Electrical and Electronics Engineering publications abstract of: 02-2018 sorted by title, page: 14

» Metaheuristic Optimization for Long-term IaaS Service Composition
Abstract:
We propose a novel dynamic metaheuristic optimization approach to compose an optimal set of IaaS service requests to align with an IaaS provider’s long-term economic expectation. This approach is designed for the context that the IaaS provisioning subjects to resource and QoS constraints. In addition, the IaaS service requests have the features of dynamic resource and QoS requirements and variable arrival times. A new economic model is proposed to evaluate the similarity between the provider’s long-term economic expectation and a composition of service requests. The evaluation incorporates the factors of dynamic pricing and operation cost modeling of the service requests. An innovative hybrid genetic algorithm is proposed that incorporates the economic inter-dependency among the requests as a heuristic operator and performs repair operations in local solutions to meet the resource and QoS constraints. The proposed approach generates dynamic global solutions by updating the heuristic operator at regular intervals with the runtime behavior data of an existing service composition. Experimental results preliminarily prove the feasibility of the proposed approach.
Autors: Sajib Mistry;Athman Bouguettaya;Hai Dong;A. K. Qin;
Appeared in: IEEE Transactions on Services Computing
Publication date: Feb 2018, volume: 11, issue:1, pages: 131 - 143
Publisher: IEEE
 
» Methods for Estimating the Convergence of Inter-Chip Min-Entropy of SRAM PUFs
Abstract:
For cryptographic applications based on physical unclonable functions (PUFs), it is very important to estimate the entropy of PUF responses accurately. The upper bound of the entropy estimated by compression algorithms, such as context-tree weighting, is too loose, while the lower bound estimated by the min-entropy calculation is too conservative, especially when the sample size is small. The actual min-entropy is between these bounds but is difficult to estimate accurately. In this paper, two models are proposed to estimate the convergence of the inter-chip min-entropy of static random-access memory (SRAM) PUFs. The basic idea is to find the relation between the expectation of the estimation result and the tested sample size, and then predict the convergence of the min-entropy. Furthermore, an improved Von Neumann extractor is used to increase the entropy per bit while retaining as many responses as possible for error correction. The experimental results demonstrate that the prediction error of the proposed estimation methods is less than 0.01/bit for the tested SRAM chips, and the improved Von Neumann extractor can reduce the number of required responses by approximately 11/16, the amount of helper data by 2/3, and the number of masks by 3/8 compared with the original method.
Autors: Hailong Liu;Wenchao Liu;Zhaojun Lu;Qiaoling Tong;Zhenglin Liu;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 593 - 605
Publisher: IEEE
 
» Micro-Doppler Mini-UAV Classification Using Empirical-Mode Decomposition Features
Abstract:
In this letter, we propose an empirical-mode decomposition (EMD)-based method for automatic multicategory mini-unmanned aerial vehicle (UAV) classification. The radar echo signal is first decomposed into a set of oscillating waveforms by EMD. Then, eight statistical and geometrical features are extracted from the oscillating waveforms to capture the phenomenon of blade flashes. After feature normalization and fusion, a nonlinear support vector machine is trained for target class-label prediction. Our empirical results on real measurement of radar signals show encouraging mini-UAV classification accuracy performance.
Autors: Beom-Seok Oh;Xin Guo;Fangyuan Wan;Kar-Ann Toh;Zhiping Lin;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 227 - 231
Publisher: IEEE
 
» Microbeam SEE Analysis of MIM Capacitors for GaN Amplifiers
Abstract:
Broad-beam and microbeam single-event effect tests were performed on metal–insulator–metal capacitors with three different thicknesses of silicon nitride (Si3N4) dielectric insulator: 250, 500, and 750 nm. The broad-beam tests indicated that the devices with the thicker, 500- and 750-nm dielectric did not have a greater breakdown voltage. The surrounding structures of the capacitor were suspected to be a possible cause. Microbeam techniques made it possible to localize the failure location for the 500- and 750-nm devices. The failure occurs in the air bridge structure connected to the top capacitor plate, which can therefore be considered as an edge effect, while for the 250-nm devices, the failure occurs in the body of the capacitor.
Autors: Pawel Kupsc;Arto Javanainen;Véronique Ferlet-Cavrois;Michele Muschitiello;Andrew Barnes;Ali Zadeh;Jordan Calcutt;Christian Poivey;Hermann Stieglauer;Kay-Obbe Voss;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 732 - 738
Publisher: IEEE
 
» Microfabricated Electrodynamic Synthetic Jet Actuators
Abstract:
This paper presents the design, fabrication, and characterization of a chip-scale electrodynamic synthetic jet actuator with batch-fabricated die components. The actuator is an assembly of two dies with a plastic spacer sandwiched in between. The top die consists of a copper micro-coil and an orifice through which the jet is synthesized. The bottom die consists of a poly-dimethyl-siloxane diaphragm with a wax-bonded NdFeB magnet. When assembled, an ac current applied to the micro-coil forces an oscillatory actuation of the magnet, and correspondingly ingestion and expulsion of fluid through the orifice. The dimensions of the assembled actuator are 7.5 mm mm mm. The peak jet velocity is measured to be 4.3 m/s at 160 Hz for an input of 200-mA current corresponding to 20 mW of input electrical power. [2017-0166]
Autors: Shashank G. Sawant;Benjamin George;Lawrence S. Ukeiley;David P. Arnold;
Appeared in: Journal of Microelectromechanical Systems
Publication date: Feb 2018, volume: 27, issue:1, pages: 95 - 105
Publisher: IEEE
 
» Microplasma Generation of Iron Microparticles for 3-D Manufacturing
Abstract:
Three-D metal selective laser sintering is a relatively new but growing field of microfabrication. Iron used in alloys commonly starts as micropellet feedstock made with spray atomization; however, this process is power intensive and less economical than the microplasma generation. In this letter, iron nitrate is used to produce iron microparticles in an aqueous-based microplasma process to form metal microparticles that can be used in additive manufacturing. We show that it is possible to form particles on the order of micrometers. The plasma process was successfully used to make iron microparticles that would work in the selective laser sintering process and can be used for any metal solution. The fabricated particles are investigated for size, size distribution, shape, and composition. [2017-0201]
Autors: Alex Ulrich;William Clower;Chester G. Wilson;
Appeared in: Journal of Microelectromechanical Systems
Publication date: Feb 2018, volume: 27, issue:1, pages: 25 - 27
Publisher: IEEE
 
» Microw(h)att?! Ultralow-Power Six-Port Radar: Realizing Highly Integrated Portable Radar Systems with Good Motion Sensitivity at Relatively Low Cost
Abstract:
In this article, we have presented a lightweight, ultralow-power 24-GHz six-port radar system for remote vibration monitoring. Based on a detailed analysis of this year's competition scenario (featuring a slightly modified FOM), an optimized system concept and hardware implementation were proposed, with a strong focus on the ultralow-power system design. Using a purely passive six-port microwave interferometer, both a high phase resolution and an ultralow power consumption have been achieved. During the SDC, a sensitivity well below 100 nm was demonstrated, with the average power consumption of the whole system (not including USB data transmission) being approximately 30 nW (9 nA at 3.3 V). This is a significant improvement compared to previous years' SDCs [8], [9] and, to the best of our knowledge, currently the lowest reported power consumption for a short-range radar system. Table 3 compares the work presented here with all previous high-sensitivity radar SDC winners. With a standard CR2032 coin cell (3 V, 220 mAh), the proposed radar system (Figure 9) could be powered for more than two years, continuously performing six measurements each second. Furthermore, the number of measurements per second can easily be adjusted by software, depending on the application scenario. In this way, a higher measurement update rate or a higher sensitivity can be achieved when using additional filtering in the digital baseband, but at the cost of higher power consumption.
Autors: Fabian Lurz;Fabian Michler;Benedict Scheiner;Robert Weigel;Alexander Koelpin;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 91 - 98
Publisher: IEEE
 
» Microwave Heating Visualization for Carbon Fibers Composite Material: Development of Tunable Microstrip Structures
Abstract:
The visualization of carbon fibers polyether ether ketone (PEEK) composite material heating for a grounded coplanar waveguide and a stepped impedance low-pass filter by the thermal camera is performed. The purpose of such visualization is to characterize electromagnetic field influence on the diagonally anisotropic composite material and find out its application opportunity. COMSOL Multiphysics simulation has been done in order to understand heating principles and origin. Experimental results were in a good agreement with simulations and they showed that the characteristics of the microstrip structures can be modulated/tuned by simple rotation of the composite material. Finally, a tunable application by the carbon/PEEK composite material for the microstrip low-pass filter was developed due to the microwave absorption selectivity dependence on the composite material orientation.
Autors: Shant Arakelyan;Hanju Lee;Do-Suck Han;Arsen Babajanyan;Gerard Berthiau;Barry Friedman;Kiejin Lee;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 883 - 888
Publisher: IEEE
 
» Microwave Photonic Filter Based All-Optical Virtual Private Network Supporting Dynamic Bandwidth Allocation in OFDMA-PON System
Abstract:
We propose an all-optical virtual private network (VPN) supporting dynamic bandwidth allocation (DBA) in an orthogonal frequency division multiple access-based passive optical network. A microwave photonic bandpass filter (MP-BPF) is used to transmit the VPN signal without electrical conversion. The DBA is implemented by adjusting a free spectral range of the MP-BPF with corresponding subcarrier allocation. A RF clipping-tone (CT) is used to stabilize the optical channel suffered from phase induced-intensity noise and Rayleigh back-scattering noise. The DBA is experimentally verified at different two DBA scenarios in 20-km single-fiber loopback link in terms of channel error vector magnitude, spectral efficiency after adaptive modulation. Due to the CT-based channel stabilization, achievable spectral efficiency could be improved, and the feasibility of the proposed system is successfully demonstrated.
Autors: Chang-Hun Kim;Sun-Young Jung;Sang-Kook Han;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 8
Publisher: IEEE
 
» Microwave Photonic Harmonic Down-Conversion Based on Cascaded Four-Wave Mixing in a Semiconductor Optical Amplifier
Abstract:
A reconfigurable and wideband photonic method is proposed for microwave photonic harmonic down-conversion based on cascaded four-wave mixing in a semiconductor optical amplifier (SOA). The cascaded four-wave mixing in SOA triggers high-order harmonics generation of local oscillator (LO) in the optical domain, and enables microwave down-conversion in the electrical domain with a low-frequency electrical LO. Compared with the conventional photonic method, ours allows microwave down-conversion operation for wide frequency range RF signal with a low-frequency electrical LO, and at the same time it avoids the requirement of complex phase control and heavy driving for the electrical LO. Moreover, it enables reconfigurable down-conversion with frequency tunability. In the demonstration, the 3∼40 GHz RF signals are experimentally down-converted to IF signals below 2 GHz with a low-frequency electrical LO within the range of 5 GHz.
Autors: Xinhai Zou;Shangjian Zhang;Heng Wang;Zhiyao Zhang;Jinjin Li;Yali Zhang;Shuang Liu;Yong Liu;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 8
Publisher: IEEE
 
» Microwave Photonics Filtering Interrogation Technique Under Coherent Regime For Hot Spot Detection on a Weak FBGs Array
Abstract:
An interrogation technique of cascaded FBG sensors based on a microwave photonics filtering technique under coherent regime is presented. The sensing information of a 5-m fiber coil containing 500 weak FBG with a similar central wavelength is retrieved. The FBGs are 9-mm long and the spatial separation between consecutive FBGs is 1 mm. The principle of operation is based on the calculation of the impulse response by recording the electrical frequency response of the system. Hot spot detection, location, and temperature measurement are demonstrated by experimental measurements with a temperature sensitivity of 0.6 dB/°C in a 10 °C range. Fifteen measurements are recorded in order to average them to reduce noise and smooth the saw tooth appearance typical of coherent measurements. The resolution of the proposed interrogation technique is related to the bandwidth of the electrical measurement. We have obtained a resolution of 20 cm for an electrical bandwidth of 1 GHz. The SNR was larger than 16 dB despite the fact that no amplification was used within the system.
Autors: Javier Hervás;David Barrera;Javier Madrigal;Salvador Sales;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 1039 - 1045
Publisher: IEEE
 
» Millimeter Wave Beam-Selection Using Out-of-Band Spatial Information
Abstract:
Millimeter wave (mmWave) communication is one feasible solution for high data-rate applications like vehicular-to-everything communication and next generation cellular communication. Configuring mmWave links, which can be done through channel estimation or beam-selection, however, is a source of significant overhead. In this paper, we propose using spatial information extracted at sub-6 GHz to help establish the mmWave link. Assuming a fully digital architecture at sub-6 GHz; and an analog architecture at mmWave, we outline a strategy to extract spatial information from sub-6 GHz and its use in mmWave compressed beam-selection. Specifically, we formulate compressed beam-selection as a weighted sparse signal recovery problem, and obtain the weighting information from sub-6 GHz channels. In addition, we outline a structured precoder/combiner design to tailor the training to out-of-band information. We also extend the proposed out-of-band aided compressed beam-selection approach to leverage information from all active subcarriers at mmWave. To simulate multi-band frequency dependent channels, we review the prior work on frequency dependent channel behavior and outline a multi-frequency channel model. The simulation results for achievable rate show that out-of-band aided beam-selection can considerably reduce the training overhead of in-band only beam-selection.
Autors: Anum Ali;Nuria González-Prelcic;Robert W. Heath;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1038 - 1052
Publisher: IEEE
 
» Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures
Abstract:
We consider the problem of channel estimation for millimeter wave (mmWave) systems, where, to minimize the hardware complexity and power consumption, an analog transmit beamforming and receive combining structure with only one radio frequency chain at the base station and mobile station is employed. Most existing works for mmWave channel estimation exploit sparse scattering characteristics of the channel. In addition to sparsity, mmWave channels may exhibit angular spreads over the angle of arrival, angle of departure, and elevation domains. In this paper, we show that angular spreads give rise to a useful low-rank structure that, along with the sparsity, can be simultaneously utilized to reduce the sample complexity, i.e., the number of samples needed to successfully recover the mmWave channel. Specifically, to effectively leverage the joint sparse and low-rank structure, we develop a two-stage compressed sensing method for mmWave channel estimation, where the sparse and low-rank properties are respectively utilized in two consecutive stages, namely, a matrix completion stage and a sparse recovery stage. Our theoretical analysis reveals that the proposed two-stage scheme can achieve a lower sample complexity than a conventional compressed sensing method that exploits only the sparse structure of the mmWave channel. Simulation results are provided to corroborate our theoretical results and to show the superiority of the proposed two-stage method.
Autors: Xingjian Li;Jun Fang;Hongbin Li;Pu Wang;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1123 - 1133
Publisher: IEEE
 
» MIMO Radar Calibration and Imagery for Near-Field Scattering Diagnosis
Abstract:
Multiple-input multiple-output (MIMO) radar is an enabling technique for high-resolution imaging, which is especially useful for near-field electromagnetic scattering diagnosis of complex targets. Among others, high sidelobes and radar cross section (RCS) calibration uncertainty are the major challenges for such applications, due to array nonuniformity, imperfect channels, and antenna pattern tapering. These shortcomings prevent a MIMO radar from obtaining high-quality images with enough dynamic range and RCS accuracy. In this paper, we develop a complete solution for these problems. A novel adaptive weighting technique is proposed, where the complex weights are optimized for exact amplitude and phase error calibration of a MIMO array and for azimuth sidelobe reduction. A MIMO filtered backprojection algorithm is developed for image formation with improved RCS calibration accuracy, where propagation path-loss, antenna pattern tapering, and phase distortion due to the near-field spherical wave front are compensated. Both indoor and outdoor field test results are presented to show the high-quality images obtained using the proposed techniques, demonstrating the applicability of a MIMO radar for diagnostic RCS imaging of complex targets.
Autors: Yongze Liu;Xiaojian Xu;Guangyao Xu;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 442 - 452
Publisher: IEEE
 
» Miniaturized Electrospray Thrusters
Abstract:
Electrospray thrusters are a promising micropropulsion technology for CubeSats, among others, because they have the potential to provide high specific impulse. They avoid moving parts and allow a high degree of miniaturization. In combination with fabrication technologies from microelectromechanical systems (MEMS), miniaturization of individual emitters to the range of tens of micrometers brings with it a new concept of constructing and scaling thrusters, namely, by numbering-up the microthrusters to a device of suitable thrust. The current state of the art is briefly reviewed with an emphasis on MEMS technology. Furthermore, preliminary results, which indicate the feasibility of fabricating electrospray emitters in nonsilicon MEMS technology, notably by 3-D microlithography (two-photon lithography) are presented.
Autors: Torsten Henning;Katharina Huhn;Leonard W. Isberner;Peter J. Klar;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Feb 2018, volume: 46, issue:2, pages: 214 - 218
Publisher: IEEE
 
» Miniaturized Plasma Sources: Can Technological Solutions Help Electric Micropropulsion?
Abstract:
In this paper, we examine several different types of miniaturized plasma sources that have been developed for nonpropulsion applications, but could be useful for the advancement of electric propulsion. With the same or similar physical principles and often similar design solutions, such sources suggest useful pathways for modernization and integration of presently available well established as well as emerging miniaturized plasma sources into space thruster systems. Features related to miniaturization and optimization of the technological plasma sources will provide useful insights for consideration by the electric propulsion specialists. It is not the aim of this paper to show an entire spectrum of technological microplasma systems, but rather to outline possible future trends and perspectives for the miniaturized technological plasmas in relation to space micropropulsion systems.
Autors: Oleg O. Baranov;Shuyan Xu;Luxiang Xu;S. Huang;J. W. M. Lim;U. Cvelbar;Igor Levchenko;Kateryna Bazaka;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Feb 2018, volume: 46, issue:2, pages: 230 - 238
Publisher: IEEE
 
» Minimizing Controller Response Time Through Flow Redirecting in SDNs
Abstract:
Software defined networking (SDN) is becoming increasingly prevalent for its programmability that enables centralized network configuration and management. With the growth of SDNs, a cluster of controllers cooperatively manages more and more switches/flows in a network to avoid the single-controller congestion/failure and improve the control-plane robustness. Under the architecture with multiple controllers, it is expected to minimize the maximum response time on these controllers to provide better QoS for users. To achieve this target, two previous methods are mainly used, the static scheme and the dynamic scheme. However, these methods may lead to an increase of the control-plane communication overhead/delay. In this paper, we propose to minimize the maximum response time on controllers through flow redirecting, which is implemented by installing wildcard rules on switches. We formulate the minimum controller response time problem, which takes the flow-table size and link capacity constraints into account, as an integer linear program, and prove its NP-Hardness. Two algorithms with bounded approximation factors are designed to solve this problem. We implement the proposed methods on our SDN testbed. The testing results and extensive simulation results show that our proposed algorithm can reduce the maximum controller response time by about 50%–80% compared with the static/dynamic methods under the same controller cost, or reduce the number of controllers by 30% compared with the dynamic method while preserving almost the same controller response time.
Autors: Pengzhan Wang;Hongli Xu;Liusheng Huang;Chen Qian;Shaowei Wang;Yanjing Sun;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 562 - 575
Publisher: IEEE
 
» Minimizing the Number of Spans for Terrestrial Fiber-Optic Systems Using Quasi-Single-Mode Transmission
Abstract:
We show that quasi-single-mode transmission in few-mode fibers (FMFs) can reduce the number of spans for a fixed transmission distance and, consequently, the cost per bit for terrestrial transmission systems by minimizing both the Capex and Opex. The Gaussian-noise model is employed to estimate the nonlinear noise power spectral density both, which depends on the effective area of the FMF and span length, for Er-doped fiber amplifier (EDFA) and hybrid Raman/EDFA systems. Together with amplified spontaneous emission noise, an optical signal-to-noise ratio (OSNR) for a fixed transmission distance as a function of the effective area of the FMF and span length can be obtained. Given a target OSNR for a particular modulation format, we determine the maximum span length or the minimum number of spans as the effective area of the FMF varies both analytically and through numerical simulations. The effect of multipath interference in the FMF on the minimum number of span has also been investigated.
Autors: Jian Zhao;Inwoong Kim;Olga Vassilieva;Tadashi Ikeuchi;Wei Wang;He Wen;Guifang Li;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 10
Publisher: IEEE
 
» Minimum Rates of Approximate Sufficient Statistics
Abstract:
Given a sufficient statistic for a parametric family of distributions, one can estimate the parameter without access to the data. However, the memory or code size for storing the sufficient statistic may nonetheless still be prohibitive. Indeed, for independent samples drawn from a -nomial distribution with degrees of freedom, the length of the code scales as . In many applications, we may not have a useful notion of sufficient statistics (e.g., when the parametric family is not an exponential family), and we may also not need to reconstruct the generating distribution exactly. By adopting a Shannon-theoretic approach in which we allow a small error in estimating the generating distribution, we construct various approximate sufficient statistics and show that the code length can be reduced to . We consider errors measured according to the relative entropy and variational distance criteria. For the code constructions, we leverage Rissanen’s minimum description length principle, which yields a non-vanishing error measured according to the relative entropy. For the converse parts, we use Clarke and Barron’s formula for the relative entropy of a parameterized distribution and the corresponding mixture distribution. However, this method only yields a weak converse for the variational distance. We develop new techniques to achieve vanishing errors, and we also prove strong converses. The latter means that even if the code is allowed to have a non-vanishing error, its length must still be at least $({d}/{2})log n$ .
Autors: Masahito Hayashi;Vincent Y. F. Tan;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 875 - 888
Publisher: IEEE
 
» Mitigation of the Background Radiation for Free-Space Optical IM/DD Systems
Abstract:
Atmospheric turbulence and pointing errors cause fluctuations in the signal intensity of the free-space optical intensity-modulation/direct-detection link. Additionally, background radiation brings a noisy photocurrent component into the received signal. Using the generalized likelihood ratio test principle, a Viterbi-type trellis-search sequence receiver is proposed, which estimates both the channel gain and the background component and detects the data sequence simultaneously. It has the advantage of a low search complexity that does not depend on the observation window length , and its error performance approaches that of detection with perfect channel state information and no background radiation, as becomes large.
Autors: Tianyu Song;Ming-Wei Wu;Pooi-Yuen Kam;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 292 - 295
Publisher: IEEE
 
» Mixed Electric/Magnetic Fano Resonances in a Combined Square-Shaped Split Ring With an Internal Square Nanoantenna Nanocavities
Abstract:
Generally, the plasmonic Fano resonances can be divided into two types: the electric and the magnetic Fano resonance. Compared to pure electric or magnetic multiple Fano resonances, the mixed electric/magnetic multiple Fano resonances provide more flexibility for their application in multiwavelength surface enhanced Raman scattering and biosensing. Whereas, the dramatic difference between the two Fano resonances makes it difficult to realize magnetic and electric Fano resonances together in the same structure. In this paper, magnetic-octupole mode based Fano resonance and electric-quadrupole mode based Fano resonances in optical frequency were together achieved in a combined square-shaped split-ring resonator with an internal square nanoantenna nanocavities. The two Fano resonances are switchable by adjusting the polarization of the incident light. The lineshape modulated by the geometry and the environment of the two Fano resonances was investigated. Both the Fano resonances show high sensitivity to the environment. This study reveals a new multiple Fano resonance constitution and the proposed structure, which are expected with benefit application in multiwavelength polarization modulated chemistry and biological sensing.
Autors: Shan Huang;Cheng-Wu Zou;Feng Lin;Chen Lu;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 7
Publisher: IEEE
 
» Mixed Neural Network Approach for Temporal Sleep Stage Classification
Abstract:
This paper proposes a practical approach to addressing limitations posed by using of single-channel electroencephalography (EEG) for sleep stage classification. EEG-based characterizations of sleep stage progression contribute the diagnosis and monitoring of the many pathologies of sleep. Several prior reports explored ways of automating the analysis of sleep EEG and of reducing the complexity of the data needed for reliable discrimination of sleep stages at lower cost in the home. However, these reports have involved recordings from electrodes placed on the cranial vertex or occiput, which are both uncomfortable and difficult to position. Previous studies of sleep stage scoring that used only frontal electrodes with a hierarchical decision tree motivated this paper, in which we have taken advantage of rectifier neural network for detecting hierarchical features and long short-term memory network for sequential data learning to optimize classification performance with single-channel recordings. After exploring alternative electrode placements, we found a comfortable configuration of a single-channel EEG on the forehead and have shown that it can be integrated with additional electrodes for simultaneous recording of the electro-oculogram. Evaluation of data from 62 people (with 494 hours sleep) demonstrated better performance of our analytical algorithm than is available from existing approaches with vertex or occipital electrode placements. Use of this recording configuration with neural network deconvolution promises to make clinically indicated home sleep studies practical.
Autors: Hao Dong;Akara Supratak;Wei Pan;Chao Wu;Paul M. Matthews;Yike Guo;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Feb 2018, volume: 26, issue:2, pages: 324 - 333
Publisher: IEEE
 
» Mixing It Up: A Double-Balanced Mixer with Wide RF and IF Bandwidth
Abstract:
This article presents the design details of a wide-band, high-dynamic-range passive gallium arsenide (GaAs) mixer submitted for the Student Design Competition (SDC) held during the IEEE Microwave Theory and Techniques Society (MTT-S) 2017 International Microwave Symposium in Honolulu, Hawaii, this past May. The target of our research was to achieve a wide-band mixer with high dynamic range and zero power consumption. The "High-Dynamic-Range Mixer" SDC was sponsored by Technical Coordination Committee MTT-22.
Autors: Tiedi Zhang;Xiansuo Liu;Yuehang Xu;Lei Wang;Ruimin Xu;Bo Yan;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 106 - 111
Publisher: IEEE
 
» Mixture WG $Gamma$ -MRF Model for PolSAR Image Classification
Abstract:
The WG model has been validated as an effective model for the characteristic of polarimetric synthetic aperture radar (PolSAR) data statistics. However, due to the complexity of natural scene and the influence of coherent wave, the WG model still needs to be improved to fully consider the polarimetric information. Then, we propose the WG mixture model (WGMM) for PolSAR data to maintain the correlations among statistics in PolSAR data. To further consider the spatial-contextual information in PolSAR image classification, we propose a novel mixture model, named mixture WG-Markov random field (MWG-MRF) model, by introducing the MRF to improve the WGMM model for classification. In each law of the MWG-MRF model, the interaction term based on the edge penalty function is constructed by the edge-based multilevel-logistic model, while the likelihood term being constructed by the WG model, so that each law of the MWG-MRF model can achieve an energy function and has its contribution to the inference of attributive class. Then, the mixture energy function of the MWG-MRF model has the fusion of the weig- ted component, given the energy functions of every law. The mixture coefficient and the corresponding mean covariance matrix of the MWG-MRF model are estimated by the expectation-maximization algorithm, while the parameters of the WG model being estimated by the method of matrix log-cumulants. Experiments on simulated data and real PolSAR images demonstrate the effectiveness of the MWG-MRF model and illustrate that it can provide strong noise immunity, get smoother homogeneous areas, and obtain more accurate edge locations.
Autors: Wanying Song;Ming Li;Peng Zhang;Yan Wu;Xiaofeng Tan;Lin An;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 905 - 920
Publisher: IEEE
 
» MobiCoRE: Mobile Device Based Cloudlet Resource Enhancement for Optimal Task Response
Abstract:
Cloudlets are small self maintained clouds, with hotspot like deployment, to enhance the computational capabilities of the mobile devices. The limited resources of cloudlets can become heavily loaded during peak utilization. Consequently, per user available computational capacity decreases and at times mobile devices find no execution time benefit for using the cloudlet. Researchers have proposed augmenting the cloudlet resources using mobile devices; however, the proposed approaches do not consider the offered service to load ratio while using mobile device resources. In this paper, we propose easy to implement Mobile Device based Cloudlet Resource Enhancement (MobiCoRE) while ensuring that: (i) mobile device always have time benefit for its tasks submitted to the cloudlet and (ii) cloudlet induced mobile device load is a fraction of its own service requirement from the cloudlet. We map MobiCoRE on M/M/c/K queue and model the system using birth death markov chain. Given the arrival rate of , cpu cores in cloudlet, maximum tasks in the cloudlet to be and be probability of having no user in cloudlet, we derive the condition for optimal average service time of cloudlet such that the mobile applications have maximum benefit for using cloudlet services. We show that the optimal average service time is independent of the applications service requirement. Evaluation shows that MobiCoRE can accommodate upto 50 percent extra users when operating at optimal service time and sharing mobile resources for remaining task, compared to completing the entire user applications in cloudlet. Similarly, up to 47 percent time benefit can be achieved for mobile devices by sharing only 16 percent computational resources with the cloudlet.
Autors: Md Whaiduzzaman;Anjum Naveed;Abdullah Gani;
Appeared in: IEEE Transactions on Services Computing
Publication date: Feb 2018, volume: 11, issue:1, pages: 144 - 154
Publisher: IEEE
 
» Mobile Crowdsensing Games in Vehicular Networks
Abstract:
Vehicular crowdsensing takes advantage of the mobility of vehicles to provide location-based services in large-scale areas. In this paper, mobile crowdsensing (MCS) in vehicular networks is analyzed and the interactions between a crowdsensing server and vehicles equipped with sensors in an area of interest is formulated as a vehicular crowdsensing game. Each participating vehicle chooses its sensing strategy based on the sensing cost, radio channel state, and the expected payment. The MCS server evaluates the accuracy of each sensing report and pays the vehicle accordingly. The Nash equilibrium of the static vehicular crowdsensing game is derived for both accumulative sensing tasks and best-quality sensing tasks, showing the tradeoff between the sensing accuracy and the overall payment by the MCS server. A Q-learning-based MCS payment strategy and sensing strategy is proposed for the dynamic vehicular crowdsensing game, and a postdecision state learning technique is applied to exploit the known radio channel model to accelerate the learning speed of each vehicle. Simulations based on a Markov-chain channel model are performed to verify the efficiency of the proposed MCS system, showing that it outperforms the benchmark MCS system in terms of the average utility, the sensing accuracy, and the energy consumption of the vehicles.
Autors: Liang Xiao;Tianhua Chen;Caixia Xie;Huaiyu Dai;H. Vincent Poor;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1535 - 1545
Publisher: IEEE
 
» Mobility and Popularity-Aware Coded Small-Cell Caching
Abstract:
In heterogeneous cellular networks with caching capability, due to mobility of users and storage constraints of small-cell base stations (SBSs), users may not be able to download all of their requested content from the SBSs within the delay deadline of the content. In that case, the users are directed to the macro-cell base station (MBS) in order to satisfy the service quality requirement. Coded caching is exploited here to minimize the amount of data downloaded from the MBS, taking into account the mobility of the users as well as the popularity of the contents. An optimal distributed caching policy is presented when the delay deadline is below a certain threshold, and a distributed greedy caching policy is proposed when the delay deadline is relaxed.
Autors: Emre Ozfatura;Deniz Gündüz;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 288 - 291
Publisher: IEEE
 
» Model Predictive Control for the Flow Field in an Intermittent Transonic Wind Tunnel
Abstract:
To accurately test aircraft models, the flow field featured by the stagnation pressure and the Mach number must be kept constant at the predefined state during wind tunnel tests. The objective of this study is to design a multivariable controller to quickly reject various disturbances for the varying angle of attack (AoA) tests in a large-scale Intermittent Transonic Wind Tunnel (ITWT). First, the flow field control structure is specially designed to simplify the controller design. Next, a novel AoA model (i.e., Hammerstein model) with corresponding modeling approach is developed to characterize the influence of varying AoA on the static pressure. Finally, the flow field controller is designed in the offset-free model predictive control (MPC) framework, which uses the feedforward strategy to compensate for the varying AoA disturbance and copes with other unknown disturbances and model mismatch using the augmented model method. Simulation results and practical wind tunnel tests prove the effectiveness of the proposed modeling and control methods.
Autors: Jian Zhang;Ping Yuan;Kwai-Sang Chin;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 324 - 338
Publisher: IEEE
 
» Model Reference Adaptive Control for Hybrid Electric Vehicle With Dual Clutch Transmission Configurations
Abstract:
This paper proposes the use of an adaptive control of a hybrid electric vehicle with dual clutch transmission (HDCT). First, this paper shows mathematical equations for the nonlinear system. Then it presents the linearized model for the proposed system. The control objective of the model reference adaptive controller (MRAC) considered in this paper is to minimize fuel consumption and reduce torque interruption in a hybrid electric vehicle. The MRAC can be used to control the electric motor during changes in speed and gear, and the system can adapt to a model that simulates different driver patterns. The effects of using different model responses as input combinations are analyzed in an effort to exploit the over-actuation feature of the system, as is the sensitivity of the performance to various design factors. The simulation results for an HDCT demonstrate that the MRAC achieves reduced torque interruption and less vehicle jerk compared to the conventional method of operation.
Autors: Walid Elzaghir;Yi Zhang;Narasimhamurthi Natarajan;Frank Massey;Chunting Chris Mi;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 991 - 999
Publisher: IEEE
 
» Model Reference Adaptive Sliding Surface Design for Nonlinear Systems
Abstract:
The paper introduces a new model reference adaptive sliding surface design algorithm in order to determine possible nonlinear time-varying “sliding surface” for a general class of nonlinear systems. A model reference sliding surface is first designed for a reference nonlinear system by using the state-dependent Riccati equation techniques. Then, the sliding surfaces for nonlinear systems are obtained from the reference sliding surface by using an adaptation rule. The adaptation rule to satisfy the convergence of sliding surface for the nonlinear system to that of reference one is derived. The sliding mode controller for the nonlinear plant is then designed by using the adaptive sliding surfaces. The proposed method is illustrated with an autopilot design for different missile models.
Autors: Fatma Kara;Metin U. Salamci;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 611 - 624
Publisher: IEEE
 
» Model-Based Target Scattering Decomposition of Polarimetric SAR Tomography
Abstract:
When dealing with forest scenario, target scattering separation using synthetic aperture radar (SAR) tomography is a challenging task for the application of biophysical parameter retrieval approaches. One important and widely popular solution used to investigate the scattering mechanism separation based on multipolarimetric multibaseline (MPMB) SAR data is the sum of Kronecker products (SKPs), which provides the basis for decomposition of the data into ground-only and canopy-only contributions. In this paper, we investigate the possibility of characterizing multiple scattering mechanisms using the SKPs of covariance matrix. In particular, we present a method for characterization of forest structure using MPMB data that adapt SKP with the generalized volume description and the physical model of interferometric cross correlation as the sum of scattering contributions. According to the Freeman–Durden model, the method expresses the estimated covariance matrix in terms of the Kronecker product of polarimetric and interferometric coherence matrices corresponding to direct, double-bounce, and random-volume scattering mechanisms. The proposed method is tested with simulated and P-band MB data acquired by ONERA over a tropical forest in French Guiana in the frame of the European Space Agency’s campaign TROPISAR. Comparison of the retrieved height of trees with a LiDAR-based canopy model as a reference showed that the proposed method has the potential to decrease root-mean-square error of forest height by up to 3.9 m with respect to SKP.
Autors: Hossein Aghababaee;Mahmod Reza Sahebi;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 972 - 983
Publisher: IEEE
 
» Model-Free Control for Continuum Robots Based on an Adaptive Kalman Filter
Abstract:
Continuum robots with structural compliance have promising potential to operate in unstructured environments. However, this structural compliance brings challenges to the controller design due to the existence of considerable uncertainties in the robot and its kinematic model. Typically, a large number of sensors are required to provide the controller the state variables of the robot, including the length of each actuator and position of the robot tip. In this paper, a model-free method based on an adaptive Kalman filter is developed to accomplish path tracking for a continuum robot using only pressures and tip position. As the Kalman filter operates only with a two-step algebraic calculation in every control interval, the low computational load and real-time control capability are guaranteed. By adding an optimal vector to the control law, buckling of the robot can also be avoided. Through simulation analysis and experimental validation, this control method shows good robustness against the system uncertainty and external disturbance, and lowers the number of sensors.
Autors: Minhan Li;Rongjie Kang;David T. Branson;Jian S. Dai;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 286 - 297
Publisher: IEEE
 
» Modeling and Analysis of Magnetic Field Induced Coupling on Embedded STT-MRAM Arrays
Abstract:
Spin transfer torque magnetic random access memory (STT-MRAM) is an emerging memory technology which exhibits nonvolatility, high density, high endurance, and nano-second read and write times. These characteristics make STT-MRAM suitable for last-level cache and other embedded applications. The STT-MRAM bit-cell consists of a magnetic tunnel junction (MTJ) which is composed of two ferromagnetic layers (free and fixed layers) and one insulating layer in between. As STT-MRAM arrays become denser to meet cost and requirements of high performance computing, the distance between adjacent MTJ bits reduces. This aggravates the magnetic coupling from free and fixed layer of one MTJ bit to its neighbors. Even though magnetic coupling is expected to become stronger as MTJ scales down, its impacts on static and dynamic properties on MTJ is relatively unexplored. In this paper, we present a model of the magnetic field coupling in high-density MTJ arrays for three different types of MTJ stacks and evaluate the effect of magnetic field induced coupling on static and dynamic properties. Lastly, we show how process induced variations in MTJ characteristics affect the magnitude of magnetic coupling and their effect on the electrical characteristics of the STT-RAM arrays.
Autors: Insik Yoon;Arijit Raychowdhuryarijit;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Feb 2018, volume: 37, issue:2, pages: 337 - 349
Publisher: IEEE
 
» Modeling and Parameter Extraction for the Metal Surface Roughness Loss Effect on Substrate Integrated Waveguides From S-Parameters
Abstract:
This paper presents a new simple model for representing and characterizing the loss effect introduced by the roughness of the metal-to-dielectric interface on the conductor attenuation of substrate integrated waveguides. The proposal allows for the parameter determination using simple linear regressions which can be implemented directly from S-parameter data and avoids the use of data corresponding to structures with perfectly smooth conductors. In fact, no previous knowledge of the metal surface profile is required to obtain the model parameters. Excellent agreement between full-wave simulations and experimental data at several tens of gigahertz is achieved.
Autors: Gabriela Méndez-Jerónimo;Svetlana C. Sejas-García;Reydezel Torres-Torres;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 875 - 882
Publisher: IEEE
 
» Modeling of an Uncooled CMOS THz Thermal Detector With Frequency-Selective Dipole Antenna and PTAT Temperature Sensor
Abstract:
A thermal THz detector based on commercial CMOS technology working in room temperature is proposed. The THz electromagnetic wave is first selectively absorbed by an on-chip dipole antenna realized in the metallization layer. The absorbed wave energy is then converted to Joule heat energy via a polysilicon resistor. The heat-generated temperature rise is finally detected by a proportional to absolute temperature sensor. The theoretical analysis and physical modeling of the detector including the mechanism of the electromagnetic energy absorption, the thermal conversion, and the electrical circuit response, are presented. The detectors at three typical THz frequencies of 1, 2.9, and 28.3 THz are designed in standard 0.18- CMOS technology and post-simulated to illustrate the detector’s frequency-selective capability in the whole THz range. The simulated detector’s voltage responsivity is 18.0 V/W at 1 THz, 18.9 V/W at 2.9 THz, and 18.6 V/W at 28.3 THz, respectively. The noise equivalent power is Hz at the three frequencies.
Autors: Fei Chen;Jiao Yang;Zimeng Li;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1483 - 1492
Publisher: IEEE
 
» Modeling of Electroporation Induced by Pulsed Electric Fields in Irregularly Shaped Cells
Abstract:
During the past decades, the poration of cell membrane induced by pulsed electric fields has been widely investigated. Since the basic mechanisms of this process have not yet been fully clarified, many research activities are focused on the development of suitable theoretical and numerical models. To this end, a nonlinear, nonlocal, dispersive, and space-time numerical algorithm has been developed and adopted to evaluate the transmembrane voltage and pore density along the perimeter of realistic irregularly shaped cells. The presented model is based on the Maxwell's equations and the asymptotic Smoluchowski's equation describing the pore dynamics. The dielectric dispersion of the media forming the cell has been modeled by using a general multirelaxation Debye-based formulation. The irregular shape of the cell is described by using the Gielis’ superformula. Different test cases pertaining to red blood cells, muscular cells, cell in mitosis phase, and cancer-like cell have been investigated. For each type of cell, the influence of the relevant shape, the dielectric properties, and the external electric pulse characteristics on the electroporation process has been analyzed. The numerical results demonstrate that the proposed model is an efficient numerical tool to study the electroporation problem in arbitrary-shaped cells.
Autors: Luciano Mescia;Michele A. Chiapperino;Pietro Bia;Johan Gielis;Diego Caratelli;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 414 - 423
Publisher: IEEE
 
» Modeling of Inhomogeneous and Lossy Waveguide Components by the Segmentation Technique Combined With the Calculation of Green’s Function by Ewald’s Method
Abstract:
This paper presents a novel algorithm for the analysis of piecewise homogeneous, possibly lossy, waveguide circuits. The algorithm is based on the segmentation technique to split the circuit into homogeneous building blocks, combined with the representation of the generalized admittance matrix (GAM) of each block by the boundary integral-resonant mode expansion (BI-RME) method. The GAMs are then recombined by a circuital cascading procedure. The core of the method is the calculation of the quasi-static Green’s function of a rectangular box, which is required to determine the terms of the BI-RME pole-expansion of the GAM. The expressions of the quasi-static Green’s function, manipulated by Ewald’s technique to improve the convergence, are fully described, and numerical considerations for their efficient and accurate calculation are provided, with a particular focus on the proper selection of the splitting parameter. To demonstrate the correctness of the given formulas, the algorithm is developed and applied in the limited case of circuits segmentable into boxed building blocks. Numerical examples demonstrate the accuracy and efficiency of the proposed technique.
Autors: Marco Bressan;Simone Battistutta;Maurizio Bozzi;Luca Perregrini;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 633 - 642
Publisher: IEEE
 
» Modeling of mmW and THz Imaging Systems Using Conjugate Field Coupling
Abstract:
We propose a novel technique for efficient and robust modeling of multistatic, multidimensional, large-format millimeter-wave/terahertz imaging systems. The proposed method significantly reduces the necessary computational resources for the design of electrically large systems of multiple sensors that acquire multifrequency images, such as imaging radars used in three-dimensional mapping. To alleviate the problem, the radiated and scattered fields are individually computed for the sensor and the target, respectively, using full-wave numerical solvers. Afterward, the fields are properly combined using conjugate field coupling, thus minimizing the necessary computational resources, without compromising solution accuracy. In this letter, the theoretical background of the technique is presented, along with numerical results for beam steering and raster scanning imaging systems.
Autors: Panagiotis C. Theofanopoulos;Georgios C. Trichopoulos;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Feb 2018, volume: 17, issue:2, pages: 213 - 216
Publisher: IEEE
 
» Modeling, Simulation, and Testing of Switching Surge Transients in Rapid Transit Vehicles DC Power Systems
Abstract:
During the operation of dc rapid transit systems, the rail passenger vehicles are subjected to surge transient events that can damage the on-board equipment and cause service interruption. During the testing phase, vehicle manufacturers must demonstrate the performance of the vehicles under the specified transients. However, system testing is generally not available during design. Engineering analysis must be performed to ensure that the design will meet the transient requirements, and that the overvoltage and overcurrent protective devices are coordinated on a system level. In response to these design challenges, detailed time-domain simulation models of a switching surge transient generator and the vehicle equipment have been developed and validated experimentally. These models are used to evaluate vehicle system parameters sensitivity, as well as to provide design guidelines for increased vehicle power system safety, reliability, and availability.
Autors: Maxime Berger;Jean-Pierre Magalhaes Grave;Carl Lavertu;Ilhan Kocar;Jean Mahseredjian;Daniele Ferrara;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 822 - 831
Publisher: IEEE
 
» Moderate Deviation Analysis for Classical-Quantum Channels and Quantum Hypothesis Testing
Abstract:
In this paper, we study the tradeoffs between the error probabilities of classical-quantum channels and the blocklength when the transmission rates approach the channel capacity at a rate lower than , a research topic known as moderate deviation analysis. We show that the optimal error probability vanishes under this rate convergence. Our main technical contributions are a tight quantum sphere-packing bound, obtained via Chaganty and Sethuraman’s concentration inequality in strong large deviation theory, and asymptotic expansions of error-exponent functions. Moderate deviation analysis for quantum hypothesis testing is also established. The converse directly follows from our channel coding result, while the achievability relies on a martingale inequality.
Autors: Hao-Chung Cheng;Min-Hsiu Hsieh;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1385 - 1403
Publisher: IEEE
 
» Modification of Level Dependent ASE-Signal Beat Noise by Optical and Electrical Filtering in Optically Preamplified Direct Detection Receivers
Abstract:
We derive compact equations describing the modification of amplified spontaneous emission signal beat noise arising from optical and electrical filtering in optically preamplified direct detection receivers. In particular, we show that this modification typically results in a further decrease of the signal quality factor. This is particularly pronounced in the presence of electrical filters with steep transfer functions such as, e.g., occurring when feeding the signal through an antialiasing filter prior to analog-to-digital conversion or in a real-time oscilloscope, in the latter case leading to counter-intuitive dependencies of the measured signal quality on the characteristics of the test setup. Predictions are exemplified in concrete system models and verified with experiments. While the modeling assumptions and the accuracy of the predictions are in line with models previously reported in the literature, derived expressions allow straightforwardly tying the modification of the level dependent noise to signal levels, baud rate, signal spectrum, and filter transfer functions.
Autors: J. Witzens;J. Müller;A. Moscoso-Mártir;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 16
Publisher: IEEE
 
» Modified Tensor Locality Preserving Projection for Dimensionality Reduction of Hyperspectral Images
Abstract:
By considering the cubic nature of hyperspectral image (HSI) to address the issue of the curse of dimensionality, we have introduced a tensor locality preserving projection (TLPP) algorithm for HSI dimensionality reduction and classification. The TLPP algorithm reveals the local structure of the original data through constructing an adjacency graph. However, the hyperspectral data are often susceptible to noise, which may lead to inaccurate graph construction. To resolve this issue, we propose a modified TLPP (MTLPP) via building an adjacency graph on a dual feature space rather than the original space. To this end, the region covariance descriptor is exploited to characterize a region of interest around each hyperspectral pixel. The resulting covariances are the symmetric positive definite matrices lying on a Riemannian manifold such that the Log-Euclidean metric is utilized as the similarity measure for the search of the nearest neighbors. Since the defined covariance feature is more robust against noise, the constructed graph can preserve the intrinsic geometric structure of data and enhance the discriminative ability of features in the low-dimensional space. The experimental results on two real HSI data sets validate the effectiveness of our proposed MTLPP method.
Autors: Yang-Jun Deng;Heng-Chao Li;Lei Pan;Li-Yang Shao;Qian Du;William J. Emery;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 277 - 281
Publisher: IEEE
 
» Modular 128-Channel $Delta$ - $Delta Sigma$ Analog Front-End Architecture Using Spectrum Equalization Scheme for 1024-Channel 3-D Neural Recording Microsystems
Abstract:
We report an area- and energy-efficient integrated circuit architecture of a 128-channel -modulated analog front-end (- AFE) for 1024-channel 3-D massive-parallel neural recording microsystems. Our platform has adopted a modularity of 128 channels and consists of eight multi-shank neural probes connected to individual AFEs through interposers in a small form factor. In order to reduce both area and energy consumption in the recording circuits, we implemented a spectrum equalization scheme to take advantage of the inherent spectral characteristics of neural signals, where most of the energy is confined in low frequencies and follows a ~1/f curve in the spectrum. This allows us to implement the AFE with a relaxed dynamic range by ~30 dB, thereby contributing to the significant reduction of both energy and area without sacrificing signal integrity. The - AFE was fabricated using 0.18- CMOS processes. The single-channel AFE consumes 3.05 from 0.5 and 1.0 V supplies in an area of 0.05 mm2 with 63.8-dB signal-to-noise-and-distortion ratio, 3.02 noise efficiency factor (NEF), and 4.56 NEF2VDD. We also have achieved an energy-area product, a figure-of-merit most critical for massive-parallel neural recording systems, of 6.34 fJ/ $text{C}cdot text{s}cdot$ mm2.
Autors: Sung-Yun Park;Jihyun Cho;Kyounghwan Na;Euisik Yoon;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Feb 2018, volume: 53, issue:2, pages: 501 - 514
Publisher: IEEE
 
» Modular Architectures Make You Agile in the Long Run
Abstract:
Researchers have developed ways to think about, visualize, and measure software modularity and its erosion objectively and quantifiably. Using these techniques, you'll be able to determine whether your software is modular and identify complexity hotspots in your code that warrant further investigation.
Autors: Dan Sturtevant;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 104 - 108
Publisher: IEEE
 
» Modular Multilevel Converter DC Fault Protection
Abstract:
High-voltage direct current (HVDC) grids will require the development of dc protections that provide fast fault isolation and minimize the disturbance caused to the existing ac power networks. This paper investigates how the dc fault recovery performance of a half-bridge modular multilevel converter (HB-MMC) is impacted by different dc protection design choices. An HB-MMC point-to-point HVDC system that is protected with dc circuit breakers (CBs) is simulated on a real-time digital simulator using detailed switch models of the converters and switch gear. A dc CB controller has been developed and implemented in a software-in-the-loop fashion, and has been made available free for download. A novel blocking scheme for the HB-MMC is proposed, which limits the prospective dc-side fault current, benefiting dc switch gear. A comparison of circulating current controllers shows that the standard dq controller is likely to be unsuitable for fault studies. Finally, benchmarking shows that a 48% reduction in power-flow recovery time and a 90% reduction in the energy dissipated in the circuit breaker can be achieved, along with other benefits, depending on the protection design.
Autors: O. Cwikowski;H. R. Wickramasinghe;G. Konstantinou;J. Pou;M. Barnes;R. Shuttleworth;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 291 - 300
Publisher: IEEE
 
» Moisture Prevention in a Pre-Purged Front-Opening Unified Pod (FOUP) During Door Opening in a Mini-Environment
Abstract:
Contamination in a wafer transportation box [e.g., a front-opening unified pod (FOUP)] can influence device yield and performance. Additional precautions might be required to prevent outside contamination during FOUP door opening. This paper experimentally examines moisture evolution in a pre-purged FOUP with an open door in a mini-environment. Air curtains of different widths () were employed to prevent outside moisture intrusion, and their performance was compared with that of a conventional purge method. Clean dry air was used as the supplied gas in experiments. A moisture prevention index (MPI) was further introduced as a tool for interpreting results. When the conventional purge method was used, moisture in the mini-environment was rapidly transferred into the FOUP, and relative humidity (RH) reached approximately the same levels as the mini-environment, indicating poor moisture prevention performance. RH values were much lower when the air curtain was used. The best moisture prevention performance was observed for a system using an air curtain with mm. The MPIs for the conventional purge method were approximately 8.0%–8.4%, whereas those for the air curtain application ranged from 40%–100%. Most importantly, the MPIs for and 70 mm reached or exceeded 90%.
Autors: Tee Lin;Ben-Ran Fu;Shih-Cheng Hu;Yi-Han Tang;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 108 - 115
Publisher: IEEE
 
» Monitoring of Historical Glacier Recession in Yulong Mountain by the Integration of Multisource Remote Sensing Data
Abstract:
Yulong Mountain, which is the southernmost snowcapped mountain in mainland Eurasia, has been confronted with significant glacier recession in the last decades due to global climate warming. The recession of these small-scale monsoonal temperate glaciers is a sensitive indicator of global warming. However, there have been few studies that have comprehensively monitored the historical glacier recession in Yulong Mountain area. This paper integrates multisource remote sensing data to monitor the glacial status on Yulong Mountain between 1957 and 2009. Integrating a topographic map, the long-term observed Landsat TM/ETM+ images, and multitemporal digital elevation model datasets, both the area change and regional mass balance of the Yulong glaciers are analyzed. According to the results, the area of the Yulong glaciers decreased from 11.57 to 4.55 km2 at a rate of −0.14 km2 yr−1 over the last 52 years between 1957 and 2009. The 1987–1999 specific mass balance was −0.31 ± 0.33 m yr−1 water equivalent, while the 1987–2008 mass balance was −0.27 ± 0.35 m yr−1 water equivalent. It can be interpreted from the results that the Yulong glaciers have experienced persistent glacier recession during the last decades. The glacier melting is still significant due to the continuously rising temperature. Furthermore, spatially heterogeneous glacier recession has been observed in this area. The glacier changes are spatially varied, which is probably due to the local temperature and precipitation, the glacier sizes, the terminus altitudes, and terrain factors. The influencing elements interacted with each other, and the climate conditions are the dominant factors affecting glacier status.
Autors: Linwei Yue;Huanfeng Shen;Wei Yu;Liangpei Zhang;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 388 - 400
Publisher: IEEE
 
» Monolithic Red/Green/Blue Micro-LEDs With HBR and DBR Structures
Abstract:
In this letter, monolithic red, green, and blue (RGB) micro light-emitting diodes (LEDs) were fabricated using gallium nitride based blue micro LEDs and quantum dots (QDs). Red and green QDs were sprayed onto individual region surrounded by patterned black matrix photoresist on the blue micro LEDs to form color conversion layers. Owing to its light-blocking capability, the patterned black matrix photoresist improved the contrast ratio of the micro LEDs from 11 to 22. To enhance the color conversion efficiency and the light output intensity, a hybrid Bragg reflector (HBR) was deposited on the bottom side of the monolithic RGB micro LEDs, thus reflecting the RGB light emitted to the substrate. To further improve the color purity of the red and green light, a distributed Bragg reflector (DBR) with high reflection for the blue light was deposited on the top side of the QDs/micro LEDs. The red and green light output intensities of the micro LEDs with HBR and DBR were enhanced by about 27%.
Autors: Guan-Syun Chen;Bo-Yu Wei;Ching-Ting Lee;Hsin-Ying Lee;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:3, pages: 262 - 265
Publisher: IEEE
 
» More documentaries for engineers [Resources Reviews]
Abstract:
Last August, IEEE Spectrum plucked three films from the video deluge that we felt were particularly suited for engineers. Now, we've waded back in to bring you three more apropos documentaries that have recently become available to stream or download.
Autors: Stephen Cass;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 22 - 22
Publisher: IEEE
 
» MoTe2: A Promising Candidate for SF6 Decomposition Gas Sensors With High Sensitivity and Selectivity
Abstract:
In this letter, we took a first principles calculation of five SF6 decomposition gas molecules (SO2, H2 S, SOF2, SO2F2, and SF6) adsorption on monolayer MoTe2. By calculating adsorption energy, charge transfer, and work function combined with differential charge density analysis, we predict that MoTe2 is sensitive and selective to the SO2 molecule. Furthermore, the total density of states analysis and projected density of states analysis demonstrate that the orbital hybridization is the main reason of the intense charge transfer between the SO2 molecule and monolayer MoTe2. In summary, it can be concluded that MoTe2 is a promising candidate for SF6 decomposition gas sensors with high sensitivity and selectivity.
Autors: Da-Wei Wang;Xiao-Hua Wang;Ai-Jun Yang;Ji-Feng Chu;Pin-Lei Lv;Yang Liu;Ming-Zhe Rong;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 292 - 295
Publisher: IEEE
 
» Motion-Based Rapid Serial Visual Presentation for Gaze-Independent Brain-Computer Interfaces
Abstract:
Most event-related potential (ERP)-based brain–computer interface (BCI) spellers primarily use matrix layouts and generally require moderate eye movement for successful operation. The fundamental objective of this paper is to enhance the perceptibility of target characters by introducing motion stimuli to classical rapid serial visual presentation (RSVP) spellers that do not require any eye movement, thereby applying them to paralyzed patients with oculomotor dysfunctions. To test the feasibility of the proposed motion-based RSVP paradigm, we implemented three RSVP spellers: 1) fixed-direction motion (FM-RSVP); 2) random-direction motion (RM-RSVP); and 3) (the conventional) non-motion stimulation (NM-RSVP), and evaluated the effect of the three different stimulation methods on spelling performance. The two motion-based stimulation methods, FM- and RM-RSVP, showed shorter P300 latency and higher P300 amplitudes (i.e., 360.4–379.6 ms; 5.5867–) than the NM-RSVP (i.e., 480.4 ms; ). This led to higher and more stable performances for FM- and RM-RSVP spellers than NM-RSVP speller (i.e., 79.06±6.45% for NM-RSVP, 90.60±2.98% for RM-RSVP, and 92.74±2.55% for FM-RSVP). In particular, the proposed motion-based RSVP paradigm was significantly beneficial for about half of the subjects who might not accurately perceive rapidly presented static stimuli. These results indicate that the use of proposed motion-based RSVP paradigm is more beneficial for target recognition when developing BCI applications for severely paralyzed patients with com- lex ocular dysfunctions.
Autors: Dong-Ok Won;Han-Jeong Hwang;Dong-Min Kim;Klaus-Robert Müller;Seong-Whan Lee;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Feb 2018, volume: 26, issue:2, pages: 334 - 343
Publisher: IEEE
 
» Moving Point Target Detection Based on Higher Order Statistics in Very Low SNR
Abstract:
This letter presents an approach for the detection of moving point targets on high-frame-rate image sequences with low spatial resolution and low SNR based on higher order statistical theory. We propose a novel method for analyzing the time-domain evolution of image data for distinguishing between the background and the target in situations when the spatial signal of the target is swamped by noise. Our method is formulated to detect a time-domain transient signal of unknown scale and arrival time in noisy background. We proposed a bispectrum-based model to characterize the temporal behavior of pixels, and the detection ability under different frame rates and SNRs is analyzed. The method is evaluated using both simulated and real-world data, and we provide a comparison to other widely used point target detection approaches. Our experimental results demonstrate that our algorithm can efficiently detect extremely low SNR targets that are virtually invisible to humans based on time-domain analysis of image sequences.
Autors: Wenlong Niu;Wei Zheng;Zhen Yang;Yong Wu;Balazs Vagvolgyi;Bo Liu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 217 - 221
Publisher: IEEE
 
» MTT-S Wireless Power Transfer Conference 2017 [Conference Reports]
Abstract:
Presents information on the 2017 MTT-S Wireless Power Transfer Conference.
Autors: Heng-Ming Hsu;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 127 - 128
Publisher: IEEE
 
» Multi-Channel Resource Allocation Toward Ergodic Rate Maximization for Underlay Device-to-Device Communications
Abstract:
In underlay device-to-device (D2D) communications, a D2D pair reuses the cellular spectrum causing interference to regular cellular users. Maximizing the performance of underlay D2D communications requires joint consideration for the achieved D2D rate and the interference to cellular users. In this paper, we consider the D2D power allocation optimization over multiple resource blocks (RBs), aimed at maximizing either the ergodic D2D rate or the ergodic sum rate of D2D and cellular users, under the long-term sum-power constraint of the D2D users and per-RB probabilistic signal-to-interference-and-noise (SINR) requirements for all cellular users. We formulate stochastic optimization problems for D2D power allocation over time. The proposed optimization framework is applicable to both uplink and downlink cellular spectrum sharing. To solve the proposed stochastic optimization problems, we first convexify the problems by introducing a family of convex constraints as a replacement for the non-convex probabilistic SINR constraints. We then present two dynamic power allocation algorithms: a Lagrange dual-based algorithm that is optimal but with a high computational complexity and a low-complexity heuristic algorithm based on dynamic time averaging. Through simulation, we show that the performance gap between the optimal and heuristic algorithms is small, and the effective long-term stochastic D2D power optimization over the shared RBs can lead to substantial gains in the ergodic D2D rate and the ergodic sum rate.
Autors: Ruhallah AliHemmati;Min Dong;Ben Liang;Gary Boudreau;S. Hossein Seyedmehdi;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1011 - 1025
Publisher: IEEE
 
» Multi-Perspective Tracking for Intelligent Vehicle
Abstract:
The multi-camera array has drawn attention of researchers in recent years, and has been configured and deployed on intelligent vehicle to capture the panoramic views. Understanding surroundings is crucial for the ego-vehicle. This paper presents a Multi-perspective Tracking (MPT) framework for intelligent vehicle. An iterative search procedure is proposed to associate detections and tracklets in different perspectives. This procedure iteratively assigns determined states and estimates non-determined states for the detections and tracklets. An inherent determined and non-determined graph is utilized to reinforce this procedure. For more reliable associations between perspectives, a Siamese convolutional neural network is employed to learn feature representation. The supervised classification and verification signals are added to train the network. The features in different conventional stages are integrated together as the discriminative appearance model. The experiments are conducted on a MPT data set with five perspectives. The proposed framework is tested in each pair of adjacent perspectives for the ability to associate target objects between perspectives.
Autors: Xiangyang Ji;Guanwen Zhang;Xiaogang Chen;Qi Guo;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 518 - 529
Publisher: IEEE
 
» Multi-Rate Acquisition for Dead Time Reduction in Magnetic Resonance Receivers: Application to Imaging With Zero Echo Time
Abstract:
For magnetic resonance imaging of tissues with very short transverse relaxation times, radio-frequency excitation must be immediately followed by data acquisition with fast spatial encoding. In zero-echo-time (ZTE) imaging, excitation is performed while the readout gradient is already on, causing data loss due to an initial dead time. One major dead time contribution is the settling time of the filters involved in signal down-conversion. In this paper, a multi-rate acquisition scheme is proposed to minimize dead time due to filtering. Short filters and high output bandwidth are used initially to minimize settling time. With increasing time since the signal onset, longer filters with better frequency selectivity enable stronger signal decimation. In this way, significant dead time reduction is accomplished at only a slight increase in the overall amount of output data. Multi-rate acquisition was implemented with a two-stage filter cascade in a digital receiver based on a field-programmable gate array. In ZTE imaging in a phantom and in vivo, dead time reduction by multi-rate acquisition is shown to improve image quality and expand the feasible bandwidth while increasing the amount of data collected by only a few percent.
Autors: Josip Marjanovic;Markus Weiger;Jonas Reber;David O. Brunner;Benjamin E. Dietrich;Bertram J. Wilm;Romain Froidevaux;Klaas P. Pruessmann;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 408 - 416
Publisher: IEEE
 
» Multi-Scale and Frequency-Dependent Modeling of Electric Power Transmission Lines
Abstract:
A frequency-dependent transmission line model for multi-scale simulation of diverse transients over a wide range of frequencies is developed, implemented, and validated. It makes use of the concept of frequency-adaptive simulation of transients in which the Fourier spectra are adaptively shifted in the frequency domain to reduce the discretization time-steps in the time domain. The transients are modeled through dynamic phasors comprising the real and imaginary parts of analytic signals to facilitate the frequency shifting. In the proposed line model, all mathematical operations such as numerical recursive convolutions are, therefore, expressed in terms of analytic signals. A modal decomposition is performed to attain decoupled modes for the multi-phase case. The transition from the representation of electromagnetic traveling waves with time-steps below the wave propagation time to the tracking of slower electromechanical transients at time-steps above the wave propagation time is achieved by the automatic insertion of a -segment to represent the galvanic coupling within one time-step. Accurate and efficient simulation of both electromagnetic and electromechanical transients within a simulation run is so supported. The validation is verified through comparison with a staged field test covering the diverse transients of line energization, transient recovery voltage, and steady state.
Autors: Hua Ye;Kai Strunz;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 32 - 41
Publisher: IEEE
 
» Multi-Scale Segmentation and Surface Fitting for Measuring 3-D Macular Holes
Abstract:
Macular holes are blinding conditions, where a hole develops in the central part of retina, resulting in reduced central vision. The prognosis and treatment options are related to a number of variables, including the macular hole size and shape. High-resolution spectral domain optical coherence tomography allows precise imaging of the macular hole geometry in three dimensions, but the measurement of these by human observers is time-consuming and prone to high inter- and intra-observer variability, being characteristically measured in 2-D rather than 3-D. We introduce several novel techniques to automatically retrieve accurate 3-D measurements of the macular hole, including: surface area, base area, base diameter, top area, top diameter, height, and minimum diameter. Specifically, we introduce a multi-scale 3-D level set segmentation approach based on a state-of-the-art level set method, and we introduce novel curvature-based cutting and 3-D measurement procedures. The algorithm is fully automatic, and we validate our extracted measurements both qualitatively and quantitatively, where our results show the method to be robust across a variety of scenarios. Our automated processes are considered a significant contribution for clinical applications.
Autors: Amar V. Nasrulloh;Chris G. Willcocks;Philip T. G. Jackson;Caspar Geenen;Maged S. Habib;David H. W. Steel;Boguslaw Obara;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 580 - 589
Publisher: IEEE
 
» Multi-Target Regression via Robust Low-Rank Learning
Abstract:
Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.
Autors: Xiantong Zhen;Mengyang Yu;Xiaofei He;Shuo Li;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 497 - 504
Publisher: IEEE
 
» Multi-Touch in the Air: Concurrent Micromovement Recognition Using RF Signals
Abstract:
The human–computer interactions have moved from the conventional approaches of entering inputs into the keyboards/touchpads to the brand-new approaches of performing interactions in the air. In this paper, we propose RF-glove, a system that recognizes concurrent multiple finger micromovement using RF signals, so as to realize the vision of “multi-touch in the air.” It uses a commercial-off-the-shelf (COTS) RFID reader with three antennas and five COTS tags attached to the five fingers of a glove, one tag per finger. During the process of a user performing finger micromovements, we let the RFID reader continuously interrogate these tags and obtain the backscattered RF signals from each tag. For each antenna–tag pair, the reader obtains a sequence of RF phase values called a phase profile from the tag’s responses over time. To tradeoff between accuracy and robustness in terms of matching resolution, we propose a two phase approach, including coarse-grained filtering and fine-grained matching. To tackle the variation of template phase profiles at different positions, we propose a phase-model-based solution to reconstruct the template phase profiles based on the exact locations. Experiment results show that we achieve an average accuracy of 92.1% under various moving speeds, orientation deviations, and so on.
Autors: Lei Xie;Chuyu Wang;Alex X. Liu;Jianqiang Sun;Sanglu Lu;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 231 - 244
Publisher: IEEE
 
» Multi-User Computation Offloading in Mobile Edge Computing: A Behavioral Perspective
Abstract:
By providing cloud computing capabilities at the network edge in proximity of mobile device users, mobile edge computing offers an effective solution to help mobile devices with computation- intensive and delay-sensitive tasks. In this article, we investigate the multi-user computation offloading problem in an uncertain wireless environment. Most of the existing works assume that mobile device users are rational and make offloading decisions to maximize their expected objective utilities. However, in practice, users tend to have subjective perceptions under uncertainty, such that their behavior deviates considerably from the conventional rationality assumption. Drawing on the framework of prospect theory (PT), we formulate users' decision making of whether to offload or not as a PT-based non-cooperative game. We propose a distributed computation offloading algorithm to achieve the Nash equilibrium of the game. Numerical results assess the impact of mobile device users' behavioral biases on offloading decision making.
Autors: Ling Tang;Shibo He;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 48 - 53
Publisher: IEEE
 
» Multiagent-Based Flexible Edge Computing Architecture for IoT
Abstract:
This article presents a proposal for FLEC architecture, which solves problems resulting from the rigidity of the traditional IoT architecture and edge computing. FLEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. We utilize COSAP, a system configuration platform based on a multiagent framework, as an implementation procedure for FLEC architecture. Furthermore, this article presents its application case study of a healthcare support system for a sports event with many participants. Finally, we demonstrate the contribution of this proposed architecture to problem solution in edge computing.
Autors: Takuo Suganuma;Takuma Oide;Shinji Kitagami;Kenji Sugawara;Norio Shiratori;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 16 - 23
Publisher: IEEE
 
» Multibeam Focal Plane Arrays With Digital Beamforming for High Precision Space-Borne Ocean Remote Sensing
Abstract:
The present-day ocean remote sensing instruments that operate at low microwave frequencies are limited in spatial resolution and do not allow for monitoring of the coastal waters. This is due to the difficulties of employing a large reflector antenna on a satellite platform, and generating high-quality pencil beams at multiple frequencies. Recent advances in digital beamforming focal-plane arrays (FPAs) have been exploited in this paper to overcome the above problems. A holistic design procedure for such novel multibeam radiometers has been developed, where: 1) the antenna system specifications are derived directly from the requirements to oceanographic surveys for future satellite missions and 2) the numbers of FPA elements/receivers are determined through a dedicated optimum beamforming procedure minimizing the distance to coast. This approach has been applied to synthesize FPAs for two alternative radiometer systems: a conical scanner with an offset parabolic reflector and a stationary wide-scan torus reflector system, each operating at -, -, and Ku-bands. Numerical results predict excellent beam performance for both systems with as low as 0.14% total received power over the land.
Autors: Oleg A. Iupikov;Marianna V. Ivashina;Niels Skou;Cecilia Cappellin;Knud Pontoppidan;Cornelis G. M. van ’t Klooster;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 737 - 748
Publisher: IEEE
 
» Multicore fibers for high-capacity submarine transmission systems
Abstract:
Applications of multicore fibers (MCFs) in undersea transmission systems are investigated, and various potential architectures of branching units for MCF-based undersea transmission systems are presented. Some MCF-based submarine network architectures based on the amount of data traffic are also proposed. It is shown how different architectures of branching units affect the number of network components. The effects of intercore crosstalk on the network components are also investigated.
Autors: Md. Nooruzzaman;Toshio Morioka;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A175 - A184
Publisher: IEEE
 
» Multidevice Map-Constrained Fingerprint-Based Indoor Positioning Using 3-D Ray Tracing
Abstract:
This paper studies the use of deterministic channel modeling through 3-D ray tracing (RT) for constructing device-independent radiomaps for Wi-Fi RSSI-based fingerprinting indoor positioning, applicable to different devices. Device heterogeneity constitutes a limitation in fingerprint-based approaches and also constructing radiomaps through extensive in situ measurement campaigns is laborious and time-consuming even with a single device let alone the need for radiomaps constructed using multiple different devices. This paper tackles both challenges through the use of 3-D RT for radiomap generation in conjunction with data calibration using a small set of device-specific measurements to make the radiomap device independent. The efficiency of this approach is evaluated using simulations and measurements in terms of the time spent to generate the radiomap, the amount of device-specific data required for calibration, and in terms of the achievable positioning accuracy. Potential accuracy improvements in the RT-based indoor positioning process are further investigated, by studying the use of map constraints into the algorithm in the form of a priori probabilities. In this approach, a route probability factor (RPF), which reflects the likelihood of a user being in various locations inside the environment is used. The outcome of the evaluation process, which includes a study of different RPF distributions, indicates the validity of the approach, demonstrated by a reduction in the positioning error for various devices. The versatility of this approach is also demonstrated for different scenarios, different devices, and by considering different device-handling conditions.
Autors: Marios Raspopoulos;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 466 - 476
Publisher: IEEE
 
» Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method
Abstract:
Conventional supervised content-based remote sensing (RS) image retrieval systems require a large number of already annotated images to train a classifier for obtaining high retrieval accuracy. Most systems assume that each training image is annotated by a single label associated to the most significant semantic content of the image. However, this assumption does not fit well with the complexity of RS images, where an image might have multiple land-cover classes (i.e., multilabels). Moreover, annotating images with multilabels is costly and time consuming. To address these issues, in this paper, we introduce a semisupervised graph-theoretic method in the framework of multilabel RS image retrieval problems. The proposed method is based on four main steps. The first step segments each image in the archive and extracts the features of each region. The second step constructs an image neighborhood graph and uses a correlated label propagation algorithm to automatically assign a set of labels to each image in the archive by exploiting only a small number of training images annotated with multilabels. The third step associates class labels with image regions by a novel region labeling strategy, whereas the final step retrieves the images similar to a given query image by a subgraph matching strategy. Experiments carried out on an archive of aerial images show the effectiveness of the proposed method when compared with the state-of-the-art RS content-based image retrieval methods.
Autors: Bindita Chaudhuri;Begüm Demir;Subhasis Chaudhuri;Lorenzo Bruzzone;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 1144 - 1158
Publisher: IEEE
 
» Multilayer Millimeter-Wave MCMs [From the Guest Editors' Desk]
Abstract:
After a brief review of the state of the art, this focus issue on multilayer millimeter-wave (mmW) multichip modules (MCMs) presents four cover features that showcase the evolution in some key areas of multilayer mmW MCM integration and packaging technologies: advanced interconnects, integration techniques, components, and systems that use additive as well as substructure manufacturing technologies aimed toward making next-generation mmW applications feasible. The first two features provide an overview of state-of-the-art multilayer ceramic-based multichip module and packaging techniques, while the third and fourth features are more specific: one describing SiP eWLB packaging techniques and the other covering recent developments in inkjet and 3-D printed components and subsystems using additive manufacturing technologies.
Autors: Kamal K. Samanta;Dietmar Kissinger;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 20 - 135
Publisher: IEEE
 
» Multimodal Forecasting Methodology Applied to Industrial Process Monitoring
Abstract:
Industrial process modeling represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, accurate models of critical signals need to be designed in order to forecast process deviations. In this work, a novel multimodal forecasting methodology based on adaptive dynamics packaging and codification of the process operation is proposed. First, a target signal is decomposed by means of the empirical mode decomposition in order to identify the characteristic intrinsic mode functions. Second, such dynamics are packaged depending on their significance and modeling complexity. Third, the operating condition of the considered process, reflected by available auxiliary signals, is codified by means of a self-organizing map and presented to the modeling structure. The forecasting structure is supported by a set of ensemble adaptive-neurofuzzy-inference-system-based models, each one being focused on a different set of signal dynamics. The performance and effectiveness of the proposed method are validated experimentally with industrial data from a copper rod manufacturing plant and performance comparison with classical approaches. The proposed method shows improved performance and generalization over classical single-model approaches.
Autors: Daniel Zurita;Miguel Delgado;Jesus A. Carino;Juan A. Ortega;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 494 - 503
Publisher: IEEE
 
» Multimodal Measurements Fusion for Surface Material Categorization
Abstract:
Sound and acceleration measurements are two classes of sensing modalities which frequently occur in surface material categorization. Their fusion problem is extremely important in many practical scenarios, since they provide different properties about materials. In this paper, we investigate the multimodal measurements fusion categorization problem exhibiting nontrivial challenges that there does not exist sample-to-sample pairing relation between sound and acceleration measurements. To this end, we design a dictionary learning model that can simultaneously learn the projection subspace and the latent common dictionary for the different measurements. Furthermore, an optimization algorithm is developed to effectively solve the common dictionary learning problem. Based on the obtained solutions, the fusion categorization algorithm can be easily developed. Finally, we perform experimental validations on the publicly available data set to show the effectiveness of the proposed method.
Autors: Huaping Liu;Fuchun Sun;Bin Fang;Shan Lu;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 246 - 256
Publisher: IEEE
 
» Multiobjective Optimal Sizing of Hybrid Energy Storage System for Electric Vehicles
Abstract:
Energy storage system (ESS) is an essential component of electric vehicles, which largely affects their driving performance and manufacturing cost. A hybrid energy storage system (HESS) composed of rechargeable batteries and ultracapacitors shows a significant potential for maximally exploiting their complementary characteristics. This study focuses on optimal HESS sizing of an example electric vehicle using a multi-objective optimization algorithm, with the overarching goal of reducing the ESS cost while prolonging battery life. To this end, a battery state-of-health model is incorporated to quantitatively investigate the impact of component sizing on battery life. The wavelet-transform-based power management algorithm is adopted to realize the power coordination between the batteries and ultracapacitors, in which the ultracapacitors are responsible for handling high-frequency power transients, whereas the batteries deal with average power leveling. The Urban Dynamometer Driving Schedule is used to represent real power demands.
Autors: Lei Zhang;Xiaosong Hu;Zhenpo Wang;Fengchun Sun;Junjun Deng;David. G. Dorrell;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1027 - 1035
Publisher: IEEE
 
» Multiobjective Optimization Design for Electrically Large Coverage: Fragment-Type Near-Field/Far-Field UHF RFID Reader Antenna Design
Abstract:
The design of an ultrahigh-frequency (UHF) radio-frequency identification (RFID) reader antenna covering an electrically large near-field area is challenging for near-field UHF RFID applications. In such a design, magnetic field distribution on a large coverage area is required to be as uniform as possible. For some specific UHF near-field RFID applications, given radiation pattern characteristics are expected. A fragment-type wire structure is quite suitable for these demands because uniform magnetic field distribution and given patterns could be generated through optimizing the fragmented wires in a designated electrically large area to obtain corresponding current distribution. In this article, the concept of a fragment-type structure as well as some design guidelines are reviewed and summarized. Then, two omnidirectional fragment-type wire antennas with different cell size and two directional fragment-type wire antennas are designed. Both simulation and experiment results show that there is no reading null within an electrically large near-field zone having a perimeter of four operating wavelengths at 915 MHz (i.e., 320 mm x 320 mm). The omnidirectional designs are promising in the applications of UHF near-field RFID tag detection in self-confined volumes, and the directional designs are potential in the systems of UHF near-field/far-field RFID.
Autors: Dawei Ding;Jing Xia;Lixia Yang;Xiaodong Ding;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Feb 2018, volume: 60, issue:1, pages: 27 - 37
Publisher: IEEE
 
» Multipartite Quantum Key Agreement Over Collective Noise Channels
Abstract:
In this paper, two classes of multiparticle entangled states are constructed to resist against the collective-dephasing noise and collective-rotation noise, respectively. Based on it, two new multipartite quantum key agreement protocols over the collective noise are presented. In each protocol, only one user needs to prepare the multiparticle quantum entangled state. Then, the user keeps the first qubit, and distributes each two qubits of the state to other users. In this case, all users can perform the security test and derive the shared key from the measurement outcomes of the qubits in their hands. From the security analysis, it is evident that the presented protocols are secure against the inside attack and some common outside attacks.
Autors: Binbin Cai;Gongde Guo;Song Lin;Huijuan Zuo;Chaohua Yu;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 11
Publisher: IEEE
 
» Multipath Maximum Likelihood Probabilistic Multihypothesis Tracker for Low Observable Targets
Abstract:
In many practical scenarios with multipath propagation, one target may generate multiple detections in one scan. Proper use of multipath-induced measurements can improve the detection of very low observable (VLO) targets. In this paper, a true multitarget tracker, the joint multipath maximum likelihood probabilistic multihypothesis tracker (JMP-ML-PMHT) is proposed to address this problem. The standard ML-PMHT is extended to incorporate multipath detections and jointly track multiple VLO targets. The Cramer–Rao lower bound with multipath detections is derived. Simulation results with an over-the-horizon-radar scenario show that the JMP-ML-PMHT can detect and track multiple VLO targets by effectively utilizing the information in multipath measurements.
Autors: X. Tang;Q. Wu;R. Tharmarasa;T. Kirubarajan;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 502 - 510
Publisher: IEEE
 
» Multipoint Fiber Bragg Grating Sensing Using Two-Photon Absorption Process in Silicon Avalanche Photodiode
Abstract:
We propose a multipoint fiber Bragg grating (FBG) sensing system that measures both spectral change of FBGs and precise distance to them by using intensity-modulated light and two-photon absorption process in a silicon avalanche photodiode. We experimentally confirm the principle using five cascaded FBGs with almost the same Bragg wavelength. The optical path length difference and the reflection spectrum for each FBG are successfully measured at the same time. The relative uncertainty of path length measurement is in the order of 10−4.
Autors: Yosuke Tanaka;Hiromasa Miyazawa;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 1032 - 1038
Publisher: IEEE
 
» Multiport Pixel Rectenna for Ambient RF Energy Harvesting
Abstract:
We describe the design of a multiport pixel rectenna for ambient radio-frequency (RF) energy harvesting consisting of an optimized triple-port pixel antenna and a triple-port rectifier with dc combining. The advantages of the multiport pixel approach include enhanced harvested RF power for a given area as well as a reduction in the antenna matching requirements. We formulate the design of the triple-port pixel antenna as a binary optimization problem with an objective function related to harvested RF power in the GSM-1800 band for specified power angular spectrums without the need for antenna matching components. The optimization of the triple-port pixel antenna is obtained by using successive exhaustive Boolean optimization. The design for the triple-port rectifier with dc combining is also provided and a prototype is demonstrated. The rectenna measurement demonstrates that the proposed triple-port pixel antenna has dc output power over double that of single-port-based antennas of similar size. The overall RF-to-dc efficiency of the multiport pixel rectenna is also evaluated and shown to be 19% when the total input RF power is −20 dBm. The effects of nonuniformity in the input RF power across antenna ports are also investigated.
Autors: Shanpu Shen;Chi-Yuk Chiu;Ross D. Murch;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 644 - 656
Publisher: IEEE
 
» Multisensor Data-Fusion-Based Approach to Airspeed Measurement Fault Detection for Unmanned Aerial Vehicles
Abstract:
Fault detection (FD) plays an important role in guaranteeing system safety and reliability for unmanned aerial vehicles (UAVs). This paper focuses on developing an alternative approach to FD for airspeed sensor in UAVs by using data from gyros, accelerometers, global positioning system, and wind vanes. Based on the kinematics model of the UAV, an estimator is proposed to provide analytical redundancy using information from the above-mentioned sensors, which are commonly implemented on UAVs. This filter process is independent of the airspeed measurement and the aircraft dynamics model. Furthermore, we employ the observability rank criterion based on Lie derivatives and prove that the nonlinear system describing the airspeed kinematics is observable. The test and cumulative sum detector are employed to detect the occurrence of airspeed measurement faults together. Finally, the performance of the proposed methodology has been evaluated through flight experiments of UAVs.
Autors: Dingfei Guo;Maiying Zhong;Donghua Zhou;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 317 - 327
Publisher: IEEE
 
» Multisource Remote Sensing Data Classification Based on Convolutional Neural Network
Abstract:
As a list of remotely sensed data sources is available, how to efficiently exploit useful information from multisource data for better Earth observation becomes an interesting but challenging problem. In this paper, the classification fusion of hyperspectral imagery (HSI) and data from other multiple sensors, such as light detection and ranging (LiDAR) data, is investigated with the state-of-the-art deep learning, named the two-branch convolution neural network (CNN). More specific, a two-tunnel CNN framework is first developed to extract spectral-spatial features from HSI; besides, the CNN with cascade block is designed for feature extraction from LiDAR or high-resolution visual image. In the feature fusion stage, the spatial and spectral features of HSI are first integrated in a dual-tunnel branch, and then combined with other data features extracted from a cascade network. Experimental results based on several multisource data demonstrate the proposed two-branch CNN that can achieve more excellent classification performance than some existing methods.
Autors: Xiaodong Xu;Wei Li;Qiong Ran;Qian Du;Lianru Gao;Bing Zhang;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 937 - 949
Publisher: IEEE
 
» Multivariate Alarm Systems for Time-Varying Processes Using Bayesian Filters With Applications to Electrical Pumps
Abstract:
Alarm systems are critically important for safety and efficiency of industrial plants. However, many alarm variables in contemporary alarm systems are generated in a way being isolated from related process variables, resulting in false and missing alarms. This paper is motivated by abnormality detection for condensate-water electrical pumps in thermal power plants and proposes a method to design multivariate alarm systems for time-varying processes. A novel feature to distinguish normal and abnormal conditions is observed on the variation rates of multiple linear regression model parameters. A model estimator based on Bayesian filters is formulated to track the variations of model parameters in normal conditions, and not to do so in abnormal conditions so that absolute cumulative modeling errors are large enough to raise alarms. The effectiveness of the proposed method is validated by industrial case studies.
Autors: Wanqi Xiong;Jiandong Wang;Kuang Chen;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 504 - 513
Publisher: IEEE
 
» Multiview Intensity-Based Active Learning for Hyperspectral Image Classification
Abstract:
In remote sensing image classification, active learning aims to learn a good classifier as best as possible by choosing the most valuable (informative and representative) training samples. Multiview is a concept that regards analyzing the same object from multiple different views. Generally, these views show diversity and complementarity of features. In this paper, we propose a new multiview active learning (MVAL) framework for hyperspectral image classification. First, we generate multiple views by extracting different attribute components from the same image data. Specifically, we adopt the multiple morphological component analysis to decompose the original image into multiple pairs of attribute components, including content, coarseness, contrast, and directionality, and the smooth component from each pair is chosen as one single view. Second, we construct two multiview intensity-based query strategies for active learning. On the one hand, we exploit the intensity differences of multiple views along with the samples’ uncertainty to choose the most informative candidates. On the other hand, we consider the clustering distribution of all unlabeled samples, and query the most representative candidates in addition to the highly informative ones. Our experiments are performed on four benchmark hyperspectral image data sets. The obtained results show that the proposed MVAL framework can lead to better classification performance than the traditional, single-view active learning schemes. In addition, compared with the conventional disagree-based MVAL scheme, the proposed query selection strategies show competitive classification accuracy.
Autors: Xiang Xu;Jun Li;Shutao Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 669 - 680
Publisher: IEEE
 
» Multiview Rectification of Folded Documents
Abstract:
Digitally unwrapping images of paper sheets is crucial for accurate document scanning and text recognition. This paper presents a method for automatically rectifying curved or folded paper sheets from a few images captured from multiple viewpoints. Prior methods either need expensive 3D scanners or model deformable surfaces using over-simplified parametric representations. In contrast, our method uses regular images and is based on general developable surface models that can represent a wide variety of paper deformations. Our main contribution is a new robust rectification method based on ridge-aware 3D reconstruction of a paper sheet and unwrapping the reconstructed surface using properties of developable surfaces via conformal mapping. We present results on several examples including book pages, folded letters and shopping receipts.
Autors: Shaodi You;Yasuyuki Matsushita;Sudipta Sinha;Yusuke Bou;Katsushi Ikeuchi;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 505 - 511
Publisher: IEEE
 
» Multiyear Trans-Horizon Radio Propagation Measurements at 3.5 GHz
Abstract:
The design, realization, and measurement results of a high-accuracy multiyear 3.5 GHz trans-horizon radio propagation measurement system are discussed, with both emphasis on the results and implemented technical measures to enhance the accuracy and overall reliability of the measurements. The propagation measurements have been performed on two different paths of 253 and 234 km length, using two transmitters and one receiver in the period September 2013 till November 2016. One of the paths travels over wetland; the other path can be considered as a land path. On each path, an additional transmitter is placed at 107 km (in the 253 km path) and 84 km (in the 234 km path) from the receiver. With this arrangement, the correlation between two nonaligned paths of comparable length, and two aligned paths of dissimilar length, was studied. The measurements show that for the land path, the predicted ITU-R P.452-16 cumulative distribution function (CDF) typically shows 5 dB higher path loss than the actual measured CDF for the region of interest; anomalous propagation. This means that the measured signal is on average weaker than predicted (a higher path loss). For the wetland path, the actual CDF is very close to the predicted CDF. Also, the measurements reveal that typically 30% of the anomalous propagation occurrences are correlated with other paths.
Autors: Loek C. Colussi;Roel Schiphorst;Herman W. M. Teinsma;Ben A. Witvliet;Sjoert R. Fleurke;Mark J. Bentum;Erik van Maanen;Johan Griffioen;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 884 - 896
Publisher: IEEE
 
» MV Generator Ground Fault Arcing Power Damage Assessment
Abstract:
An industrial medium voltage (MV) system usually consists of multiple power sources such as utility tie transformers and generators. These are normally low-resistance grounding as shown in Fig. 1 . When a ground fault occurs at the generator stator, ground currents from its own neutral circuit and external power sources will flow into the fault and cause damages to the stator winding. The IEEE Generator Grounding Working Group issued a guideline for generator grounding practices, which recommends using a hybrid grounding system to minimize the ground fault damage induced by its own neutral grounding source. This paper will evaluate the total ground fault damages based on the arcing power energy to derive a maximum MV system ground current that would limit the ground damage to 1800 kW-cycle or 30 kJ as the minimum arcing power energy damage as suggested by Conrad and Dalasta [10].
Autors: Alex Y. Wu;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 912 - 915
Publisher: IEEE
 
» Nanocrystalline Silicon Lateral MSM Photodetector for Infrared Sensing Applications
Abstract:
A novel lateral nanocrystalline silicon (nc-Si) metal–semiconductor–metal photodetector architecture is proposed using an organic blocking layer. Fabricated devices exhibit low dark current, high dynamic range, and a measured external quantum efficiency approaching 35% at 740 nm and 15% at 850 nm. The higher performance is enabled by integrating an nc-Si film with a previously reported thin organic polyimide blocking layer and subsequently operating at high electric fields. Unlike industry standard p-i-n photodiodes, our high-performance lateral photosensor does not require doped p+ and n+ layers. Thus, the reported device is compatible with industrial standard amorphous silicon thin-film transistor display fabrication process, making it promising for large-area biometric full-hand imaging applications.
Autors: Muhammad A. Martuza;Sina Ghanbarzadeh;Czang-Ho Lee;Celal Con;Karim S. Karim;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 584 - 590
Publisher: IEEE
 
» NASA's MODIS and VIIRS Land Surface Temperature and Emissivity Products: A Long-Term and Consistent Earth System Data Record
Abstract:
Land surface temperature and emissivity (LST&E) determine the total amount of upward long-wave infrared radiation emitted from the Earth's surface, making them key variables in a wide range of studies, including climate variability, land cover/use change, and the energy balance between the land and the atmosphere. LST&E products are currently produced on a routine basis using data from the MODIS instruments on the NASA EOS platforms and by the VIIRS instrument on the Suomi-NPP platform that serves as a bridge between NASA EOS and the next-generation JPSS platforms. Two new NASA LST&E products for MODIS (MxD21) and VIIRS (VNP21) will be produced during 2017 using a new approach that addresses discrepancies in accuracy and consistency between the current suite of MODIS and VIIRS LST split-window-based products. The new approach uses a temperature emissivity separation (TES) algorithm, originally developed for the ASTER instrument, to physically retrieve both LST and spectral emissivity consistently for both sensors with high accuracy and well-defined uncertainties. This study demonstrates continuity between the new MYD21 and VNP21 LST products at the <±0.5 K level, with differences that are invariant to environmental conditions and land cover type. Furthermore, MYD21 and VNP21 retrieved emissivities matched closely in magnitude and temporal variation to within 1%–2% over two land validation sites consisting of quartz sands and grassland. Continuity between the new suite of MODIS and VIIRS LST&E products will ensure a consistent and well-characterized long-term LST&E data record for better monitoring and understanding trends in Earth system behavior.
Autors: Glynn C. Hulley;Nabin K. Malakar;Tanvir Islam;Robert J. Freepartner;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 522 - 535
Publisher: IEEE
 
» NASH: Navigation-Assisted Seamless Handover Scheme for Smart Car in Ultradense Networks
Abstract:
In the vehicular network, the smart car provides various network services for the passenger by the user equipment (UE). However, the services might be interrupted since the handover procedure of the UE is performed frequently. The existing handover decision schemes in cellular networks are mostly based on received signal strength to make the handover decision. However, these schemes suffer from a ping-pong effect and, as a result, perform unnecessary handovers incurring extra signaling overhead and packet loss, which is even more exaggerated in the ultradense environment. The failure probability of the handover procedure will increase when the velocity of the car is fast. Therefore, in this paper, we propose a navigation-assisted seamless handover (NASH) scheme for reducing unnecessary handovers and the ping-pong effect. NASH uses the multiple input multiple output technique to perform the bicasting scheme and then it utilizes coordination multipoint and carrier aggregation mechanisms in the handover procedure to avoid the packet loss problem and enhance throughput. Moreover, a dynamic time to trigger mechanism is proposed according to the velocity of the car. The simulation results show that the proposed scheme has a better performance in terms of handover latency, packet loss, network throughput, handover failure probability, and the number of unnecessary handovers.
Autors: Ming-Chin Chuang;Meng Chang Chen;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1649 - 1659
Publisher: IEEE
 
» Naturalness Preserved Nonuniform Illumination Estimation for Image Enhancement Based on Retinex
Abstract:
Illumination estimation is important for image enhancement based on Retinex. However since illumination estimation is an ill-posed problem it is difficult to achieve accurate illumination estimation for nonuniform illumination images. The conventional illumination estimation algorithms fail to comprehensively take all the constraints into the consideration such as spatial smoothness sharp edges on illumination boundaries and limited range of illumination. Thus these algorithms cannot effectively and efficiently estimate illumination while preserving naturalness. In this paper we present a naturalness preserved illumination estimation algorithm based on the proposed joint edge-preserving filter which exploits all the abovementioned constraints. Moreover a fast estimation is implemented based on the box filter. Experimental results demonstrate that the proposed algorithm can achieve the adaptive smoothness of illumination beyond edges and ensure the range of the estimated illumination. When compared with other state-of-the-art algorithms it can achieve better quality from both subjective and objective aspects.
Autors: Yuanyuan Gao;Hai-Miao Hu;Bo Li;Qiang Guo;
Appeared in: IEEE Transactions on Multimedia
Publication date: Feb 2018, volume: 20, issue:2, pages: 335 - 344
Publisher: IEEE
 
» Nature of Sideband Generation
Abstract:
The serious investigation of sidebands (SBs), which are the result of nonlinear processes, began in the late 19th century when research was being conducted on amplitude modulation (Panter, 1965). In 1875, A.M. Mayer experimentally proved the existence of SBs. In 1886, M. Leblanc was likely the first to amplitude modulate a carrier signal with speech. Later, in 1894, Lord Rayleigh theoretically demonstrated the existence of SBs.
Autors: Don E. Czyzyk;
Appeared in: IEEE Potentials
Publication date: Feb 2018, volume: 37, issue:1, pages: 19 - 22
Publisher: IEEE
 
» Near-Field VLF Electromagnetic Signal Propagation in Multistory Buildings
Abstract:
In this paper, we present modeling of very low frequency (3–30 kHz) through-the-Earth (TTE) radio transmissions in four multistory buildings using the finite-difference time-domain method. These structures are generally made of reinforced concrete, whose steel content is the most important control on bulk conductivity. The floors and walls are represented as sheets of a given conductance, based on the fact that electromagnetic geophysical methods will only resolve conductive sheets in terms of their conductance as opposed to both conductivity and thickness. We validate this approach first using synthetic data and second by comparison with field data. Conductance models were derived from observed data for a variety of propagation environments, including reinforced concrete, steel floors, and basements, and for transmission into, out of, or within a building. The models were able to account for nonintuitive observations, such as increase in signal strength near the edges of buildings and in localized areas in between buildings. Conductances obtained for the floors and walls could be used as representative values in future forward modeling to assess the viability or optimize a TTE radio link in a multistory building.
Autors: Maxim Ralchenko;Mike Roper;Claire Samson;Markus Svilans;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 848 - 856
Publisher: IEEE
 
» Negative Capacitance Carbon Nanotube FETs
Abstract:
As continued scaling of silicon FETs grows increasingly challenging, alternative paths for improving digital system energy efficiency are being pursued. These paths include replacing the transistor channel with emerging nanomaterials (such as carbon nanotubes), as well as utilizing negative capacitance effects in ferroelectric materials in the FET gate stack, e.g., to improve sub-threshold slope beyond the 60 mV/decade limit. However, which path provides the largest energy efficiency benefits—and whether these multiple paths can be combined to achieve additional energy efficiency benefits—is still unclear. Here, we experimentally demonstrate the first negative capacitance carbon nanotube FETs (CNFETs), combining the benefits of both carbon nanotube channels and negative capacitance effects. We demonstrate negative capacitance CNFETs, achieving sub-60 mV/decade sub-threshold slope with an average sub-threshold slope of 55 mV/decade at room temperature. The average ON-current () of these negative capacitance CNFETs improves by versus baseline CNFETs, (i.e., without negative capacitance) for the same OFF-current (). This work demonstrates a promising path forward for future generations of energy-efficient electronic systems.
Autors: Tathagata Srimani;Gage Hills;Mindy D. Bishop;Ujwal Radhakrishna;Ahmad Zubair;Rebecca S. Park;Yosi Stein;Tomas Palacios;Dimitri Antoniadis;Max M. Shulaker;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 304 - 307
Publisher: IEEE
 
» Negative Iris Recognition
Abstract:
Elements of a person's biometrics are typically stable over the duration of a lifetime, and thus, it is highly important to protect biometric data while supporting recognition (it is also called secure biometric recognition). However, the biometric data that are derived from a person usually vary slightly due to a variety of reasons, such as distortion during picture capture, and it is difficult to use traditional techniques, such as classical encryption algorithms, in secure biometric recognition. The negative database (NDB) is a new technique for privacy preservation. Reversing the NDB has been demonstrated to be an NP-hard problem, and several algorithms for generating hard-to-reverse NDBs have been proposed. In this paper, first, we propose negative iris recognition, which is a novel secure iris recognition scheme that is based on the NDB. We show that negative iris recognition supports several important strategies in iris recognition, e.g., shifting and masking. Next, we analyze the security and efficiency of negative iris recognition. Experimental results show that negative iris recognition is an effective and secure iris recognition scheme. Specifically, negative iris recognition can achieve a highly promising recognition performance (i.e., GAR = 98.94% at FAR = 0.01%, EER = 0.60%) on the typical database CASIA-IrisV3-Interval.
Autors: Dongdong Zhao;Wenjian Luo;Ran Liu;Lihua Yue;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Feb 2018, volume: 15, issue:1, pages: 112 - 125
Publisher: IEEE
 
» Negative Resistance-Based Electronic Impedance Tuner
Abstract:
An electronic impedance tuner using the negative resistance of tunneling diodes is proposed in this paper. Aside from the fact that it is an interesting solution to synthesize impedance with reflection coefficient larger than one, this scheme is proven to be simpler and consume less power than the state-of-the-art techniques. The overall circuit topology consists of two parts, namely, impedance tuning circuit including a hybrid block of PIN and tunneling diode for generating a set of impedance points, and wideband nonlinear transmission line-based 360° phase shifter for rotating the set of impedance points around the Smith chart from 1.5 to 5 GHz. The operating power of the electronic tuner is below −25 dBm, which is limited by the tunneling diode. The worst-case maximum power consumption of the electronic tuner is as low as 3 mW. Such an electronic tuner should be useful for the development of on-wafer noise characterization systems.
Autors: Y. Zhao;S. Hemour;T. Liu;K. Wu;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 144 - 146
Publisher: IEEE
 
» NEPHELE: An End-to-End Scalable and Dynamically Reconfigurable Optical Architecture for Application-Aware SDN Cloud Data Centers
Abstract:
The efficient integration of optical switching in data center networks is being studied as a means to cope with surging traffic demands. Optically switched, flatter network architectures more efficiently handle the east-west traffic profiles of modern data centers. Limitations in the port count and reconfiguration speed of optical switches require novel network designs offering network scalability and dynamicity. Interaction of the optically switched data plane with a software-defined control and orchestration framework, meeting current common practices in data centers, necessitates the design of custom network control algorithms and software modules as well as the integration of novel functionalities. The approach of the European project NEPHELE is presented, offering an endto- end solution that addresses the optical data plane, the control plane, and its interaction with the application layer.
Autors: Paraskevas Bakopoulos;Konstantinos Christodoulopoulos;Giada Landi;Muzzamil Aziz;Eitan Zahavi;Domenico Gallico;Richard Pitwon;Konstantinos Tokas;Ioannis Patronas;Marco Capitani;Christos Spatharakis;Konstantinos Yiannopoulos;Kai Wang;Konstantinos Konto
Appeared in: IEEE Communications Magazine
Publication date: Feb 2018, volume: 56, issue:2, pages: 178 - 188
Publisher: IEEE
 
» Neuro-Inspired Computing With Emerging Nonvolatile Memorys
Abstract:
This comprehensive review summarizes state of the art, challenges, and prospects of the neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the demand for developing neuro-inspired architecture beyond today’s von-Neumann architecture. Second, we summarize the various approaches to designing the neuromorphic hardware (digital versus analog, spiking versus nonspiking, online training versus offline training) and discuss why emerging nonvolatile memory is attractive for implementing the synapses in the neural network. Then, we discuss the desired device characteristics of the synaptic devices (e.g., multilevel states, weight update nonlinearity/asymmetry, variation/noise), and survey a few representative material systems and device prototypes reported in the literature that show the analog conductance tuning. These candidates include phase change memory, resistive memory, ferroelectric memory, floating-gate transistors, etc. Next, we introduce the crossbar array architecture to accelerate the weighted sum and weight update operations that are commonly used in the neuro-inspired machine learning algorithms, and review the recent progresses of array-level experimental demonstrations for pattern recognition tasks. In addition, we discuss the peripheral neuron circuit design issues and present a device-circuit-algorithm codesign methodology to evaluate the impact of nonideal device effects on the system-level performance (e.g., learning accuracy). Finally, we give an outlook on the customization of the learning algorithms for efficient hardware implementation.
Autors: Shimeng Yu;
Appeared in: Proceedings of the IEEE
Publication date: Feb 2018, volume: 106, issue:2, pages: 260 - 285
Publisher: IEEE
 
» Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes
Abstract:
High-performance computing systems are moving towards 2.5D and 3D memory hierarchies, based on High Bandwidth Memory (HBM) and Hybrid Memory Cube (HMC) to mitigate the main memory bottlenecks. This trend is also creating new opportunities to revisit near-memory computation. In this paper, we propose a flexible processor-in-memory (PIM) solution for scalable and energy-efficient execution of deep convolutional networks (ConvNets), one of the fastest-growing workloads for servers and high-end embedded systems. Our co-design approach consists of a network of Smart Memory Cubes (modular extensions to the standard HMC) each augmented with a many-core PIM platform called NeuroCluster. NeuroClusters have a modular design based on NeuroStream coprocessors (for Convolution-intensive computations) and general-purpose RISC-V cores. In addition, a DRAM-friendly tiling mechanism and a scalable computation paradigm are presented to efficiently harness this computational capability with a very low programming effort. NeuroCluster occupies only 8 percent of the total logic-base (LoB) die area in a standard HMC and achieves an average performance of 240 GFLOPS for complete execution of full-featured state-of-the-art (SoA) ConvNets within a power budget of 2.5 W. Overall 11 W is consumed in a single SMC device, with 22.5 GFLOPS/W energy-efficiency which is 3.5X better than the best GPU implementations in similar technologies. The minor increase in system-level power and the negligible area increase make our PIM system a cost-effective and energy efficient solution, easily scalable to 955 GFLOPS with a small network of just four SMCs.
Autors: Erfan Azarkhish;Davide Rossi;Igor Loi;Luca Benini;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Feb 2018, volume: 29, issue:2, pages: 420 - 434
Publisher: IEEE
 
» New Constructions of Binary and Ternary Locally Repairable Codes Using Cyclic Codes
Abstract:
New constructions of binary and ternary locally repairable codes (LRCs) using cyclic codes and their concatenation are proposed. The proposed binary LRCs with and some and with and some are shown to be optimal in terms of the upper bounds. In addition, the similar method of the binary case is applied to construct the ternary LRCs with good parameters.
Autors: Chanki Kim;Jong-Seon No;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 228 - 231
Publisher: IEEE
 
» New Constructions of Optimal Locally Recoverable Codes via Good Polynomials
Abstract:
In recent literature, a family of optimal linear locally recoverable codes (LRC codes) that attain the maximum possible distance (given code length, cardinality, and locality) is presented. The key ingredient for constructing such optimal linear LRC codes is the so-called -good polynomials, where is equal to the locality of the LRC code. However, given a prime , known constructions of -good polynomials over some extension field of exist only for some special integers , and the problem of constructing optimal LRC codes over small field for any given locality is still open. In this paper, by using function composition, we present two general methods of designing good polynomials, which lead to three new constructions of -good polynomials. Such polynomials bring new constructions of optimal LRC codes. In particular, our constructed polynomials as well as the power functions yield optimal LRC codes over for all positive integers as localities, where is near the code length .
Autors: Jian Liu;Sihem Mesnager;Lusheng Chen;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 889 - 899
Publisher: IEEE
 
» New Heights for Satellites: LTCC Multilayer Technology for Future Satellites
Abstract:
Over the past few years, the demands on satellite communication have undergone significant changes, and, as a consequence, its technologies and system designs are also changing in important ways. Since the introduction of high-definition television, classical geostationary (GEO) satellites in orbit at 36,800 km must transmit higher data rates. Also, GEO satellites are increasingly used for global data transfer, e.g., for Internet applications and business communication. As a consequence, higher-frequency bandwidth, higher transmitting frequencies in the millimeter-wave range, and efficient frequency reuse are needed [1].
Autors: Ingo Wolff;Carsten Günner;Jürgen Kassner;Reinhard Kulke;Peter Uhlig;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 36 - 47
Publisher: IEEE
 
» New Mobility Model for Accurate Modeling of Transconductance in FDSOI MOSFETs
Abstract:
Anomalous transconductance with nonmono- tonic back-gate bias dependence observed in the fully depleted silicon-on-insulator (FDSOI) MOSFET with thick front-gate oxide is discussed. It is found that the anomalous transconductance is attributed to the domination of the back-channel charge in the total channel charge. This behavior is modeled with a novel two-mobility model, which separates the mobility of the front and back channels. These two mobilities are physically related by a charge-based weighting function. The proposed model is incorporated into BSIM-IMG and is in good agreement with the experimental and simulated data of FDSOI MOSFETs for various front-gate oxides, body thicknesses, and gate lengths.
Autors: Yen-Kai Lin;Pragya Kushwaha;Juan Pablo Duarte;Huan-Lin Chang;Harshit Agarwal;Sourabh Khandelwal;Angada B. Sachid;Michael Harter;Josef Watts;Yogesh Singh Chauhan;Sayeef Salahuddin;Chenming Hu;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 463 - 469
Publisher: IEEE
 
» New Models for the Calibration of Four-Channel Time-Interleaved ADCs Using Filter Banks
Abstract:
New linear models to calibrate four-channel time-interleaved analog-to-digital converters are proposed and investigated. The ideal four-periodic correction filters, which cancel distortions, are computed as a function of the error filters that model the analog transfer function of each channel, including the sampling time. These correction filters are then approximated as a linear combination of base filters and new accurate models with a limited number of free parameters are proposed. Calibration is performed using the recursive least squares algorithm to estimate the coefficients of the linear combination (and the offset term). The resulting algorithms are tested for accuracy, convergence speed, and stability in a fixed-point implementation, and are compared with previously published linear background calibration techniques. The proposed filter bank significantly improves the accuracy/complexity tradeoff with respect to previously published techniques.
Autors: Pietro Monsurrò;Felice Rosato;Alessandro Trifiletti;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Feb 2018, volume: 65, issue:2, pages: 141 - 145
Publisher: IEEE
 
» New Negative Coupling Structure for ${K}$ -Band Substrate-Integrated Waveguide Resonator Filter With a Pair of Transmission Zeros
Abstract:
In this letter, we present a new negative coupling structure applicable to a substrate-integrated waveguide (SIW) resonator filter structure. Unlike conventional negative coupling structure, the proposed coupling structure can achieve a negative coupling value without employing an additional substrate or slots on ground planes. To demonstrate the new negative coupling structure, we designed, fabricated, and measured a fourth-order -band SIW resonator filter with a pair of transmission zeros.
Autors: Boyoung Lee;Seunggoo Nam;Changsoo Kwak;Juseop Lee;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 135 - 137
Publisher: IEEE
 

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