Electrical and Electronics Engineering publications abstract of: 09-2017 sorted by title, page: 7

» Discrete Nonnegative Spectral Clustering
Abstract:
Spectral clustering has been playing a vital role in various research areas. Most traditional spectral clustering algorithms comprise two independent stages (e.g., first learning continuous labels and then rounding the learned labels into discrete ones), which may cause unpredictable deviation of resultant cluster labels from genuine ones, thereby leading to severe information loss and performance degradation. In this work, we study how to achieve discrete clustering as well as reliably generalize to unseen data. We propose a novel spectral clustering scheme which deeply explores cluster label properties, including discreteness, nonnegativity, and discrimination, as well as learns robust out-of-sample prediction functions. Specifically, we explicitly enforce a discrete transformation on the intermediate continuous labels, which leads to a tractable optimization problem with a discrete solution. Besides, we preserve the natural nonnegative characteristic of the clustering labels to enhance the interpretability of the results. Moreover, to further compensate the unreliability of the learned clustering labels, we integrate an adaptive robust module with loss to learn prediction function for grouping unseen data. We also show that the out-of-sample component can inject discriminative knowledge into the learning of cluster labels under certain conditions. Extensive experiments conducted on various data sets have demonstrated the superiority of our proposal as compared to several existing clustering approaches.
Autors: Yang Yang;Fumin Shen;Zi Huang;Heng Tao Shen;Xuelong Li;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1834 - 1845
Publisher: IEEE
 
» Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification
Abstract:
This paper proposes a new framework for deep learning that has been particularly tailored for hyperspectral image classification. We learn multiple levels of dictionaries in a robust fashion. The last layer is discriminative that learns a linear classifier. The training proceeds greedily; at a time, a single level of dictionary is learned and the coefficients used to train the next level. The coefficients from the final level are used for classification. Robustness is incorporated by minimizing the absolute deviations instead of the more popular Euclidean norm. The inbuilt robustness helps combat mixed noise (Gaussian and sparse) present in hyperspectral images. Results show that our proposed techniques outperform all other deep learning methods—deep belief network, stacked autoencoder, and convolutional neural network. The experiments have been carried out on both benchmark deep learning data sets (MNIST, CIFAR-10, and Street View House Numbers) as well as on real hyperspectral imaging data sets.
Autors: Vanika Singhal;Hemant K. Aggarwal;Snigdha Tariyal;Angshul Majumdar;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Sep 2017, volume: 55, issue:9, pages: 5274 - 5283
Publisher: IEEE
 
» Distributed Adaptive Consensus Output Regulation of Network-Connected Heterogeneous Unknown Linear Systems on Directed Graphs
Abstract:
This technical note deals with output regulation of network connected linear systems under directed connection graphs. The subsystem dynamics are unknown and heterogeneous. The desired output signal, generated by a linear exosystem, is only available to some subsystems, and the others will estimate the exosystem state through the network connections for obtaining regulation errors. The exosystem is parametrised in a specific form such that it has a skew-symmetric system matrix, whose property is further explored in the estimation of exosystem state, and in the estimation of the desired feed-forward control inputs for output regulation. The unknown subsystem parameters are dealt with by the adaptive laws, driven by the estimated regulation errors. The proposed adaptive control strategy is fully distributed, in the sense that the control design only uses the information in the connected neighbourhood, without reference to the eigenstructure of the associated Laplacian matrix, as long as the connection graph is strongly connected.
Autors: Zhengtao Ding;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4683 - 4690
Publisher: IEEE
 
» Distributed Classification of Urban Congestion Using VANET
Abstract:
Vehicular ad hoc networks (VANETs) can efficiently detect traffic congestion, but detection is not enough, because congestion can be further classified as recurrent and non-recurrent congestion (NRC). In particular, NRC in an urban network is mainly caused by incidents, work zones, special events, and adverse weather. We propose a framework for the real-time distributed classification of congestion into its components on a heterogeneous urban road network using VANET. We present models built on an understanding of the spatial and temporal causality measures and trained on synthetic data extended from a real case study of Cologne. Our performance evaluation shows a predictive accuracy of 87.63% for the deterministic classification tree, 88.83% for the nave Bayesian classifier, 89.51% for random forest, and 89.17% for the boosting technique. This framework can assist transportation agencies in reducing urban congestion by developing effective congestion mitigation strategies knowing the root causes of congestion.
Autors: Ranwa Al Mallah;Alejandro Quintero;Bilal Farooq;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Sep 2017, volume: 18, issue:9, pages: 2435 - 2442
Publisher: IEEE
 
» Distributed Cooperative Two-Cell Zero-Forcing Precoding With Local Channel Correlation
Abstract:
This study focuses on local channel correlation based zero-forcing (ZF) precoding design for boosting weighted ergodic sum-rate (WESR) in the cooperative two-cell multiple-input single-output system. We first present that the WESRs of the statistical channel state information (SCSI) aided general eigenvector coordinated beamforming (SCSI-GE) and the conventional ZF beamforming with erroneous instantaneous channel state information (ICSI; eICSI-ZF) saturate to constant values at high SNR due to inter-cell interference. Motivated by this, we develop a ZF coordination framework with local SCSI requirement at the transmitter and low data-sharing backhaul load. Additionally, a low-cost but effective two-dimensional ZF precoding design called 2d-SZF is proposed, which involves only distributed computations based on the local channel correlation. Theoretical analysis and simulation results confirm that the proposed local SCSI-based 2d-SZF scheme yields the most desirable WESR while the WESRs of SCSI-GE and eICSI-ZF both saturate in the high regime of SNR, and are respectively sensitive to the level of spatial channel correlation and ICSI accuracy at finite SNR.
Autors: Jing Xu;Pinyi Ren;Chongbin Xu;Yizhai Zhang;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8086 - 8102
Publisher: IEEE
 
» Distributed Effect in High-Frequency Electroporation of Biological Cells
Abstract:
Electroporation of Jurkat T-lymphoma human cells was investigated using 10-MHz continuous waves and benchmarked against that at 100 kHz. Both cell poration and cell death were simultaneously monitored by fluorescence microscopy, and found to occur under approximately four times higher voltages at 10 MHz than that at 100 kHz. This weaker-than-expected increase in poration threshold could be explained by detailed analysis of the distributed effect often ignored in electroporation studies.
Autors: Hang Li;Agnese Denzi;Xiao Ma;Xiaotian Du;Yaqing Ning;Xuanhong Cheng;Francesca Apollonio;Micaela Liberti;James C. M. Hwang;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Sep 2017, volume: 65, issue:9, pages: 3503 - 3511
Publisher: IEEE
 
» Distributed Fault Detection Isolation and Accommodation for Homogeneous Networked Discrete-Time Linear Systems
Abstract:
This note presents a discrete-time distributed fault diagnosis and accommodation scheme for homogeneous teams of cooperative autonomous agents. Each agent estimates, via a local observer, the overall state of the team; such an estimate is used to compute both the control input to the agent itself and a set of residual vectors, sensitive to faults occurring on anyone of the teammates. The occurrence of a fault in an agent is recognized by each of the teammates, even if they are not in direct communication with each other, when the corresponding residual exceeds a suitable adaptive threshold. A recovery strategy, based on the estimate of the maximum detection time, is then applied to remove the faulty agent and to rearrange the mission. The approach is validated via numerical simulations.
Autors: Alessandro Marino;Francesco Pierri;Filippo Arrichiello;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4840 - 4847
Publisher: IEEE
 
» Distributed Global Output-Feedback Control for a Class of Euler–Lagrange Systems
Abstract:
This paper investigates the distributed tracking control problem for a class of Euler–Lagrange multiagent systems when the agents can only measure the positions. In this case, the lack of the separation principle and the strong nonlinearity in unmeasurable states pose severe technical challenges to global output-feedback control design. To overcome these difficulties, a global nonsingular coordinate transformation matrix in the upper triangular form is first proposed such that the nonlinear dynamic model can be partially linearized with respect to the unmeasurable states. And, a new type of velocity observers is designed to estimate the unmeasurable velocities for each system. Then, based on the outputs of the velocity observers, we propose distributed control laws that enable the coordinated tracking control system to achieve uniform global exponential stability. Both theoretical analysis and numerical simulations are presented to validate the effectiveness of the proposed control scheme.
Autors: Qingkai Yang;Hao Fang;Jie Chen;Zhong-Ping Jiang;Ming Cao;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4855 - 4861
Publisher: IEEE
 
» Distributed Nash Equilibrium Seeking by a Consensus Based Approach
Abstract:
In this paper, Nash equilibrium seeking among a network of players is considered. Different from many existing works on Nash equilibrium seeking in noncooperative games, the players considered in this paper cannot directly observe the actions of the players who are not their neighbors. Instead, the players are supposed to be capable of communicating with each other via an undirected and connected communication graph. By a synthesis of a leader-following consensus protocol and the gradient play, a distributed Nash equilibrium seeking strategy is proposed for the noncooperative games. Analytical analysis on the convergence of the players’ actions to the Nash equilibrium is conducted via Lyapunov stability analysis. For games with nonquadratic payoffs, where multiple isolated Nash equilibria may coexist in the game, a local convergence result is derived under certain conditions. Then, a stronger condition is provided to derive a nonlocal convergence result for the nonquadratic games. For quadratic games, it is shown that the proposed seeking strategy enables the players’ actions to converge to the Nash equilibrium globally under the given conditions. Numerical examples are provided to verify the effectiveness of the proposed seeking strategy.
Autors: Maojiao Ye;Guoqiang Hu;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4811 - 4818
Publisher: IEEE
 
» Distributed Optimal Control for Stability Enhancement of Microgrids With Multiple Distributed Generators
Abstract:
The distributed secondary control in a microgrid can be used for complementing the function of the primary droop-based control. However, its dynamic performance may be undesirable and furthermore it may introduce new less-damped modes to the system leading to oscillatory responses. Unfortunately, mechanism analysis of the undesirable dynamic performance and the possible oscillations, and more importantly, stabilization of the microgrid with the distributed secondary control have not been reported. To fill this gap, this paper first develops a unified small-signal dynamic model of the microgrid. Based on the developed model, a small-signal stability analysis is utilized to perform the aforementioned mechanism analysis. A distributed optimal controller is thereafter proposed to enhance the system stability and improve the system dynamic performance. The distributed optimal controller can coordinate multiple distributed generation units in the microgrid and exhibits robust performance under a wide range of operating conditions. Finally, theoretical analysis and time-domain simulation results on a benchmark microgrid system are provided to verify the effectiveness of the proposed methods.
Autors: Xiangyu Wu;Chen Shen;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4045 - 4059
Publisher: IEEE
 
» Distributed Power Control for the Downlink of Multi-Cell NOMA Systems
Abstract:
This paper investigates the power control problem for the downlink of a multi-cell non-orthogonal multiple access system. The problem, called P-OPT, aims to minimize the total transmit power of all the base stations subject to the data rate requirements of the users. The feasibility and optimality properties of P-OPT are characterized through a related optimization problem, called Q-OPT, which is constituted by some relevant power control subproblems. First, we characterize the feasibility of Q-OPT and prove the uniqueness of its optimal solution. Next, we prove that the feasibility of P-OPT can be characterized by the Perron-Frobenius eigenvalues of the matrices arising from the power control subproblems. Subsequently, the relationship between the optimal solutions to P-OPT and that to Q-OPT is presented, which motivates us to obtain the optimal solution to P-OPT through solving the corresponding Q-OPT. Furthermore, a distributed algorithm to solve Q-OPT is designed, and the underlying iteration is shown to be a standard interference function. According to Yates’s power control framework, the algorithm always converges to the optimal solution if exists. Numerical results validate the convergence of the distributed algorithm and quantify the improvement of our proposed method over fractional transmit power control and orthogonal multiple access schemes in terms of power consumption and outage probability.
Autors: Yaru Fu;Yi Chen;Chi Wan Sung;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6207 - 6220
Publisher: IEEE
 
» Distributed Power Optimization for Security-Aware Multi-Channel Full-Duplex Communications: A Variational Inequality Framework
Abstract:
In this paper, we consider the physical layer security issue for the multi-channel full-duplex (FD) communications in the presence of eavesdroppers. There co-exist multiple FD pairs, where the two users in each pair perform bi-directional transmissions. The secure communication is then challenged by the users’ self-interference, external interference from other pairs, and threats from the eavesdroppers. We investigate the problem from a distributed perspective and formulate the problem as a non-cooperative game, where each user optimizes their power allocation over the channels to maximize their own secrecy rate. Confirming the existence of the Nash equilibrium, we introduce an equivalent variational inequality (VI) formulation to derive the sufficient condition for the equilibrium to be unique. We then develop the iterative security-aware water-filling (ISWF) algorithm that can be implemented at each individual user in a distributed manner and prove that the condition for the unique equilibrium also claims the convergence of ISWF algorithm. Furthermore, we extend our formulation to the heterogeneous cases that there co-exist FD and half-duplex users with different security requirements in the networks, and demonstrate that they can all be covered as special cases under our formulated VI framework. Finally, we present simulation results to validate our theoretical findings.
Autors: Xiao Tang;Pinyi Ren;Zhu Han;
Appeared in: IEEE Transactions on Communications
Publication date: Sep 2017, volume: 65, issue:9, pages: 4065 - 4079
Publisher: IEEE
 
» Distributed Ramp Metering—A Constrained Discharge Flow Maximization Approach
Abstract:
Considered in this paper is a novel model-based, coordinated ramp metering strategy. It aims at maximizing the discharge flow in motorway networks by minimizing the divergence of the traffic density from its critical value caused by unknown demand flow. The suggested synthesis algorithm casts the traffic control objective into the form of an induced -norm minimization problem. Hence, we aim at rejecting the effect of disturbance on the overall network performance output while the ramp input flow is subjected to constraints. With such a problem formulation, it is not required to know the disturbance input in order to find the proper control input. Without any central decision unit (traffic control center), ramp meters coordinate by sharing their local variables with solely their neighbor units (upstream and downstream) to achieve the global performance goal. Under some network symmetry conditions, a compositionally inexpensive distributed flow control method is suggested to address scalability issues. The method is implemented in simulation environment and compared with other control algorithms in two comprehensive case studies.
Autors: Azita Dabiri;Balázs Kulcsár;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Sep 2017, volume: 18, issue:9, pages: 2525 - 2538
Publisher: IEEE
 
» Distributed Real-Time Optimal Power Flow Control in Smart Grid
Abstract:
Conventionally, power system has a hierarchical control structure including primary, secondary, and tertiary controls. The drawbacks of this hierarchical scheme are manifest: 1) it lacks flexibility and scalability, which is against the trend toward an open-access power system; 2) load forecast as the basis of tertiary control could be inaccurate and infeasible, especially in microgrid for example; 3) as the penetration of renewable energy increases, the relatively long time-scales of secondary and tertiary controls cannot accommodate to more severe power fluctuation within the system. To avoid these drawbacks, a distributed real-time optimal power flow control strategy is introduced in this paper. With the aid of up-to-date smart grid technologies such as two-way communication and distributed sensor, the proposed approach can avoid the need of load forecast and achieve the same objective as hierarchical control with a feedback mechanism in real time, that is to recover the nominal system frequency and maintain the active power of the generators close to the optimal operational condition in the presence of any disturbance. Convergence of the proposed approach is analytically proved. Simulation results in a 34-bus islanded microgrid and the IEEE 118-bus bulk power grid validate the effectiveness and efficiency of the proposed approach.
Autors: Yun Liu;Zhihua Qu;Huanhai Xin;Deqiang Gan;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 3403 - 3414
Publisher: IEEE
 
» Distributed Robust Finite-Time Secondary Voltage and Frequency Control of Islanded Microgrids
Abstract:
This paper presents a distributed, robust, finite-time secondary control for both voltage and frequency restoration of an islanded microgrid with droop-controlled inverter-based distributed generators (DGs). The distributed cooperative secondary control is fully distributed (i.e., uses only the information of neighboring DGs that can communicate with one another through a sparse communication network). In contrast to existing distributed methods that require a detailed model of the system (such as line impedances, loads, other DG units parameters, and even the microgrid configuration, which are practically unknown), the proposed protocols are synthesized by considering the unmodeled dynamics, unknown disturbances, and uncertainties in their models. The other novel idea in this paper is that the consensus-based distributed controllers restore the islanded microgrid's voltage magnitudes and frequency to their reference values for all DGs within finite time, irrespective of parametric uncertainties, unmodeled dynamics, and disturbances, while providing accurate real-power sharing. Moreover, the proposed method considers the coupling between the frequency and voltage of the islanded microgrid. Unlike conventional distributed controllers, the proposed approach quickly reaches consensus and exhibits a more accurate robust performance. Finally, we verify the proposed control strategy's performance using the MATLAB/SimPowerSystems toolbox.
Autors: Nima Mahdian Dehkordi;Nasser Sadati;Mohsen Hamzeh;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 3648 - 3659
Publisher: IEEE
 
» Distributed Solutions for Energy Efficiency Fairness in Multicell MISO Downlink
Abstract:
This paper aims at guaranteeing the achievable energy efficiency (EE) fairness in a multicell multiuser multiple-input single-output downlink system. The design objective is to maximize the minimum EE among all base stations (BSs) subject to per-BS power constraints. This results in a max-min fractional program and as such is difficult to solve in general. Our goal is to develop decentralized algorithms for the max-min EE problem based on combining the successive convex approximation (SCA) framework and the alternating direction method of multipliers (ADMMs). Specifically, leveraging the SCA principle, we iteratively approximate the nonconvex design problem by a sequence of convex programs for which two decentralized algorithms are then proposed. In the first approach, the convex program obtained at each step of the SCA procedure is solved optimally by allowing the BSs to exchange the required information until the ADMM converges. The convergence of the first method is analytically guaranteed but the amount of backhaul signaling can be noticeable in some realistic settings. To reduce the backhaul overhead, the second method performs an abstract version of the ADMM where only one variables update is carried out. Numerical results are provided to demonstrate the effectiveness of the two proposed decentralized algorithms.
Autors: Kien-Giang Nguyen;Quang-Doanh Vu;Markku Juntti;Le-Nam Tran;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6232 - 6247
Publisher: IEEE
 
» Distributed Transmission Control in Multichannel S-ALOHA for Ad-Hoc Networks
Abstract:
Wireless ad-hoc networks are marked without a basic infrastructure and global information for the current status of the network. For multichannel slotted ALOHA systems of wireless ad-hoc networks, this letter proposes a (re)transmission control algorithm for the transmitters to employ. The algorithm aims at minimizing Lyapunov (negative) drift on the sum of all transmitters’ queue, while it is implemented in a distributed way such that each transmitter only needs local information, such as the number of idle channels. To control (re)transmission probability optimally, with the local information, each transmitter solves a subproblem of estimating the number of backlogged nodes in each time slot. Simulation results show that our proposed algorithm yields near-optimal queuing performance.
Autors: Waqas Tariq Toor;Jun-Bae Seo;Hu Jin;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 2093 - 2096
Publisher: IEEE
 
» Distribution Network Electric Vehicle Hosting Capacity Maximization: A Chargeable Region Optimization Model
Abstract:
To coordinate electric vehicle (EV) charging, the EV aggregator (EVA) is usually assumed to obtain the privilege from EV owners (EVOs) to determine the EV charging profile, and complex communication between EVA and EVOs is demanded, which poses difficulties for practical applications. In contrast, this paper proposes the concept of an EV chargeable region to evaluate the distribution network (DN) EV hosting capacity, i.e., how much EV charging demand can be accommodated in a DN, within which the technical constraints of DN (e.g., voltage deviation) are guaranteed and EVOs’ charging requests are maximally ensured. The optimization of the EV chargeable region is formulated as a two-stage robust optimization model with adjustable uncertainty set. The EV chargeable region and DN decision variables are optimized in the first stage and the feasibility in the real-time worst-case scenario is checked in the second stage, considering the uncertainty of EV charging demand and DN active and reactive power. A modified column and constraint generation and outer approximation method is adopted to address the proposed problem. Simulations on an IEEE 123-node DN demonstrate the effectiveness of the proposed model.
Autors: Jian Zhao;Jianhui Wang;Zhao Xu;Cheng Wang;Can Wan;Chen Chen;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4119 - 4130
Publisher: IEEE
 
» Disturbance Estimator-Based Predictive Current Controller for Single-Phase Interconnected PV Systems
Abstract:
A digital predictive current controller for a single-phase grid-side power electronics converter employed in photovoltaic (PV) systems is presented in this paper. A disturbance estimator is employed with the controller in order to minimize its sensitivity to any parameter variation, as well as to reject grid-side disturbances. The design of the controller and the estimator are carried out using the pole placement method. The performance of the developed current controller was tested and verified experimentally using a 5.4-kW grid-connected PV system. These experiments are carried out for different levels of power delivered to the grid under different variation in the system parameters. In addition, other controllers used for interconnected PV systems are also tested to highlight the advantages of the developed current controller. The testing results illustrate the capability of the developed current controller to provide accurate, fast, and robust responses with negligible sensitivity to parameters variations and disturbances on the grid side.
Autors: H. Mohomad;S. A. Saleh;L. Chang;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Sep 2017, volume: 53, issue:5, pages: 4201 - 4209
Publisher: IEEE
 
» Diversity: The IEEE Robotics and Automation Society Culture [President's Message]
Abstract:
Autors: Satoshi Tadokoro;
Appeared in: IEEE Robotics & Automation Magazine
Publication date: Sep 2017, volume: 24, issue:3, pages: 7 - 7
Publisher: IEEE
 
» DoA Estimation Using Compact CRLH Leaky-Wave Antennas: Novel Algorithms and Measured Performance
Abstract:
Traditional direction-of-arrival (DoA) estimation algorithms for multielement antenna arrays (AAs) are not directly applicable to reconfigurable antennas due to inherent design and operating differences between AAs and reconfigurable antennas. In this paper, we propose novel modifications to the existing DoA algorithms and show how these can be adapted for real-time DoA estimation using two-port composite right/ left-handed (CRLH) reconfigurable leaky-wave antennas (LWAs). First, we propose a single/two-port multiple signal classification (MUSIC) algorithm and derive the corresponding steering vector for reconfigurable LWAs. We also present a power pattern cross correlation algorithm that is based on finding the maximum correlation between the measured radiation patterns and the received powers. For all algorithms, we show how to simultaneously use both ports of the two-port LWA in order to improve the DoA estimation accuracy and, at the same time, reduce the scanning time for the arriving signals. Moreover, we formulate the Cramer–Rao bound for MUSIC-based DoA estimation with LWAs and present an extensive performance evaluation of MUSIC algorithm based on numerical simulations. In addition, these results are compared to DoA estimation with conventional AAs. Finally, we experimentally evaluate the performance of the proposed algorithms in an indoor multipath wireless environment with both line-of-sight (LoS) and non-LoS components. Our results demonstrate that DoA estimation of the received signal can be successfully performed using the two-port CRLH-LWA, even in the presence of severe multipath.
Autors: Henna Paaso;Nikhil Gulati;Damiano Patron;Aki Hakkarainen;Janis Werner;Kapil R. Dandekar;Mikko Valkama;Aarne Mämmelä;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4836 - 4849
Publisher: IEEE
 
» Domain Adaptation Using Representation Learning for the Classification of Remote Sensing Images
Abstract:
Traditional machine learning (ML) techniques are often employed to perform complex pattern recognition tasks for remote sensing images, such as land-use classification. In order to obtain acceptable classification results, these techniques require there to be sufficient training data available for every particular image. Obtaining training samples is challenging, particularly for near real-time applications. Therefore, past knowledge must be utilized to overcome the lack of training data in the current regime. This challenge is known as domain adaptation (DA), and one of the common approaches to this problem is based on finding invariant representations for both the training and test data, which are often assumed to come from different “domains.” In this study, we consider two deep learning techniques for learning domain-invariant representations: Denoising autoencoders (DAE) and domain-adversarial neural networks (DANN). While the DAE is a typical two-stage DA technique (unsupervised invariant representation learning followed by supervised classification), DANN is an end-to-end approach where invariant representation learning and classification are considered jointly during training. The proposed techniques are applied to both hyperspectral and multispectral images under different DA scenarios. Results obtained show that the proposed techniques outperform traditional approaches, such as principal component analysis (PCA) and kernel PCA, and can also compete with a fully supervised model in the multispatial scenario.
Autors: Ahmed Elshamli;Graham W. Taylor;Aaron Berg;Shawki Areibi;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Sep 2017, volume: 10, issue:9, pages: 4198 - 4209
Publisher: IEEE
 
» Downlink Non-Orthogonal Multiple Access With Limited Feedback
Abstract:
In this paper, we analyze downlink non-orthogonal multiple access (NOMA) networks with limited feedback. Our goal is to derive appropriate transmission rates for rate adaptation and minimize outage probability of minimum rate for the constant-rate data service, based on distributed channel feedback information from receivers. We propose an efficient quantizer with variable-length encoding that approaches the best performance of the case where perfect channel state information is available everywhere. We prove that in the typical application with two receivers, the losses in the minimum rate and outage probability decay at least exponentially with the minimum feedback rate. We analyze the diversity gain and provide a sufficient condition for the quantizer to achieve the maximum diversity order. For NOMA with receivers where , we solve the minimum rate maximization problem within an accuracy of in time complexity of , and then, we apply the previously proposed quantizers for to the case of . Numerical simulations are presented to demonstrate the efficiency of our proposed quantizers and the accuracy of the analytical results.
Autors: Xiaoyi Liu;Hamid Jafarkhani;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6151 - 6164
Publisher: IEEE
 
» Downscaling of TRMM3B43 Product Through Spatial and Statistical Analysis Based on Normalized Difference Water Index, Elevation, and Distance From Sea
Abstract:
This letter aims to explore the potentialities of normalized difference water index (NDWI) and distance from sea to downscale coarse precipitation (TRMM3B43 product), whose contribution to downscaling precipitation remains unstudied. For this purpose, based on an open data set of 14 years, including TRMM3B43 and three predictors (NDWI, elevation, and distance from sea), stepwise regression and Akaike information criterion were applied in order to identify the best-fit models. The models that have given rise to best approximations and best-fits were used to downscale TRMM3B43 product, to a spatial resolution of 1 km. The resulting downscaled calibrated precipitations were validated by independent rain gauge stations (RGSs). The analysis exhibited that there is good and statistically significant correlations between TRMM3B43 and NDWI and a great agreement between downscaled precipitations and RGS measurements.
Autors: Hicham Ezzine;Ahmed Bouziane;Driss Ouazar;Moulay Driss Hasnaoui;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Sep 2017, volume: 14, issue:9, pages: 1449 - 1453
Publisher: IEEE
 
» Dual LiNbO3 Crystal-Based Batteryless and Contactless Optical Transient Overvoltage Sensor for Overhead Transmission Line and Substation Applications
Abstract:
Advanced high-voltage and overvoltage measurement techniques are required for smart grid construction. The existing overvoltage measurement methods that are currently used for power system measurements are mostly based on the use of electromagnetic voltage transformers and capacitive voltage transformers, which have contradiction in measuring accuracy, measuring distance, antijamming, and system compatibility. A batteryless sensor for contactless measurement of the overvoltage on overhead transmission lines based on a combination of the electrooptic effect in LiNbO3 with stray capacitance in the air is designed in this work. On the basis of this design, a dual-crystal structure-based electrooptic conversion unit is presented that eliminates the natural birefringence and improves the operating stability of the sensor. Testing platforms were set up to measure the characteristics of the sensor in thermal stability. In combination with a data acquisition device, the newly designed sensor was applied to online monitoring of the overvoltage in the ac bus and the overhead transmission lines of a 500-kV transformer station and a ±500-kV convertor station in the China Southern Power Grid.
Autors: Wenxia Sima;Rui Han;Qing Yang;Shangpeng Sun;Tong Liu;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7323 - 7332
Publisher: IEEE
 
» Dual Theory of Transmission Line Outages
Abstract:
A new graph dual formalism is presented for the analysis of line outages in electricity networks. The dual formalism is based on a consideration of the flows around closed cycles in the network. After some exposition of the theory is presented, a new formula for the computation of line outage distribution factors is derived, which is not only computationally faster than existing methods, but also generalizes easily for multiple line outages and arbitrary changes to line series reactance. In addition, the dual formalism provides new physical insight for how the effects of line outages propagate through the network. For example, in a planar network a single-line outage can be shown to induce monotonically decreasing flow changes, which are mathematically equivalent to an electrostatic dipole field.
Autors: Henrik Ronellenfitsch;Debsankha Manik;Jonas Hörsch;Tom Brown;Dirk Witthaut;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4060 - 4068
Publisher: IEEE
 
» Dual-Band Design Theory for Dual Transmission-Line Transformer
Abstract:
In this letter, a novel dual-band (DB) design theory for dual transmission-line (TL) transformer is introduced, and it only consists of two parallel TLs with different physical lengths. Design equations for these two characteristic impedances and their physical lengths are derived in closed form. Through mathematical analysis, two different DB design expressions are newly summarized and proved under the condition of even and odd physical length ratios, respectively. It is proven that the proposed topology could realize around eight times lower impedance transformation ratio than that in conventional works. For verification purposes, two 5– transformers with different frequency ratios have been simulated, fabricated, and measured. Measured and simulation results are matched very well.
Autors: Xiaolong Wang;Zhewang Ma;Masataka Ohira;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Sep 2017, volume: 27, issue:9, pages: 782 - 784
Publisher: IEEE
 
» Dual-Band Hybrid Antenna Structure With Spatial Diversity for DTV and WLAN Applications
Abstract:
This communication presents the design of a dual-band hybrid antenna for digital television (DTV) and wireless local area network (WLAN) applications. Radiations are produced with spatial diversity for WLAN applications to realize multiple-input–multiple-output functionality and omnidirectional coverage. The structure embeds two slots into an ultrawideband monopole body for high- and low-frequency operations, which are excited by three ports of DTV and WLAN. The resultant frequency bandwidth covers most of the global DTV frequencies and the free WLAN band at 2.45 GHz. The radiations exhibit omnidirectional patterns for all three cases. Numerical and measurement results are presented to demonstrate the characteristics of radiation.
Autors: Hsi-Tseng Chou;Hsuan-Jui Su;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4850 - 4853
Publisher: IEEE
 
» Dual-Core Optical Fiber as Beam Splitter With Arbitrary, Tunable Polarization-Dependent Transfer Function
Abstract:
We present the design of a microstructured dual-core optical fiber with integrated electrodes and filled with liquid crystals. The dual-core structure acts as a directional coupler whose properties depend on the liquid crystal alignment. We show that with four electrodes and two separate driving voltages below 30 V on the electrodes, the beam-splitting properties of the fiber can be controlled independently and continuously for the two polarization components, thus allowing for the realization of any arbitrary 2 × 2 transfer function, such as tunable polarizers, polarization-dependent attenuators, or polarization-independent beam splitting.
Autors: Nina Podoliak;Peter Horak;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:18, pages: 4040 - 4046
Publisher: IEEE
 
» Dual-Gate Phototransistor With Perovskite Quantum Dots-PMMA Photosensing Nanocomposite Insulator
Abstract:
Dual-gate InGaZnO thin-film-transistors were fabricated to demonstrate their feasibility as phototransistors by fully exploiting the perovskite quantum dots (QDs) with superior quantum yield. Here, we show that by coupling the top-gate photo sensing polymethyl methacrylate (PMMA)/CsPbBr3 QDs hybrid insulator with the classic SiO2 bottom-gate insulator, the phototransistor can exhibit a combination of excellent detective performance ( Jones detectivity and /W responsivity) and electrical performance (small 3-V threshold voltage, 0.53-V/decade substhreshold slop, and 0.1-V hysteretic threshold voltage’s shift). Additionally, this dual-gate phototransistor exhibits high stability and accelerated detecting speed () due to the inorganic perovskite QDs/PMMA hybrid gate insulator. Our results suggest that in a proper device architecture, perovskite nanomaterials can be promising candidates for cost-effective, high-performance phototransistor.
Autors: Xiang Liu;Zhi Tao;Wenjian Kuang;Qianqian Huang;Qing Li;Jing Chen;Wei Lei;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1270 - 1273
Publisher: IEEE
 
» Dynamic 2-D/3-D Rigid Registration Framework Using Point-To-Plane Correspondence Model
Abstract:
In image-guided interventional procedures, live 2-D X-ray images can be augmented with preoperative 3-D computed tomography or MRI images to provide planning landmarks and enhanced spatial perception. An accurate alignment between the 3-D and 2-D images is a prerequisite for fusion applications. This paper presents a dynamic rigid 2-D/3-D registration framework, which measures the local 3-D-to-2-D misalignment and efficiently constrains the update of both planar and non-planar 3-D rigid transformations using a novel point-to-plane correspondence model. In the simulation evaluation, the proposed method achieved a mean 3-D accuracy of 0.07 mm for the head phantom and 0.05 mm for the thorax phantom using single-view X-ray images. In the evaluation on dynamic motion compensation, our method significantly increases the accuracy comparing with the baseline method. The proposed method is also evaluated on a publicly-available clinical angiogram data set with “gold-standard” registrations. The proposed method achieved a mean 3-D accuracy below 0.8 mm and a mean 2-D accuracy below 0.3 mm using single-view X-ray images. It outperformed the state-of-the-art methods in both accuracy and robustness in single-view registration. The proposed method is intuitive, generic, and suitable for both initial and dynamic registration scenarios.
Autors: Jian Wang;Roman Schaffert;Anja Borsdorf;Benno Heigl;Xiaolin Huang;Joachim Hornegger;Andreas Maier;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Sep 2017, volume: 36, issue:9, pages: 1939 - 1954
Publisher: IEEE
 
» Dynamic Alternation of Huffman Codebooks for Sensor Data Compression
Abstract:
Signal compression is crucial for reducing the amount of communication, and hence power consumption of wireless sensors. Lossless compression techniques, such as Huffman coding, are often used in healthcare applications since they do not compromise the integrity of vital signals. Techniques that adapt to changing signal patterns have been proposed. However, most of them involve significant computation overhead or are too simple to maintain high compression rates under changing signal patterns. In this letter, we propose a technique that makes use of multiple codebooks, which are generated offline based on the signal context. In the applications we study, we observe that the symbols that compose a big variety of signals follow Laplacian distributions in which the spread changes over time. This can be effectively utilized to generate a set of codebooks. Then, appropriate codebooks are selected online depending on the currently measured spread, which ensures high compression efficiency and the adaptability to changing signal patterns. Our experiments on real-world medical datasets show that our approach is computationally very efficient, and exhibits competitive compression rates. Our proposed technique outperforms a state-of-the-art compression algorithm, FAS-LEC, in terms of average data reduction by 4.3%, while consuming a similar amount of energy. Compared to the adaptive Huffman method, which achieves near-optimal compression rates, our results indicate energy savings of 19% due to the reduced computational complexity, while the compression rate is improved by 0.6%.
Autors: Daniel Yunge;Sangyoung Park;Philipp Kindt;Samarjit Chakraborty;
Appeared in: IEEE Embedded Systems Letters
Publication date: Sep 2017, volume: 9, issue:3, pages: 81 - 84
Publisher: IEEE
 
» Dynamic Attack Detection in Cyber-Physical Systems With Side Initial State Information
Abstract:
This technical note studies the impact of side initial state information on the detectability of data deception attacks against cyber-physical systems. We assume the attack detector has access to a linear function of the initial system state that cannot be altered by an attacker. First, we provide a necessary and sufficient condition for an attack to be undetectable by any dynamic attack detector under each specific side information pattern. Second, we characterize attacks that can be sustained for arbitrarily long periods without being detected. Third, we define the zero state inducing attack, the only type of attack that remains dynamically undetectable regardless of the side initial state information available to the attack detector. Finally, we design a dynamic attack detector that detects detectable attacks.
Autors: Yuan Chen;Soummya Kar;José M. F. Moura;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4618 - 4624
Publisher: IEEE
 
» Dynamic Characterization and Modeling of Isotropic Magnetorheological Elastomers Under Tensile-Compressive Loadings
Abstract:
This paper presents dynamic behavior of an isotropic magnetorheological elastomer (MRE) under harmonic tensile-compressive loadings. The dynamic viscoelastic behavior of the MRE is experimentally investigated at various external magnetic fields as well as different loadings of frequency and strain. A generalized Maxwell viscoelastic model is developed to portray the relationships between the stress and strain of the MRE based on input frequency, strain, and magnetic flux density. The coefficients of the proposed model under various input conditions, such as magnetic flux density, strain amplitude, and input frequency, are calculated by implementing the least-squares method. Unlike the previous models of MRE, which mostly focused on shear mode, the present model enables to capture dynamic behavior of MRE in tensile-compressive loadings. Furthermore, tensile-compressive operation offers the most compact design in many axial loading applications such as rotor systems, MRE bearing isolators in bridges, suspension systems in cars, building isolators, and vertical vibration settings, which cannot be controlled with MRE in shear mode due to its low capacity of stiffness. The results show that the proposed model can effectively predict dynamic behavior of MREs under tensile-compressive loadings. This model is useful to simulate the performances of MRE base devices under harmonic tensile-compressive loadings.
Autors: M. Norouzi;M. Gilani;S. M. Sajjadi Alehashem;H. Vatandoost;
Appeared in: IEEE Transactions on Magnetics
Publication date: Sep 2017, volume: 53, issue:9, pages: 1 - 12
Publisher: IEEE
 
» Dynamic Control of Agents Playing Aggregative Games With Coupling Constraints
Abstract:
We address the problem to control a population of noncooperative heterogeneous agents, each with convex cost function depending on the average population state, and all sharing a convex constraint, toward an aggregative equilibrium. We assume an information structure through which a central coordinator has access to the average population state and can broadcast control signals for steering the decentralized optimal responses of the agents. We design a dynamic control law that, based on operator theoretic arguments, ensures global convergence to an equilibrium independently on the problem data, that are the cost functions and the constraints, local and global, of the agents. We illustrate the proposed method in two application domains: Network congestion control and demand side management.
Autors: Sergio Grammatico;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4537 - 4548
Publisher: IEEE
 
» Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition
Abstract:
We propose a joint force estimation method to compute elbow flexion force using surface electromyogram (sEMG) considering time-varying effects in a fatigue condition. Muscle fatigue is a major cause inducing sEMG changes with respect to time over long periods and repetitive contractions. The proposed method composed the muscle-twitch model representing the force generated by a single spike and the spikes extracted from sEMG. In this study, isometric contractions at six different joint angles (10 subjects) and dynamic contractions with constant velocity (six subjects) were performed under non-fatigue and fatigue conditions. Performance of the proposed method was evaluated and compared with that of previous methods using mean absolute value (MAV). The proposed method achieved average 6.7 ± 2.8 %RMSE for isometric contraction and 15.6 ± 24.7%RMSE for isokinetic contraction under fatigue condition with more accurate results than the previous methods.
Autors: Youngjin Na;Jung Kim;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Sep 2017, volume: 25, issue:9, pages: 1431 - 1439
Publisher: IEEE
 
» Dynamic Hierarchical Aggregation for Vehicular Sensing
Abstract:
Vehicular sensing has gained prominence in recent years with its use in entities, including traffic management centers, forensic authorities, and air pollution control units. It also provides end users with real-time street images, parking summaries, and road congestion status. To reduce bandwidth usage and improve the content value, the sensed data must be aggregated. Data aggregation is said to be efficient when the destination (i.e., a node that serves as a data collection point in the network) is capable of receiving sensed data from a significant proportion of vehicles. However, when a large number of vehicles attempt to send sensed data, the network becomes congested eventually causing packet losses and collisions. Thus, if aggregation is performed without considering key factors, such as number of vehicles and network dynamics, it is difficult to ensure the efficient collection of sensed data at the destination. In this paper, we propose a dynamic hierarchical aggregation scheme in which sensed data is aggregated using a hierarchy. Moreover, the hierarchy is dynamically updated based on theoretically estimated delivery efficiency. In particular, we perform partition and merge operations within the hierarchy to achieve an improved value of delivery efficiency. The simulation results show that the proposed scheme ensures efficient data collection even with stringent delay requirements and achieves scalability with respect to a number of vehicles in the network.
Autors: Jagruti Sahoo;Soumaya Cherkaoui;Abdelhakim Hafid;Pratap Kumar Sahu;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Sep 2017, volume: 18, issue:9, pages: 2539 - 2556
Publisher: IEEE
 
» Dynamic Load-Balancing Spectrum Decision for Heterogeneous Services Provisioning in Multi-Channel Cognitive Radio Networks
Abstract:
In this paper, we study dynamic load-balancing spectrum decision for a cognitive radio network (CRN) that dynamically distributes packets from the secondary user (SU) to different available primary channels. We consider two different classes of services at the SU, i.e., delay sensitive (DS) and best effort (BE) services, and assign a higher priority to the DS services. We apply priority queuing model to address this priority issue in the CRN. Based on the queuing model, two Markov decision processes (MDPs) are formulated with objectives to minimize the average delay of both services while guaranteeing the priority of the DS services. Reinforcement learning is applied to find the optimal solutions when the traffic and channel characteristics are unknown. To address the computational complexity issue in the MDP solutions, we propose a myopic method based on the estimated packet sojourn time, which is derived by formulating a phase type distribution. Simulation results demonstrate the effectiveness of all proposed algorithms for load-balancing spectrum decision. It also shows that the proposed myopic scheme can achieve significant reduction on computational complexity with a cost on the delay performance of low priority BE services.
Autors: Huijin Cao;Hongqiao Tian;Jun Cai;Attahiru S. Alfa;Shiwei Huang;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 5911 - 5924
Publisher: IEEE
 
» Dynamic Multi-Connectivity Performance in Ultra-Dense Urban mmWave Deployments
Abstract:
Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.
Autors: Vitaly Petrov;Dmitrii Solomitckii;Andrey Samuylov;Maria A. Lema;Margarita Gapeyenko;Dmitri Moltchanov;Sergey Andreev;Valeriy Naumov;Konstantin Samouylov;Mischa Dohler;Yevgeni Koucheryavy;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Sep 2017, volume: 35, issue:9, pages: 2038 - 2055
Publisher: IEEE
 
» Dynamic Stability Analysis of Synchronverter-Dominated Microgrid Based on Bifurcation Theory
Abstract:
In the traditional power grid, inverter-inter-faced distributed energy resources are widely used in microgrids such as conventional synchronous generators (SGs) in the traditional power grid. They are expected to decrease the rotational inertia and spinning reserve capacity that are specific to SGs, while synchronverters can compensate for the loss. Thus, an increasing number of interfaced inverters may act as synchronverters in a microgrid. The dynamic stability of the synchronverter-dominated microgrid must thus be carefully evaluated to ensure the reliable operation of this type of system. This paper presents a nonlinear model of a synchronverter-dominated microgrid. The eigenvalues of the system state matrix, along with the participation factors, are analyzed to determine the predominant parameters affecting the stability. Bifurcation theory is then used to predict and describe the unstable phenomenon as the system parameters fluctuate; the effect of these parameters on the system stability is then examined. A simulation on MATLAB/Simulink and experiments were performed and results validated the presented analysis.
Autors: Zhikang Shuai;Yang Hu;Yelun Peng;Chunming Tu;Z. John Shen;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7467 - 7477
Publisher: IEEE
 
» EAAP: Efficient Anonymous Authentication With Conditional Privacy-Preserving Scheme for Vehicular Ad Hoc Networks
Abstract:
Providing an efficient anonymous authentication scheme in vehicular ad hoc networks (VANETs) with low computational cost is a challenging issue. Even though, there are some existing schemes to provide anonymous authentication, the existing schemes suffer from high computational cost in the certificate and the signature verification process, which leads to high message loss. Therefore, they fail to meet the necessity of verifying hundreds of messages per second in VANETs. In our scheme, we propose an efficient anonymous authentication scheme to avoid malicious vehicles entering into the VANET. In addition, the proposed scheme offers a conditional tracking mechanism to trace the vehicles or roadside units that abuse the VANET. As a result, our scheme revokes the privacy of misbehaving vehicles to provide conditional privacy in a computationally efficient way through which the VANET entities will be anonymous to each other until they are revoked from the VANET system. Moreover, the proposed scheme is implemented and the performance analysis shows that our scheme is computationally efficient with respect to the certificate and the signature verification process by keeping conditional privacy in VANETs.
Autors: Maria Azees;Pandi Vijayakumar;Lazarus Jegatha Deboarh;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Sep 2017, volume: 18, issue:9, pages: 2467 - 2476
Publisher: IEEE
 
» Economical Colorimetric Smart Sensor to Measure Water Quality of Drinking Water in CKDu Prevalence Areas
Abstract:
Safe drinking water is essential for good health. Recommendations on drinking water sources of CKDu prevalence areas are utmost important due to health risk of long-term consumption. This paper focuses on designing a sensor to measure fluoride and hardness in well water with an automated mechanism. Here, a simple colorimetric approach was adapted to develop the proposed optical sensor using procedures of variation of color with SPADNS reagent and complexometric titration. Added measurement of conductivity and pH supports decision making. Reduced reagent volumes make the design to be eco-friendly and estimated cost of U.S. $1 per sample analysis is affordable to the communities with low income.
Autors: S. A. D. A. N. Dissanayake;H. Pasqual;B. C. L. Athapattu;
Appeared in: IEEE Sensors Journal
Publication date: Sep 2017, volume: 17, issue:18, pages: 5885 - 5891
Publisher: IEEE
 
» Editorial
Abstract:
In Australia many university engineering research projects are funded by 3- to 5-year grants where the cost is split evenly between government and industry. Due to the small industrial manufacturing base in Australia, much power engineering research is funded by the utilities. In our project we set out to investigate new strategies for working with industry, in order to strengthen collaboration and enrich the education of our students. We took great care to set research aims in cooperation with our industrial partners so that, where appropriate, the outcomes could be implemented by the partner organizations. The planned research work was outlined in course materials for the students, who then had the opportunity to work on thesis projects co-supervised by industry.
Autors: Dan Martin;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Sep 2017, volume: 33, issue:5, pages: 4 - 6
Publisher: IEEE
 
» Effect of Active Damping on Output Impedance of Three-Phase Grid-Connected Converter
Abstract:
LCL-filter is commonly used to attenuate the switching harmonics of grid-connected converters. LCL -filter creates resonances in the converter dynamics which shall be damped for ensuring robust performance of the converter. Active damping methods can be used to attenuate the resonant behavior effectively. Accordingly, the output impedance is affected and the grid-interaction sensitivity of the converter varies with the active damping design. In order to carry out impedance-based stability analysis or assessment of the harmonic rejection capability, an accurate analytical model to predict the output impedance is necessary. This paper investigates the output impedance properties of capacitor-current-feedback active damping, which are so far not considered thoroughly in the literature. The output impedance modification with the active damping design is explained, thus, the stability and harmonic rejection capability of the converter can be improved. Furthermore, in order to validate the model, experimental measurements of the output impedance with active damping are presented for the first time in the literature.
Autors: Aapo Aapro;Tuomas Messo;Tomi Roinila;Teuvo Suntio;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7532 - 7541
Publisher: IEEE
 
» Effect of Adding Edges to Consensus Networks With Directed Acyclic Graphs
Abstract:
Consensus of a network with a directed acyclic graph, a directed graph with no directed cycles, is always guaranteed if it contains a spanning tree. This paper studies the effect of adding edges to a directed acyclic graph that may result in a directed cycle. It is shown that the effect on consensus performance of the whole network is only determined by a local subnetwork containing all the added edges. More specifically, both a one-dimensional (1-D) chain network and a 2-D grid network are investigated in this paper. It is proved that, when a reverse edge is added, the consensus performance is degraded by the amount only determined by the edge range, that is, independent of the network size or the location of the added edge.
Autors: Hai-Tao Zhang;Zhiyong Chen;Xiaoyu Mo;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4891 - 4897
Publisher: IEEE
 
» Effect of Ambient Electrons on Primary Discharge Energy in Laser-Induced Discharge
Abstract:
We examined the laser-induced discharge (LID) in medium-vacuum air. The time-averaged discharge energy Wd of a primary discharge prior to an arc discharge was affected by the number of initial electrons. The initial electrons were produced by the laser irradiation of electrodes. The number of electrons was proportional to the energy of the laser, Lp. Thus, it was adjusted by changing Lp. Although the experimental conditions were rather limited, i.e., air at 200-Pa pressure, we demonstrated a simple relationship, , where Vs is the applied voltage and s is an exponent determined empirically. Note that the number of initial electrons is a function of Lp. Such a simple relationship for the behavior of LID that incorporates Wd is proposed for the first time in this paper.
Autors: Y. Hoshi;H. Yoshida;N. Iki;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Sep 2017, volume: 45, issue:9, pages: 2416 - 2421
Publisher: IEEE
 
» Effect of Carbon Black Film on High-Frequency Power Absorption
Abstract:
This letter proposes the use of carbon black film in absorbing high-frequency power. This low-cost material can be obtained easily using a low-cost fabrication process (i.e., screen printer). The 70 wt% carbon black film is 0.055-mm thick, with sheet resistance of /sq and conductivity of 113.6 S/m. Results show that carbon black film absorbs high-frequency signal, and the power loss reaches 70% at 3 GHz. Moreover, the starting suppression frequency could be controlled by adjusting the proportion of carbon black.
Autors: Guo-Sheng Lin;Jing-Lun Chen;Lih-Shan Chen;Mau-Phon Houng;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Sep 2017, volume: 27, issue:9, pages: 779 - 781
Publisher: IEEE
 
» Effect of Cavity Ohmic Losses on Efficiency of Low-Power Terahertz Gyrotron
Abstract:
The problem of power degradation due to the dominant ohmic losses in gyrotron cavity is considered. As an example, the operating performances of the FU CW III gyrotron of Fukui University are investigated numerically. It is found that, for this gyrotron, there is a significant divergence between the classical and the self-consistent computations of the loss-induced power degradation. The reason is that the former computations ignore the effect of the cavity ohmic losses on beam-wave interaction efficiency.
Autors: Vitalii I. Shcherbinin;Anton V. Hlushchenko;Aleksandr V. Maksimenko;Viktor I. Tkachenko;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3898 - 3903
Publisher: IEEE
 
» Effect of Circuit Parameters and Environment on Shock Waves Generated by Underwater Electrical Wire Explosion
Abstract:
The electrical explosion of wire (EEW), which can generate a convenient, stable, and controllable shock wave (SW), is gradually acted as a physical and environmentally friendly enhanced oil recovery technology in petroleum industry. In order to establish the relationship between the SWs and EEW, the process and mechanism of underwater EEW were investigated and discussed as a function of recipe current, voltage, and pressure in the test conditions. This work describes the effect of wire diameter, capacitance, energy deposition, water conductivity, and temperature on the pressure of SWs. It was found that the amplitude of SWs has a close relationship to the energy deposition in vaporization process. Under the same stored energy of different capacitors, the energy deposition in vaporization stage is more efficient with high charging voltage and low capacitance in a stable explosion, because of the high magnetic pressure and short discharge time. While, the water conductivity and temperature have a significant effect on current and voltage in vaporization stage. The shunt effect of saline water and high thermal conductivity of high-temperature water effect the energy deposition in this stage, which made the amplitude of SWs are falling.
Autors: Ben Liu;Deguo Wang;Yanbao Guo;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Sep 2017, volume: 45, issue:9, pages: 2519 - 2526
Publisher: IEEE
 
» Effect of Spatial Filtering on Characterizing Soil Properties From Imaging Spectrometer Data
Abstract:
Airborne imaging spectroscopy covering wavelength range of 0.35–2.5 m can be used to quantify soil textural properties and chemical constituents. In this paper, we evaluate the effects of spatial resolution on the quantification of soil constituents using a lasso algorithm-based ensemble bootstrapping framework. Airborne visible infrared imaging spectrometer data collected at 7.6 m resolution over Bird's Point New Madrid (BPNM) floodway in Missouri, USA, is upscaled using a spatial filter to simulate a satellite-based sensor and generate multiple coarser resolution datasets, including the originally proposed 60.8 m hyperspectral infrared imager like data. The simulated data at multiple spatial resolutions are used in an ensemble lasso algorithm-based modeling framework for developing quantitative prediction models and spatial mapping of the soil constituents. We outline an evaluation framework with a set of metrics that considers the point-scale model performance as well as the consistency of cross-scale spatial predictions. The model results demonstrate that the ensemble quantification method is scalable, and further the model structure indicates the persistence of important spectral features across spatial resolutions. The probability density functions of the constituents over the BPNM landscape show that it is similar for multiple spatial resolutions. Finally, a comparison of the model predictions with statistical central values together with the within pixel variance across fine to coarse resolutions indicate that the model accurately captures the median values of the fine subgrid that the coarse-resolution data is composed of. This study establishes the feasibility for quantifying soil constituents from space-borne hyperspectral sensors.
Autors: Debsunder Dutta;Praveen Kumar;Jonathan A. Greenberg;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Sep 2017, volume: 10, issue:9, pages: 4149 - 4170
Publisher: IEEE
 
» Effect of Truncated Input Parameter Distribution on the Integrity of Safety Instrumented Systems Under Epistemic Uncertainty
Abstract:
Safety instrumented system (SIS) is widely applied to reduce or prevent risk in industry. Practical SIS commonly meets with epistemic uncertainty arising from incompleteness of knowledge on various input parameters due to lack of data. Epistemic uncertainty can be reduced by collecting more knowledge or data. Epistemic uncertainty in input parameters can lead to variation in probability of failure to perform its intended functions on demand (PFD) for an SIS. This paper employs the complementary cumulative distribution function of PFD to define exceedance probability (EP) that the PFD exceeds a prescribed value. Sensitivity analysis is further investigated, analyzing the effect of an epistemically uncertain input parameter with truncated distribution on EP of an SIS. We have derived the analytic expression for evaluating the effect, and only an evaluation is needed to estimate the effects of all the parameters. Two examples are employed to demonstrate the applicability of the proposed method. We further compare the effects for the truncated and nontruncated parameter situations. Their results converge to the same ones as the truncated region of an input parameter decreases to zero. When the truncated region of an input parameter is less than 10–3 , the corresponding results can be approximated by the ones of the nontruncated case with lower computational cost.
Autors: Zhang-Chun Tang;Ming Jian Zuo;Yanjun Xia;
Appeared in: IEEE Transactions on Reliability
Publication date: Sep 2017, volume: 66, issue:3, pages: 735 - 750
Publisher: IEEE
 
» Effective utilization of unallocated intervals in TDD-based fronthaul employing TDM-PON
Abstract:
A time-division-multiplexing passive optical network (TDM-PON) accommodating a time-division duplex (TDD)-based mobile fronthaul (MFH) contributes to the realization of a low-cost network. However, there are two issues with the TDM-PON. The first is the limited number of optical network units (ONUs) that can be accommodated because the statistical multiplexing effect is weaker than with the accommodation of a conventional MFH. The other issue is the discovery process for registering new ONUs. While operating the discovery process, the signals of the registered ONUs cannot be forwarded in the optical link, and a huge latency is added to the registered ONUs. We have proposed a technique for the effective utilization of unallocated intervals, which certainly occur in optical links. Secondary service signals are forwarded in the unallocated intervals to increase the number of ONUs. The discovery process also operates in the unallocated intervals to avoid any latency increase. In this paper, we report evaluation results obtained using the numerical simulations.
Autors: Daisuke Hisano;Tatsuya Shimada;Hiroshi Ou;Takayuki Kobayashi;Yu Nakayama;Hiroyuki Uzawa;Jun Terada;Akihiro Otaka;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Sep 2017, volume: 9, issue:9, pages: D1 - D9
Publisher: IEEE
 
» Effects of Coating Material Properties on the Wideband Reflectivity Performance of Microwave Calibration Targets
Abstract:
This communication investigates the wideband reflectivity performance of calibration targets for spaceborne radiometers, which are fabricated as coated pyramids/cones. Specifically, the effects of the coating material properties on the wideband reflectivity performance are studied. Numerical studies based on finite-difference time-domain (FDTD) methods are carried out considering two coating materials with distinct characteristics. The mechanisms of structural absorption and reflection in both the low- and the high-frequency regions are discussed, and the relations between the coating material properties and the total reflectivity are determined. The results show that the absorption within the coating layer is not the only factor that determines the structural reflection in the high-frequency region; the impedance matching between the coating and free space, especially in the case of coated pyramids, is also a determinant. Different geometry optimization strategies are presented for the two materials based on their distinct characteristics. The wideband reflectivity performance is found to be well improved.
Autors: Ming Bai;Dong Xia;Ming Jin;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4909 - 4913
Publisher: IEEE
 
» Effects of Concurrent and Delayed Visual Feedback on Motor Memory Consolidation
Abstract:
In many domains, it's important to understand the ways in which humans learn and develop new motor skills effectively and efficiently. For example, in dental operations, the ability to apply a weak force with a required tolerance is a fundamental skill to ensure diagnostic and treatment outcome, but acquiring such a skill is a challenge for novices. In this paper, we focus on motor memory for producing normally applied force by a hand-held probe and we compare the effects of two feedback methods on motor memory consolidation. Fourteen participants were randomly assigned to two groups: a Concurrent Group and a Delayed Group. Participants in the Concurrent Group were trained to apply a target force with concurrent visual feedback, while those in the Delayed Group were trained with delayed visual feedback. The task included two phases: a Training/Testing Phase, and a Retention Phase. The results indicated that participants in the Delayed Group obtained more effective learning outcomes and better retention effects. These findings provide a new perspective to explore the relationship between feedback methods and the cognitive process of motor skill learning, and open a new way to train motor skill using more effective methods than the traditional concurrent feedback approaches.
Autors: Dangxiao Wang;Teng Li;Gaofeng Yang;Yuru Zhang;
Appeared in: IEEE Transactions on Haptics
Publication date: Sep 2017, volume: 10, issue:3, pages: 350 - 357
Publisher: IEEE
 
» Effects of the Winding Cross-Section Shape on the Magnetic Field Uniformity of the High Field Circular Helmholtz Coil Systems
Abstract:
Massive windings must be used for strong magnetic field applications, which results in low magnetic field uniformity. In this paper, a simple circular Helmholtz coil system is analyzed to identify the main causes of the problems, which arise for high intensity uniform magnetic field applications. Here, dominant deformations of the circular solenoid winding cross-section shape and its dimensions effects on the generated magnetic field and its uniformity are analyzed. These analyses can be applied to the modified Helmholtz coil and multi-axial systems, as well. The system dimensions are optimized and normalized to easily scale the given results for any desired uniform magnetic field and workspace without doing further laborious calculations. The optimized dimensions increase the magnetic field uniformity in a large portion of the available workspace and realize the desired magnetic field at the center of the system. Also, the necessary conductor mass and the total electrical power are reduced. To verify the given analyses, two small-scale Helmholtz coil systems have been implemented and their generated magnetic fields and nonuniformities have been measured under a variety of conditions.
Autors: Reza Beiranvand;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7120 - 7131
Publisher: IEEE
 
» Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization
Abstract:
Accurately determining the position and orientation from which an image was taken, i.e., computing the camera pose, is a fundamental step in many Computer Vision applications. The pose can be recovered from 2D-3D matches between 2D image positions and points in a 3D model of the scene. Recent advances in Structure-from-Motion allow us to reconstruct large scenes and thus create the need for image-based localization methods that efficiently handle large-scale 3D models while still being effective, i.e., while localizing as many images as possible. This paper presents an approach for large scale image-based localization that is both efficient and effective. At the core of our approach is a novel prioritized matching step that enables us to first consider features more likely to yield 2D-to-3D matches and to terminate the correspondence search as soon as enough matches have been found. Matches initially lost due to quantization are efficiently recovered by integrating 3D-to-2D search. We show how visibility information from the reconstruction process can be used to improve the efficiency of our approach. We evaluate the performance of our method through extensive experiments and demonstrate that it offers the best combination of efficiency and effectiveness among current state-of-the-art approaches for localization.
Autors: Torsten Sattler;Bastian Leibe;Leif Kobbelt;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Sep 2017, volume: 39, issue:9, pages: 1744 - 1756
Publisher: IEEE
 
» Efficient 3-D Model-Based Reconstruction Scheme for Arbitrary Optoacoustic Acquisition Geometries
Abstract:
Optimal optoacoustic tomographic sampling is often hindered by the frequency-dependent directivity of ultrasound sensors, which can only be accounted for with an accurate 3-D model. Herein, we introduce a 3-D model-based reconstruction method applicable to optoacoustic imaging systems employing detection elements with arbitrary size and shape. The computational complexity and memory requirements are mitigated by introducing an efficient graphic processing unit (GPU)-based implementation of the iterative inversion. On-the-fly calculation of the entries of the model-matrix via a small look-up table avoids otherwise unfeasible storage of matrices typically occupying more than 300GB of memory. Superior imaging performance of the suggested method with respect to standard optoacoustic image reconstruction methods is first validated quantitatively using tissue-mimicking phantoms. Significant improvements in the spatial resolution, contrast to noise ratio and overall 3-D image quality are also reported in real tissues by imaging the finger of a healthy volunteer with a hand-held volumetric optoacoustic imaging system.
Autors: Lu Ding;Xosé Luís Deán-Ben;Daniel Razansky;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Sep 2017, volume: 36, issue:9, pages: 1858 - 1867
Publisher: IEEE
 
» Efficient Algorithms for Throughput Maximization in Software-Defined Networks With Consolidated Middleboxes
Abstract:
Today’s computer networks rely on a wide spectrum of specialized middleboxes to improve network security and performance. A promising emerging technique to implementing traditional middleboxes is the consolidated middlebox technique, which implements the middleboxes as software in virtual machines in software-defined networks (SDNs), offering economical, and simplified management for middleboxes. This however poses a great challenge, that is, how to find a cost-optimal routing path for each user request such that the data traffic of the request will pass through the middleboxes in their orders in the service chain of the request, with the objective to maximize the network throughput, subject to various resource capacity constraints in SDNs. In this paper, we study the network throughput maximization problem in an SDN under two different scenarios: one is the snapshot scenario where a set of requests at one time slot is given, we aim to admit as many requests in the set as possible to maximize the network throughput; another is the online scenario in which requests arrive one by one without the knowledge of future arrivals. Given a finite time horizon consisting of equal time slots, the system must respond to the arrived requests in the beginning of each time slot, by either admitting or rejecting the requests, depending on the resource availabilities in the network. For the snapshot scenario, we first formulate an integer linear program (ILP) solution, we then devise two heuristics that strive for fine tradeoffs between the quality of a solution and the running time of obtaining the solution. For the online scenario, we show how to extend the proposed algorithms for the snapshot scenario to solve the online scenario. We finally evaluate the performance of the proposed algorithms through experimental simulations, based on both real and synthetic network topo- ogies. Experimental results demonstrate that the proposed algorithms admit more requests than the baseline algorithm and the quality of the solutions delivered by heuristics is comparable to the exact solution by the ILP in most cases.
Autors: Meitian Huang;Weifa Liang;Zichuan Xu;Song Guo;
Appeared in: IEEE Transactions on Network and Service Management
Publication date: Sep 2017, volume: 14, issue:3, pages: 631 - 645
Publisher: IEEE
 
» Efficient Analysis of Confined Guided Modes in Phoxonic Crystal Slabs
Abstract:
Today's standard fabrication processes are just capable of manufacturing slab of photonic and phononic crystals, so an efficient method for analysis of these crystals is indispensable. Plane wave expansion (PWE) as a widely used method in studying photonic and phononic (phoxonic) crystals in full three dimensions is not suitable for slab analysis in its standard form, because of convergence and stability issues. Here, we propose a modification to this method which overcomes these limitations. This improved method can be utilized for calculation of both photonic and phononic modes in phoxonic slabs. While in the standard three-dimensional PWE, Fourier series are used to estimate the field dependence across the normal component of the slab, we expand the fields across the third dimension using eigenmodes of a plain unstructured slab. Despite its approximate nature, this approach is observed to be both much faster and more accurate than the conventional PWE method and can give a very accurate estimation of confined propagating modes. As an application example of the proposed method, we investigate a nonreciprocal photonic device. This device is a phoxonic slab waveguide, which changes modes of optical waves by elastic waves and can be used as an optical insulator or mode converter.
Autors: Mohammad Hasan Aram;Sina Khorasani;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:17, pages: 3734 - 3742
Publisher: IEEE
 
» Efficient and Fast Implementation of Embedded Time-of-Flight Ranging System Based on FPGAs
Abstract:
Time-of-flight cameras perceive depth information about the surrounding environment with an amplitude-modulated near-infrared light source. The distance between the sensor and objects is calculated through measuring the time the light needs to travel. To be used in fast and embedded applications, such as 3-D reconstruction, visual SLAM, human-robot interactions, and object detection, the 3-D imaging must be performed at high frame rates and accuracy. Thus, this paper presents a real-time field programmable gate arrays platform that calculates the phase shift and then the distance. Experimental results shown that the platform can acquire ranging images at the maximum frame rate of 131fps with a fine measurement precision (appropriately 5.1mm range error at 1.2m distance with the proper integration time). Low resource utilization and power consumption of the proposed system make it very suitable for embedded applications.
Autors: Weiguo Zhou;Congyi Lyu;Xin Jiang;Weihua Zhou;Peng Li;Haoyao Chen;Tongtong Zhang;Yun-Hui Liu;
Appeared in: IEEE Sensors Journal
Publication date: Sep 2017, volume: 17, issue:18, pages: 5862 - 5870
Publisher: IEEE
 
» Efficient Clue-Based Route Search on Road Networks
Abstract:
With the advances in geo-positioning technologies and location-based services, it is nowadays quite common for road networks to have textual contents on the vertices. Previous work on identifying an optimal route that covers a sequence of query keywords has been studied in recent years. However, in many practical scenarios, an optimal route might not always be desirable. For example, a personalized route query is issued by providing some clues that describe the spatial context between PoIs along the route, where the result can be far from the optimal one. Therefore, in this paper, we investigate the problem of clue-based route search (), which allows a user to provide clues on keywords and spatial relationships. First, we propose a greedy algorithm and a dynamic programming algorithm as baselines. To improve efficiency, we develop a branch-and-bound algorithm that prunes unnecessary vertices in query processing. In order to quickly locate candidate, we propose an AB-tree that stores both the distance and keyword information in tree structure. To further reduce the index size, we construct a PB-tree by utilizing the virtue of 2-hop label index to pinpoint the candidate. Extensive experiments are conducted and verify the superiority of our algorithms and index structures.
Autors: Bolong Zheng;Han Su;Wen Hua;Kai Zheng;Xiaofang Zhou;Guohui Li;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1846 - 1859
Publisher: IEEE
 
» Efficient Codebook-Based Beamforming Algorithm for Millimeter-Wave Massive MIMO Systems
Abstract:
Hybrid beamforming architecture, consisting of a low-dimensional baseband digital beamforming component and a high-dimensional analog beamforming component, has received considerable attention in the context of millimeter-wave massive multiple-input multiple-output systems. This is because it can achieve an effective compromise between hardware complexity and system performance. To avoid accurate estimation of the channel, a codebook-based technique is widely used in analog beamforming components, wherein a transmitter and receiver jointly examine an analog precoder and analog combiner pair according to predesigned codebooks, without using a priori channel information. However, identifying an optimal analog precoder and analog combiner pair using the exhaustive search algorithm (ESA) incurs exponential complexity, causing the number of radio frequency chains to proliferate and hindering the resolution of the phase shifters, which cannot be solved even for highly reasonable system parameters. To reduce the search complexity while maximizing the achievable rate, we propose a low-complexity, near-optimal algorithm developed from a cross-entropy optimization framework. Our simulation results reveal that our algorithm achieves near-optimal performance at a much lower complexity than does the optimal ESA.
Autors: Jung-Chieh Chen;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 7809 - 7817
Publisher: IEEE
 
» Efficient Critical Path Identification Based on Viability Analysis Method Considering Process Variations
Abstract:
In this brief, we propose an effective adaptation of viability analysis in statistical static timing analysis. The adaption benefits well from a dynamic programming implementation of the viability function. For a rapid identification of statistical longest true paths, the technique makes use of a fast preprocessing step identifying the gates with a small probability of being viable in the circuit, and a number of simple optimization techniques. This makes the approach fast without lowering its accuracy. The efficacy of the proposed statistical timing analysis is assessed using ISCAS benchmark circuits and carry skip adders. The results show that the proposed technique leads to, on average, higher speed compared to those of the state-of-the-art technique. This improvement is achieved at the cost of −1.7% precision lost compared to that of the Monte-Carlo method.
Autors: Sheis Abolmaali;Nika Mansouri-Ghiasi;Mehdi Kamal;Ali Afzali-Kusha;Massoud Pedram;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Sep 2017, volume: 25, issue:9, pages: 2668 - 2672
Publisher: IEEE
 
» Efficient FPGA Mapping of Pipeline SDF FFT Cores
Abstract:
In this paper, an efficient mapping of the pipeline single-path delay feedback (SDF) fast Fourier transform (FFT) architecture to field-programmable gate arrays (FPGAs) is proposed. By considering the architectural features of the target FPGA, significantly better implementation results are obtained. This is illustrated by mapping an R22SDF 1024-point FFT core toward both Xilinx Virtex-4 and Virtex-6 devices. The optimized FPGA mapping is explored in detail. Algorithmic transformations that allow a better mapping are proposed, resulting in implementation achievements that by far outperforms earlier published work. For Virtex-4, the results show a 350% increase in throughput per slice and 25% reduction in block RAM (BRAM) use, with the same amount of DSP48 resources, compared with the best earlier published result. The resulting Virtex-6 design sees even larger increases in throughput per slice compared with Xilinx FFT IP core, using half as many DSP48E1 blocks and less BRAM resources. The results clearly show that the FPGA mapping is crucial, not only the architecture and algorithm choices.
Autors: Carl Ingemarsson;Petter Källström;Fahad Qureshi;Oscar Gustafsson;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Sep 2017, volume: 25, issue:9, pages: 2486 - 2497
Publisher: IEEE
 
» Efficient High Utility Pattern Mining for Establishing Manufacturing Plans With Sliding Window Control
Abstract:
In industrial areas, understanding the preference of customers is one of the important considerations for establishing profitable product manufacturing plans. As one of the approaches in pattern mining, high utility pattern mining has been employed to find a set of products creating high profits by considering the purchase quantity and price of each product. In this regard, high utility pattern mining can be useful to establish profitable product manufacturing plans that allow a corporation to maximize its revenue. For establishing manufacturing plans, we also need to understand the recent preference of customers from stream data, which are continually generated without limitations. In this paper, we propose a novel algorithm and list structure for finding high utility patterns over data streams on the basis of a sliding window mode. Unlike existing algorithms, the proposed algorithm does not consume huge computational resources for verifying candidate patterns because it can avoid the generation of candidate patterns. Therefore, the algorithm efficiently works in complex dynamic systems. Experimental results obtained from various tests using real-world dataset show that the proposed algorithm outperforms state-of-the-art methods in terms of runtime, memory usage, and scalability.
Autors: Unil Yun;Gangin Lee;Eunchul Yoon;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7239 - 7249
Publisher: IEEE
 
» Efficient Large-Scale Energy Storage Dispatch: Challenges in Future High Renewable Systems
Abstract:
Future power systems with high penetrations of variable renewables will require increased levels of flexibility from generation and demand-side sources in order to maintain secure and stable operation. One potential flexibility source is large-scale energy storage, which can provide a variety of ancillary services across multiple time scales. In order for appropriate levels of investment to take place, and in order for existing assets to be utilized optimally, it is essential that market signals are present which encourage suitable levels of flexibility, either from storage or alternative sources. Suboptimal storage plant dispatch due to uncertainty and inefficient market incentives are represented as operational constraints on the storage plant, and the impact of these inefficiencies are highlighted. Thus, changes required in operational practices for storage plant at different installed wind capacity levels, and the challenges that private storage plant operators will face in generating appropriate bids in a market environment at high variable renewable penetrations are explored. The impacts on system generating costs and storage profits are explored under different plant operating assumptions.
Autors: Ciara O’Dwyer;Lisa Ryan;Damian Flynn;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 3439 - 3450
Publisher: IEEE
 
» Efficient Method for High-Quality Removal of Nonuniform Blur in the Wavelet Domain
Abstract:
This paper presents a novel nonuniform deblurring approach, which defines the blur model and calculates regularized nonuniform deconvolution in the wavelet domain to achieve high efficiency and high accuracy simultaneously. Targeting high computation efficiency, we derive a wavelet-domain hierarchical blur model, which can be calculated efficiently by exploiting the sparsity property of natural images in the wavelet domain. Correspondingly, the blur model is incorporated into a multilayer framework and at each layer spatially varying step sizes are introduced to further accelerate the convergence of the algorithm. In addition to the efficiency advantages, the proposed approach deals with intensely nonuniform blur with high accuracy due to the intrinsic tight supportness of wavelet basis. We conduct a series of experiments and comparisons to validate the efficiency and effectiveness of our algorithm.
Autors: Tao Yue;Jinli Suo;Xun Cao;Qionghai Dai;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Sep 2017, volume: 27, issue:9, pages: 1869 - 1881
Publisher: IEEE
 
» Efficient Solar Power Management System for Self-Powered IoT Node
Abstract:
An efficient micro-scale solar power management architecture for self-powered Internet-of-Things node is presented in this paper. The proposed architecture avoids the linear regulator and presents a complete on-chip switched capacitor-based power converter in order to achieve higher end-to-end efficiency. Unlike traditional architectures, where the harvested energy processes twice, the proposed architecture processes the harvested energy only once before it reaches to the load circuit, irrespective of the ambient conditions. The system efficiency has been improved by ~12% over the traditional architecture. The entire power management system has been designed using 0.18- CMOS technology node, and the circuit simulations demonstrate that the proposed architectural changes bring in a system efficiency of 82.4% under different light conditions. In addition to that, a hardware setup is created using commercially available ICs and photovoltaic cells, to validate that the proposed power management system is practically realizable.
Autors: Saroj Mondal;Roy Paily;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Sep 2017, volume: 64, issue:9, pages: 2359 - 2369
Publisher: IEEE
 
» Efficiently Coding Replicas to Erasure Coded Blocks in Distributed Storage Systems
Abstract:
Modern distributed storage systems usually store new data in replicas, and later code these data into erasure coded blocks when they get cold. This letter studies optimal bandwidth consumption problem for this replica to erasure coded blocks (R2E) coding process, and proposes schemes of R2E_singleTree and R2E_multiTree based on problem observations. Theoretical analysis and evaluation are conducted for these two schemes.
Autors: Zimu Yuan;Huiying Liu;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 1897 - 1900
Publisher: IEEE
 
» EIT Imaging Regularization Based on Spectral Graph Wavelets
Abstract:
The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.
Autors: Bo Gong;Benjamin Schullcke;Sabine Krueger-Ziolek;Marko Vauhkonen;Gerhard Wolf;Ullrich Mueller-Lisse;Knut Moeller;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Sep 2017, volume: 36, issue:9, pages: 1832 - 1844
Publisher: IEEE
 
» Elastic State Machine Replication
Abstract:
State machine replication (SMR) is a fundamental technique for implementing stateful dependable systems. A key limitation of this technique is that the performance of a service does not scale with the number of replicas hosting it. Some works have shown that such scalability can be achieved by partitioning the state of the service into shards. The few SMR-based systems that support dynamic partitioning implement ad-hoc state transfer protocols and perform scaling operations as background tasks to minimize the performance degradation during reconfigurations. In this work we go one step further and propose a modular partition transfer protocol for creating and destroying such partitions at runtime, thus providing fast elasticity for crash and Byzantine fault tolerant replicated state machines and making them more suitable for cloud systems.
Autors: Andre Nogueira;Antonio Casimiro;Alysson Bessani;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Sep 2017, volume: 28, issue:9, pages: 2486 - 2499
Publisher: IEEE
 
» Electrically Stable Carbon Nanotube Yarn Under Tensile Strain
Abstract:
We report a highly stable electrical conductance of a compact and well-oriented carbon nanotube yarn under tensile strain. The gauge factor of the yarn was found to be extremely small of approximately 0.15 thanks to the improvements in the dry spinning process, including multi-web spinning and heat treatment. The threshold strain , below which the yarn retains its electrical conductance stability, has also been determined to be approximately ppm. Owing to its highly stable resistance under mechanical strain, the yarn has a good potential as a wiring material for niche applications, where light weight and resistance stability are required.
Autors: Tuan-Khoa Nguyen;Toan Dinh;Hoang-Phuong Phan;Canh-Dung Tran;Abu Riduan Md. Foisal;Yong Zhu;Dzung Viet Dao;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1331 - 1334
Publisher: IEEE
 
» Electricity Auction Simulation Platform for Learning Competitive Energy Markets
Abstract:
Electricity trading is an essential aspect in the business model for all players in the electricity industry. However, electricity differs from other commodities in some fundamental aspects: it cannot be stored, its demand and supply must be matched instantaneously, and generation and transmission are performed through a complex infrastructure system. These features make the electricity market environment very different from other commodities markets.
Autors: Edgar B. Xavier;David A.V. Goncalves;Bruno H. Dias;Bruno S.M.C. Borba;
Appeared in: IEEE Potentials
Publication date: Sep 2017, volume: 36, issue:5, pages: 32 - 36
Publisher: IEEE
 
» Electrochemical Sensor for Square Wave Voltammetric Determination of Clozapine by Glassy Carbon Electrode Modified by WO3 Nanoparticles
Abstract:
A simple and sensitive sensor based on glassy carbon (GC) electrode modified by composite of multiwall carbon nanotubes and WO3 nanoparticles hydride by (MWWT) was introduced for the electrochemical determination of clozapine (CLZ). The presented sensor was characterized by the atomic force microscopy and the electrochemical impedance spectroscopy. The electro-oxidation of CLZ was investigated on modified GC electrode by cyclic voltammetry and square wave voltammetry (SWV) methods. The oxidation peak potential of clozapine on MWWT was appeared at 462 mV, which was accompanied with smaller overpotential and increase in oxidation peak current in comparing to the bare GC electrode. Under optimum conditions, the sensor provides two linear SWV responses in the range of 0.1–2 and 2–150 for CLZ with a detection limit of 30 nM. The proposed sensor was successfully used for determining CLZ in serum and urine samples and satisfactory responses were obtained.
Autors: Mohammad Reza Fat′hi;Dariush Almasifar;
Appeared in: IEEE Sensors Journal
Publication date: Sep 2017, volume: 17, issue:18, pages: 6069 - 6076
Publisher: IEEE
 
» Electromagnetic Emission-Aware Scheduling for the Uplink of Multicell OFDM Wireless Systems
Abstract:
The increasing demand for data and multimedia services, as well as the ubiquitous nature of the current generation of mobile devices have resulted in continuous network upgrades to support an ever-increasing number of users. Given that wireless communication systems rely on radiofrequency waves, the electromagnetic (EM) emissions from these systems are increasingly becoming a concern, especially in terms of adverse health effects. In order to address these concerns, we propose a novel resource allocation scheme for minimizing the EM emission of users in the uplink of multicell orthogonal frequency division multiplexing (OFDM) systems, while ensuring the quality of service. Our scheme is based on the assumption that long-term channel state information of all the users in the network is available. A new multicell user grouping that uses the received interference powers of the users of different sectors is proposed. Furthermore, we propose two power allocation algorithms to minimize EM emission. The first power allocation algorithm performs multicell iterative optimization to obtain the transmit powers of each user in the system. On the other hand, our second power allocation algorithm uses the average channel gains of the users of different sectors to obtain an approximation of the transmit power of each user without multicell iterative optimization. As a result, this approach has a reduced complexity when compared to our first power allocation algorithm. Simulation results show that our scheme reduces EM emission by up to 70% when compared to a single-cell EM emission aware scheme and by over 3 to 4 orders of magnitude when compared to spectral efficiency maximization schemes.
Autors: Yusuf Abdulrahman Sambo;Fabien Héliot;Muhammad Ali Imran;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8212 - 8222
Publisher: IEEE
 
» Electromagnetic Wave Reflection From Boundaries Defined by General Linear and Local Conditions
Abstract:
Electromagnetic boundaries, defined by the most general linear and local conditions, are considered in this paper. The conditions relate the normal components of the D and B vectors to the tangential components of the E and H vectors at each point of the boundary. Reflection of a plane wave from a planar boundary in an isotropic half-space is analyzed, and an analytic expression for the reflection dyadic is derived. It is shown that any plane wave can be decomposed in two components, which do not interact in reflection. Properties of plane waves matched to the general boundary are given. Certain special cases, arising naturally from the general theory and labeled as E-boundary, H-boundary, and EH-boundary conditions, are introduced as interesting novelties, and some of their properties are studied. Other special cases with known results are considered in verifying the theory. A possible realization of the general boundary in terms of an interface of a bianisotropic medium is discussed in the Appendix.
Autors: Ismo V. Lindell;Ari Sihvola;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4656 - 4663
Publisher: IEEE
 
» Electronically Reconfigurable FSS-Inspired Transmitarray for 2-D Beamsteering
Abstract:
A novel electronically reconfigurable transmitarray (TA) with 2-D beamsteering capability is presented in this communication. The proposed structure, inspired on frequency selective surfaces loaded with varactor diodes, allows the phase range of each TA element to be individually controlled enabling an automated steering of the main lobe of an original antenna pattern, in both elevation and azimuth planes (2-D beamsteering). This has been demonstrated on a unit-cell stacked structure with active feeding, coupled to the aperture of a standard gain horn antenna. A complete electromagnetic study using CST Microwave Studio is presented to evaluate and characterize the TA elements and the effect the proposed feeding network has on the structure’s behavior. Following initial simulations, a prototype of the active TA has been characterized. Automated antenna beamsteering with ranges up to Az = 28° and El = 26° and 1° of angular resolution, is achieved by means of electromagnetic simulations and validated against experimental results at 5.2 GHz.
Autors: Joao R. Reis;Rafael F. S. Caldeirinha;Akram Hammoudeh;Nigel Copner;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4880 - 4885
Publisher: IEEE
 
» Electrooptical Comparator: From Formula to Implementation
Abstract:
This paper is concerned with a process of transforming the mathematical representation of a multithreshold comparator to electrooptical implementations. The basic comparator converts an analog input into one of two levels at its (binary) output. If this functionality can be made periodic (as a function of the analog input), efficient implementation of analog-to-digital conversion can be realized. This paper begins by modeling such functionality as a square-wave via its representation as a Fourier series. Some mathematical manipulations are then performed aimed at tailoring the obtained representation for implementation by optical components such as waveguides and microring resonators. Thus, three basic integrated-optical devices are proposed for realizing a comparator with well-defined binary output levels and a steep transition slope between these levels.
Autors: Tamir Weinstock;Yossef Ehrlichman;Ofer Amrani;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:18, pages: 4056 - 4066
Publisher: IEEE
 
» Electrothermal Effects on Hot Carrier Injection in n-Type SOI FinFET Under Circuit-Speed Bias
Abstract:
Electrothermal study of the n-type SOI Fin-FETs at 50-nm node is performed by analytical method and numerical algorithm. The self-heating effects (SHE) are investigated and validated by commercial software and other published analytical solutions. Further, the time-dependent thermal conduction equation is solved to get the temperature response under different signal stresses, including step pulse, AC signal, and circuit-speed random stress which is mimicked by the pseudorandom binary sequence (PRBS) signal. It is found that the PRBS signal leads to a lower transient temperature peak in the n-type FinFET of an inverter than the AC signal due to the less logic transitions in the PRBS, and signal with higher frequency induces worse SHE. According to the temperature response, hot-carrier injection (HCI)-induced threshold voltage shift (TVS) in the n-type FinFET of an inverter is further captured. It is shown that TVS under PRBS stress is much lower than that the AC case with the same frequency due to less logic transitions in PRBS signal, and the TVS becomes more severe with the increase of signal frequency. Although the gradual-width structure for n-type FinFET leads to a much lower static temperature, it does not help a lot to improve dynamic temperature and TVS when the inverter is biased by AC or PRBS signals.
Autors: Peng Zhang;Wenchao Chen;Jun Hu;Wen-Yan Yin;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3802 - 3807
Publisher: IEEE
 
» Embedded Software Implementation of the SISO Adaptive Predictive Control Algorithm
Abstract:
Advancements in microelectronic technology provide the opportunity of implementing more complex and computation-heavy algorithms. One area that benefits from these advancements is the automation and control industry. Control techniques and algorithms, previously implemented in industrial and commercial personal computers, are being ported to embedded systems, taking advantage of their real-time and customization capabilities. This work introduces a software-based embedded implementation of a single-input single-output adaptive predictive control (APC) algorithm. The goal of the proposed implementation is to minimize execution time of the APC algorithm without affecting the precision of the results. The ZYBO Zynq-7000 development board was the selected platform for development and evaluation. Our proposed software-centric implementation relies on the development of libraries for matrix data storage and manipulation, and data structures to minimize data transactions. Experimental results included the comparison of APC implementations with different memory usage and data management approaches. An improvement on execution time was possible, reducing it nearly 50% from an initial implementation. Experimental results show no impact on the precision after comparing the implementation results to the results obtained using Scilab-based numerical computation.
Autors: Luis M. Gallegos-Canales;Antonio Favela-Contreras;Alfonso Ávila;Sergio O. Martínez-Chapa;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7229 - 7238
Publisher: IEEE
 
» Embroidered Electromyography: A Systematic Design Guide
Abstract:
Muscle activity monitoring or electromyography (EMG) is a useful tool. However, EMG is typically invasive, expensive and difficult to use for untrained users. A possible solution is textile-based surface EMG (sEMG) integrated into clothing as a wearable device. This is, however, challenging due to 1) uncertainties in the electrical properties of conductive threads used for electrodes, 2) imprecise fabrication technologies (e.g., embroidery, sewing), and 3) lack of standardization in design variable selection. This paper, for the first time, provides a design guide for such sensors by performing a thorough examination of the effect of design variables on sEMG signal quality. Results show that imprecisions in digital embroidery lead to a trade-off between low electrode impedance and high manufacturing consistency. An optimum set of variables for this trade-off is identified and tested with sEMG during a variable force isometric grip exercise with n = 12 participants, compared with conventional gel-based electrodes. Results show that thread-based electrodes provide a similar level of sensitivity to force variation as gel-based electrodes with about 90% correlation to expected linear behavior. As proof of concept, jogging leggings with integrated embroidered sEMG are made and successfully tested for detection of muscle fatigue while running on different surfaces.
Autors: Ali Shafti;Roger B. Ribas Manero;Amanda M. Borg;Kaspar Althoefer;Matthew J. Howard;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Sep 2017, volume: 25, issue:9, pages: 1472 - 1480
Publisher: IEEE
 
» EMG-Driven Optimal Estimation of Subject-SPECIFIC Hill Model Muscle–Tendon Parameters of the Knee Joint Actuators
Abstract:
Objective: the purpose of this paper is to propose an optimal control problem formulation to estimate subject-specific Hill model muscle–tendon (MT-) parameters of the knee joint actuators by optimizing the fit between experimental and model-based knee moments. Additionally, this paper aims at determining which sets of functional motions contain the necessary information to identify the MT-parameters. Methods: the optimal control and parameter estimation problem underlying the MT-parameter estimation is solved for subject-specific MT-parameters via direct collocation using an electromyography-driven musculoskeletal model. The sets of motions containing sufficient information to identify the MT-parameters are determined by evaluating knee moments simulated based on subject-specific MT-parameters against experimental moments. Results: the MT-parameter estimation problem was solved in about 30 CPU minutes. MT-parameters could be identified from only seven of the 62 investigated sets of motions, underlining the importance of the experimental protocol. Using subject-specific MT-parameters instead of more common linearly scaled MT-parameters improved the fit between inverse dynamics moments and simulated moments by about 30% in terms of the coefficient of determination (from to ) and by about 26% in terms of the root mean square error (from to ). In particular, subject-specific MT-parameters of the knee flexors were very different from linearly scaled MT-parameters. Conclus- on: we introduced a computationally efficient optimal control problem formulation and provided guidelines for designing an experimental protocol to estimate subject-specific MT-parameters improving the accuracy of motion simulations. Significance: the proposed formulation opens new perspectives for subject-specific musculoskeletal modeling, which might be beneficial for simulating and understanding pathological motions.
Autors: Antoine Falisse;Sam Van Rossom;Ilse Jonkers;Friedl De Groote;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Sep 2017, volume: 64, issue:9, pages: 2253 - 2262
Publisher: IEEE
 
» Empirical Multiphase Dielectric Mixing Model for Cement-Based Materials Containing Alkali-Silica Reaction Gel
Abstract:
Alkali-silica reaction (ASR) is a common cause of concrete deterioration. Water (either in free or bound form), in the presence of reactive aggregates, plays a major role in the reaction itself and in the formation and expansion of the deleterious gel produced. Since microwave signals are sensitive to the presence of water in dielectric materials, microwave materials characterization techniques have the potential to detect and monitor ASR gel in concrete structures. Dielectric mixing models are physics-based models that relate the macroscopic (i.e., effective) dielectric constant of a material to the dielectric constant of its constituents and their respective volumetric contents. In this investigation, an empirical multiphase dielectric mixing model is developed in conjunction with measured dielectric constants of two sets of mortar samples with ASR-reactive and nonreactive aggregates at R-band (1.7–2.6 GHz). The proposed model is capable of closely predicting the effective (temporal) dielectric constant of the samples. The modeling results are validated by a comparison with the measured temporal dielectric constant of the samples, showing good agreement. Through this investigation, quantitative information on the influence of constituents of ASR-reactive mortar samples (including ASR gel) are obtained, and the pertinent results indicate significant potential for microwave materials characterization techniques for ASR detection and evaluation.
Autors: Ashkan Hashemi;Kimberly E. Kurtis;Kristen M. Donnell;Reza Zoughi;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Sep 2017, volume: 66, issue:9, pages: 2428 - 2436
Publisher: IEEE
 
» Emulating Short-Term and Long-Term Plasticity of Bio-Synapse Based on Cu/a-Si/Pt Memristor
Abstract:
Short-term plasticity and long-term plasticity of bio-synapse are thought to underpin critical physiological functions in neural circuits. In this letter, we vividly emulated the short-term and long-term synaptic functions in a single Cu/a-Si/Pt memristor. By controlling the injection quantity of Cu cations into the a-Si layer, the device showed volatile and non-volatile resistive switching behaviors. Owing to the unique characteristics of Cu/a-Si/Pt device, the short-term synaptic functions, i.e., short-term potentiation, pair-pulse facilitation, and long-term functions, i.e., long-term potentiation/depression, spike-timing-dependent plasticity, were mimicked in the memristor successfully. Furthermore, the transition from short-term memory to long-term memory of the device was also observed under repeated stimuli. The experimental results confirm that the Cu/a-Si/Pt memristor with various synaptic behaviors has a potential application in the brain-inspired computing systems.
Autors: Xumeng Zhang;Sen Liu;Xiaolong Zhao;Facai Wu;Quantan Wu;Wei Wang;Rongrong Cao;Yilin Fang;Hangbing Lv;Shibing Long;Qi Liu;Ming Liu;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1208 - 1211
Publisher: IEEE
 
» Enabling Anonymous Authorization and Rewarding in the Smart Grid
Abstract:
The smart grid leverages infrastructural support to achieve fine-grained power consumption monitoring in an attempt to offer higher efficiency, reliability, and security. Such functionality, however, requires the collection of fine-grained usage data which may raise serious concerns with respect to consumer privacy. Thus far, existing work has solely focused on the problem of privately aggregating energy measurements. However, these solutions do not allow the provider to acquire detailed energy measurements which are essential for maintaining the network, debugging configuration problems, etc. In this work, we address this problem and we propose an authentication scheme that allows a smart meter to anonymously interact with the utility provider when submitting detailed consumption data. We then move one step further, enabling the incorporation of anonymous rewarding mechanisms in the smart grid in exchange for detailed measurements that users report. We argue that such rewarding mechanisms provide solid incentives for users to accept the release of their detailed energy consumption; we show that our proposal does notleak any information about the identity of users—even when redeeming the rewards. Finally, we implement a prototype based on our proposal and we evaluate its performance in realistic deployment settings.
Autors: Tassos Dimitriou;Ghassan O. Karame;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Sep 2017, volume: 14, issue:5, pages: 565 - 572
Publisher: IEEE
 
» Enabling Efficient and Reliable Transition from Replication to Erasure Coding for Clustered File Systems
Abstract:
To balance performance and storage efficiency, modern clustered file systems often first store data with replication, followed by encoding the replicated data with erasure coding. We argue that the commonly used random replication does not take into account erasure coding in its design, thereby raising both performance and availability issues in the subsequent encoding operation. We propose encoding-aware replication, which carefully places the replicas so as to (i) eliminate cross-rack downloads of data blocks during the encoding operation, (ii) preserve availability without data relocation after the encoding operation, and (iii) maintain load balancing across replicas as in random replication before the encoding operation. We conduct extensive HDFS-based testbed experiments and discrete-event simulations, and demonstrate the performance gains of encoding-aware replication over random replication.
Autors: Runhui Li;Yuchong Hu;Patrick P. C. Lee;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Sep 2017, volume: 28, issue:9, pages: 2500 - 2513
Publisher: IEEE
 
» Enabling Highly Efficient Spectral Discretization-Based Eigen-Analysis Methods by Kronecker Product
Abstract:
This letter presents a computationally efficient approach to implement the spectral discretization-based methods for eigenanalysis of large delayed cyber-physical power system by intensively exploiting the unique property of Kronecker product. Theoretical analyses and numerical tests demonstrate the novelty and effectiveness of the efficiently implemented explicit infinitesimal generator discretization method.
Autors: Hua Ye;Qianying Mou;Yutian Liu;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4148 - 4150
Publisher: IEEE
 
» Encoding and Decoding for Multicell Massive MIMO Systems
Abstract:
For a multicell, massive multiple-input multiple-output (MIMO) system with pilot reuse, pilot contamination largely degrades the performance of the system. One prominent effect caused by the pilot contamination is the existence of the error floor, that is, the error probability of the system cannot go to zero, even when the signal-to-noise ratio (SNR) of the system goes to infinity. This paper proposes new encoding and decoding schemes to reduce the error floor. In fact, based on the detailed analysis on the massive MIMO system, the design criterion of the encoding is proposed, and several concrete code design examples are given. Moreover, two decoding methods based on the oblique projection are presented, which have lower decoding complexity than the ML decoding while having good error performance. Simulation results show that our schemes have better performance than the system with the minimum mean square error (MMSE) decoder.
Autors: Mengyun Ying;Haiquan Wang;Feng Liu;Wei Zhang;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 7964 - 7973
Publisher: IEEE
 
» End-to-End Analysis of Integration for Thermocouple-Based Sensors Into 3-D ICs
Abstract:
Solutions to the integration challenges of a new thermal sensor technology into 3-D integrated circuits (ICs) will be discussed in this paper. Our proposed architecture uses bimetallic thin-film thermocouples, which are thermally linked to points of measurement throughout the 3-D stack with dedicated vias. These vias will be similar to thermal through-silicon vias (TSVs) in structure, yet different in functionality. We propose a low-overhead design methodology by linking the sensor placement task with the existing thermal TSV planning phase for 3-D ICs. A fraction of thermal TSV resources is decoupled from their original use and repurposed for the temperature sensing infrastructure. Tradeoffs concerning the reduction of the thermal TSV resources are investigated. Furthermore, we present an end-to-end system, including the physical realization of the sensor network as well as its analog interface circuitry with the sensor data sampling unit. We demonstrate the operation and correctness of this interface with transistor-level simulations. Next, through thermal modeling and simulation using a state-of-the-art tool (FloTHERM), we demonstrate that we can achieve high accuracy (1 °C error) in temperature tracking while still maintaining the effectiveness of the thermal TSVs in heat management (conforming to a peak temperature constraint of 95 °C).
Autors: Dawei Li;Siddhartha Joshi;Ji-Hoon Kim;Seda Ogrenci-Memik;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Sep 2017, volume: 25, issue:9, pages: 2498 - 2511
Publisher: IEEE
 
» Energy and Lifetime Optimizations for Dark Silicon Manycore Microprocessor Considering Both Hard and Soft Errors
Abstract:
In this paper, we propose a new energy and lifetime optimization techniques for emerging dark silicon manycore microprocessors considering both hard long-term reliability effects (hard errors) and transient soft errors, which have been studied less in the past. We consider a recently proposed physics-based electromigration (EM) reliability model to predict the EM-induced reliability. We employ both dynamic voltage and frequency scaling (DVFS) and dark silicon core state using ON/OFF switching action as the two control knobs. We show that on-chip power consumption has different (even contradicting) impacts on soft and hard reliability effects. This paper also shows that soft error should be mitigated by other techniques if aggressive low power and high long-term reliability are pursued. We focus on two optimization techniques for improving lifetime and reducing energy. To optimize EM-induced lifetime, we first apply the adaptive Q-learning-based method, which is suitable for dynamic runtime operation as it can provide cost-effective yet good solutions. The second lifetime optimization approach is the mixed-integer linear programming (MILP) method, which typically yields better solutions but at higher computational costs. To optimize the energy of a dark silicon chip subject to the both hard and soft reliability effects, power budgets, and performance limits, the Q-learning method has been applied as well. A large class of multithreaded applications is used as our benchmarks to validate and compare the proposed dynamic reliability management methods. Experimental results on a 64-core dark silicon chip show that the proposed DRM algorithm can effectively manage and optimize the lifetime of a dark silicon microprocessor under the given power budget and performance limit. Also, the proposed energy optimization can effectively manage and optimize energy consumption subject to both hard and soft-error rates, power budget, and performance limits as constraints. We also sho- that the under tightened power and performance constraints, we cannot satisfy both hard and soft errors at the same time as there is no simple tradeoff between performance/power and reliability in this case. Some other soft-error mitigation techniques are required in this case.
Autors: Taeyoung Kim;Zeyu Sun;Hai-Bao Chen;Hai Wang;Sheldon X.-D. Tan;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Sep 2017, volume: 25, issue:9, pages: 2561 - 2574
Publisher: IEEE
 
» Energy Efficiency Maximization of Full-Duplex Two-Way Relay With Non-Ideal Power Amplifiers and Non-Negligible Circuit Power
Abstract:
In this paper, we maximize the energy efficiency (EE) of full-duplex (FD) two-way relay (TWR) systems under non-ideal power amplifiers (PAs) and non-negligible transmission-dependent circuit power. We start with the case where only the relay operates full duplex and two timeslots are required for TWR. Then, we extend to the advanced case, where the relay and the two nodes all operate full duplex, and accomplish TWR in a single timeslot. In both cases, we establish the intrinsic connections between the optimal transmit powers and durations, based on which the original non-convex EE maximization can be convexified and optimally solved. Simulations show the superiority of FD-TWR in terms of EE, especially when traffic demand is high. The simulations also reveal that the maximum EE of FD-TWR is more sensitive to the PA efficiency, than it is to self-cancellation. The full FD design of FD-TWR is susceptible to traffic imbalance, while the design with only the relay operating in the FD mode exhibits strong tolerance.
Autors: Qimei Cui;Yuhao Zhang;Wei Ni;Mikko Valkama;Riku Jäntti;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6264 - 6278
Publisher: IEEE
 
» Energy Efficient Data Acquisition Techniques Using Context Aware Sensing for Landslide Monitoring Systems
Abstract:
Real-time wireless sensor networks are an emerging technology for continuous environmental monitoring. But real-world deployments are constrained by resources, such as power, memory, and processing capabilities. In this paper, we discuss a set of techniques to maximize the lifetime of a system deployed in south India for detecting rain-fall induced landslides. In this system, the sensing subsystem consumes 77.5%, the communication subsystem consumes 22%, and the processing subsystem consumes 0.45% of total power consumption. Hence, to maximize the lifetime of the system, the sensing subsystem power consumption has to be reduced. The major challenge to address is the development of techniques that reduce the power consumption, while preserving the reliability of data collection and decision support by the system. This paper proposes a wavelet-based sampling algorithm for choosing the minimum sampling rate for ensuring the data reliability. The results from the wavelet sampling algorithm along with the domain knowledge have been used to develop context aware data collection models that enhance the lifetime of the system. Two such models named context aware data management (CAD) and context aware energy management (CAE) have been devised. The results show that the CAD model extends the lifetime by six times and the CAE model does so by 20 times when compared with the continuous data collection model, which is the existing approach. In this paper, we also developed mathematical modeling for CAD and CAE, which have been validated using real-time data collected in the past.
Autors: Rekha Prabha;Maneesha Vinodini Ramesh;Venkat P. Rangan;P. V. Ushakumari;T. Hemalatha;
Appeared in: IEEE Sensors Journal
Publication date: Sep 2017, volume: 17, issue:18, pages: 6006 - 6018
Publisher: IEEE
 
» Energy Efficient Localization Algorithm With Improved Accuracy in Cognitive Radio Networks
Abstract:
An energy efficient localization algorithm with high accuracy for the cognitive radio networks (CRNs) is proposed in this letter. The key idea underlying this proposed algorithm is to provide the optimal transmission range for secondary users (SUs) to minimize the power consumption of the overall CRNs. Since energy efficiency is a key factor to consider in designing a node in the CRNs, location information of primary users (PUs) and SUs is valuable to calculate the optimal transmission range so that a spectrally efficient CRN can opportunistically take advantage of the spectrum with no or little interference to the PUs. In addition, the optimal positions of the SUs with known location are determined to improve the final localization accuracy for the whole CRN, which enables the optimal transmission range to be obtained. Thereby, the users in the CRN are localized with minimum energy consumption for a given target root mean square error. Simulation results validate the effectiveness of the proposed algorithm by showing the optimal transmission range for various number of users in the network.
Autors: Nasir Saeed;Haewoon Nam;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 2017 - 2020
Publisher: IEEE
 
» Energy Efficient Precoding Design for SWIPT in MIMO Two-Way Relay Networks
Abstract:
This paper deals with the energy efficiency (EE) maximization problem in multiple-input multiple-output two-way relay networks with simultaneous wireless information and power transfer. The network consists of a multiple-antenna amplify-and-forward relay node which provides bidirectional communications between two multiple-antenna transceiver nodes. In addition, one of the transceivers is considered battery limited and has the capability of energy harvesting from the received signals. Assuming the network EE as the objective function, we design power splitting factor and optimum precoding matrices at the relay node and two transceivers. The constraints are transmit power of the nodes, harvested energy and quality of service of two transceivers. The resulting non-convex optimization problem is divided into three sub-problems which are then solved via an alternation approach. In addition, sufficient conditions for optimality are derived and the computational complexity of the proposed algorithm is analyzed. Simulation results are provided to evaluate the performance and confirm the efficiency of the proposed scheme as well as its convergence.
Autors: Javane Rostampoor;S. Mohammad Razavizadeh;Inkyu Lee;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 7888 - 7896
Publisher: IEEE
 
» Energy Efficient User Association and Power Allocation in Millimeter-Wave-Based Ultra Dense Networks With Energy Harvesting Base Stations
Abstract:
Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology are expected to increase both energy efficiency and spectral efficiency. In this paper, user association and power allocation in mmWave-based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. The joint user association and power optimization problem are modeled as a mixed-integer programming problem, which is then transformed into a convex optimization problem by relaxing the user association indicator and solved by Lagrangian dual decomposition. An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point. The complexity of the proposed algorithm is analyzed and its effectiveness compared with existing methods is verified by simulations.
Autors: Haijun Zhang;Site Huang;Chunxiao Jiang;Keping Long;Victor C. M. Leung;H. Vincent Poor;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Sep 2017, volume: 35, issue:9, pages: 1936 - 1947
Publisher: IEEE
 
» Energy Storage in Microgrids: Compensating for Generation and Demand Fluctuations While Providing Ancillary Services
Abstract:
Driven by global environmental emission issues, energy access in remote communities, and tighter requirements for system resilience and reliability, electricity production is shifting from a centralized paradigm to a decentralized one. In this context, renewable energy sources (RESs) have proliferated over the past decade, exhibiting a steadily increasing trend. Thus, today, a large number of wind turbines and photovoltaic (PV) panels are connected to medium- (1-69 kV) and low-voltage (=1 kV) grids, with traditional integrated bulk power systems becoming decentralized in the presence of active distribution networks, where the flow of power is bidirectional between generators and "prosumers." In particular, with decreasing RES s costs, these technologies are becoming attractive solutions to bring energy to remote communities and/or replace expensive fossil-fuel-based generators. However, RES s such as wind and solar are intermittent sources of energy, difficult to predict, and prone to large output fluctuations-therefore, significantly affecting system voltage and frequency.
Autors: Mostafa Farrokhabadi;Bharatkumar V. Solanki;Claudio A. Canizares;Kankar Bhattacharya;Sebastian Koenig;Patrick S. Sauter;Thomas Leibfried;Sören Hohmann;
Appeared in: IEEE Power and Energy Magazine
Publication date: Sep 2017, volume: 15, issue:5, pages: 81 - 91
Publisher: IEEE
 
» Energy Storage Systems: Applications, Regulations, & Renewable Resources [From the Editor]
Abstract:
Presents the introductory editorial for this issue of the publication.
Autors: Michael Henderson;
Appeared in: IEEE Power and Energy Magazine
Publication date: Sep 2017, volume: 15, issue:5, pages: 4 - 8
Publisher: IEEE
 
» Energy Storage: From Holywood Stunt Double to Action Hero [In My View]
Abstract:
Discusses the growing market for advanced battery-based energy storage systems and reports on applications for their use.
Autors: J. Chris Shelton;
Appeared in: IEEE Power and Energy Magazine
Publication date: Sep 2017, volume: 15, issue:5, pages: 112 - 108
Publisher: IEEE
 
» Energy-Efficient and Adaptive Design for Wireless Power Transfer in Electric Vehicles
Abstract:
Wireless power transfer (WPT) could revolutionize global transportation and accelerate growth in the electric vehicle (EV) market, offering an attractive alternative to cabled charging. Coil misalignment is inevitable due to driver parking behavior and has a detrimental effect on power transfer efficiency (PTE). This paper proposes a novel coil design and adaptive hardware to improve PTE in magnetic resonant coupling WPT and mitigate coil misalignment, a crucial roadblock in the acceptance of WPT for EVs. The new design was verified using ADS, providing a good match to theoretical analysis. Custom designed receiver and transmitter circuitry was used to simulate vehicle and parking bay conditions and obtain PTE data in a small-scale setup. Experimental results showed that PTE can be improved by 30% at the array's center, and an impressive 90% when misaligned by three-fourths of the array's radius. The proposed novel coil array achieves overall higher PTE compared to the benchmark single coil design.
Autors: Xiaolin Mou;Oliver Groling;Hongjian Sun;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Sep 2017, volume: 64, issue:9, pages: 7250 - 7260
Publisher: IEEE
 

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