate in electricity markets. This paper proposes an optimization model to determine the day-ahead inflexible bidding and real-time flexible bidding under market uncertainties. Based on the relationship between market price and bid price, the proposed optimal bidding model of EVA aims to minimize the conditional expectation of electricity purchase cost in two markets considering price volatility. Moreover, the penalty cost of the deviation between the bidding quantities is included to avoid large power variation and arbitrage. The conditional expectation optimization model is formulated as an expectation minimization problem with the conditional value-at-risk constraints. Based on the price data in the PJM market, simulation results verify that our model is a decision-making tool in electricity markets, which can help market players comprehend the variants of bid price, expected cost and probability of successful bidding.
Autors: Hongming Yang;Sanhua Zhang;Jing Qiu;Duo Qiu;Mingyong Lai;ZhaoYang Dong;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2555 - 2565
Publisher: IEEE
 
» Cybersecurity and Rural Electric Power Systems: Considering Competing Requirements for Implementing a Protection Plan
Abstract:
Cybersecurity is a topic of increasing importance and interest to small utility operators like rural electric associations. Cyberattacks are a threat to our society's functioning, and cybersecurity is an urgent need in areas that include national security, business operations, and regulatory compliance. Several fundamental concepts can guide an operator when implementing a cybersecurity plan. Operators must consider the competing requirements of confidentiality, integrity, availability (CIA), and cost. They must also consider the potential of impact levels for an incident. While implementing a cybersecurity plan, operators will constantly identify adversaries, threats, vulnerabilities, consequences, and risks. They will implement physical, technical, and administrative controls to protect networks and other assets, detect attacks, respond to those attacks, and recover from any damage. The process will be continuous as operators respond to the changing environment.
Autors: Paul Kaster;Pankaj P.K. Sen;
Appeared in: IEEE Industry Applications Magazine
Publication date: Oct 2017, volume: 23, issue:5, pages: 14 - 20
Publisher: IEEE
 
» Cybersecurity in Power Systems
Abstract:
Did you know that cyberattackers have already created outages in Ukraine, not once but twice? On 23 December 2015, cyberintruders at three electric distribution companies in Ukraine opened breakers, creating a power outage that affected 225,000 people. Power was restored in approximately 6 h, as field personnel manually closed the breakers.
Autors: Michael F. Ahern;
Appeared in: IEEE Potentials
Publication date: Oct 2017, volume: 36, issue:5, pages: 8 - 12
Publisher: IEEE
 
» Daily Clearness Index Profiles Cluster Analysis for Photovoltaic System
Abstract:
Due to various weather perturbation effects, the stochastic nature of real-life solar irradiance has been a major issue for solar photovoltaic (PV) system planning and performance evaluation. This paper aims to discover clearness index (CI) patterns and to construct centroids for the daily CI profiles. This will be useful in being able to provide a standardized methodology for PV system design and analysis. Four years of solar irradiance data collected from Johannesburg (26.21 S, 28.05 E), South Africa are used for the case study. The variation in CI could be significant in different seasons. In this paper, cluster analysis with Gaussian mixture models (GMM), K-Means with Euclidean distance (ED), K-Means with Manhattan distance, Fuzzy C-Means (FCM) with ED, and FCM with dynamic time warping (FCM DTW) are performed for the four seasons. A case study based on sizing a stand-alone solar PV and storage system with anaerobic digestion biogas power plants is used to examine the usefulness of the clustering results. It concludes that FCM DTW and GMM can determine the correct PV farm rated capacity with an acceptable energy storage capacity, with 36 and 46 rather than 1457 solar irradiance profiles, respectively.
Autors: Chun Sing Lai;Youwei Jia;Malcolm D. McCulloch;Zhao Xu;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2322 - 2332
Publisher: IEEE
 
» Damping Dependence of Spin-Torque Effects in Thermally Assisted Magnetization Reversal
Abstract:
Thermal fluctuations of nanomagnets driven by spin-polarized currents are treated via the Landau–Lifshitz–Gilbert equation as generalized to include both the random thermal noise field and Slonczewski spin-transfer torque terms. The magnetization reversal time of such a nanomagnet is then evaluated for wide ranges of damping by using a method which generalizes the solution of the so-called Kramers turnover problem for mechanical Brownian particles, thereby bridging the very low damping and intermediate damping Kramers escape rates, to the analogous magnetic turnover problem. The reversal time is then evaluated for a nanomagnet with the free energy density given in the standard form of superimposed easy-plane and in-plane easy-axis anisotropies with the dc bias field along the easy axis.
Autors: Y. P. Kalmykov;D. Byrne;W. T. Coffey;W. J. Dowling;S. V. Titov;J. E. Wegrowe;
Appeared in: IEEE Transactions on Magnetics
Publication date: Oct 2017, volume: 53, issue:10, pages: 1 - 8
Publisher: IEEE
 
» Data Backup Optimization for Nonvolatile SRAM in Energy Harvesting Sensor Nodes
Abstract:
Nonvolatile static random access memory (nvSRAM) has been widely investigated as a promising on-chip memory architecture in energy harvesting sensor nodes, due to zero standby power, resilience to power failures, and fast read/write operations. However, conventional approaches back up all data from static random access memory into nonvolatile memory when power failures happen. It leads to significant energy overhead and peak inrush current, which has a negative impact on the system performance and circuit reliability. This paper proposes a holistic data backup optimization to mitigate these problems in nvSRAM, consisting of a partial backup algorithm and a run-time adaptive write policy. A statistic dead-block predictor is employed to achieve dead block identification with trivial hardware overhead. An adaptive policy is used to switch between write-back and write-through strategy to reduce the rollback induced by backup failures. Experimental results show that the proposed scheme improves the performance by 4.6% on average while the backup power consumption and the inrush current are reduced by 38.1% and 54% on average compared to the full backup scheme. What is more, the backup capacitor size for energy buffer can be reduced by 40% on average under the same performance constraint.
Autors: Yongpan Liu;Jinshan Yue;Hehe Li;Qinghang Zhao;Mengying Zhao;Chun Jason Xue;Guangyu Sun;Meng-Fan Chang;Huazhong Yang;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Oct 2017, volume: 36, issue:10, pages: 1660 - 1673
Publisher: IEEE
 
» Data Leakage Prevention for Secure Cross-Domain Information Exchange
Abstract:
Cross-domain information exchange is an increasingly important capability for conducting efficient and secure operations, both within coalitions and within single nations. A data guard is a common cross-domain sharing solution that inspects the security labels of exported data objects and validates that they are such that they can be released according to policy. While we see that guard solutions can be implemented with high assurance, we find that obtaining an equivalent level of assurance in the correctness of the security labels easily becomes a hard problem in practical scenarios. Thus, a weakness of the guard-based solution is that there is often limited assurance in the correctness of the security labels. To mitigate this, guards make use of content checkers such as dirty word lists as a means of detecting mislabeled data. To improve the overall security of such cross-domain solutions, we investigate more advanced content checkers based on the use of machine learning. Instead of relying on manually specified dirty word lists, we can build data-driven methods that automatically infer the words associated with classified content. However, care must be taken when constructing and deploying these methods as naive implementations are vulnerable to manipulation attacks. In order to provide a better context for performing classification, we monitor the incoming information flow and use the audit trail to construct controlled environments. The usefulness of this deployment scheme is demonstrated using a real collection of classified and unclassified documents.
Autors: Kyrre Wahl Kongsgard;Nils Agne Nordbotten;Federico Mancini;Raymond Haakseth;Paal E. Engelstad;
Appeared in: IEEE Communications Magazine
Publication date: Oct 2017, volume: 55, issue:10, pages: 37 - 43
Publisher: IEEE
 
» Data-Based Predictive Optimization for Byproduct Gas System in Steel Industry
Abstract:
In light of significant complexity of the byproduct gas system in steel industry (which limits an ability to establish its physics-based model), this paper proposes a data-based predictive optimization (DPO) method to carry out real-time adjusting for the gas system. Two stages of the method, namely, the prediction modeling and real-time optimization, are involved. At the prediction stage, the states of the optimized objectives, the consumption of the outsourcing natural gas and oil, the power generation, and the tank levels, are forecasted based on a proposed mixed Gaussian kernel-based prediction intervals (PIs) construction model. The Jacobian matrix of this model is represented by a kernel matrix through derivation, which greatly facilitates the subsequent calculation. At the second stage, a rolling optimization based on a mathematical programming technique involving continuous and integer decision-making variables is developed via the PIs. To demonstrate the performance of the DPO method, the practical data coming from the energy center of a steel plant are employed. The results show that the proposed DPO method can supply the human operators with effective solution for secure and economically justified optimization of the gas system.

Note to Practitioners—Given that the byproduct gas system in steel industry can hardly be described by a physics or mechanism-based model, its operation is widely realized by the experience-based manual measure at present, which exhibits a very low automation level. Since a large number of real-time energy data have been accumulated by the existing SCADA system implemented in most of steel plants, a novel data-driven real-time predictive optimization method is proposed in this study.

The proposed method aims at the short term energy optimization, thus the sample interval of the real-time data acquired from the SCADA system is set as 1 minute. The application system can provide the r- lling optimized solution via real-time predicting the running circumstances of the gas system. Therefore, it is required for the plant in advance to implement the SCADA system for the energy data acquisition, and the sampling interval should be less than or equal to 1 minute. Furthermore, it is necessary for the sample data to complete the preliminary processing such as data imputation if needed since there are usually a large number of possible missing data points existed in the SCADA system of the production practice. Because such preliminary processing for the sample data belongs to a class of generic methods, this study avoids the redundant technical introduction.

Autors: Jun Zhao;Chunyang Sheng;Wei Wang;Witold Pedrycz;Quanli Liu;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Oct 2017, volume: 14, issue:4, pages: 1761 - 1770
Publisher: IEEE
 
» Data-Driven Distributed Local Fault Detection for Large-Scale Processes Based on the GA-Regularized Canonical Correlation Analysis
Abstract:
Large-scale processes have become common, and fault detection for such processes is imperative. This work studies the data-driven distributed local fault detection problem for large-scale processes with interconnected subsystems and develops a genetic algorithm (GA)-regularized canonical correlation analysis (CCA)-based distributed local fault detection scheme. For each subsystem, the GA-regularized CCA is first performed with its all coupled systems, which aims to preserve the maximum correlation with the minimal communication cost. A CCA-based residual is then generated, and corresponding statistic is constructed to achieve optimal fault detection for the subsystem. The distributed fault detector performs local fault detection for each subsystem using its own measurements and the information provided by its coupled subsystems and therefore exhibits a superior monitoring performance. The regularized CCA-based distributed fault detection approach is tested on a numerical example and the Tennessee Eastman benchmark process. Monitoring results indicate the efficiency and feasibility of the proposed approach.
Autors: Qingchao Jiang;Steven X. Ding;Yang Wang;Xuefeng Yan;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 8148 - 8157
Publisher: IEEE
 
» DC and RF Performance of AlGaN/GaN/SiC MOSHEMTs With Deep Sub-Micron T-Gates and Atomic Layer Epitaxy MgCaO as Gate Dielectric
Abstract:
In this letter, we report on the dc and RF performance of AlGaN/GaN metal-oxide-semiconductor high-electron mobility transistors (MOSHEMTs) with various gate lengths () from 90 to 500 nm using atomic-layer-epitaxy single crystalline Mg0.25Ca0.75O as gate dielectric. The 90-nm T-gate MOSHEMT simultaneously demonstrates a ft/fmax of 113/160 GHz with high on/off ratio of . The on/off ratio increases to at nm by reducing short channel effects. The gate leakage current is around 10−11 A/mm at off-state and 10−5 A/mm at on-state. A 160 nm MOSHEMT also exhibits an output power density of 4.18 W/mm at GHz and V. MgCaO demonstrates to be a promising dielectric for GaN MOS technology in serving as the surface passivation layer and reducing the gate leakage current while maintaining high RF performances for high-power applications.
Autors: Hong Zhou;Xiabing Lou;Karynn Sutherlin;Jarren Summers;Sang Bok Kim;Kelson D. Chabak;Roy G. Gordon;Peide D. Ye;
Appeared in: IEEE Electron Device Letters
Publication date: Oct 2017, volume: 38, issue:10, pages: 1409 - 1412
Publisher: IEEE
 
» DC-Link Current and Torque Ripple Optimized Self-Sensing Control of Interior Permanent-Magnet Synchronous Machines for Hybrid and Electrical Vehicles
Abstract:
To minimize the ripple on the dc-link current and torque due to carrier signal injections, conventional saliency based self-sensing control schemes using voltage and current carrier signals for interior permanent magnet synchronous machines (IPMSMs) are optimized in this paper. Carrier signal oriented coordinates are introduced to model the high-frequency behavior of IPMSMs and are used for the analysis and signal processing of proposed methods. Moreover, stability issues are discussed in this paper. Experimental results on a commercial high voltage inverter for application in hybrid and electrical vehicles confirm the applicability of the proposed methods.
Autors: Lei Chen;Gunther Götting;Ingo Hahn;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4536 - 4546
Publisher: IEEE
 
» DCO-OFDM Signals With Derated Power for Visible Light Communications Using an Optimized Adaptive Network-Based Fuzzy Inference System
Abstract:
Direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) signals used in visible light communications suffer from high peak-to-average-power ratio (PAPR) or cubic metric (CM). It strongly degrades the performance due to the great back-off necessary to avoid the clipping effect in the light-emitting diode. Thus, PAPR and CM reduction techniques become crucial to improve the system performance. In this paper, an adaptive network-based fuzzy inference system (ANFIS) is used to obtain efficient DCO-OFDM signals with a low power envelope profile. First, signals specially designed for DCO-OFDM with very low CM, as the ones obtained from the raw cubic metric (RCM)–active constellation extension method, are used to train the fuzzy systems in time and frequency domains. Second, after the off-line training, the ANFIS can generate a real-valued signal in a one-shot way with 8.9 dB of RCM reduction from the original real-valued signal, which involves a gain in the input power back off larger than 2.8 dB, an illumination-to-communication conversion efficiency gain of more than 35% and considerable improvements in bit error rate.
Autors: Borja Genovés Guzmán;Víctor P. Gil Jiménez;
Appeared in: IEEE Transactions on Communications
Publication date: Oct 2017, volume: 65, issue:10, pages: 4371 - 4381
Publisher: IEEE
 
» Deadline-Aware Opportunistic Network Coding for Multi-Relay-Aided Single-Source Single-Destination Network
Abstract:
An opportunistic network coding (NC) scheme is proposed for the multi-relay-aided single-source single-destination network with transmission deadline. With the help of matrix analysis, the lower bound of decoding failure probability of the proposed scheme is given. Simulation results show that: 1) the proposed scheme outperforms NC based on direct recoding scheme and the lower bound is tight when the source-to-relay channel erasure probability is relatively small and 2) given fixed network parameters, the optimal number of systematic packets delivered within deadline could be determined by using the derived bound for maximizing the throughput.
Autors: Guojie Hu;Kui Xu;Youyun Xu;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2282 - 2285
Publisher: IEEE
 
» Decoding Local Field Potentials for Neural Interfaces
Abstract:
The stability and frequency content of local field potentials (LFPs) offer key advantages for long-term, low-power neural interfaces. However, interpreting LFPs may require new signal processing techniques which should be informed by a scientific understanding of how these recordings arise from the coordinated activity of underlying neuronal populations. We review current approaches to decoding LFPs for brain–machine interface (BMI) applications, and suggest several directions for future research. To facilitate an improved understanding of the relationship between LFPs and spike activity, we share a dataset of multielectrode recordings from monkey motor cortex, and describe two unsupervised analysis methods we have explored for extracting a low-dimensional feature space that is amenable to biomimetic decoding and biofeedback training.
Autors: Andrew Jackson;Thomas M. Hall;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Oct 2017, volume: 25, issue:10, pages: 1705 - 1714
Publisher: IEEE
 
» Decomposing Joint Distortion for Adaptive Steganography
Abstract:
Recent advances on adaptive steganography imply that the security of steganography can be improved by exploiting the mutual impact of modifications between adjacent cover elements, such as pixels of images, which is called a nonadditive distortion model. In this paper, we propose a framework for nonadditive distortion steganography by defining joint distortion on pixel blocks. To reduce the complexity for minimizing joint distortion, we design a coding method to decompose the joint distortion (abbreviated to DeJoin) into distortion on individual pixels; thus, the message can be efficiently embedded with syndrome-trellis codes. We prove that DeJoin can approach the lower bound of joint distortion. As an example, we define joint distortion according to the principle of synchronizing modification direction and then design steganographic algorithms with DeJoin. The experimental results show that the proposed method outperforms previous nonadditive distortion steganography when resisting the state-of-the-art steganalysis.
Autors: Weiming Zhang;Zhuo Zhang;Lili Zhang;Hanyi Li;Nenghai Yu;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Oct 2017, volume: 27, issue:10, pages: 2274 - 2280
Publisher: IEEE
 
» Decoupled Uplink-Downlink User Association in Multi-Tier Full-Duplex Cellular Networks: A Two-Sided Matching Game
Abstract:
In multi-tier cellular networks, user performance in both the downlink (DL) and uplink (UL) transmissions depend on the transmit powers of the base stations (BSs) in different network tiers, users' distances, and non-uniform traffic loads of different BSs. In such a network, decoupled UL-DL user association (DUDe), which allows users to associate with different BSs for UL and DL transmissions, can be used to optimize network performance. Again, in-band full-duplex (FD) communication is considered as a promising technique to improve the spectral efficiency of future multi-tier fifth generation (5G) cellular networks. Nonetheless, due to UL-to-DL and DL-to-UL interferences arising due to FD communications, the performance gains of DUDe in FD multi-tier networks are inconspicuous. To this end, this paper develops a comprehensive framework to analyze the usefulness of DUDe in a full-duplex multi-tier cellular network. We first formulate a joint UL and DL user association problem (with the provisioning for decoupled association) that maximizes the sum-rate for UL and DL transmission of all users. Since the formulated problem is a mixed-integer non-linear programming (MINLP) problem, we invoke approximations and binary constraint relaxations to convert the problem into a Geometric Programming (GP) problem that is solved by using Karush-Kuhn-Tucker (KKT) optimality conditions. Given the centralized nature and complexity of the GP problem, we formulate a distributed two-sided iterative matching game and obtain a solution of the game. In this game, the users and BSs rank one another using preference metrics that are subject to the externalities (i.e., dynamic interference conditions). The solution of the game is guaranteed to converge and provides Pareto-optimal stable associations. Finally, we derive efficient light-weight versions of the iterative matching solution, i.e., non-iterative matching and sequential UL-DL matching algorithms. The performances of the solutions a- e evaluated in terms of aggregate UL and DL rates of all users, the number of unassociated users, and the number of coupled/decoupled associations. Simulation results demonstrate the efficacy of the proposed algorithms over the centralized GP solution as well as traditional coupled and decoupled user association schemes.
Autors: Silvia Sekander;Hina Tabassum;Ekram Hossain;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Oct 2017, volume: 16, issue:10, pages: 2778 - 2791
Publisher: IEEE
 
» Decoy-State Reference-Frame-Independent Measurement-Device-Independent Quantum Key Distribution With Biased Bases
Abstract:
Reference-frame-independent measurement-device-independent quantum key distribution (RFI-MDI-QKD) can eschew the alignment of reference frames in practical systems and defeat all potential detector side channel attacks. Here, we propose the decoy-state RFI-MDI-QKD protocol with biased bases. In this protocol, two legitimate parties Alice and Bob prepare signal states in , , and bases and decoy states in and bases, which avoids the futility in basis for decoy states and simplifies the operation of existing systems. Considering the security against coherent attacks with statistical fluctuations, we investigate the performance of the decoy-state RFI-MDI-QKD protocol with biased bases in the environment of unknown and slowly drifting reference frames and make comparisons with the original decoy-state RFI-MDI-QKD protocol under the same conditions. Simulation results show that the proposed protocol can increase the achievable secret key rate and transmission distance obviously compared with the original protocol, which is very promising in real-life QKD systems.
Autors: Chun-Mei Zhang;Jian-Rong Zhu;Qin Wang;
Appeared in: Journal of Lightwave Technology
Publication date: Oct 2017, volume: 35, issue:20, pages: 4574 - 4578
Publisher: IEEE
 
» Deep Conditional Random Field Approach to Transmembrane Topology Prediction and Application to GPCR Three-Dimensional Structure Modeling
Abstract:
Transmembrane proteins play important roles in cellular energy production, signal transmission, and metabolism. Many shallow machine learning methods have been applied to transmembrane topology prediction, but the performance was limited by the large size of membrane proteins and the complex biological evolution information behind the sequence. In this paper, we proposed a novel deep approach based on conditional random fields named as dCRF-TM for predicting the topology of transmembrane proteins. Conditional random fields take into account more complicated interrelation between residue labels in full-length sequence than HMM and SVM-based methods. Three widely-used datasets were employed in the benchmark. DCRF-TM had the accuracy 95 percent over helix location prediction and the accuracy 78 percent over helix number prediction. DCRF-TM demonstrated a more robust performance on large size proteins (>350 residues) against 11 state-of-the-art predictors. Further dCRF-TM was applied to ab initio modeling three-dimensional structures of seven-transmembrane receptors, also known as G protein-coupled receptors. The predictions on 24 solved G protein-coupled receptors and unsolved vasopressin V2 receptor illustrated that dCRF-TM helped abGPCR-I-TASSER to improve TM-score 34.3 percent rather than using the random transmembrane definition. Two out of five predicted models caught the experimental verified disulfide bonds in vasopressin V2 receptor.
Autors: Hongjie Wu;Kun Wang;Liyao Lu;Yu Xue;Qiang Lyu;Min Jiang;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Oct 2017, volume: 14, issue:5, pages: 1106 - 1114
Publisher: IEEE
 
» Deep Fully Convolutional Network-Based Spatial Distribution Prediction for Hyperspectral Image Classification
Abstract:
Most of the existing spatial-spectral-based hyperspectral image classification (HSIC) methods mainly extract the spatial-spectral information by combining the pixels in a small neighborhood or aggregating the statistical and morphological characteristics. However, those strategies can only generate shallow appearance features with limited representative ability for classes with high interclass similarity and spatial diversity and therefore reduce the classification accuracy. To this end, we present a novel HSIC framework, named deep multiscale spatial-spectral feature extraction algorithm, which focuses on learning effective discriminant features for HSIC. First, the well pretrained deep fully convolutional network based on VGG-verydeep-16 is introduced to excavate the potential deep multiscale spatial structural information in the proposed hyperspectral imaging framework. Then, the spectral feature and the deep multiscale spatial feature are fused by adopting the weighted fusion method. Finally, the fusion feature is put into a generic classifier to obtain the pixelwise classification. Compared with the existing spectral-spatial-based classification techniques, the proposed method provides the state-of-the-art performance and is much more effective, especially for images with high nonlinear distribution and spatial diversity.
Autors: Licheng Jiao;Miaomiao Liang;Huan Chen;Shuyuan Yang;Hongying Liu;Xianghai Cao;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5585 - 5599
Publisher: IEEE
 
» Deep Learning of Graphs with Ngram Convolutional Neural Networks
Abstract:
Convolutional Neural Network (CNN) has gained attractions in image analytics and speech recognition in recent years. However, employing CNN for classification of graphs remains to be challenging. This paper presents the Ngram graph-block based convolutional neural network model for classification of graphs. Our Ngram deep learning framework consists of three novel components. First, we introduce the concept of -gram block to transform each raw graph object into a sequence of -gram blocks connected through overlapping regions. Second, we introduce a diagonal convolution step to extract local patterns and connectivity features hidden in these -gram blocks by performing -gram normalization. Finally, we develop deeper global patterns based on the local patterns and the ways that they respond to overlapping regions by building a -gram deep learning model using convolutional neural network. We evaluate the effectiveness of our approach by comparing it with the existing state of art methods using five real graph repositories from bioinformatics and social networks domains. Our results show that the Ngram approach outperforms existing methods with high accuracy and comparable performance.
Autors: Zhiling Luo;Ling Liu;Jianwei Yin;Ying Li;Zhaohui Wu;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Oct 2017, volume: 29, issue:10, pages: 2125 - 2139
Publisher: IEEE
 
» Deep TSK Fuzzy Classifier With Stacked Generalization and Triplely Concise Interpretability Guarantee for Large Data
Abstract:
Although Takagi–Sugeno–Kang (TSK) fuzzy classifier has been applied to a wide range of practical scenarios, how to enhance its classification accuracy and interpretability simultaneously is still a challenging task. In this paper, based on the powerful stacked generalization principle, a deep TSK fuzzy classifier (D-TSK-FC) is proposed to achieve the enhanced classification accuracy and triplely concise interpretability for fuzzy rules. D-TSK-FC consists of base-building units. Just like the existing popular deep learning, D-TSK-FC can be built in a layer-by-layer way. In terms of the stacked generalization principle, the training set plus random shifts obtained from random projections of prediction results of current base-building unit are presented as the input of the next base-building unit. The hidden layer in each base-building unit of D-TSK-FC is represented by triplely concise interpretable fuzzy rules in the sense of randomly selected features with the fixed five fuzzy partitions, random rule combinations, and the same input space kept in every base-building unit of D-TSK-FC. The output layer of each base-building unit can be learnt quickly by least learning machine (LLM). Besides, benefiting from LLM, D-TSK-FC's deep learning can be well scaled up for large datasets. Our extensive experimental results witness the power of the proposed deep TSK fuzzy classifier.
Autors: Ta Zhou;Fu-Lai Chung;Shitong Wang;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1207 - 1221
Publisher: IEEE
 
» DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features
Abstract:
Accurate ground-based cloud image categorization is a critical but challenging task that has not been well addressed. One of the essential issues that affect the performance is to extract the representative visual features. Nearly all of the existing methods rely on the hand-crafted descriptors (e.g., local binary patterns, CENsus TRsansform hISTogram, and scale-invariant feature transform). Their limited discriminative power indeed leads to the unsatisfactory performance. To alleviate this, we propose “DeepCloud” as a novel cloud image feature extraction approach by resorting to the deep convolutional visual features. In the recent years, the deep convolutional neural network (CNN) has achieved the promising results in lots of computer vision and image understanding fields. Nevertheless, it has not been applied to cloud image classification yet. Thus, we actually pay the first effort to fill this blank. Since cloud image classification can be attributed to a multi-instance learning problem, simply employing the convolutional features within CNN cannot achieve the promising result. To address this, Fisher vector encoding is applied to executing the spatial feature aggregation and high-dimensional feature mapping on the raw deep convolutional features. Moreover, the hierarchical convolutional layers are used simultaneously to capture the fine textural characteristics and high-level semantic information in the unified manner. To further leverage the performance, a cloud pattern mining and selection method are also proposed. It targets at finding the discriminative local patterns to better distinguish the different kinds of clouds. The experiments on a challenging ground-based cloud image data set demonstrate the superiority of the proposition over the state-of-the-art methods.
Autors: Liang Ye;Zhiguo Cao;Yang Xiao;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5729 - 5740
Publisher: IEEE
 
» Defense Mechanisms against Data Injection Attacks in Smart Grid Networks
Abstract:
In the smart grid, bidirectional information exchange among customers, operators, and control devices significantly improves the efficiency of energy supplying and consumption. However, integration of intelligence and cyber systems into a power grid can lead to serious cyber security challenges and makes the overall system more vulnerable to cyber attacks. To address this challenging issue, this article presents defense mechanisms to either protect the system from attackers in advance or detect the existence of data injection attacks to improve the smart grid security. Focusing on signal processing techniques, this article introduces an adaptive scheme on detection of injected bad data at the control center. This scheme takes the power measurements of two sequential data collection slots into account, and detects data injection attacks by monitoring the measurement variations and state changes between the two time slots. The proposed scheme has the capability of adaptively detecting attacks including both non-stealthy attacks and stealthy attacks. Stealthy attacks are proved impossible to detect using conventional residual- based methods, and can cause more dangerous effects on power systems than non-stealthy attacks. It is demonstrated that the proposed scheme can also be used for attack classification to help system operators prioritize their actions to better protect their systems, and is therefore very valuable in practical smart grid systems.
Autors: Jing Jiang;Yi Qian;
Appeared in: IEEE Communications Magazine
Publication date: Oct 2017, volume: 55, issue:10, pages: 76 - 82
Publisher: IEEE
 
» Degradation Effects on Energy Absorption Capability and Time to Failure of Low Voltage Metal Oxide Varistors
Abstract:
Reliability of a surge protection device depends on the health of its protecting elements. Metal oxide Varistors (MOVs) are widely used in electric appliances and power distribution systems. They are known to degrade over time when they experience high-surges and long-duration transients. In this paper, more than 120 MOVs are subjected to nominal 8/20 μs unipolar and bipolar surges of 40 kA in different groups, up to different levels of degradations. Then, they are subjected to energy absorption capability (EAC) tests with ac currents, in a UL-certified lab. Their EAC, peak currents, and time to failures (TtFs) are measured and analyzed. Results show that although degradation due to surges might decrease EAC and TtF of the MOVs in a given current, the average EAC and TtF of degraded MOVs are increased for a certain applied over-voltage. This paper explains the reasons and proposes a model for a degraded MOV that shows a realistic behavior in a transient overvoltage (TOV) condition.
Autors: Dawood Talebi Khanmiri;Roy Ball;Brad Lehman;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Oct 2017, volume: 32, issue:5, pages: 2272 - 2280
Publisher: IEEE
 
» Degrees of Freedom of Full-Duplex Cellular Networks: Effect of Self-Interference
Abstract:
It was recently shown that full-duplex (FD) operation at a base station (BS) can provide up to twice as many degrees of freedom (DoF) as a conventional half-duplex (HD) cellular network in the absence of self-interference. In practice, however, self-interference in an FD BS may not be eliminated completely due to imperfect cancellation, and it is not yet known whether FD operation can improve the sum DoF of cellular networks in the presence of residual self-interference. In this paper, we provide a complete characterization of the sum DoF in an FD-BS cellular network with self-interference, where the rank of the self-interference matrix is arbitrary. Specifically, we propose a self-interference cancellation scheme that maximizes the sum DoF, and we prove its optimality by deriving the matching upper bound. Our results show that even in the presence of residual self-interference, an FD-BS network can still outperform a conventional HD-BS network, and furthermore, the sum DoF coincides with that of an FD-BS network with no self-interference under certain conditions. We also derive an achievable sum rate under ergodic phase fading, showing that not only a sum-DoF gain but also a sum-rate gain can be obtained over the entire signal-to-noise ratio range even if residual self-interference exists.
Autors: Sung Ho Chae;Kisong Lee;
Appeared in: IEEE Transactions on Communications
Publication date: Oct 2017, volume: 65, issue:10, pages: 4507 - 4518
Publisher: IEEE
 
» Delay Properties of Energy Efficient Ethernet Networks
Abstract:
Networking operational costs and environmental concerns have lately driven the quest for energy efficient equipment. In wired networks, energy efficient Ethernet (EEE) interfaces can greatly reduce power demands when compared with regular Ethernet interfaces. Their power saving capabilities have been studied and modeled in many research articles in the last few years, together with their effects on traffic delay. However, to this date, all articles have considered them in isolation instead of as part of a network of EEE interfaces. In this letter, we develop a model for the traffic delay on a network of EEE interfaces. We prove that, whatever the network topology, the per interface delay increment due to the power savings capabilities is bounded and, in most scenarios, negligible. This confirms that EEE interfaces can be used in all but the most delay constrained scenarios to save considerable amounts of power.
Autors: Miguel Rodríguez-Pérez;Sergio Herrería-Alonso;Manuel Fernández-Veiga;Cándido López-García;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2194 - 2197
Publisher: IEEE
 
» Delay Robustness of an $\mathcal {L}_1$ Adaptive Controller for a Class of Systems With Unknown Matched Nonlinearities
Abstract:
This paper studies the delay robustness of an adaptive controller designed for systems with unknown matched nonlinearities and unknown input-gain matrices. The analysis establishes rigorously the existence of a positive lower bound for the closed-loop system's time-delay margin (TDM), provided that a filter bandwidth and an adaptive gain are chosen sufficiently large. In this case, if the input delay is below a critical value, then the state and control input of the control system follow those of a nonadaptive, robust reference system closely. The analysis also suggests a way to estimate this lower bound for the delay robustness using Padé approximants. Results from forward simulation are consistent with the Padé estimate and with an explicit upper bound on the TDM which decays to 0 as the filter bandwidth grows without bound.
Autors: Kim-Doang Nguyen;Yang Li;Harry Dankowicz;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5485 - 5491
Publisher: IEEE
 
» Delivering Real-Time Information Services on Public Transit: A Framework
Abstract:
Public transit is described by a wide range of data, which include sensor data, open data, and social network data. Data come in large real-time streams, and are heterogeneous. How to integrate such data in real time? We propose MOBility ANAlyzer (MOBANA), a distributed stream-based framework. MOBANA deals with the integration of heterogeneous information, processing efficiency, and redundancy reduction. As far as integration is concerned, MOBANA integrates data at different layers, and converts them into exchangeable data formats. Specifically, to integrate feed information, MOBANA uses an improved incremental text classifier, based on Kullback Leibler distance. As far as efficiency is concerned, MOBANA is implemented by distributed stream processing engine and distributed messaging system, which enable scalable, efficient, and reliable real-time processing. Specifically, within the transport domain, MOBANA identifies the real-time position of vehicles by an as-needed adjustment of planned position against the real-time position, thus dropping network load. As far as redundancy is concerned, MOBANA filters tweets through a three-fold similarity analysis, which encompasses geo-location, text, and image. In addition, MOBANA is a complete framework, which has been tested as a pilot with real data in the city of Pavia, Italy.
Autors: Tianyi Ma;Gianmario Motta;Kaixu Liu;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Oct 2017, volume: 18, issue:10, pages: 2642 - 2656
Publisher: IEEE
 
» DEM Retrieval From Airborne LiDAR Point Clouds in Mountain Areas via Deep Neural Networks
Abstract:
Airborne light detection and ranging (LiDAR) remote sensing enables accurate estimation and monitoring of terrain and vegetation, and digital surface model (DSM) and digital elevation model (DEM) are vital analytical tools to achieve this estimation and monitoring. Among them, DSM can be directly acquired from airborne LiDAR point clouds; nevertheless, for the production of DEM, point clouds representing a surface of ground objects should be accurately filtered out at first. In some mountain forest areas, due to the limited penetration of airborne LiDAR, ground points sustain a serious lack, which results in the difficulty in producing accurate DEMs. To reduce the intricacy and subjectivity caused by the manual supplement to ground points, this letter proposes a new DEM retrieval method from airborne LiDAR point clouds in mountain areas based on deep neural networks (DNNs). With a DNN model trained by accurate DEMs and DSMs, DEM retrieval becomes much easier by inputting their DSM into this model for prediction. Experiments on Fujian and Hainan mountain data sets demonstrate the effectiveness of this supervised method.
Autors: Yimin Luo;Hongchao Ma;Liguo Zhou;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Oct 2017, volume: 14, issue:10, pages: 1770 - 1774
Publisher: IEEE
 

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