Electrical and Electronics Engineering publications abstract of: 11-2017 sorted by title, page: 16

» Resilient Sampled-Data Control for Markovian Jump Systems With an Adaptive Fault-Tolerant Mechanism
Abstract:
This brief investigates the problem of passivity-based resilient sampled-data control for Markovian jump systems subject to actuator faults via an adaptive fault-tolerant mechanism. By constructing a proper Lyapunov function, a set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which ensures that the closed-loop system is stochastically passive. In order to reflect the imprecision in controller, the additive gain variations is considered. Then, the resilient sampled-data control parameters can be determined by solving the obtained LMIs. Finally, an illustrative example is presented to show the validity and applicability of the proposed design technique.
Autors: R. Sakthivel;Hamid Reza Karimi;Maya Joby;Srimanta Santra;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Nov 2017, volume: 64, issue:11, pages: 1312 - 1316
Publisher: IEEE
 
» Resistive Switching Characteristics of Al2O3 Film for Transparent Nonvolatile Memory
Abstract:
Transparent resistive memory requires a transparent electrode and thin storage layer. In this letter, we highlight the importance of a dielectric and metal multilayer electrode for transparency with good flexible characteristics also. In particular, we utilized the stable properties of resistive memory obtained from an inserted thin layer near the oxide layer. The optimized thickness of the whole structure was calculated by MATLAB simulation, which followed the model of the optical transfer matrix theory. The transparent resistive memory has stable resistive switching behaviors.
Autors: Myeongcheol Kim;Kyung Cheol Choi;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Nov 2017, volume: 16, issue:6, pages: 1129 - 1131
Publisher: IEEE
 
» Resistive Switching Characteristics of Flexible TiO2 Thin Film Fabricated by Deep Ultraviolet Photochemical Solution Method
Abstract:
A novel ultraviolet photochemical method was used to prepare TiO2 resistive-switching films. Amorphous TiO2 films were formed on flexible indium-tin oxide (ITO) coated polyethylene terephthalate (PET) substrates by deep ultraviolet irradiation at 150 °C. A Pt/TiO2/ITO/PET device was then fabricated to investigate bipolar resistive switching of the films for potential application in non-volatile memories. The ratio of on-state to off-state currents was measured, and a good value of 1000 was obtained. The retention and switch-cycling characteristics of the device were investigated for different bending radii. The resistive switching behavior of the flexible device remained stable after 600 cycles of electrical switching and 1000 cycles of bending.
Autors: Yuanqing Chen;Lingwei Li;Xiaoru Yin;Aditya Yerramilli;Yuxia Shen;Yang Song;Weibai Bian;Na Li;Zhao Zhao;Wenwen Qu;N. David Theodore;T. L. Alford;
Appeared in: IEEE Electron Device Letters
Publication date: Nov 2017, volume: 38, issue:11, pages: 1528 - 1531
Publisher: IEEE
 
» Resource Allocation for Energy Harvesting-Powered D2D Communication Underlaying Cellular Networks
Abstract:
Energy harvesting (EH)-powered wireless communications have attracted great attention from both industry and academia. However, the available energy, which relies on EH efficiency, will become another nonnegligible factor when we do research on EH-powered wireless communications. This paper studies the resource allocation problems in terms of spectrum and energy under EH-powered Device-to-Device (D2D) Communication underlaying Cellular Network (EH-DCCN). In this network, D2D pairs powered by EH are allowed to reuse the spectrum resources occupied by Cellular Users (CUs). To investigate the resource allocation problems, a sum-rate maximization problem of the whole cellular network with consideration of Quality of Service (QoS) and available energy constraints is formulated. The maximization problem is a nonconcave mixed-integer nonlinear programming (MINLP) problem, which has been proved to be NP-hard. To solve the problem, we first relax it with a concave lower bound on the original problem and then obtain the theoretical performance of the lower bound by Outer Approximation Algorithm. Moreover, a heuristic algorithm, an Energy-aware Space Matching approach (ESM), is proposed to acquire a suboptimal solution with low computational complexity. Finally, numerical simulation results indicate our considered resource allocation strategy is more effective than the strategy only based on channel state information under the EH-DCCN. Moreover, the performance in aspects of the sum rate and the matching probability shows that the ESM can approximately obtain the theoretical performance of the lower bound on the original problem under the scenarios with higher ratio of CU and EH-powered D2D numbers.
Autors: Ying Luo;Peilin Hong;Ruolin Su;Kaiping Xue;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Nov 2017, volume: 66, issue:11, pages: 10486 - 10498
Publisher: IEEE
 
» Resource assignment strategy in optical networks integrated with quantum key distribution
Abstract:
Data transmission with optical fiber is vulnerable to eavesdropping. Moreover, conventional key distribution technology suffers from increasing computational power and upgraded attack algorithms. To address these issues, quantum key distribution (QKD), a quantum technology that secures secret information (such as a cryptographic key) exchange between two parties, can be used to guarantee secure data transmission. Integrating QKD into existing wavelength division multiplexing optical networks has been verified through a series of experiments, which contribute to ensuring network security and saving fiber resources. This paper addresses the resource assignment problem in QKD-enabled optical networks. First, a QKD-enabled optical network architecture is introduced. A small fraction of wavelength channels are segmented into multiple time slots with optical time division multiplexing technology to construct quantum key channels (QKChs) and measuring-basis channels, and then the remaining wavelengths can construct traditional data channels. Second, a static routing, wavelength, and time-slot assignment (RWTA) strategy is proposed and verified by the integer linear programming formulation and a heuristic algorithm. In the RWTA, QKChs are assigned for service requests according to the security levels specified by relevant key-updating periods. Thus, the secret keys for data encryption can update periodically to enhance security. Simulation results indicate that there is a trade-off between security (i.e., security levels and security-level types) and resource utilization.
Autors: Yuan Cao;Yongli Zhao;Xiaosong Yu;Yu Wu;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Nov 2017, volume: 9, issue:11, pages: 995 - 1004
Publisher: IEEE
 
» Response to Comments on “Microstrip T-Junction Power Divider With Exponentially Tapered Transmission Lines”
Abstract:
The authors recognize that the equation for the cutoff wavelength in [1] is incorrect. It is unfortunate as it was directly used in the derivations in [2]. However, the authors would like to emphasize that by using the correct equation for , the rest of the analysis in [2] is valid for the magnitude of the S-parameters, as was demonstrated in the comment by Sinha and Chatterjee [3]. In fact, this correction greatly improves the agreement between the theoretical, simulated, and measured responses. Using the corrected expression for , updated results for Prototype 2 are shown in Fig. 1.
Autors: C. Justin R. Smith;Hjalti H. Sigmarsson;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Nov 2017, volume: 27, issue:11, pages: 1039 - 1039
Publisher: IEEE
 
» Reusability of the Output of Map-Matching Algorithms Across Space and Time Through Machine Learning
Abstract:
A map-matching algorithm outputs a vector per GPS point, projecting the moving object on one of the segments of the transportation network. Although developing more sophisticated map-matching algorithms for vehicle and pedestrian navigation systems have been the focus of research in this field, reusability of the historical information already provided by map-matching algorithms has not been addressed yet. In other words, although researchers have been attempting to improve the accuracy of the aforementioned vector to correctly project GPS points on the transportation network, no research has exploited the spatial-temporal pattern in the arrangement of these projection vectors. This pattern, if properly detected, can be used as a rough surrogate for map-matching algorithms, in addition to other applications that require better positional accuracy for moving objects in smart cities. This paper detects and validates the spatial-temporal pattern in projection vectors produced by map-matching algorithms via machine learning. Projection vectors showed a strong spatial-temporal pattern in Chicago, IL, USA, which was captured best via a local nonlinear regressor, K-nearest neighbors, and helped double the positional accuracy of unseen GPS points. While a global nonlinear regressor, multilayer Perceptron was able to slightly improve the positional accuracy of GPS points, the linear least squares had an exacerbating effect on the positional accuracy.
Autors: Mahdi Hashemi;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 3017 - 3026
Publisher: IEEE
 
» Reverse Backprojection Algorithm for the Accurate Generation of SAR Raw Data of Natural Scenes
Abstract:
Future synthetic aperture radar (SAR) mission concepts often rely on locally nonlinear (e.g., high orbits and bistatic) surveys or acquisition schemes. The simulation of the raw data of natural scenes as acquired by future systems appears as one powerful tool in order to understand the particularities of these systems and assess the impact of system and propagation errors on their performance. We put forward, in this letter, a new formulation of the reverse backprojection algorithm for the accurate simulation of raw data of natural surfaces. In particular, the algorithm is perfectly suited to accommodate any kind (1-D/2-D) of temporal and spatial variation, e.g., in observation geometry, acquisition strategy, or atmospheric propagation. The algorithm is analyzed with respect to its SAR image formation sibling, and tested under different simulation scenarios. We expect the reverse backprojection algorithm to play a relevant role in the simulation of future geosynchronous and multistatic SAR missions.
Autors: Dexin Li;Marc Rodriguez-Cassola;Pau Prats-Iraola;Manqing Wu;Alberto Moreira;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Nov 2017, volume: 14, issue:11, pages: 2072 - 2076
Publisher: IEEE
 
» Reversible Permeabilization of Cancer Cells by High Sub-Microsecond Magnetic Field
Abstract:
Exposure of cells to pulsed electric fields (PEFs) induces a phenomenon known as electroporation, which leads to increase of membrane permeability. Electroporation is applied in biotechnology, food processing, and medicine, including cancer treatment. Recently, a contactless method based on pulsed magnetic fields (PMFs) for the permeabilization of biological cells has been proposed; however, the permeabilization mechanism of the PMF method is still hypothetical. In this paper, we have shown that it is possible to reversibly permeabilize Sp2/0 myeloma cells by sub-microsecond (450 ns) PMF in the range of 0–3.3 T. The PMF methodology was also combined with PEF treatment to evaluate additive effects. The 1.35 kV/cm (PEF) and 3.3 T, 50 pulses, 0.25 Hz (PMF) protocols were applied. The cells were treated in the presence of fluorescence dye YO-PRO-1 and influx into the cells was evaluated by cytometry. Cell viability after the treatment was evaluated by CellEvent Caspase-3/7 assays. A significant (P < 0.05) additive effect of the two pulsed power methodologies was detected, resulting in up to 12% increase of membrane permeabilization. The PMF method is an emerging technique and the results of the study can be used for the development of new effective protocols, while the determined additive effects with PEF are promising in the field of electrochemotherapy.
Autors: Vitalij Novickij;Irutė Girkontaitė;Auksė Zinkevičienė;Jurgita Švedienė;Eglė Lastauskienė;Algimantas Paškevičius;Svetlana Markovskaja;Jurij Novickij;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 4
Publisher: IEEE
 
» Revision of Clausius–Clapeyron Relation for the First-Order Phase Transition in Ni–Mn–In Heusler Alloys
Abstract:
The derivation is presented of the Clausius–Clapeyron relation (CCR) in the second order of expansion of free energy potential on the change of temperature and magnetic field on the example of Ni–Mn–In Heusler alloys with the first-order metamagnetostructural phase transition (FOMMSPT), which can be treated as thermoelastic structural transition: austenite—martensite merging with metamagnetic transition: ferromagnet–antiferromagnet. It is shown that the second-order CCR describes satisfactory the nonlinear shift in the characteristic temperatures of the FOMMSPT in magnetic fields up to 25 T. It qualitatively and quantitatively explains the observed nonlinear dependence of the characteristic temperatures and the hysteresis of FOMMSPT including its elimination in some compositions of the Ni–Mn–In Heusler alloys under sufficiently high magnetic field.
Autors: A. V. Mashirov;A. P. Kamantsev;A. V. Koshelev;E. A. Ovchenkov;E. T. Dilmieva;A. S. Los;A. M. Aliev;V. V. Koledov;V. G. Shavrov;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 4
Publisher: IEEE
 
» Revisiting and Optimizing the Design of the Timer-Based Distributed Selection Scheme for Tackling Imperfect Power Control
Abstract:
Opportunistic selection improves the performance of a multi-node wireless system by exploiting multi-user or spatial diversity. In it, the nodes are sorted in the descending order of their metrics, which captures the utility of a node to the system if selected, and the best node with the highest metric is selected. We analyze the effect of imperfect power control on the conventional timer with power control scheme, which selects the best node in a distributed manner, and quantify the extent by which it reduces the probability of selecting the best node and increases the probability of selecting a non-best node. We then redesign it to ameliorate the impact of imperfect power control. Our systematic approach eschews several ad hoc assumptions implicit in the design of the conventional timer scheme, and jointly optimizes its various parameters to maximize the probability of selecting the best node in the presence of imperfect power control. We present several structural insights, including asymptotic ones, about the optimal scheme, which also enable it to be determined with much lower computational complexity. Our benchmarking results show that it is scalable and outperforms the conventional schemes.
Autors: Vikas Kumar Dewangan;Neelesh B. Mehta;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Nov 2017, volume: 16, issue:11, pages: 7646 - 7657
Publisher: IEEE
 
» Riemannian Alternative Matrix Completion for Image-Based Flame Recognition
Abstract:
The flame image has important significance in combustion state recognition and judgment, which can be used effectively for control of energy consumption and exhaust emissions. Due to the harsh industrial environments, flame images are usually corrupted by transmission errors or coding issues, which makes the combustion state analysis very challenging. This paper proposes a novel flame combustion state analysis framework, which provides new insight into two crucial issues: corrupted flame image recovery and combustion state recognition. First, we propose Riemannian alternative optimization (RAO) with fast convergence and the global optimization ability to recover the corrupted flame image. More specifically, RAO constructs a low-rank factorization model and exploits the geometric nature of the flame image to perform the optimization on Riemannian manifolds. Second, we use Fisher discriminant analysis to exploit discriminative features of the recovered flame image and provide well-separated classes of the combustion state for recognition. The experiments show that the proposed framework recovers the corrupted flame image efficiently and achieves satisfying performance of combustion state recognition.
Autors: Zhichao Wang;Min Liu;Mingyu Dong;Lian Wu;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Nov 2017, volume: 27, issue:11, pages: 2490 - 2503
Publisher: IEEE
 
» Risk-Limiting Unit Commitment in Smart Grid With Intelligent Periphery
Abstract:
This paper proposes the risk-limiting unit commitment (RLUC) as the operational method to address the uncertainties in the smart grid with intelligent periphery (GRIP). Three key requirements are identified for the RLUC in GRIP. The first one requires the RLUC to be modeled as a multistage multiperiod unit commitment problem considering power trades, operational constraints, and operational risks. The second one requires the RLUC considering the conditional prediction to achieve a globally optimal solution. It is addressed by using conditional probability in a scenario-based form. The last one requires the risk index in the RLUC to be both valid and computationally friendly, and it is tackled by the utilization of a coherent risk index and the mathematical proof of a risk chain theorem. Finally, the comprehensive RLUC in GRIP satisfying all the three requirements is solved by an equivalent transformation into a mixed integer piecewise linear programming problem. Case studies on a nine-bus system, a realistic provincial power system, and a regional power grid in China demonstrate the advantages of the proposed RLUC in GRIP.
Autors: Chaoyi Peng;Yunhe Hou;Nanpeng Yu;Weisheng Wang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Nov 2017, volume: 32, issue:6, pages: 4696 - 4707
Publisher: IEEE
 
» Road Recognition From Remote Sensing Imagery Using Incremental Learning
Abstract:
Roads, as important artificial objects, are the main body of modern traffic system, providing many conveniences for human civilization. With the development of Intelligent Transportation Systems (ITS), the road structure is changing frequently. Road recognition is to identify the road type from remote sensing imagery, and road types depend largely on the characteristics of roads. Thus, how to extract road features and further making road classification efficient have become a popular and challenging research topic. In this paper, we propose a road recognition method for remote sensing imagery using incremental learning. In principle, our method includes the following steps: 1) the non-road remote sensing imagery is first filtered by using support vector machine; 2) the road network is obtained from the road remote sensing imagery by computing multiple saliency features; 3) the road features are extracted from road network and background environment; and 4) the roads are recognized as three road types according to the classification results of incremental learning algorithm. The experimental results show that our method has higher road recognition rate as well as less recognition time than the other popular algorithms.
Autors: Jing Zhang;Lu Chen;Chao Wang;Li Zhuo;Qi Tian;Xi Liang;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 2993 - 3005
Publisher: IEEE
 
» Robust $H_{infty }$ Observer-Based Control of Fractional-Order Systems With Gain Parametrization
Abstract:
This paper investigates the robust observer-based control (OBC) for linear time-invariant disturbed uncertain fractional-order systems (DU-FOS). First, the existence conditions for robust OBC are given. Then, based on the -norm analysis using the generalized Kalman–Yakubovich–Popov lemma for FOS, and following the fractional derivative order , new sufficient linear matrix inequalities (LMIs) conditions are obtained to ensure the stability of the estimation errors and the stabilization of the DU-FOS simultaneously. All observer matrices gains and control laws can be computed by solving a unique LMI condition in one step. Numerical simulation is given to illustrate the validity of the proposed method.
Autors: Yassine Boukal;Mohamed Darouach;Michel Zasadzinski;Nour-Eddine Radhy;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Nov 2017, volume: 62, issue:11, pages: 5710 - 5723
Publisher: IEEE
 
» Robust AN-Aided Secure Precoding for an AF MIMO Untrusted Relay System
Abstract:
Robust artificial noise (AN) aided secure precoding for an amplify-and-forward multiple-input multiple-output untrusted relay system is studied, where the relay is untrusted and willing to help forwarding multiple data streams from the source to destination. We consider that the available channel state information is imperfect and modeled by the worst case model. Our objective is to maximize the worst case secrecy rate under the robust transmit power constraints at the source and relay, by jointly designing the signal and AN precoding matrices at the source and the precoding matrix at the relay. The robust secure precoding problem is nonconvex and hard to solve. To overcome this difficulty, we propose the weighted minimum mean square error based method, where the sign-definiteness lemma is used to eliminate the channel uncertainties and an effective iterative optimization algorithm is developed. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.
Autors: Quanzhong Li;Liang Yang;Qi Zhang;Jiayin Qin;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Nov 2017, volume: 66, issue:11, pages: 10572 - 10576
Publisher: IEEE
 
» Robust Control of Magnetic Levitation Systems Considering Disturbance Force by LSM Propulsion Systems
Abstract:
In this paper, the robust control method is proposed for air-gap positioning of magnetic levitation systems considering levitation disturbance forces caused by propulsion systems. Even though the disturbance effect occurs inevitably by propulsion systems, it is very difficult or impossible to be measured by sensors in real time. In order to maintain the constant air-gap position according to the reference command in the propulsion state of the vehicle, robust control for electromagnetic suspension against levitation disturbance force is highly required. The disturbance force caused by propulsion systems is predicted by the finite-element method analysis of the magnetic flux distribution. Based on the analyzed result, the robust and optimal levitation controller is designed by the convex optimization method for the proposed proportional integral derivative controller with the inner feedback compensator stabilizing the nonlinear plant. The proposed controller has the formulation of the conventional full-state feedback optimal controller based on state-output matching for the unmeasured state. The effectiveness of the proposed controller is verified by simulation and finite-element method analysis.
Autors: Chang-Hyun Kim;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 5
Publisher: IEEE
 
» Robust Degradation Analysis With Non-Gaussian Measurement Errors
Abstract:
Degradation analysis is an effective way to infer the health status and lifetime of products. Due to variability in the measurement, degradation observations are often subject to measurement errors. Existing studies generally assume Gaussian measurement errors, which may be deficient when there are outliers in the observations. To make a robust inference, we propose a Wiener degradation model with measurement errors modeled by Student's t-distribution. The t-distribution is a useful extension to the Gaussian distribution that provides a parametric approach to robust statistics. Nevertheless, the resulting likelihood function involves multiple integrals, which makes direct maximization difficult. Therefore, we propose an expectation-maximization algorithm, where the variational Bayes technique is introduced to derive an approximate conditional distribution in the E-step. The effectiveness of the proposed model is validated through Monte Carlo simulations. The applicability of the robust method is illustrated through applications to the degradation data of lithium-ion batteries and hard disk drives.
Autors: Qingqing Zhai;Zhi-Sheng Ye;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Nov 2017, volume: 66, issue:11, pages: 2803 - 2812
Publisher: IEEE
 
» Robust Design of a Supersonic Natural Laminar Flow Wing-Body
Abstract:
The robust design of a natural laminar flow wingbody for a supersonic business jet is here described. The pursued goal is to obtain a wing shape whose performance is influenced as least as possible by geometrical uncertainties. The starting point is a supersonic business jet wing-body that was already optimized for natural laminar flow using a deterministic objective function formulation. The definition of the optimization goal is based on special risk functions, namely Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), that are widely used in financial engineering community and that offer interesting advantages with respect to more classical approaches based on expectation or variance risk functions. VaR and CVaR are used in conjunction with two different stochastic optimization algorithms, namely the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and the Surrogate-based Local Optimization (SBLO). These risk functions are computed using a very coarse sample set and their confidence intervals are computed using the bootstrap computational statistics technique. The results illustrate the feasibility of such a robust optimization approach for the application to industrial class robust design optimization problems in aerospace.
Autors: Domenico Quagliarella;Emiliano Iuliano;
Appeared in: IEEE Computational Intelligence Magazine
Publication date: Nov 2017, volume: 12, issue:4, pages: 14 - 27
Publisher: IEEE
 
» Robust Disjunctive-Codiagnosability of Discrete-Event Systems Against Permanent Loss of Observations
Abstract:
Recently, the so-called robust diagnosability of DESs against permanent loss of observations (RDPLO) has been introduced. In this regard, the language generated by the system is said to be robustly diagnosable if it is possible to detect the failure occurrence, within a bounded delay, even when some sensors permanently fail to communicate the occurrence of the events to the diagnoser. In this technical note, we extend the definition of RDPLO to the decentralized case, considering the disjunctive architecture, leading to the definition of robust disjunctive-codiagnosability against permanent loss of observations (RDCPLO). The technical note also addresses the issue of online implementation, and we propose an efficient scheme to carry out online robust decentralized diagnosis against permanent loss of observations. Other contributions of the technical note are the development of algorithms for the verification of the RDCPLO, and the computation of the delay bound for robust decentralized diagnosis.
Autors: Jean H. A. Tomola;Felipe G. Cabral;Lilian K. Carvalho;Marcos V. Moreira;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Nov 2017, volume: 62, issue:11, pages: 5808 - 5815
Publisher: IEEE
 
» Robust Dual Clustering with Adaptive Manifold Regularization
Abstract:
In recent years, various data clustering algorithms have been proposed in the data mining and engineering communities. However, there are still drawbacks in traditional clustering methods which are worth to be further investigated, such as clustering for the high dimensional data, learning an ideal affinity matrix which optimally reveals the global data structure, discovering the intrinsic geometrical and discriminative properties of the data space, and reducing the noises influence brings by the complex data input. In this paper, we propose a novel clustering algorithm called robust dual clustering with adaptive manifold regularization (RDC), which simultaneously performs dual matrix factorization tasks with the target of an identical cluster indicator in both of the original and projected feature spaces, respectively. Among which, the -norm is used instead of the conventional -norm to measure the loss, which helps to improve the model robustness by relieving the influences by the noises and outliers. In order to better consider the intrinsic geometrical and discriminative data structure, we incorporate the manifold regularization term on the cluster indicator by using a particularly learned affinity matrix which is more suitable for the clustering task. Moreover, a novel augmented lagrangian method (ALM) based procedure is designed to effectively and efficiently seek the optimal solution of the proposed RDC optimization. Numerous experiments on the representative data sets demonstrate the superior performance of the proposed method compares to the existing clustering algorithms.
Autors: Nengwen Zhao;Lefei Zhang;Bo Du;Qian Zhang;Jane You;Dacheng Tao;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Nov 2017, volume: 29, issue:11, pages: 2498 - 2509
Publisher: IEEE
 
» Robust Event-Triggered MPC With Guaranteed Asymptotic Bound and Average Sampling Rate
Abstract:
We propose a robust event-triggered model predictive control (MPC) scheme for linear time-invariant discrete-time systems subject to bounded additive stochastic disturbances and hard constraints on the input and state. For given probability distributions of the disturbances acting on the system, we design event conditions such that the average frequency of communication between the controller and the actuator in the closed-loop system attains a given value. We employ Tube MPC methods to guarantee robust constraint satisfaction and a robust asymptotic bound on the system state. Moreover, we show that instead of a given periodically updated Tube MPC scheme, an appropriate event-triggered MPC scheme can be applied, with the same guarantees on constraints and region of attraction, but with a reduced number of average communications.
Autors: Florian David Brunner;W. P. M. H. Heemels;Frank Allgöwer;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Nov 2017, volume: 62, issue:11, pages: 5694 - 5709
Publisher: IEEE
 
» Robust Granger Analysis in Lp Norm Space for Directed EEG Network Analysis
Abstract:
Granger analysis (GA) is widely used to construct directed brain networks based on various physiological recordings, such as functional magnetic resonance imaging, and electroencephalogram (EEG). However, in real applications, EEGs are inevitably contaminated by unexpected artifacts that may distort the networks because of the L2 norm structure utilized in GAs when estimating directed links. Compared with the L2 norm, the Lp () norm can compress outlier effects. In this paper, an extended GA is constructed by applying the Lp () norm strategy to estimate robust causalities under outlier conditions, and a feasible iteration procedure is utilized to solve the new GA model. A quantitative evaluation using a predefined simulation network demonstrates smaller bias errors and higher linkage consistence for the Lp (, 0.8, 0.6, 0.4, 0.2) -GAs compared with both the Lasso- and L2-GAs under various simulated outlier conditions. Applications in resting-state EEGs that contain ocular artifacts also show that the proposed GA can effectively compress the ocular outlier influence and recover the reliable networks. The proposed Lp-GA may be helpful in capturing the reliable network structure when EEGs are contaminated with artifacts in related studies.
Autors: Peiyang Li;Xiaoye Huang;Fali Li;Xurui Wang;Weiwei Zhou;Huan Liu;Teng Ma;Tao Zhang;Daqing Guo;Dezhong Yao;Peng Xu;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Nov 2017, volume: 25, issue:11, pages: 1959 - 1969
Publisher: IEEE
 
» Robust Minimum Volume Simplex Analysis for Hyperspectral Unmixing
Abstract:
Most blind hyperspectral unmixing methods exploit convex geometry properties of hyperspectral data. The minimum volume simplex analysis (MVSA) is one of such methods, which, as many others, estimates the minimum volume (MV) simplex where the measured vectors live. MVSA was conceived to circumvent the matrix factorization step often implemented by MV-based algorithms and also to cope with outliers, which compromise the results produced by MV algorithms. Inspired by the recently proposed robust MV enclosing simplex (RMVES) algorithm, we herein introduce the robust MVSA (RMVSA), which is a version of MVSA robust to noise. As in RMVES, the robustness is achieved by employing chance constraints, which control the volume of the resulting simplex. RMVSA differs, however, substantially from RMVES in the way optimization is carried out. In this paper, we develop a linearization relaxation of the nonlinear chance constraints, which can greatly lighten the computational complex of chance constraint problems. The effectiveness of RMVSA is illustrated by comparing its performance with the state of the art.
Autors: Shaoquan Zhang;Alexander Agathos;Jun Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Nov 2017, volume: 55, issue:11, pages: 6431 - 6439
Publisher: IEEE
 
» Robust Online Algorithms for Peak-Minimizing EV Charging Under Multistage Uncertainty
Abstract:
In this paper, we study how to utilize forecasts to design online electrical vehicle (EV) charging algorithms that can attain strong performance guarantees. We consider the scenario of an aggregator serving a large number of EVs together with its background load, using both its own renewable energy (for free) and the energy procured from the external grid. The goal of the aggregator is to minimize its peak procurement from the grid, subject to the constraint that each EV has to be fully charged before its deadline. Further, the aggregator can predict the future demand and the renewable energy supply with some levels of uncertainty. We show that such prediction can be very effective in reducing the competitive ratios of online control algorithms, and even allow online algorithms to achieve close-to-offline-optimal peak. Specifically, we first propose a 2-level increasing precision model (2-IPM), to model forecasts with different levels of accuracy. We then develop a powerful computational approach that can compute the optimal competitive ratio under 2-IPM over any online algorithm, and also online algorithms that can achieve the optimal competitive ratio. Simulation results show that, even with up to 20% day-ahead prediction errors, our online algorithms still achieve competitive ratios fairly close to 1, which are much better than the classic results in the literature with a competitive ratio of . The second contribution of this paper is that we solve a dilemma for online algorithm design, e.g., an online algorithm with good competitive ratio may exhibit poor average-case performance. We propose a new Algorithm-Robustification procedure that can convert an online algorithm with good average-case performance to one with both the optimal competitive ratio and good average-case performance. We demonstrate via trace-based simulations the superior performance - f the robustified version of a well-known heuristic algorithm based on model predictive control.
Autors: Shizhen Zhao;Xiaojun Lin;Minghua Chen;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Nov 2017, volume: 62, issue:11, pages: 5739 - 5754
Publisher: IEEE
 
» Robust Online Multi-Task Learning with Correlative and Personalized Structures
Abstract:
Multi-Task Learning (MTL) can enhance a classifier’s generalization performance by learning multiple related tasks simultaneously. Conventional MTL works under the offline or batch setting, and suffers from expensive training cost and poor scalability. To address such inefficiency issues, online learning techniques have been applied to solve MTL problems. However, most existing algorithms of online MTL constrain task relatedness into a presumed structure via a single weight matrix, which is a strict restriction that does not always hold in practice. In this paper, we propose a robust online MTL framework that overcomes this restriction by decomposing the weight matrix into two components: The first one captures the low-rank common structure among tasks via a nuclear norm and the second one identifies the personalized patterns of outlier tasks via a group lasso. Theoretical analysis shows the proposed algorithm can achieve a sub-linear regret with respect to the best linear model in hindsight. Even though the above framework achieves good performance, the nuclear norm that simply adds all nonzero singular values together may not be a good low-rank approximation. To improve the results, we use a log-determinant function as a non-convex rank approximation. The gradient scheme is applied to optimize log-determinant function and can obtain a closed-form solution for this refined problem. Experimental results on a number of real-world applications verify the efficacy of our method.
Autors: Peng Yang;Peilin Zhao;Xin Gao;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Nov 2017, volume: 29, issue:11, pages: 2510 - 2521
Publisher: IEEE
 
» Robust Secure Beamforming for Wireless Powered Full-Duplex Systems With Self-Energy Recycling
Abstract:
In this paper, we study a multiuser wireless powered communication system, where an energy-constrained full-duplex information transmitter (IT), powered by wireless energy from a dedicated energy transmitter (ET), intends to send confidential information to the information receiver (IR) in the presence of multiple idle users that could be the potential eavesdroppers. In the practical scenario of imperfect channel state information and assuming that the idle users need to harvest energy from the ET, we aim to maximize the worst-case secrecy rate at the IR by jointly optimizing the transmit covariance matrix at the ET as well as the information beamforming and artificial noise covariance at the IT, subject to their individual transmit power constraints and the minimum required power transferred to the idle users. We employ the semidefinite relaxation (SDR) and extended S-procedure approaches to transform the original nonconvex optimization problem into convex problem, which can be efficiently solved by solving a sequence of semidefinite programs. Furthermore, we show that the SDR is tight since there always exists a rank-one optimal solution. For performance comparison, two heuristic schemes for ease of implementation are also developed. Numerical results are presented to show the effectiveness of our proposed schemes.
Autors: Wei Wu;Baoyun Wang;Yong Zeng;Haiyang Zhang;Zhenxing Yang;Zhixiang Deng;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Nov 2017, volume: 66, issue:11, pages: 10055 - 10069
Publisher: IEEE
 
» Robust Semisupervised Classification for PolSAR Image With Noisy Labels
Abstract:
The robustness of the supervised polarimetric synthetic aperture radar (PolSAR) image classification is severely affected by two main aspects, namely, the quantity and quality of the labeled training pixels. Specifically, limited manually labeled pixels with respect to the large scale of PolSAR image have limited the performance of the automatic classification methods, while manually labeled training pixels shall be unfaithful with the speckle and impure cell for their low qualities. In order to address the above two fundamental problems, we propose a robust semisupervised probability graphic-based classification framework. First, a semisupervised learning scheme is implemented to simultaneously exploit both labeled and unlabeled pixels for information compensation. Moreover, structural relationship among neighboring pixels inducing from the prior information is further benefit to reduce the influence of limited labeled pixels. Second, a robust classification loss function is added in the process of training classifier to enhance the robustness to the noisy labeled pixels. Third, unfaithful limited labeled data can be settled with a hybrid generative/discriminative classification framework, where labeled and unlabeled pixels are simultaneously exploited for learning high-level feature for the low-quality pixels. The effectiveness of the proposed framework on the specific aspect is validated in experiments on real PolSAR data sets, which reveal the superiority in both visual performance and classification accuracy compared with the state-of-the-art methods. Totally speaking, our model has improved the classification accuracy by at least 20% on data set Flevoland, 10% on Oberpfaffenhofen, and 5% on Weihe River than the compared ones.
Autors: Biao Hou;Qian Wu;Zaidao Wen;Licheng Jiao;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Nov 2017, volume: 55, issue:11, pages: 6440 - 6455
Publisher: IEEE
 
» Robust Synchronization Waveform Design for Massive IoT
Abstract:
Machine-type communication (MTC) is the key technology to support data transfer among devices (sensors and actuators) in Internet of Things (IoT). However, MTC, especially when applied to massive low-power IoT (mIoT), poses some unique and serious challenges due to the low-cost and low-power nature of an mIoT device. One of the most challenging issues is providing a robust way for an mIoT device to acquire the network under a large frequency offset/error (due to the use of a low-cost crystal oscillator) and a low operating SNR (due to the extended coverage). We address the issues in the existing mIoT system acquisition, particularly the initial synchronization waveform detection, and derive a new synchronization waveform that is more robust in an mIoT environment. The mathematical approach provides a useful analytical insight into the design of the synchronization signal waveform for the 5G mIoT system.
Autors: Jingjing Zhang;Mao Wang;Min Hua;Wenjie Yang;Xiaohu You;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Nov 2017, volume: 16, issue:11, pages: 7551 - 7559
Publisher: IEEE
 
» Robust Ultraminiature Capsule Antenna for Ingestible and Implantable Applications
Abstract:
Progress in implantable and ingestible wireless biotelemetry requires versatile and efficient antennas to communicate reliably from a body. We propose an ultraminiature 434 MHz antenna immune to impedance detuning caused by varying electromagnetic properties of the surrounding biological environment. It is designed for a standard input impedance of 50 . The antenna is synthesized and miniaturized using a hybrid analytical–numerical approach, and then optimized to conform to the inner surface of a 17 mm long biocompatible encapsulation (7 mm diameter). The substrate is 50 thick. The capsule antenna is analyzed both in simplified and anatomically realistic heterogeneous phantoms. It remains matched at common implantation sites and through the whole gastrointestinal tract. Enhanced robustness allows using the antenna for a wide range of in-body applications. Computed reflection coefficients and radiation performance both show good agreement with measurements. The far field is characterized with the direct illumination technique using an analog fiber optic link. The realized gain (measured max. value −19.6 dBi) exceeds the counterparts by about 3 dBi. The proposed antenna contributes to the further development of a new generation of miniature in-body devices that involve complex and dense integration of sensors, logic, and power source.
Autors: Denys Nikolayev;Maxim Zhadobov;Laurent Le Coq;Pavel Karban;Ronan Sauleau;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Nov 2017, volume: 65, issue:11, pages: 6107 - 6119
Publisher: IEEE
 
» Rotational Magnetization Lag-Angle Plots Using the Anisotropic Stoner–Wohlfarth Model
Abstract:
A numerical implementation of the classical Stoner–Wohlfarth (SW) model to simulate the magnetization angle of an assembly of SW particles with an effective axis of anisotropy under a rotating applied field is presented. Using an angular distribution for the angle each SW particle is making with the medium’s reference axis, the proposed model successfully simulated lag-angle plots exhibiting the same rotational magnetization behavior measured for different ellipsoidally magnetizable media in the literature. The developed algorithm provides a simple tool for rotational-energy-loss calculations, preserves the physical intuition of the classical SW model, and is computationally faster compared to the Preisach–Stoner–Wohlfarth models. The effect of the angular distribution parameters on the switching transition angle and the algorithm’s potential for modeling additional anisotropies through using different angular distributions are discussed.
Autors: Hatem ElBidweihy;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 6
Publisher: IEEE
 
» Rough Surface and Volume Scattering of Soil Surfaces, Ocean Surfaces, Snow, and Vegetation Based on Numerical Maxwell Model of 3-D Simulations
Abstract:
In this paper, we give an overview and an update on the recent progress of our research group in numerical model of Maxwell equations in three dimensions (NMM3D) on random rough surfaces and discrete random media and their applications in active and passive microwave remote sensing. The random rough surface models were applied to soil surfaces and ocean surfaces. The discrete random media models were applied to snow and vegetation. For rough surface scattering, we use the surface integral equations of Poggio–Miller–Chang–Harrington–Wu–Tsai that are solved by the method of moments using the Rao–Wilton–Glisson basis functions. The sparse matrix canonical grid method is used to accelerate the matrix column multiplications. In modeling the rough surfaces, we use the exponential correlation functions for soil surfaces and the Durden–Vesecky ocean spectrum for ocean surfaces. In scattering by terrestrial snow and snow on sea ice, we use the volume integral equations formulated with the dyadic half-space Green's function. The microstructure of snow is modeled by the bicontinuous media. In scattering by vegetation, we use the discrete scatterers of cylinder. The NMM3D formulation is based on the Foldy–Lax multiple scattering equations in conjunction with the body of revolution for a single scatterer. For rough surface scattering, simulations results are compared with advanced integral equation model, small slope approximation, small perturbation method, and two scale model. For volume scattering by snow, results are compared with the bicontinuous dense media radiative transfer. For scattering by vegetation, results are compared with distorted Born approximation and radiative transfer equation. Comparisons are also made with experiments.
Autors: Leung Tsang;Tien-Hao Liao;Shurun Tan;Huanting Huang;Tai Qiao;Kung-Hau Ding;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Nov 2017, volume: 10, issue:11, pages: 4703 - 4720
Publisher: IEEE
 
» Round-Trip Delay Modeling for Smart Body Area Networks
Abstract:
This letter presents the first round-trip delay study of the recently proposed smart body area networks (SmartBANs) to address the challenge of achieving ultra-low round-trip delay for ubiquitous e-health applications. Based on the SmartBAN medium access control (MAC) protocol, an embedded Markov chain is developed for queuing and delay analysis of downlink packets broadcasted by the central hub to the attached nodes. The uplink delay caused by a time division multiple access mechanism is formulated by an M/D/1 queue with a vacation model. Finally, the round-trip delay, as the combination of both uplink and downlink delays, is derived. Based on our proposed model, we highlight a tradeoff between uplink and downlink delays under varying downlink transmission durations, providing an understanding of how the predefined MAC timing parameters impact the round-trip delay. The accuracy of our models is validated by extensive simulations.
Autors: Lihua Ruan;Maluge P. I. Dias;Ye Feng;Elaine Wong;
Appeared in: IEEE Communications Letters
Publication date: Nov 2017, volume: 21, issue:11, pages: 2528 - 2531
Publisher: IEEE
 
» Routability-Driven TSV-Aware Floorplanning Methodology for Fixed-Outline 3-D ICs
Abstract:
Although 3-D floorplanning has been studied widely, routability which is a very important issue in modern integrated circuit (IC) designs is rarely discussed. Floorplanning in 3-D ICs is much difficult than that in 2-D ICs because of large difference in sizes between modules and through silicon vias (TSVs), which are key components in 3-D ICs. And the locations of TSVs have great impact on wirelength and routability in resulting floorplans. Hence, this paper proposes a TSV-aware 3-D floorplanning methodology which can consider wirelength and routability at the same time under the fixed-outline constraint. Unlike most of previous works which completely apply the simulated annealing algorithm, our methodology mainly apply deterministic algorithms to resolve the problem. Thus, our approach is more efficient and flexible than previous works. Experimental results have demonstrated that the proposed methodology can significantly reduce routing congestion in 3-D ICs with a slight increase in wirelength.
Autors: Jai-Ming Lin;Jung-An Yang;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Nov 2017, volume: 36, issue:11, pages: 1856 - 1868
Publisher: IEEE
 
» RSD: Rate-Based Sync Deferment for Personal Cloud Storage Services
Abstract:
Cloud storage services, such as Dropbox, Google Drive, and OneDrive, to cite a few, are becoming an increasingly “vital” tool in our everyday life. Unluckily, these services can incur large network overhead in different usage scenarios. To reduce it, these systems utilize several techniques, such as source-based deduplication, chunking, delta compression, and so on. One of these techniques is sync deferment, which relies on the packing of updates to intentionally defer the synchronization process for some time, and increase the volume of useful data per overhead byte. The scientific literature has shown this technique to be very helpful, though there are still some limitations on current solutions. To resolve them, we present here a new adaptive sync deferment method, which is comparable to the current state of the art in terms of network overhead, but is also able to minimize the file synchronization time up to 12 times.
Autors: Raúl Sáiz-Laudó;Marc Sánchez-Artigas;Pedro García-López;
Appeared in: IEEE Communications Letters
Publication date: Nov 2017, volume: 21, issue:11, pages: 2384 - 2387
Publisher: IEEE
 
» Rural Building Detection in High-Resolution Imagery Based on a Two-Stage CNN Model
Abstract:
High-level feature extraction and hierarchical feature representation of image objects with a convolutional neural network (CNN) can overcome the limitations of the traditional building detection models using middle/low-level features extracted from a complex background. Aiming at the drawbacks of manual village location, high cost, and the limited accuracy of building detection in the existing rural building detection models, a two-stage CNN model is proposed in this letter to detect rural buildings in high-resolution imagery. Simulating the hierarchical processing mechanism of human vision, the proposed model is constructed with two CNNs, whose architectures can automatically locate villages and efficiently detect buildings, respectively. This two-stage CNN model effectively reduces the complexity of the background and improves the efficiency of rural building detection. The experiments showed that the proposed model could automatically locate all the villages in the two study areas, achieving a building detection accuracy of 88%. Compared with the existing models, the proposed model was proved to be effective in detecting buildings in rural areas with a complex background.
Autors: Li Sun;Yuqi Tang;Liangpei Zhang;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Nov 2017, volume: 14, issue:11, pages: 1998 - 2002
Publisher: IEEE
 
» RWW 2018 Student Paper Contest [RWW]
Abstract:
Presents information on the RWW 2018 Student Paper Contest.
Autors: Holger Maune;
Appeared in: IEEE Microwave Magazine
Publication date: Nov 2017, volume: 18, issue:7, pages: 22 - 22
Publisher: IEEE
 
» RWW 2018 Technical Program Chair's Greeting [RWW]
Abstract:
Presents the Chair's opening message for the RWW 2018 Technical Program.
Autors: Robert Caverly;
Appeared in: IEEE Microwave Magazine
Publication date: Nov 2017, volume: 18, issue:7, pages: 14 - 16
Publisher: IEEE
 
» S-Shaped ${I}$ – ${V}$ Characteristics of Organic Solar Cells: Solving Mazhari’s Lumped-Parameter Equivalent Circuit Model
Abstract:
We explain how to obtain closed-form analytic solutions from the set of equations that describe the three-diode lumped-parameter equivalent circuit model proposed by Mazhari [1] to portray the undesirable S-shape often observed in – characteristics of illuminated organic solar cells (OSCs), and occasionally seen in other types of solar cells. This allows quick extraction of the model’s parameter values by directly fitting the resulting closed-form solution to the cell’s measured – data. Such mathematical simplification of the extraction procedure facilitates individually studying the effect of each parameter on the illuminated OSC – characteristics, and thus on its power generation capacity. We illustrate application of the direct extraction procedure to measured – characteristics of an experimental OSC, which exhibits the illumination intensity-dependent S-shapes. The usefulness of the analytic solution to assess the effect of the model parameters is further corroborated by graphically illustrating the progression of a series of hypothetical synthetic – characteristics generated by this analytic solution using gradually changing the parameter values. Analysis of the results, in this case, indicates that activation of the diode that represents recombination is the key factor responsible for the emergence of the illuminated – curve’s S-shape.
Autors: Beatriz Romero;Gonzalo del Pozo;Belén Arredondo;Diego Martín-Martín;María P. Ruiz Gordoa;Andrew Pickering;Ana Pérez-Rodríguez;Esther Barrena;Francisco J. García-Sánchez;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Nov 2017, volume: 64, issue:11, pages: 4622 - 4627
Publisher: IEEE
 
» Safe Optimization of Highway Traffic With Robust Model Predictive Control-Based Cooperative Adaptive Cruise Control
Abstract:
Road traffic crashes have been the leading cause of death among young people. Most of these accidents occur when the driver becomes distracted due to fatigue or external factors. Vehicle platooning systems, as cooperative adaptive cruise control, are one of the results of efforts devoted to the development of technologies for decreasing the number of road crashes and fatalities. Previous studies have suggested that such systems improve up to 273% highway traffic throughput and over 15% of fuel consumption if the clearance between vehicles in this class of roads can be reduced to 2 m. In this paper, we propose an approach that guarantees a minimum safety distance between vehicles taking into account the overall system delays and braking capacity of each vehicle. An -norm robust model predictive controller has been developed to guarantee the minimum safety distance is not violated due to uncertainties on the preceding vehicle behavior. A formulation for a lower bound clearance of vehicles inside a platoon is also proposed. Simulation results show the performance of the approach compared to a nominal controller when the system is subject to both modeled and unmodeled disturbances.
Autors: Carlos Massera Filho;Marco H. Terra;Denis F. Wolf;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 3193 - 3203
Publisher: IEEE
 
» Sampling and Distortion Tradeoffs for Indirect Source Retrieval
Abstract:
Consider a continuous signal that cannot be observed directly. Instead, one has access to multiple corrupted versions of the signal. The available corrupted signals are correlated because they carry information about the common remote signal. The goal is to reconstruct the original signal from the data collected from its corrupted versions. Known as the indirect or remote reconstruction problem, it has been mainly studied in the literature from an information theoretic perspective. A variant of this problem for a class of Gaussian signals, known as the “Gaussian CEO problem,” has received particular attention; for example, it has been shown that the problem of recovering the remote signal is equivalent with the problem of recovering the set of corrupted signals (separation principle). The information theoretic formulation of the remote reconstruction problem assumes that the corrupted signals are uniformly sampled and the focus is on optimal compression of the samples. On the other hand, in this paper, we revisit this problem from a sampling perspective. More specifically, assuming restrictions on the sampling rate from each corrupted signal, we look at the problem of finding the best sampling locations for each signal to minimize the total reconstruction distortion of the remote signal. In finding the sampling locations, one can take advantage of the correlation among the corrupted signals. The statistical model of the original signal and its corrupted versions adopted in this paper are similar to the one considered for the Gaussian CEO problem; i.e., we restrict to a class of Gaussian signals. Our main contribution is a fundamental lower bound on the reconstruction distortion for any arbitrary nonuniform sampling strategy. This lower bound is valid for any sampling rate. Furthermore, it is tight and matches the optimal reconstruction distortion in low and high sampling rates. Moreover, it is shown that- in the low sampling rate region, it is optimal to use a certain nonuniform sampling scheme on all the signals. On the other hand, in the high sampling rate region, it is optimal to uniformly sample all the signals. We also consider the problem of finding the optimal sampling locations to recover the set of corrupted signals, rather than the remote signal. Unlike the information theoretic formulation of the problem in which these two problems were equivalent, we show that they are not equivalent in our setting. Finally, another contribution of this paper is a new reverse majorization inequality that might be of independent interest.
Autors: Elaheh Mohammadi;Alireza Fallah;Farokh Marvasti;
Appeared in: IEEE Transactions on Information Theory
Publication date: Nov 2017, volume: 63, issue:11, pages: 6833 - 6848
Publisher: IEEE
 
» Sampling-Based Path Planning for UAV Collision Avoidance
Abstract:
The ability to avoid collisions with moving obstacles, such as commercial aircraft is critical to the safe operation of unmanned aerial vehicles (UAVs) and other air traffic. This paper presents the design and implementation of sampling-based path planning methods for a UAV to avoid collision with commercial aircraft and other moving obstacles. In detail, the authors develop and demonstrate a method based on the closed-loop rapidly-exploring random tree algorithm and three variations of it. The variations are: 1) simplification of trajectory generation strategy; 2) utilization of intermediate waypoints; 3) collision prediction using reachable set. The methods were validated in software-in-the-loop simulations, hardware-in-the-loop simulations, and real flight experiments. It is shown that the algorithms are able to generate collision free paths in real time for the different types of UAVs among moving obstacles of different numbers, approaching angles, and speeds.
Autors: Yucong Lin;Srikanth Saripalli;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 3179 - 3192
Publisher: IEEE
 
» SAR Target Discrimination Based on BOW Model With Sample-Reweighted Category-Specific and Shared Dictionary Learning
Abstract:
To improve the synthetic aperture radar (SAR) target discrimination performance under complex scenes, this letter presents a new SAR target discrimination method based on the bag-of-words model. The method contains three main stages. In the local feature extraction stage, the SAR-SIFT feature is extracted. In the feature coding stage, we improve the existing category-specific and shared dictionary learning (CSDL) and propose the sample-reweighted CSDL (SR-CSDL). The local features are sparsely coded using the codebook learned from SR-CSDL. In the feature pooling stage, spatial pyramid matching with max pooling is used to aggregate the local coding coefficients to generate the global feature for each chip image. Experimental results using the miniSAR data verify the effectiveness of the proposed method.
Autors: Yinghua Wang;Hongwei Liu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Nov 2017, volume: 14, issue:11, pages: 2097 - 2101
Publisher: IEEE
 
» SAR-Based Vessel Velocity Estimation From Partially Imaged Kelvin Pattern
Abstract:
Spaceborne synthetic aperture radar (SAR) can be considered an operational asset for maritime monitoring applications. Well-assessed approaches exist for ship detection, validated in several maritime surveillance systems. However, measuring vessel velocity from detected single-channel SAR images of ships is in general difficult. This letter contributes to this problem by investigating the possibility of retrieving vessel velocity by wake analysis. An original method for velocity estimation is developed for calm sea (Beaufort scale 1–2) and applied over seven X-band SAR images, gathered by COSMO-SkyMed mission over the Gulf of Naples, Italy. The algorithm exploits the well-known relation between the wavelength of the waves composing the Kelvin pattern and the ship velocity. But the proposed approach extends the applicability of the existing wake-based techniques since it foresees evaluation of the wavelength along a generic direction in the Kelvin angle. Promising results have been achieved, which are in good agreement with those of more assessed techniques for ship velocity estimation in SAR images.
Autors: Alessandro Panico;Maria Daniela Graziano;Alfredo Renga;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Nov 2017, volume: 14, issue:11, pages: 2067 - 2071
Publisher: IEEE
 
» Scalable and Unified Digit-Serial Processor Array Architecture for Multiplication and Inversion Over GF( $2^{m}$ )
Abstract:
This paper proposes a scalable and unified digit-serial structure, with low space complexity to perform multiplication and inversion operations in , based on the bit serial multiplication algorithm and the previously modified extended Euclidean inversion algorithm. In this structure, the multiplier and inverter shares the data-path and thus saves more area resources and power than the case of using separate data-path for each operation. Also, this structure is suitable for fixed size processor that only reuse the core and does not require to modulate the core size when the field size is modified. This structure is extracted by applying a nonlinear methodology that gives the designer more flexibility to control the processing element workload. Implementation results for of the proposed scalable and unified digit-serial design and previously reported efficient designs show that the proposed scalable structure achieves a significant reduction in area ranging from 64.3% to 85.5% and also achieves a significant saving in energy ranging from 21.9% to 92.5% over them, but it has lower throughput compared with them. This makes the proposed design more suitable for constrained implementations of cryptographic primitives in ultra-low power devices, such as wireless sensor nodes and radio frequency identification devices.
Autors: Atef Ibrahim;Fayez Gebali;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Nov 2017, volume: 64, issue:11, pages: 2894 - 2906
Publisher: IEEE
 
» Scalable Mammogram Retrieval Using Composite Anchor Graph Hashing With Iterative Quantization
Abstract:
Content-based image retrieval (CBIR) shows great significance in clinical decision-making, which explores the visual content of medical images rather than keywords, tags, or descriptions. It provides doctors an image-guided approach to explore relevant cases that could offer doctors instructive reference. Mammogram screening has been known to be widely used in the early stage diagnosis of breast cancer and could reduce its morbidity and mortality. In this paper, we aim to develop a scalable CBIR method for a large repository of mammogram. To this end, we extend the original Anchor Graph Hashing (AGH) and propose a new unsupervised hashing algorithm, named as composite AGH with iterative quantization (C-AGH-ITQ), which compresses mammographic regions of interest (ROIs) into compact binary codes and enables real-time searching in Hamming space. Multimodal features and different distance metrics are integrated, performing upon a composite Anchor Graph. To improve the effectiveness of the hash code, quantization error is further iteratively minimized by introducing an orthogonal rotation matrix. We evaluate the presented C-AGH-ITQ algorithm on a data set of 11 533 mammographic ROIs obtained from the Digital Database for Screening Mammography. Our method obtains more than 84% retrieval precision and 93% classification accuracy (using NN prediction), which demonstrates that hash codes produced by C-AGH-ITQ well capture the visual similarities between mammographic images. In addition, since C-AGH-ITQ ensures linear complexity of the training procedure and constant time for query, our system is readily applicable to large-scale mammogram databases and has the potential to provide abundant clinical cases as reference.
Autors: Jingjing Liu;Shaoting Zhang;Wei Liu;Cheng Deng;Yuanjie Zheng;Dimitris N. Metaxas;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Nov 2017, volume: 27, issue:11, pages: 2450 - 2460
Publisher: IEEE
 
» Scalable Planning for Energy Storage in Energy and Reserve Markets
Abstract:
Energy storage can facilitate the integration of renewable energy resources by providing arbitrage and ancillary services. Jointly optimizing energy and ancillary services in a centralized electricity market reduces the system's operating cost and enhances the profitability of energy storage systems. However, achieving these objectives requires that storage be located and sized properly. We use a bilevel formulation to optimize the location and size of energy storage systems, which perform energy arbitrage and provide regulation services. Our model also ensures the profitability of investments in energy storage by enforcing a rate of return constraint. Computational tractability is achieved through the implementation of a primal decomposition and a subgradient-based cutting-plane method. We test the proposed approach on a 240-bus model of the Western Electricity Coordinating Council system and analyze the effects of different storage technologies, rate of return requirements, and regulation market policies on energy storage participation on the optimal storage investment decisions. We also demonstrate that the proposed approach outperforms exact methods in terms of solution quality and computational performance.
Autors: Bolun Xu;Yishen Wang;Yury Dvorkin;Ricardo Fernández-Blanco;Cesar A. Silva-Monroy;Jean-Paul Watson;Daniel S. Kirschen;
Appeared in: IEEE Transactions on Power Systems
Publication date: Nov 2017, volume: 32, issue:6, pages: 4515 - 4527
Publisher: IEEE
 
» Scaling Agile
Abstract:
Scaling agile allows tailoring and blending agile and lean practices to address actual industry needs for critical systems. This article explores the state of the practice with frameworks such as the Scaled Agile Framework (SAFe).
Autors: Christof Ebert;Maria Paasivaara;
Appeared in: IEEE Software
Publication date: Nov 2017, volume: 34, issue:6, pages: 98 - 103
Publisher: IEEE
 
» Scaling Electrochemical Battery Models for Time-Accelerated and Size-Scaled Experiments on Test-Benches
Abstract:
This paper presents a dimensional-analysis supported scaling procedure applied to a mathematical model of electrochemical batteries. The main objective of this research is to allow for laboratory size-scaled and time-compressed experimental analysis of processes involving large physical magnitudes and evolving over long time spans. These situations are of interest when considering the sizing of battery packs and other components of energy systems, particularly smart grids, and further systems where battery storage is relevant, like hybrid vehicles and other standalone systems, as well as deciding management strategies on them. Voltage-, current- and time-scaled models preserving the dynamic evolution of a group of relevant physical magnitudes are presented. These models have been validated through simulation and physical experiments on a test-bench designed and constructed on purpose. The physical implementation of the scaled models is not possible in the cases where some of the scaled model parameters cannot be met using real batteries. But, as the mathematical construction of the scaled models is always possible, this problem can be circumvented with a Hardware-in-the-loop approach: the scaled battery is numerically emulated on a programmable and controllable power source/sink system, which is run in real-time embedded in the test-bench representing the whole system under study.
Autors: Javier M. Cabello;Xavier Roboam;Sergio Junco;Eric Bru;Fabien Lacressonniere;
Appeared in: IEEE Transactions on Power Systems
Publication date: Nov 2017, volume: 32, issue:6, pages: 4233 - 4240
Publisher: IEEE
 
» Scaling Study of Spin-Hall-Assisted Spin Transfer Torque Driven Magnetization Switching in the Presence of Dzyaloshinskii–Moriya Interaction
Abstract:
Spin-hall-assisted spin transfer torque (SHA-STT) can achieve high-speed, magnetic-field-free, and high-reliable magnetization switching in a three-terminal device consisting of magnetic tunnel junctions (MTJ) above a heavy-metal. Nowadays, the development of perpendicular magnetic anisotropy drives the continuous scaling of the MTJ. In addition, an asymmetric exchange interaction called Dzyaloshinskii–Moriya interaction (DMI) inevitably exists at the heavy metal/ferromagnet interface and has a considerable influence on the magnetization dynamics. Considering these factors, in this work, we study the scaling performance of the SHA-STT driven magnetization dynamics in the presence of DMI. Simulation results demonstrate that, for nonzero DMI, the magnetization switching is activated by domain nucleation, whose mechanism is strongly dependent on the MTJ size and DMI magnitude. The critical SHE current density for magnetization switching decreases with the enlarged MTJ or enhanced DMI. In the presence of DMI, the switching time decreases with the scaling of the MTJ. Moreover, compared with the case of zero DMI, the switching speed is improved or deteriorated for the weak or strong DMI, respectively. Our work demonstrates that the MTJ size and DMI magnitude should be optimized in order to achieve a good tradeoff among a set of performance metrics of the SHA-STT devices.
Autors: Yuqian Gao;Zhaohao Wang;Xiaoyang Lin;Wang Kang;Youguang Zhang;Weisheng Zhao;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Nov 2017, volume: 16, issue:6, pages: 1138 - 1142
Publisher: IEEE
 
» Scanning Enhanced Low-Profile Broadband Phased Array With Radiator-Sharing Approach and Defected Ground Structures
Abstract:
In this paper, a scanning enhanced low-profile broadband phased array is presented. This array is based on the radiator-sharing approach and the defected ground structures (DGSs). In this phased array, the radiator-sharing approach has been implemented by using metasurface antenna, and the scanning range has been remarkably enhanced by reducing element spacing. An attractive behavior in broadband impedance matching has still been obtained, in spite that closely spaced feedings are adopted. Moreover, the scanning performance is considerably improved by applying meander-line slots cut from the ground plane, forming DGS. In order to validate this proposed design, a nine-element linear phased array with DGSs has been fabricated and measured. Based on the uniform magnitude and the progressive phase, the capability of wide-angle scanning can be achieved over the measured bandwidth of 23.1% (4.6–5.8 GHz). At the center frequency of 5.2 GHz, this array scans up to 50° and the realized gain varies from 14.76 to 11.85 dBi.
Autors: Li Gu;Yan-Wen Zhao;Qiang-Ming Cai;Zhi-Peng Zhang;Bi-Hui Xu;Zai-Ping Nie;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Nov 2017, volume: 65, issue:11, pages: 5846 - 5854
Publisher: IEEE
 
» Scanning Spreading Resistance Microscopy for Doping Profile in Saddle-Fin Devices
Abstract:
Scanning capacitance microscopy (SCM) and scanning spreading resistance microscopy (SSRM) are used to investigate the doping profile of saddle-fin (S-fin) devices in a 30-nm dynamic-random-access-memory (DRAM) technology. Due to the limited resolution of SCM, SCM cannot provide a clear doping profile of an S-fin array device. In the meantime, SSRM and focused ion beam milling during sample preparation provide an opportunity to obtain a 2-D and scanning line doping profile. The common-source region between two adjacent buried word lines is treated with an additional phosphorus (P) implantation with energy and dosage modification to have a doping profile modification in the array devices of DRAM product. With condition of the medium energy and high dosage in this additional P implantation, the row hammer effect of 30-nm DRAM could be minimized by the localized shielding effect from the electric field by a depletion effect. The junction profile of the additional P implantation is about 10 nm deeper than that of the control sample, as verified by SSRM and technology computer-aided design simulation. The experimental results of the doping profile can be used to support a mechanism of improvement of row hammer. The SSRM methodology proposed in this study could be used to optimize the doping profiles in DRAMs for future scaling technology.
Autors: Chia-Ming Yang;Chen-Kang Wei;Hsiu-Pin Chen;Jian-Shing Luo;Yu Jing Chang;Tieh-Chiang Wu;Chao-Sung Lai;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Nov 2017, volume: 16, issue:6, pages: 999 - 1003
Publisher: IEEE
 
» Scanning the Issue
Abstract:
Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges
Autors: Petros Ioannou;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 2893 - 2897
Publisher: IEEE
 
» Scheduling of Electric Vehicle Charging via Multi-Server Fair Queueing
Abstract:
Charging electric vehicles (EVs) at home is attractive to EV users. However, when the penetration level of EVs becomes high, a distribution grid suffers from problems such as under-voltage and transformer overloading. EV users also experience a fairness problem, i.e., the limited capacity is unfairly shared among EVs. To solve these problems, a physical fair-queueing framework is established for EV charging. In this framework, a distribution sub-grid is first mapped to a multi-server queueing system, and then a fluid-model based queueing scheme called physical multi-server generalized processor sharing (pMGPS) is designed. pMGPS ensures perfect fairness but cannot be used practically due to its nature of fluid model. To this end, a packetized scheme called physical start-time fair queueing (pSTFQ) is developed to schedule tasks of EV charging. The fairness performance of the pSTFQ scheduling scheme is characterized by the ratio of energy difference between pSTFQ and pMGPS. This critical performance metric is studied through theoretical analysis and is also evaluated via simulations. Performance results show that the pSTFQ scheduling scheme achieves an energy difference ratio of less than 4 percent in various scenarios without causing under-voltage and transformer overloading problems.
Autors: Xudong Wang;Yibo Pi;Aimin Tang;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Nov 2017, volume: 28, issue:11, pages: 3298 - 3312
Publisher: IEEE
 
» Schottky Barrier FET Biosensor for Dual Polarity Detection: A Simulation Study
Abstract:
In this letter, we present the first tunable polarity biosensor which exhibits a high sensitivity detection capability for both negatively and positively charged biomolecules. The concept is enabled by the use of a reconfigurable transistor in which two individually gated Schottky junctions permit a selective transport of carriers through the junctions. Using TCAD simulations, we show that a threshold voltage shift of ~0.6 V and a current sensitivity are obtained. We further demonstrate through simulations that the proposed structure enhances the sensitivity (~3 times) of the state-of-the-art Schottky FET biosensors which suffer from severely reduced transconductance due to contact passivation. With a high sensitivity and operation versatility, the proposed device holds a great promise for more compact and multiplexed sensing capabilities than the existing FET biosensors.
Autors: Sumeet Kalra;Mamidala Jagadesh Kumar;Anuj Dhawan;
Appeared in: IEEE Electron Device Letters
Publication date: Nov 2017, volume: 38, issue:11, pages: 1594 - 1597
Publisher: IEEE
 
» Sea Ice Classification Using Cryosat-2 Altimeter Data by Optimal Classifier–Feature Assembly
Abstract:
Sea ice type is one of the most sensitive variables in Arctic ice monitoring and detailed information about it is essential for ice situation evaluation, vessel navigation, and climate prediction. Many machine-learning methods including deep learning can be employed for ice-type detection, and most classifiers tend to prefer different feature combinations. In order to find the optimal classifier–feature assembly (OCF) for sea ice classification, it is necessary to assess their performance differences. The objective of this letter is to make a recommendation for the OCF for sea ice classification using Cryosat-2 (CS-2) data. Six classifiers including convolutional neural network (CNN), Bayesian, nearest-neighbor (KNN), support vector machine (SVM), random forest (RF), and back propagation neural network (BPNN) were studied. CS-2 altimeter data of November 2015 and May 2016 in the whole Arctic were used. The overall accuracy was estimated using multivalidation to evaluate the performances of individual classifiers with different feature combinations. Overall, RF achieved a mean accuracy of 89.15%, followed by Bayesian, SVM, and BPNN (~86%), outperforming the worst (CNN and KNN) by 7%. Trailing-edge width (TeW) and leading-edge width (LeW) were the most important features, and feature combination of TeW, LeW, Sigma0, maximum of the returned power waveform (MAX), and pulse peakiness (PP) was the best choice. RF with feature combination of TeW, LeW, Sigma0, MAX, and PP was finally selected as the OCF for sea ice classification and the results that demonstrated this method achieved a mean accuracy of 91.45%, which outperformed the other state-of-art methods by 9%.
Autors: Xiaoyi Shen;Jie Zhang;Xi Zhang;Junmin Meng;Changqing Ke;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Nov 2017, volume: 14, issue:11, pages: 1948 - 1952
Publisher: IEEE
 
» Second-Order Sliding Mode Based P-Q Coordinated Modulation of DFIGs Against Interarea Oscillations
Abstract:
This letter presents an active and reactive power coordinated damping controller for doubly fed induction generator (DFIG) using second-order sliding mode technique. Through simultaneously modulating active and reactive power of DFIG, the proposed controller has an enhanced damping performance. Its advantages include faster damping speed and robustness to modeling uncertainties and parameter variations. Simulation results have verified its superior performance over existing schemes.
Autors: Kai Liao;Yan Xu;Zhengyou He;Zhao Yang Dong;
Appeared in: IEEE Transactions on Power Systems
Publication date: Nov 2017, volume: 32, issue:6, pages: 4978 - 4980
Publisher: IEEE
 
» Secret Key Generation With Limited Interaction
Abstract:
A basic two-terminal secret key generation model is considered, where the interactive communication rate between the terminals may be limited, and in particular may not be enough to achieve the maximum key rate. We first prove a multi-letter characterization of the key-communication rate region (where the number of auxiliary random variables depends on the number of rounds of the communication), and then provide an equivalent but simpler characterization in terms of concave envelopes in the case of unlimited number of rounds. Two extreme cases are given special attention. First, in the regime of very low communication rates, the key bits per interaction bit (KBIB) is expressed with a new “symmetric strong data processing constant”, which has a concave envelope characterization analogous to that of the conventional strong data processing constant. The symmetric strong data processing constant can be upper bounded by the supremum of the maximal correlation coefficient over a set of distributions, which allows us to determine the KBIB for binary symmetric sources, and conclude, in particular, that the interactive scheme is not more efficient than the one-way scheme at least in the low communication-rate regime. Second, a new characterization of the minimum interaction rate needed for achieving the maximum key rate (MIMK) is given, and we resolve a conjecture by Tyagi regarding the MIMK for (possibly nonsymmetric) binary sources. We also propose a new conjecture for binary symmetric sources that the interactive scheme is not more efficient than the one-way scheme at any communication rate.
Autors: Jingbo Liu;Paul Cuff;Sergio Verdú;
Appeared in: IEEE Transactions on Information Theory
Publication date: Nov 2017, volume: 63, issue:11, pages: 7358 - 7381
Publisher: IEEE
 
» Secure and Energy-Efficient Beamforming for Simultaneous Information and Energy Transfer
Abstract:
Some next-generation wireless networks will likely involve the energy-efficient transfer of information and energy over the same wireless channel. Moreover, densification of such networks will make the physical layer more vulnerable to cyber attacks by potential multi-antenna eavesdroppers. To address these issues, this paper considers transmit time-switching (TS) mode, in which energy and information signals are transmitted separately in time by the base station (BS). This protocol is not only easy to implement but also delivers the opportunity for multi-purpose beamforming, in which energy beamformers can be used to jam eavesdroppers during wireless power transfer. In the presence of imperfect channel estimation and multi-antenna eavesdroppers, the energy and information beamformers and the transmit TS ratio are jointly optimized to maximize the worst-case user secrecy rate subject to energy constrained users’ harvested energy thresholds and a BS transmit power budget. New robust path-following algorithms, which involve one simple convex quadratic program at each iteration are proposed for computational solutions of this difficult optimization problem and also the problem of secure energy efficiency maximization. The latter adds further complexity due to additional optimization variables appearing in the denominator of the secrecy rate function. Numerical results confirm that the performance of the proposed computational solutions is robust against channel uncertainties.
Autors: Ali Arshad Nasir;Hoang Duong Tuan;Trung Q. Duong;H. Vincent Poor;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Nov 2017, volume: 16, issue:11, pages: 7523 - 7537
Publisher: IEEE
 
» Secure Degrees of Freedom for the MIMO Wire-Tap Channel With a Multi-Antenna Cooperative Jammer
Abstract:
In this paper, a multiple antenna wire-tap channel in the presence of a multi-antenna cooperative jammer is studied. In particular, the secure degrees of freedom (s.d.o.f.) of this channel is established, with antennas at the transmitter, antennas at the legitimate receiver, and antennas at the eavesdropper, for all possible values of the number of antennas, , at the cooperative jammer. In establishing the result, several different ranges of need to be considered separately. The lower and upper bounds for these ranges of are derived, and are shown to be tight. The achievability techniques developed rely on a variety of signaling, beamforming, and alignment techniques, which vary according to the (relative) number of antennas at each terminal and whether the s.d.o.f. is integer valued. Specifically, it is shown that, whenever the s.d.o.f. is integer valued, Gaussian signaling for both transmission and cooperative jamming, linear precoding at the transmitter and the cooperative jammer, and linear processing at the legitimate receiver, are sufficient for achieving the s.d.o.f. of the channel. By contrast, when the s.d.o.f. is not an integer, the achievable schemes need to rely on structured signaling at the transmitter and the cooperative jammer, and joint signal space and signal scale alignment. The converse is established by combining an upper bound, which allows for full cooperation between the transmitter and the cooperative jammer, with another upper bound which exploits the secrecy and - eliability constraints.
Autors: Mohamed Nafea;Aylin Yener;
Appeared in: IEEE Transactions on Information Theory
Publication date: Nov 2017, volume: 63, issue:11, pages: 7420 - 7441
Publisher: IEEE
 
» Secure Massive MIMO Relaying Systems in a Poisson Field of Eavesdroppers
Abstract:
A cooperative relay network operating in the presence of eavesdroppers, whose locations are distributed according to a homogeneous Poisson point process, is considered. The relay is equipped with a very large antenna array and can exploit maximal ratio combing in the uplink and maximal ratio transmission in the downlink. A realistic model in which the channel state information of every eavesdropper is not known is considered, as eavesdroppers tend to hide themselves in practice. The destination is thus in a much weaker position than all the eavesdroppers because it only receives the retransmitted signal from the relay. Under this setting, the security performance is investigated for two relaying protocols: amplify-and-forward and decode-and-forward. The secrecy outage probability, the connection outage probability, and the tradeoff between them, which is controlled by the source power allocation, are examined. Finally, suitable solutions for the source power (such that once the transmission occurs with high reliability, the secure risk is below a given threshold) are proposed for a tradeoff between security and reliability.
Autors: Tiep M. Hoang;Trung Q. Duong;Hoang Duong Tuan;H. Vincent Poor;
Appeared in: IEEE Transactions on Communications
Publication date: Nov 2017, volume: 65, issue:11, pages: 4857 - 4870
Publisher: IEEE
 
» Security Constrained Multi-Stage Transmission Expansion Planning Considering a Continuously Variable Series Reactor
Abstract:
This paper introduces a continuously variable series reactor (CVSR) to the transmission expansion planning (TEP) problem. The CVSR is a flexible ac transmission system (FACTS)-like device, which has the capability of controlling the overall impedance of the transmission line. However, the cost of the CVSR is about one-tenth of a similar rated FACTS device, which potentially allows large numbers of devices to be installed. The multi-stage TEP with the CVSR considering the security constraints is formulated as a mixed-integer linear programming model. The nonlinear part of the power flow introduced by the variable reactance is linearized by a reformulation technique. To reduce the computational burden for a practical large-scale system, a decomposition approach is proposed. The detailed simulation results on the IEEE 24-bus and a more practical Polish 2383-bus system demonstrate the effectiveness of the approach. Moreover, the appropriately allocated CVSRs add flexibility to the TEP problem and allow reduced planning costs. Although the proposed decomposition approach cannot guarantee global optimality, a high-level picture of how the network can be planned reliably and economically considering CVSR is achieved.
Autors: Xiaohu Zhang;Kevin Tomsovic;Aleksandar Dimitrovski;
Appeared in: IEEE Transactions on Power Systems
Publication date: Nov 2017, volume: 32, issue:6, pages: 4442 - 4450
Publisher: IEEE
 
» Security Semantics Modeling with Progressive Distillation
Abstract:
The prevalence of Android platform has attracted adversaries to craft malicious payloads for illegal profit. Such malicious artifacts are frequently reused and embedded in benign, paid apps to lure victims that the apps have been cracked for free. To discover these fraudulent apps, administrators of app markets desire an automated scanning process to maintain the health of app ecosystem. However, conventional approaches cannot be efficiently applied due to the lack of a scalable, effective approach to malware characteristics aggregation. On the other hand, the vast number of apps significantly increases the analysis complexity. In this paper, we propose Petridish which generates discriminative models against the repacked malicious apps. These representative models of malicious semantics can be progressively distilled with malign and benign samples. These models can further detect repacked malicious apps. Our experiment shows that, after two retraining rounds, Petridish achieved an average of 28 percent progressive detection improvement from 63 to 91.2 percent for the large families, exceeding 38 test samples in size. With noise reduction, it accomplished 88 percent detection rate and 1.7 percent false alarm rate. The characteristics aggregation approach will become critical in the age of app explosion.
Autors: Zong-Xian Shen;Chia-Wei Hsu;Shiuhpyng Winston Shieh;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Nov 2017, volume: 16, issue:11, pages: 3196 - 3208
Publisher: IEEE
 
» Segmental Prediction for Video Coding
Abstract:
The emerging standards for screen content coding (SCC) and 3D video coding known as High Efficiency Video Coding (HEVC)-SCC and 3D-HEVC, respectively, have been developed as extensions of HEVC. Compared with camera-captured video, screen content video and depth maps usually contain significantly fewer colors or sample intensities and much sharper edges in a frame. In this paper, a new coding method named segmental prediction is proposed to code screen content and depth maps more efficiently. First, samples in a prediction block are classified into several segments according to the sample intensities. Second, a particular predictor is calculated for each segment. Then an offset for a segment is derived at the encoder side and signaled to the decoder side. Finally, a single sample value is assigned to each segment in the reconstructed block. The experimental results show that the proposed approach can achieve a 2.2% average Bjontegaard Distortion-rate (BD-rate) saving under the HEVC-SCC common test conditions (CTCs) for sequences of the category YUV, text and graphics with motion, 1080p, with the all intra configuration. It can also achieve a 0.6% average BD-rate saving for synthesized views under the 3D-HEVC CTCs with the random access configuration.
Autors: Kai Zhang;Jicheng An;Han Huang;Jian-Liang Lin;Yu-Wen Huang;Shaw-Min Lei;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Nov 2017, volume: 27, issue:11, pages: 2425 - 2436
Publisher: IEEE
 
» Segmentation of Skeleton and Organs in Whole-Body CT Images via Iterative Trilateration
Abstract:
Whole body oncological screening using CT images requires a good anatomical localisation of organs and the skeleton. While a number of algorithms for multi-organ localisation have been presented, developing algorithms for a dense anatomical annotation of the whole skeleton, however, has not been addressed until now. Only methods for specialised applications, e.g., in spine imaging, have been previously described. In this work, we propose an approach for localising and annotating different parts of the human skeleton in CT images. We introduce novel anatomical trilateration features and employ them within iterative scale-adaptive random forests in a hierarchical fashion to annotate the whole skeleton. The anatomical trilateration features provide high-level long-range context information that complements the classical local context-based features used in most image segmentation approaches. They rely on anatomical landmarks derived from the previous element of the cascade to express positions relative to reference points. Following a hierarchical approach, large anatomical structures are segmented first, before identifying substructures. We develop this method for bone annotation but also illustrate its performance, although not specifically optimised for it, for multi-organ annotation. Our method achieves average dice scores of 77.4 to 85.6 for bone annotation on three different data sets. It can also segment different organs with sufficient performance for oncological applications, e.g., for PET/CT analysis, and its computation time allows for its use in clinical practice.
Autors: Marie Bieth;Loic Peter;Stephan G. Nekolla;Matthias Eiber;Georg Langs;Markus Schwaiger;Bjoern Menze;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Nov 2017, volume: 36, issue:11, pages: 2276 - 2286
Publisher: IEEE
 
» Seismic Random Noise Attenuation Using Synchrosqueezed Wavelet Transform and Low-Rank Signal Matrix Approximation
Abstract:
Random noise elimination acts as an important role in the seismic signal processing. Generally, noise in seismic data can be divided into two categories of coherent and incoherent or random noise. Suppression of wide-band noise which is characterized by random oscillation in seismic data over time is one of the challenging issues in the seismic data processing. This paper describes a new noise suppression algorithm for seismic data denoising. The seismic data, trace-by-trace are transformed into sparse subspace using the synchrosqueezed wavelet transform, then the obtained sparse time-frequency representation is decomposed into semilow-rank and sparse components using the Optshrink algorithm. Finally, the denoised seismic trace can be recovered by back-transforming the semilow-rank component to the time domain using inverse synchrosqueezed wavelet transform. The proposed method is assessed using a single synthetic seismic trace and a synthetic seismic section with two crossover linear and curve events with two discontinuities that are buried in the random noise. We have also evaluated the method using a prestack real seismic data set from an oil field in the southwest of Iran. A comparison is performed between the proposed method and the semisoft GoDec algorithm, classical f-x singular spectrum analysis, and prediction Wiener filter. The results visually and quantitatively confirmed the superiority of the proposed method in contrast to the other well-established noise reduction methods.
Autors: Rasoul Anvari;Mohammad Amir Nazari Siahsar;Saman Gholtashi;Amin Roshandel Kahoo;Mokhtar Mohammadi;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Nov 2017, volume: 55, issue:11, pages: 6574 - 6581
Publisher: IEEE
 
» Selecting Power-Efficient Signal Features for a Low-Power Fall Detector
Abstract:
Falls are a serious threat to the health of older people. A wearable fall detector can automatically detect the occurrence of a fall and alert a caregiver or an emergency response service so they may deliver immediate assistance, improving the chances of recovering from fall-related injuries. One constraint of such a wearable technology is its limited battery life. Thus, minimization of power consumption is an important design concern, all the while maintaining satisfactory accuracy of the fall detection algorithms implemented on the wearable device. This paper proposes an approach for selecting power-efficient signal features such that the minimum desirable fall detection accuracy is assured. Using data collected in simulated falls, simulated activities of daily living, and real free-living trials, all using young volunteers, the proposed approach selects four features from a set of ten commonly used features, providing a power saving of 75.3%, while limiting the error rate of a binary classification decision tree fall detection algorithm to 7.1%.
Autors: Changhong Wang;Stephen J. Redmond;Wei Lu;Michael C. Stevens;Stephen R. Lord;Nigel H. Lovell;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Nov 2017, volume: 64, issue:11, pages: 2729 - 2736
Publisher: IEEE
 
» Self-Energy Concept for the Numerical Solution of the Liouville-von Neumann Equation
Abstract:
A new numerical approach is presented for the determination of the statistical density matrix as a solution of the Liouville-von Neumann equation in center-mass coordinates. The numerical discretization is performed by utilizing a finite volume method, which leads to a discretized drift and diffusion operator. The solution is based on the eigenvector basis of the discretized diffusion operator with its corresponding eigenvalues and on the introduction of the self-energy concept. More specifically, the self-energy concept is essential to describe open-boundary problems adequately. Furthermore, this approach allows the definition of inflow and outflow conditions. The method presented is investigated with regard to the conventional Wigner transport equation and the quantum transmitting boundary method, when investigating coherent effects.
Autors: Khuram Shahzad Khalid;Lukas Schulz;Dirk Schulz;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Nov 2017, volume: 16, issue:6, pages: 1053 - 1061
Publisher: IEEE
 
» Self-Limited CBRAM With Threshold Selector for 1S1R Crossbar Array Applications
Abstract:
In this letter, we demonstrate a self-limited conductive-bridging random access memory (CBRAM) that removes the necessity for external current compliance in a one selector–one resistor (1S1R) architecture. The standard Ge2Sb2Te5 (GST) is used as a CBRAM switching layer. In addition, Te-rich GST is also considered. Their performance is then compared. Both samples exhibit self-limited on-current characteristics, and the on-currents of the standard GST and Te-rich GST are ~300 and , respectively. The observed self-limited characteristics are caused by the Te in the GST layer because in the presence of Te, Cu tends to form a more stable CuTe phase that restrict Cu filament growth. Furthermore, to confirm the feasibility of crossbar array applications, the 1S1R device is evaluated using a Ag/TiO2-based threshold selector device reported in our previous work. Hence, we confirm leakage current reduction, a uniform resistance distribution, and stable retention characteristics in the 1S1R configuration with no external current compliance.
Autors: Jeonghwan Song;Jiyong Woo;Seokjae Lim;Solomon Amsalu Chekol;Hyunsang Hwang;
Appeared in: IEEE Electron Device Letters
Publication date: Nov 2017, volume: 38, issue:11, pages: 1532 - 1535
Publisher: IEEE
 
» Self-Regulated Reconfigurable Voltage/Current-Mode Inductive Power Management
Abstract:
A reconfigurable power management structure for inductive power delivery has been proposed by adaptively employing either resonant voltage or current mode (VM or CM) to improve the inductive power transmission performance against coils’ coupling distance (d), orientation (), and load impedance (RL) variations. At the presence of these variations, unlike conventional VM and CM power managements with poor voltage- and power-conversion efficiencies (VCE and PCE), respectively, the proposed voltage/current-mode inductive power management (VCIPM) chip can achieve high VCE by automatically switching to CM when the receiver (Rx) coil voltage (VR) is smaller than the required load voltage (VL), and achieve high PCE by operating in VM when VR > VL. In addition, since VM and CM are only suitable for small and large RL within the range of hundreds of ohms and above, respectively, the VCIPM chip can extend the RL range. The VCIPM chip also eliminates the need for two off-chip capacitors by performing rectification, regulation, and over-voltage protection (OVP) in one step with one off-chip capacitor. In VM, intentional reverse current is employed for both voltage regulation and OVP, while the Rx coil switching frequency (fsw) is adjusted for voltage regulation in CM. The theory behind the proposed VCIPM structure has been presented and validated by simulations and measurements. A VCIPM prototype chip was fabricated in a 0.35- 2P4M standard CMOS process occupying 0.52-mm2 active area. In measurements, the VCIPM chip, operating at 1 MHz, achieved - high VCE of 4.1 V/V for RL of 100 by operating in CM with fsw = 166.6 kHz, and extended d and from 6 to 13.5 cm (125%) and 30° to 75° (150%), respectively, compared to its VM counterpart by adaptively switching from VM to CM.
Autors: Hesam Sadeghi Gougheri;Mehdi Kiani;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Nov 2017, volume: 52, issue:11, pages: 3056 - 3070
Publisher: IEEE
 
» Self-Seeded RSOA Fiber Cavity Laser and the Role of Rayleigh Backscattering—An Analytical Model
Abstract:
Reflective semiconductor optical amplifiers (RSOAs) in a fiber cavity are attractive self-seeding optical sources for wavelength division multiplexed (WDM) access networks. This paper presents an analytical model of this fiber cavity laser (FCL). The model accounts for the Rayleigh backscattering (RB) of the fiber cavity as a primary mechanism of optical feedback inside the FCL. Moreover, it also includes the reflectivity of the remote node mirror. The purpose of the model is to analytically estimate the threshold RSOA gain required for the FCL to lase, by taking into account the fiber cavity length, the related attenuation and the RB. The model is suitable to experimentally characterize the Rayleigh backscattering coefficient, once the threshold gain of RSOA-FCL is measured.
Autors: Dejan M. Gvozdić;Angelina R. Totović;Jasna V. Crnjanski;Marko M. Krstić;Simon A. Gebrewold;Juerg Leuthold;Milan L. Mašanović;
Appeared in: Journal of Lightwave Technology
Publication date: Nov 2017, volume: 35, issue:22, pages: 4845 - 4850
Publisher: IEEE
 
» Semantic Development and Integration of Standards for Adoption and Interoperability
Abstract:
Semantic applications can help commercial applications perform quickly and reliably by improving ecosystem interoperability. Converting and integrating current standards specifications to OWL models could support the adoption of semantic models, as well as machine-processable standards compliance and data interoperability.
Autors: Jack Hodges;Kimberly García;Steven Ray;
Appeared in: Computer
Publication date: Nov 2017, volume: 50, issue:11, pages: 26 - 36
Publisher: IEEE
 
» Semisupervised PolSAR Image Classification Based on Improved Cotraining
Abstract:
In order to obtain good classification performance of polarimetric synthetic aperture radar (PolSAR) images, many labeled samples are needed for training. However, it is difficult, expensive, and time-consuming to obtain labeled samples in practice. On the other hand, unlabeled samples are substantially cheaper and more plentiful than labeled ones. In addressing this issue, semisupervised learning techniques are proposed. In this paper, a novel semisupervised algorithm based on an improved cotraining process is proposed for PolSAR image classification. First, we propose an indirect analysis strategy to analyze the nature of sufficiency and independence between two different views for cotraining. Then, an improved cotraining process with a new sample selection strategy is presented, which can effectively take advantage of unlabeled samples to improve the performance of classification, particularly when labeled samples are limited. Finally, a new postprocess method based on a similarity principle and a superpixel algorithm is developed to improve the consistency of the classification. Experimental results on three real PolSAR images show that our proposed method is an effective classification method, and is superior to other traditional methods.
Autors: Wenqiang Hua;Shuang Wang;Hongying Liu;Kun Liu;Yanhe Guo;Licheng Jiao;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Nov 2017, volume: 10, issue:11, pages: 4971 - 4986
Publisher: IEEE
 
» Sensing Dynamic Forces by Fe–Ga in Compression
Abstract:
This paper concerns the sensing of dynamic force/stress by means of a measuring system based on the use of an Fe–Ga sample (Galfenol) coupled to a magnetic circuit. The study is focused on the measurement of the effective magnetic field, detected at the rod specimen surface, and its variation under time-dependent applied sinusoidal stress , oscillating at frequencies between 5 and 20 Hz at different values of applied bias field (2.5 kA/m kA/m). For the considered frequency and range, the measured tends to linearly depend on , in contrast with the corresponding induction variation behavior (), where hysteresis effects appear. With in the range of ±15 MPa, we obtain 0.06 MPa resolution in the determination of the alternating stress , a result pointing to the effectiveness and sensitivity of this Galfenol-based method for detection and measurement of time-dependent stresses.
Autors: Mauro Zucca;Pasquale Mei;Enzo Ferrara;Fausto Fiorillo;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 4
Publisher: IEEE
 
» Sequential Necessary and Sufficient Conditions for Capacity Achieving Distributions of Channels With Memory and Feedback
Abstract:
We derive sequential necessary and sufficient conditions for any channel input conditional distribution to maximize the finite-time horizon directed information defined by , where , for channel distributions and , where and are the channel input and output random processes, and is a finite non-negative integer. We apply the necessary and sufficient conditions to application examples of time-varying channels with memory to derive recursive closed form expressions of the optimal distributions, which maximize the finite-time horizon directed information. Furthermore, we derive the feedback capacity from the asymptotic properties of the optimal distributions by investigating the limit without any ´ a p- iori assumptions, such as stationarity, ergodicity, or irreducibility of the channel distribution. The framework based on sequential necessary and sufficient conditions can be easily applied to a variety of channels with memory, beyond the ones considered in this paper.
Autors: Photios A. Stavrou;Charalambos D. Charalambous;Christos K. Kourtellaris;
Appeared in: IEEE Transactions on Information Theory
Publication date: Nov 2017, volume: 63, issue:11, pages: 7095 - 7115
Publisher: IEEE
 
» Shaped Beam Synthesis Based on Superposition Principle and Taylor Method
Abstract:
A technique for the synthesis of shaped beam radiation patterns is proposed. The new synthesis method is based on superposition principle and Taylor method. The method may control the sidelobe level of the shaped beam. The approach includes four steps: 1) get the distribution of pencil beam array with low sidelobe by Taylor method; 2) let the beams scan as a phased array to the specific angles according to the requirement of the shaped beam, The sum pattern is close to the shaping beam; 3) determine the value of angles and weights; and 4) count the distribution of the shaped beam array according to the new array factor function. Numerical results are provided to assess the capabilities of the proposed design method. The method develops an effective approach for the synthesis of shaped beams via uniform linear arrays. Both the ripple and sidelobe level of shaped beam may be controlled by the new synthesis method.
Autors: J.-Y. Li;Y.-X. Qi;S.-G. Zhou;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Nov 2017, volume: 65, issue:11, pages: 6157 - 6160
Publisher: IEEE
 
» Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees
Abstract:
Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems.
Autors: Matija Štrbac;Milica Isaković;Minja Belić;Igor Popović;Igor Simanić;Dario Farina;Thierry Keller;Strahinja Došen;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Nov 2017, volume: 25, issue:11, pages: 2133 - 2145
Publisher: IEEE
 
» Signal Dependent Transform Based on SVD for HEVC Intracoding
Abstract:
Transform is used to compact the energy of the blocks into a small number of coefficients and is widely used in recent image/video coding standards. In the latest video coding standard high efficiency video coding (HEVC), a combination of discrete cosine transform (DCT) and discrete sine transform (DST) is adopted to transform the residuals from intra prediction. Since the DCT and DST are the fixed transforms that are derived from the Gauss-Markov model, some of residual blocks may not be compacted well by the DCT/DST. In this paper, we propose a signal dependent transform based on singular value decomposition (SVD) for HEVC intracoding. The proposed transform (SDT-SVD) is derived by performing SVD on the synthetic block and applied to the residual block considering the structural similarity between them. Furthermore, we extend SDT-SVD to template matching prediction (TMP) to further improve the intracoding performance. Experimental results show that the proposed transform on angular intra prediction (AIP) outperforms the latest HEVC reference software with a bit rate reduction of 1.0% on average and it can be up to 2.1%. When the proposed transform is extended to TMP-based intracoding, the overall bit rate reduction is 2.7% on average and can be up to 5.8%.
Autors: Tao Zhang;Haoming Chen;Ming-Ting Sun;Debin Zhao;Wen Gao;
Appeared in: IEEE Transactions on Multimedia
Publication date: Nov 2017, volume: 19, issue:11, pages: 2404 - 2414
Publisher: IEEE
 
» Signal Processing Is More than Its Beloved Name [President's Message]
Abstract:
Autors: Rabab Ward;
Appeared in: IEEE Signal Processing Magazine
Publication date: Nov 2017, volume: 34, issue:6, pages: 5 - 7
Publisher: IEEE
 
» Signals and Signal Processing: The Invisibles and the Everlastings [From the Editor]
Abstract:
Autors: Min Wu;
Appeared in: IEEE Signal Processing Magazine
Publication date: Nov 2017, volume: 34, issue:6, pages: 4 - 7
Publisher: IEEE
 
» Simple Ears Inspire Frequency Agility in an Engineered Acoustic Sensor System
Abstract:
Standard microphones and ultrasonic devices are generally designed with a static and flat frequency response in order to address multiple acoustic applications. However, they may not be flexible or adaptable enough to deal with some requirements. For instance, when operated in noisy environments such devices may be vulnerable to wideband background noise which will require further signal processing techniques to remove it, generally relying on digital processor units. In this paper, we consider if microphones and ultrasonic devices could be designed to be sensitive only at selected frequencies of interest, whilst also providing flexibility in order to adapt to the different signals of interest and to deal with environmental demands. This research exploits the concept where the “transducer becomes part of the signal processing chain” by exploring feedback processes between mechanical and electrical mechanisms that together can enhance peripheral sound processing. This capability is present within a biological acoustic system, namely in the ears of certain moths. That was used as the model of inspiration for a smart acoustic sensor system which provides dynamic adaptation of its frequency response with amplitude and time dependence according to the input signal of interest.
Autors: José Guerreiro;Joseph C. Jackson;James F. C. Windmill;
Appeared in: IEEE Sensors Journal
Publication date: Nov 2017, volume: 17, issue:22, pages: 7298 - 7305
Publisher: IEEE
 
» Simple High-Performance Metal-Plating Procedure for Stereolithographically 3-D-Printed Waveguide Components
Abstract:
This letter presents a simple and cheap metal-plating procedure for plastic 3-D printed microwave components. The devices are built using a Stereolithographic printer and then metalized by a two-step process consisting in a silver-painted substrate followed by copper electrodeposition. The method achieves good adhesion of the metal to the plastic body and high conductivity. Resonators and -band filters have been fabricated and tested, showing excellent performance in terms of dimensional accuracy and low loss, with quality factors better than 6500. The technique can be usefully employed for fast and cheap prototyping of microwave components at least up to the -band.
Autors: Marco Dionigi;Cristiano Tomassoni;Giuseppe Venanzoni;Roberto Sorrentino;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Nov 2017, volume: 27, issue:11, pages: 953 - 955
Publisher: IEEE
 
» SimRank on Uncertain Graphs
Abstract:
SimRank is a similarity measure between vertices in a graph. Recently, many algorithms have been proposed to efficiently evaluate SimRank similarities. However, the existing algorithms either overlook uncertainty in graph structures or depends on an unreasonable assumption. In this paper, we study SimRank on uncertain graphs. Following the random-walk-based formulation of SimRank on deterministic graphs and the possible world model of uncertain graphs, we first define random walks on uncertain graphs and show that our definition of random walks satisfies Markov’s property. We formulate our SimRank measure based on random walks on uncertain graphs. We discover a critical difference between random walks on uncertain graphs and random walks on deterministic graphs, which makes all existing SimRank computation algorithms on deterministic graphs inapplicable to uncertain graphs. For SimRank computation, we consider computing both single-pair SimRank and single-source top- SimRank. We propose three algorithms, namely the sampling algorithm with high efficiency, the two-phase algorithm with comparable efficiency and higher accuracy, and a speeding-up algorithm with much higher efficiency. Meanwhile, we present an optimized algorithm for efficient computing the single-source top- SimRank. The experimental results verify the effectiveness of our SimRank measure and the efficiency of the proposed SimRank computation algorithms.
Autors: Rong Zhu;Zhaonian Zou;Jianzhong Li;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Nov 2017, volume: 29, issue:11, pages: 2522 - 2536
Publisher: IEEE
 
» Simulating the Canopy Reflectance of Different Eucalypt Genotypes With the DART 3-D Model
Abstract:
Finding suitable models of canopy reflectance in forward simulation mode is a prerequisite for their use in inverse mode to characterize canopy variables of interest, such as leaf area index (LAI) or chlorophyll content. In this study, the accuracy of the three-dimensional reflectance model DART (Discrete Anisotropic Radiative Transfer) was assessed for canopies of different genotypes of Eucalyptus, having distinct biophysical and biochemical characteristics, to improve the knowledge on how these characteristics are influencing the reflectance signal as measured by passive orbital sensors. The first step was to test the model suitability to simulate reflectance images in the visible and near infrared. We parameterized DART model using extensive measurements from Eucalyptus plantations including 16 contrasted genotypes. Forest inventories were conducted and leaf, bark, and forest floor optical properties were measured. Simulation accuracy was evaluated by comparing the mean top of canopy (TOC) bidirectional reflectance of DART with TOC reflectance extracted from a Pleiades very high resolution satellite image. Results showed a good performance of DART with mean reflectance absolute error lower than 2%. Intergenotype reflectance variability was correctly simulated, but the model did not succeed at catching the slight spatial variation for a given genotype, excepted when large gaps appeared due to tree mortality. The second step consisted of sensitivity analysis to explore which biochemical or biophysical characteristics influenced more the canopy reflectance between genotypes. Perspectives for using DART model in inversion mode in these ecosystems were discussed.
Autors: Julianne de Castro Oliveira;Jean-Baptiste Féret;Flávio Jorge Ponzoni;Yann Nouvellon;Jean-Philippe Gastellu-Etchegorry;Otávio Camargo Campoe;José Luiz Stape;Luiz Carlos Estraviz Rodriguez;Guerric le Maire;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Nov 2017, volume: 10, issue:11, pages: 4844 - 4852
Publisher: IEEE
 
» Simulating the Effects of Skin Thickness and Fingerprints to Highlight Problems With Non-Invasive RF Blood Glucose Sensing From Fingertips
Abstract:
The non-invasive measurement of blood glucose is a popular research topic where RF/microwave sensing of glucose is one of the promising methods in this area. From the many available measurement sites in the human body, fingertips appear to be a good choice due to a good amount of fresh blood supply and homogeneity in terms of biological layers present. The non-invasive RF measurement of blood glucose relies on the detection of the change in the permittivity of the blood using a resonator as a sensor. However, the change in the permittivity of blood due to the variation in glucose content has a limited range resulting in a very small shift in the sensor’s frequency response. Any inconsistency between measurements may hinder the measurement results. These inconsistencies mostly arise from the varied thickness of the biological layers and variation of fingerprints that are unique to every human. Therefore, the effects of biological layers and fingerprints in fingertips were studied in detail and are reported in this paper.
Autors: Volkan Turgul;Izzet Kale;
Appeared in: IEEE Sensors Journal
Publication date: Nov 2017, volume: 17, issue:22, pages: 7553 - 7560
Publisher: IEEE
 
» Simulation and Analysis of Three-Dimensional Electromagnetism, Heat Transfer, and Gas Flow for Flow-Levitation System
Abstract:
Magnetic levitation systems are influenced by an intense demand to gain greater feature sizes of metal nanoparticles and to increase the production efficiency for the flow-levitation (FL) method. This paper presents a systematic stability and temperature analysis of the process during the induction heating based on ANSYS. The comprehensive model was a liquid aluminum droplet levitated electromagnetically in an axisymmetric magnetic field induced by different sets of coaxial circular coils. First, we developed an optimized coil with a double helix structure to compare the force applied to the sample, electric field distribution, and temperature distribution in the eddy current field with an initial coil structure. The optimized coil has a more stable and efficient induction heating process for the FL method. We also utilized the optimized coil geometry to predict the maximum parameters of the electromagnetic induction system used to fabricate Al nanoparticles. The results from this approach shows that the turns = 2 + 3, D = 24 mm, I = ∼350 A, d = 1∼2 mm, with an equilibrium coefficient k of 0.30, are the maximum and optimal settings in the frequency of 400 kHz induction heating process.
Autors: Xiaoyang Zheng;Jiangshan Luo;Kai Li;Yong Yi;Kai Du;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Nov 2017, volume: 16, issue:6, pages: 1106 - 1114
Publisher: IEEE
 
» Simulation of LSPR Sensor Based on Exposed-Core Grapefruit Fiber With a Silver Nanoshell
Abstract:
A localized surface plasmon resonance (LSPR) sensor based on exposed-core grapefruit fiber (EC-GF) with a silver nanoshell (SNS) is presented. The SNS, composed of a dielectric core coated with a thin silver layer, is placed at the exposed section of the EC-GF as the sensing channel to avoid the metal coating, and then deposited with the analyte to avert the liquid filling. Two orthogonal polarized resonance peaks (x-polarized and y-polarized) can be observed due to the birefringence and each polarization exhibits multipolar plasmon resonances, which can realize the cross reference. Due to the good features of the SNS, the position of the LSPR band can be tuned in a broad range, from 2100 to 4020 nm, making the proposed sensor of great importance for biosensing. An extremely high sensitivity 7903.03 nm/RIU is obtained in the sensing range of 1.33-1.42, almost twice as high as the same type works. The influence of the SNS structure on the sensor's performance is also investigated numerically.
Autors: Xianchao Yang;Ying Lu;Baolin Liu;Jianquan Yao;
Appeared in: Journal of Lightwave Technology
Publication date: Nov 2017, volume: 35, issue:21, pages: 4728 - 4733
Publisher: IEEE
 
» Simulation-Based Interpretation and Alignment of High-Resolution Optical and SAR Images
Abstract:
The successful alignment of optical and synthetic aperture radar (SAR) satellite data requires that we account for the effects of sensor-specific geometric distortion, which is a consequence of the different imaging concepts of the sensors. This paper introduces SimGeoI, a simulation framework for the object-related interpretation of optical and SAR images, as a solution to this problem. Using metainformation from the images and a digital surface model as input, the processor follows the steps of scene definition, ray tracing, image generation, geocoding, interpretation layer generation, and image part extraction. Thereby, for the first time, object-related sections of optical and SAR images are automatically identified and extracted in world coordinates under consideration of three-dimensional object shapes. A case study for urban scenes in Munich and London, based on WorldView-2 images and high-resolution TerraSAR-X data, confirms the potential of SimGeoI in the context of a perspective-independent and object-focused analysis of high-resolution satellite data.
Autors: Stefan Auer;Isabel Hornig;Michael Schmitt;Peter Reinartz;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Nov 2017, volume: 10, issue:11, pages: 4779 - 4793
Publisher: IEEE
 
» Simultaneous Angular Rate Estimates Extracted From a Single Axisymmetric Resonator
Abstract:
An axisymmetric planar microelectromechanical (MEM) resonator resonator is configured, such that the elliptical pair of modes near 13.5kHz, and the pair of modes near 23.8kHz, are both degenerate, i.e., the frequency difference within a given pair of modes is close to the resonance bandwidth. This configuration enables not only the exploitation of the standard elliptical pair of modes for angular rate sensing but also permits the operation of the pair of modes as a high-sensitivity Coriolis vibratory gyro. The performance for each pair of modes separately acting as a vibratory gyro is quantified, however, the control architecture also facilitates the simultaneous operation of both pairs of modes. In this scenario, two measurements of angular rate are extracted from a single resonator and although the short-term rate noise associated with the pair is an order of magnitude larger than the rate extracted from the pair, the long-term drift in the rate offsets are correlated. Thus, a filter architecture for fusing the rate measurements is proposed and it is shown how the derived rate estimate possesses superior offset stability but also retains the low short-term noise associated with the rate measurement from the pair.
Autors: Howard Ge;Robert M’Closkey;
Appeared in: IEEE Sensors Journal
Publication date: Nov 2017, volume: 17, issue:22, pages: 7460 - 7469
Publisher: IEEE
 
» Simultaneous Evaluation of Conductive/Near-Field Noise Suppression in Co-Zr-Nb Film Using Magnetic Circuit
Abstract:
This paper discusses the integrated evaluation of the conductive and near-field noise suppression using magnetic circuit network. The proposed magnetic circuit evaluated the ferromagnetic resonance (FMR) loss and near-field intensity simultaneously and agreed with the measured value. The validity of the evaluation is successfully clarified. It is clarified that the near-field shielding effectiveness is maximized at the intrinsic FMR frequency, because the reluctance of the magnetic film is minimized. It is also clarified that the conductive noise suppression is maximized and the near-field shielding effectiveness is simultaneously minimized at the shifted FMR frequency by the demagnetizing field, because the magnetic circuit resonates. These results demonstrate that the proposed magnetic network model is of great usefulness for developing the integrated design method of the magnetic film-type noise suppressor.
Autors: Sho Muroga;Yasushi Endo;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 4
Publisher: IEEE
 
» Simultaneous Optimization of Airspace Congestion and Flight Delay in Air Traffic Network Flow Management
Abstract:
Air traffic flow management (ATFM) aims to facilitate the utilization of airspace and airport resources and is critical in air transportation systems. During the past decades, several challenging problems have arisen from this domain and attracted intensive studies. This paper addresses the problem of alleviating the airspace congestion and reducing the flight delays in ATFM simultaneously. We formulate this problem as a multi-objective air traffic network flow optimization (MATNFO) problem. In this MATNFO model, comprehensive ATFM actions, for instance, ground-holding, airborne-holding, rerouting, and speed control, are considered. Meanwhile, a systematic approach, namely route and time-slot assignment (RTA) algorithm, is developed to solve the MATNFO problem. The idea of divide-and-conquer is embedded in the algorithm by sequentially applying both route searching module and time refinement module. Furthermore, for the sake of efficiency, a pre-selection operator is proposed as one heuristic strategy to identify promising solutions and reduce the search space by defining a sector equilibrium metric. Experiments on real data of the Chinese airspace show that the RTA algorithm outperforms an existing competitor and three related multi-objective evolutionary algorithms. In addition, RTA is competent for high-quality real-time air traffic network flow assignment.
Autors: Kai-Quan Cai;Jun Zhang;Ming-Ming Xiao;Ke Tang;Wen-Bo Du;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Nov 2017, volume: 18, issue:11, pages: 3072 - 3082
Publisher: IEEE
 
» Simultaneous Ultrasonic Measurement of Thickness and Speed of Sound in Elastic Plates Using Coded Excitation Signals
Abstract:
Layer thickness and the speed of sound are important parameters for nondestructive testing applications. If one of the parameters is known, the other one can be determined by simple time-of-flight (TOF) measurement of ultrasound. However, often these parameters are both unknown. In this contribution, we examine and adapt ultrasonic imaging techniques using coded excitation signals to simultaneously measure the thickness and the speed of sound of homogeneous elastic plates of unknown material. Good axial resolution is required to measure thin samples. We present a new approach for transmission signal conditioning to improve axial resolution. This conditioning consists of enhancing spectral components that are damped by the transducer prior to transmit. Due to the long duration of coded excitation signals, pulse compression techniques are required for TOF measurements. Common pulse compression filters are discussed, and appropriate filtering of the compression waveform is designed to keep the sidelobe level (SLL) acceptably low. An experimental assessment of the presented measurement techniques reveals that the signal conditioning substantially increases the axial resolution. However, a tapered Wiener filter should be used for the best tradeoff between SLL and axial resolution. We used the proposed method to measure different plates of steel, aluminum, and polymethylmethacrylate of various thicknesses, and the results show very good agreement with the reference values, which we obtained with a micrometer screw and by standard TOF measurement, respectively. The relative error for the plate thickness is smaller than 2.2% and that for the speed of sound is smaller than 3%. It is remarkable that plate thickness could be measured down to 60% of the wavelength.
Autors: Daniel A. Kiefer;Michael Fink;Stefan J. Rupitsch;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Nov 2017, volume: 64, issue:11, pages: 1744 - 1757
Publisher: IEEE
 
» Single Sample Fictitious Play
Abstract:
This paper is concerned with distributed learning and optimization in large-scale settings. The well-known fictitious play (FP) algorithm has been shown to achieve Nash equilibrium learning in certain classes of multiagent games. However, FP can be computationally difficult to implement when the number of players is large. Sampled FP (SFP) is a variant of FP that mitigates the computational difficulties arising in FP by using a Monte Carlo (i.e., sampling based) approach. Despite its computational advantages, a shortcoming of SFP is that the number of samples that must be drawn at each iteration grows without bound as the algorithm progresses. In this paper, we propose single sample FP (SSFP)—A variant of SFP in which only one sample needs to be drawn in each round of the algorithm. Convergence of SSFP to the set of Nash equilibria is proven. Simulation results show the performance of SSFP is comparable to that of SFP, despite drawing far fewer samples.
Autors: Brian Swenson;Soummya Kar;João Xavier;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Nov 2017, volume: 62, issue:11, pages: 6026 - 6031
Publisher: IEEE
 
» Single-Camera-Based Method for Step Length Symmetry Measurement in Unconstrained Elderly Home Monitoring
Abstract:
Objective: single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes. Methods: according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking. Results: Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects’ normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%. Conclusion: Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking. Significance: This demonstrates our method is applicable for elders’ daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.
Autors: Xi Cai;Guang Han;Xin Song;Jinkuan Wang;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Nov 2017, volume: 64, issue:11, pages: 2618 - 2627
Publisher: IEEE
 
» Single-Layered Circularly Polarized Substrate-Integrated Waveguide Horn Antenna Array
Abstract:
In this communication, a circularly polarized (CP) substrate-integrated waveguide horn antenna is proposed and studied. The CP horn antenna is implemented on a single-layer substrate with a thickness of at the center frequency (1.524 mm) for 24 GHz system applications. It comprises of an integrated phase controlling and power dividing structure, two waveguide antennas, and an antipodal linearly tapered slot antenna. With such a phase controlling and power dividing structure fully integrated inside the horn antenna, two orthogonal electric fields of the equal amplitude with 90° phase difference are achieved at the aperture plane of the horn antenna, thus, yielding an even effective circular polarization in a compact single-layered geometry. The measured results of the prototyped horn antenna exhibit a 5% bandwidth (23.7–24.9 GHz) with an axial ratio below 3 dB and a VSWR below 2. The gain of the antenna is around 8.5 dBi.
Autors: Yifan Yin;Behnam Zarghooni;Ke Wu;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Nov 2017, volume: 65, issue:11, pages: 6161 - 6166
Publisher: IEEE
 
» Single-Source Multiple-Coil Homogeneous Induction Heating
Abstract:
This paper proposes and implements an approach to achieve homogeneous heating in a single-source multiple-coil induction heating system. In a traditional induction heating system, one of the key disadvantages is the inhomogeneous heating effect. In particular, the heating power concentrates on a small ring area of the pan, while the outer part receives much lower power. The proposed induction heating system consists of two concentric coils with its compensated capacitors connecting in series, respectively. Currents in the two coils are controlled by newly employing the magnetic resonant coupling mechanism so that the heating power distribution in the inner and outer parts of the pan can be adjusted accordingly. Therefore, the proposed induction heating can achieve homogeneity and simplicity simultaneously by optimizing the operating frequency of only one inverter. Both the simulation and experimental results are given to validate the feasibility of the proposed homogeneous induction heating.
Autors: Wei Han;K. T. Chau;Zhen Zhang;Chaoqiang Jiang;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 6
Publisher: IEEE
 
» Single-Turn Magnet With an Additional Balanced Winding and Flux Concentrators
Abstract:
The balanced winding displaced in the cavity, the magnet provides the possibility for obtaining the stronger magnet field without enhancing mechanical stresses in the conductors. The model of such a system is the single-turn magnet with an additional triple-thread spiral winding. The equilibrium condition with respect to the radial force takes place at definite values of the axial current and pitch of the turns. In order to decrease the transverse field provoking the azimuthal force, the correction system in the form of cylindrical conductors with slits has been used. The discharging of the end part of the additional winding from the axial force is achieved using the flat concentrators of the flux.
Autors: German Abramovich Shneerson;Kirill Alexandrovich Danilin;Alexey Pavlovich Nenashev;Anatoly Alexeevich Parfentiev;Artem Anatolievich Pozdeev;Dmitry Alexandrovich Dyogtev;Dmitry Petrov;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Nov 2017, volume: 45, issue:11, pages: 3038 - 3041
Publisher: IEEE
 
» SiRF 2018 [RWW]
Abstract:
Presents information on the SiRF 2018 conference.
Autors: Dietmar Kissinger;
Appeared in: IEEE Microwave Magazine
Publication date: Nov 2017, volume: 18, issue:7, pages: 23 - 104
Publisher: IEEE
 
» Site Preference and Hyperfine Structure in Doped Z-Type Hexaferrite Ba1.5Sr1.5Co2(Fe1–xAlx)24O41 Investigated by Mössbauer Spectroscopy
Abstract:
The Ba1.5Sr1.5Co2(Fe1–xAlx)24O41 (x = 0, 0.01, 0.03, and 0.05) polycrystalline samples were synthesized by the polymerizable complex method. Based on the Rietveld refinement, the crystal structures of samples were found to be single phased and determined to be rhombohedral with space group of P63/mmc. The hysteresis curves of these samples were measured under 20 kOe at 295 K, showing that they were not saturated with increasing Al ion contents because spin structure was modified due to the reduction of magnetic anisotropy. With increasing Al ions contents, the value of M20kOe decreases due to the preferential occupation of non-magnetic Al ions in the up-spin site, while Hc increases. The Mössbauer spectra of the samples were obtained at 295 K, and analyzed as six distinguishable sextets (4f, 4f, 12k, 4f, 12k, and 2d) below due to the superposition of ten sextets of Fe sites corresponding to the Z-type hexagonal ferrite. The occupation number of up-spin site decreases with increasing Al ions. This suggests that the Al ions preferentially occupy the tetrahedral sublattices, leading to decrease in .
Autors: Jung Tae Lim;Chul Sung Kim;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 4
Publisher: IEEE
 
» Sizing Optimization of the Synchronous Generator and the Measurement Uncertainty Analysis
Abstract:
This paper discusses the design process of a generator to utilize waste diesel engines in the automotive industry, and presents the results of the design, analysis, and test evaluation of a 78 kW permanent magnet synchronous generator. In the initial design process using the finite-element analysis and space harmonic analysis, the number of poles and slots was determined. Then, the generator characteristics were investigated by the torque per rotor unit volume method and the , -axis equivalent circuit. Last, the optimal size of the generator was determined. This process makes it possible to design in consideration of efficiency, inductance, material cost, and temperature characteristics. A prototype of the model was created and tested with uncertainty analysis, and a comparison between the experimental results and the results of the optimization was conducted to validate the analytic approach.
Autors: Youn-Hwan Kim;Hae-Joong Kim;Sang-Yong Jung;Jae-Won Moon;
Appeared in: IEEE Transactions on Magnetics
Publication date: Nov 2017, volume: 53, issue:11, pages: 1 - 8
Publisher: IEEE
 

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