Electrical and Electronics Engineering publications abstract of: 01-2018 sorted by title, page: 9

» Generalized Rank Weights of Reducible Codes, Optimal Cases, and Related Properties
Abstract:
Reducible codes for the rank metric were introduced for cryptographic purposes. They have fast encoding and decoding algorithms, include maximum rank distance (MRD) codes, and can correct many rank errors beyond half of their minimum rank distance, which makes them suitable for error correction in network coding. In this paper, we study their security behavior against information leakage on networks when applied as coset coding schemes, giving the following main results: 1) we give lower and upper bounds on their generalized rank weights (GRWs), which measure worst case information leakage to the wire tapper; 2) we find new parameters for which these codes are MRD (meaning that their first GRW is optimal) and use the previous bounds to estimate their higher GRWs; 3) we show that all linear (over the extension field) codes, whose GRWs are all optimal for fixed packet and code sizes but varying length are reducible codes up to rank equivalence; and 4) we show that the information leaked to a wire tapper when using reducible codes is often much less than the worst case given by their (optimal in some cases) GRWs. We conclude with some secondary related properties: conditions to be rank equivalent to Cartesian products of linear codes and conditions to be rank degenerate, duality properties, and MRD ranks.
Autors: Umberto Martínez-Peñas;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 192 - 204
Publisher: IEEE
 
» Generalized Semi-supervised and Structured Subspace Learning for Cross-Modal Retrieval
Abstract:
Motivated by the fact that unlabeled data can be easily collected and help to exploit the correlations among different modalities, this paper proposes a novel method named generalized semi-supervised structured subspace learning (GSS-SL) for the task of cross-modal retrieval. First, to predict more relevant class labels for unlabeled data, we propose a label graph constraint that ensures the intrinsic geometric structures of different feature spaces consistent with that of label space. Second, considering that class labels directly reveal the semantic information of multimedia data, GSS-SL takes the label space as a linkage to model the correlations among different modalities. Concretely, the label graph constraint, label-linked loss function, and regularization are integrated into a joint minimization formulation to learn a discriminative common subspace. Finally, an efficient optimization algorithm is designed to alternately optimize multiple linear transformations for different modalities and update the class indicator matrices for unlabeled data. Furthermore, an arbitrary number of modalities can be solved in the proposed framework. Extensive experiments on three standard benchmark datasets demonstrate that GSS-SL outperforms previous methods on exploiting the correlations among different modalities.
Autors: Liang Zhang;Bingpeng Ma;Guorong Li;Qingming Huang;Qi Tian;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 128 - 141
Publisher: IEEE
 
» Generalized Sheet Transition Condition FDTD Simulation of Metasurface
Abstract:
We propose a finite-difference time-domain (FDTD) scheme based on generalized sheet transition conditions (GSTCs) for the simulation of polychromatic, nonlinear, and space–time varying metasurfaces. This scheme consists in placing the metasurface at virtual nodal plane introduced between the regular nodes of the staggered Yee grid and inserting fields determined by GSTCs in this plane in the standard FDTD algorithm. The resulting update equations are an elegant generalization of the standard FDTD equations. Indeed, in the limiting case of a null surface susceptibility (), they reduce to the latter, while in the next limiting case of a time-invariant metasurface , they split in two terms, one corresponding to the standard equations for a one-cell () thick slab with diluted volume susceptibility (), and the other one reducing that slab to a quasi-zero-thickness mesh-less sheet. The proposed scheme is fully numerical and very easy to implement. Although it is explicitly derived for a monoisotropic metasurface, it may be straightforwardly extended to the bianisotropic case. Except for some particular cases, it is not applicable to dispersive metasurfaces, for which an efficient auxiliary different equation extension of the scheme is currently being developed by the authors. The scheme is validated and illustrated by five representative examples.
Autors: Yousef Vahabzadeh;Nima Chamanara;Christophe Caloz;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 271 - 280
Publisher: IEEE
 
» Generating Arm-Swing Trajectories in Real-Time Using a Data-Driven Model for Gait Rehabilitation With Self-Selected Speed
Abstract:
Gait rehabilitation is often focused on the legs and overlooks the role of the upper limbs. However, a variety of studies have demonstrated the importance of proper arm swing both during healthy walking and during rehabilitation. In this paper, we describe a method for generating proper arm-swing trajectories in real time using only measurements of the angular velocity of a person’s thighs, to be used during gait rehabilitation with self-selected walking speed. A data-driven linear time-invariant transfer function is developed, using frequency-response methods, which captures the frequency-dependent magnitude and phase relationship between the thighs’ angular velocities and the arm angles (measured at the shoulder, in the sagittal plane), using a data set of 30 healthy adult subjects. We show that the proposed method generates smooth trajectories for both healthy individuals and patients with mild to moderate Parkinson disease. The proposed method can be used in future robotic devices that integrate arm swing in gait rehabilitation of patients with walking impairments to improve the efficacy of their rehabilitation.
Autors: Babak Hejrati;Andrew S. Merryweather;Jake J. Abbott;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 115 - 124
Publisher: IEEE
 
» Generating Music from Literature Using Topic Extraction and Sentiment Analysis
Abstract:
This article presents Tambr, a new software for translating literature into sound using multiple synthesized voices selected for the way in which their timbre relates to the meaning and sentiment of the topics conveyed in the story. It achieves this by leveraging a large lexical semantic database to implement a machine-learning-based synthesizer search engine used to select the synthesizers whose meaning best reflects the ideas of the novel. Tambr uses sentiment analysis to generate the pitches, durations, and intervals of the output melodies in a way corresponding to the sentiment of the novel-implementing algorithmic composition of literature-based music at a level of musicality not previously explored.
Autors: Jessie Salas;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 15 - 18
Publisher: IEEE
 
» Generation Scheduling Optimization of Wind-Energy Storage System Based on Wind Power Output Fluctuation Features
Abstract:
As the output from wind power generation is intermittent in nature, making the wind power output “dependable” is critical for seamless integration of wind generation. One of the most favorable solutions is incorporating energy storage system (ESS) with wind farms to establish a wind-energy storage hybrid system. Since it requires capital investment for ESS installation, it is important to estimate appropriate storage capacity and charging/discharging rate of ESS for desired applications. In this paper, the fluctuation feature of wind power output is analyzed both in time domain and frequency domain. The degree of fluctuation is extracted and illustrated as quantization index (QI). Based on QI clustering, the wind scenario with largest power fluctuation is selected as “worst performance,” according to which, scheduling time horizon, along with the capacity and charging/discharging power of ESS, can be determined. After the case study, the proposed model is proved to improve the generation scheduling process.
Autors: Jie Shi;Wei-Jen Lee;Xiaofei Liu;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Jan 2018, volume: 54, issue:1, pages: 10 - 17
Publisher: IEEE
 
» Generative Adversarial Networks: An Overview
Abstract:
Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this by deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image superresolution, and classification. The aim of this review article is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.
Autors: Antonia Creswell;Tom White;Vincent Dumoulin;Kai Arulkumaran;Biswa Sengupta;Anil A. Bharath;
Appeared in: IEEE Signal Processing Magazine
Publication date: Jan 2018, volume: 35, issue:1, pages: 53 - 65
Publisher: IEEE
 
» Generative Local Metric Learning for Nearest Neighbor Classification
Abstract:
We consider the problem of learning a local metric in order to enhance the performance of nearest neighbor classification. Conventional metric learning methods attempt to separate data distributions in a purely discriminative manner; here we show how to take advantage of information from parametric generative models. We focus on the bias in the information-theoretic error arising from finite sampling effects, and find an appropriate local metric that maximally reduces the bias based upon knowledge from generative models. As a byproduct, the asymptotic theoretical analysis in this work relates metric learning to dimensionality reduction from a novel perspective, which was not understood from previous discriminative approaches. Empirical experiments show that this learned local metric enhances the discriminative nearest neighbor performance on various datasets using simple class conditional generative models such as a Gaussian.
Autors: Yung-Kyun Noh;Byoung-Tak Zhang;Daniel D. Lee;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 106 - 118
Publisher: IEEE
 
» Generic Construction of Binary Sequences of Period $2N$ With Optimal Odd Correlation Magnitude Based on Quaternary Sequences of Odd Period $N$
Abstract:
Binary sequences with low odd correlation have important applications in communication systems to reduce interference. In this paper, using the interleaving technique, we present a generic connection between binary sequences with low odd correlation and quaternary sequences with low even correlation. As a result, some new binary sequences with optimal odd auto-correlation magnitude are obtained. Besides, two sets consisting of binary sequences of period with the maximum odd correlation magnitude are derived, which are the first two optimal classes of binary sequence sets achieving the Sarwate bound on the odd correlation magnitude in the literature.
Autors: Yang Yang;Xiaohu Tang;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 384 - 392
Publisher: IEEE
 
» Generic Proposal Evaluator: A Lazy Learning Strategy Toward Blind Proposal Quality Assessment
Abstract:
Existing detection or recognition systems typically select one state-of-the-art proposal algorithm to produce massive object-covered candidate windows, and a quality metric specifically designed for this algorithm is utilized to single out small amounts of proposals. However, in practice, the accuracies of different proposal algorithms significantly change from one image content to another one. To obtain more robust proposal results, a generic proposal evaluator (GPE) is highly desired, which could choose optimal candidate windows across multiple proposal algorithms. In this paper, we propose a lazy learning strategy to train the GPE, which aims to blindly estimate the quality of each proposal without accessing to its manual annotation. Unlike the traditional end-to-end framework that learns a universal model from all training samples, we try to build query-specific training subset for each given proposal, where only its -nearest-neighborhoods are collected from all labeled candidate windows. Benefits from the capability of updating the regression parameters for different visual contents, the proposed method delivers a higher quality prediction accuracy even with respect to the deep neural network learned by end-to-end method. Experimental results confirm that the proposed algorithm significantly outperforms many state-of-the-art proposal quality metrics.
Autors: Qingbo Wu;Hongliang Li;Fanman Meng;King N. Ngan;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 306 - 319
Publisher: IEEE
 
» Geometric Accuracy Analysis for GaoFen3 Stereo Pair Orientation
Abstract:
Due to the all-weather and all-day advantage and the high geometric accuracy, the spaceborne synthetic aperture radar (SAR) stereo pair has a wide application in digital elevation model (DEM) production and ground control points (GCPs) extraction around the world. The GaoFen3 (GF3) remote sensing satellite is the first C-band multipolarization SAR satellite with a resolution of 1 m in China and plays an important role in commercial exploitation and scientific research. This letter performs a comprehensive analysis of the geometric accuracy for GF3 stereo pair orientation. By analyzing the orientation error sources, it is proven that the affine transformation model in image space can effectively compensate the unmodeled errors in GF3 imagery. Based on the rational polynomial coefficient model, the integrated orientation model for the GF3 stereo pair is presented here. Moreover, the model parameters and weight determination are further studied to analyze the influence of weight matrixes on geometric accuracy. Experimental results demonstrate that the proposed integrated orientation model can be effectively used for the GF3 stereo pair. The GCPs, convergent angle, and weight setting are the key factors influencing the geometric accuracy.
Autors: Mi Wang;Yanli Wang;Yi Run;Yufeng Cheng;Shuying Jin;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 92 - 96
Publisher: IEEE
 
» Geometry-Based Statistical Modeling of Non-WSSUS Mobile-to-Mobile Rayleigh Fading Channels
Abstract:
In this paper, we present a novel geometry-based statistical model for small-scale non-wide-sense stationary uncorrelated scattering (non-WSSUS) mobile-to-mobile (M2M) Rayleigh fading channels. The proposed model builds on the principles of plane wave propagation to capture the temporal evolution of the propagation delay and Doppler shift of the received multipath signal. This is different from existing non-WSSUS geometry-based statistical channel models, which are based on a spherical wave propagation approach, that in spite of being more realistic is more mathematically intricate. By considering an arbitrary geometrical configuration of the propagation area, we derive general expressions for the most important statistical quantities of nonstationary channels, such as the first-order probability density functions of the envelope and phase, the four-dimensional (4-D) time-frequency correlation function (TF-CF), local scattering function (LSF), and time-frequency-dependent delay and Doppler profiles. We also present an approximate closed-form expression of the channel's 4-D TF-CF for the particular case of the geometrical one-ring scattering model. The obtained results provide new theoretical insights into the correlation and spectral properties of non-WSSUS M2M Rayleigh fading channels.
Autors: Carlos A. Gutiérrez;José T. Gutiérrez-Mena;José M. Luna-Rivera;Daniel U. Campos-Delgado;Ramiro Velázquez;Matthias Pätzold;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 362 - 377
Publisher: IEEE
 
» Get Involved [Standards News]
Abstract:
As IAS Standards Department chair, my earnest appeal to all of you reading this article is to get involved in IAS standards. If you are an employer, convince your employees to join the standards-making group that aligns with your company's objectives.
Autors: Daleep Mohla;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 114 - 115
Publisher: IEEE
 
» GeTrust: A Guarantee-Based Trust Model in Chord-Based P2P Networks
Abstract:
More and more users are attracted by P2P networks characterized by decentralization, autonomy and anonymity. However, users’ unconstrained behavior makes it necessary to use a trust model when establishing trust relationships between peers. Most existing trust models are based on recommendations, which, however, suffer from the shortcomings of slow convergence and high complexity of trust computations, as well as huge overhead of network traffic. Inspired by the establishment of trust relationships in human society, a guarantee-based trust model, GeTrust, is proposed for Chord-based P2P networks. A service peer needs to choose its guarantee peer(s) for the service it is going to provide, and they are both required to pledge reputation mortgages for the service. The request peer makes evaluations on all the candidates of service peer by referring their service reputations and their guarantee peers’ reputations, and selects the one with highest evaluation to be its service provider. In order to enhance GeTrust's availability and prevent malicious behavior, we also present incentive mechanism and anonymous reputation management strategy. Simulation results show that GeTrust is effective and efficient in terms of improving successful transaction rate, resisting complex attacks, reducing network overhead and lowering computational complexity.
Autors: Xianfu Meng;Dongxu Liu;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Jan 2018, volume: 15, issue:1, pages: 54 - 68
Publisher: IEEE
 
» Getting into Microwaves and the MTT-S [Presidents' Column]
Abstract:
Presents reflections from the departing MTTS society President.
Autors: Dylan Williams;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 8 - 10
Publisher: IEEE
 
» Giant Amplification of Terahertz Waves in a Nonlinear Graphene Layered Medium
Abstract:
In this letter, a novel technique for terahertz (THz) wave amplification based on subjecting a nonlinear graphene layered medium to two intensive optical waves is proposed. The principle of operation is based on generating a backward-propagating THz wave at the expense of the THz input wave, by properly designing the medium dispersion, graphene nonlinear response, and optical frequency spacing. The generated THz wave interacts, in turn, with the co-propagating (THz and optical) waves, enabling an energy exchange regime. It is shown that, via proper design of the propagation length, a giant THz gain can be achieved by means of optical parametric downconversion. The presented numerical evaluations show a possible 50-dB-THz gain for a few centimeters of propagation lengths with reasonable optical input intensities. The proposed scheme is tunable, simple, and operates at room temperature.
Autors: Montasir Qasymeh;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:1, pages: 35 - 38
Publisher: IEEE
 
» Global Communications Newsletter
Abstract:
Presents key events and topics in the global communications industry.
Autors: Fabricio Braga Soares de Carvalho;Amit Patel;Iti Saha Misra;Ali Abedi;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 9 - 12
Publisher: IEEE
 
» Global Model for Self-Discharge and Capacity Fade in Lithium-Ion Batteries Based on the Generalized Eyring Relationship
Abstract:
In this paper, we present an innovative and precise way to calculate the available capacity in a battery. This quantity is essential to assess the ageing process during real use or ageing tests. Classical methods for measuring the available capacity in a battery are very dependent of impedance and relaxation state of the battery. Consequently, these methods are not suitable to quantify reversible and irreversible capacity losses occurring on batteries. We propose an indirect measure of available capacity that reduces the distortion caused by battery relaxation and impedance changes. This new method provides more accurate results allowing to distinguish reversible from irreversible part of capacity losses. The obtained results on calendar ageing tests are used in a second part to model both self-discharge and capacity fade in a global approach by using the generalized Eyring relationship.
Autors: Eduardo Redondo-Iglesias;Pascal Venet;Serge Pelissier;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 104 - 113
Publisher: IEEE
 
» Globally Optimal Matching Networks With Lossy Passives and Efficiency Bounds
Abstract:
Impedance transformation is one of the central concepts in high-frequency circuits and systems and is used ubiquitously for optimal power matching, noise matching, and high-efficiency power delivery to the antenna by power amplifiers. The matching network can be generally expressed as a path on the Smith chart and given the load and source impedances, there are theoretically infinite ways to achieve the transformation. When losses are included, each path will encounter a different loss, and currently, no comprehensive theory exist for finding the most optimal matching network. Furthermore, the networks will also provide different bandwidths of operation. Due to the matching network losses, it is often not optimal to force conjugate matching for maximizing end-to-end power transfer efficiency. In this paper, we provide a method toward finding 1) the globally most efficient path between two arbitrary impedances with lossy passives; 2) given the source and the load impedances, the optimal (typically non-conjugate) impedance to match and the highest efficiency path to reach the impedance; and 3) upper bounds on achievable efficiencies under the various scenarios. This paper also proposes ways to combine this method with nonlinear load-pull simulations for optimal combiner and matching network for integrated power amplifiers. This analysis creates interesting ways to maximize efficiency and bandwidths simultaneously and the paper also discusses this joint optimization. To the best of our knowledge, this is the first comprehensive analysis of globally optimal impedance transformation networks between arbitrary impedances with lossy passives.
Autors: Chandrakanth Reddy Chappidi;Kaushik Sengupta;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 257 - 269
Publisher: IEEE
 
» Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization
Abstract:
Results of planetary mapping are often shared openly for use in scientific research and mission planning. In its raw format, however, the data is not accessible to non-experts due to the difficulty in grasping the context and the intricate acquisition process. We present work on tailoring and integration of multiple data processing and visualization methods to interactively contextualize geospatial surface data of celestial bodies for use in science communication. As our approach handles dynamic data sources, streamed from online repositories, we are significantly shortening the time between discovery and dissemination of data and results. We describe the image acquisition pipeline, the pre-processing steps to derive a 2.5D terrain, and a chunked level-of-detail, out-of-core rendering approach to enable interactive exploration of global maps and high-resolution digital terrain models. The results are demonstrated for three different celestial bodies. The first case addresses high-resolution map data on the surface of Mars. A second case is showing dynamic processes, such as concurrent weather conditions on Earth that require temporal datasets. As a final example we use data from the New Horizons spacecraft which acquired images during a single flyby of Pluto. We visualize the acquisition process as well as the resulting surface data. Our work has been implemented in the OpenSpace software [8], which enables interactive presentations in a range of environments such as immersive dome theaters, interactive touch tables, and virtual reality headsets.
Autors: Karl Bladin;Emil Axelsson;Erik Broberg;Carter Emmart;Patric Ljung;Alexander Bock;Anders Ynnerman;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 802 - 811
Publisher: IEEE
 
» Good Preparation [Electrical Safety]
Abstract:
The author argues that it is easy to find connections between good preparation and safety, and electrical safety in particular. Many incidents, injuries, and fatalities occur when the scope changes on an electrical job. The workers may go into areas or equipment by mistake that are not properly de-energized. A well-prepared plan of action will clearly identify the scope of the job and help warn the workers to stop a job when the scope is changing. Good preparation will help identify the proper tools and test equipment needed and any special training that is required for the workers; without the right tools, test equipment, and training, there is a higher chance of an accident. A team that puts together a well-prepared plan of action can often reduce the number of electrical switching operations; this can dramatically lower the chance of a fault in the equipment during the job. As Miguel de Cervantes (1547–1616) said, "To be prepared is half the victory." For an electrical task, it should be considered a victory to have the job completed safely. Is your team prepared for every contingency?
Autors: Daniel Doan;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 6 - 6
Publisher: IEEE
 
» GPU-Accelerated Algorithm for Online Probabilistic Power Flow
Abstract:
This letter proposes a superior GPU-accelerated algorithm for probabilistic power flow (PPF) based on Monte-Carlo simulation with simple random sampling (MCS-SRS). By means of offloading the tremendous computational burden to GPU, the algorithm can solve PPF in an extremely fast manner, two orders of magnitude faster in comparison to its CPU-based counterpart. Case studies on three large-scale systems show that the proposed algorithm can solve a whole PPF analysis with 10000 SRS and ultra-high-dimensional dependent uncertainty sources in seconds and therefore presents a highly promising solution for online PPF applications.
Autors: Gan Zhou;Rui Bo;Lungsheng Chien;Xu Zhang;Shengchun Yang;Dawei Su;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1132 - 1135
Publisher: IEEE
 
» Grading electric field in high voltage insulation using composite materials
Abstract:
Localized overstress due to electric field concentration is a threat to the long-term performance of the insulation in almost all high voltage apparatus. Resistive field grading using field grading materials (FGMs) may be a solution to this problem. Insulation matrixes such as ethylene propylene diene monomer, epoxy, or silicone rubbers, blended with fillers such as ZnO microvaristors, are reported to possess field dependent conductivity with greater and more stable nonlinearity than traditional FGMs [1]. Their application in high voltage apparatus such as bushings [1], cable accessories [2]–[4], insulators [5], [6], and stator coils [7] has been studied recently. It is well known [8] that the most important parameters for FGMs are the nonlinear coefficient α and switching field Eb; the challenge is to tailor these two parameters to a specific application. FGMs can function effectively in most cases when α >10 [9], but the adjustment of Eb is more complex.
Autors: Xiao Yang;Xiaolei Zhao;Jun Hu;Jinliang He;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Jan 2018, volume: 34, issue:1, pages: 15 - 25
Publisher: IEEE
 
» GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit
Abstract:
We propose GraphD, an out-of-core Pregel-like system targeting efficient big graph processing with a small cluster of commodity PCs connected by Gigabit Ethernet, an environment affordable to most users. This is in contrast to some recent efforts for out-of-core graph computation with specialized hardware. In our setting, a vertex-centric program is often data-intensive, since the CPU cost of calculating a message value is negligible compared with the network cost of transmitting that message. As a result, network bandwidth is usually the bottleneck, and out-of-core execution would not sacrifice performance if disk IO overhead can be hidden by message transmission, which is achieved by GraphD through the parallelism of computation and communication. GraphD streams edge and message data on local disks, and thus consumes negligible memory space. For a broad class of Pregel algorithms where message combiner is applicable, GraphD completely eliminates the need of any expensive external-memory join or group-by, which is required by existing systems such as Pregelix and Chaos. Extensive experiments show that GraphD beats existing out-of-core systems by orders of magnitude, and achieves comparable performance to in-memory systems running with adequate memory.
Autors: Da Yan;Yuzhen Huang;Miao Liu;Hongzhi Chen;James Cheng;Huanhuan Wu;Chengcui Zhang;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Jan 2018, volume: 29, issue:1, pages: 99 - 114
Publisher: IEEE
 
» Graphene Heat Spreaders for Thermal Management of InGaP/GaAs Collector-Up HBTs
Abstract:
We present a novel thermal management design for InGaP/GaAs power amplifiers (PAs) by placing the graphene heat spreader (GHS) at the backside of GaAs/InGaAs/InGaP collector-up (C-up) heterojunction bipolar transistors (HBTs), including n-p-n and p-n-p types. The GHS was used to create extra escape channel for thermal spread, and a physics-based analysis was performed to justify heat-dissipation improvements. Temperature distribution in the GHS and the application of these spreaders to ameliorate thermal coupling effects on multifinger transistors were discussed. Compared to the n-p-n device, the p-n-p device exhibits greater thermal stability enhancement results, which are extraordinary and reproducible. Both numerical simulation and experimental measurement were achieved to scrutinize thermal performance of the GHS. This brief demonstrates the potential of the suggested structure in replacing the conventional thermal-removal configuration of GaAs-based HBTs used in high-efficiency cellular handset PAs.
Autors: P.-H. Lee;W.-M. Tu;H.-C. Tseng;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 352 - 355
Publisher: IEEE
 
» Graphene/Ag-NWs Electrodes for Highly Transparent and Extremely Stretchable Supercapacitor
Abstract:
Highly transparent and supremely stretchable electrodes based on graphene and silver nanowires (Ag-NWs) hybrid structures are being reported in this study. A prestretched polyacrylate (PAC) technique is used which endows 200% multiaxial stretch ability to the fabricated electrodes. A novel bubble template method is used for the uniform distribution of Ag-NWs. The Ag-NWs decrease the resistivity of the fabricated electrodes remarkably and enhance the connectivity between graphene segments when graphene gets partially divided into small segments upon appliance of strains >150%. Piezoresistive measurements show that the graphene/Ag-NWs electrodes are suitable for the fabrication of stretchable electronic devices. The electrodes are tested for the fabrication of supercapacitors and their working under high applied strains. Results from cyclic voltammetry measurements show that the demonstrated electrodes can work efficiently under applied strains up to 200%.
Autors: Zaka Ullah;Qi Li;Rubing Wang;Qi Zeng;Weiwei Li;Liwei Liu;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 65 - 68
Publisher: IEEE
 
» Graphiti: Interactive Specification of Attribute-Based Edges for Network Modeling and Visualization
Abstract:
Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw data remains a challenging task, often requiring users to program custom scripts or write complex SQL commands. Some existing tools also allow users to both visualize and model networks. Interaction techniques adopted by these tools often assume users know the exact conditions for defining edges in the resulting networks. This assumption may not always hold true, however. In cases where users do not know much about attributes in the dataset or when there are several attributes to choose from, users may not know which attributes they could use to formulate linking conditions. We propose an alternate interaction technique to model networks that allows users to demonstrate to the system a subset of nodes and links they wish to see in the resulting network. The system, in response, recommends conditions that can be used to model networks based on the specified nodes and links. In this paper, we show how such a demonstration-based interaction technique can be used to model networks by employing it in a prototype tool, Graphiti. Through multiple usage scenarios, we show how Graphiti not only allows users to model networks from a tabular dataset but also facilitates updating a pre-defined network with additional edge types.
Autors: Arjun Srinivasan;Hyunwoo Park;Alex Endert;Rahul C. Basole;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 226 - 235
Publisher: IEEE
 
» Grating Coupler Design for Reduced Back-Reflections
Abstract:
A grating coupler having asymmetric grating trenches for low back reflections is experimentally demonstrated. Conventional and asymmetric-trench grating couplers have been fabricated on a silicon nitride waveguide platform. Both grating couplers have fully etched trenches, which normally result in higher back reflections than shallow-etched trenches. For evaluating the back reflection characteristics, test structures based on a 3-dB multimode interference power splitter have been measured and the backreflection has been extracted from each grating coupler using an equivalent optical circuit. The designed grating coupler has no critical penalty (<0.2 dB) in coupling efficiency and ~5 dB lower back reflections than a conventional grating coupler design. Using ray transfer matrix modeling, further improvements to the back reflection characteristics of the asymmetric grating coupler are expected.
Autors: Jeong Hwan Song;Bradley Snyder;Kristof Lodewijks;Roelof Jansen;Xavier Rottenberg;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 217 - 220
Publisher: IEEE
 
» Greetings from the New Editor-in-Chief [From the Editor's Desk]
Abstract:
Presents the introductory editorial for this issue of the publication.
Autors: Robert Caverly;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 6 - 16
Publisher: IEEE
 
» Grid-Synchronization Stability Improvement of Large Scale Wind Farm During Severe Grid Fault
Abstract:
Loss of synchronization between wind farm and power grid during severe grid faults would cause wind farm tripping. In this paper, the mechanism of grid-synchronization is uncovered, described as motion of an autonomous nonlinear differential equation with specific initial states. The revealed mechanism indicates that even though steady-state working point exists, improper initial states and poor system dynamic properties could lead to synchronization instability. In order to keep wind farm synchronous with the power grid during severe grid faults, special requirements on system dynamic properties are stated. Moreover, to satisfy all the requirements, a current injecting method is proposed. By adjusting active and reactive output currents of the wind farm, the proposed method could ensure system synchronization stability during severe grid faults. Implementation of the proposed method on PMSG- and DFIG-based wind farm is illustrated. Simulation results validate the analysis and the control method.
Autors: ShaoKang Ma;Hua Geng;Lu Liu;Geng Yang;Bikash C. Pal;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 216 - 226
Publisher: IEEE
 
» Guest Editorial Circuit and System Design Automation for Internet of Things
Abstract:
Internet-of-Things (IoT) is the technical backbone of smart cities which are envisioned to cope up with rapid urbanization of human population with limited resources. IoT provides three key features of smart cities such as intelligence, interconnection, and instrumentation. IoT is essentially a system-of-systems which can be considered as a configurable dynamic global network of networks. The main components of IoT include the following: 1) The Things; 2) Internet; 3) LAN; and 4) The Cloud. IoT is built by various diverse components including electronics, sensors, actuators, controllers, networks, firmware, and software. However, the existing electronics, controllers, and processors do not meet IoT requirements, such as multiple sensors, communication protocols, and security requirements. The existing computer-aided design (CAD) or electronic design automation tools are not enough to meet diverse challenges such as time-to-market, complexity, and cost of IoT. The required electronic circuits and systems need to be developed by handling and solving specific requirements. Real-time and ultralow power plays a major role since mobile devices in the IoT have to provide a long availability with a relative small energy budget. At the same time, reliability, availability, real-time constraints, and performance requirements pose significant challenges, and therefore, lead to a high interest in research. In this special issue, different approaches to design novel devices, circuits, and systems for solving the challenges with IoT are targeted. Various novel design automation components including modeling, design flows, simulation methods, and optimizations for designing of modern IoT are targeted, from system level down to device level. The current special issue was envisioned with the above technical considerations. After a rigorous review process, a set of articles were selected for this special issue. These papers are briefly discussed i- the rest of the editorial.
Autors: Saraju P. Mohanty;Michael Hüebner;Chun Jason Xue;Xin Li;Hai Li;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Jan 2018, volume: 37, issue:1, pages: 3 - 6
Publisher: IEEE
 
» Guest Editorial Introduction to the Special Issue on Robust and Efficient Vision Techniques for Intelligent Vehicles
Abstract:
In recent years, intelligent vehicles have been a hot topic for both research and industry communities. Since the whole system is a comprehensive integration of many advanced techniques, their respective development and improvement become fundamentally important.
Autors: Qi Wang;Luis M. Bergasa;José M. Álvarez;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 129 - 130
Publisher: IEEE
 
» Guest Editorial Localisation, Communication and Networking With VLC
Abstract:
We are at the dawn of an era in information and communication technology with unprecedented demand for connected and automated everything. Both Shannon theories and industrial advances have clearly evidenced that more densely packed networks and a much wider operating bandwidth are key drivers for meeting the escalating wireless network demands. Recently, there have been substantial research efforts on the exploitation of higher frequency bands, in particular the millimetre wave and optical wireless bands. After a decade of active research and development, and along with the maturity of device technology, Visible Light Communications (VLC) has emerged as a very promising technology to enable next generation digital innovations and support wide range of applications. This special issue on VLC focuses on three core thrusts of the discipline: Localisation, Communication and Networking. The overall aim of the special issue is to inspire multi-disciplinary international communities to work together in order to achieve further research advances. Indeed, a total of 96 high quality papers were received from both academia and industry. After a careful peer-reviewing process, 17 papers were selected based on their combined novelty, rigour, and impact. Owing to the highly selective nature of JSAC, many other interesting papers were not selected for the special issue, but we hope that these papers might appear elsewhere.
Autors: Rong Zhang;Mauro Biagi;Lutz Lampe;Thomas D. C. Little;Stefan Mangold;Zhengyuan Xu;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 1 - 7
Publisher: IEEE
 
» Guest Editorial Special Issue on Marine and Maritime Radar Remote Sensing
Abstract:
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
Autors: Maurizio Migliaccio;David G. Long;Malcolm L. Heron;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Jan 2018, volume: 43, issue:1, pages: 3 - 6
Publisher: IEEE
 
» Guest Editorial Special Section on Electric Powertrains for Future Vehicles
Abstract:
The papers in this special section focus on electric power trains, with particular emphasis on state-of-the-art research and development and new design concepts. These papers were presented at the IEEE Vehicle Power and Propulsion Conference (VPPC) that was held in Hangzhou, China, in October 2016.
Autors: D. Hissel;Q. Lu;J. P. F. Trovão;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 72 - 75
Publisher: IEEE
 
» Guest Editorial: Special Section on the IEEE TNANO International Nanoelectronics Conference (INEC)
Abstract:
The papers in this special section were presented at the IEEE TNANO International Nanoelectronics Conference (INEC) that was held in Chengdu, China, on May 7-9, 2016.
Autors: C.-W. Kok;W.-S. Tam;H. Wong;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 3 - 3
Publisher: IEEE
 
» H.264 and H.265 Video Bandwidth Prediction
Abstract:
The explosive growth of multimedia applications renders the efficiency of network resource allocation a problem of major importance. The burstiness of video traffic, in particular, calls for traffic control solutions that will help prevent significant packet losses. Such losses can lead to unacceptable quality of service (QoS) and quality of experience (QoE) to users. In this paper, we focus on a large variety of H.264- and H.265-encoded video traces with different GoP patterns. Different versions of each trace, in low, medium, and high quality have been used in our study. We evaluate the accuracy of an existing video traffic prediction approach for the size of B-frames, and we propose a new Markovian model that predicts B-frames’ sizes with significantly higher accuracy. B-frame size prediction can be used in order to reduce bandwidth requirements and smooth the encoded video stream, by selective B-frame dropping, when the model predicts larger upcoming B-frame traffic than the network can handle.
Autors: Athina Kalampogia;Polychronis Koutsakis;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 171 - 182
Publisher: IEEE
 
» Hardware Implementation of the Compressed Beamforming Weights Calculation for the Practical Wireless MIMO-OFDM Communication System
Abstract:
The compressed beamforming weights (CBWs) feedback is used in the IEEE 802.11n/ac WLAN, an example of the practical beamforming multiple input multiple output-orthogonal frequency division multiplexing system, to reduce the amount of feedback information so that the beamformee can respond rapidly to the beamformer. The CBW associated with each sub-carrier includes the quantized angles obtained from QR-decomposition (QRD) of the right singular vectors of each corresponding channel matrix. Efficient matrix QRD and singular value decomposition (SVD) together are therefore desirable for computing the CBWs associated with all sub-carriers. Considering the exemplary antenna configuration of 4 beamformer and 2 beamformee antennas, we propose to apply the same matrix triangulation to compute the SVD of a 2-by-4 matrix and to compute the QRD of a 4-by-2 matrix. We can achieve gate count reduction by exploiting only one matrix triangulation module in our architecture. The VLSI implementation results under the TSMC 90-ns CMOS technology reveal that our architecture requires 194.25K gates while operating at frequency 200.75 MHz. Additionally, with better normalized matrix throughput and gate efficiency, our architecture outperforms one earlier architectural design to compute the CBWs.
Autors: Tsung-Hsien Liu;Yu-Jie Chen;Yi-Kuang Ko;Yang-Cheng Lin;Yuan-Sun Chu;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 46 - 50
Publisher: IEEE
 
» Hashtagger+: Efficient High-Coverage Social Tagging of Streaming News
Abstract:
News and social media now play a synergistic role and neither domain can be grasped in isolation. On one hand, platforms such as Twitter have taken a central role in the dissemination and consumption of news. On the other hand, news editors rely on social media for following their audience’s attention and for crowd-sourcing news stories. Twitter hashtags function as a key connection between Twitter crowds and the news media, by naturally naming and contextualizing stories, grouping the discussion of news and marking topic trends. In this work, we propose Hashtagger+, an efficient learning-to-rank framework for merging news and social streams in real-time, by recommending Twitter hashtags to news articles. We provide an extensive study of different approaches for streaming hashtag recommendation, and show that pointwise learning-to-rank is more effective than multi-class classification as well as more complex learning-to-rank approaches. We improve the efficiency and coverage of a state-of-the-art hashtag recommendation model by proposing new techniques for data collection and feature computation. In our comprehensive evaluation on real-data, we show that we drastically outperform the accuracy and efficiency of prior methods. Our prototype system delivers recommendations in under 1 minute, with a Precision@1 of 94 percent and article coverage of 80 percent. This is an order of magnitude faster than prior approaches, and brings improvements of 5 percent in precision and 20 percent in coverage. By effectively linking the news stream to the social stream via the recommended hashtags, we open the door to solving many challenging problems related to story detection and tracking. To showcase this potential, we present an application of our recommendations to automated news story tracking via social tags. Our recommendation framework is implemented in a real-time Web system available from insight4news.ucd.ie.
Autors: Bichen Shi;Gevorg Poghosyan;Georgiana Ifrim;Neil Hurley;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Jan 2018, volume: 30, issue:1, pages: 43 - 58
Publisher: IEEE
 
» HE-MAC: Harvest-Then-Transmit Based Modified EDCF MAC Protocol for Wireless Powered Sensor Networks
Abstract:
Energy transfer (ET) and energy harvesting (EH) through radio frequency (RF) signals are a promising technology that can reduce the dependency on batteries in wireless sensor networks. However, there is a tradeoff between the RF-based ET and data communication when they operate in the same frequency band. Therefore, a proper medium access control (MAC) protocol is needed in wireless powered sensor networks (WPSNs). However, a utilization degradation problem occurs when the distributed coordination function (DCF) MAC protocol of the IEEE 802.11 is applied to WPSNs. In order to overcome this problem, this paper extends the IEEE 802.11e enhanced DCF (EDCF) into a harvest-then-transmit-based modified EDCF MAC (HE-MAC) protocol. In addition, the HE-MAC’s Markov chain model and steady-state probabilities are derived and used in the performance analysis. Next, based on the steady-state conditions, optimization is conducted to maximize the EH rate, which satisfies the frame generation rate and transfers additional energy to achieve a self-sustained energy consumption profile. Finally, the simulation performance of EH protocols HE-MAC, RF-MAC, and DOS are compared, where the results show that HE-MAC provides in a superior performance for the range of interest.
Autors: Taeyoung Ha;Junsung Kim;Jong-Moon Chung;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 3 - 16
Publisher: IEEE
 
» Head Motion and Head Gesture-Based Robot Control: A Usability Study
Abstract:
The assistive robot system adaptive head motion control for user-friendly support (AMiCUS) has been developed to increase the autonomy of motion impaired people. The six degrees of freedom robot arm with gripper is controlled with head motion and head gestures only, so especially tetraplegics benefit from collaboration with AMiCUS. In this paper, a usability study with a total number of 30 subjects was conducted to validate the AMiCUS interaction technology and design. 24 able-bodied subjects of demographically diverse groups and 6 tetraplegics participated in this paper. All subjects performed different pick and place tasks by controlling AMiCUS. The evaluation of the interaction design was carried out subjectively with a questionnaire as well as objectively by measurement of time, completion rate, and number of trials for correct head gesture performance. The influence of several factors like age, sex, motion impairment, and previous experience on head motion-based human-robot interaction was analyzed. The interaction design has been proven successful in laboratory environment and assessed overall positive by the subjects. The results of the presented paper confirm the usability of the assistive robot AMiCUS. AMiCUS has the potential to benefit tetraplegics by improving their independence in activities of daily living and adapted workplaces.
Autors: Anja Jackowski;Marion Gebhard;Roland Thietje;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 161 - 170
Publisher: IEEE
 
» Heath Monitoring of Capacitors and Supercapacitors Using the Neo-Fuzzy Neural Approach
Abstract:
Despite their great improvements, reliability and availability of power electronic devices always remain a focus. In safety-critical equipment, where the occurrence of faults can generate catastrophic losses, health monitoring of most critical components is absolutely needed to avoid and prevent breakdowns. In this paper, a noninvasive health monitoring method is proposed. It is based on fuzzy logic and the neural network to estimate and predict the equivalent series resistance (ESR) and the capacitance (C) of capacitors and supercapacitors (SCs). This method, based on the neo-fuzzy neuron model, performs a real-time processing (time series prediction) of the measured device impedance and the degradation data provided by accelerated ageing tests. To prove the efficiency of the proposed method, two experiments are performed. The first one is dedicated to the estimation of the ESR and C for a set of 8 polymer film capacitors, while the second one is dedicated to the prediction of the ESR and C for a set of 18 SCs. The obtained results show that combining fuzzy logic and the neural network is an accurate approach for the health monitoring of capacitors and SCs.
Autors: Abdenour Soualhi;Maawad Makdessi;Ronan German;Francklin Rivas Echeverría;Hubert Razik;Ali Sari;Pascal Venet;Guy Clerc;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 24 - 34
Publisher: IEEE
 
» Heavy-Ion Soft Errors in Back-Biased Thin-BOX SOI SRAMs: Hundredfold Sensitivity Due to Line-Type Multicell Upsets
Abstract:
Silicon-on-insulator technology is often used to develop high-reliability devices with low sensitivity to single-event upsets or soft errors. Its key component, the buried-oxide (BOX) layer, is now thinned down to 10 nm. This thinning enables transistors on the layer to be efficiently conditioned by back-bias voltages fed underneath the layer. However, a little is known about the influence of such conditioning on the sensitivity to soft errors caused by heavy ion radiation. A static random access memory supported by a 10-nm-thick BOX layer was exposed to high-energy heavy ions. Back-bias voltages were fed to the memory cells through a triple well structure fabricated underneath the BOX layer. The applied back-bias conditioning led to a 100-fold increase in the soft-error sensitivity compared with the counterpart zero-bias condition. In addition, interesting line patterns of the upset cells were revealed on the memory floor. These findings are contrary to previous results in neutron and alpha-particle tests. Analyses and modeling as well as supplementary gamma-ray total ionizing dose tests suggest that they are caused by a new soft-error mechanism. Back-bias conditioning may increase perturbations in potential under the BOX layer, which are originally induced by respective single heavy-ion strikes. Each perturbation may spread under the layer and cause multiple cells on the layer to be upset via the capacitance coupling principle.
Autors: Daisuke Kobayashi;Kazuyuki Hirose;Taichi Ito;Yuya Kakehashi;Osamu Kawasaki;Takahiro Makino;Takeshi Ohshima;Daisuke Matsuura;Takanori Narita;Masahiro Kato;Shigeru Ishii;Kazunori Masukawa;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Jan 2018, volume: 65, issue:1, pages: 523 - 532
Publisher: IEEE
 
» Heavy-Tailed Transmission Line Restoration Times Observed in Utility Data
Abstract:
The empirical probability distribution of transmission line restoration times is obtained from 14 years of field data from a large utility. The distribution of restoration times has a heavy tail that indicates that long restoration times, although less frequent, routinely occur. The heavy tail differs from the convenient assumption of exponentially distributed restoration times, impacts power system resilience, and makes estimates of the mean restoration time highly variable.
Autors: Sameera Kancherla;Ian Dobson;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1145 - 1147
Publisher: IEEE
 
» Heteroepitaxial Diamond Field-Effect Transistor for High Voltage Applications
Abstract:
The exceptional performance of diamond-based field-effect transistor technology is not restricted to devices that use single crystalline diamond alone. This letter explores the full potential of the heteroepitaxial diamond field-effect transistor (HED-FET). HED-FET devices were fabricated with a long gate–drain length () configuration using C–H bonded channels, and a high maximum current density of 80 mA/mm and a high ratio of 109 were achieved. Additionally, the HED-FETs showed an average breakdown voltage of ≥500 V and comparatively high breakdown voltage of more than 1 kV. This letter represents a significant step toward the realization of the potential of widely available heteroepitaxial diamond for use in FET applications.
Autors: Mohd Syamsul;Nobutaka Oi;Satoshi Okubo;Taisuke Kageura;Hiroshi Kawarada;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 51 - 54
Publisher: IEEE
 
» Hierarchical Matching Game for Service Selection and Resource Purchasing in Wireless Network Virtualization
Abstract:
Wireless network virtualization is identified as one of the key enabling technologies to bring fifth-generation networks into fruition. In this letter, we model the service selection and resource purchasing problem as a two-stage combinatorial optimization problem. To solve this problem, we propose a hierarchical matching game-based scheme, which satisfies the efficient resource allocation and strict isolation requirements. Simulation results show that our proposal outperforms the fixed sharing approach by 32% and achieves up to 97% of performance obtained by the optimal approach (general sharing scheme) in terms of average sum rate.
Autors: S. M. Ahsan Kazmi;Nguyen H. Tran;Tai Manh Ho;Choong Seon Hong;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 121 - 124
Publisher: IEEE
 
» Hierarchical Spatial Sum–Product Networks for Action Recognition in Still Images
Abstract:
Recognizing actions from still images has been popularly studied recently. In this paper, we model an action class as a flexible number of spatial configurations of body parts by proposing a new spatial sum–product network (SPN). First, we discover a set of parts in image collections via unsupervised learning. Then, our new spatial SPN is applied to model the spatial relationship and also the high-order correlations of parts. To learn robust networks, we further develop a hierarchical spatial SPN method, which models pairwise spatial relationship between parts inside subimages and models the correlation of subimages via extra layers of SPN. Our method is shown to be effective on two benchmark data sets.
Autors: Jinghua Wang;Gang Wang;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 90 - 100
Publisher: IEEE
 
» Hierarchical Voltage Control of Weak Subtransmission Networks With High Penetration of Wind Power
Abstract:
In this paper, we propose a novel coordinated control framework to handle negative voltage impacts caused by wind power in a weak subtransmission system. The designed controller addresses the problem of optimal coordination of controls with different response time and control characteristics. In our control design, the traditional voltage regulators (TVRs) such as on-load tap changers and capacitors are primarily used to regulate voltages in the network. If the control actions of TVRs cannot meet the control requirements, an event-triggered load-side aggregate controller will be activated immediately to help regulate voltages. The control schedules of TVRs are calculated through a multitime-step optimization-based model-predictive control method and are updated with the help of wind power predictions. The load-side controller is realized by controlling active power consumptions of load aggregators through an optimal distributed algorithm that relies on local information exchanges between neighboring load aggregators. The effectiveness of the proposed control scheme is tested through a case study on a modified IEEE 30-bus test system with high penetration of wind power.
Autors: Zhiyuan Tang;David J. Hill;Tao Liu;Haomin Ma;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 187 - 197
Publisher: IEEE
 
» High Extinction Ratio Hybrid Graphene-Silicon Photonic Crystal Switch
Abstract:
In this letter, we demonstrate a compact optical switch realized by integrating a graphene layer with a silicon photonic crystal cavity fabricated using deep UV immersion lithography and a novel transfer printing approach. A 17-dB extinction ratio and 0.75-nm shift in the cavity resonance are measured for a swing voltage of only 1.2 V. The graphene layer is limited to m in size. The experimental results are linked to a theoretical model and used to predict possible improvements to the design.
Autors: Leili Abdollahi Shiramin;Weiqiang Xie;Brad Snyder;Peter De Heyn;Peter Verheyen;Gunther Roelkens;Dries Van Thourhout;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 157 - 160
Publisher: IEEE
 
» High Performance Black Phosphorus Electronic and Photonic Devices with HfLaO Dielectric
Abstract:
As an emerging two-dimensional material, few-layer black phosphorus (BP) shows great potential in nanoelectronics and nanophotonics due to its high carrier velocity. However, non-optimized gate dielectrics often degrade the performance of BP devices severely. In this letter, we demonstrate high-performance BP devices using a novel HfLaO as back gate dielectric with improved interface quality. High current exceeding 1.15 mA/ has been achieved at 20 K for BP transistors with improved noise spectral density. Moreover, BP photodetectors with a record high photoresponsivity up to A/W and fast response time of at 300 K are demonstrated. Excellent photoresponse in a broadband spectrum range from 514 to 1800 nm at 70 K has also been achieved.
Autors: Xiong Xiong;Xuefei Li;Mingqiang Huang;Tiaoyang Li;Tingting Gao;Yanqing Wu;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 127 - 130
Publisher: IEEE
 
» High Performance of Trench Schottky Contact Super Barrier Rectifier With a p-Injector
Abstract:
In this paper, a trench Schottky contact super barrier rectifier (SSBR) with a p-injector (P-T-SSBR) is proposed and investigated by simulation. In addition to the concept of SSBR, the proposed P-T-SSBR also includes a trench gate design and a p-injector plug. The trench gate design eliminating the junction-type field-effect transistor effect of planar gate structure enables the new rectifier to have ultralow forward voltages and a good tradeoff between the forward voltages and reverse leakage currents. The p-injector plug combined with the trenched SSBR cells equips this new rectifier with the merged p-i-n/Schottky operating mechanism resulting in bipolar conducting mode at large forward current densities (larger than 1500 A/cm2) which will be helpful for surge current capability. Compared to the modified SSBR with an -enhancement layer, we presented earlier, simulation results show that, with almost the same breakdown voltage of 57 V, the new rectifier increases the figure of merit (equates to ) by 35.1% at the forward current density of 200 A/cm2, decreases the reverse leakage current by 34.9%, and decreases the reverse recovery time by 25.4% at the reverse voltage of 12 V.
Autors: Wensuo Chen;Ruijin Liao;Peijian Zhang;Zheng Zeng;Bo Zhang;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 215 - 222
Publisher: IEEE
 
» High Performance Parallel Single-Phase Converter Reconfiguration for Enhanced Availability
Abstract:
Paralleling power converters is a common practice in industries to enhance total power rating, reliability, and availability of the system. In case of fault occurring in systems with parallel converters, the faulty power converter can be isolated and the system can still be operated at reduced power level. In this paper, a grid-connected power converter consisting of two parallel H-bridge converters with low ground leakage current is considered. Two contingency configurations, that are also of low ground leakage current, are proposed to enhance the availability of the system. This is done by reconfiguring the power circuit to a single H-bridge in the case of failure in one of the bridges. The power converter is experimentally tested with the proposed configurations for experimental validation. The results show that the second configuration has better performance in terms of power loss and current total harmonic distortion when operating at lower power level.
Autors: Mohammad Hassan Hedayati;Vinod John;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Jan 2018, volume: 54, issue:1, pages: 388 - 394
Publisher: IEEE
 
» High-Accuracy Heart Rate Variability Monitoring Using Doppler Radar Based on Gaussian Pulse Train Modeling and FTPR Algorithm
Abstract:
This paper presents the theoretical and experimental study of a novel noncontact heart-beat signal modeling and estimation algorithm using a compact 2.4-GHz Doppler radar. The proposed technique is able to accurately reconstruct the heart-beat signal and generates heart rate variability indices at a distance of 1.5 m away from the human body. The feasibility of the proposed approach is validated by obtaining data from eight human subjects and comparing them with photoplethysmography (PPG) measurements. A Gaussian pulse train model is suggested for the heart-beat signal along with a modified-and-combined autocorrelation and frequency-time phase regression technique for high-accuracy detection of the human heart-beat rate. The proposed method is accurate, robust, and simple, and demonstrates an average heart-beat detection accuracy of more than 90% at a distance of 1.5 m away from the subjects. In addition, the average beat-to-beat time intervals extracted from the proposed model and signal reconstruction method show less than 2% error compared to PPG measurements. Bland–Altman analysis further validated the accuracy of the proposed approach in comparison with reference data.
Autors: Mehrdad Nosrati;Negar Tavassolian;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 556 - 567
Publisher: IEEE
 
» High-Accuracy Synchronous Extraction Algorithm of Star and Celestial Body Features for Optical Navigation Sensor
Abstract:
This paper provides an optimal high-performance image processing algorithm for a miniaturized independent optical navigation sensor, which combines the functions of a star tracker and a navigation camera. This novel image processing algorithm is capable of extracting two different types of optical navigation measurements from a raw image. The aim is to simultaneously extract stars and target celestial body features with high accuracy and reliability to estimate observer-to-body relative position in subsequent navigation process. This paper presents star and celestial body imaging models and a novel slope edge model. We propose an high-performance algorithm to achieve the synchronous extraction of star and celestial body image features based on the aforementioned models. Double-window variance difference method is proposed to segment and classify stars and edge image regions of a celestial body with strong robustness. The sub-pixel level position of star centroid and celestial body edges are then simultaneously extracted by using the same operator on the basis of the consistency of the derivative distribution of star and celestial body edge profiles. The edge extraction deviation when using the slope edge model is also analyzed and compensated, and the accuracy of the celestial body edge extraction is improved to a higher level. The proposed algorithm has excellent feature extraction performance in terms of qualitative and quantitative measurements. This paper has established a technical foundation for the development of the miniaturized independent optical navigation sensor, which is low cost, light weight and has flexible applicability due to its high accuracy and robustness.
Autors: Jie Jiang;Hao Wang;Guangjun Zhang;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 713 - 723
Publisher: IEEE
 
» High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection
Abstract:
Robust and efficient infrared (IR) small target detection plays an important role in image processing for IR remote sensing. In order to detect the IR small target with high detection rate, low false alarm rate (FAR), and high detection speed, a novel method called high-boost-based multiscale local contrast measure (HB-MLCM) is proposed in this letter. First, improved high boost filter is proposed to enhance the high frequency signal where the target may appear and suppress the low frequency signal. Then, a simple MLCM is proposed for further enhancing the target and suppressing the background. Finally, a simple and adaptive thresholding method is used to segment targets from the contrast map. Experimental results on three real image sequences with various typical complex backgrounds demonstrate that the proposed method can effectively detect the target with faster speed, higher detection rate, and lower FAR compared with the state-of-the-art methods.
Autors: Yafei Shi;Yantao Wei;Huang Yao;Donghui Pan;Guangrun Xiao;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 33 - 37
Publisher: IEEE
 
» High-Efficiency mosfet-Based MMC Design for LVDC Distribution Systems
Abstract:
Low-voltage dc (LVdc) distribution networks have the potential to release larger capacity without having to upgrade the existing cables. One of the main challenges of LVdc networks is the extra customer-end dc–ac conversion stage. This paper proposes and evaluates a five-level Si mosfet-based modular multilevel converter (MMC) as a promising alternative to the conventional two-level insulated gate bipolar transistor-based converter. This is due to the comparatively higher efficiency, power quality and reliability, and reduced electromagnetic (EM) emissions. A comprehensive analysis of a Si mosfet five-level MMC converter design is performed to investigate the suitability of the topology for LVdc applications. Detailed theoretical analysis of the five-level MMC is presented, with simulated and experimental results to demonstrate circuit performance. To suppress the ac circulating current, especially the dominant second harmonics, this paper presents a double line-frequency proportional integral (PI) with orthogonal imaginary axis control method. Comparison of simulation and experimental results with those for double line-frequency proportional resonant control shows that the proposed PI controller has a better performance. In addition, it is simpler to implement and more immune to sampling/discretization errors.
Autors: Yanni Zhong;Nina Roscoe;Derrick Holliday;Tee Chong Lim;Stephen J. Finney;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Jan 2018, volume: 54, issue:1, pages: 321 - 334
Publisher: IEEE
 
» High-Fidelity Model Order Reduction for Microgrids Stability Assessment
Abstract:
Proper modeling of inverter-based microgrids is crucial for accurate assessment of stability boundaries. It has been recently realized that the stability conditions for such microgrids are significantly different from those known for large-scale power systems. In particular, the network dynamics, despite its fast nature, appears to have major influence on stability of slower modes. While detailed models are available, they are both computationally expensive and not transparent enough to provide an insight into the instability mechanisms and factors. In this paper, a computationally efficient and accurate reduced-order model is proposed for modeling inverter-based microgrids. The developed model has a structure similar to quasi-stationary model and at the same time properly accounts for the effects of network dynamics. The main factors affecting microgrid stability are analyzed using the developed reduced-order model and shown to be unique for microgrids, having no direct analogy in large-scale power systems. Particularly, it has been discovered that the stability limits for the conventional droop-based system are determined by the ratio of inverter rating to network capacity, leading to a smaller stability region for microgrids with shorter lines. Finally, the results are verified with different models based on both frequency and time domain analyses.
Autors: Petr Vorobev;Po-Hsu Huang;Mohamed Al Hosani;James L. Kirtley;Konstantin Turitsyn;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 874 - 887
Publisher: IEEE
 
» High-Frequency Radar Ocean Surface Cross Section Incorporating a Dual-Frequency Platform Motion Model
Abstract:
The first- and second-order high-frequency radar cross sections of the ocean surface are derived for an antenna on a floating platform. In this analysis, simulations are conducted for a more complicated platform motion than appear in earlier work and comparisons are made to model outputs for a fixed antenna. Results show that motion-induced peaks appear symmetrically in the Doppler frequency and have less energy in the second-order radar cross section than those in the first-order radar cross section. The magnitude and width of the Bragg peaks are seen to decrease and broaden, respectively, as compared to the case for a fixed antenna. The platform motion modulates the radar signals as a frequency modulator, and the modulation indices are related to the amplitudes of the platform motion. With a larger amplitude of platform motion, more energy is transferred from the Bragg peaks to the motion-induced peaks, and more motion-induced peaks need to be considered.
Autors: Yue Ma;Weimin Huang;Eric W. Gill;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Jan 2018, volume: 43, issue:1, pages: 195 - 204
Publisher: IEEE
 
» High-Gain and High-Efficiency GRIN Metamaterial Lens Antenna With Uniform Amplitude and Phase Distributions on Aperture
Abstract:
A gradient index (GRIN) metamaterial lens antenna with extremely high gain and high aperture efficiency is presented. The proposed antenna is much more advantageous in terms of gain and aperture efficiency without compromising in simplicity and stability. The gain and aperture efficiency are improved by using a new method to design the GRIN lens for a hybrid mode, which possesses both uniform amplitude and phase distributions on the aperture. At the center of frequency band (14.25 GHz), the proposed antenna achieves a gain of 26.6 dBi, which corresponds to aperture efficiency greater than 90%.
Autors: Zui Tao;Wei Xiang Jiang;Hui Feng Ma;Tie Jun Cui;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 16 - 22
Publisher: IEEE
 
» High-Level Asynchronous Concepts at the Interface Between Analog and Digital Worlds
Abstract:
Asynchronous circuits are becoming increasingly important in system design for Internet of Things, where they orchestrate the interface between big synchronous computation components and the analog environment, which is inherently asynchronous and has high uncertainty with respect to power supply, temperature, and long-term aging effects. However, wide adoption of asynchronous circuits by industrial users is hindered by a steep learning curve for asynchronous control models, such as signal transition graphs (STGs), that are developed by the academic community for specification, verification, and synthesis of asynchronous circuits. In this paper, we introduce a novel high-level description language for asynchronous circuits, which is based on behavioral concepts—high-level descriptions of asynchronous circuit requirements, that can be shared, reused, and extended by users, and can be automatically translated to STGs for further processing by conventional asynchronous and synchronous electronic design automation tools, such as Petrify and Mpsat. Our aim is to simplify the process of capturing system requirements in the form of a formal specification, and to promote behavioral concepts as a means for design reuse. The proposed design flow is fully automated in open-source toolsuite Workcraft, and is applied to the development of an asynchronous power regulator.
Autors: Jonathan Beaumont;Andrey Mokhov;Danil Sokolov;Alex Yakovlev;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Jan 2018, volume: 37, issue:1, pages: 61 - 74
Publisher: IEEE
 
» High-Performance Double-Gate $alpha $ -InGaZnO ISFET pH Sensor Using a HfO2 Gate Dielectric
Abstract:
In this paper, we present a high-performance double-gate (DG) amorphous indium–gallium–zinc–oxide (-InGaZnO) ion-sensitive field-effect transistor (ISFET) using three HfO2 gate dielectric thicknesses as a top gate (TG). The DG structure -InGaZnO TFTs with a 40-nm TG HfO2 dielectric exhibited a small threshold voltage of 50 mV, a low subthreshold swing of 144.1 mV/decade, and a high current ratio of . The -InGaZnO ISFET prepared at the 40-nm HfO2 sensing membrane in the DG mode showed a pH sensitivity of 937 mV/pH, which is far more than the Nernst limit. The hysteresis and drift behaviors of DG ISFET fabricated with the 40-nm condition also showed relatively better chemical stability compared with other conditions.
Autors: Chih-Hung Lu;Tuo-Hung Hou;Tung-Ming Pan;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 237 - 242
Publisher: IEEE
 
» High-Resolution Gamma-Ray Spectroscopy With a SiPM-Based Detection Module for 1” and 2” LaBr3:Ce Readout
Abstract:
In this paper, we present a silicon photomultiplier (SiPM)-based photodetector module designed to readout large cerium-doped lanthanum bromide (LaBr3:Ce) scintillators (cylindrical 1” 1” and 2” 2”) for nuclear physics experiments. The detector prototype has a modular structure and implements a real-time stabilization of the SiPM gain to compensate for the gain drift with temperature. The SiPM module consists of an array of 5 by 6 near-ultraviolet high-density SiPMs (Fondazione Bruno Kessler, Italy), each one having an active area of 6 mm 6 mm and 30- microcells. The single array is used for the 1” crystal readout, and it is assembled in a format to read the 2” scintillator. Spectroscopic measurements were performed with both crystals. The 2” crystal was irradiated with different radioactive sources in an energy range between 122 keV and 1.3 MeV, and an energy resolution of 3.19 ± 0.01% full-width at half-maximum (FWHM) has been achieved at 662 keV. The result is very close to the 3.07 ± 0.03% FWHM measured with Super Bialkali photomultiplier tube (PMT) (Hamamatsu R6233-100) at the same energy with the same 2” crystal. In the framework of the comparison between SiPM and PMT for LaBr3:Ce readout, we provide an analysis of the energy resolution contributions based on the measurements performed with the develope- gamma-ray detection system.
Autors: Giulia Cozzi;Paolo Busca;Marco Carminati;Carlo Fiorini;Giovanni L. Montagnani;Fabio Acerbi;Alberto Gola;Giovanni Paternoster;Claudio Piemonte;Veronica Regazzoni;Nives Blasi;Franco Camera;Benedicte Million;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Jan 2018, volume: 65, issue:1, pages: 645 - 655
Publisher: IEEE
 
» High-Resolution Interannual Mass Anomalies of the Antarctic Ice Sheet by Combining GRACE Gravimetry and ENVISAT Altimetry
Abstract:
Knowledge of interannual mass variations of the Antarctic ice sheet (AIS) associated with its surface mass change is important for correctly interpreting the long-term mass trend and evaluating the fidelity of surface mass balance from regional climate models. Here, we revisit the interannual anomalies of mass change from Gravity Recovery and Climate Experiment and elevation change from ENVISAT over the AIS during 2003–2009, with the objective of obtaining higher resolution interannual mass anomalies based on ENVISAT data. High positive correlations (>0.6) between the two interannual anomalies are primarily found over the west AIS and coastal regions in the east AIS, occupying more than 40% of the AIS. By combining the two interannual anomalies, we are able to estimate the density of snow/ice changing interannually over regions in the AIS. Especially over the Amundsen Sea sector with significant interannual signals, the temporal variability of the density of snow/ice associated with interannual anomalies is shown for the first time, which agrees with the events of excess snow accumulation and the accelerated ice discharge occurring there. Furthermore, we demonstrate the feasibility of obtaining higher resolution interannual mass anomalies over the west AIS, based on the density-corrected ENVISAT data. Negative correlations, which were also found in a previous study, are likely related to errors in the relatively weak interannual signals.
Autors: Xiaoli Su;C. K. Shum;Junyi Guo;Ian M. Howat;Chungyen Kuo;Kenneth C. Jezek;Jianbin Duan;Yuchan Yi;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 539 - 546
Publisher: IEEE
 
» High-Temperature Magnetic Properties of Anisotropic SmCo7/Fe(Co) Bulk Nanocomposite Magnets
Abstract:
High-temperature magnetic properties of the anisotropic bulk SmCo7/Fe(Co) nanocomposite magnets prepared by multistep deformation have been investigated and compared with the corresponding isotropic nanocomposites. The anisotropic SmCo7/Fe(Co) nanocomposites with a Fe(Co) fraction of 28% exhibit much higher energy products than the corresponding isotropic nanocomposites at both room and high temperatures. These magnets show a small remanence (%/K) and a coercivity (%/K) temperature coefficient which can be comparable to those of the conventional SmCo5 and Sm2Co17 high-temperature magnets. The magnetic properties of these nanocomposites at high temperatures are sensitive to the weight fractions of the Fe(Co) phase. This paper demonstrates that the anisotropic bulk SmCo7/Fe(Co) nanocomposites have better high-temperature magnetic properties than the corresponding isotropic ones.
Autors: Wenpeng Song;Xiaohong Li;Li Lou;Yingxin Hua;Qian Zhang;Guangwei Huang;Fuchen Hou;Xiangyi Zhang;
Appeared in: IEEE Transactions on Magnetics
Publication date: Jan 2018, volume: 54, issue:1, pages: 1 - 5
Publisher: IEEE
 
» Highly Accurate Facial Nerve Segmentation Refinement From CBCT/CT Imaging Using a Super-Resolution Classification Approach
Abstract:
Facial nerve segmentation is of considerable importance for preoperative planning of cochlear implantation. However, it is strongly influenced by the relatively low resolution of the cone-beam computed tomography (CBCT) images used in clinical practice. In this paper, we propose a super-resolution classification method, which refines a given initial segmentation of the facial nerve to a subvoxel classification level from CBCT/CT images. The super-resolution classification method learns the mapping from low-resolution CBCT/CT images to high-resolution facial nerve label images, obtained from manual segmentation on micro-CT images. We present preliminary results on dataset, 15 ex vivo samples scanned including pairs of CBCT/CT scans and high-resolution micro-CT scans, with a leave-one-out evaluation, and manual segmentations on micro-CT images as ground truth. Our experiments achieved a segmentation accuracy with a Dice coefficient of , surface-to-surface distance of , and Hausdorff distance of . We compared the proposed technique to two other semi-automated segmentation software tools, ITK-SNAP and GeoS, and show the ability of the proposed approach to yield subvoxel levels of accuracy in delineating the facial nerve.
Autors: Ping Lu;Livia Barazzetti;Vimal Chandran;Kate Gavaghan;Stefan Weber;Nicolas Gerber;Mauricio Reyes;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Jan 2018, volume: 65, issue:1, pages: 178 - 188
Publisher: IEEE
 
» Highly Tunable Electrostatic Nanomechanical Resonators
Abstract:
There has been significant interest toward highly tunable resonators for on-demand frequency selection in modern communication systems. Here, we report highly tunable electrostatically actuated silicon-based nanomechanical resonators. In-plane doubly clamped bridges, slightly curved as shallow arches due to residual stresses are fabricated using standard electron beam lithography and surface nanomachining. The resonators are designed such that the effect of midplane stretching dominates the softening effect of the electrostatic force. This is achieved by controlling the gap-to-thickness ratio and by exploiting the initial curvature of the structure from fabrication. We demonstrate considerable increase in the resonance frequency of nanoresonators with the dc bias voltages up to 108% for 180 nm thick structures with a transduction gap of 1 μm separating them from the driving/sensing electrodes. The experimental results are found in good agreement with those of a nonlinear analytical model based on the Euler–Bernoulli beam theory. As a potential application, we demonstrate a tunable narrow bandpass filter using two electrically coupled nanomechanical arch resonators with varied dc bias voltages.
Autors: Syed N. R. Kazmi;Amal Z. Hajjaj;Md A. Al Hafiz;Pedro M. F. J. Costa;Mohammad I. Younis;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 113 - 121
Publisher: IEEE
 
» HiPiler: Visual Exploration of Large Genome Interaction Matrices with Interactive Small Multiples
Abstract:
This paper presents an interactive visualization interface—HiPiler—for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of regions on the genome to each other and can contain up to 3 million rows and columns with many sparse regions. Regions of interest (ROIs) can be defined, e.g., by sets of adjacent rows and columns, or by specific visual patterns in the matrix. However, traditional matrix aggregation or pan-and-zoom interfaces fail in supporting search, inspection, and comparison of ROIs in such large matrices. In HiPiler, ROIs are first-class objects, represented as thumbnail-like “snippets”. Snippets can be interactively explored and grouped or laid out automatically in scatterplots, or through dimension reduction methods. Snippets are linked to the entire navigable genome interaction matrix through brushing and linking. The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices. We describe six exploration tasks that are crucial for analysis of interaction matrices and demonstrate how HiPiler supports these tasks. We report on a user study with a series of data exploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.
Autors: Fritz Lekschas;Benjamin Bach;Peter Kerpedjiev;Nils Gehlenborg;Hanspeter Pfister;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 522 - 531
Publisher: IEEE
 
» Hollow Clay Brick Wall Propagation Analysis and Modified Brick Design for Enhanced Wi-Fi Coverage
Abstract:
The radiowave propagation through hollow clay brick walls, which are common in southern European construction, is analyzed. The brick walls have thicknesses of 11, 15, and 20 cm, common in both interior and exterior walls, and are bound with a portland cement, water, and sand mixture. For each brick dimension, three prototypes were assembled, varying in the type of wall finish, i.e., exposed brick, smooth painted plaster, and rough painted plaster. A 10 cm concrete wall was also included for comparison purposes. Penetration loss metrics were evaluated in an anechoic chamber at frequencies ranging from 680 MHz to 10 GHz. Results demonstrate that the brick wall internal heterogeneity, as well as the type of finish, significantly influences the propagation phenomena and thus the frequency response of the walls, with relatively high penetration losses observed at some relevant commercial frequency bands. Finally, an alternative brick design, with reduced penetration losses, is also proposed and evaluated under simulation environment only.
Autors: David Ferreira;Rafael F. S. Caldeirinha;Telmo R. Fernandes;Iñigo Cuiñas;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 331 - 339
Publisher: IEEE
 
» HoneyBot: A Honeypot for Robotic Systems
Abstract:
Historically, robotics systems have not been built with an emphasis on security. Their main purpose has been to complete a specific objective, such as to deliver the correct dosage of a drug to a patient, perform a swarm algorithm, or safely and autonomously drive humans from point A to point B. As more and more robotic systems become remotely accessible through networks, such as the Internet, they are more vulnerable to various attackers than ever before. To investigate remote attacks on networked robotic systems we have leveraged HoneyPhy, a physics-aware honeypot framework, to create the HoneyBot. The HoneyBot is the first software hybrid interaction honeypot specifically designed for networked robotic systems. By simulating unsafe actions and physically performing safe actions on the HoneyBot we seek to fool attackers into believing their exploits are successful, while logging all the communication to be used for attacker attribution and threat model creation. In this paper, we present the HoneyBot and discuss our proof of concept implementation. Our HoneyBot prototype swaps between physical actuation and using prebuilt models of sensor behavior for simulation at runtime given user input commands.
Autors: Celine Irvene;David Formby;Samuel Litchfield;Raheem Beyah;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 61 - 70
Publisher: IEEE
 
» Hotspot-Oriented Green Frameworks for Ultrasmall Cell Cloud Radio Access Networks
Abstract:
Sleep-mode operation of base stations aims to switch OFF some hardware modules to reduce power consumption while not degrading the quality of service. In this paper, novel hotspot-oriented green frameworks based on sleep-mode operation of remote radio heads (RRHs) are proposed for cloud radio access networks (C-RANs). The tradeoff between the reduction in power consumption of RRHs and the increase in transmission power at user equipment (UE) is first analyzed based on realistic models for ultrasmall cell C-RANs. In the proposed energy-efficient frameworks, corresponding clustering strategies are adopted to ensure that active RRHs are located as near as possible to hotspot areas for different infrastructure conditions and information availabilities. This reduces the increase in the uplink transmission power while maximizing the overall RRH power reduction. The green frameworks are modeled using C-RANs based on random topologies. It is shown that area power consumption can be reduced by more than 79% at a low traffic level compared with no sleep-mode operation. One of the frameworks is also compared with a baseline strategy that deals with hotspot areas and shows a 70% reduction in UE transmission power. The pros and cons of applying different frameworks are also investigated and analyzed.
Autors: Zhehan Li;David Grace;Paul Mitchell;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 703 - 717
Publisher: IEEE
 
» How Do Ancestral Traits Shape Family Trees Over Generations?
Abstract:
Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).
Autors: Siwei Fu;Hao Dong;Weiwei Cui;Jian Zhao;Huamin Qu;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 205 - 214
Publisher: IEEE
 
» How Robust Is Your Development Team?
Abstract:
Given the collaborative nature of software development, a robust team is a necessity for project success in both commercial and open source environments. That is, in the event of developers’ absence due to various reasons, how could it potentially disrupt a team’s routine operations? This article offers an automatic approach to intuitively visualize development team hierarchy, quantify overall team robustness, and identify the point (developers) of risk for team robustness. An investigation of six Apache open source projects has shown its effectiveness. This article is part of a special issue on Actionable Analytics for Software Engineering.
Autors: Lu Xiao;Zhongyuan Yu;Bohong Chen;Xiao Wang;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 64 - 71
Publisher: IEEE
 
» Human-Enabled Edge Computing: Exploiting the Crowd as a Dynamic Extension of Mobile Edge Computing
Abstract:
The MEC vision leverages the availability of powerful and low-cost middleboxes, statically deployed at suitable edges of the network and acting as local proxies for the centralized cloud backbone; this potentially enables, among other things, better scalability and better reactivity in the interaction with mobile nodes via local control decisions and actuation. MEC has already been proposed as an enabler for several Internet of Things and cyber-physical systems application scenarios, and also mutual benefits due to the integration of MEC and mobile crowdsensing (MCS). The article originally proposes human-driven edge computing (HEC) as a new model to ease the provisioning and to extend the coverage of traditional MEC solutions. From a methodological perspective, we show how it is possible to exploit MCS i) to support the effective deployment of fixed MEC (FMEC) proxies and ii) to further extend their coverage through the introduction of impromptu and human-enabled mobile MEC (M2EC) proxies. In addition, we describe how we have implemented these novel concepts in the MCS ParticipAct platform through the integration of the MEC Elijah platform in the ParticipAct living lab, an ongoing MCS real-world experiment that involved about 170 students at the University of Bologna for more than two years. Reported experimental results quantitatively show the effectiveness of the proposed techniques in elastically scaling the load at edge nodes according to runtime provisioning needs.
Autors: Paolo Bellavista;Stefano Chessa;Luca Foschini;Leo Gioia;Michele Girolami;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 145 - 155
Publisher: IEEE
 
» Humanitarian Activities Make a Difference [President's Message]
Abstract:
Presents the President’s message for this issue of the publication.
Autors: Tomy Sebastian;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 4 - 5
Publisher: IEEE
 
» Hybrid Access Femtocells in Overlaid MIMO Cellular Networks With Transmit Selection Under Poisson Field Interference
Abstract:
This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or preprocessed interference-aware operation. This paper presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.
Autors: Amr A. AbdelNabi;Fawaz S. Al-Qahtani;Redha M. Radaydeh;Mohammad Shaqfeh;
Appeared in: IEEE Transactions on Communications
Publication date: Jan 2018, volume: 66, issue:1, pages: 163 - 179
Publisher: IEEE
 
» Hybrid Dual Mode Sensor for Simultaneous Detection of Two Serum Metabolites
Abstract:
Metabolites are the ultimate readout of disease phenotype that plays a significant role in the study of human disease. Multiple metabolites sometimes serve as biomarkers for a single metabolic disease. Therefore, simultaneous detection and analysis of those metabolites facilitate early diagnostics of the disease. Conventional approaches to detect and quantify metabolites include mass spectrometry and nuclear magnetic resonance that require bulky and expensive equipment. Here, we present a disposable sensing platform that is based on complementary metal–oxide–semiconductor process. It contains two sensors: an ion sensitive field-effect transistor and photodiode that can work independently for detection of pH and color change produced during the metabolite-enzyme reaction. Serum glucose and cholesterol have been detected and quantified simultaneously with the new platform, which shows good sensitivity within the physiological range. Low cost and easy manipulation make our device a prime candidate for personal metabolome sensing diagnostics.
Autors: Chunxiao Hu;Mohammed A. Al-Rawhani;Boon Chong Cheah;Srinivas Velugotla;David R. S. Cumming;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 484 - 493
Publisher: IEEE
 
» Hybrid Half-Duplex/Full-Duplex Cooperative Non-Orthogonal Multiple Access With Transmit Power Adaptation
Abstract:
Power allocation is an important issue in order to optimize the performance of non-orthogonal multiple access (NOMA) systems. However, the power allocation problem for cooperative NOMA systems has not been well investigated. In this paper, we investigate the power allocation problems for half-duplex cooperative NOMA (HD-CNOMA) and full-duplex cooperative NOMA (FD-CNOMA) systems, respectively. From the fairness standpoint, the optimization problem for each system is formulated to maximize the minimum achievable user rate in a NOMA user pair. Even though both of the formulated problems are neither concave nor quasi-concave, the optimal closed-form solutions of both cases are still obtained with the proposed two-step method. First, we transform the initial problem into a quasi-concave problem by treating the relay transmit power, namely , as a constant, and then solve the obtained quasi-concave problem. Second, we convert the original problem into a univariate problem of based on the results of the first step, and eventually obtain the optimal power allocation. In addition, a hybrid half/full-duplex cooperative NOMA scheme, which dynamically switches between the HD-CNOMA and FD-CNOMA mode, is proposed. After that, a relay selection scheme is also investigated to extend the hybrid scheme into general networks with multiple users. Numerical results demonstrate that the proposed hybrid relaying scheme can achieve a significant performance improvement with respect to the conventional NOMA, HD-CNOMA, and FD-CNOMA scheme.
Autors: Gang Liu;Xianhao Chen;Zhiguo Ding;Zheng Ma;F. Richard Yu;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 506 - 519
Publisher: IEEE
 
» Hybrid Labels Are the New Measure!
Abstract:
Developing minimum viable products (MVPs) is critical for start-up companies to hit the market fast with an accepted level of performance. The US Food and Drug Administration mandates additional nonfunctional requirements in healthcare systems, meaning that the MVP should provide the best availability, privacy, and security. This critical demand is motivating companies to further rely on analytics to optimize the development process. In a collaborative project with Brightsquid, the authors provided a decision-support system based on analogical reasoning to assist in effort estimation, scoping, and assignment of change requests. This experience report proposes a new metric, change request labels, for better prediction. Using different methods for textual-similarity analysis, the authors found that the combination of machine-learning techniques with experts’ manually added labels has the highest prediction accuracy. Better prediction of change impacts allows a company to optimize its resources and provide proper timing of releases to target MVPs. This article is part of a special issue on Actionable Analytics for Software Engineering.
Autors: Maleknaz Nayebi;Shaikh Jeeshan Kabeer;Guenther Ruhe;Chris Carlson;Francis Chew;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 54 - 57
Publisher: IEEE
 
» Hybrid Massive MIMO for Secure Transmissions Against Stealthy Eavesdroppers
Abstract:
Physical-layer secure transmissions require that the legitimate parties Alice and Bob have certain signal advantages over the eavesdropper Eve. Unfortunately, it is still unknown what advantages can be guaranteed realistically in practice. This letter shows that hybrid massive MIMO can be exploited to the advantage of Alice for this purpose. Specifically, it allows Alice to use large antenna arrays that stealthy eavesdroppers cannot afford in many practical situations. To realize this advantage, an efficient transmission scheme is developed with hybrid massive MIMO, random dumb antenna selection, and channel reciprocity-based signal randomization techniques. It can secure the transmission against multiple stealthy eavesdroppers. Transmission security is analyzed assuming eavesdroppers with sufficient side knowledge and channel estimation capabilities. Simulations are conducted to verify the superior performance.
Autors: Xiaohua Li;Yun Zhang;Wednel Cadeau;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 81 - 84
Publisher: IEEE
 
» Hybrid Optimization for Economic Deployment of ESS in PV-Integrated EV Charging Stations
Abstract:
Electric vehicle (EV) charging stations will play an important role in the smart city. Uncoordinated and statistical EV charging loads would further stress the distribution system. Photovoltaic (PV) systems, which can reduce this stress, also show variation due to weather conditions. In this paper, a hybrid optimization algorithm for energy storage management is proposed, which shifts its mode of operation between the deterministic and rule-based approaches depending on the electricity price band allocation. The cost degradation model of the energy storage system (ESS) along with the levelized cost of PV power is used in the case of EV charging stations. The algorithm comprises of three parts: categorization of real-time electricity price in different price bands, real-time calculation of PV power from solar irradiation data, and optimization for minimizing the operating cost of EV charging station integrated with PV and ESS. An extensive simulation study is carried out with an uncoordinated and statistical EV charging model in the context of Singapore to check effectiveness of this algorithm. Furthermore, detailed analysis of subsidy and incentive to be given by the government agencies for higher penetration of renewable energy is also presented. This work would aid in planning of adoption of PV-integrated EV charging stations, which would expectedly replace traditional gas stations in future.
Autors: Kalpesh Chaudhari;Abhisek Ukil;K Nandha Kumar;Ujjal Manandhar;Sathish Kumar Kollimalla;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 106 - 116
Publisher: IEEE
 
» Hybrid Plasmonic Nanoantenna With the Capability of Monolithic Integration With Laser and Photodetector on InP Substrate
Abstract:
In this paper, a novel InP-based hybrid plasmonic (HP) bowtie nanoantenna with director was proposed that can serve as a good alternative to the silicon-on-insulator based ones. The proposed bowtie HP nanoantenna is capable of monolithic integration with laser and photodetector at optical communication wavelengths. By using the finite-element method, it was observed that the device can radiate and receive the optical field with a gain of about 9 dB at frequency range of 180 to 220 THz. In addition, the results showed that this device is expandable in array structure. Antenna gains with two diverse array arrangements of single row and square array were also determined.
Autors: Mahmoud Nikoufard;Abbas Nourmohammadi;Saeid Esmaeili;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 3 - 8
Publisher: IEEE
 
» Hybrid PWM/DPAM Dimming Control for Digital Color Shift Keying Using RGB-LED Array
Abstract:
As a method of dimming support for visible light communications using a massive LED array, we consider a hybrid pulse width modulation/digitally controlled pulse amplitude modulation (PWM/DPAM) system. Especially, in this paper, we consider a digital color shift keying (DCSK) using an RGB-LED array as an optical intensity modulation scheme, that transmits data through the ratio of the optical intensities (i.e., color) emitted by red, green, and blue LEDs. In DCSK, since only one color is activated in each RGB-LED at a time, the color can be represented by the combination of the digitally (i.e., linearly) controlled “ON-OFF” LEDs. In general, for the dimming control system of DCSK, two schemes have been considered. One is the dimming control by PWM, which changes the duty cycle of optical transmit signals, and the other is the dimming control by DPAM, which changes the number of active LEDs in the RGB-LED array. In this paper, PWM and DPAM are combined to realize a higher spectral efficiency than PWM and a wider dimming range than DPAM. We evaluate the error performances of the proposed system, DCSK with PWM, and DCSK with DPAM from a simulation analysis under several measured light dimming levels. The results show that DPAM should be used only for low bit rate systems because the effect of inter-symbol-interference (ISI), caused by the LED frequency response, increases at a high bit rate. While, PWM is significantly robust against ISI because the PWM signal duration is limited in a symbol duration at the low dimming levels and the empty duration can mitigate the effect of ISI even if the bit rate is high. When focusing on symbol error rate performances corresponding to the dimming levels, the hybrid dimming control and the PWM dimming control can achieve lower signal energy-to-noise-ratio at the dimming level of low and high, respectively.
Autors: Jumpei Okumura;Yusuke Kozawa;Yohtaro Umeda;Hiromasa Habuchi;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 45 - 52
Publisher: IEEE
 
» Hybrid-Trip-Model-Based Energy Management of a PHEV With Computation-Optimized Dynamic Programming
Abstract:
Plug-in hybrid electric vehicles (PHEVs) with fuel and electricity have demonstrated the capability to reduce fuel consumption and emissions by adopting appropriate energy management strategies. In the existing energy management strategies, the dynamic programming (DP)-based energy management strategy (EMS) can realize the global optimization of the fuel consumption if the global vehicle-speed trajectory is known in advance. The global vehicle-speed trajectory can be obtained by applying GPS data of vehicles when the trip path is determined. However, for a trip path without GPS data, the global vehicle-speed trajectory is difficult to be gained. In this case, the DP-based EMS cannot be utilized to achieve the globally optimal fuel consumption, which is the issue discussed in this paper. This paper makes the following two contributions to solve this issue. First of all, the cell transmission model of the road traffic flow and the vehicle kinematics are introduced to obtain the traffic speeds of road segments and the accelerations of the PHEV. On this basis, a hybrid trip model is presented to obtain the vehicle-speed trajectory for the trip path without GPS data. Next, a DP-based EMS with prediction horizon is proposed, and moreover, in order to improve its real-time implementation, a search range optimization algorithm of the state of charge (SOC) is designed to reduce the computational load of DP. In summary, we propose a computation-optimized DP-based EMS through applying the hybrid trip model. Finally, a simulation study is conducted for applying the proposed EMS to a practical trip path in Beijing road network. The results show that the hybrid trip model can effectively construct the vehicle-speed trajectory online, and the average accuracy of the vehicle-speed trajectory is more than 78%. In addition, compared with the existing optimization algorithm for DP calculation, the SOC search range optimization algorithm can further reduce the calcu- ation load of DP. More importantly, compared to the globally optimal DP-based EMS, although the proposed EMS makes the fuel consumption grow less than 5.36%, it can be implemented in real time. Moreover, compared with the existing real-time strategies, it can further reduce the fuel consumption and emissions. Thus, the proposed EMS can offer an effective solution for the PHEV applying it online in the trip path without GPS data.
Autors: Jichao Liu;Yangzhou Chen;Wei Li;Fei Shang;Jingyuan Zhan;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Jan 2018, volume: 67, issue:1, pages: 338 - 353
Publisher: IEEE
 
» HYDRA: Heterodyne Crosstalk Mitigation With Double Microring Resonators and Data Encoding for Photonic NoCs
Abstract:
Silicon-photonic networks on chip (PNoCs) provide high bandwidth with lower data-dependent power dissipation than does the traditional electrical NoCs (ENoCs); therefore, they are promising candidates to replace ENoCs in future manycore chips. PNoCs typically employ photonic waveguides with dense wavelength division multiplexing (DWDM) for signal traversal and microring resonators (MRs) for signal modulation. Unfortunately, DWDM increases susceptibility to intermodulation (IM) and off-resonance filtering effects, which reduce optical signal-to-noise ratio (OSNR) for photonic data transfers. Additionally, process variations (PVs) induce variations in the width and thickness of MRs causing resonance wavelength shifts, which further reduce OSNR, and create communication errors. This paper proposes a novel cross-layer framework called HYDRA to mitigate heterodyne crosstalk due to PVs, off-resonance filtering, and IM effects in PNoCs. The framework consists of two device-level mechanisms and a circuit-level mechanism to improve heterodyne crosstalk resilience in PNoCs. Simulation results on three PNoC architectures indicate that HYDRA can improve the worst case OSNR by up to and significantly enhance the reliability of DWDM-based PNoC architectures.
Autors: Sai Vineel Reddy Chittamuru;Ishan G. Thakkar;Sudeep Pasricha;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 168 - 181
Publisher: IEEE
 
» Hyperspectral Image Classification Using Joint Sparse Model and Discontinuity Preserving Relaxation
Abstract:
As a promising signal processing technique, a joint sparse model (JSM) has been used to integrate spatial and spectral information in the classification of remotely sensed images. This technique defines a local region of a fixed window size and assumes an equal contribution from each neighborhood pixel in the classification process of the test pixel. However, equal weighting is less reasonable for heterogeneous pixels, especially around class boundaries. Hence, a discontinuity preserving relaxation (DPR) method can be used to locally smooth the results without crossing the boundaries by detecting the discontinuities of an image in advance. In this letter, we developed a novel strategy that combines these two methods to improve the hyperspectral image classification. A JSM is first applied to obtain a posteriori probability distribution of pixels and then a DPR method is used to further improve the classification results. Experiments conducted on two benchmark data sets demonstrate that the proposed method leads to superior performance when compared with several popular algorithms.
Autors: Qishuo Gao;Samsung Lim;Xiuping Jia;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 78 - 82
Publisher: IEEE
 
» Hyperspectral Image Classification via Multiscale Joint Collaborative Representation With Locally Adaptive Dictionary
Abstract:
In this letter, a multiscale joint collaborative representation with locally adaptive dictionary (MLJCRC) method is proposed for hyperspectral image classification. Based on the joint collaborative representation model, instead of selecting only a single region scale, MLJCRC incorporates complementary contextual information into classification by multiplying different scales with distinct spatial structures and characteristics. Also, MLJCRC uses a locally adaptive dictionary to reduce the influence of irrelevant pixels on representation, which improves the classification accuracy. The results of experiments on Indian Pines data and Pavia University data demonstrate that the proposed method performs better than support vector machine, sparse representation classification, and other collaborative representation-based classifications.
Autors: Jinghui Yang;Jinxi Qian;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 112 - 116
Publisher: IEEE
 
» Hypoperfusion Induced by Preconditioning Treadmill Training in Hyper-Early Reperfusion After Cerebral Ischemia: A Laser Speckle Imaging Study
Abstract:
Exercise preconditioning induces neuroprotective effects during cerebral ischemia and reperfusion, which involves the recovery of cerebral blood flow (CBF). Mechanisms underlying the neuroprotective effects of re-established CBF following ischemia and reperfusion are unclear. The present study investigated CBF in hyper-early stage of reperfusion by laser speckle contrast imaging, a full-field high-resolution optical imaging technique. Rats with or without treadmill training were subjected to middle cerebral artery occlusion followed by reperfusion. CBF in arteries, veins, and capillaries in hyper-early stage of reperfusion (1, 2, and 3 h after reperfusion) and in subacute stage (24 h after reperfusion) were measured. Neurological scoring and 2,3,5-triphenyltetrazolium chloride staining were further applied to determine the neuroprotective effects of exercise preconditioning. In hyper-early stage of reperfusion, CBF in the rats with exercise preconditioning was reduced significantly in arteries and veins, respectively, compared to rats with no exercise preconditioning. Capillary CBF remained stable in the hyper-early stage of reperfusion, though it increased significantly 24 h after reperfusion in the rats with exercise preconditioning. As a neuroprotective strategy, exercise preconditioning reduced the blood perfusion of arteries and veins in the hyper-early stage of reperfusion, which indicated intervention-induced neuroprotective hypoperfusion after reperfusion onset.
Autors: Zhijie He;Hongyang Lu;Xiaojiao Yang;Li Zhang;Yi Wu;Wenxiu Niu;Li Ding;Guili Wang;Shanbao Tong;Jie Jia;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Jan 2018, volume: 65, issue:1, pages: 219 - 223
Publisher: IEEE
 
» IC Design and Measurement of an Inductorless 48 V DC/DC Converter in Low-Cost CMOS Technology Facing Harsh Environments
Abstract:
With reference to 48-V systems, used in electric and hybrid vehicles and for telecom and networking power supply, this paper presents the circuit/transistor-level design, implementation, and test of an inductorless dc/dc converter. Its architecture is a cascade of three switched-capacitor converters with step-up/down capabilities plus linear converters, working in parallel at the end of the cascade. It provides multiple regulated voltages, which are isolated from input failures. The design also includes on-chip control unit and a serial interface toward an external host. Experimental tests carried out on the chip, fabricated in 0.35- CMOS technology, proves that the design is suitable to face harsh operating environments, including the 48-V automotive one. Compared with the state-of-art, the proposed design stands for its wide input voltage regulation range, load/line regulation, power supply rejection ratio, and low electromagnetic interference emissions.
Autors: Sergio Saponara;Gabriele Ciarpi;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 380 - 393
Publisher: IEEE
 
» Iceberg Detection in Open and Ice-Infested Waters Using C-Band Polarimetric Synthetic Aperture Radar
Abstract:
Icebergs can cause a significant threat to shipping, offshore oil and gas production facilities, and subsea pipelines. Synthetic aperture radar (SAR) is a well-established tool for detecting and monitoring sea-ice objects in the often dark and cloud-covered polar regions. However, detection of small icebergs floating in nonhomegeous sea clutter environments is still a challenging task. We propose a new methodology for automatic identification of potential icebergs in high-resolution polarimetric SAR images. The algorithm adopts to various sea-ice conditions and it tackles high iceberg density situations and heterogeneous background conditions in the marginal ice zone. Results from a time series of RADARSAT-2 data containing numerous icebergs broken off from glaciers in Kongsfjorden on Svalbard demonstrate that the approach is viable.
Autors: Vahid Akbari;Camilla Brekke;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 407 - 421
Publisher: IEEE
 
» Identification of Various Image Operations Using Residual-Based Features
Abstract:
Image forensics has attracted wide attention during the past decade. However, most existing works aim at detecting a certain operation, which means that their proposed features usually depend on the investigated image operation and they consider only binary classification. This usually leads to misleading results if irrelevant features and/or classifiers are used. For instance, a JPEG decompressed image would be classified as an original or median filtered image if it was fed into a median filtering detector. Hence, it is important to develop forensic methods and universal features that can simultaneously identify multiple image operations. Based on extensive experiments and analysis, we find that any image operation, including existing anti-forensics operations, will inevitably modify a large number of pixel values in the original images. Thus, some common inherent statistics such as the correlations among adjacent pixels cannot be preserved well. To detect such modifications, we try to analyze the properties of local pixels within the image in the residual domain rather than the spatial domain considering the complexity of the image contents. Inspired by image steganalytic methods, we propose a very compact universal feature set and then design a multiclass classification scheme for identifying many common image operations. In our experiments, we tested the proposed features as well as several existing features on 11 typical image processing operations and four kinds of anti-forensic methods. The experimental results show that the proposed strategy significantly outperforms the existing forensic methods in terms of both effectiveness and universality.
Autors: Haodong Li;Weiqi Luo;Xiaoqing Qiu;Jiwu Huang;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 31 - 45
Publisher: IEEE
 
» Identifying the Requirements for Qualified, Unqualified, and Competent Persons Electrical Safety Training
Abstract:
This paper provides an understanding of what constitutes a qualified person, an unqualified person, and a competent person. Also included are the training requirements for each classification. The principles for performing a needs assessment, a job/task analysis, and job hazard analysis are addressed as they relate to the information gathering needed for the development of an effective training program. This gathered information applies to all personnel who are, or may be, exposed to electrical hazards, and who may work on, near, or interact with the electrical systems and equipment.
Autors: Dennis K. Neitzel;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Jan 2018, volume: 54, issue:1, pages: 5 - 9
Publisher: IEEE
 
» IEC/IEEE 60079-30 Standard, Parts 1 and 2: An Introduction to the Joint Standard for Trace Heating in Explosive Atmospheres
Abstract:
In 2015, the International Electrotechnical Commission (IEC) and the IEEE released the jointly developed standard IEC/IEEE 60079-30, Parts 1 and 2 [1]. The IEE sponsor was the IEE Industry Applications Society (IAS) Petroleum and Chemical Industry Technical Conference (PCIC), and the IEC sponsor was IEC Technical Committee (TC) 31, Equipment for Explosive Atmospheres. The joint development combined the requirements and recommendations of IEEE 515 [2] with IEC 60079-30-1, 2007-01 [3] and IEC 60079-30-2, 2007-01 [4]. This joint development represented the complete harmonization of the international, IEC , and North American certification and design requirements for trace heating in explosive atmospheres. In addition to type tests for product certification, this standard has extensive requirements so that certifying bodies can determine the manufacturer's ability to predict maximum sheath temperatures for trace heaters in explosive atmospheres. This article provides a background for understanding the joint development process and provides an overview of the key technical requirements found in the standards.
Autors: Ben C. Johnson;Richard H. Hulett;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 32 - 41
Publisher: IEEE
 
» IEEE 1900.7 Standard for White Space Dynamic Spectrum Access Radio Systems
Abstract:
Various measurements and studies have shown that some licensed frequency bands are underutilized at certain times and in certain locations. In particular, TV bands have been shown to have unused spectrum. Such observations have triggered strong interest in white space dynamic spectrum access among researchers, wireless equipment manufacturers, and standards development organizations. The IEEE Standards Committee on Dynamic Spectrum Access Networks created the White Space Radio Working Group in June 2011 to develop the IEEE 1900.7 standard for white space dynamic spectrum access radio systems. The standard was published in February 2016. This article gives an overview of key concepts and technologies of the IEEE 1900.7 standard, including use cases and requirements, the physical layer, and the MAC sublayer.
Autors: Stanislav Filin;Dominique Noguet;Jean-Baptiste Dore;Baher Mawlawi;Oliver Holland;Muhammad Zeeshan Shakir;Hiroshi Harada;Fumihide Kojima;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 188 - 192
Publisher: IEEE
 
» IEEE Student Branch Awards [The Way Ahead]
Abstract:
Presents the recipients of the IEEE Student Branch Awards.
Autors: J. Patrick Donohoe;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 4 - 4
Publisher: IEEE
 
» IEEE Visualization and Graphics Technical Committee (VGTC)
Abstract:
Presents a listing of the IEEE Visualization and Graphics Technical Committee (VGTC).
Autors: Cláudio T. Silva;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: xvi - xvi
Publisher: IEEE
 
» Image Registration Based on Low Rank Matrix: Rank-Regularized SSD
Abstract:
Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge, which affects the performance of similarity measures. Correlation among the pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squared-differences (SSD) and mutual information ignore this correlation; hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce rank-regularized SSD (RRSSD). This new similarity measure is a modified SSD based on singular values of difference image in mono-modal imaging. In fact, image registration and distortion correction are performed simultaneously in the proposed model. Based on our experiments, the RRSSD similarity measure achieves clinically acceptable registration results, and outperforms other state-of-the-art similarity measures, such as the well-known method of residual complexity.
Autors: Aboozar Ghaffari;Emad Fatemizadeh;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 138 - 150
Publisher: IEEE
 
» Image Segmentation Using Disjunctive Normal Bayesian Shape and Appearance Models
Abstract:
The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. For instance, most active shape and appearance models require landmark points and assume unimodal shape and appearance distributions, and the level set representation does not support construction of local priors. In this paper, we present novel appearance and shape models for image segmentation based on a differentiable implicit parametric shape representation called a disjunctive normal shape model (DNSM). The DNSM is formed by the disjunction of polytopes, which themselves are formed by the conjunctions of half-spaces. The DNSM’s parametric nature allows the use of powerful local prior statistics, and its implicit nature removes the need to use landmarks and easily handles topological changes. In a Bayesian inference framework, we model arbitrary shape and appearance distributions using nonparametric density estimations, at any local scale. The proposed local shape prior results in accurate segmentation even when very few training shapes are available, because the method generates a rich set of shape variations by locally combining training samples. We demonstrate the performance of the framework by applying it to both 2-D and 3-D data sets with emphasis on biomedical image segmentation applications.
Autors: Fitsum Mesadi;Ertunc Erdil;Mujdat Cetin;Tolga Tasdizen;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 293 - 305
Publisher: IEEE
 
» Image-Guided Nanopositioning Scheme for SEM
Abstract:
Positioning of micro-nanoobjects inside a scanning electron microscope (SEM) for manipulation is a key and challenging task to perform. Often it is performed by skilled operators via teleoperation, which is tedious and lacks repeatability. In this paper, rendering this task as an image-guided problem, we present a frequency domain scheme for automatic control of positioning platform movements. The designed controller uses the relative global image motion computed using the frequency spectral information of the images as visual signal and can provide control up to five degrees of freedom. The proposed approach is validated in simulations as well as experimentally using a high-resolution piezo-positioning platform mounted inside a SEM vacuum chamber. The obtained results quantify the performance of the proposed nanopositioning scheme.

Note to Practitioners—The main motivation behind this paper comes from the very need for automatic positioning of objects inside a scanning electron microscope (SEM) to perform dynamic analysis and structural characterization. Mostly, the positioning tasks are exhibited by skilled operators via teleoperation. Nevertheless, it is still a difficult task to repeat, and hence automatic strategies are indispensable. This can be tackled up to an extent using microscopic vision information. However, the regular vision-guided strategies with integrated feature tracking are hard to use with SEM due to multiple instabilities associated with the imaging process. To address this issue, this paper presents an image frequency-based positioning stage controller that does not require any visual tracking and is capable of dealing with electronic images provided by SEM for automatic nanopositioning. The presented results illustrate the capability of the method to handle various perturbations and demonstrate its performance in terms of accuracy, robustness, and repeatability. Due to the existence of orthographic p- ojection, the proposed method is limited to control depth displacements. This can be resolved by combining it with visual servoing-based autofocus methods.

Autors: Naresh Marturi;Brahim Tamadazte;Sounkalo Dembélé;Nadine Piat;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 45 - 56
Publisher: IEEE
 
» Imagining Replications: Graphical Prediction & Discrete Visualizations Improve Recall & Estimation of Effect Uncertainty
Abstract:
People often have erroneous intuitions about the results of uncertain processes, such as scientific experiments. Many uncertainty visualizations assume considerable statistical knowledge, but have been shown to prompt erroneous conclusions even when users possess this knowledge. Active learning approaches been shown to improve statistical reasoning, but are rarely applied in visualizing uncertainty in scientific reports. We present a controlled study to evaluate the impact of an interactive, graphical uncertainty prediction technique for communicating uncertainty in experiment results. Using our technique, users sketch their prediction of the uncertainty in experimental effects prior to viewing the true sampling distribution from an experiment. We find that having a user graphically predict the possible effects from experiment replications is an effective way to improve one's ability to make predictions about replications of new experiments. Additionally, visualizing uncertainty as a set of discrete outcomes, as opposed to a continuous probability distribution, can improve recall of a sampling distribution from a single experiment. Our work has implications for various applications where it is important to elicit peoples' estimates of probability distributions and to communicate uncertainty effectively.
Autors: Jessica Hullman;Matthew Kay;Yea-Seul Kim;Samana Shrestha;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 446 - 456
Publisher: IEEE
 
» Imminent Communication Security for Smart Communities
Abstract:
A smart community is a collection of interdependent human-cyber-physical systems, in which the states of these systems are estimated and adapted by IoT technology. It enables sustainable societies that can offer increased well being, safety, and security. However, a smart community may be susceptible to novel forms of cyber-attacks. This article highlights GPS security vulnerabilities of unmanned ground vehicles (UGVs), which will become more popular in smart communities. We show that UGVs do not have adequate protection against GPS spoofing attacks. Consequently, they can easily be penetrated by attackers.
Autors: Daojing He;Sammy Chan;Yinrong Qiao;Nadra Guizani;
Appeared in: IEEE Communications Magazine
Publication date: Jan 2018, volume: 56, issue:1, pages: 99 - 103
Publisher: IEEE
 

Publication archives by date

  2018:   January     February     March     April     May     June     July     August     September     October     November     December    

  2017:   January     February     March     April     May     June     July     August     September     October     November     December    

  2016:   January     February     March     April     May     June     July     August     September     October     November     December    

  2015:   January     February     March     April     May     June     July     August     September     October     November     December    

  2014:   January     February     March     April     May     June     July     August     September     October     November     December    

  2013:   January     February     March     April     May     June     July     August     September     October     November     December    

  2012:   January     February     March     April     May     June     July     August     September     October     November     December    

  2011:   January     February     March     April     May     June     July     August     September     October     November     December    

  2010:   January     February     March     April     May     June     July     August     September     October     November     December    

  2009:   January     February     March     April     May     June     July     August     September     October     November     December    

 
0-C     D-L     M-R     S-Z