Electrical and Electronics Engineering publications abstract of: 02-2018 sorted by title, page: 7

» Crack-Free Silicon-Nitride-on-Insulator Nonlinear Circuits for Continuum Generation in the ${C}$ -Band
Abstract:
We report on the fabrication and testing of silicon-nitride-on-insulator nonlinear photonic circuits for complementary metal–oxide–semiconductor (CMOS) compatible monolithic co-integration with silicon-based optoelectronics. In particular, a process has been developed to fabricate low-loss crack-free Si3N4 730-nm-thick films for Kerr-based nonlinear functions featuring full process compatibility with existing silicon photonics and front-end Si optoelectronics. Experimental evidence shows that 2.1-cm-long nanowires based on such crack-free silicon nitride films are capable of generating a frequency continuum spanning 1515–1575 nm via self-phase modulation. This work paves the way to time-stable power-efficient Kerr-based broadband sources featuring full process compatibility with Si photonic integrated circuits on CMOS lines.
Autors: Houssein El Dirani;Marco Casale;Sébastien Kerdiles;Carole Socquet-Clerc;Xavier Letartre;Christelle Monat;Corrado Sciancalepore;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 355 - 358
Publisher: IEEE
 
» CRITIC-Based Node Importance Evaluation in Skeleton-Network Reconfiguration of Power Grids
Abstract:
Seven centrality indexes are first presented for identifying important nodes with topological features of a complex network and electrical characteristics of a power system considered. Then, a criteria importance through intercriteria correlation-based multi-index decision-making method, in which entropy and the Spearman’s rank correlation coefficient are integrated for reflecting the differences and correlations among multiple indexes, respectively, is presented to comprehensively identify the importance degrees of nodes in a given power grid. Finally, the proposed indexes and method are applied to actual Guangdong power system in China, and the results are compared with those attained by single-attribute and multi-attribute evaluation methods.
Autors: Zhenzhi Lin;Fushuan Wen;Huifang Wang;Guanqiang Lin;Tianwen Mo;Xiaojun Ye;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Feb 2018, volume: 65, issue:2, pages: 206 - 210
Publisher: IEEE
 
» Critical Link Analysis for Urban Transportation Systems
Abstract:
A fundamental and important step for safety analysis for an urban transportation system is to find its critical links. However, most approaches in the current literature focused on highway or intercity transportation systems. The key characteristics of urban transportation systems were not considered and the concept of criticality of links was mixed up with the concept of vulnerability. This paper defines the criticality of links from two perspectives, i.e., the vulnerability and potential, based on which a novel methodology for identifying critical links in an urban transportation network is proposed. This novel methodology includes a ranking method and a novel mesoscopic model to examine the urban transportation network performance. The mesoscopic model is a novel cell transmission model, which grasps key characteristics of an urban transportation network, such as dynamic demand generated on links, different link lengths, and intersection flow assignment. The method is validated by a real world case from Hong Kong. The simulation results indicate that the ranking of critical links depends on particular scenarios, available resources, and both supply and demand of the system; furthermore, two paradoxes are discovered and discussed.
Autors: Yaoming Zhou;Junwei Wang;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 402 - 415
Publisher: IEEE
 
» Critical Links Identification for Selective Outages in Interdependent Power-Communication Networks
Abstract:
Critical infrastructure, such as the smart grid, is vulnerable to failures and attacks. The complex nature of these systems embeds hidden vulnerabilities that threaten their functionality when exploited. In this paper, we perform a vulnerability analysis of the smart grid based on the power flow dynamics and in the presence of the essential communication network. Our analysis identifies a small number of power lines and communication links that can trigger a cascading failure and result in a blackout when removed. We quantify the failure effect in the form of fractional loss in the served load. Moreover, we formulate a mathematical model to present both components of the smart grid and their interdependency. A scalable algorithm is introduced to analyze the output of the model. We evaluate the proposed model and algorithm on the IEEE 14, 30, 57, and 300 Bus systems and associated communication networks, and report on the collected results.
Autors: Bassam Moussa;Parisa Akaber;Mourad Debbabi;Chadi Assi;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 472 - 483
Publisher: IEEE
 
» Cross-Correlation-Based Algorithm for Monitoring Laser Cutting With High-Power Fiber Lasers
Abstract:
We report on an innovative algorithm for an InGaAs and Si photodiode-based sensor system to detect incomplete cuts during high-power near infrared fiber laser cutting. Using such dual-photodiode-based sensor, the thermal radiation from the process zone is measured with the diode current being digitalized with a sampling rate of 20 kHz. The algorithm encompasses a normalization of the measured current, digital filtering, and cross-correlation calculation of both filtered diode signals. This sensor approach allows us to successfully detect cut interruptions in a series of more than 100 cuts in stainless steel, mild steel, and aluminum of different thicknesses with a type I and type II error of 0%. The underlying physics of the detection scheme based on the changes of the dynamic melt flow in the cut kerf from a complete cut to an incomplete cut is discussed.
Autors: Max Schleier;Benedikt Adelmann;Cemal Esen;Ralf Hellmann;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1585 - 1590
Publisher: IEEE
 
» Cross-layer adaptive elastic optical networks
Abstract:
Optical networks are designed to be operated statically: lightpaths are provisioned for uninterrupted operation for several years using high margins to anticipate the deterioration of their quality of transmission (QoT) from various factors (equipment aging, malfunctioning, and maintenance operations). Operating the network dynamically and closer to its actual capabilities increases efficiency and reduces capital expenditure. We develop a cross-layer QoT-aware toolkit that leverages monitoring information and the flexibility dimensions of elastic optical networks. It adapts the network's parameters and regulates the QoT to achieve high efficiency. The toolkit can be used in a plethora of use cases in the deployment or during the operation phase of the network, e.g., to harvest the excessive margins when lightpaths are initially deployed or failures are repaired, to adapt the network to changing traffic demands, and to restore margins when soft failures such as equipment malfunction or aging render the QoT of certain lightpaths unacceptable. In the last case, the toolkit can be used to appropriately reconfigure the lightpaths to restore their QoT and postpone the deployment of regenerators, as indicated by our simulations.
Autors: Ippokratis Sartzetakis;Konstantinos Christodoulopoulos;Emmanuel Varvarigos;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A154 - A164
Publisher: IEEE
 
» Crowdsourcing, Mixed Elastic Systems and Human-Enhanced Computing–A Survey
Abstract:
State-of-the-art practices have recognized the utility of leveraging human intervention as a crucial aspect of modern computing systems. The emerging crowdsourcing paradigm is based on harnessing human intelligence, effort and rational behaviors to augment computation and analysis. In addition to the crowdsourcing paradigm, new techniques have emerged that incorporate machine and human computational resources together forming a hybrid intelligence when addressing complex problems and tasks. This combined technique is particularly impactful if human and machine contributions can scale automatically in response to their respective efficiency and effectiveness when addressing subsets of a bigger problem – an approach that we have named mixed elastic systems. In this survey, we highlight state-of-the-art projects that investigate crowdsourcing, hybrid intelligence systems and mixed elastic systems. We also present a taxonomy and classification of the broader domain of human-enhanced computing systems as it assimilates crowdsourcing, hybrid intelligence, and mixed elastic systems.
Autors: Julian Jarrett;M. Brian Blake;Iman Saleh;
Appeared in: IEEE Transactions on Services Computing
Publication date: Feb 2018, volume: 11, issue:1, pages: 202 - 214
Publisher: IEEE
 
» Cryogenic Heat–Light Detection System for 1-cm³ Scintillating Crystals
Abstract:
We have developed a cryogenic heat and light detection system to investigate phonon and scintillation properties of scintillating crystals for rare event search experiments. The detector setup is designed to utilize a cm3 scintillating crystal as a target material. A cm3 Ge wafer is used as the absorber of the light detection. Metallic magnetic calorimeters are employed to measure heat and scintillation-light signals of the scintillating crystal, simultaneously, at millikelvin temperatures. This measurement setup is motivated to characterize various types of scintillation crystals in a standard coupon size for a final selection of the crystal compounds to be used for a rare event search experiment. We present the first measurement for a calcium molybdate crystal doped with niobium in the test setup of heat–light detection. Clear particle identification was obtained in comparison of relative amplitude ratios of the phonon and scintillation signals. Moreover, alpha- and electron-induced events showed difference in their pulse shapes of phonon and scintillation signals. We discuss the usage of this setup for the AMoRE search experiment.
Autors: H. L. Kim;G. B. Kim;H. J. Kim;I. Kim;Y. H. Kim;H. J. Lee;S. Y. Oh;J. H. So;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 766 - 770
Publisher: IEEE
 
» Cryogenic Preamplifiers for Magnetic Resonance Imaging
Abstract:
Pursuing the ultimate limit of detection in magnetic resonance imaging (MRI) requires cryogenics to decrease the thermal noise of the electronic circuits. As cryogenic coils for MRI are slowly emerging cryogenic preamplifiers are required to fully exploit their potential. A cryogenic preamplifier operated at 77 K is designed and implemented for C imaging at 3 T (32.13 MHz), using off-the-shelves components. The design is based on a high electron mobility transistor (ATF54143) in a common source configuration. Required auxiliary circuitry for optimal cryogenic preamplifier performance is also presented consisting of a voltage regulator (noise free supply voltage and optimal power consumption), switch, and trigger (for active detuning during transmission to protect the preamplifier). A gain of 18 dB with a noise temperature of 13.7 K is achieved. Performing imaging experiments in a 3 T scanner showed an 8% increased signal-to-noise ratio from 365 to 399 when lowering the temperature of the preamplifier from 296 to 77 K while keeping the coil at room temperature. This paper thus enables the merger of cryogenic coils and preamplifiers in the hopes of reaching the ultimate limit of detection for MRI.
Autors: Daniel H. Johansen;Juan D. Sanchez-Heredia;Jan R. Petersen;Tom K. Johansen;Vitaliy Zhurbenko;Jan H. Ardenkjær-Larsen;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Publication date: Feb 2018, volume: 12, issue:1, pages: 202 - 210
Publisher: IEEE
 
» Cryptanalysis of a Public Key Encryption Scheme Based on QC-LDPC and QC-MDPC Codes
Abstract:
This letter presents a cryptanalysis of the modified McEliece cryptosystem recently proposed by Moufek et al.. The system is based on the juxtaposition of quasi-cyclic LDPC and quasi-cyclic MDPC codes. The idea of our attack is to find an alternative permutation matrix together with an equivalent LDPC code which allow the decoding of any cipher-text with a very high probability. We also apply a recent technique to determine weak keys for this scheme. The results show that the probability of weak keys is high enough that this variant can be ruled out as a possible secure encryption scheme.
Autors: Vlad Dragoi;Hervé Talé Kalachi;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 264 - 267
Publisher: IEEE
 
» CubeSat Lunar Positioning System Enabled by Novel On-Board Electric Propulsion
Abstract:
Due to the advances in miniaturization, CubeSats are becoming more versatile, with projected mission capabilities that are traditionally reserved for larger satellites. However, they are still limited by a lack of efficient propulsive means. A novel electric thruster based on electron cyclotron resonance heating and magnetic nozzle acceleration may provide a suitable yet simple solution. This device, while currently providing 1000 s and 1 mN of thrust at 30 W of power, may enable lunar CubeSat missions from geosynchronous earth orbit using on-board propulsion. An example mission to provide GPS on the lunar surface using 3-U CubeSats in a 60°:28/4/6 Walker constellation with a semimajor axis of 4000 km is proposed; a preliminary assessment of this mission, together with the satellite architecture and cost, is performed. Concurrent trajectory design for very-low-energy transfers is used to demonstrate the feasibility of the mission and its impact on the spacecraft design.
Autors: Mick Wijnen;Nereida Agüera-Lopez;Sara Correyero-Plaza;Daniel Perez-Grande;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Feb 2018, volume: 46, issue:2, pages: 319 - 329
Publisher: IEEE
 
» Current Ripple Recovery Modeling Technique for Voltage-Mode Control Converters
Abstract:
In this brief, a current ripple recovery (CRR) model is proposed for voltage-mode control converters. By adding a duty cycle sample-hold effect, the inductor current ripple can be recovered so that the high-frequency dynamical information in the inductor current compensates for a conventional averaged model. The CRR model can be used to judge the system stability and, more importantly, identify the subharmonic oscillation. These theoretical results are in good agreement with experimental ones, which demonstrates the validity of the CRR model.
Autors: Hao Zhang;Chuanzhi Yi;Pengcheng Luo;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Feb 2018, volume: 65, issue:2, pages: 211 - 215
Publisher: IEEE
 
» Current Status and Future Trends of Photonic-Integrated FBG Interrogators
Abstract:
In this paper, we present an overview of the current efforts toward integration on chip of fiber Bragg grating (FBG) sensor interrogators. Different photonic-integration platforms are discussed, including monolithic planar lightwave circuit technology, silicon on insulator (SOI), indium phosphide, and gallium arsenide material platforms. Furthermore, various possible techniques for wavelength metering and methods for FBG multiplexing are discussed and compared in terms of resolution, dynamic performance, multiplexing capabilities, and reliability. The use of linear filters, array waveguide gratings (AWG) as multiple linear filters, and AWG-based centroid signal processing techniques are presented as well as interrogation techniques based on tunable microring resonators and Mach–Zehnder interferometers for phase sensitive detection. FBG sensor interrogation based on SOI platform using active and passive phase sensitive detection is also described, demonstrating specifically the potential of passive phase demodulation for high-speed dynamic strain measurements. This paper finally presents the challenges and perspectives of photonic integration to address the increasing requirements of several industrial applications.
Autors: Yisbel Eloisa Marin;Tiziano Nannipieri;Claudio J. Oton;Fabrizio Di Pasquale;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 946 - 953
Publisher: IEEE
 
» Current Waveform for Noise Reduction of a Switched Reluctance Motor Under Magnetically Saturated Condition
Abstract:
A novel method is proposed to derive the current waveform to reduce noise and vibration of a switched reluctance motor in a magnetically saturated region. Principle of noise and vibration reduction is based on reducing the variation of the radial force sum. To realize the minimum variation in the sum of the radial forces, radial force expression has been derived. In a magnetically saturated region, radial force expression is approximated with Fourier series with parameters as a function of current. With the proper approximation of radial force, the current waveform is derived to minimize the variation of the radial force sum. The proposed current waveform consists of dc, fundamental, second, and third harmonic components. Finite-element analysis and experiment result are included to show the validity of the proposed method.
Autors: Jihad Furqani;Masachika Kawa;Kyohei Kiyota;Akira Chiba;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 213 - 222
Publisher: IEEE
 
» Curvilinear Structure Analysis by Ranking the Orientation Responses of Path Operators
Abstract:
The analysis of thin curvilinear objects in 3D images is a complex and challenging task. In this article, we introduce a new, non-linear operator, called RORPO (Ranking the Orientation Responses of Path Operators). Inspired by the multidirectional paradigm currently used in linear filtering for thin structure analysis, RORPO is built upon the notion of path operator from mathematical morphology. This operator, unlike most operators commonly used for 3D curvilinear structure analysis, is discrete, non-linear and non-local. From this new operator, two main curvilinear structure characteristics can be estimated: an intensity feature, that can be assimilated to a quantitative measure of curvilinearity; and a directional feature, providing a quantitative measure of the structure's orientation. We provide a full description of the structural and algorithmic details for computing these two features from RORPO, and we discuss computational issues. We experimentally assess RORPO by comparison with three of the most popular curvilinear structure analysis filters, namely Frangi Vesselness, Optimally Oriented Flux, and Hybrid Diffusion with Continuous Switch. In particular, we show that our method provides up to 8 percent more true positive and 50 percent less false positives than the next best method, on synthetic and real 3D images.
Autors: Odyssée Merveille;Hugues Talbot;Laurent Najman;Nicolas Passat;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 304 - 317
Publisher: IEEE
 
» Cut-Set Bound is Loose for Gaussian Relay Networks
Abstract:
The cut-set bound developed by Cover and El Gamal in 1979 has since remained the best known upper bound on the capacity of the Gaussian relay channel. We develop a new upper bound on the capacity of the Gaussian primitive relay channel, which is tighter than the cut-set bound. Our proof uses Gaussian measure concentration to establish geometric relations, satisfied with high probability, between the -letter random variables associated with a reliable code for communicating over this channel. We then translate these geometric relations into new information inequalities that cannot be obtained with classical methods. Combined with a tensorization argument proposed by Courtade and Ozgur in 2015, our result also implies that the current capacity approximations for Gaussian relay networks, which have linear gap to the cut-set bound in the number of nodes, are order-optimal and lead to a lower bound on the pre-constant.
Autors: Xiugang Wu;Ayfer Özgür;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1023 - 1037
Publisher: IEEE
 
» Cyclic Continuous Max-Flow: A Third Paradigm in Generating Local Phase Shift Maps in MRI
Abstract:
Sensitivity to phase deviations in MRI forms the basis of a variety of techniques, including magnetic susceptibility weighted imaging and chemical shift imaging. Current phase processing techniques fall into two families: those which process the complex image data with magnitude and phase coupled, and phase unwrapping-based techniques that first linearize the phase topology across the image. However, issues, such as low signal and the existence of phase poles, can lead both methods to experience error. Cyclic continuous max-flow (CCMF) phase processing uses primal-dual-variational optimization over a cylindrical manifold, which represent the inherent topology of phase images, increasing its robustness to these issues. CCMF represents a third distinct paradigm in phase processing, being the only technique equipped with the inherent topology of phase. CCMF is robust and efficient with at least comparable accuracy as the prior paradigms.
Autors: John S. H. Baxter;Zahra Hosseini;Terry M. Peters;Maria Drangova;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 568 - 579
Publisher: IEEE
 
» Cylindrically Curved Checkerboard Surfaces for Radar Cross-Section Reduction
Abstract:
Checkerboard surfaces, for radar cross-section (RCS) reduction, utilizing artificial magnetic conductor structures on flexible cylindrically curved ground planes are introduced. The RCSs of cylindrical checkerboard surfaces are examined for two different radii of curvature. Wideband curved checkerboard surfaces are evaluated under normal incidence for HH and VV polarizations. Simulated bistatic RCS patterns of the cylindrical checkerboard surfaces are presented, discussed, and justified, and the backscattering is compared with measurements. A very good agreement is observed.
Autors: Wengang Chen;Constantine A. Balanis;Craig R. Birtcher;Anuj Y. Modi;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Feb 2018, volume: 17, issue:2, pages: 343 - 346
Publisher: IEEE
 
» Data Quality Guided Incentive Mechanism Design for Crowdsensing
Abstract:
In crowdsensing, appropriate rewards are always expected to compensate the participants for their consumptions of physical resources and involvements of manual efforts. While continuous low quality sensing data could do harm to the availability and preciseness of crowdsensing based services, few existing incentive mechanisms have ever addressed the issue of data quality. The design of quality based incentive mechanism is motivated by its potential to avoid inefficient sensing and unnecessary rewards. In this paper, we incorporate the consideration of data quality into the design of incentive mechanism for crowdsensing, and propose to pay the participants as how well they do, to motivate the rational participants to efficiently perform crowdsensing tasks. This mechanism estimates the quality of sensing data, and offers each participant a reward based on her effective contribution. We also implement the mechanism and evaluate its improvement in terms of quality of service and profit of service provider. The evaluation results show that our mechanism achieves superior performance when compared to general data collection model and uniform pricing scheme.
Autors: Dan Peng;Fan Wu;Guihai Chen;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Feb 2018, volume: 17, issue:2, pages: 307 - 319
Publisher: IEEE
 
» Data Transfer Methods in Real-Time Controller of Ion Cyclotron High-Voltage Power Supply
Abstract:
Ion cyclotron high-voltage power supply (IC-HVPS) with dual output (27 kV, and 15 kV, 3 MW) is operational at ITER-India laboratory with a 1.5-MW Diacrode-based RF source to be used for ion cyclotron RF system. The controller for IC-HVPS is designed with LabVIEW Real-time (RT) peripheral component interconnect eXtension for Instrumentation (PXI) controller to support all control and monitoring operations of the pulse step modulation-based power supply. Besides regulation of output voltage, the controller supports all essential features like fast dynamics, low ripple, and protection for source and loads. This is managed by close integration between RT system and field-programmable gate array (FPGA) inside the controller. Two types of data transfers inside the RT controller are implemented: 1) between FPGAs and RT controller and 2) among internal algorithms. RT controller and FPGAs are interconnected through PXI bus. Critical functions, signal generations, monitoring and data acquisition, and interfaces are assigned to FPGAs and managed by RT operating system installed in the controller. This paper discusses different techniques used mostly for transfer of information between RT controller and FPGAs. Information includes critical signals, data, measurements, commands, and configuration required for internal algorithms. Discussion also includes some specific choices made for synchronized and asynchronous transmission of parallel and sequential data.
Autors: H. Dhola;A. Patel;A. Thakar;N. P. Singh;R. Dave;D. Parmar;K. Mehta;N. Goswami;S. Gajjar;U. K. Baruah;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 828 - 835
Publisher: IEEE
 
» Data-Dependent Clustering-CFAR Detector in Heterogeneous Environment
Abstract:
This paper devises a new constant false alarm rate (CFAR) detection scheme to deal with the problem of radar target detection in heterogeneous environment. The proposed scheme, called “clustering-CFAR detector,” is data dependent and composed of three stages: an adaptive clustering procedure that, exploiting the recorded measurements of the clutter environment, divides the detection area into different classes to provide auxiliary information, a dynamic reference cell selector that chooses appropriate secondary data according to the classes, and a conventional CFAR processor to make the final decision about the target presence. The performance of “clustering-CFAR detector” is analyzed by computer simulation and public radar measured data (IPIX data and MSTAR data), and compared with existing CFAR detectors. The results show that the new detector achieves a better performance in the aspects of terrain classification, control of false alarm points, and probability of detection.
Autors: Shuping Lu;Wei Yi;Weijian Liu;Guolong Cui;Lingjiang Kong;Xiaobo Yang;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 476 - 485
Publisher: IEEE
 
» Data-Driven Motion Compensation Techniques for Noncooperative ISAR Imaging
Abstract:
We consider the data-driven motion compensation problem in inverse synthetic aperture radar (ISAR) imaging. We present optimization-based ISAR techniques and propose improvements to the range alignment, time-window selection, autofocus, time–frequency-based image reconstruction, and cross-range scaling procedures. In experiments, the improvements reduced the computational burden and increased the image contrast by 50% at best and 28% on average in several test cases, including changing translational and rotational motion.
Autors: Risto Vehmas;Juha Jylhä;Minna Väilä;Juho Vihonen;Ari Visa;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 295 - 314
Publisher: IEEE
 
» Data-Driven Subspace Predictive Control of a Nuclear Reactor
Abstract:
This paper introduces a methodology of designing subspace predictive reactor core power control during load-following mode of operation. The central idea is to implement predictive control law directly from the preprocessed input–output data set without using any explicit process model. The controller is designed to include design constraints, feedforward control, and integral control action effectively. Furthermore, time variations in the process are taken into account by recursively updating control parameters with the arrival of new data set. The efficacy of the proposed technique is demonstrated for tracking various load rejection as well as load-following transients for a pressurized water nuclear reactor. A detailed parameter sensitivity analysis is carried out to analyze the controller performance.
Autors: Vineet Vajpayee;Siddhartha Mukhopadhyay;Akhilanand Pati Tiwari;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 666 - 679
Publisher: IEEE
 
» DC Interrupting With Self-Excited Oscillation Based on the Superconducting Current-Limiting Technology
Abstract:
A dc circuit breaker (DCCB), which combines a superconducting current-limiting technology and a self-excited oscillation interrupting technology, was proposed. The proposed DCCB includes a superconducting current-limiting module and an interrupter module. The objective of this paper is to investigate the effects of a transverse magnetic field (TMF) on dc interruption based on the self-excited oscillation principle. The dc interruption characteristics of CO2 and SF6 were investigated by applying a TMF of 0 and 200 mT with a puffer-type structure as a benchmark. The experimental results show that applying a TMF of 200 mT can significantly reduce the arcing time compared with a TMF of 0 mT and puffer-type structure. The dc interruption capacity for the SF6 insulation is higher than that for the CO2 insulation in the interrupter module under the same experimental condition. The simulation results of rated voltage of 10 kV show that the superconducting current-limit module limited the short current of 20 kA to less than 1 kA, and the arcing time was 4.5 ms. The results of rated voltage of 200 kV, short current of 30 kA, show that the DCCB only needed to interrupt the limited current of 3.5 kA and the overvoltage was less than 200 kV.
Autors: Bin Xiang;Zhiyuan Liu;Chuanchuan Wang;Zhenle Nan;Yingsan Geng;Jianhua Wang;Satoru Yanabu;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 529 - 536
Publisher: IEEE
 
» DCAP: Improving the Capacity of WiFi Networks with Distributed Cooperative Access Points
Abstract:
This paper presents the Distributed Cooperative Access Points (DCAP) system that can simultaneously serve multiple clients using cooperative beamforming to increase the capacity of WiFi-type wireless networks. The distributed APs are connected by Ethernet and driven by independent low-cost local oscillators. To facilitate cooperative beamforming, we address three major challenges: the phase synchronization, the channel state information (CSI) measurement, and the user selection. Specifically, we develop 1) a cooperative tracking scheme to track signal phase drifts at symbol level without adding extra hardware complexity; 2) an incremental CSI estimation mechanism that removes the per-frame CSI measurement overhead of previous approaches; and 3) a simple random user selection algorithm that scales the network capacity linearly and delivers over percent performance compared to the optimal but complex greedy algorithm. We implement DCAP on the Sora software radio platform and evaluate it in a wireless network with nine nodes. Experimental results show that the cooperative beamforming is feasible in practice, and our cooperative phase tracking can ensure strict phase alignment ( 0.03 radian) among APs during the entire beamforming period (1.2 ms). Otherwise, without tracking, phases may drift by 0.3 radian over merely 600 s, causing that the symbol SNR decreases as large as 20 dB.
Autors: Taotao Wang;Qing Yang;Kun Tan;Jiansong Zhang;Soung Chang Liew;Shengli Zhang;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Feb 2018, volume: 17, issue:2, pages: 320 - 333
Publisher: IEEE
 
» De-Correlated Improved Adaptive Exponential FLAF-Based Nonlinear Adaptive Feedback Cancellation for Hearing Aids
Abstract:
Modern-day digital hearing aids are prone to an unavoidable acoustic feedback phenomenon, degrading sound quality and speech intelligibility. The linear adaptive feedback cancellation (AFC) systems based on finite-impulse-response filters do not yield satisfactory performance under nonlinearity encountered in the feedback path. In an endeavor to overcome this, a de-correlated improved adaptive exponential functional link adaptive filter (DI-AEF)-based nonlinear AFC (NAFC) system is developed in this paper. It utilizes cross terms of the input samples and trigonometrical expansion with exponentially varying amplitude. To save computations, the delayed outputs of the feedback canceler are appended at the input layer, inspired by the IIR filtering technique. The adaptive de-correlation filter is updated by variable convergence and forgetting factor windowed recursive least square algorithm to address the biased estimation problem. The corresponding update rules, convergence, and bounded-input bounded-output stability conditions have been derived. Extensive simulation results demonstrate the efficacy of the proposed NAFC system for real input signals in terms of perceptual evaluation of speech and audio quality and added stable gain (ASG). The DI-AEF-based system achieves nearly 4-dB improvement in ASG while consuming 53% and 37% less multiplications and additions than the existing nonlinear methods.
Autors: Vasundhara;N. B. Puhan;Ganapati Panda;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 650 - 662
Publisher: IEEE
 
» Decaying Time Constant Enhanced MEMS Disk Resonator for High Precision Gyroscopic Application
Abstract:
This paper reports a new design strategy of adding lumped masses to the frame structure of a disk resonator gyroscope (DRG) to mitigate its figure of merit (FOM). A greatly enhanced decaying time constant τ can lead to very small FOM, which could then greatly mitigate the DRG's bias and bias drift. Additionally, this technique could also reduce the Brownian noise floor. A comprehensive investigation of the possible ways to add the lumped masses is presented, and a detailed design guideline is provided. A DRG prototype based on this design strategy is then presented and shows a τ of 38.5 s, a quality factor Q of 358 k, and a FOM of 1.9°/s. The prototype is operated in the force-to-rebalance mode, and an angle random walk of 0.012°/√h and a bias stability of 0.08°/h are demonstrated experimentally. This design strategy is suitable for use in batch fabrication of very high precision microelectromechanical systems devices such as gyroscopes.
Autors: Xin Zhou;Dingbang Xiao;Qingsong Li;Zhanqiang Hou;Kaixuan He;Zhihua Chen;Yulie Wu;Xuezhong Wu;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 452 - 458
Publisher: IEEE
 
» Decentralized Active and Reactive Power Control for an AC-Stacked PV Inverter With Single Member Phase Compensation
Abstract:
This paper proposes a decentralized control scheme for controlling active and reactive power of grid-tied ac-stacked photovoltaic (PV) inverter architecture using single member phase compensation. Reactive power control is required for the next generation of grid-tied smart PV inverter systems in power networks with high PV penetration. The decentralized control scheme proposed in this paper allows for a fully distributed architecture, both in terms of active and reactive power control and physical implementation of a PV system. This will result in higher reliability and potentially lower cost with minimum communications requirements. A decentralized controller enables higher switching frequencies that can shrink passive components. Therefore, string voltage variations due to voltage drop across passive components will be negligible and the system will be controlled with minimum communications requirement. The relative gain array approach has been used to study the feasibility of the decentralized control scheme. Detailed modeling and analysis are provided to show the effectiveness of the proposed decentralized approach and the effect of this approach on control implementation. Finally, effectiveness of the proposed decentralized approach is verified using mathematical modeling, simulation, and a lab-scale experimental setup in different operation conditions.
Autors: Hamidreza Jafarian;Robert Cox;Johan H. Enslin;Shibashis Bhowmik;Babak Parkhideh;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 345 - 355
Publisher: IEEE
 
» Decentralized Event-Triggered Control for Large-Scale Networked Fuzzy Systems
Abstract:
This paper addresses event-triggered data transmission in a class of large-scale networked nonlinear systems with transmission delays and nonlinear interconnections. Each nonlinear subsystem in the considered large-scale system is represented by a Takagi–Sugeno model, and exchanges its information through a digital channel. We propose an event-triggering mechanism, which determines when the premise variables and system states should be transmitted to the controller. Our goal is to design a decentralized event-triggered state-feedback fuzzy controller, such that the resulting closed-loop fuzzy control system is asymptotically stable while the measured information is transmitted to the controller as little as possible. By using the input delay and perturbed system approaches, the closed-loop sampled-data fuzzy system with event-triggered control is first reformulated into a continuous-time system with time-varying delay and extra disturbance. Then, based on the new model, we introduce a Lyapunov–Krasovskii functional with virtue of Wirtinger's inequality, where not all of the Lyapunov matrices are required to be positive definite. The codesign result is derived to obtain simultaneously the controller gains, sampled period, network delay, and event-triggered parameter in terms of a set of linear matrix inequalities. Finally, two simulation examples are provided to validate the advantage of the proposed method.
Autors: Zhixiong Zhong;Chih-Min Lin;Zhenhua Shao;Min Xu;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 29 - 45
Publisher: IEEE
 
» Decoupled Current Control With Synchronous Frequency Damping for MMC Considering Sub-module Capacitor Voltage Ripple
Abstract:
Capacitor voltage ripple in the fundamental frequency is distinctive in the performance of modular multilevel converters (MMCs), unlike other voltage-source converters. First, in order to reveal the influence of capacitor voltage ripple, the coupling effect of conventional MMC double-loop control strategy is investigated to explain the unsatisfactory response. Then, decoupled current control with synchronous frequency damping is proposed, eliminating the coupling terms in the presented average value MMC model, which can improve the system dynamic behavior. Moreover, the damping index is defined and designed in the proposed control strategy to compromise between current decoupling and oscillation damping. Furthermore, the dynamic MMC characteristics with the decoupled current control and appropriate damping index are explored with detailed theoretical analysis. Finally, the simulation results validate the effectiveness of the proposed control strategy.
Autors: Heya Yang;Wuhua Li;Lei Lin;Xiangning He;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 419 - 428
Publisher: IEEE
 
» Decoupling Structures for Millimeter Wave Integrated Circuits in Digital CMOS Processes
Abstract:
This brief studies the effect of nonideal decoupling structures on the performance of single-ended circuits operating at the millimeter wave frequency range. Based on a first-order approximation, an upper limit on the impedance of decoupling structures is derived, given a prespecified accepted degradation in insertion loss. To verify the analysis, a 110-GHz single-ended amplifier with a compact decoupling structure based on distributed interdigitized metal-oxide-metal capacitor is implemented. The full-wave electromagnetic simulations of the decoupling structure show an input impedance of (0.47 – j0.12) at 110 GHz, and the magnitude is less than from 82 to 144 GHz. The degradation in the insertion loss of the matching network is simulated to be less than 0.5-dB compared with the use of ideal decoupling capacitors at 110 GHz. The area of the decoupling structure is when implemented in 65-nm digital CMOS process.
Autors: Kefei Wu;Sriram Muralidharan;Mona Mostafa Hella;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 788 - 792
Publisher: IEEE
 
» Deep Convolutional Computation Model for Feature Learning on Big Data in Internet of Things
Abstract:
Currently, a large number of industrial data, usually referred to big data, are collected from Internet of Things (IoT). Big data are typically heterogeneous, i.e., each object in big datasets is multimodal, posing a challenging issue on the convolutional neural network (CNN) that is one of the most representative deep learning models. In this paper, a deep convolutional computation model (DCCM) is proposed to learn hierarchical features of big data by using the tensor representation model to extend the CNN from the vector space to the tensor space. To make full use of the local features and topologies contained in the big data, a tensor convolution operation is defined to prevent overfitting and improve the training efficiency. Furthermore, a high-order backpropagation algorithm is proposed to train the parameters of the deep convolutional computational model in the high-order space. Finally, experiments on three datasets, i.e., CUAVE, SNAE2, and STL-10 are carried out to verify the performance of the DCCM. Experimental results show that the deep convolutional computation model can give higher classification accuracy than the deep computation model or the multimodal model for big data in IoT.
Autors: Peng Li;Zhikui Chen;Laurence Tianruo Yang;Qingchen Zhang;M. Jamal Deen;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 790 - 798
Publisher: IEEE
 
» Deep Learning Based Communication Over the Air
Abstract:
End-to-end learning of communications systems is a fascinating novel concept that has so far only been validated by simulations for block-based transmissions. It allows learning of transmitter and receiver implementations as deep neural networks (NNs) that are optimized for an arbitrary differentiable end-to-end performance metric, e.g., block error rate (BLER). In this paper, we demonstrate that over-the-air transmissions are possible: We build, train, and run a complete communications system solely composed of NNs using unsynchronized off-the-shelf software-defined radios and open-source deep learning software libraries. We extend the existing ideas toward continuous data transmission, which eases their current restriction to short block lengths but also entails the issue of receiver synchronization. We overcome this problem by introducing a frame synchronization module based on another NN. A comparison of the BLER performance of the “learned” system with that of a practical baseline shows competitive performance close to  dB, even without extensive hyperparameter tuning. We identify several practical challenges of training such a system over actual channels, in particular, the missing channel gradient, and propose a two-step learning procedure based on the idea of transfer learning that circumvents this issue.
Autors: Sebastian Dörner;Sebastian Cammerer;Jakob Hoydis;Stephan ten Brink;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 132 - 143
Publisher: IEEE
 
» Deep Learning for Infrared Thermal Image Based Machine Health Monitoring
Abstract:
The condition of a machine can automatically be identified by creating and classifying features that summarize characteristics of measured signals. Currently, experts, in their respective fields, devise these features based on their knowledge. Hence, the performance and usefulness depends on the expert's knowledge of the underlying physics or statistics. Furthermore, if new and additional conditions should be detectable, experts have to implement new feature extraction methods. To mitigate the drawbacks of feature engineering, a method from the subfield of feature learning, i.e., deep learning (DL), more specifically convolutional neural networks (NNs), is researched in this paper. The objective of this paper is to investigate if and how DL can be applied to infrared thermal (IRT) video to automatically determine the condition of the machine. By applying this method on IRT data in two use cases, i.e., machine-fault detection and oil-level prediction, we show that the proposed system is able to detect many conditions in rotating machinery very accurately (i.e., 95 and 91.67% accuracy for the respective use cases), without requiring any detailed knowledge about the underlying physics, and thus having the potential to significantly simplify condition monitoring using complex sensor data. Furthermore, we show that by using the trained NNs, important regions in the IRT images can be identified related to specific conditions, which can potentially lead to new physical insights.
Autors: Olivier Janssens;Rik Van de Walle;Mia Loccufier;Sofie Van Hoecke;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 151 - 159
Publisher: IEEE
 
» Deep Learning for Passive Synthetic Aperture Radar
Abstract:
We introduce a deep learning (DL) framework for inverse problems in imaging, and demonstrate the advantages and applicability of this approach in passive synthetic aperture radar (SAR) image reconstruction. We interpret image reconstruction as a machine learning task and utilize deep networks as forward and inverse solvers for imaging. Specifically, we design a recurrent neural network (RNN) architecture as an inverse solver based on the iterations of proximal gradient descent optimization methods. We further adapt the RNN architecture to image reconstruction problems by transforming the network into a recurrent auto-encoder, thereby allowing for unsupervised training. Our DL based inverse solver is particularly suitable for a class of image formation problems in which the forward model is only partially known. The ability to learn forward models and hyper parameters combined with unsupervised training approach establish our recurrent auto-encoder suitable for real world applications. We demonstrate the performance of our method in passive SAR image reconstruction. In this regime a source of opportunity, with unknown location and transmitted waveform, is used to illuminate a scene of interest. We investigate recurrent auto-encoder architecture based on the and constrained least-squares problem. We present a projected stochastic gradient descent based training scheme which incorporates constraints of the unknown model parameters. We demonstrate through extensive numerical simulations that our DL based approach out performs conventional sparse coding methods in terms of computation and reconstructed image quality, specifically, when no information about the transmitter is available.
Autors: Bariscan Yonel;Eric Mason;Birsen Yazıcı;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 90 - 103
Publisher: IEEE
 
» Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks
Abstract:
With the increasing presence of cognitive radio networks as a means to address limited spectral resources, improved wireless security has become a necessity. In particular, the potential of a node to impersonate a licensed user demonstrates the need for techniques to authenticate a radio's true identity. In this paper, we use deep learning to detect physical-layer attributes for the identification of cognitive radio devices, and demonstrate the performance of our method on a set of IEEE 802.15.4 devices. Our method is based on the empirical principle that manufacturing variability among wireless transmitters that conform to the same standard creates unique, repeatable signatures in each transmission, which can then be used as a fingerprint for device identification and verification. We develop a framework for training a convolutional neural network using the time-domain complex baseband error signal and demonstrate 92.29% identification accuracy on a set of seven 2.4 GHz commercial ZigBee devices. We also demonstrate the robustness of our method over a wide range of signal-to-noise ratios.
Autors: Kevin Merchant;Shauna Revay;George Stantchev;Bryan Nousain;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 160 - 167
Publisher: IEEE
 
» Deep Learning Methods for Improved Decoding of Linear Codes
Abstract:
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.
Autors: Eliya Nachmani;Elad Marciano;Loren Lugosch;Warren J. Gross;David Burshtein;Yair Be’ery;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 119 - 131
Publisher: IEEE
 
» Deep Learning: The Frontier for Distributed Attack Detection in Fog-to-Things Computing
Abstract:
The increase in the number and diversity of smart objects has raised substantial cybersecurity challenges due to the recent exponential rise in the occurrence and sophistication of attacks. Although cloud computing has transformed the world of business in a dramatic way, its centralization hammers the application of distributed services such as security mechanisms for IoT applications. The new and emerging IoT applications require novel cybersecurity controls, models, and decisions distributed at the edge of the network. Despite the success of the existing cryptographic solutions in the traditional Internet, factors such as system development flaws, increased attack surfaces, and hacking skills have proven the inevitability of detection mechanisms. The traditional approaches such as classical machine-learning-based attack detection mechanisms have been successful in the last decades, but it has already been proven that they have low accuracy and less scalability for cyber-attack detection in massively distributed nodes such as IoT. The proliferation of deep learning and hardware technology advancement could pave a way to detecting the current level of sophistication of cyber-attacks in edge networks. The application of deep networks has already been successful in big data areas, and this indicates that fog-tothings computing can be the ultimate beneficiary of the approach for attack detection because a massive amount of data produced by IoT devices enable deep models to learn better than shallow algorithms. In this article, we propose a novel distributed deep learning scheme of cyber-attack detection in fog-to-things computing. Our experiments show that deep models are superior to shallow models in detection accuracy, false alarm rate, and scalability.
Autors: Abebe Abeshu;Naveen Chilamkurti;
Appeared in: IEEE Communications Magazine
Publication date: Feb 2018, volume: 56, issue:2, pages: 169 - 175
Publisher: IEEE
 
» Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors
Abstract:
Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.
Autors: Juan P. Dominguez-Morales;Angel F. Jimenez-Fernandez;Manuel J. Dominguez-Morales;Gabriel Jimenez-Moreno;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Publication date: Feb 2018, volume: 12, issue:1, pages: 24 - 34
Publisher: IEEE
 
» Deep Unfolding for Topic Models
Abstract:
Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.
Autors: Jen-Tzung Chien;Chao-Hsi Lee;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 318 - 331
Publisher: IEEE
 
» Defending from Stealthy Botnets Using Moving Target Defenses
Abstract:
In today’s IT landscape, organizations are increasingly exposed to an array of novel and sophisticated threats—including advanced persistent threats (APTs) and distributed denial-of-service (DDoS) attacks—which can bypass traditional defenses and persist in target systems indefinitely. Threat actors often rely on networks of compromised and remotely controlled hosts, known as botnets, to execute a number of different cyberattacks and engage in criminal or unauthorized activities. Protecting sensitive and mission-critical data from competitors, state actors, and organized crime has become increasingly critical for the well-being of many organizations. A promising approach to botnet detection and mitigation relies on moving target defense (MTD), a novel and game-changing approach to cyber defense. MTD creates asymmetric uncertainty, providing the defender with a tactical advantage over the attacker. MTD techniques are designed to continuously change or shift a system’s attack surface, thus increasing cost and complexity for the threat actors. We show how the botnet detection and mitigation problem can be decomposed in three related and relatively simpler challenges, and how these challenges can be effectively tackled adopting an MTD approach, ultimately limiting the ability of a botnet to persist within a target system.
Autors: Massimiliano Albanese;Sushil Jajodia;Sridhar Venkatesan;
Appeared in: IEEE Security & Privacy
Publication date: Feb 2018, volume: 16, issue:1, pages: 92 - 97
Publisher: IEEE
 
» Degradation Behavior of Lithium-Ion Batteries During Calendar Ageing—The Case of the Internal Resistance Increase
Abstract:
Lithium-ion batteries are regarded as the key energy storage technology for both e-mobility and stationary renewable energy storage applications. Nevertheless, Lithium-ion batteries are complex energy storage devices, which are characterized by a complex degradation behavior, which affects both their capacity and internal resistance. This paper investigates, based on extended laboratory calendar ageing tests, the degradation of the internal resistance of a lithium-ion battery. The dependence of the internal resistance increase on the temperature and state-of-charge level has been extensive studied and quantified. Based on the obtained laboratory results, an accurate semiempirical lifetime model, which is able to predict with high accuracy the internal resistance increase of the lithium-ion battery over a wide temperature range and for all state-of-charge levels, was proposed and validated.
Autors: Daniel-Ioan Stroe;Maciej Swierczynski;Søren Knudsen Kær;Remus Teodorescu;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 517 - 525
Publisher: IEEE
 
» Degrees of Freedom of Full-Duplex Multiantenna Cellular Networks
Abstract:
We study Please be advised that per instructions from the Communications Society this proof was formatted in Times Roman font and therefore some of the fonts will appear different from the fonts in your originally submitted manuscript. For instance, the math calligraphy font may appear different due to usage of the usepackage[mathcal]euscript. The Communications Society has decided not to use Computer Modern fonts in their publications. the degrees of freedom (DoF) of cellular networks in which a full duplex (FD) base station (BS) equipped with multiple transmit and receive antennas communicates with multiple mobile users. We consider two different scenarios. In the first scenario, we study the case when half duplex (HD) users, partitioned to either the uplink (UL) set or the downlink (DL) set, simultaneously communicate with the FD BS. In the second scenario, we study the case when FD users simultaneously communicate UL and DL data with the FD BS. Unlike conventional HD only systems, inter-user interference (within the cell) may severely limit the DoF, and must be carefully taken into account. With the goal of providing theoretical guidelines for designing such FD systems, we completely characterize the sum DoFs for both FD cellular networks. The key idea of the proposed scheme is to carefully allocate UL and DL streams using interference alignment and beam forming techniques. By comparing the DoFs of the FD systems with those of the conventional HD systems, we show that the DoF can approach the two-fold gain over the HD systems, when the number of users becomes large enough compared with the number of antennas at the BS.
Autors: Sung Ho Chae;Sung Hoon Lim;Sang-Woon Jeon;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 982 - 995
Publisher: IEEE
 
» Delay-Based Traffic Signal Control for Throughput Optimality and Fairness at an Isolated Intersection
Abstract:
With the attractive feature of guaranteeing maximum network throughput, backpressure routing has been widely used in wireless communication networks. Motivated by the backpressure routing, in this paper, we propose a delay-based traffic signal control algorithm in transportation networks. We prove that this delay-based control achieves optimal throughput performance, same as the queue-based traffic signal control in the literature. However, a vehicle at a lane whose queue length remains very small may be excessively delayed under the queue-based signal control. Our delay-based backpressure control can deal with the excessive delays and achieve better fairness with respect to delay while still guaranteeing throughput optimality. Moreover, a general weighted control scheme combining the queue-based and delay-based schemes is also investigated, to provide a more flexible control according to the quality of service requirements. Numerical results explore their performance under both homogeneous and heterogeneous traffic scenarios.
Autors: Jian Wu;Dipak Ghosal;Michael Zhang;Chen-Nee Chuah;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 896 - 909
Publisher: IEEE
 
» Demodulation Approach for Slowly Sampled Sensorless Field-Oriented Control Systems Enabling Multiple-Frequency Injections
Abstract:
This paper describes a demodulation approach based on the least squares method for a saliency-based position estimation in slowly sampled field-oriented control systems. The proposed approach focuses on the sensorless control of electrical drives in which the sample rate of the control task chosen is slower than both the maximum possible update rate of the phase voltages and the maximum possible sample rate of the phase current measurement by a multiple. Under those conditions, it is possible to inject multiple-frequency carrier signals between two successive control sampling instances without affecting the control. Furthermore, a combined demodulation of these signals is enabled by exploiting the constant manipulated variables of the field-oriented control system during the injection sequence. With the proposed method, the signal-to-noise-ratio of the calculated rotor position as well as the acoustic noise produced by signal injections can be optimized. The approach is implemented in a field-oriented control for permanent magnet synchronous machines and is verified in experiments.
Autors: Marco Roetzer;Ulrich Vollmer;Ralph M. Kennel;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 732 - 744
Publisher: IEEE
 
» Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers
Abstract:
Biometrics is the technique of automatically recognizing individuals based on their biological or behavioral characteristics. Various biometric traits have been introduced and widely investigated, including fingerprint, iris, face, voice, palmprint, gait and so forth. Apart from identity, biometric data may convey various other personal information, covering affect, age, gender, race, accent, handedness, height, weight, etc. Among these, analysis of demographics (age, gender, and race) has received tremendous attention owing to its wide real-world applications, with significant efforts devoted and great progress achieved. This survey first presents biometric demographic analysis from the standpoint of human perception, then provides a comprehensive overview of state-of-the-art advances in automated estimation from both academia and industry. Despite these advances, a number of challenging issues continue to inhibit its full potential. We second discuss these open problems, and finally provide an outlook into the future of this very active field of research by sharing some promising opportunities.
Autors: Yunlian Sun;Man Zhang;Zhenan Sun;Tieniu Tan;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 332 - 351
Publisher: IEEE
 
» Demonstrating the Ultrathin Metal–Insulator– Metal Diode Using TiN/ZrO2–Al2O3–ZrO2 Stack by Employing RuO2 Top Electrode
Abstract:
Metal–insulator–metal (MIM) diodes with ultrathin insulators are highly promising for a variety of applications, such as vertical integration technology. However, MIM diodes with thin enough structures have not been achieved in previous studies on diodes using Schottky emission or tunneling conduction asymmetry. In this paper, we demonstrate an MIM diode with an ultrathin, 5-nm ZrO2/Al2O3/ZrO2 insulator, using the work-function difference between the top and bottom electrodes. The rectifying properties of the diode were enhanced by employing RuO2 as an electrode, due to its high work function and the catalytic effect on oxygen decomposition, contributing to the suppression of trap-assisted tunneling. This paper presents an important development in understanding MIM structures with respect to the electrical and chemical properties.
Autors: Woojin Jeon;Youngjin Kim;Cheol Hyun An;Cheol Seong Hwang;Patrice Gonon;Christophe Vallée;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 660 - 666
Publisher: IEEE
 
» Demonstration of a Curable Nanowire FinFET Using Punchthrough Current to Repair Hot-Carrier Damage
Abstract:
Device degradation caused by gate oxide damage in a FinFET on silicon-on-insulator is recovered using punchthrough current via a silicon fin. As the high level of drain current flows under a punchthrough mode, localized Joule heat driven by drain current, enough to anneal the gate oxide, is induced in the channel. This selectively cured localized damage in the FinFET. The dependence of recovery on the gate length, substrate material underneath the channel, and the proper range of annealing voltage are investigated.
Autors: Jun-Young Park;Jae Hur;Yang-Kyu Choi;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 180 - 183
Publisher: IEEE
 
» Demonstration of a Microfiber-Based Add–Drop Filter Using One Tapered Fiber
Abstract:
We propose a novel approach to demonstrate an add–drop filter based on microfiber knot resonator (MFKR). The two coupled regions and four ports (including input port, through port, drop port, and add port) of this device are formed using the same one microfiber. By reconnecting the ends of the through and add ports with other two microfibers, this structure could serve as an add–drop filter, which is a key building block in the fields of optical networks and optical information processing system. The MFKR-based add–drop filter with the quality factor (Q-factor) of 21 000 and a diameter of 740 μm is demonstrated successfully. The intrinsic loss and extinction ratio are about –2 and 18.5 dB for the drop port, and –4.6 and 10.7 dB for the through port, respectively. The fabrication process also shows the feasibility and simplicity of this device.
Autors: Lin Deng;Xiaonan Guo;Yinghao Meng;Ting Zhao;Zilong Liu;Huifu Xiao;Guipeng Liu;Yonghui Tian;Jianhong Yang;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 6
Publisher: IEEE
 
» Demonstration of GaN Current Aperture Vertical Electron Transistors With Aperture Region Formed by Ion Implantation
Abstract:
In this paper, we report the successful demonstration of current aperture vertical electron transistors (CAVETs) obtained by using a novel implantation-based compensation method to achieve a conductive aperture. This innovation leads to the first demonstration of “regrowth-free” CAVETs. Two gallium nitride (GaN) CAVETs were fabricated using the ion-implantation-compensated aperture regions, both with Mg-doped p-GaN as current-blocking layers (CBLs). The aperture regions were formed by implanting Si into the p-GaN CBL. In one of the CAVET samples, the Si-implantation-based aperture was formed prior to the regrowth of AlGaN/GaN layers on top. The other CAVET sample was subjected to aperture formation via Si implantation after all the device layers were grown. An ion-implantation scheme using multiple-energy levels was designed to realize a 250-nm Si box profile with a total dose of cm−2, converting a 250-nm p-GaN (Mg: cm−2) to conductive (n-type) GaN successfully. This novel fabrication method enables the use of Mg-doped CBLs without conventional etch and regrowth steps. Moreover, the proposed scheme can ultimately lead to regrowth-free CAVETs.
Autors: Dong Ji;Anchal Agarwal;Wenwen Li;Stacia Keller;Srabanti Chowdhury;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 483 - 487
Publisher: IEEE
 
» Dense Invariant Feature-Based Support Vector Ranking for Cross-Camera Person Reidentification
Abstract:
Recently, support vector ranking (SVR) has been adopted to address the challenging person reidentification problem. However, the ranking model based on ordinary global features cannot well represent the significant variation of pose and viewpoint across camera views. To address this issue, a novel ranking method that fuses the dense invariant features (DIFs) is proposed in this paper to model the variation of images across camera views. An optimal space for ranking is learned by simultaneously maximizing the margin and minimizing the error on the fused features. The proposed method significantly outperforms the original SVR algorithm due to the invariance of the DIFs, the fusion of the bidirectional features, and the adaptive adjustment of parameters. Experimental results demonstrate that the proposed method is competitive with state-of-the-art methods on two challenging data sets, showing its potential for real-world person reidentification.
Autors: Shoubiao Tan;Feng Zheng;Li Liu;Jungong Han;Ling Shao;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Feb 2018, volume: 28, issue:2, pages: 356 - 363
Publisher: IEEE
 
» Deploying Software Team Analytics in a Multinational Organization
Abstract:
Implementing a software engineering analytics solution poses challenges and offers significant value for the globally distributed software development organization at ABB. Because software development activities in agile methodologies revolve around the team, ABB decided to implement an analytics solution focused on team metrics as part of its Software Development Improvement Program. Using key indicators focused around team improvement, researchers found that teams could manage their activities with metrics such as cycle time. Key lessons learned include paying attention to visual design and navigation and providing drill-down capabilities for the user. This article is part of a special issue on Actionable Analytics for Software Engineering.
Autors: Vinay Augustine;John Hudepohl;Przemyslaw Marcinczak;Will Snipes;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 72 - 76
Publisher: IEEE
 
» Deshadowing of Urban Airborne Imagery Based on Object-Oriented Automatic Shadow Detection and Regional Matching Compensation
Abstract:
With the increase of the spatial resolution of aerial images, the shadow problem is more prominent. The shadows affect the applications such as object recognition, image dense matching, and object classification. Existing shadow detection methods can acquire results with high accuracy, but usually need much manual intervention and the traditional stretch models generally lead to color distortion and undercompensation. Therefore, we propose an object-oriented automatic shadow detection method without manual intervention and a shadow compensation method by regional matching. In the proposed method, pixel-based soft shadow detection, which uses Gaussian mixture model to simulate the gray distribution and refines soft shadow map with guiled filtering, is combined with image segmentation result to obtain accurate shadow regions with complete shape and no hole. Then shadow regions are compensated, with less loss of details and brightness imbalance, referring to their optimal homogeneous nonshadow region obtained by regional matching based on Bag-of-Words. The total variation model is used to decrease the noise amplified by the pixel-based stretch and boundary effect in the result. Experiments are performed on three publicly available high-resolution aerial images to demonstrate the superiority of our proposed methods. It shows that the proposed method can accurately detect shadows from urban high-resolution aerial images with an overall rate of over 88%. The compensation results display excellent visual effects compared with the state-of-the-art methods, consistent with the true color of ground objects.
Autors: Nan Mo;Ruixi Zhu;Li Yan;Zhan Zhao;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 585 - 605
Publisher: IEEE
 
» Design and Analysis of a Flux Reversal Machine With Evenly Distributed Permanent Magnets
Abstract:
In this paper, a flux reversal machine (FRM), which has a larger torque density and a smoother torque waveform than the conventional FRM, is introduced. The FRM has the same combinations of stator and rotor slots, winding pole pair, and permanent magnet (PM) usage as the conventional FRM, but has different PM arrangements, i.e., in the conventional FRM, a pair of PMs is mounted on the surface of each stator teeth while the PMs of the FRM introduced in this paper are evenly distributed along the inner surface of the stator. First, the origination from the conventional FRM to the proposed FRM is introduced. Then, the effects of the rotor slot number, split ratio, stator/rotor slot opening ratio, PM thickness, and pole arc on the average torque and cogging torque are investigated and analyzed, which give a reasonable prediction for maximum achievable power density and minimum possible cogging torque of the proposed FRM. Moreover, the proposed FRM is compared with a conventional FRM in terms of back electromotive force, rated torque, pulsating torque, power factor, and overload capabilities. Finally, a 12-stator-slot/17-rotor-slot FRM prototype is built to verify the theoretical analyses.
Autors: Dawei Li;Yuting Gao;Ronghai Qu;Jian Li;Yongsheng Huo;Han Ding;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 172 - 183
Publisher: IEEE
 
» Design and Analysis of Relay-Selection Strategies for Two-Way Relay Network-Coded DCSK Systems
Abstract:
This paper investigates a two-way two-relay network-coded differential-chaos-shift-keying (DCSK) system over multipath Rayleigh fading channels. First, a decode-and-forward protocol is considered, when the two relays first decode the two users’ orthogonal transmitted signals and then forward their XORed version back to the users. Based on the equal-gain-combining method at the receiver of each user, the bit-error-rate (BER), achievable diversity order, and throughput are analyzed. It is shown that, as compared to the conventional two-way one-relay network-coded DCSK system, the proposed system achieves lower BER, but reduces the throughput meanwhile. To improve the overall performance and avoid the throughput loss, a novel relay-selection criterion is developed based on the decision metrics used for conventional symbol detection, which can be implemented without requiring the channel state information. According to the criterion, three relay-selection strategies are suggested, namely the max-sum, max-product and max–min relay selections. Both analytical and simulated results show that the proposed relay-selection strategies significantly improve the BER and throughput of the two-way two-relay network-coded DCSK system and achieve higher diversity order. As a further insight, the superiority of the proposed relay-selection strategies is demonstrated in multirelay scenarios. Overall, the proposed system stands out as a promising candidate for low-power and low-complexity short-range wireless-communication applications, such as wireless sensor networks.
Autors: Guofa Cai;Yi Fang;Guojun Han;Jie Xu;Guanrong Chen;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1258 - 1271
Publisher: IEEE
 
» Design and Characterization of a Low-Cost FPGA-Based TDC
Abstract:
We present a field-programmable gate array (FPGA) implementation of a time-to-digital converter (TDC) based on a low-cost, low-area Spartan 6 device. The converter is based on a tapped delay line model. Several implementation details are discussed with a particular focus on critical blocks such as the input stage and thermometer-to-binary decoding techniques. We implemented a tap filtering technique to improve the differential nonlinearity (DNL) of the single delay line while keeping a good LSB value of 25.57 ps with a single-shot precision (SSP) between LSB. Measured DNL and integral nonlinearity (INL) lie in the range between and LSB, respectively. Measured DNL and INL lie in the range between and LSB, respectively. We then implemented an interpolating TDC to overcome the limitations of a single delay line in terms of linearity and measurement range. The interpolating TDC uses the sliding scale technique, where the time interval to be measured is asynchronous with respect to the FPGA clock, achieving DNL and INL in the range and LSB. SSP is in the range. Moreover, we present a novel comparison between the DNLs obtained with two different methods: statistical code density test and using a finely controlled delay source. Finally, we present the results of- a Monte Carlo simulation used to investigate the effects of nonlinear propagation of the signal through the delay line.
Autors: Alessandro Tontini;Leonardo Gasparini;Lucio Pancheri;Roberto Passerone;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 680 - 690
Publisher: IEEE
 
» Design and Control of a Dual-Probe Atomic Force Microscope
Abstract:
Current atomic force microscopes (AFMs) support single-probe operation, in which one nanosized tip enables versatile operations such as surface imaging, nanomanipulation, and nanomanufacturing to be performed, although one at a time. Some AFM operations involve switching between imaging and the operational mode, which is cumbersome, challenging, and limiting, particularly when different probe geometries are preferred for each mode. This paper presents a new dual-probe atomic force microscope (DP-AFM) that has two independent probes operating in a common workspace. Such a setup enables two AFM operations to be carried out simultaneously. For instance, one probe can be used to image, while the other probe performs one of the many tip-based processes. The hardware and software design involved in developing the DP-AFM is discussed in detail. Furthermore, to demonstrate the capability of dual-probe arrangement, a controller is developed for real-time plowing depth control, where one probe is used to plow the surface, while the other is used to image the plow profile, thus enabling real-time feedback control of the AFM plow process. Experimental results show that the plow depth can be regulated with nanometer-level accuracy.
Autors: Muthukumaran Loganathan;Ayad Al-Ogaidi;Douglas A. Bristow;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 424 - 433
Publisher: IEEE
 
» Design and Evaluation of Nonlinear Verification Device for Nonlinear Vector Network Analyzers
Abstract:
A simple diode-based nonlinear verification device (NVD) design for nonlinear vector network analyzers is presented together with an improved figure of merit (FOM) parameter that is insensitive to impedance match and isolates variation of the device’s nonlinear parameters. The stability over 84 h and load–pull performance of this new design have been evaluated.
Autors: Mohammad Rajabi;David A. Humphreys;Gustavo Avolio;Paweł Barmuta;Konstanty R. Łukasik;Troels S. Nielsen;Dominique M. M.-P. Schreurs;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 1121 - 1130
Publisher: IEEE
 
» Design and Experimental Verification of Hip Exoskeleton With Balance Capacities for Walking Assistance
Abstract:
Most current hip exoskeletons emphasize assistance for walking rather than stability. The goal of this paper is to develop a novel, high-power, self-balancing, and passively and software-controlled actively compliant hip exoskeleton that can assist with movement and maintain balance in both the sagittal and frontal planes. The developed hip exoskeleton includes powered hip abduction/adduction and hip flexion/extension joints. Each actuation unit employs a modular and compact series elastic actuator (SEA) with a high torque-to-weight ratio. It provides mechanical compliance at the interface between the exoskeleton and the wearer to ensure safety and a natural gait in the coupled wearer-exoskeleton system. A new balance controller based on the extrapolated center of mass concept is presented for maintaining walking stability. This controller reacts to perturbations in balance and produces a compliant guidance force through a combination of the passive elasticity of the SEA and active compliant control based on adaptive admittance control. The function of the hip exoskeleton is not to override human control, but rather to involve the wearer in movement control in order to avoid conflicts between wearer and exoskeleton. Our preliminary experiments on a healthy subject wearing the hip exoskeleton demonstrate the potential effectiveness of the proposed hip exoskeleton and controller for walking balance control.
Autors: Ting Zhang;Minh Tran;He Huang;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 274 - 285
Publisher: IEEE
 
» Design and Fabrication of a Novel Force Sensor for Robot Grippers
Abstract:
Force sensors using strain gauge have been widely applied in mechanical systems. They usually possess a structure consisting of a simple cantilever beam and two strain gauges attached to two opposite beam surfaces. However, this structure shows severely distorted stress in the implementation of smart robot grippers with lateral offsets, which is usual in limited-space applications. In order to overcome the limitation and to reduce the nonlinearity of the gauge sensor, a novel hinged-joint cantilever beam sensor structure is proposed. An analytical model is derived to predict the force sensitivity and force linearity. The simple cantilever beam sensor and the hinged-joint sensor are analyzed and compared with the conducting finite-element-method simulation. Signal processing circuits are designed and implemented. A hinged-joint prototype force sensor is fabricated for calibration and testing. Experiments show that the proposed hinged-joint sensor possesses a high quality of linearity and excellent sensitivity, which can be applied to diverse fields including smart robot grippers.
Autors: Lisheng Kuang;Yunjiang Lou;Shuang Song;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1410 - 1418
Publisher: IEEE
 
» Design and Implementation of Fourth Arm for Elimination of Bearing Current in NPC-MLI-Fed Induction Motor Drive
Abstract:
The exploration result of an increase in power electronics converter-based variable-speed drives for industrial applications reveals the impact of inverter-induced bearing current on the prevailing electric machine failure. The bearing current associated with drive systems is concerned about operating frequencies of the solid-state semiconductor switches, which may cause the electrostatic charge between stator and rotor, which eventually causes damage to windings and bearings. The various techniques comprised in the literature to suppress bearing currents are filter design, switching redundancy, common-mode circuitry, isolated grounding scheme, and grounding the motor shaft. From the literature, the pulse-width modulation inverter-injected common-mode voltage (CMV) is the main source of common-mode current, which causes the bearing current. Hence, the elimination of CMV paves the way for eliminating bearing current of the machine. This paper presents an innovative solution to suppress bearing currents by aiding a fourth arm circuitry to acquire near to zero potential (zero CMV) at machine neutral point. All the proposed circuitry and algorithm are simulated using MATLAB/Simulink and validation is done through a 2.5-kW neutral-point-clamped-multilevel inverter laboratory prototype using a Xilinx family SPARTAN-III-3A XC3SD1800A-FG676 digital signal processor-field programmable gate array board.
Autors: C. Bharatiraja;Raghu Selvaraj;Thanga Raj Chelliah;Josiah L. Munda;Mohd Tariq;Ali I. Maswood;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 745 - 754
Publisher: IEEE
 
» Design and Implementation of Low Complexity 2-D Variable Digital FIR Filters Using Single-Parameter-Tunable 2-D Farrow Structure
Abstract:
In this paper, a novel single-parameter-tunable 2-D Farrow structure is proposed and used for implementing linear phase 2-D variable digital filters (VDFs) with tunable spectral characteristics. Real-time tunability in the spectral characteristics of the 2-D filter is achieved by varying a single tunable parameter in a fixed hardware structure. The proposed structure enables the realization of multiple 2-D filters from a single structure with minimum error and hardware complexity. The reduction in the hardware complexity becomes pronounced when the number of 2-D filters included in the 2-D VDF increases. The proposed structure is capable of efficiently realizing circularly symmetric and fan-type variable 2-D filters, which is demonstrated using different design examples. Results show that the proposed approach ensures up to 60% reduction in the hardware complexity when compared with the state-of-the-art approaches used for the design and implementation of 2-D VDFs. The proposed approach ensures a drastic reduction in the hardware complexity without sacrificing the accuracy with a normalized root mean square error less than 0.5%.
Autors: T. Bindima;Elizabeth Elias;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 618 - 627
Publisher: IEEE
 
» Design and Implementation of LTE RRM With Switched LWA Policies
Abstract:
LTE-WLAN aggregation (LWA) combines the radio resources of LTE and WLAN, which takes the advantage of Wi-Fi's high availability and indoor coverage to provide better usage of both WLAN and LTE. In this mechanism, it is essential that the network should intelligently switch a data radio bearer (DRB) to utilize either LTE or Wi-Fi. This paper implements the radio resource management layer (RRM) for LWA and proposes two types of the switched LWA policies: the guaranteed bandwidth and the equal sharing policies. We measure the delay times of the LWA procedures, which indicate that the switched LWA policies can be implemented at the RRM with negligible overhead. We conduct emulation, simulation, and analytic analysis to evaluate the performance of the switched LWA policies. The beauty of the LWA policies is that the performance is not affected by the DRB holding time distribution. Our study indicates that switched LWA can effectively reduce the blocking probability of the LWA's DRBs.
Autors: Yi-Bing Lin;Ying-Ju Shih;Pei-Wen Chao;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1053 - 1062
Publisher: IEEE
 
» Design and Performance Analysis of Three-Phase Solar PV Integrated UPQC
Abstract:
This paper deals with the design and performance analysis of a three-phase single stage solar photovoltaic integrated unified power quality conditioner (PV-UPQC). The PV-UPQC consists of a shunt and series-connected voltage compensators connected back-to-back with common dc-link. The shunt compensator performs the dual function of extracting power from PV array apart from compensating for load current harmonics. An improved synchronous reference frame control based on moving average filter is used for extraction of load active current component for improved performance of the PV-UPQC. The series compensator compensates for the grid side power quality problems such as grid voltage sags/swells. The compensator injects voltage in-phase/out of phase with point of common coupling (PCC) voltage during sag and swell conditions, respectively. The proposed system combines both the benefits of clean energy generation along with improving power quality. The steady state and dynamic performance of the system are evaluated by simulating in MATLAB-Simulink under a nonlinear load. The system performance is then verified using a scaled down laboratory prototype under a number of disturbances such as load unbalancing, PCC voltage sags/swells, and irradiation variation.
Autors: Sachin Devassy;Bhim Singh;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 73 - 81
Publisher: IEEE
 
» Design and Tuning of Robust Fractional Order Controller for Autonomous Microgrid VSC System
Abstract:
A robust controller design for the voltage control of an autonomous three-phase voltage source converter (VSC) is proposed. As compared with the conventional proportional plus integral (PI) controllers, fractional order controllers make the VSC system robust due to their fractional characteristics. The fractional PI controller has an additional degree of freedom along with and gains of the conventional PI controller. Detailed modeling of a VSC is used in the controller design process so as it include inner current control and filter dynamics. The outer fractional voltage controller is designed such that the VSC system satisfies a required phase margin, with improved robustness in the system and capability to attenuate the noise. The overall system stability is analyzed using both bode plot and step response, and these responses are compared with a conventional PI controller. Further, the dynamic performance of the fractional controller is evaluated by simulating the nonlinear system. A hardware prototype is also developed to demonstrate the practical realization of the controller.
Autors: Deepak Pullaguram;Sukumar Mishra;Nilanjan Senroy;Monish Mukherjee;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 91 - 101
Publisher: IEEE
 
» Design Methodology for Constructing Multimaterial Origami Robots and Machines
Abstract:
Robotic origami allows rapid prototyping of intelligent robots and machines constructed from thin sheets of functional materials. Multimaterial-based design freedom of origami robots creates functional versatility; however, the design parameters pose challenges in their mechanical layout and fabrication. While the conventional robot design follows a coherent and well-established design process, the construction of origami robots requires close study of their three-dimensional (3-D) and two-dimensional (2-D) geometries, compliant mechanisms, functional material specific components, and 2-D fabrication methods. In this paper, we report a systematic design methodology for building origami-inspired machines and robots based on these four essential design features. We provide their comprehensive formulation, comparing them to conventional robots and highlighting design challenges as well as potentials. We demonstrate the applicability of our procedure to the majority of origami robots in the literature and also validate it by designing a centimeter-scale jumping and crawling origami robot, Tribot, as a showcase. The 6-g Tribot crawls with fixed steps in a closed loop, adjusts its vertical jumping height by power modulation, and overcomes obstacles of 45-mm height by side jumps. This paper advances the design and fabrication methodology of origami robots, with customizable functionality from the ground-up.
Autors: Zhenishbek Zhakypov;Jamie Paik;
Appeared in: IEEE Transactions on Robotics
Publication date: Feb 2018, volume: 34, issue:1, pages: 151 - 165
Publisher: IEEE
 
» Design of 5G Full Dimension Massive MIMO Systems
Abstract:
This paper discusses full-dimension multiple-input-multiple-output (FD-MIMO) technology, which is currently an active area of research and standardization in wireless communications for evolution toward Fifth Generation (5G) cellular systems. FD-MIMO utilizes an active antenna system (AAS) with a 2-D planar array structure that not only allows a large number of antenna elements to be packed within feasible base station form factors, but also provides the ability of adaptive electronic beamforming in the 3-D space. However, the compact structure of large-scale planar arrays drastically increases the spatial correlation in FD-MIMO systems. In order to account for its effects, the generalized spatial correlation functions for channels constituted by individual elements and overall antenna ports in the AAS are derived. Exploiting the quasi-static channel covariance matrices of users, the problem of determining the optimal downtilt weight vector for antenna ports, which maximizes the minimum signal-to-interference ratio of a multi-user multiple-input-single-output system, is formulated as a fractional optimization problem. A quasi-optimal solution is obtained through the application of semi-definite relaxation and Dinkelbach’s method. Finally, the user-group specific elevation beamforming scenario is devised, which offers significant performance gains as confirmed through simulations. These results have direct application in the analysis of 5G FD-MIMO systems.
Autors: Qurrat-Ul-Ain Nadeem;Abla Kammoun;Mérouane Debbah;Mohamed-Slim Alouini;
Appeared in: IEEE Transactions on Communications
Publication date: Feb 2018, volume: 66, issue:2, pages: 726 - 740
Publisher: IEEE
 
» Design of 600-W Low-Loss Ultra-Wideband Ferriteless Balun
Abstract:
We present the development of a low-loss, high-power, and ferriteless balun that operates over 0.1–1.6 GHz bandwidth. The proposed balun employs a novel compensated circuit, a single quarter-wave semirigid coaxial cable and an on-board inductor on a thermoset ceramic board to achieve high power and ultrawide bandwidth performance. The experimental results show that the balun achieves a measured average insertion loss of less than 0.5 dB and return loss of better than 10 dB from 100 MHz to more than 1.6 GHz. Within the measured bandwidth, the amplitude and phase imbalances are within ±1 dB and ±5°, respectively. Multiphysics analysis and high-power measurements demonstrate that the balun can handle more than 600 W and above at 1.6 GHz. To the best of our knowledge, the reported balun has the highest measured power handling capability per the largest 16:1 bandwidth ratio to date.
Autors: Chi Van Pham;Anh-Vu Pham;Robert E. Leoni;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 902 - 910
Publisher: IEEE
 
» Design of a Photo-Excited Switchable Broadband Reflective Linear Polarization Conversion Metasurface for Terahertz Waves
Abstract:
We present a photo-excited switchable broadband reflective linear polarization conversion metasurface for terahertz waves. The unit-cell structure of the switchable polarization conversion metasurface is composed of metallic disk and split-ring resonator (together named as DSRR) integrated with semiconductor photoconductive silicon (Si) placed over the continuous films. The electric response of the photoconductive Si filled in the gap of the DSRR can be tunable through a pump beam with different optical power. The simulation results indicate that the polarization conversion ratio (PCR) of the compound metasurface without pump beam is greater than 80% in the frequency range of 0.65–1.58 THz, and the PCR is up to 99% at resonances frequencies of 0.69 THz, 1.01 THz and 1.42 THz, respectively. The numerical simulation results are in good agreement with the theoretical predictions based on the interference theory. Furthermore, the broadband PCR can be tunable continuously with the changes of Si conductivity by adjusting the pump optical power. Moreover, the surface current distributions of the unit-cell structure with different Si conductivity at the resonance frequency are discussed to illustrate its physics mechanism. Thus, our design can find potential applications in many areas, such as remote sensors, reflector antennas, and radiometers in terahertz region.
Autors: Jingcheng Zhao;Yongzhi Cheng;Zhengze Cheng;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 10
Publisher: IEEE
 
» Design of Broadband High-Efficiency Power Amplifiers Based on the Hybrid Continuous Modes With Phase Shift Parameter
Abstract:
The hybrid continuous modes are constituted by a continuum of power amplifier (PA) modes between class-J and continuous class-F. In this letter, a phase shift parameter is introduced in the voltage waveform formula of the hybrid continuous modes to generate complex fundamental and harmonic load impedances, leading to a further extension on the operation bandwidth. Based on the proposed theory, a gallium nitride PA is designed and fabricated over the frequency band of 1.2–3.6 GHz. The measured results show a 60%–72% drain efficiency at a saturated power of 40–42.2 dBm. In addition, when driven by a 20-MHz long-term evolution signal with a peak-to-average power ratio of 7.4 dB, the proposed PA obtains an adjacent channel leakage ratio of −35 dBc at an average output power of 35 dBm at 2.3 GHz.
Autors: Chaoyi Huang;Songbai He;Weimin Shi;Bin Song;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 159 - 161
Publisher: IEEE
 
» Design of Capacity-Approaching Constrained Codes for DNA-Based Storage Systems
Abstract:
We consider coding techniques that limit the lengths of homopolymer runs in strands of nucleotides used in DNA-based mass data storage systems. We compute the maximum number of user bits that can be stored per nucleotide when a maximum homopolymer runlength constraint is imposed. We describe simple and efficient implementations of coding techniques that avoid the occurrence of long homopolymers, and the rates of the constructed codes are close to the theoretical maximum. The proposed sequence replacement method for -constrained -ary data yields a significant improvement in coding redundancy than the prior art sequence replacement method for the -constrained binary data. Using a simple transformation, standard binary maximum runlength limited sequences can be transformed into maximum runlength limited -ary sequences which opens the door to applying the vast prior art binary code constructions to DNA-based storage.
Autors: Kees A. Schouhamer Immink;Kui Cai;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 224 - 227
Publisher: IEEE
 
» Design of Chipless RFID Tag by Using Miniaturized Open-Loop Resonators
Abstract:
In this paper, an open-loop resonator with fragment-loading structure is used for the first time in the design of radar cross section-based chipless radio-frequency identification (RFID) tag. By optimizing the distribution of fragment patches in an open loop, a microstrip open-loop resonator can be miniaturized so that the data capacity of the chipless RFID tag designed using such a miniaturized loop resonator can be significantly increased. Moreover, the resonant frequency of the fragment-loaded resonator can be adjusted conveniently by removing or disconnecting some fragment patches, which provides great flexibility for data encoding of the chipless RFID tag. The proposed chipless RFID tag with miniaturized open-loop resonators is designed and tested and can acquire 3.56 bits per resonator and a coding density of approximately . Several experimental results validate the proposed design as well as its implementation in a realistic environment.
Autors: Lu Wang;Ting Liu;Johan Sidén;Gang Wang;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 618 - 626
Publisher: IEEE
 
» Design of Dual-Band High-Efficiency Power Amplifiers Based on Compact Broadband Matching Networks
Abstract:
This letter reports a novel synthesis method to design an extended dual-band power amplifier (PA). The proposed matching networks exhibit dual-band impedance rotation, leading the transistor to yield flat gain at the two designed passbands and suppressed gain responses at frequencies outsides the passbands. The fabricated PA represents a competitive solution in multiband and multimode applications as compared with the conventional dual-band PA based on the multifrequency techniques. The transistor CGH40010F from Cree is employed for verification. At 1.4 and 2.4 GHz, the bandwidth has been extended over 150 MHz at each individual passband. The implemented PA can deliver the saturated output power of 10 W minimum, and power-added efficiency of 65% minimum has been measured.
Autors: Xiangyu Meng;Cuiping Yu;Yongle Wu;Yuanan Liu;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 162 - 164
Publisher: IEEE
 
» Design of Fragment-Type Antenna Structure Using an Improved BPSO
Abstract:
An improved binary particle swarm optimization (BPSO) algorithm is proposed for the design of high-dimensional, multifunctional, and compact fragment-type antenna (FTA). First, orthogonal array-based initialization instead of randomized initialization is employed to uniformly sample the design space for better population diversity. Then, a new transfer function with a time-variant transfer factor is proposed to improve the problem of easily falling into local optimum in basic BPSO. Experimental results of the two miniaturized FTA designs show that the proposed BPSO exhibits better convergence performance than that of other published discrete optimization algorithms and can provide excellent candidates for the internal miniaturized antenna designs in wireless and portable applications.
Autors: Jian Dong;Qianqian Li;Lianwen Deng;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 564 - 571
Publisher: IEEE
 
» Design of global submarine networks
Abstract:
System design issues introduced by different ownership models in undersea fiber-optic transmission systems are discussed, including design elements related to the overall cable, the individual fiber pairs, and the separate optical add-drop multiplexing bands.
Autors: Lara D. Garrett;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A185 - A195
Publisher: IEEE
 
» Design of Multioctave High-Efficiency Power Amplifiers Using Stochastic Reduced Order Models
Abstract:
This paper presents a novel general design method of frequency varying impedance matching. The method is applied to design of a broadband high-efficiency power amplifier (PA). The proposed method defines the optimal impedance regions of a PA at several frequency sections over the operational frequency band. These regions contain the impedances that can achieve a high output power and a high-power added efficiency (PAE) simultaneously. A low-pass -ladder circuit is selected as the matching network (MN). The element values of the MN can be obtained using a synthesizing method based on stochastic reduced order models and Voronoi partition. The MN provides desired impedance in the predefined optimal impedance region at each frequency section. Thus, optimal output power and PAE of the PA can be achieved. To validate the proposed method, two eighth-order low-pass -ladder networks are designed as the input and output MNs, respectively. A gallium nitride (GaN) HEMT from Cree is employed as the active device. Packaging parasitic of the transistor has been taken into account. A PA is designed, fabricated, and measured. The measurement results show that the PA can achieve P1 dB PAE of better than 60% over a fractional bandwidth of 160% (0.2–1.8 GHz). The output power is 42–45 dBm (16–32 W), and the gain is 12–15 dB. The performance of the PA outperforms existing broadband high-efficiency PAs in many aspects, which demonstrates the excellence of the proposed method.
Autors: Yuan Zhuang;Zhouxiang Fei;Anqi Chen;Yi Huang;Khondker Rabbi;Jiafeng Zhou;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 1015 - 1023
Publisher: IEEE
 
» Design of Planar High-Gain Antenna Using SIW Cavity Hybrid Mode
Abstract:
In this communication, a planar high-gain slot antenna backed by a rectangular substrate-integrated waveguide (SIW) cavity is presented. The proposed antenna uses a narrow rectangular SIW cavity with high length-to-width ratio. This modifies the conventional sinusoidal field distribution of the cavity modes to generate a hybrid mode field distribution with more field concentration at the center of the cavity. A closed form expression is presented which represents the proposed hybrid mode field distribution as a summation of multiple TEym10 cavity modes. A slot antenna placed at the top plate of the proposed cavity is excited by the hybrid mode. Calculation of far-field radiation pattern of the proposed antenna is presented, which exhibits its potential to produce narrower main beam along with high gain. To validate the concept, a prototype is fabricated in a thin substrate (). The experimental result shows antenna resonance at 9.5 GHz with high gain of 9.62 dBi.
Autors: Soumava Mukherjee;Animesh Biswas;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 972 - 977
Publisher: IEEE
 
» Design Optimization of a High-Speed Synchronous Reluctance Machine
Abstract:
Synchronous reluctance machines, including the permanent-magnet-assisted variants, are competitive motor topologies if the application requires high efficiency and a cost-effective solution with a high flux-weakening capability. However, increasing operating speeds incur challenging design and development decisions, mainly in order to find design solutions that ensure the machine's structural integrity without compromising the overall performance. In this paper, a comprehensive design procedure for high-speed synchronous reluctance machines is presented. In order to validate the procedure, a 5-kW 80 000-r/min machine is considered. The proposed strategy consists of a two-step procedure in which the electromagnetic and structural designs have been properly decoupled, dividing the design space in two subsets. Each subset mainly affects the electromagnetic or the structural performances. Several structural design optimizations have been then performed with the aim of finding the optimal tradeoff between the rotor geometrical complexity (that defines the required computational resources) and the electromagnetic performance. The reported experimental tests of the prototyped machine validate the proposed design strategy, which can be used as general guidelines on the structural design of synchronous reluctance machines.
Autors: Mauro Di Nardo;Giovanni Lo Calzo;Michael Galea;Chris Gerada;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 233 - 243
Publisher: IEEE
 
» Design-Phase Buffer Allocation for Post-Silicon Clock Binning by Iterative Learning
Abstract:
At submicrometer manufacturing technology nodes, process variations affect circuit performance significantly. To counter these variations, engineers are reserving more timing margin to maintain yield, leading to an unaffordable overdesign. Most of these margins, however, are wasted after manufacturing, because process variations cause only some chips to be really slow, while other chips can easily meet given timing specifications. To reduce this pessimism, we can reserve less timing margin and tune failed chips after manufacturing with clock buffers to make them meet timing specifications. With this post-silicon clock tuning, critical paths can be balanced with neighboring paths in each chip specifically to counter the effect of process variations. Consequently, chips with timing failures can be rescued and the yield can thus be improved. This is specially useful in high-performance designs, e.g., high-end CPUs, where clock binning makes chips with higher performance much more profitable. In this paper, we propose a method to determine where to insert post-silicon tuning buffers during the design phase to improve the overall profit with clock binning. This method learns the buffer locations with a Sobol sequence iteratively and reduces the buffer ranges afterward with tuning concentration and buffer grouping. Experimental results demonstrate that the proposed method can achieve a profit improvement of about 14% on average and up to 26%, with only a small number of tuning buffers inserted into the circuit.
Autors: Grace Li Zhang;Bing Li;Jinglan Liu;Yiyu Shi;Ulf Schlichtmann;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Feb 2018, volume: 37, issue:2, pages: 392 - 405
Publisher: IEEE
 
» Designing Energy-Efficient Intermittently Powered Systems Using Spin-Hall-Effect-Based Nonvolatile SRAM
Abstract:
Intermittently powered systems represent a new class of batteryless devices that operate solely on energy harvested from their environment. Due to the unreliable nature of ambient energy sources, these devices experience frequent intervals of power loss, leading to sudden reboots. Tolerating such power supply disruptions require the ability to rapidly checkpoint/save system state when power loss is imminent and restore it at the start of the next power cycle to continue computations in a seamless manner. A typical microcontroller used in these systems consists of a fast nonvolatile SRAM and a nonvolatile Flash storage. Prior work has shown how emerging nonvolatile memory technologies such as STT-MRAM can improve the energy efficiency of these systems, either by using STT-MRAM as a drop-in replacement for Flash (henceforth referred to as the SRAM+STT-MRAM memory configuration) or using STT-MRAM as unified memory (henceforth referred to as the unified STT-MRAM memory configuration). However, both these configurations have significant drawbacks. Using the SRAM+STT−MRAM configuration leads to high checkpointing overhead due to the inefficient write operations of STT-MRAM whereas using the unified STT-MRAM configuration is inefficient due to executing every program instruction directly from STT-MRAM. This paper proposes a novel Spin Hall Effect-based nonvolatile-SRAM (SNVRAM) bit-cell that combines the nonvolatility of spin devices with the speed and energy efficiency of conventional 6T SRAM cells. We explore the use of the proposed SNVRAM to replace the SRAM in a transiently powered system to mitigate the drawbacks of the aforementioned memory configurations. Simulation results using a set of evaluation benchmarks demonstrate that the SNVRAM+STT−MRAM configuration leads to significant memory energy benefits of and on average, compared to the SRAM+STT−MRAM and unified STT-MRAM memory configurations, respectively.
Autors: Arnab Raha;Akhilesh Jaiswal;Syed Shakib Sarwar;Hrishikesh Jayakumar;Vijay Raghunathan;Kaushik Roy;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Feb 2018, volume: 26, issue:2, pages: 294 - 307
Publisher: IEEE
 
» Detecting Essential Proteins Based on Network Topology, Gene Expression Data, and Gene Ontology Information
Abstract:
The identification of essential proteins in protein-protein interaction (PPI) networks is of great significance for understanding cellular processes. With the increasing availability of large-scale PPI data, numerous centrality measures based on network topology have been proposed to detect essential proteins from PPI networks. However, most of the current approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology annotation information. In this paper, we propose a novel centrality measure, called TEO, for identifying essential proteins by combining network topology, gene expression profiles, and GO information. To evaluate the performance of the TEO method, we compare it with five other methods (degree, betweenness, NC, Pec, and CowEWC) in detecting essential proteins from two different yeast PPI datasets. The simulation results show that adding GO information can effectively improve the predicted precision and that our method outperforms the others in predicting essential proteins.
Autors: Wei Zhang;Jia Xu;Yuanyuan Li;Xiufen Zou;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Feb 2018, volume: 15, issue:1, pages: 109 - 116
Publisher: IEEE
 
» Detection and Discrimination of Ship Targets in Complex Background From Spaceborne ALOS-2 SAR Images
Abstract:
This paper proposes a novel method for ship detection and discrimination in complex background from synthetic aperture radar (SAR) images. It first implements a pixel-level land–sea segmentation with the aid of a global 250-m water mask. Then, an efficient multiscale constant false alarm rate (CFAR) detector with generalized Gamma distribution clutter model is designed to detect candidate targets in the sea. At last, eigenellipse discrimination and maximum-likelihood (ML) discrimination are designed to further exclude false alarm nonship objects in nearshore and harbor area. The proposed land–sea segmentation method is compared with multilevel Otsu method. The proposed multiscale ship detector is compared with conventional CFAR detectors. These contrast experiments show the good performance of our method. Finally, experiments undertaken on actual ALOS-2 SAR data show the efficacy of the proposed approach in detecting nearshore ship targets in a complex coastal environment.
Autors: Wei Ao;Feng Xu;Yongchen Li;Haipeng Wang;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 536 - 550
Publisher: IEEE
 
» Detection of Bond Pad Discolorations at Outgoing Wafer Inspections
Abstract:
Deployment of an automatic visual inspection system in semiconductor industry has become increasingly popular than ever not only due to its relatively high value as a yield analysis tool of outgoing products but more importantly for the prevention of defect escapee. A lot of studies are done on the application of in-line defect scan but the application of outgoing wafer inspection at post-fab environment has been very limited and rarely found in literature. With rapid growth of automotive application in worldwide industry, the importance of quality of the wafer at die level has never been so critical. This paper provides a method for detection of bond pad discolorations at outgoing quality check especially in semiconductor industry. An effective method for detection of the bond pad discolorations was proposed. The advantages and disadvantages of the detection method are discussed. Factors that are affecting the performances of the detection method are also described and analyzed.
Autors: S. N. David Chua;S. Mohamaddan;S. J. Tanjong;A. Yassin;S. F. Lim;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 144 - 148
Publisher: IEEE
 
» Detection of Multiple Movers Based on Single Channel Source Separation of Their Micro-Dopplers
Abstract:
Studies have demonstrated the usefulness of micro-Doppler signatures for classifying dynamic radar targets such as humans, helicopters, and wind turbines. However, these classification works are based on the assumption that the propagation channel consists of only a single moving target. When multiple targets move simultaneously in the channel, the micro-Dopplers, in their radar backscatter, superimpose thereby distorting the signatures. In this paper, we propose a method to detect multiple targets that move simultaneously in the propagation channel. We first model the micro-Doppler radar signatures of different movers using dictionary learning techniques. Then, we use a sparse coding algorithm to separate the aggregate radar backscatter signal from multiple targets into their individual components. We demonstrate that the disaggregated signals are useful for accurately detecting multiple targets.
Autors: Shelly Vishwakarma;Shobha Sundar Ram;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 159 - 169
Publisher: IEEE
 
» Detection of Range Migrating Targets in Compound-Gaussian Clutter
Abstract:
This paper deals with the problem of coherent radar detection of fast-moving targets in a high-range resolution mode. In particular, we are focusing on the spiky clutter modeled as a compound Gaussian process with rapidly varying power along range. Additionally, a fast-moving target of interest has a few range cells migration within the coherent processing interval. Two coherent CFAR detectors are proposed taking into account target migration and highly inhomogeneous clutter. Both detectors involve solution of a transcendental equation, carried out numerically in a few iterations. The performance evaluation is addressed by numerical simulations and it shows a significant improvement in detection of fast-moving targets in inhomogeneous heavy tailed radar clutter.
Autors: Nikita Petrov;François Le Chevalier;Alexander G. Yarovoy;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 37 - 50
Publisher: IEEE
 
» Detection of Vessel Targets in Sea Clutter Using In Situ Sea State Measurements With HFSWR
Abstract:
The detection of vessel targets could be effectively resolved in a high-frequency surface wave radar (HFSWR). However, signals reflected from vessels are concealed by sea clutter in the Doppler spectrum, where such detections are performed. Consequently, differences between these features in the Doppler domain cannot be readily observed, which greatly increases the difficulty in detecting vessel targets. In this letter, in situ sea state information is utilized to facilitate the detection of targets within sea clutter. First, the sea clutter spectrum, which is absent of vessel, is constructed. Second, sensitive sea clutter features that are influenced by vessel targets are selected and analyzed. Third, anomalies in sensitive sea clutter features are detected by obtaining respective thresholds. Finally, vessel targets are identified by the synthesized anomaly detection. Experimental results demonstrate the effectiveness of the proposed method, and the vessels detected using the HFSWR are further verified using synchronous automatic identification system information.
Autors: Yiming Wang;Xingpeng Mao;Jie Zhang;Yonggang Ji;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 302 - 306
Publisher: IEEE
 
» Determination of Complex Permittivity of Low-Loss Samples From Position-Invariant Transmission and Shorted-Reflection Measurements
Abstract:
In this paper, we devise a position-invariant method for unique and accurate complex permittivity () determination of low-loss samples from transmission and shorted-reflection scattering (S-) parameter measurements while mitigating the effect around Fabry–Perot frequencies. For this goal, we derived a metric function in terms of propagation factor only and utilized a branch-index-independent expression for unique by eliminating multiple solutions problem. We measured S-parameters of two low-loss samples with substantial thickness, which both introduced a Fabry–Perot effect in the frequency range, and the measurements were conducted to validate our method and compare its accuracy with the accuracy of similar methods in the literature. We also performed an uncertainty analysis to evaluate and improve the accuracy of our method.
Autors: Ugur Cem Hasar;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 1090 - 1098
Publisher: IEEE
 
» Determination of the oxidation induction time of mineral insulating oils using a modified EN 14112 method
Abstract:
The most common cause of chemical aging of insulating oils is oxidation. Inhibited oils are insulating oils to which an oxidation inhibitor such as 2,6 ditertiary-butyl phenol or 2,6 dietertiary-butyl cresol has been added in order to slow the rate of oxidation [1]-[3]. The oxidation induction time (OIT) is the time at which the oxidation inhibitor has been exhausted.
Autors: Helena M. Wilhelm;Paulo O. Fernandes;Leandro G. Feitosa;Geovana C. Dos Santos;Giorgi Dal Pont;Andreza Balielo;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Feb 2018, volume: 34, issue:1, pages: 7 - 14
Publisher: IEEE
 
» Determining the Optimal Location of Terror Response Facilities Under the Risk of Disruption
Abstract:
The highly strategic nature of terrorist attacks has often frustrated attempts at locating emergency response facilities. To better determine the optimal location of such facilities, we present a leader–follower game between State and Terrorist by considering facility failures. The first stage of the game allows State to make a facility location decision and facility assignment to the attacked city, while the second stage allows Terrorist to select one city to attack after observing the State’s strategy. The game is translated into a minmaxmin problem, and a population-based heuristic algorithm is proposed to solve it. We evaluate the performance of both model and heuristic by using an emergency example. Our results indicate that the proposed algorithm is able to generate suitable facility location solutions, allowing us to deploy resources more efficiently during a terrorist attack to where they are needed.
Autors: LingPeng Meng;Qi Kang;ChuanFeng Han;MengChu Zhou;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 476 - 486
Publisher: IEEE
 
» Developing a Nonstationary Computational Framework With Application to Modeling Dynamic Modulations in Neural Spiking Responses
Abstract:
Objective: This paper aims to develop a computational model that incorporates the functional effects of modulatory covariates (such as context, task, or behavior), which dynamically alter the relationship between the stimulus and the neural response. Methods: We develop a general computational approach along with an efficient estimation procedure in the widely used generalized linear model (GLM) framework to characterize such nonstationary dynamics in spiking response and spatiotemporal characteristics of a neuron at the level of individual trials. The model employs a set of modulatory components, which nonlinearly interact with other stimulus-related signals to reproduce such nonstationary effects. Results: The model is tested for its ability to predict the responses of neurons in the middle temporal cortex of macaque monkeys during an eye movement task. The fitted model proves successful in capturing the fast temporal modulations in the response, reproducing the spike response temporal statistics, and accurately accounting for the neurons’ dynamic spatiotemporal sensitivities, during eye movements. Conclusion: The nonstationary GLM framework developed in this study can be used in cases where a time-varying behavioral or cognitive component makes GLM-based models insufficient to describe the dependencies of neural responses on the stimulus-related covariates. Significance: In addition to being quite powerful in encoding time-varying response modulations, this general framework also enables a readout of the neural code while dissociating the influence of other nonstimulus covariates. This framework will advance our ability to understand sensory processing in higher brain areas when modulated by several behavioral or cognitive variables.
Autors: Amir Akbarian;Kaiser Niknam;Moahammadbagher Parsa;Kelsey Clark;Behrad Noudoost;Neda Nategh;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 241 - 253
Publisher: IEEE
 
» Development and Application of ±500 kV DC Transmission Line Arrester in China Power Grid
Abstract:
In order to solve the frequently occurring lightning flashover problems on ±500 kV dc transmission lines in China, the authors have conducted the research on the dc line arrester since 2011. In this paper, the structure and installation, technical parameters, and protection performances, as well as their deterministic processes of the arrester are presented and analyzed in detail. In 2013, the authors successfully developed the arrester products, and the type tests show that they have excellent performance parameters and can act effectively against the lightning impulse and cutoff the dc follow current. By now more than 500 dc line arresters have been installed and used on seven ±500 kV dc transmission lines in eight provinces of China. About four years of operating experience shows that the arresters work safely and reliably over a long period of time, and have been effectively reducing the lightning flashover rate of the ±500 kV dc lines.
Autors: Shanqiang Gu;Shuai Wan;Jian Wang;Jiahong Chen;Tao Li;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 209 - 217
Publisher: IEEE
 
» Development and Assessment of a Data Set Containing Frame Images and Dense Airborne Laser Scanning Point Clouds
Abstract:
This letter describes the main features of a data set that contains aerial images acquired with a medium format digital camera and point clouds collected using an airborne laser scanning unit, as well as ground control points and direct georeferencing data. The flights were performed in 2014 over an urban area in Presidente Prudente, São Paulo, Brazil, using different flight heights. These flights covered several features of interest for research, including buildings of different sizes and roof materials, roads, and vegetation. Three point clouds with different densities, a block of digital aerial images, and auxiliary data are available. A geometric assessment was conducted to ensure the accuracy and consistency of the data, and an RMSE of 7 cm was achieved using bundle block adjustment. The data set is freely available for download, and it will be expanded with data collected over time.
Autors: Antonio Maria Garcia Tommaselli;Maurício Galo;Thiago Tiedtke dos Reis;Roberto da Silva Ruy;Marcus Vinicius Antunes de Moraes;Wander Vieira Matricardi;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 192 - 196
Publisher: IEEE
 
» Development and Calibration of a Variable Range Stand for Testing Space Micropropulsion Thrusters
Abstract:
Microthrusters are used for microsatellites to provide precise motion control in space by applying very low thrust pulses, which must be properly calibrated on earth. The range of thrust levels required varies from one thruster to another, depending on its use. Thus, microthrusts that stand capable of reading thrusts of multiple ranges, depending on the configuration, are in demand. This paper discusses the features and the calibration method for a typical miniaturized thrust stand. This device is essentially a torsional pendulum whose sensitivity can be varied. As a source of torsion, a piece of wire is used. For the purpose of this paper, the thrust stand was configured to achieve a micro-Newton resolution.
Autors: M. W. A. B. Rohaizat;M. Lim;L. Xu;S. Huang;I. Levchenko;S. Xu;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Feb 2018, volume: 46, issue:2, pages: 289 - 295
Publisher: IEEE
 
» Development and Evaluation of an Axial Gap Motor Using Neodymium Bonded Magnet
Abstract:
In general, radial gap motors employing neodymium sintered permanent magnet (Nd sintered PM) are used to achieve high torque density in many applications. However, the motors are not suited to a flat, disk-like shape because the dead space, such as the coil ends, occupies most of the motor volume. Therefore, axial gap motors are frequently used for flat shape instead of radial gap motors. Nd sintered PM is a well-known high-performance magnet that has high residual magnetic flux density, but eddy current loss easily occurs in the magnet because of its high conductivity. In axial gap motors for industrial applications, it is difficult to take measures against eddy current loss of Nd sintered PM in terms of cost. Therefore, general axial gap motors employing Nd sintered PM often have unsatisfactory characteristics, such as low efficiency, even though the motor produces high torque. On the other hand, radial gap motors can take measures to suppress eddy current in PMs easily if radial gap motors employ interior permanent magnet structure. Accordingly, this paper discusses an axial gap motor employing neodymium bonded permanent magnet (Nd bonded PM) for flat shape. Compared with Nd sintered PM, Nd bonded PM has lower residual magnetic flux density, but also lower cost. In addition, Nd bonded PM has extremely low eddy current loss due to its low conductivity. It is found from three-dimensional finite element analysis and experimental results that the axial gap motor employing Nd bonded PM can achieve higher torque and higher efficiency compared with the radial gap motor employing Nd sintered PM with the same PM weight and a flat shape.
Autors: Ren Tsunata;Masatsugu Takemoto;Satoshi Ogasawara;Asako Watanabe;Tomoyuki Ueno;Koji Yamada;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 254 - 262
Publisher: IEEE
 
» Development and Performance of a Photoelectric Salt Concentration Sensor
Abstract:
The lack of medical salt aerosssol concentration detection method and instability powder atomization result in poor aerosol inhalation treatment effects. Considering medical vaporizer specific requirements, physical and chemical characteristics of salt powder commonly used, this paper analyzes salt particle light scattering using T-matrix method based on discrete source, calculated scattering intensity of salt particle with diameter of 0.4 to , develops photoelectric salt aerosol concentration sensor with forward differential scattering light path and weak current signal conditioning circuits. Sensor salt aerosol concentration calibration experiments and performance tests was carried out, and the results show as follows: the maximum residuals of sensor is 0.262 mg/L in calibration experiments and relative error in performance tests was 12.9%, satisfied salt aerosol concentration detection requirements and could provide basis for on line stability control of aerosol concentration in medical salt powder atomization process.
Autors: Xiliang Zhang;Lin Zhao;Changyuan Ma;Gang Jiao;Kun Xu;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1694 - 1702
Publisher: IEEE
 
» Development of a Bidirectional DC/DC Converter With Dual-Battery Energy Storage for Hybrid Electric Vehicle System
Abstract:
This study develops a newly designed, patented, bidirectional dc/dc converter (BDC) that interfaces a main energy storage (ES1), an auxiliary energy storage (ES2), and dc-bus of different voltage levels, for application in hybrid electric vehicle systems. The proposed converter can operate in a step-up mode (i.e., low-voltage dual-source-powering mode) and a step-down (i.e., high-voltage dc-link energy-regenerating mode), both with bidirectional power flow control. In addition, the model can independently control power flow between any two low-voltage sources (i.e., low-voltage dual-source buck/boost mode). Herein, the circuit configuration, operation, steady state analysis, and closed-loop control of the proposed BDC are discussed according to its three modes of power transfer. Moreover, the simulation and experimental results for a 1-kW prototype system are provided to validate the proposed converter.
Autors: Ching-Ming Lai;Yu-Huei Cheng;Ming-Hua Hsieh;Yuan-Chih Lin;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1036 - 1052
Publisher: IEEE
 
» Development of a Fluid Dynamic Model for Quantitative Contrast-Enhanced Ultrasound Imaging
Abstract:
Contrast-enhanced ultrasound (CEUS) is a non-invasive imaging technique extensively used for blood perfusion imaging of various organs. This modality is based on the acoustic detection of gas-filled microbubble contrast agents used as intravascular flow tracers. Recent efforts aim at quantifying parameters related to the enhancement in the vascular compartment using time-intensity curve (TIC), and at using these latter as indicators for several pathological conditions. However, this quantification is mainly hampered by two reasons: first, the quantification intrinsically solely relies on temporal intensity variation, the explicit spatial transport of the contrast agent being left out. Second, the exact relationship between the acquired US-signal and the local microbubble concentration is hardly accessible. This paper introduces the use of a fluid dynamic model for the analysis of dynamic CEUS (DCEUS), in order to circumvent the two above-mentioned limitations. A new kinetic analysis is proposed in order to quantify the velocity amplitude of the bolus arrival. The efficiency of proposed methodology is evaluated both in-vitro, for the quantitative estimation of microbubble flow rates, and in-vivo, for the classification of placental insufficiency (control versus ligature) of pregnant rats from DCEUS. Besides, for the in-vivo experimental setup, we demonstrated that the proposed approach outperforms the performance of existing TIC-based methods.
Autors: Baudouin Denis de Senneville;Anthony Novell;Chloé Arthuis;Vanda Mendes;Paul-Armand Dujardin;Frédéric Patat;Ayache Bouakaz;Jean-Michel Escoffre;Franck Perrotin;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 372 - 383
Publisher: IEEE
 
» Development of a high-performance indirectly hydrogen-cooled turbine generator [News from Japan]
Abstract:
Global warming caused by CO2 emission, and continuously growing power demands world-wide, are of considerable concern. Among the various types of electric power generation systems, thermal power generation is the largest emitter of CO2. Thus reducing the CO2 emission from thermal power generation plants by increasing their efficiency is an important task for the manufacturers of such plants. Thermal power plants and turbine generators are therefore required to supply electric power more efficiently, where efficiency is defined as generator efficiency.
Autors: Y. Ohki;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Feb 2018, volume: 34, issue:1, pages: 61 - 63
Publisher: IEEE
 
» Development of a Low Radar Cross Section Antenna With Band-Notched Absorber
Abstract:
A low radar cross section (RCS) antenna designed with band-notched absorber is described. First, a dual-polarization absorber with relative bandwidth more than 80% is designed using loaded resistors. Pairs of circular slot resonators and metal strip array resonators are introduced in the absorber to realize a notch band with full reflectance in the vertical polarization, while a wide absorption band in the horizontal polarization is maintained. The proposed band-notched absorber is thus realized. Within the notch band, the absorber can be served as a metal ground for antenna; while a great RCS reduction is obtained out of the notch band and in the horizontal polarization band. Then, a dipole antenna rigorously designed is mounted above the band-notched absorber, whose operating frequency is exactly in accordance with that of the notch band. The proposed low RCS antenna is established based on assembling the dipole antenna and the band-notched absorber together. The measured results demonstrate that the proposed antenna has fairly good radiation patterns. Added to that, more than 10 dB RCS reduction in two polarizations is realized simultaneously compared with that one of a conventional dipole antenna.
Autors: Peng Mei;Xian Qi Lin;Jia Wei Yu;Abdelheq Boukarkar;Peng Cheng Zhang;Zi Qiang Yang;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 582 - 589
Publisher: IEEE
 
» Development of a Nonresonant Piezoelectric Motor With Nanometer Resolution Driving Ability
Abstract:
A nonresonant-type piezoelectric motor with a precise driving ability was proposed. The operating principle of the proposed motor is different from the previous nonresonant piezoelectric motors using either the clamping and feeding mechanism (inchworm mechanism) or the inertia drive mechanism. An oblique linear motion formed by the hybrid of two bending motions of a sandwich transducer was used to push the runner step-by-step. Two square-wave voltages were applied to the horizontal and vertical PZT elements to obtain the desired oblique linear motion. The mechanism of the proposed piezoelectric motor was illustrated in detail. Then, transient analyses were performed by ANSYS software to simulate the motion trajectory and to find the response characteristics of the motor. Finally, a prototype was fabricated to verify the mechanism and to test the mechanical output characteristics of the proposed motor. Under the input square-wave voltages of 500 V, the prototype achieved a step displacement of 5.96 μm, a maximum no-load velocity of 59.64 μm/s, and a maximum thrust of 30 N. This paper provides a new mechanism for the design of a nonresonant piezoelectric motor with long stroke and precise driving ability.
Autors: Dongmei Xu;Yingxiang Liu;Shengjun Shi;Junkao Liu;Weishan Chen;Liang Wang;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 444 - 451
Publisher: IEEE
 

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