Electrical and Electronics Engineering publications abstract of: 01-2018 sorted by title, page: 8

» 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
 
» 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 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
 
» Impact of Forming Compliance Current on Storage Window Induced by a Gadolinium Electrode in Oxide-Based Resistive Random Access Memory
Abstract:
Enlargement of memory window through forming compliance current was demonstrated in Gd:SiO2 resistive random access memory (RRAM) with a gadolinium (Gd) electrode. Lower forming compliance current for Gd:SiO2 RRAM with a Gd electrode results in larger memory window as compared with the RRAM with a Pt electrode. Through analyses on the current conduction mechanism, we demonstrate that a lower forming compliance current leads to a thinner conductive filament forming and less oxygen ions penetrating into Gd electrode, which caused higher on current and lower off current. Furthermore, a possible resistive switching model was proposed to explain the effect of Gd electrode on RRAM device.
Autors: Qing Xia;Jiaji Wu;Chih-Hung Pan;Cong Ye;Kuan-Chang Chang;Ting-Chang Chang;Chih-Cheng Shih;Cheng-Hsien Wu;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 96 - 100
Publisher: IEEE
 
» Impact of Plasma Treatment on Reliability Performance for HfZrOx-Based Metal-Ferroelectric-Metal Capacitors
Abstract:
TiN/ferroelectric-HfZrOx (FE-HZO)/TiN capacitors were employed as the platform to investigate the impact of plasma treatment on reliability of FE-HZO. NH3 plasma treatment at different HZO/TiN interfaces was carried out to study the dependence of oxygen vacancies (Vo) on FE behaviors against cycling. It has been electrically confirmed that HZO free from wake-up and fatigue effects up to 106 cycles (±2.5 MV/cm, long pulses of 1 ms) with high value of 29~30, low leakage current can be achieved by treatments at both top and bottom interfaces. It is a great advance for HfO2-based FE and is mainly attributed to significant reduction of Vo in HZO, especially the treatment at the bottom interface, which greatly suppresses the formation of oxygen-deficient HZO. Fewer Vo in NH3-plasma-treated HZO has also been confirmed by physical analysis. The plasma treatment has shed light on a feasible approach to enhance FE reliability.
Autors: Kuen-Yi Chen;Pin-Hsuan Chen;Ruei-Wen Kao;Yan-Xiao Lin;Yung-Hsien Wu;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 87 - 90
Publisher: IEEE
 
» Impact of Process Variations on Negative Capacitance FinFET Devices and Circuits
Abstract:
We report on the impact of process variations on short-channel negative capacitance (NC)-based FinFETs through statistical Monte Carlo simulations using a physics-based model of NC-FinFETs. We find that relative to regular FinFETs, the impact of geometrical variability can be lesser or higher in NC-FinFETs in different regimes of device operation and is strongly dependent on the nominal ferroelectric (FE) thickness (). The contribution of the FE layer to the overall variability behaves non-monotonically with increase in the nominal . While the OFF-current and threshold voltage variabilities scale down, the ON-current variability does not follow a monotonic trend with increase in the nominal . We also show that although relative to the regular FinFET-based ring oscillator (RO) circuit, the NC-FinFET-based RO (NC-RO) circuit displays increased immunity to process variation induced delay variability, the trend is non-monotonic with regard to scaling.
Autors: Tapas Dutta;Girish Pahwa;Amit Agarwal;Yogesh Singh Chauhan;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 147 - 150
Publisher: IEEE
 
» Impacts of Diameter and Ge Content Variation on the Performance of Si1-xGex p-Channel Gate-All-Around Nanowire Transistors
Abstract:
In this work, the impacts of both nanowire diameter (DNW) and Ge content (%) on the performance of Si1−xGex Gate-all-around nanowire p-channel FETs are investigated. The variations in SiGe Gate-all-around nanowire p-channel FETs induced by DNW variation, Ge content variation, and some stochastic process variations including random dopants fluctuation, gate edge roughness, and metal gate granularity are also evaluated.
Autors: Xianle Zhang;Xiaoyan Liu;Longxiang Yin;Gang Du;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 108 - 112
Publisher: IEEE
 
» Implementation and Characterization of a Physical Unclonable Function for IoT: A Case Study With the TERO-PUF
Abstract:
Today, life is becoming increasingly connected. From TVs to smartphones, including vehicles, buildings, and household appliances, everything is interconnected in what we call the “Internet of Things” (IoT). IoT is now part of our life and we have to deal with it. More than ten billion devices are already connected and five times more are expected to be deployed in the next five years. While deployment and integration of IoT is expanding, one of the main challenge is to provide practical solutions to security, privacy, and trust issues in IoT. Protection and security mechanisms need to include features such as interoperability and scalability but also traceability, authentication, and access control while remaining lightweight. Among the most promising approaches to such security mechanisms, physical unclonable functions (PUFs) provide a unique identifier for similar but different integrated circuits using some of their physical characteristics. These types of functions can thus be used to authenticate integrated circuits, provide traceability and access control. This paper presents a comprehensive case study of the transient effect ring oscillator (RO) PUF from its implementation on FPGAs to its complete characterization. The implementation of the PUF is detailed for two different families of FPGAs: 1) Xilinx Spartan 6 and 2) Altera Cyclone V. All the metrics used for the characterization are explained in detail and the results of the characterization include robustness to environmental parameters including variations in temperature and voltage. Finally, we compare our results with those obtained for another PUF: the RO PUF. All the design files are available online to ensure repeatability and enable comparison of our contribution with other studies.
Autors: Cédric Marchand;Lilian Bossuet;Ugo Mureddu;Nathalie Bochard;Abdelkarim Cherkaoui;Viktor Fischer;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Jan 2018, volume: 37, issue:1, pages: 97 - 109
Publisher: IEEE
 
» Improve Accuracy of Fingerprinting Localization with Temporal Correlation of the RSS
Abstract:
Recent study presents a fundamental limit of the RSS fingerprinting based indoor localization. In this paper, we theoretically show that the temporal correlation of the RSS can further improve accuracy of the fingerprinting localization. In particular, we construct a theoretical framework to evaluate how the temporal correlation of the RSS can influence reliability of location estimation, which is based on a newly proposed radio propagation model considering the time-varying property of signals from Wi-Fi APs. The framework is then applied to analyze localization in the one-dimensional physical space, which reveals the fundamental reason why localization performance can be improved by leveraging temporal correlation of the RSS. We extend our analysis to high-dimensional scenarios and mathematically depict the boundaries in the RSS sample space, which distinguish one physical location from another. Moreover, we develop an algorithm to utilize temporal correlation of the RSS to improve the location estimation accuracy, where the process for choosing key design parameters are provided through experiments. Experiment results show that the localization reliability and accuracy can be improved by up to 13 and 30 percent with appropriate leveraging the RSS temporal correlation information.
Autors: Xiaohua Tian;Mei Wang;Wenxin Li;Binyao Jiang;Dong Xu;Xinbing Wang;Jun Xu;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 113 - 126
Publisher: IEEE
 
» Improved Algorithms and Implementations for Integer to $tau $ NAF Conversion for Koblitz Curves
Abstract:
The conversion from an integer scalar to a short and sparse -adic nonadjacent form (NAF) is crucial for efficient elliptic curve scalar multiplication over Koblitz curves. Currently the conversion is costly both in time and area, limiting the application of Koblitz curves. In this paper, we propose improved algorithms and implementations for both the single-digit and double-digit scalar conversions. Area reduction is achieved by removing the -and-add calculation of the remainder upon division by for lazy reduction or the -and-add one for the double lazy reduction. The NAF and the double NAF algorithms are modified accordingly to support a mixed-form-reduced scalar from the new reduction algorithms. Furthermore, fair pipelining is explored to speed up conversion with only a slight increase in area. Implementation results on Altera Stratix II FPGA show that the proposed single-digit converters are both smaller and faster than existing works, and the 4-stage pipelined one achieves at least 42.3% area reduction and 78.9% better area-time product (ATP) performance. On Xilinx Virtex IV, our non-pipelined double-digit converters are at least 44.5% smaller but slightly slower, while the 4-stage pipelined one can run faster with averagely 46.6% better ATP than previous equivalent works.
Autors: Lijuan Li;Shuguo Li;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 154 - 162
Publisher: IEEE
 
» Improved Cavity for Broadband Frequency-Tunable Gyrotron
Abstract:
Cavity modification is proposed with the aim of enhancing the continuous frequency tunability of a gyrotron. The modification can be applied to both uniform and tapered gyrotron cavities and involves just using an additional cavity section. It ensures larger effective cavity length and thus lower starting current for higher order axial modes. As a consequence, the frequency tuning band of the gyrotron can be increased significantly. Moreover, the proposed cavity modification is beneficial for smoothing the variations of output power within the tuning band.
Autors: Vitalii I. Shcherbinin;Tetiana I. Tkachova;Viktor I. Tkachenko;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 257 - 262
Publisher: IEEE
 
» Improved Optimal Decentralized Load Modulation for Power System Primary Frequency Regulation
Abstract:
Nowadays the interest in smart load technologies for primary frequency regulation is spurred due to the increasing penetration of renewable energy resources. In this paper, an improved optimal load control (improved OLC) is introduced by applying a multiobjective optimization-based gain-tuning method to the conventional OLC approach. The objective is to minimize the frequency nadir, time response, steady-state error, total load shed, and aggregated disutility of controllable loads subject to power balance over the network. Simulation results indicate that enabling a multiobjective optimization-based gain-tuning procedure in the OLC approach can provide better power system frequency regulation. Time-domain analysis confirms the superior performance of improved OLC in terms of frequency nadir (Hz), steady-state error (Hz), control effort, and NERC-based performance metrics (MW/0.1 Hz), with detailed load and wind farm models. Furthermore, small-signal analysis demonstrates that the improved OLC enhances the system closed-loop performance and stability margins by increasing the damping ratio of the system's critical modes.
Autors: Atieh Delavari;Innocent Kamwa;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1013 - 1025
Publisher: IEEE
 
» Improved Performance of Amorphous InGaMgO Metal-Semiconductor-Metal Ultraviolet Photodetector by Post Deposition Annealing in Oxygen
Abstract:
In this paper, the impact of O2 postdeposition annealing treatment on the material and UV detection characteristics of amorphous InGaMgO (IGMO) thin films was intensively studied. With the replacement of Zn by Mg, amorphous InGaMgO possesses an optical bandgap larger than that of the conventional amorphous InGaZnO by over 0.5 eV. Furthermore, it was found the post-deposition annealing in O2 effectively suppressed the oxygen vacancies in the amorphous IGMO thin film, resulting in a significant reduction in its dark current. Due to strong hole trapping, all the samples except the 480-min annealed one exhibited large photocurrent and accordingly high responsivity over @ 10 V. Moreover, both photocurrent and responsivity improve with increasing annealing time up to 240 min. As a result, the Metal-Semiconductor-Metal photodetector based on the 240-min annealed amorphous InGaMgO thin film exhibited a very prominent performance, including a high responsivity of and a large photo-to-dark current ratio of . We attribute such excellent properties to the improved carrier mobility as well as the reduction of recombination centers in the O2-annealed film. However, some degradations in device performance were observed when the annealing time reached 480 min, which can be explained by the suppression of localized tail states, as demonstrated by the abruptly reduced Urbach energy, and accordingly the inhibition of related extrinsic excitation. This work has provided a promising candidate for the application in transparent contact-free interactive display.
Autors: Y. Y. Zhang;L. X. Qian;Z. H. Wu;P. T. Lai;X. Z. Liu;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 29 - 35
Publisher: IEEE
 
» Improved Sensitivity in Ultrasound Molecular Imaging With Coherence-Based Beamforming
Abstract:
Ultrasound molecular imaging (USMI) is accomplished by detecting microbubble (MB) contrast agents that have bound to specific biomarkers, and can be used for a variety of imaging applications, such as the early detection of cancer. USMI has been widely utilized in preclinical imaging in mice; however, USMI in humans can be challenging because of the low concentration of bound MBs and the signal degradation caused by the presence of heterogenous soft tissue between the transducer and the lesion. Short-lag spatial coherence (SLSC) beamforming has been proposed as a robust technique that is less affected by poor signal quality than standard delay-and-sum (DAS) beamforming. In this paper, USMI performance was assessed using contrast-enhanced ultrasound imaging combined with DAS (conventional CEUS) and with SLSC (SLSC-CEUS). Each method was characterized by flow channel phantom experiments. In a USMI-mimicking phantom, SLSC-CEUS was found to be more robust to high levels of additive thermal noise than DAS, with a 6dB SNR improvement when the thermal noise level was +6dB or higher. However, SLSC-CEUS was also found to be insensitive to increases in MB concentration, making it a poor choice for perfusion imaging. USMI performance was also measured in vivo using VEGFR2-targeted MBs in mice with subcutaneous human hepatocellular carcinoma tumors, with clinical imaging conditions mimicked using a porcine tissue layer between the tumor and the transducer. SLSC-CEUS improved the SNR in each of ten tumors by an average of 41%, corresponding to 3.0dB SNR. These results indicate that the SLSC beamformer is well-suited for USMI applications because of its high sensitivity and robust properties under challenging imaging conditions.
Autors: Dongwoon Hyun;Lotfi Abou-Elkacem;Valerie A. Perez;Sayan Mullick Chowdhury;Juergen K. Willmann;Jeremy J. Dahl;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 241 - 250
Publisher: IEEE
 
» Improved Turbo Decoding With Multivariable Taylor Series Expansion
Abstract:
In this letter, a new method is proposed to approximate -input () max* operation. Bi-variable Taylor series expansion, for the first time, is applied to approximate the correction term of -input () max* operation. It avoids the recursive computation of bi-variable Jacobian logarithm. To improve the approximation performance, multiple expansion points are considered. The proposed method is evaluated for 3GPP LTE turbo codes. The simulation results show that the approximation with five expansion points, applied with scaling factor to extrinsic information, has performance degradation of 0.01 dB compared with radix-4 Log-MAP algorithm. Furthermore, the approximation with three expansion points will bring minor performance loss but almost the same computational complexity compared with five expansion points.
Autors: Zhen Liu;Bin Wu;Tian-Chun Ye;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 37 - 40
Publisher: IEEE
 
» Improvements to the NMR Method With Flowing Water at CMI
Abstract:
Nuclear magnetic resonance (NMR) is a very important technique for making accurate measurements of the magnetic flux density B of dc magnetic fields in a wide range of values. This paper presents improvements to the NMR method with flowing water (the nutation method). The method is used at the Czech Metrology Institute and provides an improved signal-to-noise ratio of the amplitude of the NMR signal, new resonance frequency value by searching nutation double pattern recording, and an improved calibration uncertainty value. This method is used for calibration of the coil standards of magnetic flux density with a constant value below 20 mT/A. Using the improved nutation method presented here, the magnetic flux density coil standard can be calibrated within a period of less than 30 min in the range of 0.1 to 100 mT with expanded uncertainty of 20 to 60 ppm.
Autors: Michal Ulvr;Josef Kupec;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 204 - 208
Publisher: IEEE
 
» Improving Channel Capacity in Indoor $4 times 4$ MIMO Base Station Utilizing Small Bidirectional Antenna
Abstract:
Preparing toward the new-generation communication by improving the capacity in the channel can be achieved by employing a MIMO system with polarization diversity means. This paper presents a low-profile MIMO bidirectional antenna consisting of two composite antennas mounted on a ground plane. The composite antenna is constructed by stacking a notch antenna and a loop antenna on top of each other and each antenna is fed independently. This antenna is capable of dual-polarized radiation patterns pointing in two different directions, where the notch antenna produces a horizontally polarized wave in the -axis direction while the loop antenna gives a vertically polarized wave in the -axis direction. The combination of two composite antennas has good isolation between the elements and is capable of improving the channel capacity for indoor MIMO base station applications. This paper includes the validation of both the fabrication of the proposed antenna design and the channel propagation measurement using the proposed antenna, confirming the excellent antenna performance for long term evolution application at a frequency of 3.5 GHz.
Autors: Bakar Rohani;Kanata Takahashi;Hiroyuki Arai;Yasuko Kimura;Taisuke Ihara;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 393 - 400
Publisher: IEEE
 
» Improving the Safety and Security of Wide-Area Cyber–Physical Systems Through a Resource-Aware, Service-Oriented Development Methodology
Abstract:
This paper presents a service-oriented development methodology for wide-area cyber–physical systems (CPS) such as smart grid and vehicular networks. Unlike the traditional task-based development approach from the domains of automotive and avionics, the proposed service-oriented development methodology inherently enables disruption-free incremental system deployment and reconfiguration that are fundamental requirements for handling the “always-online” nature of emerging wide-area CPS application domains such as smart grid and vehicular networks. The proposed service-oriented CPS development methodology extends the traditional service-oriented computing (SOC) paradigm for handling hard real-time CPS aspects by introducing resource-aware service deployment and quality-of-service (QoS)-aware service operation phases. The proposed CPS development methodology also supports a streamlined formal interface between the traditional computer-aided feedback controller design environments and SOC paradigm. The paper utilizes a simulation-based smart grid case study to illustrate the advantages of the proposed methodology for developing wide-area cyber–physical systems with improved safety and security characteristics. The paper also identifies a set of technological requirements for the proposed service-oriented CPS development methodology that should guide future research in this area.
Autors: Muhammad Umer Tariq;Jacques Florence;Marilyn Wolf;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 144 - 159
Publisher: IEEE
 
» IMS2017 Student Design Competition Results
Abstract:
Presents information on the IMS2017 Student Design Competition.
Autors: Robert Caverly;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 67 - 68
Publisher: IEEE
 
» In Light and In Darkness, In Motion and In Stillness: A Reliable and Adaptive Receiver for the Internet of Lights
Abstract:
LEDs in our buildings, vehicles, and consumer products are rapidly gaining visible light communication capabilities. LED links however are notorious for being unreliable: shadowing, blockage, mobility, external light, all of these issues can disrupt the connectivity easily. Therefore, unless a reliable and cost-efficient data link layer is designed, VLC will be confined to niche applications. In this paper, we reveal a reason for unreliable VLC: a single type of photodetector at the receiver cannot establish a reliable link. We show that the photodetectors with complementary properties, in terms of optical spectral response and field-of-view, are necessary to handle the wide dynamic range of optical noise (such as the sun and other unwanted light sources) and mobility of users. Motivated by our experimental observations, we design a reliable and adaptive receiver for VLC (REAL-VLC) for low-end communication systems, an inexpensive receiver that senses light with complementary photodetectors and configures itself (physical and data link layers) dynamically to maintain the communication link. We implement the hardware and the software of REAL-VLC in low-end platforms, and experimentally validate it in representative test scenarios and a proof-of-concept application that consists of mobile nodes maintaining a VLC link under various lighting and path conditions.
Autors: Qing Wang;Domenico Giustiniano;Marco Zuniga;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 149 - 161
Publisher: IEEE
 
» In-Road Microwave Sensor for Electronic Vehicle Identification and Tracking: Link Budget Analysis and Antenna Prototype
Abstract:
To reduce the cost and increase reliability of the vehicle radio-frequency identification and tracking systems, an alternative placement of the interrogator is investigated. Conventional systems make use of an overhead interrogator that reads a tag in a windscreen or a license plate. The alternative approach is to embed the interrogator in the road and exclusively read license plate tags. In this paper, the link budget of such a system is fully characterized assuming the ISO/IEC 18000-63 UHF Type-C RFID standard. The obtained results indicate that a microwave sensor that has an elevated toroidal radiation pattern at around a 20°–30° elevation angle above the horizon is desired. This is a challenging task as road regulations dictate that the sensor cannot exceed a profile of 2.5 cm above the road surface. As an example of a sensor that meets those requirements, a modified discone antenna with an improved impedance matching method is presented. To reduce the antenna’s profile and give the required mechanical strength to withstand the weight of different vehicles on the road, the area between the disc and the cone is filled with Acetal, which has a high dielectric constant. The proposed microwave sensor is fabricated and successfully tested in a real-road environment. The results confirm that the sensor meets the aforementioned strict requirements from the link budget analysis.
Autors: Yifan Wang;Konstanty S. Bialkowski;Albertus J. Pretorius;Abraham G. W. du Plooy;Amin M. Abbosh;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 123 - 128
Publisher: IEEE
 
» Inadequate Software Testing Can Be Disastrous [Essay]
Abstract:
In October 2007, Activision published the Guitar Hero III: Legends of Rock video game for the Nintendo Wii gaming console. The extremely popular game sold 1.4 million copies during the first six days of its release. Guitar Hero III: Legends of Rock was a game that allowed players to play songs with a guitar-like controller. Music was the primary output of this highly entertaining game.
Autors: Edwin Torres;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 9 - 47
Publisher: IEEE
 
» InAlN/GaN HEMTs on Si With High ${{f}}_{text {T}}$ of 250 GHz
Abstract:
In this letter, InAlN/GaN high electron mobility transistors (HEMTs) with 40–200 nm rectangular gates and 300–700 nm source-to-drain distances were fabricated on Si substrates. The device with 40-nm gate and 300-nm source-to-drain distance exhibited a high drain current of 2.66 A/mm, a transconductance () of 438 mS/mm, and a high current gain cutoff frequency () of 250 GHz. To the best of our knowledge, this is the highest value reported so far for GaN-based transistors on Si. An effective electron velocity of cm/s was extracted, which is comparable with those reported for InAlN/GaN HEMTs on SiC. These excellent results indicate that GaN HEMTs on Si have a great potential for low-cost emerging mm-Wave applications.
Autors: Weichuan Xing;Zhihong Liu;Haodong Qiu;Kumud Ranjan;Yu Gao;Geok Ing Ng;Tomás Palacios;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 75 - 78
Publisher: IEEE
 
» Incorporating an Optical Clock Into a Time Scale
Abstract:
This paper discusses the results of a simulation of a time scale based on continuously operating commercial hydrogen masers and an optical frequency standard that does not operate continuously as a clock. The simulation compares the performance of this time scale with one that is based on the same commercial devices but incorporates a continuously operating cesium fountain instead of the optical standard. The results are independent of the detailed characteristics of the optical frequency standard; the only requirement is that the optical device be much more stable than the masers in the ensemble. We discuss two methods for realizing the results of this simulation in an operational time scale.
Autors: Jian Yao;Thomas E. Parker;Neil Ashby;Judah Levine;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Jan 2018, volume: 65, issue:1, pages: 127 - 134
Publisher: IEEE
 
» Indirect Power-System Contingency Screening for Real-Time Applications Based on PCA
Abstract:
This letter introduces the application of a data mining method with the purpose of contingency screening, by rapid recognition of hazardous, reoccurring power-system operating conditions. The method, suitable for real-time applications, is demonstrated on the north-western part of the Slovenian power-system, for first-swing stability issues. The presented demonstration consists of two steps: First, a database containing a set of prefault operating states and the corresponding critical clearing times of several contingencies is constructed. Second, the prefault measurements matrix is decomposed using the principal component analysis method and represented in a coordinate system, defined by the principal components. Since operating states form dense clusters of points in this coordinate system, the similarity between current and past conditions is established by identifying the shortest Euclidean distance metric. In this manner, the indication of each contingency impact is provided rapidly as long as a similar operating state exists within the database. Otherwise, the case is thoroughly investigated and included in the database. This approach is applicable to a wide spectrum of dynamic problems, providing that problem-relevant sets of input data are considered.
Autors: Teodora Dimitrovska;Urban Rudez;Rafael Mihalic;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1080 - 1081
Publisher: IEEE
 
» Indoor Positioning Algorithm Based on Nonlinear PLS Integrated With RVM
Abstract:
Indoor positioning based on received signal strength indicator of WLAN has received more and more attention because of low cost and easy implementation. However, traditional localization algorithms often fail to achieve better positioning results because of multi-path effect and shadow effect. In order to solve the problem of multi-collinearity and more noise in WLAN indoor location data, this paper presents a novel nonlinear partial least square (PLS) method to address the problem of low precision in WLAN location. The proposed method integrates an inner relevant vector machine (RVM) function with an external linear PLS framework. First, the localization area is divided into a number of small areas by K-means algorithm. Then, PLS is applied to extract the features of the fingerprint database to reduce the number of the variable dimensions and eliminate the correlations. The obtained score matrices are used as the input and output of RVM. Finally, the coordinates of test points are regressed and predicted by the RVM-PLS algorithm. Simulation and experiments in real scenario prove the effectiveness of the proposed method. Compared with SVM-PLS, RBF-PLS, SVM-PCA, EBQPLS, PLS, SVM, RBF, RVM, and WKNN algorithm, the experimental results show that the proposed algorithm has higher positioning accuracy.
Autors: Chen Chen;Yujie Wang;Yong Zhang;Yan Zhai;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 660 - 668
Publisher: IEEE
 
» Infinite Horizon Optimal Transmission Power Control for Remote State Estimation Over Fading Channels
Abstract:
This paper studies the joint design over an infinite horizon of the transmission power controller and remote estimator for state estimation over fading channels. A sensor observes a dynamic process and sends its observations to a remote estimator over a wireless fading channel characterized by a time-homogeneous Markov chain. The successful transmission probability depends on both the channel gains and the transmission power used by the sensor. The transmission power control rule and the remote estimator should be jointly designed, aiming to minimize an infinite-horizon cost consisting of the power usage and the remote estimation error. We formulate the joint optimization problem as an average cost belief-state Markov decision process and prove that there exists an optimal deterministic and stationary policy. We then show that when the monitored dynamic process is scalar or the system matrix is orthogonal, the optimal remote estimates depend only on the most recently received sensor observation, and the optimal transmission power is symmetric and monotonically increasing with respect to the norm of the innovation error.
Autors: Xiaoqiang Ren;Junfeng Wu;Karl Henrik Johansson;Guodong Shi;Ling Shi;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 85 - 100
Publisher: IEEE
 
» Influence of Chemical Potential on Graphene-Based SPR Sensor’s Performance
Abstract:
Surface plasmon resonance sensor based on “ZBLAN fluoride glass-Ag-graphene” plasmonic structure is proposed in the near-IR region. The influence of graphene chemical potential () in combination with the number of layers (L) of graphene on the sensor’s performance has been analyzed in detail. The analysis suggests that for graphene monolayer (L = 1), the maximum and almost constant sensing performance may be achieved for eV.
Autors: Anuj K. Sharma;Anumol Dominic;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:1, pages: 95 - 98
Publisher: IEEE
 
» Information Capacity of Vesicle Release in Neuro-Spike Communication
Abstract:
Information transmission in the nervous system is performed through the propagation of spikes among neurons, which is done by vesicle release to chemical synapses. Understanding the fundamentals of this communication can lead to the implementation of bio-inspired nanoscale communication paradigms. In this letter, we utilize a realistic pool-based model for vesicle release and replenishment in hippocampal pyramidal neurons and evaluate the capacity of information transmission in this process by modeling it as a binary channel with memory. Then, we derive a recurrence relation for the number of available vesicles, which is used to find successful bit transmission probabilities and mutual information between input and output. Finally, we evaluate the spiking probability that maximizes mutual information and derive the capacity of the channel.
Autors: Hamideh Ramezani;Ozgur B. Akan;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 41 - 44
Publisher: IEEE
 
» Information Geometry Approach to Verification of Dynamic Models in Power Systems
Abstract:
This paper describes a new class of system identification procedures that are tailored to electric power systems, in particular to synchronous generators (SGs) and other dynamic components. Our procedure builds on computational advances in differential geometry, and offers a new, global characterization of challenges frequently encountered in system identification of electric power systems. The approach also benefits from increasing availability of high-quality measurements. While the proposed procedure is illustrated on SG example in a multimachine benchmark (IEEE 14-bus and real-world 441-bus power systems), it is equally applicable to identification of other system components, such as loads.
Autors: Mark K. Transtrum;Andrija T. Sarić;Aleksandar M. Stanković;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 440 - 450
Publisher: IEEE
 
» Injection Locked Triple Contact F–P LDs for Uncooled WDM Systems
Abstract:
We propose an injection locked triple contact Fabry–Pérot laser diode (TC F–P LD) for an uncooled wavelength division multiplexing systems. By controlling injection currents to three electrodes of the TC F–P LD, we are able to tune the cavity mode for an optimum injection locking without using temperature control. Then, we transmitted 20-Gb/s/channel quadrature phase shift keying signal using the LD as either an optical carrier or a local oscillator. We identified contributions of the performance degradation as: 1) intensity noise resulting from a finite common mode rejection ratio associated with a relative intensity noise and 2) decrease of the effective LO power for coherent detection. Finally, we show the uniform bit error rate performance with change of the injection wavelength by 2.8 nm. This is corresponding to 28 °C change of operating temperature.
Autors: Myeonggyun Kye;Chang-Hee Lee;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 213 - 216
Publisher: IEEE
 
» Input-to-State Stability and Inverse Optimality of Linear Time-Varying-Delay Predictor Feedbacks
Abstract:
For linear systems with time-varying input delay and additive disturbances we show that the basic predictor feedback control law is inverse optimal, with respect to a meaningful differential game problem, and establish its robustness to constant multiplicative perturbations appearing at the system input. Both of these properties of the basic predictor feedback controller have not been established so far, even for the constant-delay case. We then show that the basic predictor feedback controller, when applied through a low-pass filter, is again inverse optimal and study its input-to-state stability as well as its robustness, to the low-pass filter time constant properties. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation, which allows us to construct appropriate Lyapunov functionals. A numerical example is also provided.
Autors: Xiushan Cai;Nikolaos Bekiaris-Liberis;Miroslav Krstic;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 233 - 240
Publisher: IEEE
 
» Insensitivity Characteristics in the Dual Polarization of Deployable CFRP Reflector Antennas for SAR
Abstract:
A large deployable reflector antenna is considered and designed for the application of a synthetic aperture radar system requiring high gain for the high resolution of a detected image within a distance of a few hundred kilometers. For its lightweight and strong characteristics, carbon fiber reinforced polymer (CFRP) is introduced as a composite material and fabricated for conductivity evaluation. Effective electrical characteristics are obtained as a function of carbon fiber direction, using measured S-parameters in a rectangular waveguide. By taking into account the changes of the effective electrical characteristics that depend on the fiber direction of reflector antenna, the radiation pattern is investigated at X-band in terms of gain and polarization variation effects. The proposed reflector antenna made of quasi-isotropic CFRP panel can realize the insensitive characteristics depending on the incident polarization.
Autors: Seong Sik Yoon;Jae W. Lee;Taek-Kyung Lee;Jin Ho Roh;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 88 - 95
Publisher: IEEE
 
» Instant Construction and Visualization of Crowded Biological Environments
Abstract:
We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a non-visual and non-interactive environment. Our solution unites the modeling and visualization aspect, enabling interactive construction of atomic resolution mesoscale models of large portions of a cell. We present a novel set of GPU algorithms that build the basis for the rapid construction of complex biological structures. These structures consist of multiple membrane-enclosed compartments including both soluble molecules and fibrous structures. The compartments are defined using volume voxelization of triangulated meshes. For membranes, we present an extension of the Wang Tile concept that populates the bilayer with individual lipids. Soluble molecules are populated within compartments distributed according to a Halton sequence. Fibrous structures, such as RNA or actin filaments, are created by self-avoiding random walks. Resulting overlaps of molecules are resolved by a forced-based system. Our approach opens new possibilities to the world of interactive construction of cellular compartments. We demonstrate its effectiveness by showcasing scenes of different scale and complexity that comprise blood plasma, mycoplasma, and HIV.
Autors: Tobias Klein;Ludovic Autin;Barbora Kozlíková;David S. Goodsell;Arthur Olson;M. Eduard Gröller;Ivan Viola;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 862 - 872
Publisher: IEEE
 
» Integrated Circuit for Super-Regenerative Low-Frequency Amplification
Abstract:
An improved topology for the baseband super-regenerative sampling amplifier is proposed and analyzed, which employs a series-capacitors output load to realize positive feedback. As in the conventional circuit, the gain of the amplifier is continuously variable by controlling the length of the capacitor charging phase. It is shown that decreasing feedback enhances the linearity of the circuit while trading off with a lower sampling speed. Entirely removing the feedback yields the integrating amplifier circuit. This is a practical implementation in terms of linearity, power, noise, and gain in low-frequency applications, including biomedical signal amplification. The analysis is verified by measured results from an integrated circuit prototype in 180-nm CMOS technology.
Autors: Robert Rieger;Nanang Sulistiyanto;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 31 - 35
Publisher: IEEE
 
» Integrated MIMO Slot Antenna on Laptop Computer for Eight-Band LTE/WWAN Operation
Abstract:
This paper proposes a two-element multi-input multi-output (MIMO) open-slot antenna implemented on the display ground plane of a laptop computer for eight-band long-term evolution/wireless wide-area network operations. The metal surroundings of the antennas have been well integrated as a part of the radiation structure. In the single-element open-slot antenna, the nearby hinge slot (which is bounded by two ground planes and two hinges) is relatively large as compared with the open slot itself and acts as a good radiator. In the MIMO antenna consisting of two open-slot elements, a T slot is embedded in the display ground plane and is connected to the hinge slot. The T and hinge slots when connected behave as a radiator; whereas, the T slot itself functions as an isolation element. With the isolation element, simulated isolations between the two elements of the MIMO antenna are raised from 8.3–11.2 to 15–17.1 dB in 698–960 MHz and from 12.1–21 to 15.9–26.7 dB in 1710–2690 MHz. Measured isolations with the isolation element in the desired low- and high-frequency ranges are 17.6–18.8 and 15.2–23.5 dB, respectively. Measured and simulated efficiencies for the two-element MIMO antenna with either element excited are both larger than 50% in the desired operating frequency bands.
Autors: Shu-Chuan Chen;Po-Wei Wu;Chung-I G. Hsu;Jia-Yi Sze;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 105 - 114
Publisher: IEEE
 
» Integrated Optimization of Network Topology and DG Outputs for MVDC Distribution Systems
Abstract:
Medium-voltage DC (MVDC) distribution systems are receiving more and more attractions. For a MVDC distribution system, less network power losses can be obtained if the network topology and the outputs of distributed generations are optimized together. However, this is a tough optimization problem due to the mixed integer non-convex programming property. To efficiently address this problem, a convex mixed-integer quadratic programming (MIQP) based integrated optimization approach is proposed in this letter, which is validated via three MVDC systems.
Autors: Yi Tan;Yong Li;Yijia Cao;Mohammad Shahidehpour;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1121 - 1123
Publisher: IEEE
 
» Integrated Planar Three-Beam Electron Optics System for 220-GHz Folded Waveguide TWT
Abstract:
An integrated planar three-beam electron optics system is designed for our 220-GHz cascaded folded waveguide TWT. First, a planar three-beam gun is designed based on Pierce theory and Vaughan’s synthesis method with simplification of the focus electrode and the anode to facilitate manufacture and assembly, which is characteristic with 20 kV, A, and beam radius of 0.1 mm. Simulation results show that the gun model performs well. Next, a uniform magnetic focusing structure used for constraining the three-beam array with adjacent beam separation of 8 mm is designed. Magnetic saturation analysis of the pole piece and structure parameters optimization of the magnets is considered thoroughly, which may guarantee the transport stability of the three-beam array and keep down the volume of the magnet. Simulation results show that the transmission of three-beam array up to 18 mm is 100% with the maximum ripple of 11.2% in the designed focusing structure. And the integrated planar three-beam electron optics system is verified as a stable system with the beam characteristics analyses of matching error, beam voltage fluctuation, and variation of peak .
Autors: Hongtao Liang;Qianzhong Xue;Cunjun Ruan;Jinjun Feng;Shilong Wang;Xiaohui Liu;Zhaochuan Zhang;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 270 - 276
Publisher: IEEE
 
» Integrated Systems-in-Package: Heterogeneous Integration of Millimeter-Wave Active Circuits and Passives in Fan-Out Wafer-Level Packaging Technologies
Abstract:
Recent advances in silicon semiconductor technology with transit and maximum oscillation frequencies above 300 GHz have enabled the integration of complex transceiver front ends operating in the millimeter-wave (mmW) regime for a variety of applications. Among these, the most prominent frequency ranges (and their associated applications) are currently the 60-GHz short-range communication frequency band [1]-[2] and E-band wireless back-haul solutions [3]-[4], as well as the 76-81-GHz band for automotive radar sensor realizations [5]-[6].
Autors: Amelie Hagelauer;Maciej Wojnowski;Klaus Pressel;Robert Weigel;Dietmar Kissinger;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 48 - 56
Publisher: IEEE
 
» Integration of Learning-Based Testing and Supervisory Control for Requirements Conformance of Black-Box Reactive Systems
Abstract:
A fundamental requirement of the supervisory control theory (SCT) of discrete-event systems is a finite automaton model of the plant. The requirement does not hold for black-box systems whose source code and logical model are not accessible. To apply SCT to black-box systems, we integrate automaton learning technology with SCT and apply the new method to improve the requirements conformance of software reuse. If the reused software component does not satisfy a requirement, the method adds a supervisor component to prevent the black-box system from reaching “faulty sections.” The method employs learning-based testing (LBT) to verify whether the reused software meets all requirements in the new context. LBT generates a large number of test cases and iteratively constructs an automaton model of the system under test. If the system fails the test, the learned model is applied as the plant model for control synthesis using SCT. Then, the supervisor is implemented as an executable program to monitor and control the system to follow the requirement. Finally, the integrated system, including the supervisory program and the reused component, is tested by LBT to assure the satisfiability of the requirement. This paper makes two contributions. First, we innovatively integrate LBT and SCT for the control synthesis of black-box reactive systems. Second, software component reuse is still possible even if it does not satisfy user requirements at the outset.

Note to Practitioners—In black-box software reuse, if a component does not satisfy user requirements in a new context, the developer has to abandon it and develop a new one, which is costly. The proposed method enables software reuse for black-box reactive systems by combining learning-based testing (LBT) and supervisory control theory (SCT). LBT can test whether the requirements hold in new settings and infer hypothesis models of the component at - he same time. If the component does not pass the test, the learned hypothesis is used as a plant model to compute a supervisor using SCT. Then, a supervisory program is developed according to the control actions of the supervisor to govern the system to follow the behavior of the requirements. We illustrate the proposed method through an example of a simple cruise control module. The effectiveness of the new method is demonstrated with a larger software component brake-by-wire with floating point data types. The case studies show not only the methodology of the new approach but also a working tool chain to perform it.

Autors: Huimin Zhang;Lei Feng;Naiqi Wu;Zhiwu Li;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 2 - 15
Publisher: IEEE
 
» Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning
Abstract:
Effective intelligent fault diagnosis has long been a research focus on the condition monitoring of rotary machinery systems. Traditionally, time-domain vibration-based fault diagnosis has some deficiencies, such as complex computation of feature vectors, excessive dependence on prior knowledge and diagnostic expertise, and limited capacity for learning complex relationships in fault signals. Furthermore, following the increase in condition data, how to promptly process the massive fault data and automatically provide accurate diagnosis has become an urgent need to solve. Inspired by the idea of compressed sensing and deep learning, a novel intelligent diagnosis method is proposed for fault identification of rotating machines. In this paper, a nonlinear projection is applied to achieve the compressed acquisition, which not only reduces the amount of measured data that contained all the information of faults but also realizes the automatic feature extraction in transform domain. For exploring the discrimination hidden in the acquired data, a stacked sparse autoencoders-based deep neural network is established and performed with an unsupervised learning procedure followed by a supervised fine-tuning process. We studied the significance of compressed acquisition and provided the effects of key factors and comparison with traditional methods. The effectiveness of the proposed method is validated using data sets from rolling element bearings and the analysis shows that it is able to obtain high diagnotic accuracies and is superior to the existing methods. The proposed method reduces the need of human labor and expertise and provides new strategy to handle the massive data more easily.
Autors: Jiedi Sun;Changhong Yan;Jiangtao Wen;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 185 - 195
Publisher: IEEE
 
» Intelligent NLOS Backhaul for 5G Small Cells
Abstract:
Millimeter wave (mmW) technologies are currently being proposed as backhaul for outdoor urban small cells. However, non-line-of-sight (NLOS) operation must be addressed before solutions can be fully realised. This letter proposes a reinforcement learning algorithm for improving the reliability of an mmW NLOS small cell backhaul system based on propagation by diffraction. Simulation results show that the algorithm achieves the desired data rate and can detect malfunctioning on a path within a predetermined time, and make a decision to switch to an alternative path, adjust transmission power, or change the operating mode in order to improve system performance.
Autors: Bessie Malila;Olabisi Falowo;Neco Ventura;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 189 - 192
Publisher: IEEE
 
» Intelligent Time-Adaptive Transient Stability Assessment System
Abstract:
Online identification of postcontingency transient stability is essential in power system control, as it facilitates the grid operator to decide and coordinate system failure correction control actions. Utilizing machine learning methods with synchrophasor measurements for transient stability assessment has received much attention recently with the gradual deployment of wide-area protection and control systems. In this paper, we develop a transient stability assessment system based on the long short-term memory network. By proposing a temporal self-adaptive scheme, our proposed system aims to balance the trade-off between assessment accuracy and response time, both of which may be crucial in real-world scenarios. Compared with previous work, the most significant enhancement is that our system learns from the temporal data dependencies of the input data, which contributes to better assessment accuracy. In addition, the model structure of our system is relatively less complex, speeding up the model training process. Case studies on three power systems demonstrate the efficacy of the proposed transient stability as sessment system.
Autors: James J. Q. Yu;David J. Hill;Albert Y. S. Lam;Jiatao Gu;Victor O. K. Li;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1049 - 1058
Publisher: IEEE
 
» Interactions Between Indirect DC-Voltage Estimation and Circulating Current Controllers of MMC-Based HVDC Transmission Systems
Abstract:
Estimation-based indirect dc-voltage control in MMCs interacts with circulating current control methods. This paper proposes an estimation-based indirect dc-voltage control method for MMC-HVDC systems and analyzes its performance compared to alternative estimations. The interactions between estimation-based indirect dc-voltage control and circulating current control methods, active/reactive power regulation are also investigated. The proposed method delivers similar performance to measurement-based direct dc-voltage control, regardless of the circulating current control method. Steady-state and transient performance is demonstrated using a benchmark MMC-HVDC transmission system, implemented in a real-time digital simulator. The results verify the theoretical evaluations and illustrate the operation and performance of the proposed indirect dc-voltage control method.
Autors: Harith R. Wickramasinghe;Georgios Konstantinou;Josep Pou;Vassilios G. Agelidis;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 829 - 838
Publisher: IEEE
 
» Interactions Between Large-Scale Functional Brain Networks are Captured by Sparse Coupled HMMs
Abstract:
Functional magnetic resonance imaging (fMRI) provides a window on the human brain at work. Spontaneous brain activity measured during resting-state has already provided many insights into brain function. In particular, recent interest in dynamic interactions between brain regions has increased the need for more advanced modeling tools. Here, we deploy a recent fMRI deconvolution technique to express resting-state temporal fluctuations as a combination of large-scale functional network activity profiles. Then, building upon a novel sparse coupled hidden Markov model (SCHMM) framework, we parameterised their temporal evolution as a mix between intrinsic dynamics, and a restricted set of cross-network modulatory couplings extracted in data-driven manner. We demonstrate and validate the method on simulated data, for which we observed that the SCHMM could accurately estimate network dynamics, revealing more precise insights about direct network-to-network modulatory influences than with conventional correlational methods. On experimental resting-state fMRI data, we unraveled a set of reproducible cross-network couplings across two independent datasets. Our framework opens new perspectives for capturing complex temporal dynamics and their changes in health and disease.
Autors: Thomas A. W. Bolton;Anjali Tarun;Virginie Sterpenich;Sophie Schwartz;Dimitri Van De Ville;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 230 - 240
Publisher: IEEE
 
» Interactive Communication for Data Exchange
Abstract:
Two parties observing correlated data seek to exchange their data using interactive communication. How many bits must they communicate? We propose a new interactive protocol for data exchange, which increases the communication size in steps until the task is done. We also derive a lower bound on the minimum number of bits that is based on relating the data exchange problem to the secret key agreement problem. Our single-shot analysis applies to all discrete random variables and yields upper and lower bounds of a similar form. In fact, the bounds are asymptotically tight and lead to a characterization of the optimal rate of communication needed for data exchange for a general source sequence, such as a mixture of independent and identically distributed (IID) random variables as well as the optimal second-order asymptotic term in the length of communication needed for data exchange for IID random variables, when the probability of error is fixed. This gives a precise characterization of the asymptotic reduction in the length of optimal communication due to interaction; in particular, two-sided Slepian–Wolf compression is strictly suboptimal.
Autors: Himanshu Tyagi;Pramod Viswanath;Shun Watanabe;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 26 - 37
Publisher: IEEE
 
» Interactive Design and Visualization of Branched Covering Spaces
Abstract:
Branched covering spaces are a mathematical concept which originates from complex analysis and topology and has applications in tensor field topology and geometry remeshing. Given a manifold surface and an -way rotational symmetry field, a branched covering space is a manifold surface that has an -to-1 map to the original surface except at the ramification points, which correspond to the singularities in the rotational symmetry field. Understanding the notion and mathematical properties of branched covering spaces is important to researchers in tensor field visualization and geometry processing, and their application areas. In this paper, we provide a framework to interactively design and visualize the branched covering space (BCS) of an input mesh surface and a rotational symmetry field defined on it. In our framework, the user can visualize not only the BCSs but also their construction process. In addition, our system allows the user to design the geometric realization of the BCS using mesh deformation techniques as well as connecting tubes. This enables the user to verify important facts about BCSs such as that they are manifold surfaces around singularities, as well as the Riemann-Hurwitz formula which relates the Euler characteristic of the BCS to that of the original mesh. Our system is evaluated by student researchers in scientific visualization and geometry processing as well as faculty members in mathematics at our university who teach topology. We include their evaluations and feedback in the paper.
Autors: Lawrence Roy;Prashant Kumar;Sanaz Golbabaei;Yue Zhang;Eugene Zhang;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 843 - 852
Publisher: IEEE
 
» Interactive Dynamic Volume Illumination with Refraction and Caustics
Abstract:
In recent years, significant progress has been made in developing high-quality interactive methods for realistic volume illumination. However, refraction — despite being an important aspect of light propagation in participating media — has so far only received little attention. In this paper, we present a novel approach for refractive volume illumination including caustics capable of interactive frame rates. By interleaving light and viewing ray propagation, our technique avoids memory-intensive storage of illumination information and does not require any precomputation. It is fully dynamic and all parameters such as light position and transfer function can be modified interactively without a performance penalty.
Autors: Jens G. Magnus;Stefan Bruckner;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 984 - 993
Publisher: IEEE
 
» Interactive Image Segmentation Using Semi-transparent Wearable Glasses
Abstract:
Since it is difficult to automatically and precisely extract an object of interest, interactive image segmentation techniques exploit user-provided segmentation seeds. In previous interactive segmentation applications, the segmentation seeds are typically provided by mouse clicks or finger touches. In this paper, the segmentation of an object is studied from the scene that the user sees through semi-transparent wearable glasses. In this application scenario, a front-view camera is used to obtain the segmentation seeds from the user's fingertip position. In particular, two segmentation methodologies called transparent segmentation and semi-transparent segmentation are considered to determine an effective segmentation scheme for the wearable glasses. Extensive user studies are performed to evaluate the user preferences and the segmentation accuracies of the two methodologies.
Autors: Kyumok Kim;Seung-Won Jung;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 208 - 223
Publisher: IEEE
 
» Intercalibrating the MODIS and AVHRR Visible Bands Over Homogeneous Land Surfaces
Abstract:
Sensor intercalibration has been widely performed over low-latitude deserts and circumpolar regions where surface conditions are generally well characterized. This letter proposes a new method for intercalibrating visible bands of Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) over homogenous land surfaces that differ in brightness, in order to improve calibration results. The method is based on the extended simultaneous nadir overpass events. Initially, the spectral band adjustment factors are calculated using surface reflectances in the MODIS 552 and 645-nm bands. Sensor differences related to atmospheric effects are corrected using MODIS atmospheric parameters and MODIS/AVHRR sun-target-sensor geometries. In view of excellent MODIS calibration accuracy, the residual MODIS–AVHRR difference may result from AVHRR calibration bias. A preliminary validation study over radiometric sites shows <1.0% uncertainty for the high-gain calibration and <2.0% uncertainty for the low-gain calibration. The proposed method allows sensor intercalibration over varying land surfaces, and contributes to a collection of sensor calibration and intercalibration results of AVHRR sensors.
Autors: Xingwang Fan;Yuanbo Liu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 83 - 87
Publisher: IEEE
 
» Interface Design of a Physical Human–Robot Interaction System for Human Impedance Adaptive Skill Transfer
Abstract:
It has been established that the transfer of human adaptive impedance is of great significance for physical human–robot interaction (pHRI). By processing the electromyography (EMG) signals collected from human muscles, the limb impedance could be extracted and transferred to robots. The existing impedance transfer interfaces rely only on visual feedback and, thus, may be insufficient for skill transfer in a sophisticated environment. In this paper, physical haptic feedback mechanism is introduced to result in muscle activity that would generate EMG signals in a natural manner, in order to achieve intuitive human impedance transfer through a designed coupling interface. Relevant processing methods are integrated into the system, including the spectral collaborative representation-based classifications method used for hand motion recognition; fast smooth envelop and dimensionality reduction algorithm for arm endpoint stiffness estimation. The tutor’s arm endpoint motion trajectory is directly transferred to the robot by the designed coupling module without the restriction of hands. Haptic feedback is provided to the human tutor according to skill learning performance to enhance the teaching experience. The interface has been experimentally tested by a plugging-in task and a cutting task. Compared with the existing interfaces, the developed one has shown a better performance. Note to Practitioners—This paper is motivated by the limited performance of skill transfer in the existing human–robot interfaces. Conventional robots perform tasks independently without interaction with humans. However, the new generation of robots with the characteristics, such as flexibility and compliance, become more involved in interacting with humans. Thus, advanced human robot interfaces are required to enable robots to learn human manipulation skills. In this paper, we propose a novel- interface for human impedance adaptive skill transfer in a natural and intuitive manner. The developed interface has the following functionalities: 1) it transfers human arm impedance adaptive motion to the robot intuitively; 2) it senses human motion signals that are decoded into human hand gesture and arm endpoint stiffness that ia employed for natural human robot interaction; and 3) it provides human tutor haptic feedback for enhanced teaching experience. The interface can be potentially used in pHRI, teleoperation, human motor training systems, etc.
Autors: Chenguang Yang;Chao Zeng;Peidong Liang;Zhijun Li;Ruifeng Li;Chun-Yi Su;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 329 - 340
Publisher: IEEE
 
» Interfacial Crystal Structures and Non-Local Spin Signals of Co2FeAl0.5Si0.5/n-GaAs Junctions
Abstract:
We have investigated interfacial crystal structures and non-local spin signals of Co2FeAl0.5Si0.5 (CFAS)/n-GaAs junctions. Cross-sectional transmission electron microscopy observations indicated that with the exception of Ga diffusion into CFAS of the sample deposited at 400 °C, the interfacial structure of the junctions and defect density at the interface were not very different for different CFAS fabrication temperatures of the substrate (. The obtained reflection high-energy electron diffraction patterns showed that all samples fabricated at varying from room temperature to 400 °C exhibited the L21 ordered structure in the vicinity of CFAS/n-GaAs junctions. It is found that the junctions with larger rectifying characteristic as indicated by the conduction ratio show larger spin signal . This may strongly affect the spin injection/detection efficiency.
Autors: Kohei Kataoka;Tatsuya Saito;Nobuki Tezuka;Masashi Matsuura;Satoshi Sugimoto;
Appeared in: IEEE Transactions on Magnetics
Publication date: Jan 2018, volume: 54, issue:1, pages: 1 - 3
Publisher: IEEE
 
» Interference Mitigation for Automotive Radar Using Orthogonal Noise Waveforms
Abstract:
To improve traffic safety, millimeter wave radars have been widely used for sensing traffic environment. As radars also operate on a narrow small road and in the same frequency band, mutual interference between different automotive radars that arises cannot be easily reduced by frequency or polarization diversity. This letter presents novel orthogonal noise waveforms to reduce such neighboring interferences. First, the spectral density distribution function of the proposed waveforms is defined by using an optimized Kaiser function. Subsequently, the phases of the noise waveforms are formulated as a problem of phase retrieval and are explored. Thanks to nonuniqueness solutions, the proposed method generates the orthogonal signals with a good random phase diversity. The proposed method was tested on a representative scenario for interference reduction. The experimental results show that the proposed method can produce visually convincing radar images, and the signal-to-interference and noise ratio is better than the existing methods.
Autors: Zhihuo Xu;Quan Shi;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 137 - 141
Publisher: IEEE
 
» Interference Model Similarity Index and Its Applications to Millimeter-Wave Networks
Abstract:
In wireless communication networks, interference models are routinely used for tasks, such as performance analysis, optimization, and protocol design. These tasks are heavily affected by the accuracy and tractability of the interference models. Yet, quantifying the accuracy of these models remains a major challenge. In this paper, we propose a new index for assessing the accuracy of any interference model under any network scenario. Specifically, it is based on a new index that quantifies the ability of any interference model in correctly predicting harmful interference events, that is, link outages. We consider specific wireless scenario of both conventional sub-6 GHz and millimeter-wave networks and demonstrate how our index yields insights into the possibility of simplifying the set of dominant interferers, replacing a Nakagami or Rayleigh random fading by an equivalent deterministic channel, and ignoring antenna sidelobes. Our analysis reveals that in highly directional antenna settings with obstructions, even simple interference models (such as the classical protocol model) are accurate, while with omnidirectional antennas, more sophisticated and complex interference models (such as the classical physical model) are necessary. Our new approach makes it possible to adopt the simplest interference model of adequate accuracy for every wireless network.
Autors: Hossein Shokri-Ghadikolaei;Carlo Fischione;Eytan Modiano;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 71 - 85
Publisher: IEEE
 
» Intrinsic Entropies of Log-Concave Distributions
Abstract:
The entropy of a random variable is well-known to equal the exponential growth rate of the volumes of its typical sets. In this paper, we show that for any log-concave random variable , the sequence of the intrinsic volumes of the typical sets of in dimensions grows exponentially with a well-defined rate. We denote this rate by , and call it the intrinsic entropy of . We show that is a continuous function of over the range [0, 1], thereby providing a smooth interpolation between the values 0 and at the endpoints 0 and 1, respectively.
Autors: Varun Jog;Venkat Anantharam;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 93 - 108
Publisher: IEEE
 
» Introducing Information Measures via Inference [Lecture Notes]
Abstract:
Information measures, such as the entropy and the Kullback-Leibler (KL) divergence, are typically introduced using an abstract viewpoint based on a notion of "surprise." Accordingly, the entropy of a given random variable (rv) is larger if its realization, when revealed, is on average more "surprising" (see, e.g., [1]-[3]). The goal of this lecture note is to describe a principled and intuitive introduction to information measures that builds on inference, i.e., estimation and hypothesis testing. Specifically, entropy and conditional entropy measures are defined using variational characterizations that can be interpreted in terms of the minimum Bayes risk in an estimation problem. Divergence metrics are similarly described using variational expressions derived via mismatched estimation or binary hypothesis testing principles. The classical Shannon entropy and the KL divergence are recovered as special cases of more general families of information measures.
Autors: Osvaldo Simeone;
Appeared in: IEEE Signal Processing Magazine
Publication date: Jan 2018, volume: 35, issue:1, pages: 167 - 171
Publisher: IEEE
 
» Introduction to the January Special Issue on the 2017 IEEE International Solid-State Circuits Conference
Abstract:
The IEEE International Solid-State Circuits Conference (ISSCC) is the premier global forum for presenting advances in solid-state circuits and system-on-a-chip. Every year since its first issue, the IEEE Journal of Solid-State Circuits has highlighted some well-received papers from the most recent ISSCC in special issues. This Special Issue covers the ISSCC Conference held in San Francisco, CA, USA, on February11–15, 2017.
Autors: Keith A. Bowman;Muhammad M. Khellah;Takashi Kono;Joseph Shor;Pui-In Mak;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 3 - 7
Publisher: IEEE
 
» Inversion-Driven Attenuation Compensation Using Synchrosqueezing Transform
Abstract:
Attenuation is a fundamental mechanism as seismic wave propagates through the earth. The loss of high-frequency energy and concomitant phase distortion can be compensated by inverse filtering to enhance the resolution of seismic data. Since the attenuation process depends on time and frequency, it is routinely performed in the time–frequency domain. The synchrosqueezing transform (SST), which provides highly localized time–frequency representations for the nonstationary signals due to reduced spectral smearing, is applied to implement the inverse filtering scheme. However, the amplitude compensation process is unstable because energy amplification is involved. To stabilize it, the amplitude compensation is regarded as an inverse problem with an L1-norm regularization term in the SST domain. The iteratively reweighted least-squares algorithm is used to solve the regularized inverse problem. Synthetic and real data examples illustrate the stability and effectiveness of the proposed method.
Autors: Guowei Zhang;Jinghuai Gao;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 132 - 136
Publisher: IEEE
 
» Investigation and Modeling of Ice Clouds Affecting Earth-Space Communication Systems
Abstract:
A model for ice clouds oriented to provide a useful tool for the accurate assessment of the impact of ice particles on Earth-space communications systems is presented. The model, developed starting from the data collected by the CloudSat LEO satellite, allows to synthesize vertical profiles of the ice water content from the sole knowledge of the whole integrated ice water content, which, in turn, can be typically obtained from numerical weather prediction models or as a remote sensing product of Earth observation satellites. Moreover, the base of ice clouds is investigated and modeled, separately for mid- and high-altitude clouds, mostly consisting only of ice particles, and for low-level clouds, typically composed by both ice and liquid water. In addition, the impact of ice clouds on Earth-space optical links is preliminary investigated. Results, obtained for two sites, indicate that the attenuation due to ice is not negligible at optical wavelengths, as it can be in the order of tens of decibels on zenithal paths. The present model is intended to be integrated into a broader simulator of weather disturbances affecting electromagnetic wave propagation, conceived to support the design and performance assessment of Earth-space communication systems (EHF range or optical wavelengths).
Autors: Lorenzo Luini;Andrea Quadri;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 360 - 367
Publisher: IEEE
 
» Investigation of Load Frequency Relief From Field Measurements and Its Impact on Contingency Reserve Evaluation
Abstract:
Any mismatch between load and generation (due to a generator or an interconnection trip) is intended to be balanced and stabilized by contingency reserve, which is also known as contingency Frequency Control Ancillary Services (FCAS) requirement. Load Frequency Relief (LFR), which represents the effect of frequency dependent loads on power system frequency excursion, is crucial for correctly evaluating contingency reserve requirement during generation dispatch to ensure an adequate frequency response. Over estimation of LFR can be accountable for less planned reserve during an economic dispatch that may cause undesirable frequency performance. On the other hand, under estimation of LFR can result in an excessive reserve and hence could unnecessarily increase system operational cost. Conventionally, LFR is considered as a fixed quantity during the evaluation of FCAS requirement. However, recent experience in the Australian power grid suggests that such an assumption may lead to an inaccurate outcome. To explore the above issue, this research investigates the LFR using field measurement data, which were captured at different locations of the southern states of Australia (e.g., Tasmania and Victoria). An approach is developed to identify the predominating factors affecting the LFR and subsequently a technique is proposed to appropriately determine contingency FCAS requirement.
Autors: Nahid-Al- Masood;Ruifeng Yan;Tapan Kumar Saha;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 567 - 577
Publisher: IEEE
 
» Investigation of the Double Current Path Phenomenon in Gate-Grounded Tunnel FET
Abstract:
Gate-grounded tunnel field-effect transistors (ggTFETs) are considered as basic electrostatic discharge (ESD) protection devices in TFET-integrated circuits. It has been reported that two current paths exist when the ggTFET is turned on under the ESD events. In this letter, the double current path phenomenon in ggTFETs is further investigated using TCAD simulation. It is found that the upper path is a hole current path, while the lower path mainly consists of electrons, and the grounded gate is a major factor that influences the double current path phenomenon. The heat and lattice temperature distributions in ggTFETs are also discussed.
Autors: Zhaonian Yang;Yue Zhang;Yuan Yang;Ningmei Yu;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 103 - 106
Publisher: IEEE
 
» Investigation on Iodine Concentration of Electrolyte for Dye-Sensitized Solar Cell With Platinum Counter Electrode Modified by Graphene Oxide and Magnetic Beads
Abstract:
In this study, we used graphene oxide (GO) and magnetic beads (MBs) to modify the dye-sensitized solar cell (DSSC). The titanium dioxide (TiO2) colloid was mixed with GO and MBs which was deposited on the top of platinum-counter electrode. In addition, we measured the photovoltaic performances of dssc with different iodide concentrations of electrolyte. Furthermore, we investigated the photovoltaic performances of DSSC under different light intensities. The DSSC achieves a photovoltaic conversion efficiency of 6.78% under the light intensity of 30 mw/cm2 for the electrolyte of 0.0125 m iodide.
Autors: Jung-Chuan Chou;Wan-Yu Hsu;Yi-Hung Liao;Chih-Hsien Lai;Pei-Hong You;Chien-Hung Kuo;Yu-Chi Huang;Chang-Chia Lu;Yu-Hsun Nien;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 133 - 139
Publisher: IEEE
 
» Investigations of Asymmetric Spacer Tunnel Layer Diodes for High-Frequency Applications
Abstract:
A complete description of physical models for fabricated asymmetric spacer tunnel layer (ASPAT) diodes is reported in this paper. A novel In0.53Ga0.47As/AlAs design is presented and compared to the conventional GaAs/AlAs material system. For both material schemes, physical models were developed based on experimental measurements. Simulated dc characteristics of the devices are given for both planar- and back-contacted structures to highlight the impact of spreading resistance on device behavior. Furthermore, full S-parameter derivations from numerical simulation for tunnel diodes are demonstrated for the first time on the basis of quantum-mechanical ac modeling of the capacitance–voltage and conductance–voltage performances of these ASPAT diodes. A negligibly small difference between measured and simulated zero-biased intrinsic capacitances is observed (i.e., ≤ 0.2 fF). These are beneficial for accurate predictive models for device characteristics. In addition, key parameters which can be extracted from simulation results are obtained to aid in the development of millimeter-wave/terahertz applications of these types of heterostructure tunnel devices.
Autors: K. N. Zainul Ariffin;Y. Wang;M. R. R. Abdullah;S. G. Muttlak;O. S. Abdulwahid;J. Sexton;Ka Wa Ian;M. J. Kelly;M. Missous;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 64 - 71
Publisher: IEEE
 
» Italy launches new IoT network [News]
Abstract:
Telecom Italia, Italy's largest telecommunications provider, is putting the finishing touches on a new wireless network for the Internet of Things that should be available nationwide by the end of January. The Internet of Things (IoT) is a catchall term for many kinds of connected devices-such as sensors, speakers, and cameras-found in cities, factories, and homes. These devices often don't need as much bandwidth as smartphones, but connecting them through existing LTE networks is expensive.
Autors: Amy Nordrum;
Appeared in: IEEE Spectrum
Publication date: Jan 2018, volume: 55, issue:1, pages: 9 - 10
Publisher: IEEE
 
» Iterative Deblending of Simultaneous-Source Seismic Data With Structuring Median Constraint
Abstract:
Simultaneous-source shooting can help reduce the acquisition time cost, but at the expense of introducing strong interference (blending noise) into the acquired seismic data. It has been demonstrated previously that the deblending problem can be considered as an inversion process. In this letter, we propose a new iterative approach to solve this inversion problem. In the proposed approach, a new coherency-promoting constraint, called structuring median filtering (SMF), is proposed and used to regularize the estimated model in each iteration. The SMF processes the signal by the interactions of the input signal and another given small section of signal, namely, the structuring element. The SMF is more robust than other coherency-promoting filtering such as the median filtering and mathematical morphological filtering. Numerical experiments demonstrate that the iterative deblending based on the SMF constraint obtains a better performance and a faster convergence than the low-rank and compressed sensing constraint-based deblending approaches.
Autors: Weilin Huang;Runqiu Wang;Xiangbo Gong;Yangkang Chen;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 58 - 62
Publisher: IEEE
 
» iTTVis: Interactive Visualization of Table Tennis Data
Abstract:
The rapid development of information technology paved the way for the recording of fine-grained data, such as stroke techniques and stroke placements, during a table tennis match. This data recording creates opportunities to analyze and evaluate matches from new perspectives. Nevertheless, the increasingly complex data poses a significant challenge to make sense of and gain insights into. Analysts usually employ tedious and cumbersome methods which are limited to watching videos and reading statistical tables. However, existing sports visualization methods cannot be applied to visualizing table tennis competitions due to different competition rules and particular data attributes. In this work, we collaborate with data analysts to understand and characterize the sophisticated domain problem of analysis of table tennis data. We propose iTTVis, a novel interactive table tennis visualization system, which to our knowledge, is the first visual analysis system for analyzing and exploring table tennis data. iTTVis provides a holistic visualization of an entire match from three main perspectives, namely, time-oriented, statistical, and tactical analyses. The proposed system with several well-coordinated views not only supports correlation identification through statistics and pattern detection of tactics with a score timeline but also allows cross analysis to gain insights. Data analysts have obtained several new insights by using iTTVis. The effectiveness and usability of the proposed system are demonstrated with four case studies.
Autors: Yingcai Wu;Ji Lan;Xinhuan Shu;Chenyang Ji;Kejian Zhao;Jiachen Wang;Hui Zhang;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 709 - 718
Publisher: IEEE
 
» Joint Discriminative Dictionary and Classifier Learning for ALS Point Cloud Classification
Abstract:
To efficiently recognize on-ground objects in airborne laser scanning (ALS) point clouds, we design a method that jointly learns a discriminative dictionary and a classifier. In the method, the point cloud is segmented into hierarchical point clusters, which are organized by a tree structure. Then, the feature of each point cluster is extracted. The feature of a leaf node is obtained by aggregating the features of all its parent nodes. The feature of the leaf node is called the hierarchical aggregation feature. The hierarchical aggregation features are encoded by sparse coding. We introduce a new label consistency constraint called “discriminative sparse-code error,” and combine it with the reconstruction error, the classification error, and -norm sparsity constraint to form a unified objective function. The objective function is efficiently solved by using the proposed label consistency feature sign method. We obtain an overcomplete discriminative dictionary and an optimal linear classifier. Experiments performed on different ALS point cloud scenes have shown that the hierarchical aggregation features combined with the learned classifier can significantly enhance the classification results, and also demonstrated the superior performance of our method over other techniques in point cloud classification.
Autors: Zhenxin Zhang;Liqiang Zhang;Yumin Tan;Liang Zhang;Fangyu Liu;Ruofei Zhong;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 524 - 538
Publisher: IEEE
 
» Joint Estimation of Timing and Carrier Phase Offsets for MSK Signals in Alpha-Stable Noise
Abstract:
Impulsive noise modeled as symmetric -stable () distribution is commonly seen in many practical communication scenarios. In this letter, we focus on the joint timing and carrier phase synchronization of minimum shift keying signals in noise. We first derive the Cramér–Rao lower bound (CRLB) of joint timing and carrier phase offsets estimation. Then, an optimal synchronization training sequence is designed to minimize the CRLB. As the corresponding maximum likelihood estimator is hard to implement in noise, we further propose a pragmatic synchronization parameters estimation algorithm based on explicit myriad cost function and a global optimization method. Extensive simulation results show that our proposed algorithm works well and is robust to the estimation errors of received signal-to-noise ratio and noise parameter.
Autors: Guosheng Yang;Jun Wang;Guoyong Zhang;Qijia Shao;Shaoqian Li;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 89 - 92
Publisher: IEEE
 
» Joint Inversion of Electromagnetic and Seismic Data Based on Structural Constraints Using Variational Born Iteration Method
Abstract:
An efficient 2-D joint full-waveform inversion method for electromagnetic and seismic data in a layered medium background is developed. The joint inversion method based on the integral equation (IE) method is first proposed in this paper. In forward computation, the IE method is employed, which usually has smaller discretized computation domain and less cumulative error compared with the finite-difference method. In addition, fast Fourier transform is used to accelerate the convolution between Green’s functions and induced sources due to the shift invariance property of the layered Green’s functions in the horizontal direction. In the inversion model, the cross-gradient function is incorporated into the cost function of the separate inversion to enforce the structure similarity between electric conductivity and seismic-wave velocity. We use the improved variational Born iteration method and two different iteration strategies to minimize the cost function and reconstruct the contrasts. Several typical models in geophysical applications are used to validate our joint inversion method, and the numerical simulation results show that joint inversion can improve the inversion results when compared with those from the separate inversion.
Autors: Tian Lan;Hai Liu;Na Liu;Jinghe Li;Feng Han;Qing Huo Liu;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 436 - 445
Publisher: IEEE
 
» Joint Latent Dirichlet Allocation for Social Tags
Abstract:
Social tags, serving as a textual source of simple but useful semantic metadata to reflect the user preference or describe the web objects, has been widely used in many applications. However, social tags have several unique characteristics, i.e., sparseness and data coupling (i.e., non-IIDness), which makes existing text analysis methods such as LDA not directly applicable. In this paper, we propose a new generative algorithm for social tag analysis named joint latent Dirichlet allocation, which models the generation of tags based on both the users and the objects, and thus accounts for the coupling relationships among social tags. The model introduces two latent factors that jointly influence tag generation: the user's latent interest factor and the object's latent topic factor, formulated as user-topic distribution matrix and object-topic distribution matrix, respectively. A Gibbs sampling approach is adopted to simultaneously infer the above two matrices as well as a topic-word distribution matrix. Experimental results on four social tagging datasets have shown that our model is able to capture more reasonable topics and achieves better performance than five state-of-the-art topic models in terms of the widely used point-wise mutual information metric. In addition, we analyze the learnt topics showing that our model recovers more themes from social tags while LDA may lead the topic vanishing problems, and demonstrate its advantages in the social recommendation by evaluating the retrieval results with mean reciprocal rank metric. Finally, we explore the joint procedure of our model in depth to show the non-IID characteristic of social tagging process.
Autors: Jiangchao Yao;Yanfeng Wang;Ya Zhang;Jun Sun;Jun Zhou;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 224 - 237
Publisher: IEEE
 
» Joint Magnetic Calibration and Localization Based on Expectation Maximization for Tongue Tracking
Abstract:
Background: Tongue tracking, which helps researchers gain valuable insights into speech mechanism, has many applications in speech therapy and language learning. The wireless localization technique, which involves tracking a small magnetic tracer within the 3-D oral space, provides a low cost and convenient approach to capture tongue kinematics. In practice, this technique requires accurate calibration of three-axial magnetic sensors used in the tracking system. The data-driven calibration depends on the trajectories of magnetic tracer and the ambient noise, which may change across time and space. Methods: In this paper, we model the kinematics of tracer movement and the noisy magnetic measurements in a Bayesian framework, then present a joint calibration and localization (JCL) algorithm based on expectation maximization (EM), where the unscented Rauch–Tung–Striebel smoother is employed for tracer localization and the curvilinear search algorithm is applied for sensor calibration. Results: Based on measurements conducted on our tongue tracking system with a small magnetic tracer (diameter: 6.05 mm, thickness: 1.25 mm, residual induction: 14 800 G), the JCL algorithm achieves averaged root mean square error of 0.45 mm for tracer position estimation and for tracer orientation estimation, which are significantly lower than those of the separate calibration and localization algorithms. Conclusion: These results show that JCL can help improve the localization accuracy of this system. Significance: A potentially high precision tongue tracking method is demonstrated.
Autors: Jun Lu;Zhongtao Yang;Klaus Z. Okkelberg;Maysam Ghovanloo;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Jan 2018, volume: 65, issue:1, pages: 52 - 63
Publisher: IEEE
 
» Joint Prioritized Scheduling and Resource Allocation for OFDMA-Based Wireless Networks
Abstract:
In this paper, we study the joint prioritized link scheduling and resource allocation for OFDMA-based wireless networks, which serve two classes of wireless links, namely, non-prioritized (low-priority) and prioritized (high-priority) links. Our design aims to maximize the number of scheduled non-prioritized links and their sum rate, while guaranteeing the minimum required rates of all active prioritized and non-prioritized links. We present the problem formulation as a single-stage optimization problem, which simultaneously maximizes the number of scheduled non-prioritized links and their sum rate. We propose a monotonic-based optimal approaching (MBOA) algorithm to solve this problem by employing the monotonic global optimization technique and an efficient rounding procedure. We prove that the MBOA algorithm can schedule the maximum number of non-prioritized links with slight and controllable degradation in the minimum required rates of non-prioritized links. For low-complexity design, we propose an iterative convex approximation algorithm, which sequentially performs power allocation and link removal in each iteration. We then describe how the proposed algorithms can be implemented in the standardized LTE-based cellular system. Finally, we conduct numerical studies for device-to-device communications underlaid cellular networks under perfect or imperfect channel state information (CSI). Numerical results demonstrate that the proposed algorithms can be applied to the imperfect CSI scenario with slight degradation in the network performance. Moreover, in the perfect CSI scenario, the proposed algorithms significantly outperform the conventional algorithms both in the number of scheduled non-prioritized links and their sum rate.
Autors: Tuong Duc Hoang;Long Bao Le;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 310 - 323
Publisher: IEEE
 
» Joint Statistical Iterative Material Image Reconstruction for Spectral Computed Tomography Using a Semi-Empirical Forward Model
Abstract:
By acquiring tomographic measurements with several distinct photon energy spectra, spectral computed tomography (spectral CT) is able to provide additional material-specific information compared with conventional CT. This information enables the generation of material selective images, which have found various applications in medical imaging. However, material decomposition typically leads to noise amplification and a degradation of the signal-to-noise ratio. This is still a fundamental problem of spectral CT, especially for low-dose medical applications. Inspired by the success for low-dose conventional CT, several statistical iterative reconstruction algorithms for spectral CT have been developed. These algorithms typically rely on detailed knowledge about the spectrum and the detector response. Obtaining this knowledge is often difficult in practice, especially if photon counting detectors are used to acquire the energy specific information. In this paper, a new algorithm for joint statistical iterative material image reconstruction is presented. It relies on a semi-empirical forward model which is tuned by calibration measurements. This strategy allows to model spatially varying properties of the imaging system without requiring detailed prior knowledge of the system parameters. We employ an efficient optimization algorithm based on separable surrogate functions to accelerate convergence and reduce the reconstruction time. Numerical as well as real experiments show that our new algorithm leads to reduced statistical bias and improved image quality compared with projection-based material decomposition followed by analytical or iterative image reconstruction.
Autors: Korbinian Mechlem;Sebastian Ehn;Thorsten Sellerer;Eva Braig;Daniela Münzel;Franz Pfeiffer;Peter B. Noël;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 68 - 80
Publisher: IEEE
 
» Joint Trajectory and Power Optimization for UAV Relay Networks
Abstract:
In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.
Autors: Shuhang Zhang;Hongliang Zhang;Qichen He;Kaigui Bian;Lingyang Song;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 161 - 164
Publisher: IEEE
 
» Joint User Association and Power Allocation for Cell-Free Visible Light Communication Networks
Abstract:
As a complementary technology for conventional radio frequency communication, visible light communication (VLC) is a potential form of the optical wireless communication, which can provide both communication and illumination simultaneously. Since load balancing and power control for interference management are key challenges in the network deployment, we consider a joint user association and power allocation scheme in a cell-free VLC network to improve the system performance. It is mathematically formulated as a non-convex network utility maximization problem in consideration of the user fairness, load balancing, and power control. To tackle this non-convex problem, we divide it into two subproblems (i.e., the user association subproblem and the power allocation subproblem) and solve them with the dual projected gradient algorithm and successive convex approximation algorithm iteratively until a stationary point is found. Simulation results verify that significant gain can be achieved with the proposed scheme compared with the user association schemes without consideration of the power control.
Autors: Rui Jiang;Qi Wang;Harald Haas;Zhaocheng Wang;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 136 - 148
Publisher: IEEE
 
» Joint-Transformation-Based Detection of False Data Injection Attacks in Smart Grid
Abstract:
For reliable operation and control of smart grid, estimating the correct states is of utmost importance to the system operator. With recent incorporation of information technology and advanced metering infrastructure, the futuristic grid is more prone to cyber-threats. The false data injection (FDI) attack is one of the most thoroughly researched cyber-attacks. Intelligently crafted, it can cause false estimation of states, which further seriously affects the entire power system operation. In this paper, we propose joint-transformation-based scheme to detect FDI attacks in real time. The proposed method is built on the dynamics of measurement variations. Kullback–Leibler distance is used to find out the difference between probability distributions obtained from measurement variations. The proposed method is tested using IEEE 14 bus system considering attack on different state variables. The results shows that the proposed scheme detects FDI attacks with high detection probability.
Autors: Sandeep Kumar Singh;Kush Khanna;Ranjan Bose;Bijaya Ketan Panigrahi;Anupam Joshi;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 89 - 97
Publisher: IEEE
 
» Junctionless Nanosheet (3 nm) Poly-Si TFT: Electrical Characteristics and Superior Positive Gate Bias Stress Reliability
Abstract:
In this letter, a junctionless (JL) poly-Si thin-film transistor (TFT) with a 3-nm-thick nanosheet channel is successfully fabricated using the low-temperature atomic level etching process. An inversion-mode (IM) TFT is also prepared for performance comparison and reliability investigation of positive gate bias stress (PGBS). In comparison with the IM-TFT, the JL-TFT exhibits superior PGBS reliability. The origin of the difference in degradation rates between the JL and IM-TFTs is ascribed to the different transport mechanisms and different gate dielectric fields under the same gate over-drive stress. Nanosheet JL-TFTs with a 3-nm channel thickness show excellent S.S (69 mV/decade) and extremely low off-current (1.93 fA). Results indicate that it is a promising candidate for low-power 3-D integrated circuits.
Autors: Jer-Yi Lin;Malkundi Puttaveerappa Vijay Kumar;Tien-Sheng Chao;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 8 - 11
Publisher: IEEE
 
» Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring
Abstract:
Visualizations often appear in multiples, either in a single display (e.g., small multiples, dashboard) or across time or space (e.g., slideshow, set of dashboards). However, existing visualization design guidelines typically focus on single rather than multiple views. Solely following these guidelines can lead to effective yet inconsistent views (e.g., the same field has different axes domains across charts), making interpretation slow and error-prone. Moreover, little is known how consistency balances with other design considerations, making it difficult to incorporate consistency mechanisms in visualization authoring software. We present a wizard-of-oz study in which we observed how Tableau users achieve and sacrifice consistency in an exploration-to-presentation visualization design scenario. We extend (from our prior work) a set of encoding-specific constraints defining consistency across multiple views. Using the constraints as a checklist in our study, we observed cases where participants spontaneously maintained consistent encodings and warned cases where consistency was overlooked. In response to the warnings, participants either revised views for consistency or stated why they thought consistency should be overwritten. We categorize participants' actions and responses as constraint validations and exceptions, depicting the relative importance of consistency and other design considerations under various circumstances (e.g., data cardinality, available encoding resources, chart layout). We discuss automatic consistency checking as a constraint-satisfaction problem and provide design implications for communicating inconsistencies to users.
Autors: Zening Qu;Jessica Hullman;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 468 - 477
Publisher: IEEE
 
» Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Material
Abstract:
Kilohertz electrical stimulation (KES) has enabled a novel new paradigm for spinal cord and peripheral nerve stimulation to treat a variety of neurological diseases. KES can excite or inhibit nerve activity and is used in many clinical devices today. However, the impact of different electrode materials on the efficacy of KES is unknown. We investigated the effect of different electrode materials and their respective charge injection mechanisms on KES nerve block thresholds using 20- and 40-kHz current-controlled sinusoidal KES waveforms. We evaluated the nerve block threshold and the power requirements for achieving an effective KES nerve block. In addition, we evaluated potential effects on the onset duration and recovery of normal conduction after delivery of KES. We found that thresholds and the onset and recovery of KES nerve block are not a function of the electrode material. In contrast, the power dissipation varies among electrode materials and is a function of the materials’ properties at high frequencies. We conclude that materials with a proven track record of chronic stability, both for the tissue and electrode, are suitable for developing KES nerve block therapies.
Autors: Yogi A. Patel;Brian S. Kim;Robert J. Butera;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 11 - 17
Publisher: IEEE
 
» L1-Norm Distance Linear Discriminant Analysis Based on an Effective Iterative Algorithm
Abstract:
Recent works have proposed two L1-norm distance measure-based linear discriminant analysis (LDA) methods, L1-LD and LDA-L1, which aim to promote the robustness of the conventional LDA against outliers. In LDA-L1, a gradient ascending iterative algorithm is applied, which, however, suffers from the choice of stepwise. In L1-LDA, an alternating optimization strategy is proposed to overcome this problem. In this paper, however, we show that due to the use of this strategy, L1-LDA is accompanied with some serious problems that hinder the derivation of the optimal discrimination for data. Then, we propose an effective iterative framework to solve a general L1-norm minimization–maximization (minmax) problem. Based on the framework, we further develop a effective L1-norm distance-based LDA (called L1-ELDA) method. Theoretical insights into the convergence and effectiveness of our algorithm are provided and further verified by extensive experimental results on image databases.
Autors: Qiaolin Ye;Jian Yang;Fan Liu;Chunxia Zhao;Ning Ye;Tongming Yin;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 114 - 129
Publisher: IEEE
 
» Latent-Class Hough Forests for 6 DoF Object Pose Estimation
Abstract:
In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributions at the leaf nodes as latent variables. During testing we infer by iteratively updating these distributions, providing accurate estimation of background clutter and foreground occlusions and, thus, better detection rate. Furthermore, as a by-product, our Latent-Class Hough Forests can provide accurate occlusion aware segmentation masks, even in the multi-instance scenario. In addition to an existing public dataset, which contains only single-instance sequences with large amounts of clutter, we have collected two, more challenging, datasets for multiple-instance detection containing heavy 2D and 3D clutter as well as foreground occlusions. We provide extensive experiments on the various parameters of the framework such as patch size, number of trees and number of iterations to infer class distributions at test time. We also evaluate the Latent-Class Hough Forests on all datasets where we outperform state of the art methods.
Autors: Alykhan Tejani;Rigas Kouskouridas;Andreas Doumanoglou;Danhang Tang;Tae-Kyun Kim;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 119 - 132
Publisher: IEEE
 
» Layout and Interconnect Optimization for Low-Power and High-Sensitivity Operation of $E$ -Band SiGe HBT Frequency Dividers
Abstract:
A layout and interconnect optimization techniques for low-power and high-sensitivity performance of static frequency dividers in -band is reported. The layout optimization provides optimal transistor placement and identifies critical interconnects, which allows to reduce their parasitics. These measures provide high operation frequency and good sensitivity of the divider without a need of investing additional dc current.
Autors: Aleksey Dyskin;Parisa Harati;Ingmar Kallfass;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 67 - 69
Publisher: IEEE
 
» LDSScanner: Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets
Abstract:
Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the axis and axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS ( axis) and the variation of LTS in structures (the combination of axis and axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.
Autors: Jiazhi Xia;Fenjin Ye;Wei Chen;Yusi Wang;Weifeng Chen;Yuxin Ma;Anthony K.H. Tung;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 236 - 245
Publisher: IEEE
 
» Learning From Cross-Domain Media Streams for Event-of-Interest Discovery
Abstract:
Every day, vast amounts of data are uploaded to various social-sharing websites. Each social-sharing website has its own media dataset. Recently, mining media datasets has shown great potential for our daily lives, e.g., earthquake detection. Generally, different datasets have different characteristics. Combining different datasets is capable of achieving better performance than using any dataset independently, particularly if the datasets can compensate for each other. The resulting performance, however, depends on the fusion method. Effectively combining different datasets is challenging. As a solution to this challenge, this paper presents a generic two-stage framework for events of interest. Specifically, the first stage normalizes the contents of different datasets to make them comparable; then, the second stage combines the normalized contents for a ranked event list using graph-based algorithms. Practically, this paper unifies a flow-based media dataset and a check-in-based media dataset. Based on the precision for the top n events, the experimental results demonstrate that the proposed framework can achieve better performance in finding events associated with sports, local festivals, concerts, and exhibitions compared with a state-of-the-art approach that uses one dataset alone.
Autors: Wen-Yu Lee;Winston H. Hsu;Shin’ichi Satoh;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 142 - 154
Publisher: IEEE
 
» Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging
Abstract:
The integration of compressed sensing and parallel imaging (CS-PI) has shown an increased popularity in recent years to accelerate magnetic resonance (MR) imaging. Among them, calibration-free techniques have presented encouraging performances due to its capability in robustly handling the sensitivity information. Unfortunately, existing calibration-free methods have only explored joint-sparsity with direct analysis transform projections. To further exploit joint-sparsity and improve reconstruction accuracy, this paper proposes to Learn joINt-sparse coDes for caliBration-free parallEl mR imaGing (LINDBERG) by modeling the parallel MR imaging problem as an –– minimization objective with an norm constraining data fidelity, Frobenius norm enforcing sparse representation error and the mixed norm triggering joint sparsity across multichannels. A corresponding algorithm has been developed to alternatively update the sparse representation, sensitivity encoded images and K-space data. Then, the final image is produced as the square root of sum of squares of all channel images. Experimental results on both physical phantom and in vivo data sets show that the proposed method is comparable and even superior to state-of-the-art CS-PI reconstruction approaches. Specifically, LINDBERG has presented strong capability in suppressing noise and artifacts while reconstructing MR images from highly undersampled multichannel measurements.
Autors: Shanshan Wang;Sha Tan;Yuan Gao;Qiegen Liu;Leslie Ying;Taohui Xiao;Yuanyuan Liu;Xin Liu;Hairong Zheng;Dong Liang;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 251 - 261
Publisher: IEEE
 
» Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification
Abstract:
In this paper, we propose a multiscale deep feature learning method for high-resolution satellite image scene classification. Specifically, we first warp the original satellite image into multiple different scales. The images in each scale are employed to train a deep convolutional neural network (DCNN). However, simultaneously training multiple DCNNs is time-consuming. To address this issue, we explore DCNN with spatial pyramid pooling (SPP-net). Since different SPP-nets have the same number of parameters, which share the identical initial values, and only fine-tuning the parameters in fully connected layers ensures the effectiveness of each network, thereby greatly accelerating the training process. Then, the multiscale satellite images are fed into their corresponding SPP-nets, respectively, to extract multiscale deep features. Finally, a multiple kernel learning method is developed to automatically learn the optimal combination of such features. Experiments on two difficult data sets show that the proposed method achieves favorable performance compared with other state-of-the-art methods.
Autors: Qingshan Liu;Renlong Hang;Huihui Song;Zhi Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 117 - 126
Publisher: IEEE
 
» Learning Traversability From Point Clouds in Challenging Scenarios
Abstract:
This paper aims at evaluating the capabilities to detect road traversability in urban and extra-urban scenarios of support vector machine-based classifiers that use local descriptors extracted from point cloud data. The evaluation of the proposed classifiers is carried out by using four different kernels and comparing five point descriptors obtained from geometric and appearance-based features. A comparison among the performance of descriptors individually has demonstrated that the normal vector-based descriptor achieves an accuracy of 88%, outperforming by about 6%–15% all the other considered ones. To further improve the interpretation capabilities, the space of features is augmented by merging the components of each point descriptor, reaching 92% classification accuracy. A set of test scenarios have been acquired during an extensive experimental campaign using an all-terrain vehicle. Tests on real data show high classification performance for road scenarios and rural environments; the generality of the method makes it applicable for different types of mobile robots including, but not limited to, autonomous vehicles.
Autors: Mauro Bellone;Giulio Reina;Luca Caltagirone;Mattias Wahde;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 296 - 305
Publisher: IEEE
 
» Learning-Based Caching in Cloud-Aided Wireless Networks
Abstract:
This letter studies content caching in cloud-aided wireless networks, where small cell base stations with limited storage are connected to the cloud via limited capacity fronthaul links. By formulating a utility (inverse of service delay) maximization problem, we propose a cache update algorithm based on spatio-temporal traffic demands. To account for the large number of contents, we propose a content clustering algorithm to group similar contents. Subsequently, with the aid of regret learning at small cell base stations and the cloud, each base station caches contents based on the learned content popularity subject to its storage constraints. The performance of the proposed caching algorithm is evaluated for sparse and dense environments, while investigating the tradeoff between global and local class popularity. Simulation results show 15% and 40% gains in the proposed method compared to various baselines.
Autors: Syed Tamoor-ul-Hassan;Sumudu Samarakoon;Mehdi Bennis;Matti Latva-aho;Choong Seon Hong;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 137 - 140
Publisher: IEEE
 
» Least Square Error Precoders for Massive MIMO With Signal Constraints: Fundamental Limits
Abstract:
This paper proposes nonlinear least square error (LSE) precoders for multiuser MIMO broadcast channels. The LSE precoders are designed such that the discrete output signals are from a predefined set. This predefined set allows us to model several signal constraints such as peak power constraint, constant envelope, and discrete constellations. We study the large-system performance of these precoders via the replica method from statistical physics, and derive a closed-form expression for the asymptotic distortion. Our results demonstrate that an LSE precoder with the output peak-to-average power ratio of 3 dB can perform similar to the regularized zero forcing (RZF) precoder. As the peak-to-average power ratio reduces to one, the constant envelope precoder is recovered. The investigations show that the performance of the RZF precoder is achieved by a constant envelope precoder with 20% additional transmit antennas. For -phase shift keying constellations, our analysis gives a lower bound on the asymptotic distortion which is tight for moderate antenna-to-user ratios and deviates as the ratio grows. We improve this bound by deriving the replica solution under one-step of replica symmetry breaking. Our numerical investigations for this case show that the bound is tight for antenna-to-user ratios less than 5.
Autors: Mohammad Ali Sedaghat;Ali Bereyhi;Ralf R. Müller;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 667 - 679
Publisher: IEEE
 
» Least Squares Estimation Based SDP Cuts for SOCP Relaxation of AC OPF
Abstract:
It has been known that the second-order conic programming (SOCP) relaxation of an alternating current optimal power flow (ac OPF) problem is a computationally friendly formulation, whereas the semidefinite programming (SDP) relaxation is a theoretically stronger one. This paper presents a method to strengthen the (SOCP) relaxation by generating new cutting planes, i.e., valid inequalities, using SDP relaxation, which remove SOCP solutions that are infeasible to SDP formulation. This new method relies on solving a least square estimation (LSE) problem for every cycle in a cycle basis. General feasibility cutting plane method is also employed for cuts generation. We show that the SDP cuts generated by the LSE method are indeed feasibility cuts. Numerical results show that those new cuts can effectively reduce the search space and lead to a tighter relaxation. The new cuts are comparable to the SDP cuts in [1]. Case studies on systems with several buses to thousands buses have demonstrated the method is also scalable.
Autors: Zhixin Miao;Lingling Fan;Hossein Ghassempour Aghamolki;Bo Zeng;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 241 - 248
Publisher: IEEE
 
» Lessons Learned from Protection and Control Schemes Testing: The Results of Multiple Trials Using IEC 61850 Goose Messaging at an Oil Refinery
Abstract:
Several Trials for Protection and Control Schemes based on the International Electrotechnical Commission (IEC) 61850 standard were recently implemented for the new electrical system at a U.S. oil refinery. IEC 61850, generic object-oriented substation event (GOOSE) messaging, was used for several schemes, including transfer tripping, breaker failure, islanding detection, remote synchronizing, automatic restoration, manual transfer, and load shedding. Site acceptance tests validated the operation of the protection and control schemes. Bench testing was also performed for the load-shedding scheme using a power-system simulator. All of the testing focused on verifying scheme operations during normal operation and failure modes. The experience gained during early project trials influenced the design and testing of subsequent schemes. This article describes the bench and site acceptance testing approaches used and presents example tests along with their relevant results and the lessons learned.
Autors: Jared Mraz;Aaron Cowan;Keith Gray;Kirti S. Shah;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 60 - 70
Publisher: IEEE
 
» Leveraging Accuracy-Uncertainty Tradeoff in SVM to Achieve Highly Accurate Outage Predictions
Abstract:
This letter proposes a three-dimensional Support Vector Machine (SVM) for power grid component outage prediction, and furthermore leverages its accuracy–uncertainty tradeoff to achieve highly accurate results. The model is developed based on three distinct features of component deterioration, distance from the extreme event, and the intensity of the extreme event, and is analytically investigated to exhibit its acceptable performance.
Autors: Rozhin Eskandarpour;Amin Khodaei;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1139 - 1141
Publisher: IEEE
 
» Leveraging Software-Defined Networking for Incident Response in Industrial Control Systems
Abstract:
In the past decade, the security of industrial control systems has emerged as a research priority in order to safeguard our critical infrastructures. A large number of research efforts have focused on intrusion detection in industrial networks; however, few of them discuss what to do after an intrusion has been detected. Because the safety of most of these control systems is time sensitive, we need new research on automatic incident response. This article shows how software-defined networks and network function virtualization can facilitate automatic incident response to a variety of attacks against industrial networks. It also presents a prototype of an incident-response solution that detects and responds automatically to sensor attacks and controller attacks. This work shows the promise that cloud-enabled software-defined networks and virtual infrastructures hold as a way to provide novel defense-in-depth solutions for industrial systems. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Autors: Andrés F. Murillo Piedrahita;Vikram Gaur;Jairo Giraldo;Álvaro A. Cárdenas;Sandra Julieta Rueda;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 44 - 50
Publisher: IEEE
 
» Lidar-Based Gait Analysis and Activity Recognition in a 4D Surveillance System
Abstract:
This paper presents new approaches for gait and activity analysis based on data streams of a rotating multibeam (RMB) Lidar sensor. The proposed algorithms are embedded into an integrated 4D vision and visualization system, which is able to analyze and interactively display real scenarios in natural outdoor environments with walking pedestrians. The main focus of the investigations is gait-based person reidentification during tracking and recognition of specific activity patterns, such as bending, waving, making phone calls, and checking the time looking at wristwatches. The descriptors for training and recognition are observed and extracted from realistic outdoor surveillance scenarios, where multiple pedestrians are walking in the field of interest following possibly intersecting trajectories; thus, the observations might often be affected by occlusions or background noise. Since there is no public database available for such scenarios, we created and published a new Lidar-based outdoor gait and activity data set on our website that contains point cloud sequences of 28 different persons extracted and aggregated from 35-min-long measurements. The presented results confirm that both efficient gait-based identification and activity recognition are achievable in the sparse point clouds of a single RMB Lidar sensor. After extracting the people trajectories, we synthesized a free-viewpoint video, in which moving avatar models follow the trajectories of the observed pedestrians in real time, ensuring that the leg movements of the animated avatars are synchronized with the real gait cycles observed in the Lidar stream.
Autors: Csaba Benedek;Bence Gálai;Balázs Nagy;Zsolt Jankó;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 101 - 113
Publisher: IEEE
 

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