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

» Improvement of Subthreshold Characteristic of Gate-Recessed AlGaN/GaN Transistors by Using Dual-Gate Structure
Abstract:
The subthreshold characteristic of gate-recessed high-electron-mobility transistors (HEMTs) using dual-gate (DG) architectures is systematically studied. The recessed DG structure can effectively shift the threshold voltage () in the positive direction. Different from the complex function expression between and AlGaN thickness () in the recessed single-gate (SG) device, the variation of with is monotonic in the recessed DG devices. Recessed DG device exhibits a low off-state leakage current of A/mm and gate induced drain leakage is effectively improved. A higher range of recessed DG devices broadens about 2 times and provide a wider range of than that of recessed SG devices. The DG structure has a stronger modulation effect on drain–source resistance () and gate–drain resistance () than the SG devices. A lower subthreshold swing (SS) of ~100 mV/dec is obtained by recessed DG design. Due to the second gate inducing the lateral extension of depletion - egion between the first gate and drain, the off-state leakage and first gate reverse leakage have been significantly improved. Therefore, the recessed DG architecture design can effectively improve the fluctuation of SS and off-state current versus the different AlGaN barrier thickness.
Autors: Ling Yang;Minhan Mi;Bin Hou;Jiejie Zhu;Meng Zhang;Yunlong He;Yang Lu;Qing Zhu;Xiaowei Zhou;Ling Lv;Yanrong Cao;Xiaohua Ma;Yue Hao;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4057 - 4064
Publisher: IEEE
 
» Improving IBM POWER8 Performance Through Symbiotic Job Scheduling
Abstract:
Symbiotic job scheduling, i.e., scheduling applications that co-run well together on a core, can have a considerable impact on the performance of processors with simultaneous multithreading (SMT) cores. SMT cores share most of their microarchitectural components among the co-running applications, which causes performance interference between them. Therefore, scheduling applications with complementary resource requirements on the same core can greatly improve the throughput of the system. This paper enhances symbiotic job scheduling for the IBM POWER8 processor. We leverage the existing cycle accounting mechanism to build an interference model that predicts symbiosis between applications. The proposed models achieve higher accuracy than previous models by predicting job symbiosis from throttled CPI stacks, i.e., CPI stacks of the applications when running in the same SMT mode to consider the statically partitioned resources, but without interference from other applications. The symbiotic scheduler uses these interference models to decide, at run-time, which applications should run on the same core or on separate cores. We prototype the symbiotic scheduler as a user-level scheduler in the Linux operating system and evaluate it on an IBM POWER8 server running multiprogram workloads. The symbiotic job scheduler significantly improves performance compared to both an agnostic random scheduler and the default Linux scheduler. Across all evaluated workloads in SMT4 mode, throughput improves by 12.4 and 5.1 percent on average over the random and Linux schedulers, respectively.
Autors: Josué Feliu;Stijn Eyerman;Julio Sahuquillo;Salvador Petit;Lieven Eeckhout;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Oct 2017, volume: 28, issue:10, pages: 2838 - 2851
Publisher: IEEE
 
» Improving Identification of Key Players in Aging via Network De-Noising and Core Inference
Abstract:
Current “ground truth” knowledge about human aging has been obtained by transferring aging-related knowledge from well-studied model species via sequence homology or by studying human gene expression data. Since proteins function by interacting with each other, analyzing protein-protein interaction (PPI) networks in the context of aging is promising. Unlike existing static network research of aging, since cellular functioning is dynamic, we recently integrated the static human PPI network with aging-related gene expression data to form dynamic, age-specific networks. Then, we predicted as key players in aging those proteins whose network topologies significantly changed with age. Since current networks are noisy , here, we use link prediction to de-noise the human network and predict improved key players in aging from the de-noised data. Indeed, de-noising gives more significant overlap between the predicted data and the “ground truth” aging-related data. Yet, we obtain novel predictions, which we validate in the literature. Also, we improve the predictions by an alternative strategy: removing “redundant” edges from the age-specific networks and using the resulting age-specific network “cores” to study aging. We produce new knowledge from dynamic networks encompassing multiple data types, via network de-noising or core inference, complementing the existing knowledge obtained from sequence or expression data.
Autors: Boyoung Yoo;Fazle Elahi Faisal;Huili Chen;Tijana Milenković;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Oct 2017, volume: 14, issue:5, pages: 1056 - 1069
Publisher: IEEE
 
» Improving Performance for Flash-Based Storage Systems through GC-Aware Cache Management
Abstract:
Flash-based SSDs have been extensively deployed in modern storage systems to satisfy the increasing demand of storage performance and energy efficiency. However, Garbage Collection (GC) is an important performance concern for flash-based SSDs, because it tends to disrupt the normal operations of an SSD. This problem continues to plague flash-based storage systems, particularly in the high performance computing and enterprise environment. An important root cause for this problem, as revealed by previous studies, is the serious contention for the flash resources and the severe mutually adversary interference between the user I/O requests and GC-induced I/O requests. The on-board buffer cache within SSDs serves to play an essential role in smoothing the gap between the upper-level applications and the lower-level flash chips and alleviating this problem to some extend. Nevertheless, the existing cache replacement algorithms are well optimized to reduce the miss rate of the buffer cache by reducing the I/O traffic to the flash chips as much as possible, but without considering the GC operations within the flash chips. Consequently, they fail to address the root cause of the problem and thus are far from being sufficient and effective in reducing the expensive I/O traffic to the flash chips that are in the GC state. To address this important performance issue in flash-based storage systems, particularly in the HPC and enterprise environment, we propose a Garbage Collection aware Replacement policy, called GCaR, to improve the performance of flash-based SSDs. The basic idea is to give higher priority to caching the data blocks belonging to the flash chips that are in the GC state. This substantially lessens the contentions between the user I/O operations and the GC-induced I/O operations. To verify the effectiveness of GCaR, we have integrated it into the SSD extended Disksim simulator. The simulation results show that GCaR can significantly improve the storage performan- e by up to 40.7 percent in terms of the average response times.
Autors: Suzhen Wu;Bo Mao;Yanping Lin;Hong Jiang;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Oct 2017, volume: 28, issue:10, pages: 2852 - 2865
Publisher: IEEE
 
» Improving Supervised Learning Classification Methods Using Multigranular Linguistic Modeling and Fuzzy Entropy
Abstract:
Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process play a very important role in achieving this objective. Therefore, it is important to represent the data in a way that best expresses its meaning. For this purpose, we propose to apply linguistic modeling methods in order to obtain a linguistic representation. With the help of multigranular linguistic modeling, data can be transformed and expressed using different (unbalanced) linguistic label sets. Expressing the data using linguistic expressions instead of numbers increases the readability and reduces the complexity of the problem, and data recovering methods allow us to manually control the level of precision. In this paper, several datasets are transformed and utilized for classification tasks using several supervised learning algorithms. For each combination of datasets and algorithms, the data have been expressed using several linguistic label sets that have different granularity values. After carrying out the testing processes, we can conclude that, in some cases, reducing data complexity leads to better classification results. Therefore, it is found that linguistic representation of the training data with just the necessary and sufficient precision can improve the reliability of the classification process.
Autors: Juan Antonio Morente-Molinera;József Mezei;Christer Carlsson;Enrique Herrera-Viedma;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1078 - 1089
Publisher: IEEE
 
» Improving the Algorithm of Extracting Regional Total Precipitable Water Vapor Over Land From MODIS Images
Abstract:
Precise estimation of total precipitable water vapor (TPW) with high temporal and spatial resolutions is of great importance in different disciplines. Moderate-Resolution Imaging Spectroradiometer (MODIS) is one of the sensors which have absorption and nonabsorption bands of water vapor. There is a standard algorithm to produce TPW product of MODIS (MOD05/MYD05) which uses the ratios of reflectances in strong, moderate, and weak absorption bands of water vapor to nonabsorption ones (transmission). This paper aims to present a method based on this algorithm to optimize TPW estimation in local scale. To do so, the western part of Iran was chosen as the study region. Terra MODIS images and MOD05 in clear-sky conditions related to the 100 days in four seasons of 2015–2016 were provided as the selected data. To validate and improve the results, TPW measured in six radiosonde stations and interpolated for overpass time of Terra was utilized. Four procedures were performed. In the first procedure, the coefficients of transmissions were extracted using linear least-squares technique, separately. For the second procedure, the coefficients were calculated in terms of the highest atmospheric transmission sensitivity to TPW for each absorption band separately, and in the third procedure, they were calculated simultaneously. In the last procedure, the errors from third one were modeled with a linear relationship between reflectance ratios of absorption bands. Based on the results, in highest accuracy, the coefficient of determination and Root Mean Square Error was 0.878 and 2.702 mm, respectively, which were acceptable comparing those of other researchers.
Autors: Mohammad Hossein Merrikhpour;Majid Rahimzadegan;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5889 - 5898
Publisher: IEEE
 
» Improving the Speed of Center of Sets Type Reduction in Interval Type-2 Fuzzy Systems by Eliminating the Need for Sorting
Abstract:
In the deployment of interval type-2 fuzzy systems, one of the most important steps is the type reduction. The commonly used center of sets type reducer requires the solution of two nonlinear constrained optimization problems. Frequently used approaches to solve them are the Karnik–Mendel algorithms and their variants. However, these algorithms suffer from the need for sorting, which is known to be computationally very expensive. Using the reformulations proposed in this paper for center of sets type reducer, it is possible to eliminate the need for sorting. This makes interval type-2 fuzzy systems more appropriate for cost-sensitive real-time applications. Extensive simulations are presented to illustrate the faster convergence speed of the proposed method over six other enhanced variants of the Karnik–Mendel algorithm as applied to center of sets type reduction of interval type-2 fuzzy systems.
Autors: Mojtaba Ahmadieh Khanesar;Alireza Jalalian Khakshour;Okyay Kaynak;Huijun Gao;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1193 - 1206
Publisher: IEEE
 
» Impulse Response Measurement of Few-Mode Fiber Systems by Coherence-Recovered Linear Optical Sampling
Abstract:
This paper presents impulse response measurements of few-mode optical fibers and transmission lines that were obtained by using coherence-recovered linear optical sampling or a two-comb interferometer. When performing a measurement, the probe pulse source and the sampling pulse source may be far from each other, particularly when the fibers are installed in the field, and the fiber length may exceed several tens kilometers. In this paper, by modifying a previously proposed referencing technique, the coherence between two pulse lasers is equivalently maintained by canceling out the phase noise caused both by the light sources and perturbations in the fiber. Hence, the amplitude averaging is used to enhance the signal-to-noise ratio. As a result, we can measure the impulse responses of multimode fibers with a dynamic range of 80 dB and a time resolution of a few picoseconds, over tens nanoseconds of differential mode delay.
Autors: Naoto Kono;Fumihiko Ito;Daisuke Iida;Tetsuya Manabe;
Appeared in: Journal of Lightwave Technology
Publication date: Oct 2017, volume: 35, issue:20, pages: 4392 - 4398
Publisher: IEEE
 
» In Situ Shape Estimation of Triangular Moored Hydrophone Arrays Using Ambient Signals
Abstract:
In this paper, a method is presented for correcting relative errors in the locations of individual sensors in a three-element bottom-moored array, using ambient signal arrivals recorded by the array. It has the benefit that knowledge of absolute source positions is not required to determine the relative shape of the array. The procedure is demonstrated using episodic ambient signal arrivals recorded by the southern array of the Wake Island hydrophone station, which is a component of the Comprehensive Nuclear-Test Ban Treaty Organization's (CTBTO) International Monitoring System (IMS). The original coordinates of sensors 2 and 3 were adjusted by 75 and 115 m, respectively, removing approximately 4 of error in estimating the arrival angles of signals. The estimated coordinates compared favorably with the results of a position revision by the CTBTO a year after the triad installation.
Autors: Stephen M. Nichols;David L. Bradley;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 923 - 935
Publisher: IEEE
 
» In-Plane-Gate GaN Transistors for High-Power RF Applications
Abstract:
In-plane-gate field-effect transistors (IPGFETs) offer an innovative device architecture in which the channel conductivity is modulated by the electric field from the 2D electron gas in the two adjacent in-plane gates, isolated by etched trenches. The planar nature of the gate electrode yields a huge reduction in parasitic gate capacitance, which can lead to much higher frequency. Moreover, the fabrication process for these devices is extremely simple and with inherently self-aligned gates. Here, we combine for the first time the promising architecture of IPGFETs with the exceptional properties of III-Nitrides, such as large carrier density and breakdown field, to reveal their enormous potential for high-power RF devices. AlGaN/GaN IPGFETs demonstrated large drain current up to 1.4 A/mm and transconductance up to 665 mS/mm, which are, respectively, nine times- and five times-larger than the best IPGFETs demonstrated in other semiconductors. These devices presented excellent gate control with ON–OFF ratio up to along with ultra-low capacitances down to 0.7 aF, leading to an estimated up to 0.89 THz. Extremely large breakdown voltage of 500 V was observed despite their nanoscale dimensions, with small leakage current below 1 nA up to 300 V. These results reveal that III-Nitride IPGFETs offer a promising pathway for future terahertz devices delivering large output powers.
Autors: Giovanni Santoruvo;Elison Matioli;
Appeared in: IEEE Electron Device Letters
Publication date: Oct 2017, volume: 38, issue:10, pages: 1413 - 1416
Publisher: IEEE
 
» Incentivizing Crowdsensing With Location-Privacy Preserving
Abstract:
Crowd sensing systems enable a wide range of data collection, where the data are usually tagged with private locations. How to incentivize users to participate in such systems while preserving location-privacy is coming up as a critical issue. To this end, we consider location-privacy protection when motivating users to sense data instead of viewing them separately. Without loss of generality, -anonymity is utilized to reduce the risk of location-privacy disclosure. Specifically, we propose a location aggregation method to cluster users into groups for -anonymity preserving, and meanwhile mitigating the incurred information loss. After that, an incentive mechanism is carefully designed to select efficient users and calculate rational compensations based on clustered groups obtained in location aggregation, where the influences of both the information loss and -anonymity in location-privacy preserving are captured into group values and sensing costs. Through theoretical analysis and extensive performances evaluated on real and synthetic data, we find out that the incentive payment increases sharply with more stringent privacy protection and the information loss can be further mitigated compared with conventional methods.
Autors: Xiong Wang;Zhe Liu;Xiaohua Tian;Xiaoying Gan;Yunfeng Guan;Xinbing Wang;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6940 - 6952
Publisher: IEEE
 
» Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion
Abstract:
In this paper, we investigate the sample size requirement for a general class of nuclear norm minimization methods for higher order tensor completion. We introduce a class of tensor norms by allowing for different levels of coherence, which allows us to leverage the incoherence of a tensor. In particular, we show that a th-order tensor of multilinear rank and dimension can be recovered perfectly from as few as uniformly sampled entries through an appropriate incoherent nuclear norm minimization. Our results demonstrate some key differences between completing a matrix and a higher order tensor: they not only point to potential room for improvement over the usual nuclear norm minimization but also highlight the importance of explicitly accounting for incoherence, when dealing with higher order tensors. Although our focus is primarily on the theoretical guarantees for nuclear norm minimization, such insights may prove useful for understanding performance of other related methods and developing improved practical algorithms.
Autors: Ming Yuan;Cun-Hui Zhang;
Appeared in: IEEE Transactions on Information Theory
Publication date: Oct 2017, volume: 63, issue:10, pages: 6753 - 6766
Publisher: IEEE
 
» Incorporating Intelligence in Fog Computing for Big Data Analysis in Smart Cities
Abstract:
Data intensive analysis is the major challenge in smart cities because of the ubiquitous deployment of various kinds of sensors. The natural characteristic of geodistribution requires a new computing paradigm to offer location-awareness and latency-sensitive monitoring and intelligent control. Fog Computing that extends the computing to the edge of network, fits this need. In this paper, we introduce a hierarchical distributed Fog Computing architecture to support the integration of massive number of infrastructure components and services in future smart cities. To secure future communities, it is necessary to integrate intelligence in our Fog Computing architecture, e.g., to perform data representation and feature extraction, to identify anomalous and hazardous events, and to offer optimal responses and controls. We analyze case studies using a smart pipeline monitoring system based on fiber optic sensors and sequential learning algorithms to detect events threatening pipeline safety. A working prototype was constructed to experimentally evaluate event detection performance of the recognition of 12 distinct events. These experimental results demonstrate the feasibility of the system's city-wide implementation in the future.
Autors: Bo Tang;Zhen Chen;Gerald Hefferman;Shuyi Pei;Tao Wei;Haibo He;Qing Yang;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2140 - 2150
Publisher: IEEE
 
» Incremental SAT-Based Reverse Engineering of Camouflaged Logic Circuits
Abstract:
Layout-level gate or routing camouflaging techniques have attracted interest as countermeasures against reverse engineering of combinational logic. In order to minimize area overhead, typically only a subset of gate or routing components are camouflaged, and each camouflaged component layout can implement one of a few different functions or connections. The security of camouflaging relies on the difficulty of learning the overall combinational logic function without knowing the functions implemented by the individual camouflaged components of the circuit. In this paper, we expand our previous work on using incremental SAT solving to reconstruct the logical function of a circuit with camouflaged components. Our algorithm uses the standard attacker model in which an adversary knows only the noncamouflaged component functions, and has the ability to query the circuit to learn the correct output vector for any input vector. Our results demonstrate a speedup in average runtime over the best known existing deobfuscation algorithm prior to this technique. The results presented go beyond our previous work by showing that this technique, previously applied only to a particular style of gate camouflaging, is general and can be used to deobfuscate three different proposed styles of camouflaging. We give results to quantify the effectiveness of camouflaging techniques on a variety of ISCAS-85 benchmark circuits.
Autors: Cunxi Yu;Xiangyu Zhang;Duo Liu;Maciej Ciesielski;Daniel Holcomb;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Oct 2017, volume: 36, issue:10, pages: 1647 - 1659
Publisher: IEEE
 
» Indirect-Reciprocity Data Fusion Game and Application to Cooperative Spectrum Sensing
Abstract:
Data sharing is one critical step to implement data fusion, and how to encourage sensors to share their data is an important issue. In this paper, we propose a reputation-based incentive framework, where the data sharing stimulation problem is modeled as an indirect reciprocity game. In the proposed game, sensors choose how to report their results to the fusion center and gain reputations, based on which they can obtain certain benefits in the future. Taking the sensing and fusion accuracy into account, reputation distribution is introduced in the proposed game, where we prove theoretically the Nash equilibrium of the game and its uniqueness. Furthermore, we apply the proposed scheme to the cooperative spectrum sensing. We show that within an appropriate cost-to-gain ration, the optimal strategy for the secondary users is to report when the average received energy is above a given threshold and keep silence otherwise. Such an optimal strategy is also proved to be a desirable evolutionarily stable strategy. Finally, simulation results are shown to verify the theoretical results and demonstrate that compared with the existing schemes, our proposed scheme achieves better operating characteristic curve and higher system throughput with convincing performance on fairness.
Autors: Biling Zhang;Yan Chen;Jung-Lang Yu;Bin Chen;Zhu Han;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6571 - 6585
Publisher: IEEE
 
» Inference and Learning in Evidential Discrete Latent Markov Models
Abstract:
We present the Evidential Hidden Markov Models (EvHMM), an extension of probabilistic HMM for time-series modeling, where conditional belief functions are used in place of probabilities to manage uncertainty on discrete latent variables. Inference and learning mechanisms are described and allow to solve the three problems initially defined for HMM, namely, the classification problem (find the most plausible model), the decoding problem (finding the best sequence of hidden states), and the learning problem based on incomplete and uncertain data (estimate the parameters). Exact inference mechanisms based on the GBT are proposed which allows one to recover standard HMM when probabilities are considered. An EM-like procedure is developed for parameter learning, relying on some approximations suggested to make the solutions tractable. Relationships are discussed with both the learning criterion conjectured by Vannoorenberghe and Smets and the formulation of EMCs by Pieczynski et al. A comparison with standard HMM on simulated data confirms the interest of considering random disjunctive sets to represent data incompleteness in evidential temporal graphical models.
Autors: Emmanuel Ramasso;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1102 - 1114
Publisher: IEEE
 
» Influence of MOCVD Growth Pressure on Magnetoresistance of Nanostructured La-Ca-Mn-O Films Used for Magnetic Field Sensors
Abstract:
The results of structure and magnetoresistance (MR) of nanostructured La1–xCaxMnyO3 (LCMO) films, grown at different gas pressure (from 3 to 7 Torr) by pulse injection metal–organic chemical vapor deposition (MOCVD) technique, are presented. The MR was investigated in pulsed magnetic fields up to 60 T in the temperature range 1.5–294 K. The results were analyzed from the perspective of using these films for magnetic field sensors operating at low temperatures. It was demonstrated that with the increase of Ar + O2 gas pressure, the surface morphology of the films becomes rougher and grain size increases. Also, the ratio of Mn/(La + Ca) increases with the increase of the pressure. Large MR of the films was observed in a wide temperature range below the ferromagnetic–paramagnetic phase transition. It was shown that at cryogenic temperatures, the films grown at gas pressure of 3 Torr have higher sensitivity in lower magnetic field range (<10 T), while in high magnetic fields (20–60 T), the properties of films grown at higher gas pressure 5–7 Torr are favored. The obtained results allow evaluating the influence of MOCVD growth pressure on MR and sensitivity to the magnetic field of LCMO manganites used for pulsed magnetic field sensors.
Autors: Nerija Žurauskienė;Dainius Pavilonis;Jonas Klimantavičius;Saulius Balevičius;Voitech Stankevič;Skirmantas Keršulis;Valentina Plaušinaitienė;Adulfas Abrutis;Rasuolė Lukošė;Ma
Appeared in: IEEE Transactions on Plasma Science
Publication date: Oct 2017, volume: 45, issue:10, pages: 2780 - 2786
Publisher: IEEE
 
» Influence of Radar Targets on the Accuracy of FMCW Radar Distance Measurements
Abstract:
Distance measurement tasks in micromachine tools need to be performed with micrometer accuracy. For such tasks, frequency-modulated continuous-wave (FMCW) radars with a combination of frequency and phase evaluations are a good choice. However, the accuracy cannot be indefinitely increased as there are constraints on the target size and placement imposed by the limited space inside micromachines. This paper investigates the influence of target geometry and position on the accuracy of its range estimation using a W-band FMCW radar with a bandwidth of 25 GHz. A relation between target geometry and accuracy is established through the Cramér–Rao lower bound (CRLB). Based on the measurements of different targets, an optimal shape and size is proposed, which provides an average accuracy in the single digit micrometer range. Furthermore, the influence of different bandwidths on the accuracy is investigated. It is also demonstrated how the CRLB can be used to optimize the size of a target, when a certain accuracy is needed. In addition, antenna field regions are analyzed for suitable target placements. Finally, the radar system is implemented in a machine tool and measurements with accuracies in the micrometer range are carried out.
Autors: Steffen Scherr;Rifat Afroz;Serdal Ayhan;Sven Thomas;Timo Jaeschke;Sören Marahrens;Akanksha Bhutani;Mario Pauli;Nils Pohl;Thomas Zwick;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Oct 2017, volume: 65, issue:10, pages: 3640 - 3647
Publisher: IEEE
 
» Influence of Surface Roughness Measurement Scale on Radar Backscattering in Different Agricultural Soils
Abstract:
Soil surface roughness strongly affects the scattering of microwaves on the soil surface and determines the backscattering coefficient ( observed by radar sensors. Previous studies have shown important scale issues that compromise the measurement and parameterization of roughness especially in agricultural soils. The objective of this paper was to determine the roughness scales involved in the backscattering process over agricultural soils. With this aim, a database of 132 5-m profiles taken on agricultural soils with different tillage conditions was used. These measurements were acquired coinciding with a series of ENVISAT/ASAR observations. Roughness profiles were processed considering three different scaling issues: 1) influence of measurement range; 2) influence of low-frequency roughness components; and 3) influence of high-frequency roughness components. For each of these issues, eight different roughness parameters were computed and the following aspects were evaluated: 1) roughness parameters values; 2) correlation with ; and 3) goodness-of-fit of the Oh model. Most parameters had a significant correlation with especially the fractal dimension, the peak frequency, and the initial slope of the autocorrelation function. These parameters had higher correlations than classical parameters such as the standard deviation of surface heights or the correlation length. Very small differences were observed when longer than 1-m profiles were used as well as when small-scale roughness components (<5 cm) or large-scale roughness components (>100 cm) were disregarded. In conclusion, the medium-frequency roughness components (scal- of 5–100 cm) seem to be the most influential scales in the radar backscattering process on agricultural soils.
Autors: Alex Martinez-Agirre;Jesús Álvarez-Mozos;Hans Lievens;Niko E. C. Verhoest;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5925 - 5936
Publisher: IEEE
 
» Influence of the Manufacturing Process of a Claw-Pole Alternator on Its Stator Shape and Acoustic Noise
Abstract:
This paper shows the influence of the manufacturing process of a claw-pole alternator on its acoustic noise. First, the stator welds and the assembly of the stator in the brackets are linked to deformations of the inner diameter of the stator. Then, the influences of these deformations on the magnetic forces and the subsequent acoustic noise are investigated. Results show that the deformations caused by the manufacturing process significantly increase the sound power level of particular orders.
Autors: Antoine Tan-Kim;Nicolas Hagen;Vincent Lanfranchi;Stéphane Clénet;Thierry Coorevits;Jean-Claude Mipo;Jérôme Legranger;Frédéric Palleschi;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4389 - 4395
Publisher: IEEE
 
» Information Entropy and Fuzzy Logic Based Equalizer for PolMux QAM Coherent Optical Communication Systems
Abstract:
In polarization-multiplexed (PolMux) coherent optical communication systems, adaptive blind equalizer is efficient in demultiplexing and mitigating intersymbol interference (ISI). A novel blind algorithm based on Information Entropy and fuzzy logic is proposed, in which the Renyi's entropy is adopted to measure the uncertainty of error between the desired and estimated probability density function (PDF). The nonparametric PDF estimator of Parzen window method is employed to estimate the PDF of symbols. Meantime, a fuzzy-logic tuning unit is designed to adjust the kernel size of Parzen window, which leads to fast convergence rate and small steady mean-square error. By simulation in PolMux-16 quadrature amplitude modulation (QAM) coherent systems, the correctness and effectiveness of the proposed algorithm are verified.
Autors: Zhili Zhou;Yiju Zhan;Qingling Cai;Xiukai Ruan;Guihua Cui;Yuxing Dai;Haiyong Zhu;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 16
Publisher: IEEE
 
» Information Transfer of Control Strategies: Dualities of Stochastic Optimal Control Theory and Feedback Capacity of Information Theory
Abstract:
The control-coding capacity of stochastic control systems is introduced, and its operational meaning is established using randomized control strategies, which simultaneously control output processes encode information, and communicate information from control processes to output processes. The control-coding capacity is the analog Shannon's coding-capacity of noisy channels. Furthermore, duality relations to stochastic optimal control problems with deterministic and randomized control strategies are identified including the following. First, extremum problems of stochastic optimal control with directed information payoff are equivalent to feedback capacity problems of information theory, in which the control system act as a communication channel. Second, for Gaussian linear decision models with average quadratic constraints, it is shown that optimal randomized strategies are Gaussian, and decompose into a deterministic part and a random part. The deterministic part is precisely the optimal strategy of the linear quadratic Gaussian stochastic optimal control problem, whereas the random part is the solution of an water-filling information transmission problem that encodes information, which is estimated by a decoder.
Autors: Charalambos D. Charalambous;Christos K. Kourtellaris;Ioannis Tzortzis;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5010 - 5025
Publisher: IEEE
 
» Information-Assisted Density Peak Index for Hyperspectral Band Selection
Abstract:
Band selection has become an effective method to reduce hyperspectral dimensionality. In this letter, an information-assisted density peak index (IaDPI) is proposed to prioritize the bands. Based on a clustering method by finding density peaks, IaDPI introduces the intraband information entropy into the local density and intercluster distance to ensure cluster centers with a high quality. Also, the band distance is integrated with channel proximity to control the compactness of local density. Owing to the intraband entropy and the interband weighted dissimilarity, the selected band set with top-ranked IaDPI scores can hold high local density, clear global distinction, and good informative quality. Experimental results on real hyperspectral data indicate the advantages of the proposed IaDPI in good selection quality, robust noise immunity, and high classification accuracy.
Autors: Xiaoyan Luo;Rui Xue;Jihao Yin;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Oct 2017, volume: 14, issue:10, pages: 1870 - 1874
Publisher: IEEE
 
» Infrared Absorption at 300 K in InGaN/GaN Disk-in-Nanowire Arrays Grown on (001) Silicon
Abstract:
In0.34Ga0.66N/GaN disk-in-nanowire arrays have been grown on (001) Si substrates by molecular beam epitaxy and their infrared absorption spectra have been measured at room temperature. The average diameter and area density of the nanowires are 60 nm and cm, respectively. The room temperature photoluminescence spectrum is characterized by peak emission at 540 nm. The absorption spectra measured with a Fourier transform infrared spectrometer in transmission and reflection modes exhibit multiple absorption peaks ranging from 1.6 to . The peak energies have been compared with those for intersubband transitions calculated with a simple model and there is agreement in some cases.
Autors: Arnab Hazari;Alexander Soibel;Sarath D. Gunapala;Pallab Bhattacharya;
Appeared in: IEEE Photonics Technology Letters
Publication date: Oct 2017, volume: 29, issue:20, pages: 1751 - 1754
Publisher: IEEE
 
» Infrared Dim and Small Target Detection Based on Stable Multisubspace Learning in Heterogeneous Scene
Abstract:
Infrared (IR) dim and small target detection in a highly complex background play an important role in many applications, and remain a challenging problem. In this paper, a novel method named stable multisubspace learning is presented to deal with this problem. The new method takes into account the inner structure of actual images so that it overcomes the shortage of the traditional method. First, by analyzing the multisubspace structure of heterogeneous background data, a corresponding image model is proposed using subspace learning strategy. This model is also stable to noise interference. Second, an efficient optimization algorithm is designed to solve the proposed IR image model. By adding the proper postprocessing procedure, we can get the detection result. Experiments on simulation scenes and real scenes show that the proposed method has superior detection ability under heterogeneous background.
Autors: Xiaoyang Wang;Zhenming Peng;Dehui Kong;Yanmin He;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5481 - 5493
Publisher: IEEE
 
» Infrared Small Target Detection via Nonnegativity-Constrained Variational Mode Decomposition
Abstract:
Infrared small target detection is one of the key techniques in the infrared search and track system. Frequency differences among target, background, and noise are often important information for target detection. In this letter, a nonnegativity-constrained variational mode decomposition (NVMD) method is proposed. Unlike the traditional frequency-domain methods, the proposed method can adaptively decompose the input signal into several separated band-limited subsignals, with the nonnegativity constraint. First, a bandpass filter is used as a preprocessing step. Second, by exploring the frequency and nonnegativity properties of the small target, the NVMD model is constructed. The potential target subsignal can be obtained by solving the NVMD model. By performing threshold segmentation on the potential target subsignal, we can obtain the detection result of the infrared small target. Experiments on six real infrared image sequences demonstrate that the proposed method has a good performance in target enhancement and background suppression. Additionally, the proposed method shows strong robustness under various backgrounds.
Autors: Xiaoyang Wang;Zhenming Peng;Ping Zhang;Yanmin He;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Oct 2017, volume: 14, issue:10, pages: 1700 - 1704
Publisher: IEEE
 
» Infrastructure-Assisted Message Dissemination for Supporting Heterogeneous Driving Patterns
Abstract:
With the advances of Internet of Things technologies, individual vehicles can now exchange information to improve traffic safety, and some vehicles can further improve safety and efficiency by coordinating their mobility via cooperative driving. To facilitate these applications, many studies have been focused on the design of inter-vehicle message dissemination protocols. However, most existing designs either assume individual driving pattern or consider cooperative driving only. Moreover, few of them fully exploit infrastructures, such as cameras, sensors, and road-side units. In this paper, we address the design of message dissemination that supports heterogeneous driving patterns. Specifically, we first propose an infrastructure-assisted message dissemination framework that can utilize the capability of infrastructures. We then present a novel beacon scheduling algorithm that aims at guaranteeing the timely and reliable delivery of both periodic beacon messages for cooperative driving and event-triggered safety messages for individual driving. To evaluate the performance of the protocol, we develop both theoretical analysis and simulation experiments. Extensive numerical results confirm the effectiveness of the proposed protocol.
Autors: Bingyi Liu;Dongyao Jia;Kejie Lu;Haibo Chen;Rongwei Yang;Jianping Wang;Yvonne Barnard;Libing Wu;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Oct 2017, volume: 18, issue:10, pages: 2865 - 2876
Publisher: IEEE
 
» Initial Phase and Modulation Factor Optimization for Structured Illumination Microscopy
Abstract:
Structured illumination microscopy (SIM) is a widefield super-resolution technique in fluorescent imaging. For an artifact-free reconstruction, some crucial parameters should be known with high accuracy. However, the initial phase and modulation factor of illumination pattern cannot be guaranteed with enough precision experimentally, so they have to be retrieved from the acquired data. We propose a fast and robust method to compute these two parameters and then the coefficients of frequency components can be normalized. We analyze the performance of this method using simulated data and experimental data. The results demonstrate that the coefficients normalization has important effect on the improvement of reconstruction image. Compared with widefield resolution (216 nm), the lateral resolution of SIM can achieve 97 nm.
Autors: Yanwei Zhang;Cong Luo;Hongwei Wang;Song Lang;Yan Gong;Yuguo Tang;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 9
Publisher: IEEE
 
» Injection With Negative Wavelength Detuning for Multispectrum Frequency Generation and Hopping Using SMFP-LD
Abstract:
We propose and demonstrate a novel method to generate multispectrum frequency and hopping from one frequency spectrum to another using a single external cavity based Fabry–Pérot laser diode (FP-LD) subjected to a single optical injection with negative wavelength detuning. The external cavity based FP-LD has a single dominant mode, single-mode FP-LD (SMFP-LD), and hence the beating of the dominant mode and the injected beam, and the beating of the injected beam and the corresponding side mode of SMFP-LD are possible with a single optical injection. The generated frequency can be tuned to a wide range of GHz to several THz. Individual or simultaneous RF signals generation and hopping between microwave and millimeter wave spectrum are reported. The effect of the injected beam power on generating and hopping of RF frequency is analyzed in the case of negative wavelength detuning with the input beam injected on different modes of SMFP-LD. Also, the stability of beating wavelengths, power variations of beating wavelengths for an interval of 1 hour, and linewidth of RF signals are observed.
Autors: Bikash Nakarmi;Hao Chen;Muyong Lee;Yong Hyub Won;Shilong Pan;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 11
Publisher: IEEE
 
» Innovative Antenna Front Ends from L-Band to Ka-Band [Antenna Applications Corner]
Abstract:
We provide an overview of several high-tech antenna apertures and antenna front ends, developed and realized by IMST (in some cases in cooperation with partners) over a time span of more than 15 years. These front ends have become key components for bandwidth-hungry applications such as mobile/nomadic satellite communication terminals (satcom-onthe-move) and radar systems. Satcom terminal data throughput for multimedia services provided via satellite links is increasing rapidly. Such terminals require highly complex radio-frequency (RF) systems capable of tracking satellites despite movements of the mobile terminal platform. Depending on the type of platform (land mobile, maritime, or aeronautical), the requirements for these front ends and the resulting complexity can vary. This also applies to radar sensors for automotive applications and unmanned aerial vehicle (UAV) platforms, for example. In all of these front ends, the antenna architecture is always based on a phased/steerable array topology. Such systems are, in general, complex configurations: they require not only RF circuitry but also complex baseband processing and highly accurate sensor platforms to perform adequate beam steering and tracking. The overall design must be cost-effective, a very demanding requirement. Through the years, IMST has developed a customized set of highly specialized skills to address all of these challenges.
Autors: Rens Baggen;Sybille Holzwarth;Martin Bottcher;Simon Otto;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Oct 2017, volume: 59, issue:5, pages: 116 - 129
Publisher: IEEE
 
» Innovative Contactless Energy Transfer Accessory for Rotary Ultrasonic Machining and Its Circuit Compensation Based on Coil Turns
Abstract:
An innovative concentric rotary ultrasonic machining (RUM) device based on local induction is proposed. The device is used as a machine tool accessory that can add the RUM to any machining center. Rather than using a complete ring, a portion of a ring is used as the primary core in the proposed rotary transformer, which eliminates spindle speed limits. The simplified configuration provides increased safety and is convenient for material processing applications. Additionally, a circuit compensation method based on coil turns is proposed. It takes the whole circuit, reliability of electronic components, transmission efficiency, and output power into consideration. We use this method to choose the optimal number of coil turns and compensation elements required to achieve increased and safe power transmission performance. This paper also demonstrates the performance of the device through experimentation. Finally, practicability is discussed.
Autors: Yujia Luan;Bin Lin;Xingru Ma;Xueming Zhu;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 7810 - 7818
Publisher: IEEE
 
» Input–Output Based Fault Estimation for T-S Fuzzy Systems With Local Nonlinear Parts
Abstract:
This paper is concerned with the problem of fault estimation for a class of Takagi–Sugeno fuzzy systems with local nonlinear parts and actuator faults. The system matrices in consideration contain unknown components, whereas in most of the literature, the system matrices are required to be known completely. An input–output based fault-estimation approach for the fuzzy system is proposed, by which, the estimation error for time-varying faults can asymptotically converge to zero in the absence of disturbances. The estimation convergence is proved theoretically. Based on the information of fault estimation, the design of fault-tolerant controller can be updated online to compensate the fault effect on systems so as to maintain the original performance of the system. Numerical examples are given to show the effectiveness and merits of the proposed method.
Autors: Sheng-Juan Huang;Guang-Hong Yang;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1320 - 1328
Publisher: IEEE
 
» InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique
Abstract:
Repeat pass interferometric synthetic aperture radar (InSAR) observations may be significantly impacted by the propagation delay of the microwave signal through the ionosphere, which is commonly referred to as ionospheric delay. The dispersive character of the ionosphere at microwave frequencies allows one to estimate the ionospheric delay from InSAR data through a split range-spectrum technique. Here, we extend the existing split range-spectrum technique to InSAR time-series. We present an algorithm for estimating a time-series of ionospheric phase delay that is useful for correcting InSAR time-series of ground surface displacement or for evaluating the spatial and temporal variations of the ionosphere’s total electron content (TEC). Experimental results from stacks of L-band SAR data acquired by the ALOS-1 Japanese satellite show significant ionospheric phase delay equivalent to 2 m of the temporal variation of InSAR time-series along 445 km in Chile, a region at low latitudes where large TEC variations are common. The observed delay is significantly smaller, with a maximum of 10 cm over 160 km, in California. The estimation and correction of ionospheric delay reduces the temporal variation of the InSAR time-series to centimeter levels in Chile. The ionospheric delay correction of the InSAR time-series reveals earthquake-induced ground displacement, which otherwise could not be detected. A comparison with independent GPS time-series demonstrates an order of magnitude reduction in the root mean square difference between GPS and InSAR after correcting for ionospheric delay. The results show that the presented algorithm significantly improves the accuracy of InSAR time-series and should become a routine component of InSAR time-series analysis.
Autors: Heresh Fattahi;Mark Simons;Piyush Agram;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5984 - 5996
Publisher: IEEE
 
» Insider Privileges
Abstract:
How does standard textbook economics analyze insider status in technology markets? It takes one of two perspectives. The first perspective stresses the cold logic of market competition, and the second stresses the ambiguities of the government’s influence. This essay summarizes the implications of each perspective and the troubling questions raised.
Autors: Shane Greenstein;
Appeared in: IEEE Micro
Publication date: Oct 2017, volume: 37, issue:5, pages: 70 - 72
Publisher: IEEE
 
» Integrated Design of Fault-Tolerant Control for Nonlinear Systems Based on Fault Estimation and T–S Fuzzy Modeling
Abstract:
This paper proposes an integrated design of fault-tolerant control (FTC) for nonlinear systems using Takagi–Sugeno (T–S) fuzzy models in the presence of modeling uncertainty along with actuator/sensor faults and external disturbance. An augmented state unknown input observer is proposed to estimate the faults and system states simultaneously, and using the estimates, an FTC controller is developed to ensure robust stability of the closed-loop system. The main challenge arises from the bidirectional robustness interactions, since the fault estimation (FE) and FTC functions have an uncertain effect on each other. The proposed strategy uses a single-step linear matrix inequality formulation to integrate together the designs of FE and FTC functions to satisfy the required robustness. The integrated strategy is demonstrated to be effective through a tutorial example of an inverted pendulum system (based on robust T–S fuzzy designs).
Autors: Jianglin Lan;Ron J. Patton;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1141 - 1154
Publisher: IEEE
 
» Integrated SOI High-Order Phase-Shifted Bragg Grating for Microwave Photonics Signal Processing
Abstract:
An integrated high-order phase-shifted Bragg grating, comprising six quarter-wave sections between Bragg grating mirrors in a laterally-corrugated strip waveguide has been realized in silicon-on-insulator technology. A box-like transmission window is created within the 10-nm-wide grating reflection band, realizing a sharp bandpass optical filter with out-of-band rejection exceeding 40 dB and a steep roll-off of ∼300 dB/nm in the transition band. The sharp optical filter has been experimentally tested in microwave photonics (MWP) signal processing applications, namely spectral separation of an optical sideband comprising 1.25 Gb/s data from a 15-GHz-spaced carrier, and sideband suppression for dispersion compensation in a radio-over-fiber link. The results of the characterizations indicate negligible power penalty in terms of bit-error rate for the sideband separation and robust mitigation of dispersion-induced transmission impairment. The device has an ultrasmall footprint of ∼450 × 0.5 μm2, and can be monolithically integrated with germanium photodiodes or silicon modulators as well as other passive subsystems to implement advanced on-chip MWP signal processing functionalities.
Autors: Claudio Porzi;Giovanni Serafino;Philippe Velha;Paolo Ghelfi;Antonella Bogoni;
Appeared in: Journal of Lightwave Technology
Publication date: Oct 2017, volume: 35, issue:20, pages: 4479 - 4487
Publisher: IEEE
 
» Integrating Multilayer Features of Convolutional Neural Networks for Remote Sensing Scene Classification
Abstract:
Scene classification from remote sensing images provides new possibilities for potential application of high spatial resolution imagery. How to efficiently implement scene recognition from high spatial resolution imagery remains a significant challenge in the remote sensing domain. Recently, convolutional neural networks (CNN) have attracted tremendous attention because of their excellent performance in different fields. However, most works focus on fully training a new deep CNN model for the target problems without considering the limited data and time-consuming issues. To alleviate the aforementioned drawbacks, some works have attempted to use the pretrained CNN models as feature extractors to build a feature representation of scene images for classification and achieved successful applications including remote sensing scene classification. However, existing works pay little attention to exploring the benefits of multilayer features for improving the scene classification in different aspects. As a matter of fact, the information hidden in different layers has great potential for improving feature discrimination capacity. Therefore, this paper presents a fusion strategy for integrating multilayer features of a pretrained CNN model for scene classification. Specifically, the pretrained CNN model is used as a feature extractor to extract deep features of different convolutional and fully connected layers; then, a multiscale improved Fisher kernel coding method is proposed to build a mid-level feature representation of convolutional deep features. Finally, the mid-level features extracted from convolutional layers and the features of fully connected layers are fused by a principal component analysis/spectral regression kernel discriminant analysis method for classification. For validation and comparison purposes, the proposed approach is evaluated via experiments with two challenging high-resolution remote sensing data sets, and shows the competitive perf- rmance compared with fully trained CNN models, fine-tuning CNN models, and other related works.
Autors: Erzhu Li;Junshi Xia;Peijun Du;Cong Lin;Alim Samat;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5653 - 5665
Publisher: IEEE
 
» Intelligent Early Warning of Power System Dynamic Insecurity Risk: Toward Optimal Accuracy-Earliness Tradeoff
Abstract:
Dynamic insecurity risk of a power system has been increasingly concerned due to the integration of stochastic renewable power sources (such as wind and solar power) and complicated demand response. In this paper, an intelligent early-warning system to achieve reliable online detection of risky operating conditions is proposed. The proposed intelligent system (IS) consists of an ensemble learning model based on extreme learning machine (ELM) and a decision-making process under a multiobjective programming framework. Taking an ensemble form, the randomness existing in individual ELM training is generalized and reliable classification results can be obtained. The decision making is designed for ELM ensemble whose parameters are optimized to search for the optimal tradeoff between the warning accuracy and the warning earliness of the proposed IS. The compromise solution turns out to significantly speed up the overall computation with an acceptable sacrifice in the accuracy (e.g., from 100% to 99.9%). More importantly, the proposed IS can provide multiple and switchable performances to the operators in order to satisfy different local dynamic security assessment requirements.
Autors: Yuchen Zhang;Yan Xu;Zhao Yang Dong;Zhao Xu;Kit Po Wong;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2544 - 2554
Publisher: IEEE
 
» Interactive Design of MEMS Varactors With High Accuracy and Application in an Ultralow Noise MEMS-Based RF VCO
Abstract:
The monolithic integration of microelectromechanical systems (MEMS) varactors into the backend of line metal stack of a state of the art semiconductor process is an attractive alternative to the field effect transistor or bipolar transistor varactors for continuous frequency tuning of ultralow phase noise voltage-controlled oscillators (VCOs). An efficient design of MEMS varactors according to application-specific demands requires a deep insight into the electromechanical and electromagnetic (EM) device properties and an accurate prediction of the varactor phase noise contribution to the overall phase noise of the MEMS-based VCO. Generally, MEMS varactors are designed using a combination of finite-element method and EM softwares. Due to the large computational and time effort, the required deep insight into the MEMS device is hard to achieve. This paper presents interactive design methodologies to predict the electromechanical, EM, and the phase noise properties of a MEMS varactor with high accuracy. These methodologies are verified by fabricated MEMS varactors and an experimental MEMS-based VCO with continuous frequency tuning.
Autors: Gerhard Kahmen;Hermann Schumacher;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Oct 2017, volume: 65, issue:10, pages: 3578 - 3584
Publisher: IEEE
 
» Interactive Screen Video Streaming-Based Pervasive Mobile Workstyle
Abstract:
In this paper, we develop an interactive screen video streaming-based system to enable the ubiquitous mobile workstyle, which is referred to as personal computer to pervasive computing (PC2PC). The desktop screens of virtualized systems are compressed in the PC2PC servers and delivered to remote end users for stream decoding, rendering, and interactions. We have implemented a system from the scratch, where the emerging screen content coding extension of high-efficiency video coding is implemented to compress and stream the desktop screens of the virtualized system in real time. Three core asset channels, system, display, and inputs, are defined to enable systematic end-to-end communication. Compared with Red Hat SPICE virtual desktop infrastructure scheme, the proposed PC2PC could save network bandwidth consumption by a factor of 2, 7, and 4, respectively, in terms of typical video streaming, web browsing, and stationary office applications at the same visual quality. Meanwhile, we have also measured the delays of the system and presented preliminary results on the user experience aspect. A simple network estimation is applied to optimize the quality bandwidth adaptation for both single user and multiuser scenarios to consider the network dynamics.
Autors: Zhan Ma;Tao Yue;Xun Cao;Yiling Xu;Xin Li;Yongjin Wang;
Appeared in: IEEE Transactions on Multimedia
Publication date: Oct 2017, volume: 19, issue:10, pages: 2322 - 2332
Publisher: IEEE
 
» Interference Analysis in Wireless Power Transfer
Abstract:
This letter studies the effect of co-channel interference (CCI) generated by wireless power transfer on information delivery for three widely used setups, i.e., power beacon (PB), hybrid access point (HAP), and simultaneous wireless information and power transfer (SWIPT). It focuses on the comparison of CCI from these three schemes in terms of the average interference power, the ergodic capacity, and the bit error rate. Numerical results show that the extra interference caused by wireless power transfer indeed degrades the system performance. Moreover, SWIPT has the largest degradation, while PB and HAP have the same degradation when proper parameters are chosen.
Autors: Yunfei Chen;Daniel B. da Costa;Haiyang Ding;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2318 - 2321
Publisher: IEEE
 
» Interference Coordination via Power Domain Channel Estimation
Abstract:
A novel technique is proposed, which enables each transmitter to acquire global channel state information (CSI) from the sole knowledge of individual received signal power measurements, which makes dedicated feedback or inter-transmitter signaling channels unnecessary. To make this possible, we resort to a completely new technique whose key idea is to exploit the transmit power levels as symbols to embed information and the observed interference as a communication channel the transmitters can use to exchange coordination information. Although the used technique allows any kind of low-rate information to be exchanged among the transmitters, the focus here is to exchange local CSI. The proposed procedure also comprises a phase which allows local CSI to be estimated. Once an estimate of global CSI is acquired by the transmitters, it can be used to optimize any utility function which depends on it. While algorithms, which use the same type of measurements, such as the iterative water-filling algorithm, implement the sequential best-response dynamics (BRD) applied to individual utilities, here, thanks to the availability of global CSI, the BRD can be applied to the sum-utility. Extensive numerical results show that significant gains can be obtained and, this, by requiring no additional online signaling.
Autors: Chao Zhang;Vineeth S. Varma;Samson Lasaulce;Raphaël Visoz;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6779 - 6794
Publisher: IEEE
 
» Interference Minimization in Cooperative Relay Beamforming With Multiple Communicating Pairs
Abstract:
We consider a cellular network where each cell contains multiple source–destination pairs communicating through multiple amplify-and-forward relays using orthogonal channels. We propose an optimal relay beamforming design that minimizes the maximum interference at the neighboring cells subject to per-relay power limits and minimum received signal-to-noise ratio (SNR) requirements. Even though the problem is non-convex, we show that it has zero Lagrange duality gap, and we convert its dual problem to a semi-definite programming problem. Depending on the values of the optimal dual variables, we study three cases to obtain the optimal beam vectors accordingly. This results in an iterative algorithm that provides a semi-closed-form optimal solution. We extend our algorithm to the problem of maximizing the minimum SNR subject to some pre-determined maximum interference constraints at neighboring cells, by the solution to the min-max interference problem along with a bisection search. The solution to this max-min SNR problem gives insight into the worst-case signal-to-interference-and-noise ratio given some maximum interference target. The performance of the proposed algorithm is studied numerically, both for when the knowledge of interference channel is perfect and for when it is imperfect due to either limited feedback or channel estimation error.
Autors: Ali Ramezani-Kebrya;Ben Liang;Min Dong;Gary Boudreau;Ronald Casselman;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6514 - 6527
Publisher: IEEE
 
» Interplay Between Spreading and Random Walk Processes in Multiplex Networks
Abstract:
Real networks in our surrounding are usually complex and composite by nature and they consist of many interwoven layers. The commutation of agents (nodes) across layers in these composite multiplex networks heavily influences the underlying dynamical processes, such as information, idea and disease spreading, synchronization, consensus, etc. In order to understand how the agents’ dynamics and the compositeness of multiplex networks influence the spreading dynamics, we develop a susceptible-infected-susceptible-based model on the top of these networks, which is integrated with the transition of agents across layers. Moreover, we analytically obtain a critical infection rate for which an epidemic dies out in a multiplex network, and latter show that this rate can be higher compared with the isolated networks. Finally, using numerical simulations we confirm the epidemic threshold and we show some interesting insights into the epidemic onset and the spreading dynamics in several real and generic multiplex networks.
Autors: Igor Mishkovski;Miroslav Mirchev;Sanja Šćepanović;Ljupco Kocarev;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Oct 2017, volume: 64, issue:10, pages: 2761 - 2771
Publisher: IEEE
 
» Intravascular Ultrasound Imaging With Virtual Source Synthetic Aperture Focusing and Coherence Factor Weighting
Abstract:
Intravascular ultrasound (IVUS) has been frequently used for coronary artery imaging clinically. More importantly, IVUS is the fundamental image modality for most advanced multimodality intravascular imaging techniques, since it provides a more comprehensive picture of vessel anatomy on which other imaging data can be superimposed. However, image quality in the deeper region is poor because of the downgraded lateral resolution and contrast-to-noise ratio (CNR). In this paper, we report on the application of an ultrasound beamforming method that combines virtual source synthetic aperture (VSSA) focusing and coherence factor weighting (CFW) to improve the IVUS image quality. The natural focal point of conventional IVUS transducer was treated as a virtual source that emits spherical waves within a certain region. Mono-static synthetic aperture focusing was conducted to achieve higher resolution. Coherence factor was calculated using delayed RF signals and applied to the synthesized beam to increase the CNR and focusing quality. The proposed method was tested through simulations in Field II and imaging experiments in both linear and rotational scans. The lateral resolution for linear scan mode is improved from 165–524 to 126–143 ; resolution for rotational scan mode improves by up to 42%. CNR improvement by up to 1.5 was observed on the anechoic cysts of different sizes and at different locations. Herein, it is demonstrated that the beamforming method, which combines VSSA and CFW, can significantly improve the IVUS image quality. This approach can be readily integrated into the current IVUS imaging system for enhanced clinical diagnosis.
Autors: Mingyue Yu;Yang Li;Teng Ma;K. Kirk Shung;Qifa Zhou;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Oct 2017, volume: 36, issue:10, pages: 2171 - 2178
Publisher: IEEE
 
» Introducing Our Sister Publication: IEEE Solid-State Circuits Letters
Abstract:
We are proud to introduce the IEEE Solid-State Circuits Letters (IEEE SSC-L), a new, fast-turnaround publication in the area of integrated circuits. Complementary to the Journal of Solid-State Circuits (JSSC), our new Letters publication invites authors to submit short papers describing novel integrated circuit ideas and experimental results that demonstrate high performance. Solid-State Circuits Society (SSCS) members will receive a subscription free of charge as part of their membership.
Autors: John R. Long;Jan Craninckx;Behzad Razavi;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Oct 2017, volume: 52, issue:10, pages: 2519 - 2520
Publisher: IEEE
 
» Introduction to the Special Section on the 2016 Asian Solid-State Circuits Conference (A-SSCC 2016)
Abstract:
This Special Section of the IEEE Journal of Solid-State Circuits includes some of the highlights of the excellent papers from the 2016 Asian Solid-State Circuits Conference (A-SSCC 2016) held in Toyama, Japan, from November 7 to 9, 2016.
Autors: Deog-Kyoon Jeong;Jaeha Kim;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Oct 2017, volume: 52, issue:10, pages: 2521 - 2522
Publisher: IEEE
 
» Introduction to the Special Section on the ACM/Eurographics Symposium on Computer Animation 2016
Abstract:
Autors: Miguel Otaduy;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Oct 2017, volume: 23, issue:10, pages: 2207 - 2207
Publisher: IEEE
 
» Investigating Applications in Health Care [Book\Software Reviews]
Abstract:
This book explains the multiple directions in which RF/microwave technologies are heading toward healthcare and biosensing applications, the achievements that have been made so far, and the challenges for researchers to solve in the near future. It consists of seven chapters by 15 authors, many of whom are active on the IEEE Microwave Theory and Techniques Society (MTT-S) Technical Coordinating Committee MTT-10, Biological Effects and Medical Applications. Apart from the first two chapters (which are tutorials on microwave technology and the dielectric properties of tissue), the book consists of five chapters that review different applications of RF/microwave energy to health care and biosensing. This book provides essential theories and solutions for the transmitter and receiver hardware block. The solutions offered are very practical for a circuit system designer. Whether the particular applications of RF/microwaves discussed in this volume will ever pass muster and enter the realm of evidence-based medicine remains to be seen. In their focus on the nuts and bolts of engineering, the authors of this otherwise meritorious volume are telling only a small part of the story about developing medical technology.
Autors: Kenneth R. Foster;
Appeared in: IEEE Microwave Magazine
Publication date: Oct 2017, volume: 18, issue:6, pages: 126 - 127
Publisher: IEEE
 
» Investigation of a Fault-Tolerant Three-Level T-Type Inverter System
Abstract:
In recent years, a three-level T-type inverter has attracted considerable attention due to its advantages, such as simple structure and higher efficiency. However, the reliability of a three-level T-type inverter is particularly important as increased power switches are used. Therefore, a fault-tolerant three-level T-type inverter is proposed in this paper. Fault diagnosis and fault-tolerant control strategies for power switches both in half-bridge and neutral-point bridge are investigated. Under fault-tolerant operation, redundant fourth-leg is used to balance neutral-point voltage and the low-frequency voltage oscillation is eliminated completely. The fault ride-through capability and high-quality output waveforms can be obtained. The effectiveness of the proposed inverter topology and control methods is validated by the simulation and experimental results.
Autors: Shuai Xu;Jianzhong Zhang;Jun Hang;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Oct 2017, volume: 53, issue:5, pages: 4613 - 4623
Publisher: IEEE
 
» Investigation of Border Trap Characteristics in the AlON/GeO2/Ge Gate Stacks
Abstract:
Aluminum oxynitride (AlON) is investigated as a germanium oxide (GeO) desorption barrier layer for Ge MOSFETs. Interface and border traps in the AlON/GeO2/Ge gate-stack are discussed in detail and compared with those in the Al2O3/GeO2/Ge gate-stack via MOS and MOSFET structures. Although the interface traps remain the same for AlON and Al2O3 in the gate stacks, the AlON gate-stack exhibits a reduced border trap, which results in improved reliability over the Al2O3 gate-stack. This is supported by both the charge-trapping and low-frequency noise analyses.
Autors: Yujin Seo;Choong-Ki Kim;Tae-In Lee;Wan Sik Hwang;Hyun-Yong Yu;Yang-Kyu Choi;Byung Jin Cho;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 3998 - 4001
Publisher: IEEE
 
» Investigation of Double-Snapback Characteristic in Resistor-Triggered SCRs Stacking Structure
Abstract:
Achieving high latch-up immunity is critical for power-rail electrostatic discharge (ESD) clamp circuits in high-voltage (HV) integrated circuit products. To investigate how shunt resistance affects the transmission line pulsing current–voltage characteristics of resistance-triggered stacked silicon controlled rectifiers (SCRs), a lateral SCR (LSCR) and a modified LSCR were combined in several SCR stacked structures with various shunt resistances. Compared with in tradition stacked ESD cells, the snapback margin of the SCRs does not expand and can even be reduced. A high holding voltage of 33.4 V is achieved using the resistance-triggered stacked SCR technique in a 32-V HV process. A trigger voltage of approximately 51 V and a failure current of 3.3 A is achieved in this experiment. According to theorem analysis based on a voltage decoupling equation, the minimum trigger voltage can probably be further reduced to 46 V by using the resistance-triggered stacked SCR technique. This paper can offer a simple guideline for designing ESD protection circuit using the resistor-triggered SCRs stacking structure.
Autors: Shiang-Shiou Yen;Chun-Hu Cheng;Chia-Chi Fan;Yu-Chien Chiu;Hsiao-Hsuan Hsu;Yu-Pin Lan;Chun-Yen Chang;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4200 - 4205
Publisher: IEEE
 
» Investigation of Histology Region in Dielectric Measurements of Heterogeneous Tissues
Abstract:
The dielectric properties of tissues are the key parameters in electromagnetic medical technologies. Despite the apparent simplicity of the dielectric measurement process, reported data have been inconsistent for heterogeneous tissues. Dielectric properties may be attributed to heterogeneous tissues by identifying the tissue types that contributed to the measurement through histological analysis. However, accurate interpretation of the measurements with histological analysis requires first defining an appropriate histology region to examine. Here, we investigate multiple definitions for the probe sensing depth and uniquely calculate this parameter for measurements with a realistic range of tissues. We demonstrate that different sensing depth definitions are not equivalent, and may introduce error in dielectric data. Last, we propose an improved definition, given by the depth to which the probe can detect changes in the tissue sample, within the measurement uncertainty. We equate this sensing depth with histology depth, thus supporting the need of having the tissue region that contributes to the dielectric data be the same as that which is analyzed histologically. This paper demonstrates that, for these tissues, the histology depth is both frequency and tissue dependent. Therefore, the histology depth should be selected based on the measurement scenario; otherwise, inaccuracies in the data may result.
Autors: Emily Porter;Martin O’Halloran;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Oct 2017, volume: 65, issue:10, pages: 5541 - 5552
Publisher: IEEE
 
» Investigation of Instabilities in a Folded-Waveguide Sheet-Beam TWT
Abstract:
Particle-in-cell (PIC) simulation was used for analyzing the instabilities due to zero-drive oscillations in a 220-GHz folded-waveguide (FW) traveling-wave tube. The equivalent circuit analysis based on the transmission line approach was used for the parametric design of the FW structures (FWSs) with circular and rectangular (horizontal and vertical) beam holes. Experimental validations with reference to the dispersion and interaction impedance characteristics were carried out on a scaled model of the slow wave structure in the Ku band. The oscillations observed in various configurations of the FWS were subsequently analyzed using the Brillouin diagram. The FWS with horizontal-rectangular beam hole was found to have a better immunity to instability compared to the other two configurations.
Autors: H. S. Sudhamani;Jyothi Balakrishnan;S. U. M. Reddy;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4266 - 4271
Publisher: IEEE
 
» Investigation of Monolithic Radial Transmission Lines for Z-Pinch
Abstract:
A mathematical expression of the output voltage from a nonuniform transmission line with an arbitrary input pulse was deduced. The first arriving wave, peak power efficiency, and droop of the output voltage were further clarified using analytical method. The transmission characteristics of monolithic radial transmission lines (MRTLs) with different impedance profiles were investigated by 3-D electromagnetic (EM) simulation and it was found that the hyperbolic impedance profile is the best choice for future Z-pinch drivers. The results obtained from 3-D EM simulation are in good agreement with those obtained from the experiments on a scaled-down MRTL.
Autors: Chongyang Mao;Xinxin Wang;Xiaobing Zou;Jane Lehr;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Oct 2017, volume: 45, issue:10, pages: 2639 - 2647
Publisher: IEEE
 
» Investigation of Robustness Capability of −730 V P-Channel Vertical SiC Power MOSFET for Complementary Inverter Applications
Abstract:
In this paper, a p-channel vertical 4H-silicon carbide (SiC) MOSFET (SiC p-MOSFET) has been fabricated successfully for the first time as a potential candidate for the complementary inverter application. The static characteristics and the robustness, including short circuit and avalanche capabilities of the p-MOSFET, are experimentally tested. Moreover, the comparison between the p-MOSFET and similar rating n-MOSFET is carried out. The short-circuit capability is 15% higher than that of the n-channel MOSFET. Furthermore, this paper also provides the physical insights into the failure mechanism during the short-circuit transient of the p- and n-MOSFET. Meanwhile, an electro-thermal analytical model is proposed to explain the thermal distribution during this transient. Last, the avalanche withstand time of the fabricated SiC p-MOSFET is experimentally demonstrated to be 27% higher than that of the n-channel one. It is concluded that the SiC p-MOSFET could be a competitive power switch applicable for high-frequency complementary inverters.
Autors: Junjie An;Masaki Namai;Hiroshi Yano;Noriyuki Iwamuro;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4219 - 4225
Publisher: IEEE
 
» Investigation on the Conduction Mechanisms in Metal-Base Vertical Organic Transistors by DC and LF-Noise Measurements
Abstract:
Vertical organic transistors are a promising candidate to overcome the scaling limits of conventional horizontal organic field-effect devices. In this paper, based on the results of direct current (dc) and low-frequency noise (LFN) measurements, we propose a picture for the carrier transport in metal-base organic transistors in which transmission across the base is due to the combined action of both hot-carriers (HCs) and high-conduction paths (pores) in the metal base. Investigated devices employ pentacene and copper phthalocyanine as active layers for the emitter and collector regions, and a bilayer consisting of Au/MoO3 as injecting electrode. The dc analysis highlights that the charge transport in the investigated devices is due to drift diffusion of the emitter-injected carriers in the highest occupied molecular orbital (HOMO) band and is dominated by HC injection, although conduction via pores increases and becomes not negligible at high base–emitter fields. The LFN analysis highlights the presence of two dominant and uncorrelated 1/f current noise sources, one located between base and emitter, due to the fluctuations of the not-transmitted HC current, and a second source located between collector and emitter, due to the fluctuations of the transmitted HC current and/or to the fluctuations of the current through the pores in the metallic base.
Autors: G. Giusi;E. Sarnelli;M. Barra;A. Cassinese;G. Scandurra;K. Nakayama;C. Ciofi;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4260 - 4265
Publisher: IEEE
 
» Investigations on Periodic Sequences With Maximum Nonlinear Complexity
Abstract:
The nonlinear complexity of a periodic sequence s is the length of the shortest feedback shift register that can generate s, and its value is upper bounded by the least period of s minus 1. In this paper, a recursive approach that generates all periodic sequences with maximum nonlinear complexity is presented, and the total number of such sequences is determined. The randomness properties of these sequences are also examined.
Autors: Zhimin Sun;Xiangyong Zeng;Chunlei Li;Tor Helleseth;
Appeared in: IEEE Transactions on Information Theory
Publication date: Oct 2017, volume: 63, issue:10, pages: 6188 - 6198
Publisher: IEEE
 
» Ion Beam Monitoring Over a Biased Target
Abstract:
A specially designed beam profile monitor (BPM) was produced to be assembled over a biased target plate, with the aim of studying the effect of an ion beam deceleration system on the beam fluence due to beam dispersion. The new BPM was developed with a shape as flat as possible, so it could be attached to a biased target plate without affecting the target geometry, using a slit scan method to produce an high-resolution beam profile. This system was designed and installed on the high current ion implanter at the Laboratório de Aceleradores e Tecnologias de Radiação, at the Campus Tecnológico e Nuclear, of Instituto Superior Técnico, in Lisbon. The system is capable of showing the ion beam profile for low-energy ion beams below 15 keV, using a beam deceleration system.
Autors: J. Lopes;J. Rocha;N. Catarino;M. Peres;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Oct 2017, volume: 45, issue:10, pages: 2767 - 2772
Publisher: IEEE
 
» IoT-Based Techniques for Online M2M-Interactive Itemized Data Registration and Offline Information Traceability in a Digital Manufacturing System
Abstract:
The integration of internet-of-things (IoT) technologies in the industry benefits digital manufacturing applications by allowing ubiquitous interaction and collaborative automation between machines. Online data collection and data interaction are critical for real-time decision making and machine collaborations. However, due to the specificity of digital manufacturing applications, the technical gap between IoT techniques and practical machine operation could hinder the efficient data interactions, collaborations between machines, and the effectiveness as well as the accuracy of itemized data collection. This investigation, therefore, identifies some major technical problems and challenges that current IoT-based digital manufacturing is facing, and proposes a method to bridge the technical gap for itemized product management. The highlights of this investigation are: 1) a data-oriented system architecture toward flexible data interaction between machines, 2) a customized machine-to-machine protocol for machine discovery, presence, and messaging, (3) flexible data structure and data presentation for interoperability, and (4) versatile information tracing approaches for product management. The proposed solutions have been implemented in PicknPack digital food manufacturing line, and achieved ubiquitous data interaction, online data collection, and versatile product information tracing methods have shown the feasibility and significance of the presented methods.
Autors: Zhipeng Wu;Zhaozong Meng;John Gray;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Oct 2017, volume: 13, issue:5, pages: 2397 - 2405
Publisher: IEEE
 
» IPED2: Inheritance Path Based Pedigree Reconstruction Algorithm for Complicated Pedigrees
Abstract:
Reconstruction of family trees, or pedigree reconstruction, for a group of individuals is a fundamental problem in genetics. The problem is known to be NP-hard even for datasets known to only contain siblings. Some recent methods have been developed to accurately and efficiently reconstruct pedigrees. These methods, however, still consider relatively simple pedigrees, for example, they are not able to handle half-sibling situations where a pair of individuals only share one parent. In this work, we propose an efficient method, IPED2, based on our previous work, which specifically targets reconstruction of complicated pedigrees that include half-siblings. We note that the presence of half-siblings makes the reconstruction problem significantly more challenging which is why previous methods exclude the possibility of half-siblings. We proposed a novel model as well as an efficient graph algorithm and experiments show that our algorithm achieves relatively accurate reconstruction. To our knowledge, this is the first method that is able to handle pedigree reconstruction from genotype data when half-sibling exists in any generation of the pedigree.
Autors: Dan He;Zhanyong Wang;Laxmi Parida;Eleazar Eskin;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Oct 2017, volume: 14, issue:5, pages: 1094 - 1103
Publisher: IEEE
 
» IsAProteinDB: An Indexed Database of Trypsinized Proteins for Fast Peptide Mass Fingerprinting
Abstract:
In peptite mass fingerprinting, an unknown protein is fragmented into smaller peptides whose masses are accurately measured; the obtained list of weights is then compared with a reference database to obtain a set of matching proteins. The exponential growth of known proteins discourage the use of brute force methods, where the weights’ list is compared with each protein in the reference collection; luckily, the scientific literature in the database field highlights that well designed searching algorithms, coupled with a proper data organization, allow to quickly solve the identification problem even on standard desktop computers. In this paper, IsAProteinsDB, an indexed database of trypsinized proteins, is presented. The corresponding search algorithm shows a time complexity that does not significantly depends on the size of the reference protein database.
Autors: Antonio d’Acierno;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Oct 2017, volume: 14, issue:5, pages: 1195 - 1201
Publisher: IEEE
 
» Isotherm Tracking by an Autonomous Underwater Vehicle in Drift Mode
Abstract:
Studies of marine physical, chemical, and microbiological processes benefit from observing in a Lagrangian frame of reference. Some of these processes are related to specific density or temperature ranges. We have developed a method for a Tethys-class long-range autonomous underwater vehicle (LRAUV) (which has a propeller and a buoyancy engine) to track a targeted isothermal layer (within a narrow temperature range) in a stratified water column when operating in buoyancy-controlled drift mode. In this mode, the vehicle shuts off its propeller and autonomously detects the isotherm and stays with it by actively controlling the vehicle's buoyancy. The LRAUV starts on an initial descent to search for the target temperature. Once the temperature falls in the target center bracket, the vehicle records the corresponding depth and adjusts buoyancy to hold that depth. As long as the temperature stays within a tolerance range, the vehicle continues to hold that depth. If the temperature falls out of the tolerance range, the vehicle will increase or decrease buoyancy to reacquire the target temperature and track it. In a June 2015 experiment in Monterey Bay, CA, USA, an LRAUV ran the presented algorithm to successfully track a target isotherm for 13 h. Over the isotherm tracking duration, the LRAUV mostly remained in the 0.5 C (peak-to-peak) tolerance range as designed, even though the water column's stratification kept changing. This work paves the way to coupling an LRAUV's complimentary modes of flight and drift—searching for an oceanographic feature in flight mode, and then switching to drift mode to track the feature in a Lagrangian frame of reference.
Autors: Yanwu Zhang;Brian Kieft;M. Jordan Stanway;Robert S. McEwen;Brett W. Hobson;James G. Bellingham;John P. Ryan;Thomas C. O'Reilly;Ben Y. Raanan;Monique Messié;Jason M. Smith;Francisco P. Chavez;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 808 - 817
Publisher: IEEE
 
» ISS as a Platform for Optical Remote Sensing of Ecosystem Carbon Fluxes: A Case Study Using HICO
Abstract:
Data from the hyperspectral imager for coastal ocean (HICO), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. Twenty-six HICO images were used from four study sites representing different vegetation types: grasslands, shrubland, and forest. Gross ecosystem production (GEP) data from eddy covariance were matched with HICO-derived spectra. Multiple algorithms were successful relating spectral reflectance with GEP, including: spectral vegetation indices (SVI), SVI in a light-use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to multiband hyperspectral indices from stepwise regressions and partial least squares regression. Successful algorithms were able to achieve r2 better than 0.7 for both GEP at the overpass time and daily GEP. These algorithms were successful using a diverse set of observations combining data from multiple years, multiple times during growing season, different times of day, with different view angles, and different vegetation types. The demonstrated robustness of the algorithms presented in this study over these conditions provides some confidence in mapping spatial patterns of GEP, describing variability within fields, as well as the regional patterns. The ISS orbit provides periods with multiple observations collected at different times of the day within a period of a few days. Diurnal GEP patterns were estimated comparing the half-hourly average GEP from the flux tower against HICO estimates of GEP (r2 = 0.87) if morning, midday, and afternoon observations were available.
Autors: Karl Fred Huemmrich;Petya K. Entcheva Campbell;Bo-Cai Gao;Larry B. Flanagan;Michael Goulden;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Oct 2017, volume: 10, issue:10, pages: 4360 - 4375
Publisher: IEEE
 
» Iterative Residual Generator for Fault Detection With Linear Time-Invariant State–Space Models
Abstract:
In this paper, an iterative residual generator (IRG) is proposed for discrete time-invariant state–space model with the aim of detecting faulty signals. By minimizing the mean square errors subject to unbiasedness constraint, a new filter with finite impulse response structure is derived. The resulting IRG is then obtained by extracting residual signal from the batch filter through several predictor/corrector iterations. It shows that IRG can provide a zero-mean Gaussian process regardless of previous estimation errors. More importantly, it includes the residual generation process in the Kalman filter as its special case. With the chi-square test, a numerical example is simulated to demonstrate that IRG can reduce the false alarm significantly compared with the traditional recursive strategy in the presence of actuator or sensor faults, and the estimation horizon length in IRG serves as a tuning parameter providing a tradeoff between the missed alarm and false alarm.
Autors: Shunyi Zhao;Biao Huang;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5422 - 5428
Publisher: IEEE
 
» JANUS-Based Services for Operationally Relevant Underwater Applications
Abstract:
This paper presents the design, test, and experimentation at sea of four JANUS-based services for operationally relevant underwater applications: 1) first contact and language switching; 2) transmission of automatic identification system data to submerged assets; 3) transmission of meteorological and oceanographic data to underwater vessels; and 4) support in distressed submarine operations. On March 24, 2017, JANUS was promulgated as a NATO standard (STANAG 4748) [1], marking the first time that a digital acoustic communications protocol is adopted at international level. JANUS is an open, simple, and robust modulation and coding scheme developed by the NATO STO Centre for Maritime Research and Experimentation, in collaboration with academia and industry. The implementation of the services presented in this paper is based on a standardized protocol and offers the potential to widely increase the safety and efficiency in maritime operations. The objective of this paper is to demonstrate that JANUS can be used in support of maritime operations, potentially increasing their efficiency. Such demonstration is achieved through experimentation at sea of four operationally relevant JANUS-based services. The four JANUS-based services discussed were validated during two different sea trials: REP15-Atlantic and REP16-Atlantic. During those trials, various heterogeneous configurations were considered, including the use of a state-of-the-art diesel-electric submarine, guaranteeing maximum relevance for validation and evaluation of the designed solutions. The collected results demonstrate that JANUS is a viable solution for operationally relevant underwater applications, thus validating the objective of this paper. Additionally, encouraging feedback has been provided by the operational community participating to the trials. The capabilities demonstrated served- as an initial proof of concept and will certainly lead to newer requirements and eventually even more functionalities.
Autors: Roberto Petroccia;João Alves;Giovanni Zappa;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Oct 2017, volume: 42, issue:4, pages: 994 - 1006
Publisher: IEEE
 
» Job Scheduling at Cascading Machines
Abstract:
We consider the serial batching scheduling problem in which a group of machines can process multiple jobs continuously to reduce the processing times of the second and subsequent jobs. The maximum batch size is finite. Since all jobs in the same batch are loaded and unloaded simultaneously, a completed job has to wait for the others. We examine how to schedule all jobs to minimize the total completion time. If the batch size is only one, i.e., a single job per batch, the total processing time will be longer, since no reduction in processing time is possible. As a consequence, the total completion time will also be longer. On the other hand, if the batch size is large, the total completion time can be large. Each job has to wait until all jobs in the same batch are completed. We identify several optimality properties of the optimal batching sequence. These properties are used to develop a dynamic programming algorithm to optimize the batching sequences efficiently. The complexity of the proposed method depends only on the maximum batch size and the number of jobs. The improvement achieved with the proposed method when compared with two other batching rules is illustrated using two practical applications.

Note to Practitioners— Machines with job cascading (or cluster tools) are commonly seen in semiconductor manufacturing processes. While meeting production move targets is a common goal for the nondelayed jobs, catching up with the schedule is an important task for the delayed jobs to achieve higher customer service level. From the viewpoint of scheduling, reducing the delay is equivalent to reducing completion time. Hence, we propose scheduling algorithms to reduce the completion time by taking advantage of the special structure of a cascading machine. In contrast to existing scheduling theory, the proposed algorithm can be efficient due to the small maximum batch size of real cascading machines. In addition to the theoretic- l contributions, this paper aims at solving practical problems through a rigorous approach. The finding and insight from this paper can be used to enhance shop floor control in a semiconductor fab.

Autors: Edward Huang;Kan Wu;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Oct 2017, volume: 14, issue:4, pages: 1634 - 1642
Publisher: IEEE
 
» Joint 3D Beamforming and Resource Allocation for Small Cell Wireless Backhaul in HetNets
Abstract:
Network densification and 3D beamforming are two potential techniques to support the increasing data rate in the upcoming 5G cellular networks. This letter focuses on the joint optimization of 3D beamforming and resource allocation for the small cell (SC) backhaul in a heterogeneous network. After analyzing the achievable data rates of users and SCs based on Gamma distribution, we formulate a joint optimization problem to maximize the network throughput. We then convert it to an equivalent optimization problem and develop a low-complexity algorithm on joint 3D beamforming and resource allocation. Simulation results demonstrate the performance improvement of the proposed algorithm.
Autors: Jinping Niu;Geoffrey Y. Li;Yanyan Li;Dingyi Fang;Xun Li;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2286 - 2289
Publisher: IEEE
 
» Joint Downlink and Uplink Energy Minimization in WET-Enabled Networks
Abstract:
Wireless energy transfer (WET) has received considerable attention for green communications. Unbalanced energy distribution and performance outages bring difficulties to the application of WET. This paper considers a network consisting of a WET-enabled access point (AP) and several energy-harvesting and source-powered user equipments (UEs). We investigate time-frequency resource allocation of downlink (DL) and uplink (UL) wireless information transfer (WIT) and DL WET. To improve energy efficiency and resource utilization, WET and WIT are orthogonally assigned at a low-frequency narrowband and a high-frequency wideband, respectively. A practical energy harvesting model is adopted, where power conversion efficiency depends on the received power instead of being a constant. To meet UEs’ different energy demands with the highest conversion efficiency, we develop beam switching, where the AP employs beamforming to charge UEs by jointly controlling power and time based on energy distributions and channel conditions. We formulate the overall energy minimization as a non-convex stochastic optimization problem, which is decomposed by fixing DL–UL time allocation ratio, transformed through Markov decision processes, and finally solved via linear programming. Simulation results verify the effectiveness of our proposed scheme on energy conservation and reveal the tradeoff of time allocation between DL and UL.
Autors: Qizhong Yao;Tony Q. S. Quek;Aiping Huang;Hangguan Shan;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6751 - 6765
Publisher: IEEE
 
» Joint EH Time Allocation and Distributed Beamforming in Interference-Limited Two-Way Networks With EH-Based Relays
Abstract:
In this paper, we consider an amplify-and-forward-based two-way relaying network, in which the relays need to harvest energy from the received radio frequency signals to remain active in the network and assist data exchange between two transceivers. In particular, considering time-switching architecture, we investigate the problem of joint energy harvesting (EH) time allocation and distributed beamforming in the presence of interference. Specifically, assuming that the perfect knowledge of the interfering links is not available, we study three different design approaches. First, we maximize the sum-rate of the network subject to individual EH power constraints at relays. Resorting to the semi-definite relaxation (SDR) and successive upper-bound minimization techniques, we devise an iterative algorithm that efficiently solves such a challenging problem. Next, we minimize the total power consumed by the relays subject to the rate constraints at the transceivers. Finally, we minimize the EH-phase duration subject to the individual EH power constraints at the relays as well as the rate constraints at the transceivers. The rate constraints, however, make both second and third design optimization problems non-convex and complicated. Although no closed-form solutions are available for these approaches, we propose efficient schemes by applying the SDR technique followed by semi-definite programming problems.
Autors: Soheil Salari;Il-Min Kim;Dong In Kim;Francois Chan;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6395 - 6408
Publisher: IEEE
 
» Joint Hybrid Tx–Rx Design for Wireless Backhaul With Delay-Outage Constraint in Massive MIMO Systems
Abstract:
This paper studies joint design of mixed-timescale hybrid precoding and combining to maximize the effective capacity for wireless backhaul in massive multiple-input multiple-output (MIMO) systems. Specifically, radio frequency (RF) analog processing is adaptive to statistical channel state information (CSI) while digital baseband processing is updated with instantaneous effective CSI. Equipped with traditional MIMO solutions at the baseband, the issue of RF design for both unconstrained-modulus and constant-modulus elements is addressed. Under the jointly correlated channel model, the objective function does not have a closed-form expression. In the unconstrained case, we derive the optimal RF solution structures, which lead to a combinatorial eigenmode selection formulation. Such an NP-hard problem is solved to near-optimality by semi-definite relaxation. In view of the additional difficulty posed by the non-convex modulus constraint, we exploit the problem structure to construct the constant-modulus design from the unconstrained-modulus solution which is cast as a problem of joint matrix approximation and solved by low-complexity Jacobi-like algorithms. Numerical results show that under loose and stringent delay-outage constraints, the mixed-timescale hybrid designs deliver effective rates comparable with other perfect CSI-based state-of-the-art baselines.
Autors: Ruikai Mai;Tho Le-Ngoc;Duy H. N. Nguyen;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6736 - 6750
Publisher: IEEE
 
» Joint OSNR and Interchannel Nonlinearity Estimation Method Based on Fractional Fourier Transform
Abstract:
We propose a novel joint optical signal noise ratio (OSNR) and interchannel nonlinearity (NL) estimation method by fractional Fourier transformation of linear-frequency modulation (LFM) signal. In our method, LFM signal acts as time domain pilot in front of the payload. Our method of OSNR estimation is insensitive to nonlinear noise of optical fiber. Lower OSNR estimation error is also achieved in comparison with differential pilot method. The interchannel NL measurement procedures are also simplified compared with previous work. We also provide a scientific way to calculate the reference interchannel NL. The interchannel NL estimation error of our method is lower than 1 dB for 9 channels transmission after 10 spans with launch power from 10 to 14 dBm.
Autors: Wanli Wang;Aiying Yang;Peng Guo;Yueming Lu;Yaojun Qiao;
Appeared in: Journal of Lightwave Technology
Publication date: Oct 2017, volume: 35, issue:20, pages: 4497 - 4506
Publisher: IEEE
 
» Joint Power Allocation and Beamforming for Energy-Efficient Two-Way Multi-Relay Communications
Abstract:
This paper considers the joint design of user power allocation and relay beamforming in relaying communications, in which multiple pairs of single-antenna users exchange information with each other via multiple-antenna relays in two time slots. All users transmit their signals to the relays in the first time slot while the relays broadcast the beamformed signals to all users in the second time slot. The aim is to maximize the system’s energy efficiency (EE) subject to quality-of-service (QoS) constraints in terms of exchange throughput requirements. The QoS constraints are nonconvex with many nonlinear cross-terms, so finding a feasible point is already computationally challenging. The sum throughput appears in the numerator while the total consumption power appears in the denominator of the EE objective function. The former is a nonconcave function and the latter is a nonconvex function, making fractional programming useless for EE optimization. Nevertheless, efficient iterations of low complexity to obtain its optimized solutions are developed. The performance of the multiple-user and multiple-relay networks under various scenarios is evaluated to show the merit of the proposed method.
Autors: Zhichao Sheng;Hoang Duong Tuan;Trung Q. Duong;H. Vincent Poor;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Oct 2017, volume: 16, issue:10, pages: 6660 - 6671
Publisher: IEEE
 
» Kalman-Gain Aided Particle PHD Filter for Multitarget Tracking
Abstract:
We propose an efficient sequential Monte Carlo probability hypothesis density (PHD) filter which employs the Kalman-gain approach during weight update to correct predicted particle states by minimizing the mean square error between the estimated measurement and the actual measurement received at a given time in order to arrive at a more accurate posterior. This technique identifies and selects those particles belonging to a particular target from a given PHD for state correction during weight computation. Besides the improved tracking accuracy, fewer particles are required in the proposed approach. Simulation results confirm the improved tracking performance when evaluated with different measures.
Autors: Abdullahi Daniyan;Yu Gong;Sangarapillai Lambotharan;Pengming Feng;Jonathon Chambers;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Oct 2017, volume: 53, issue:5, pages: 2251 - 2265
Publisher: IEEE
 
» Kernel Recursive Least Squares With Multiple Feedback and Its Convergence Analysis
Abstract:
In kernel adaptive filters (KAFs), feedback network can lead to performance improvement from the aspects of estimation accuracy and convergence rate. In this brief, a novel feedback structure is developed and applied to the kernel recursive least squares (KRLS), generating the KRLS with multiple feedback (KRLS-MF). In the proposed KRLS-MF, multiple previous outputs are utilized to update the structure parameters in the recurrent form. The obtained parameters are also proved to be convergent. Compared with other KAFs with and without feedback, KRLS-MF can improve both the filtering accuracy and convergence rate, efficiently.
Autors: Shiyuan Wang;Wanli Wang;Shukai Duan;Lidan Wang;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Oct 2017, volume: 64, issue:10, pages: 1237 - 1241
Publisher: IEEE
 
» KSF-OABE: Outsourced Attribute-Based Encryption with Keyword Search Function for Cloud Storage
Abstract:
Cloud computing becomes increasingly popular for data owners to outsource their data to public cloud servers while allowing intended data users to retrieve these data stored in cloud. This kind of computing model brings challenges to the security and privacy of data stored in cloud. Attribute-based encryption (ABE) technology has been used to design fine-grained access control system, which provides one good method to solve the security issues in cloud setting. However, the computation cost and ciphertext size in most ABE schemes grow with the complexity of the access policy. Outsourced ABE (OABE) with fine-grained access control system can largely reduce the computation cost for users who want to access encrypted data stored in cloud by outsourcing the heavy computation to cloud service provider (CSP). However, as the amount of encrypted files stored in cloud is becoming very huge, which will hinder efficient query processing. To deal with above problem, we present a new cryptographic primitive called attribute-based encryption scheme with outsourcing key-issuing and outsourcing decryption, which can implement keyword search function (KSF-OABE). The proposed KSF-OABE scheme is proved secure against chosen-plaintext attack (CPA). CSP performs partial decryption task delegated by data user without knowing anything about the plaintext. Moreover, the CSP can perform encrypted keyword search without knowing anything about the keywords embedded in trapdoor.
Autors: Jiguo Li;Xiaonan Lin;Yichen Zhang;Jinguang Han;
Appeared in: IEEE Transactions on Services Computing
Publication date: Oct 2017, volume: 10, issue:5, pages: 715 - 725
Publisher: IEEE
 
» Ku-/Ka-Band Extrapolation of the Altimeter Cross Section and Assessment With Jason2/AltiKa Data
Abstract:
A simple extrapolation technique is proposed for the intercalibration of the Ku- and Ka-band altimeter data based on a recent analytical scattering model referred to as “GO4.” This method is tested with AltiKa and Jason2-Ku altimeters using one year of reprocessed data with the improved retracking algorithm ICENEW. The variations of the normalized radar cross section with respect to the main oceanic parameters are investigated in the Ku and Ka bands; the latter band is shown to have an increased sensitivity to wind speed, significant wave height as well as sea surface temperature. As a by-product of this analysis, we derive an original expression for the swell impact on the mean square slope, which allows to correct the GO4 model for the contribution of long waves. We show that the Ku/Ka prediction agrees within 0.25 dB with the respective levels of AltiKa and Jason2-Ku cross sections at wind speed larger than 4 m/s.
Autors: Charles-Antoine Guérin;Jean-Christophe Poisson;Fanny Piras;Laiba Amarouche;Jean-Claude Lalaurie;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5679 - 5686
Publisher: IEEE
 
» L-Band Quantum-dash Self-Injection Locked Multiwavelength Laser Source for Future WDM Access Networks
Abstract:
We propose and demonstrate a compact, cost-effective, multiwavelength laser source employing self-injection locking scheme on InAs/InP quantum-dash (Qdash) laser diode. The device is shown to exhibit Fabry–Perot modes or subcarriers selectivity of 1 to 16 between ∼1600–1610 nm, with corresponding mode power (side mode suppression ratio) variation of ∼10 (∼38) to ∼−2.5 (∼22) dBm (dB), and able to extend beyond 1610 nm, thereby encompassing >30 optical carriers. Then, we utilized a single self-locked optical carrier at 1609.6 nm to successfully transmit 128 Gb/s dual-polarization quadrature phase shift keying signal over 20 km single mode fiber with ∼−16 dBm receiver sensitivity. To stem the viability of unifying the transceivers and addressing the requirements of next generation access networks, we propose self-seeded Qdash laser based wavelength division multiplexed passive optical network, capable of reaching a data capacity of 2.0 Tb/s () in L-band.
Autors: Mohamed Adel Shemis;Amr Mohamed Ragheb;Muhammad Talal Ali Khan;Habib Ali Fathallah;Saleh Alshebeili;Khurram Karim Qureshi;Mohammed Zahed Mustafa Khan;
Appeared in: IEEE Photonics Journal
Publication date: Oct 2017, volume: 9, issue:5, pages: 1 - 7
Publisher: IEEE
 
» Laboratory Demonstration of a Multiterminal VSC-HVDC Power Grid
Abstract:
This paper presents the design, development, control, and supervision of a hardware-based laboratory multiterminal-direct-current (MTDC) testbed. This work is a part of the TWENTIES (transmission system operation with large penetration of wind and other renewable electricity sources in networks by means of innovative tools and integrated energy solutions) DEMO 3 European project, which aims to demonstrate the feasibility of a dc grid through experimental tests. This is a hardware-in-the-loop dc system testbed with simulated ac systems in real-time simulation; the dc cables and some converters are actual, at laboratory scale. The laboratory-scale testbed is homothetic to a full-scale high-voltage direct-current (HVDC) system: electrical elements are the same in per unit. The testbed is supervised by a supervisory control and data acquisition system based on PcVue. A primary control-based droop control method to provide dc grid power balance and coordinated control methods to dispatch power as scheduled by a transmission system operator are implemented. Since primary control acts as converter level by using local measurements, a coordinated control is proposed to manage the dc grid power flow. The implemented system is innovative and achievable for real-time real-world MTDC-HVDC grid applications.
Autors: Sid-Ali Amamra;Frederic Colas;Xavier Guillaud;Pierre Rault;Samuel Nguefeu;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Oct 2017, volume: 32, issue:5, pages: 2339 - 2349
Publisher: IEEE
 
» Lake and Fjord Ice Imaging Using a Multifrequency Ground-Based Tomographic SAR System
Abstract:
The radar backscatter response of snow covered lake and fjord ice is investigated using a ground based multifrequency synthetic aperture radar system operated in a tomographic configuration. Direct imaging of the snow and ice layering is achieved by focusing the signal from a two-dimensional (2-D) synthetic array in the 3-D space. A mathematical derivation describing the propagation of electromagnetic waves across a dense and multilayered complex medium with arbitrary but finite number of layers is presented. It is used to estimate the depth and refractive indices of the snow and ice layers from the tomograms employing a simple least-square optimization scheme. The lake and fjord ice datasets are compared with respect to their vertical stratification and estimated refractive indices. The vertical structure of the reflectivity of the snow-covered lake ice is investigated and compared at two different frequencies, X-, and C-band. It is found that snow and ice volume responses at C-band are very low compared to the corresponding responses at X-band. At both frequencies, backscattering from surface and interface structures dominate volume contributions.
Autors: Temesgen Gebrie Yitayew;Laurent Ferro-Famil;Torbjørn Eltoft;Stefano Tebaldini;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Oct 2017, volume: 10, issue:10, pages: 4457 - 4468
Publisher: IEEE
 
» Land Cover Classification via Multitemporal Spatial Data by Deep Recurrent Neural Networks
Abstract:
Nowadays, modern earth observation programs produce huge volumes of satellite images time series that can be useful to monitor geographical areas through time. How to efficiently analyze such a kind of information is still an open question in the remote sensing field. Recently, deep learning methods proved suitable to deal with remote sensing data mainly for scene classification(i.e., convolutional neural networks on single images) while only very few studies exist involving temporal deep learning approaches [i.e., recurrent neural networks (RNNs)] to deal with remote sensing time series. In this letter, we evaluate the ability of RNNs, in particular, the long short-term memory (LSTM) model, to perform land cover classification considering multitemporal spatial data derived from a time series of satellite images. We carried out experiments on two different data sets considering both pixel-based and object-based classifications. The obtained results show that RNNs are competitive compared with the state-of-the-art classifiers, and may outperform classical approaches in the presence of low represented and/or highly mixed classes. We also show that the alternative feature representation generated by LSTM can improve the performances of standard classifiers.
Autors: Dino Ienco;Raffaele Gaetano;Claire Dupaquier;Pierre Maurel;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Oct 2017, volume: 14, issue:10, pages: 1685 - 1689
Publisher: IEEE
 
» Land Surface Temperature Estimate From Chinese Gaofen-5 Satellite Data Using Split-Window Algorithm
Abstract:
The Gaofen-5 (GF-5) satellite, the only satellite that provides the thermal infrared (TIR) sensor in the national high-resolution earth observation project of China, will observe earth surface at a spatial resolution of 40 m in four TIR channels. This paper aims at developing a new nonlinear, four-channel split-window (SW) algorithm to retrieve land surface temperature (LST) from GF-5 image. In the SW algorithm, its coefficients were obtained based on several subranges of atmospheric column water vapors (CWV) under various land surface conditions, in order to remove the atmospheric effect and improve the retrieval accuracy. Results showed that the new algorithm can obtain LST with root-mean-square errors of less than 1 K. Compared with previous two- and three-channel SW algorithms, the four-channel SW algorithm obtained better results in estimating LST, especially under moist atmospheres. Methods of estimating CWV and pixel emissivity were also conducted. The sensitive analysis of LST retrieval to instrument noise and uncertainty of pixel emissivity and water vapor demonstrated the good performance of the proposed algorithm. At last, the new SW algorithm was validated using ground-measured data at six sites, and some simulated images from airborne hyperspectral TIR data.
Autors: Xin Ye;Huazhong Ren;Rongyuan Liu;Qiming Qin;Yao Liu;Jijia Dong;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Oct 2017, volume: 55, issue:10, pages: 5877 - 5888
Publisher: IEEE
 
» Large Alphabet Source Coding Using Independent Component Analysis
Abstract:
Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications, such as compression of natural language text, speech, and images. The classic perception of most commonly used methods is that a source is best described over an alphabet, which is at least as large as the observed alphabet. In this paper, we challenge this approach and introduce a conceptual framework in which a large alphabet source is decomposed into “as statistically independent as possible” components. This decomposition allows us to apply entropy encoding to each component separately, while benefiting from their reduced alphabet size. We show that in many cases, such decomposition results in a sum of marginal entropies which is only slightly greater than the entropy of the source. Our suggested algorithm, based on a generalization of the binary independent component analysis, is applicable for a variety of large alphabet source coding setups. This includes the classical lossless compression, universal compression, and high-dimensional vector quantization. In each of these setups, our suggested approach outperforms most commonly used methods. Moreover, our proposed framework is significantly easier to implement in most of these cases.
Autors: Amichai Painsky;Saharon Rosset;Meir Feder;
Appeared in: IEEE Transactions on Information Theory
Publication date: Oct 2017, volume: 63, issue:10, pages: 6514 - 6529
Publisher: IEEE
 
» Large Scale Document Categorization With Fuzzy Clustering
Abstract:
Clustering documents into coherent categories is a very useful and important step for document processing and understanding. The introducing of fuzzy set theory into clustering provides a favorable mechanism to capture overlapping among document clusters. Document dataset is commonly represented as a collection of high-dimensional vectors, which may not be able to fit into memory entirely, when the dataset is large and with a very high dimensionality. However, most of the existing fuzzy clustering approaches deal with small and static datasets. Some of them may have a good scalability but they are only effective for low dimensional data. The study presented in this paper is about new efforts on fuzzy clustering of large-scale and high-dimensional data—especially suitable for document categorization. To consider both large scale and high dimensionality into the problem formulation, our key idea is to incorporate document-tailored fuzzy clustering into a scheme, which is effective for dealing with a large-scale problem. We first identified three representative schemes in fuzzy clustering for handling large-scale data, namely sampling extension, single pass, and divide ensemble. The limitation of fuzzy C-means (FCM)-based approaches for a large document clustering are then investigated. Based on the study, we propose new approaches by incorporating each of hyperspherical FCM and fuzzy coclustering with the three scale-up schemes, respectively. This enables our new approaches to maintain effectiveness for high-dimensional data with an extended scalability. Extensive experimental studies with real-world large document datasets have been conducted and the results demonstrate that the proposed approaches perform consistently better over existing ones in document categorization.
Autors: Jian-Ping Mei;Yangtao Wang;Lihui Chen;Chunyan Miao;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Oct 2017, volume: 25, issue:5, pages: 1239 - 1251
Publisher: IEEE
 
» Large Stroke High Fidelity PZN-PT Single-Crystal “Stake” Actuator
Abstract:
A new piezoelectric actuator design, called “Stake” actuator, is proposed and demonstrated in this work. As an example, the stake actuator is made of four d32–mode PZN-5.5%PT single crystals, each of 25mmL × 8mmW × 0.4mmT in dimensions, bonded with the aid of polycarbonate (PC) edge guide-cum-stiffeners into a square-pipe configuration for improved bending and twisting strengths and capped with top and bottom pedestals made of 1.5 mm thick anodized aluminium. The resultant stake actuator measured 9 mm × 9 mm × 28 mm. The hollow structure is a key design feature, which optimizes single crystal usage efficiency and lowers the overall cost of the actuator. The displacement-voltage responses, blocking forces, resonance characteristics of the fabricated stake actuator, as well as the load and temperature effects, are measured and discussed. Since d32 is negative for [011]-poled single crystal, the “Stake” actuator contracts in the axial direction when a positive polarity field is applied to the crystals. Biased drive is thus recommended when extensional displacement is desired. The single crystal stake actuator has negligible (<1%) hysteresis and a large linear strain range of > 0.13% when driven up to +300V (i.e., 0.75 kV/mm), which is close to the rhombohedral-to-orthorhombic transformation field (E RO) of 0.85 kV/mm of the single crystal used. The stake actuator displays a stroke of −36.5 μm (at +300V) despite its small overall dimensions, and has a blocking force of 114 N. The single crystal d 32 stake actuator fabricated displays more than 30% larger axial strain than the state-of-the-art PZT- stack actuators of comparable length as well as moderate blocking forces. Said actuators are thus ideal for applications when large displacements with simple open loop control are preferred.
Autors: Yu Huang;Yuexue Xia;Dian Hua Lin;Kui Yao;Leong Chew Lim;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Oct 2017, volume: 64, issue:10, pages: 1617 - 1624
Publisher: IEEE
 
» LAXY: A Location-Based Aging-Resilient Xy-Yx Routing Algorithm for Network on Chip
Abstract:
Network on chip (NoC) is a scalable interconnection architecture for ever increasing communication demand between processing cores. However, in nanoscale technology size, NoC lifetime is limited due to aging processes of negative bias temperature instability, hot carrier injection, and electromigration. Usually, because of unbalanced utilization of NoC resources, some parts of the network experience more thermal stress and duty cycle in comparison with other parts, which may accelerate chip failure. To slow down the aging rate of NoC, this paper proposes an oblivious routing algorithm called location-based aging-resilient Xy-Yx (LAXY) to distribute packet flow over entire network. LAXY is based on the fact that dimension-ordered routing algorithms imposes the highest traffic load on the central nodes in mesh topologies. To balance the traffic over the network, certain routers at the east and the west of NoC, with dimension-order XY routing, statically are configured as YX. Various configurations have been explored for LAXY and the simulations show a specific configuration, called Fishtail, increases mean time to failure of the routers and interconnects by about 42% and 56%, respectively. Moreover, by balancing the load over the network, LAXY improves overall packet latency by about 7% in average, with negligible area overhead.
Autors: Nezam Rohbani;Zahra Shirmohammadi;Maryam Zare;Seyed-Ghassem Miremadi;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Oct 2017, volume: 36, issue:10, pages: 1725 - 1738
Publisher: IEEE
 
» LCL Filter Design of a 50-kW 60-kHz SiC Inverter with Size and Thermal Considerations for Aerospace Applications
Abstract:
To achieve high power density, increasing the switching frequency of the power converter has become a trend. The LCL filter is a major contributor of the overall weight of a high-power-density converter (HPDC), especially the inverter-side inductor, which requires to suppress higher frequency harmonic contents at the inverter side. This paper describes a comprehensive design flow of the LCL filter for a 50-kW, 60-kHz two-level silicon carbide (SiC) inverter for high-power aerospace applications with space constraint and harsh ambient temperature environment. To meet the space constraint requirement and reduce the inductor size, specific design attention is made on a customized amorphous cored inductor with a comprehensive study on the relationships of inductor weight, core width, and total surface area with respect to air gap length. To overcome the harsh ambient temperature environment, a liquid cooling system of the amorphous cored inductor is also described.
Autors: Yong Liu;Kye-Yak See;Shan Yin;Rejeki Simanjorang;Chin Foong Tong;Arie Nawawi;Jih-Sheng Jason Lai;
Appeared in: IEEE Transactions on Industrial Electronics
Publication date: Oct 2017, volume: 64, issue:10, pages: 8321 - 8333
Publisher: IEEE
 
» Leakage Current and Low-Frequency Noise Analysis and Reduction in a Suspended SOI Lateral p-i-n Diode
Abstract:
In this paper, we present a detailed analysis of leakage current in a silicon-on-insulator (SOI) lateral P+PN+ (p-i-n) diode suspended on a microheating platform, combining device experimental characterization and numerical simulation. The diode leakage currents have been extensively studied using the back-gate bias as a means to alter the space-charge (SC) condition at the P region (I-region)/buried oxide interface from accumulation to full depletion, and finally to inversion. Both dark leakage current analysis and low-frequency noise characterization performed on the suspended SOI lateral p-i-n diode indicate device degradation induced by microelectromechanical systems postprocessing (i.e., deep reactive-ion etching or aluminum deposition). A low-temperature (~250 °C) in situ (i.e., using embedded microheater) annealing of SOI lateral p-i-n diode after postprocessing allows reduction of the diode leakage current and optimization of the device performance by neutralizing the interface traps and improving carriers’ lifetime and surface recombination velocity. Numerical simulations have been performed with Atlas/SILVACO for deeper analysis of the leakage current behavior in the lateral p-i-n diode and identification of the generation mechanism dominating the diode leakage behavior. Simulation reveals that the dominant generation rate in the diode depends on the SC conditions, the interface trap density, and the carriers’ lifetime in the I-region. The experimental and simulated behaviors of “as processed” and annealed diode leakage current are shown to be in good qualitative agreement.
Autors: Guoli Li;Valeriya Kilchytska;Nicolas André;Laurent A. Francis;Yun Zeng;Denis Flandre;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4252 - 4259
Publisher: IEEE
 
» Learning from Near Misses [Electrical Safety]
Abstract:
Examines ways engineers can learn from near-miss accidents. Some near-miss incidents are not reported, perhaps because the culture of the company doesn’t encourage a worker to report a near miss. If we really want to learn from these situations, we could publicize a general definition of a near miss that would include incidents where a worker could have been injured or killed if the work proceeded, and we could encourage prompt reporting so corrections can be made quickly before someone else is hurt or killed.
Autors: Daniel Doan;
Appeared in: IEEE Industry Applications Magazine
Publication date: Oct 2017, volume: 23, issue:5, pages: 6 - 13
Publisher: IEEE
 
» Learning Parameter-Advising Sets for Multiple Sequence Alignment
Abstract:
While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores), most users rely on the single default parameter setting provided by the aligner. A different parameter setting, however, might yield a much higher-quality alignment for the specific set of input sequences. The problem of picking a good choice of parameter values for specific input sequences is called parameter advising. A parameter advisor has two ingredients: (i) a set of parameter choices to select from, and (ii) an estimator that provides an estimate of the accuracy of the alignment computed by the aligner using a parameter choice. The parameter advisor picks the parameter choice from the set whose resulting alignment has highest estimated accuracy. In this paper, we consider for the first time the problem of learning the optimal set of parameter choices for a parameter advisor that uses a given accuracy estimator. The optimal set is one that maximizes the expected true accuracy of the resulting parameter advisor, averaged over a collection of training data. While we prove that learning an optimal set for an advisor is NP-complete, we show there is a natural approximation algorithm for this problem, and prove a tight bound on its approximation ratio. Experiments with an implementation of this approximation algorithm on biological benchmarks, using various accuracy estimators from the literature, show it finds sets for advisors that are surprisingly close to optimal. Furthermore, the resulting parameter advisors are significantly more accurate in practice than simply aligning with a single default parameter choice.
Autors: Dan DeBlasio;John Kececioglu;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Oct 2017, volume: 14, issue:5, pages: 1028 - 1041
Publisher: IEEE
 
» Learning to Recognize Human Activities Using Soft Labels
Abstract:
Human activity recognition system is of great importance in robot-care scenarios. Typically, training such a system requires activity labels to be both completely and accurately annotated. In this paper, we go beyond such restriction and propose a learning method that allow labels to be incomplete and uncertain. We introduce the idea of soft labels which allows annotators to assign multiple, and weighted labels to data segments. This is very useful in many situations, e.g., when the labels are uncertain, when part of the labels are missing, or when multiple annotators assign inconsistent labels. We formulate the activity recognition task as a sequential labeling problem. Latent variables are embedded in the model in order to exploit sub-level semantics for better estimation. We propose a max-margin framework which incorporate soft labels for learning the model parameters. The model is evaluated on two challenging datasets. To simulate the uncertainty in data annotation, we randomly change the labels for transition segments. The results show significant improvement over the state-of-the-art approach.
Autors: Ninghang Hu;Gwenn Englebienne;Zhongyu Lou;Ben Kröse;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Oct 2017, volume: 39, issue:10, pages: 1973 - 1984
Publisher: IEEE
 
» Less Becomes More for Microwave Imaging: Design and Validation of an Ultrawide-Band Measurement Array.
Abstract:
A compact, enclosed, ultrawide-band (UWB) antenna array is presented to acquire data for a quantitative microwave imaging method. Compared to existing systems, the proposed array allows a UWB antenna to be placed close to a target object while, at the same time, minimizing the volume of the imaging array. The antennas and metallic enclosure are designed to easily integrate with an iterative threedimensional (3-D) nonlinear inverse scattering technique. The volume of the internal imaging domain has been minimized for this particular architecture to reduce the computational time spent on reconstructing the dielectrics within the domain. Each cavity-backed element radiates toward the target and presents stable transmission characteristics across the 1-4-GHz band.
Autors: David Gibbins;Dallan Byrne;Tommy Henriksson;Beatriz Monsalve;Ian J. Craddock;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Oct 2017, volume: 59, issue:5, pages: 72 - 85
Publisher: IEEE
 
» Level Set Segmentation Algorithm for High-Resolution Polarimetric SAR Images Based on a Heterogeneous Clutter Model
Abstract:
In this paper, a heterogeneous clutter model named distribution is introduced into the level set method for segmentation of high-resolution polarimetric synthetic aperture radar (PolSAR) images. Level set methods are robust and effective techniques for segmentation. However, traditional level set methods for PolSAR data are based on the complex Wishart distribution, which is not an applicable model to high-resolution PolSAR images and heterogeneous regions such as forest and urban areas. The distribution is proved to be a highly flexible model for multilook PolSAR data, which is based on the product model with a generalized-gamma-distributed texture component. The -model-based level set segmentation method is assessed using C-band, X-band, and L-band PolSAR data acquired by RADARSAT-2, TerraSAR-X, and ESAR sensors, respectively. Experimental results show that the -distribution model has a better capacity for characterizing high-resolution PolSAR data, especially for extremely heterogeneous regions. Compared with the Wishart-model-based and Kummer-U-model-based level set methods and Markov random field based methods, it is observed that the proposed level set algorithm can obtain more precise segmentation results.
Autors: Ruijin Jin;Junjun Yin;Wei Zhou;Jian Yang;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Oct 2017, volume: 10, issue:10, pages: 4565 - 4579
Publisher: IEEE
 
» Leveraging nMOS Negative Differential Resistance for Low Power, High Reliability Magnetic Memory
Abstract:
We propose, demonstrate, and assess a nontunneling-based nMOS voltage-controlled negative differential resistance (V-NDR) concept for overcoming the intrinsic efficiency and reliability shortcomings of magnetic random access memory memories (MRAM). Using nMOS V-NDR circuits in series with MRAM tunnel junctions, we experimentally observe 40 times reduction in current during switching, enabling write termination and read margin amplification. Large scale Monte Carlo simulations also show 5X improvement in write energy savings and demonstrate the robustness of the scheme against device variability.
Autors: Shaodi Wang;Andrew Pan;Cecile Grezes;Pedram Khalili Amiri;Kang L. Wang;Chi On Chui;Puneet Gupta;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Oct 2017, volume: 64, issue:10, pages: 4084 - 4090
Publisher: IEEE
 
» Leveraging the Survivable All-Optical WDM Network Design With Network Coding Assignment
Abstract:
This letter investigates a novel use of network coding (NC) in 1 + 1 protection for transparent wavelength-division multiplexing networks by utilizing a cost-effective all-optical XOR encoder/decoder. In applying this scheme, we introduce a new problem, called routing, wavelength, and NC assignment, and formulate it as the integer linear programming model, aiming at maximizing the network throughput under constrained bandwidth capacity. We evaluate our proposal on the realistic topology, COST239, with all-to-one traffic setting. The numerical results on studied case show that the our NC-based approach could support up to 30% traffic more than the conventional 1 + 1 protection.
Autors: Dao Thanh Hai;
Appeared in: IEEE Communications Letters
Publication date: Oct 2017, volume: 21, issue:10, pages: 2190 - 2193
Publisher: IEEE
 
» Line Detection as an Inverse Problem: Application to Lung Ultrasound Imaging
Abstract:
This paper presents a novel method for line restoration in speckle images. We address this as a sparse estimation problem using both convex and non-convex optimization techniques based on the Radon transform and sparsity regularization. This breaks into subproblems, which are solved using the alternating direction method of multipliers, thereby achieving line detection and deconvolution simultaneously. We include an additional deblurring step in the Radon domain via a total variation blind deconvolution to enhance line visualization and to improve line recognition. We evaluate our approach on a real clinical application: the identification of B-lines in lung ultrasound images. Thus, an automatic B-line identification method is proposed, using a simple local maxima technique in the Radon transform domain, associated with known clinical definitions of line artefacts. Using all initially detected lines as a starting point, our approach then differentiates between B-lines and other lines of no clinical significance, including Z-lines and A-lines. We evaluated our techniques using as ground truth lines identified visually by clinical experts. The proposed approach achieves the best B-line detection performance as measured by the F score when a non-convex regularization is employed for both line detection and deconvolution. The F scores as well as the receiver operating characteristic (ROC) curves show that the proposed approach outperforms the state-of-the-art methods with improvements in B-line detection performance of 54%, 40%, and 33% for , , and ,- respectively, and of 24% based on ROC curve evaluations.
Autors: Nantheera Anantrasirichai;Wesley Hayes;Marco Allinovi;David Bull;Alin Achim;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Oct 2017, volume: 36, issue:10, pages: 2045 - 2056
Publisher: IEEE
 
» Linearity Enhancement of a Fully Integrated 6-GHz GaN Power Amplifier
Abstract:
A large-signal nonlinearity compensation technique is developed to improve the linearity of RF GaN power amplifiers. The design of a high power amplifier employing both common-source (CS) and common-gate (CG) GaN high-electron mobility transistors is presented for the IEEE 802.11p standard. The power amplifier is fabricated in 0.25- GaN-on-SiC technology and occupies 1.7 mm mm. The measurements show that 35-dBm output 1-dB compression point (OP1 dB) is obtained with 39-dBm OIP3 for two-tone intermodulation distortion testing. It also achieves 31% drain efficiency at 28.8-dBm output power with 10-V supply voltage considering a more than 6-dB back-off for orthogonal frequency division multiplexing-modulated signals. Linearity enhancement by means of the proposed CS–CG configuration is demonstrated in a fully integrated GaN power amplifier at 6 GHz.
Autors: Pilsoon Choi;Ujwal Radhakrishna;Chirn Chye Boon;Li-Shiuan Peh;Dimitri Antoniadis;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Oct 2017, volume: 27, issue:10, pages: 927 - 929
Publisher: IEEE
 
» Linearizing Discrete-Time Hybrid Systems
Abstract:
Model-based design approaches for embedded systems aim at generating correct-by-construction control software, guaranteeing that the closed-loop system (controller and plant) meets given system level formal specifications. This technical note addresses control synthesis for safety and reachability properties of possibly nonlinear discrete-time hybrid systems. By means of a syntactical transformations that requires nonlinear terms to be Lipschitz continuous functions, we overapproximate nonlinear dynamics with a linear system whose controllers are guaranteed to be controllers of the original system. We evaluate performance of our approach on meaningful control synthesis benchmarks, also comparing it to a state-of-the-art tool.
Autors: Vadim Alimguzhin;Federico Mari;Igor Melatti;Ivano Salvo;Enrico Tronci;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Oct 2017, volume: 62, issue:10, pages: 5357 - 5364
Publisher: IEEE
 

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