Electrical and Electronics Engineering publications abstract of: 01-2018 sorted by title, page: 12

» Real-Time Object Tracking on a Drone With Multi-Inertial Sensing Data
Abstract:
Real-time object tracking on a drone under a dynamic environment has been a challenging issue for many years, with existing approaches using off-line calculation or powerful computation units on board. This paper presents a new lightweight real-time onboard object tracking approach with multi-inertial sensing data, wherein a highly energy-efficient drone is built based on the Snapdragon flight board of Qualcomm. The flight board uses a digital signal processor core of the Snapdragon 801 processor to realize PX4 autopilot, an open-source autopilot system oriented toward inexpensive autonomous aircraft. It also uses an ARM core to realize Linux, robot operating systems, open-source computer vision library, and related algorithms. A lightweight moving object detection algorithm is proposed that extracts feature points in the video frame using the oriented FAST and rotated binary robust independent elementary features algorithm and adapts a local difference binary algorithm to construct the image binary descriptors. The K-nearest neighbor method is then used to match the image descriptors. Finally, an object tracking method is proposed that fuses inertial measurement unit data, global positioning system data, and the moving object detection results to calculate the relative position between coordinate systems of the object and the drone. All the algorithms are run on the Qualcomm platform in real time. Experimental results demonstrate the superior performance of our method over the state-of-the-art visual tracking method.
Autors: Peng Chen;Yuanjie Dang;Ronghua Liang;Wei Zhu;Xiaofei He;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 131 - 139
Publisher: IEEE
 
» Real-Time Scalable Visual Tracking via Quadrangle Kernelized Correlation Filters
Abstract:
Correlation filter (CF) has been widely used in tracking tasks due to its simplicity and high efficiency. However, conventional CF-based trackers fail to handle the scale variation that occurs when the targeted object is moving, which is one of the most notable unsolved problems of visual object tracking. In this paper, we propose a scalable visual tracking algorithm based on kernelized correlation filters, referred to as quadrangle kernelized correlation filters (QKCF). Unlike existing complicated scalable trackers that either perform the correlation filtering operation multiple times or extract many candidate windows at various scales, our tracker intends to estimate the scale of the object based on the positions of its four corners, which can be detected using a new Gaussian training output matrix within one filtering process. After obtaining four peak values corresponding to the four corners, we measure the detection confidence of each part response by evaluating its spatial and temporal smoothness. On top of it, a weighted Bayesian inference framework is employed to estimate the final location and size of the bounding box from the response matrix, where the weights are synchronized with the calculated detection likelihoods. Experiments are performed on the OTB-100 data set and 16 benchmark sequences with significant scale variations. The results demonstrate the superiority of the proposed method in terms of both effectiveness and robustness, compared with the state-of-the-art methods.
Autors: Guiguang Ding;Wenshuo Chen;Sicheng Zhao;Jungong Han;Qiaoyan Liu;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 140 - 150
Publisher: IEEE
 
» Realization Theory for a Class of Stochastic Bilinear Systems
Abstract:
This paper presents a complete realization theory for a class of discrete-time, bilinear systems with observed stochastic inputs, which we call generalized bilinear systems. This class of systems includes subclasses of bilinear systems, linear parameter varying (LPV) systems, and jump-Markov linear systems. We present necessary and sufficient conditions for the existence of a realization of generalized bilinear systems, along with a characterization of minimality in terms of rank conditions. We also formulate a realization algorithm and a minimization algorithm and we show that minimality can be checked algorithmically.
Autors: Mihály Petreczky;René Vidal;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 69 - 84
Publisher: IEEE
 
» Realizing a 2-D Positive Operator-Valued Measure by Local Operations and Classical Communication
Abstract:
We study the realization of a 2-D positive operator-valued measure (POVM) by local operations and classical communication (LOCC). We derive that any POVM on a 2-D Hilbert space in which each party’s space is finite dimensional can be realized by one-way LOCC. This implies that any optimal discrimination of quantum states spanning such a 2-D Hilbert space is possible by one-way LOCC, regardless of the optimality criterion used and how entangled the states are.
Autors: Kenji Nakahira;Tsuyoshi Sasaki Usuda;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 613 - 621
Publisher: IEEE
 
» Recent Advances in Zero-Shot Recognition: Toward Data-Efficient Understanding of Visual Content
Abstract:
With the recent renaissance of deep convolutional neural networks (CNNs), encouraging breakthroughs have been achieved on the supervised recognition tasks, where each class has sufficient and fully annotated training data. However, to scale the recognition to a large number of classes with few or no training samples for each class remains an unsolved problem. One approach is to develop models capable of recognizing unseen categories without any training instances, or zero-shot recognition/learning. This article provides a comprehensive review of existing zero-shot recognition techniques covering various aspects ranging from representations of models, data sets, and evaluation settings. We also overview related recognition tasks including one-shot and open-set recognition, which can be used as natural extensions of zero-shot recognition when a limited number of class samples become available or when zero-shot recognition is implemented in a real-world setting. We highlight the limitations of existing approaches and point out future research directions in this existing new research area.
Autors: Yanwei Fu;Tao Xiang;Yu-Gang Jiang;Xiangyang Xue;Leonid Sigal;Shaogang Gong;
Appeared in: IEEE Signal Processing Magazine
Publication date: Jan 2018, volume: 35, issue:1, pages: 112 - 125
Publisher: IEEE
 
» Recessed-Gate Enhancement-Mode $beta $ -Ga2O3 MOSFETs
Abstract:
We report enhancement-mode -Ga2O3 (BGO) MOSFETs on a Si-doped homoepitaxial channel grown by molecular beam epitaxy. A gate recess process is used to partially remove the epitaxial channel under the 1- gated region to fully deplete at V. BGO MOSFETs achieve drain current density near 40 mA/mm and ratio ~109 which is the highest reported for homoepitaxial normally-off BGO transistors. At V, a breakdown voltage of 198 and 505 V is achieved with the source–drain spacing of 3 and , respectively. The power switching figure of merits for dc conduction and dynamic switch losses meet or exceed the theoretical silicon limit and previously reported depletion-mode BGO transistors.
Autors: Kelson D. Chabak;Jonathan P. McCandless;Neil A. Moser;Andrew J. Green;Krishnamurthy Mahalingam;Antonio Crespo;Nolan Hendricks;Brandon M. Howe;Stephen E. Tetlak;Kevin Leedy;Robert C. Fitch;Daiki Wakimoto;Kohei Sasaki;Akito Kuramata;Gregg H. Jessen;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 67 - 70
Publisher: IEEE
 
» Reconfigurable Bandwidth Bandpass Filter With Enhanced Out-of-Band Rejection Using $pi $ -Section-Loaded Ring Resonator
Abstract:
A novel ring resonator bandpass filter with reconfigurable bandwidth with central frequency at 2.4 GHz is demonstrated. Theoretical analysis for computing the resonant frequencies is shown, and the design approach of implementing -section stubs connected to the ring to obtain the bandwidth reconfigurability is explained. The use of reconfigurable -section allows the alteration of the stub’s effective width and therefore the filter’s bandwidth reconfigurability. p-i-n diodes are used as switching elements to achieve the narrowband/wideband response. Coupled line sections are used for suppressing the higher modes by generating out-of-band transmission zeros, resulting in a significantly enhanced out-of-band rejection. Measurements indicate that the 3-dB fractional bandwidth can be switched from 58.5% to 75% at a fixed center frequency of 2.4 GHz with an insertion loss better than 1.1 dB. Moreover, the −20-dB stopband performance is extended to .
Autors: Salman Arain;Photos Vryonides;Muhammad Ali Babar Abbasi;Abdul Quddious;Marco A. Antoniades;Symeon Nikolaou;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 28 - 30
Publisher: IEEE
 
» Reconfigurable Linear/Circular Polarization Rectangular Waveguide Filtenna
Abstract:
We introduce a new reconfigurable linear polarization and circular polarization (CP) antenna, based on a rectangular waveguide (RWG) and a novel reconfigurable polarizer. The polarizer consists of two orthogonal apertures. The apertures transform the linear polarization of the dominant mode of the RWG antenna to CP. Each of these apertures is loaded by a p-i-n diode to alter its electrical length. This length difference provides the phase rotation needed to obtain CP. The signal polarization of the antenna can be selected by changing the applied bias voltage of p-i-n diodes as right-handed (RH)/left-handed (LH) CP. We can also achieve linear polarization if both diodes are ON or OFF. The reconfigurable polarizer acts as a bandpass filter, since the apertures can be considered as complementary electrically small resonators. This self-filtering capability is useful for reduction out of band noise in a communication system such as satellite links. The proposed antenna is designed to operate at 2.65 GHz, but the same approach can be applied to other frequency bands. The measurement results show a very good RH/LHCP and they are in good agreement with simulations.
Autors: Farhad Farzami;Seiran Khaledian;Besma Smida;Danilo Erricolo;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 9 - 15
Publisher: IEEE
 
» Recovery of the Complete Data Set From Focused Transmit Beams
Abstract:
The focused transmit beam is a standard tool for clinical ultrasound scanning, concentrating energy from a number of array elements toward an imaging target. However, above and below the transmit focus, much of the energy in the beam is spread in a broadened main lobe and long off-axis tails that are ignored by conventional beamforming methods. This paper proposes a method to decompose a set of focused transmit beams into their constituent components—diverging waves from individual array elements. The recovery of this complete data set enables synthetic transmit focusing at all points in the field of view without beam shape or focal depth artifacts commonly associated with virtual source synthetic aperture beamforming. An efficient frequency-domain linear decoding implementation is introduced. The principles of the method are demonstrated both in transmit field simulations and experimental imaging. At depth, up to a 9.6-dB improvement in electronic signal-to-noise ratio and 8.9-dB improvement in contrast were observed in comparison with conventional dynamic receive beamforming. The proposed method is broadly applicable to existing scan sequences and requires only channel data for processing.
Autors: Nick Bottenus;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Jan 2018, volume: 65, issue:1, pages: 30 - 38
Publisher: IEEE
 
» Rectifier Efficiency [Enigmas, etc.]
Abstract:
Various puzzles, humorous definitions, or mathematical recreations - usually having some relevance to electrical engineering - that should engage the interest of readers.
Autors: Takashi Ohira;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 136 - 136
Publisher: IEEE
 
» Reduced-Reference Quality Assessment of Screen Content Images
Abstract:
The screen content images (SCIs) quality influences the user experience and the interactive performance of remote computing systems. With numerous approaches proposed to evaluate the quality of natural images, much less work has been dedicated to reduced-reference image quality assessment (RR-IQA) of SCIs. Here, we propose an RR-IQA method from the perspective of SCI visual perception. In particular, the quality of the distorted SCI is evaluated by comparing a set of extracted statistical features that consider both primary visual information and unpredictable uncertainty. A unique property that differentiates the proposed method from previous RR-IQA methods for natural images is the consideration of behaviors when human subjects view the screen content, which motivates us to establish the perceptual model according to the distinct properties of SCIs. Validations based on the screen content IQA database show that the proposed algorithm provides accurate predictions across a wide range of SCI distortions with negligible transmission overhead.
Autors: Shiqi Wang;Ke Gu;Xinfeng Zhang;Weisi Lin;Siwei Ma;Wen Gao;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Jan 2018, volume: 28, issue:1, pages: 1 - 14
Publisher: IEEE
 
» Reducing Energy Costs in Electric-Motor-Driven Systems: Savings Through Output Power Reduction and Energy Regeneration
Abstract:
Electric-motor systems convert nearly half of worldwide electric energy into the mechanical energy ultimately used in the final application or process. The integral optimization of electric-motor-driven systems (EMODSs), including the use of high-efficiency, well-sized components, is the key strategy to effectively maximize their overall efficiency. However, the largest energy savings potential in motor-driven systems is associated with the reduction of the power required by the driven equipment through speed/torque control and/or with the partial reuse of the energy stored in the system. In this article, the basic principles and some practical examples of output power reduction and energy regeneration in EMODSs are presented.
Autors: Fernando J.T.E. Ferreira;Anibal T. de Almeida;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 84 - 97
Publisher: IEEE
 
» Reducing the Lift-Off Effect on Permeability Measurement for Magnetic Plates From Multifrequency Induction Data
Abstract:
Lift-off variation causes errors in eddy current measurement of nonmagnetic plates as well as magnetic plates. For nonmagnetic plates, previous work has been carried out to address the issue. In this paper, we follow a similar strategy, but try to reduce the lift-off effect on another index—zero-crossing frequency for magnetic plates. This modified index, termed as the compensated zero-crossing frequency, can be obtained from the measured multifrequency inductance spectral data using the algorithm we developed in this paper. Since the zero-crossing frequency can be compensated, the permeability of magnetic plates can finally be predicted by deriving the relation between the permeability and zero-crossing frequency from Dodd and Deeds method. We have derived the method through mathematical manipulation and verified it by both simulation and experimental data. The permeability error caused by liftoff can be reduced within 7.5%.
Autors: Mingyang Lu;Wenqian Zhu;Liyuan Yin;Anthony J. Peyton;Wuliang Yin;Zhigang Qu;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 167 - 174
Publisher: IEEE
 
» Redundancy Reduction for Prevalent Co-Location Patterns
Abstract:
Spatial co-location pattern mining is an interesting and important task in spatial data mining which discovers the subsets of spatial features frequently observed together in nearby geographic space. However, the traditional framework of mining prevalent co-location patterns produces numerous redundant co-location patterns, which makes it hard for users to understand or apply. To address this issue, in this paper, we study the problem of reducing redundancy in a collection of prevalent co-location patterns by utilizing the spatial distribution information of co-location instances. We first introduce the concept of semantic distance between a co-location pattern and its super-patterns, and then define redundant co-locations by introducing the concept of δ-covered, where is a coverage measure. We develop two algorithms RRclosed and RRnull to perform the redundancy reduction for prevalent co-location patterns. The former adopts the post-mining framework that is commonly used by existing redundancy reduction techniques, while the latter employs the mine-and-reduce framework that pushes redundancy reduction into the co-location mining process. Our performance studies on the synthetic and real-world data sets demonstrate that our method effectively reduces the size of the original collection of closed co-location patterns by about 50 percent. Furthermore, the RRnull method runs much faster than the related closed co-location pattern mining algorithm.
Autors: Lizhen Wang;Xuguang Bao;Lihua Zhou;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Jan 2018, volume: 30, issue:1, pages: 142 - 155
Publisher: IEEE
 
» Reflective Intensity-Demodulated Refractometer Based on S Fiber Taper
Abstract:
A compact optical fiber refractive index (RI) sensor based on a tiny S fiber taper (SFT) cascaded with a fiber Bragg grating (FBG) is proposed and experimentally demonstrated. The SFT can excite and recouple the cladding modes, and hence, it produces modal interference, which is sensitive to surrounding refractive index. Due to the reflection of FBG, RI measurement can be realized by monitoring the peak power change of the reflective FBG spectrum. The experimental result shows that the RI sensitivity of the sensor can be achieved as high as 366.69 dB/RIU ranging from 1.3330 to 1.3988. Moreover, this sensor possesses the temperature-insensitive characteristic. The corresponding RI measurement error is about RIU/°C in the temperature range of 30 °C–70 °C.
Autors: Panpan Niu;Junfa Zhao;Cheng Zhang;Hua Bai;Xiaodong Sun;Jinjun Bai;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:1, pages: 55 - 58
Publisher: IEEE
 
» Relative Geometric Refinement of Patch Images Without Use of Ground Control Points for the Geostationary Optical Satellite GaoFen4
Abstract:
Patch imaging is an important capability of GaoFen4, which is the first Chinese high-resolution planar array satellite in geosynchronous orbit. When the satellite collects images in the patch-imaging mode, overlapping images can be successively obtained. As these images are captured at different times and from a very high orbit, the initial geometric accuracy of the overlapping area between images is inconsistent, which directly affects image mosaicking. In this paper, a novel bundle block adjustment method based on the rational function model without ground control points (GCPs) is proposed to eliminate the relative geometric error among the images and to generate refined rational polynomial coefficients (RPCs). In this method, the average elevation is used instead of the true elevation of the ground points to solve the problem of weak convergence of corresponding bundles, which would result in unstable calculation in the height direction. Virtual control points (VCPs) generated from the original RPCs are used to restrain the freedom of the entire block in the horizontal direction, thereby ensuring stable calculation without the use of GCPs. A successive RPC regeneration method based on VCPs is also presented. To verify the effectiveness of the proposed method, four experiments were performed using real data to assess the geometric accuracy of the method, and the satisfactory experimental results indicate that the presented method is both practical and effective.
Autors: Bo Yang;Yingdong Pi;Xin Li;Mi Wang;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 474 - 484
Publisher: IEEE
 
» Reliability in Super- and Near-Threshold Computing: A Unified Model of RTN, BTI, and PV
Abstract:
Near-threshold computing (NTC) poses stringent constraints on designing reliable circuits, as degradations have a magnified impact at lower supply voltages () compared with super-threshold supply voltages. While phenomena, such as bias temperature instability (BTI) scale down with , mitigate their magnified impact with reduced degradations and, thus, have little impact on NTC reliability. Process variation (PV) and random telegraph noise (RTN) do not scale with and, therefore, become key reliability challenges in NTC. On the other hand, in super-threshold computing (STC), PV and BTI are the dominant phenomena, as BTI induces considerable degradations at nominal and PV imposes large enough shifts to matter at any supply voltage. Therefore, to allow -scaling from super-to near-threshold, we need to consider all of BTI, RTN, and PV. Ergo, we present a unified RTN and BTI model that models their shared physical origin and is validated against experimental data across a wide voltage range. Our unified model and PV model capture the joint impact of RTN, BTI, and PV within a probabilistic reliability estimation for NTC and STC circuits. We employed our proposed model to analyze the reliability of SRAM cells showing how taking error correction codes into account is able to mitigate the deleterious effects of BTI, RTN, and PV by 36% compared with unprotected circuits.
Autors: Victor M. van Santen;Javier Martin-Martinez;Hussam Amrouch;Montserrat Maqueda Nafria;Jörg Henkel;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 293 - 306
Publisher: IEEE
 
» Reliability of Power System with High Wind Penetration Under Frequency Stability Constraint
Abstract:
This paper presents a new method to evaluate the reliability of a power system with high penetration of wind generation, considering the impact of not only the intermittence but also the low inertia characteristic of wind power. As wind generation gradually replaces conventional generation, the system stability and the reliability are negatively affected. Some of the measures employed to deal with the challenges resulting from increasing wind penetration include operating wind generators at lower levels than their available output and providing inertia so that wind generation is able to contribute to system frequency regulation. Apart from these measures, another factor that limits the amount of wind power that can be absorbed into the grid is the imposition of the frequency standard and this also affects the reliability of the system in the presence of wind penetration. The reliability evaluation approach proposed in this paper is developed using discrete convolution and implemented on an IEEE RTS-79 system with a suitable modification. Power system reliability with and without considering the impacts of wind intermittence and low inertia are compared to show the effectiveness of the proposed method.
Autors: Nga Nguyen;Joydeep Mitra;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 985 - 994
Publisher: IEEE
 
» Reliability Worth Analysis of Distribution Systems Using Cascade Correlation Neural Networks
Abstract:
Reliability worth analysis is of great importance in the area of distribution network planning and operation. The reliability worth's precision can be affected greatly by the customer interruption cost model used. The choice of the cost models can change system and load point reliability indices. In this study, a cascade correlation neural network is adopted to further develop two cost models comprising a probabilistic distribution model and an average or aggregate model. A contingency-based analytical technique is adopted to conduct the reliability worth analysis. Furthermore, the possible effects of adding distributed generation units into the network are evaluated. The proposed approach has been tested on a radial distribution test network evaluating the reliability worth. The results show that the probabilistic distribution model provides a more realistic model for the reliability analysis.
Autors: Alireza Heidari;Vassilios G. Agelidis;Josep Pou;Jamshid Aghaei;Amer M. Y. M. Ghias;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 412 - 420
Publisher: IEEE
 
» Reliability-Aware Runtime Adaption Through a Statically Generated Task Schedule
Abstract:
Device scaling, increasing number of components in a single chip, varying environmental issues, and aging effects have brought severe reliability challenges that impose tight constraints on the operation of a system. To cope with these challenges, this paper proposes a reliability-aware scheduling framework that combines static and dynamic analyses to improve the overall system resiliency to different kinds of faults (i.e., intermittent, transient, and permanent). The static analysis technique employs genetic algorithms to optimize the overall system reliability by considering reliability level (RL) as an intermediate scheduling dimension and creating a task-to-RL mapping. This enables the RL-to-core mapping to be efficiently adapted at runtime according to fault rate variations, while the task-to-RL mapping can still be reused. The dynamic analysis tracks faults appearing in each core and measures the time correlation of those faults to update the RL-to-core mapping. The proposed reliability-aware framework is implemented in a state-of-the-art runtime system, Delaware Adaptive Run-Time System, so as to quantitatively show the advantages of using the overall framework in existing multicore platforms. Experimental results show that the proposed technique delivers up to 30% improvement in application execution time and up to 72% improvement in faults occurring at runtime.
Autors: Laura Rozo;Aaron Myles Landwehr;Yan Zheng;Chengmo Yang;Guang Gao;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 11 - 22
Publisher: IEEE
 
» Reliable Safety Message Dissemination in NLOS Intersections Using TV White Spectrum
Abstract:
Reliable safety message dissemination is a fundamental primitive for constructing intersection safety systems. Normally, the dissemination is based on vehicular communications, of which the de-facto standard is Dedicated Short Range Communications (DSRC). However, due to high frequency operations, a DSRC signal is seriously attenuated when being propagated in Non Line-Of-Sight (NLOS) conditions. Previous schemes leveraged the use of centralized infrastructures or relay vehicles enabling a safety message to bypass large obstacles. However, implementing the infrastructures in all intersections would be very costly; one may not find proper relay vehicles in low density, and frequent rebroadcasts cause serious network congestion in high density. To address this challenge, we propose a novel scheme that exploits excellent propagation characteristics of a TV White Space (TVWS) band (in addition to a DSRC band) for reliable dissemination in NLOS intersections. To ensure reliable dissemination throughout a broad range of densities without infrastructures, our scheme employs two innovative mechanisms: a collaborative procedure and a Dynamic optimal Configuration (DoC). To our knowledge, this is the first that simultaneously satisfies two vital demands for intersection safety system: 1) lacking infrastructures and 2) working well in all densities. Simulation studies show that the proposed scheme outperforms previous infrastructure-based schemes.
Autors: Jae-Han Lim;Katsuhiro Naito;Ji-Hoon Yun;Mario Gerla;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 169 - 182
Publisher: IEEE
 
» Remembering Claude Shannon [Essay]
Abstract:
Presents a tribute to Claude Shannon. The IEEE Information Theory Society launched a global initiative to commemorate Claude Shannon’s centenary in 2016. This was part of an IEEE effort to pay due tribute to accomplished names whose venerable contributions have shaped our profession. Practically speaking, the world we live in today owes a lot to Shannon. Shannon greatly influenced technology and digital communications in such a way that has rightfully earned him the nickname, the “father of the Information Age.” This man gave the world machine learning and information theory. His work paved the way for the creation of the knowledge-intensive societies we live in today. He put together the fundamental theoretical basis for how we communicate, store, secure, analyze, and measure information in the digital world.
Autors: Michael P. Salem;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 7 - 8
Publisher: IEEE
 
» Removal of Co-Frequency Powerline Harmonics From Multichannel Surface NMR Data
Abstract:
Powerline harmonics are often the primary noise source in surface nuclear magnetic resonance (NMR) measurements. State-of-the-art techniques, such as notch filtering, Wiener filtering, and model-based subtraction, have been demonstrated to greatly mitigate powerline harmonic noise, but these approaches break down when one of the powerline harmonics has a frequency close to or coincident with the Larmor frequency , referred to as a co-frequency harmonic. We propose a hybrid scheme where model-based subtraction of powerline harmonics is coupled with data from a synchronous reference coil to specifically subtract the co-frequency harmonic component. In standard model-based subtraction of powerline harmonics, a sinusoidal model of all harmonic components is fit to the data and subtracted. In the new approach, the amplitude and phase of the co-frequency harmonic are determined by a sinusoidal model fit to the synchronous noise-only data recorded in a reference coil. From the reference coil co-frequency model, the co-frequency harmonic in the primary coil is estimated using relationships between the amplitude and phase of the co-frequency harmonic in the two coils established during noise-only segments. By utilizing data from the reference coil to model the co-frequency harmonic, accidental fitting of the surface NMR signal is avoided. We investigate the efficiency of the method using a synthetic surface NMR signal embedded in noise-only data recorded in Denmark. Our results demonstrate that the co-frequency powerline harmonic can be removed efficiently without distorting the surface NMR signal and the new method performs better than standard methods.
Autors: Lichao Liu;Denys Grombacher;Esben Auken;Jakob Juul Larsen;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 53 - 57
Publisher: IEEE
 
» Representation of Storage Operations in Network-Constrained Optimization Models for Medium- and Long-Term Operation
Abstract:
This paper proposes a model to carry out analysis of storage facilities operation including a transmission network. The model represents a short-term storage operation in an approximated way that reduces computational requirements, which makes it suitable for medium- and long-term operational planning in power systems with a high level of renewable energy penetration. In the proposed model, we cluster hourly data using the so-called system-states framework developed in previous work. Within this framework, nonconsecutive similar time periods are grouped, while chronological information is represented by a transition matrix among states. We extend the system-state framework from a single-bus system to a transmission network. We define and analyze two alternative sets of representative variables for clustering hours to obtain system states when the transmission network is considered. This extension of the system states framework allows us to evaluate the impact of transmission congestions in medium- and long-term planning models in a reasonable computation time. A case study shows that the proposed model is 235 times faster than an hourly approach, used as benchmark, whereas the overall system cost is approximated with less than 2% error. The overall charging/discharging trends are similar enough to those of the hourly model, being hydro storage better approximated than fast-ramping batteries. Besides, for the analyzed case study, it is shown how congestion in the transmission network in fact improves the accuracy of the proposed approach.
Autors: Diego A. Tejada-Arango;Sonja Wogrin;Efraim Centeno;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 386 - 396
Publisher: IEEE
 
» Research on Homogeneous Multilayer DBD Driven by Submicrosecond Pulsed Power at Atmospheric Pressure Air
Abstract:
Multilayer dielectric barrier discharge (DBD) can efficiently enlarge the volume of homogeneous plasma and its interactional surface area with materials in vertical space, which seems attractive to the industry application. In this paper, a new plasma generator of DBD structure which has multilayers of dielectric barrier boards excited by repetitive submicrosecond pulsed power (0 to −100 kV, 130 Hz–1 kHz, pulsewidth 230 ns, and rise time 120 ns) is introduced, and homogeneous plasma has been obtained in atmospheric pressure air. Experiments on high-speed photography with an exposure time of 5 ns have been carried out to the discharge with three layers of dielectric barrier boards with each gap width of 2 mm. It demonstrates that luminance of the discharge distributes uniformly throughout the upper and the lower gaps. Also, the result of the time evolution image of a three-layer DBD is discussed in this paper, which shows that the two layers of luminous intensity keep good consistency with each other, and this indicates that breakdown of each gap layer happens at the same time in a multilayer DBD. A preliminary processing experiment for polytetrafluoroethylene film has been carried out by adopting homogeneous triple-layer DBD plasma. By testing the water contact angle of the polymer surface before and after the treatment, it was found that hydrophilism of the surface and efficiency of treatment could be effectively improved by the processing of each layer of discharge plasma.
Autors: Jie Li;Xi Li;Pan Dong;Yutong Xie;Jidong Long;Linwen Zhang;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Jan 2018, volume: 46, issue:1, pages: 2 - 7
Publisher: IEEE
 
» Reserve Policy Optimization for Scheduling Wind Energy and Reserve
Abstract:
The rapid increase in the integration of renewable resources has given rise to challenges in power system operations. Due to the uncertainty and variability of renewable generation, additional reserves may be needed to maintain reliability. Uncertainty complicates the process of economic dispatch and renders the deterministic optimization approach less effective. Existing optimization solutions for handling uncertainty, such as scenario-based stochastic programming and robust programming, are also computationally expensive, especially when there are multiple wind farms. Such approaches are less practical for large-scale systems during real-time operations. This paper investigates offline stochastic algorithms to train deterministic operational policies. Such policies are then added to real-time operational models. Specifically, an offline policy generation technique is proposed to provide a stochastic reserve margin to hedge against the real-time uncertainty of (multiple) wind farm generation. The proposed policy generation structure uses a forecast-based framework that accounts for wind generation and system loading conditions. The proposed approach is tested on the Reliability Test System 1996. The proposed approach is compared against existing reserve rules to demonstrate the improvement in handling uncertainty and achieving a more secure solution.
Autors: Mojgan Hedayati-Mehdiabadi;Kory W. Hedman;Junshan Zhang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 19 - 31
Publisher: IEEE
 
» Resistive Switching Device Technology Based on Silicon Oxide for Improved ON–OFF Ratio—Part I: Memory Devices
Abstract:
Resistive switching memory (RRAM) is among the most mature technologies for next generation storage class memory with low power, high density, and improved performance. The biggest challenge toward industrialization of RRAM is the large variability and noise issues, causing distribution broadening which affects retention even at room temperature. Noise and variability can be addressed by enlarging the resistance window between low-resistance state and high-resistance state, which requires a proper engineering of device materials and electrodes. This paper presents an RRAM device technology based on silicon oxide (SiOx), showing high resistance window thanks to the high bandgap in the silicon oxide. Endurance, retention, and variability show excellent performance, thus supporting SiOx as a strong active material for developing future generation RRAMs.
Autors: Alessandro Bricalli;Elia Ambrosi;Mario Laudato;Marcos Maestro;Rosana Rodriguez;Daniele Ielmini;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 115 - 121
Publisher: IEEE
 
» Resource Optimization Across the Cloud Stack
Abstract:
Previous work on optimizing resource provisioning in virtualized environments focused either on mapping virtual machines (VMs) to physical machines (PMs) or mapping application components to VMs. In this paper, we argue that these two optimization problems influence each other significantly and in a highly non-trivial way. We define a sophisticated problem formulation for the joint optimization of the two mappings, taking into account sizing aspects, colocation constraints, license costs, and hardware affinity relations. As demonstrated by the empirical evaluation on a real-world workload trace, the combined optimization leads to significantly better overall results than considering the two problems in isolation.
Autors: Zoltán Ádám Mann;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Jan 2018, volume: 29, issue:1, pages: 169 - 182
Publisher: IEEE
 
» RETRIEVAL—An Online Performance Evaluation Tool for Information Retrieval Methods
Abstract:
Performance evaluation is one of the main research topics in information retrieval. Evaluation metrics are used to quantify various performance aspects of a retrieval method. These metrics assist in identifying the optimum method for a specific retrieval challenge but also to allow its parameters fine-tuning in order to achieve a robust operation for a given set of requirements specification. In this work, we present RETRIEVAL, a Web-based integrated information retrieval performance evaluation platform. It offers a number of metrics that are popular within the scientific community, so as to compose an efficient framework for implementing performance evaluation. We discuss the functionality of RETRIEVAL by citing important aspects such as the data input approaches, the user-level performance metrics parameterization, the evaluation scenarios, the interactive plots, and the performance reports repository that offers both archiving and download functionalities.
Autors: George Ioannakis;Anestis Koutsoudis;Ioannis Pratikakis;Christodoulos Chamzas;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 119 - 127
Publisher: IEEE
 
» Reversible Data Hiding in Encrypted Three-Dimensional Mesh Models
Abstract:
Reversible data hiding in encrypted domain (RDH-ED) has greatly attracted researchers as the original content can be losslessly reconstructed after the embedded data are extracted, while the content owner's privacy remains protected. Most of the existing RDH-ED algorithms are designed for grayscale/color images, which cannot be directly applied to other carriers, such as three-dimensional (3D) meshes. With the rapid development of 3D related applications, 3D models have been widely used on the Internet, which motivated us to design a reliable RDH-ED scheme for 3D meshes. The proposed method maps decimals of the vertex coordinates into integers first, so that a bit-stream encryption technique can be executed. With a data-hiding key, several least-significant bits are operated to embed data. By using the encryption key, a receiver can roughly reconstruct the content of the mesh. According to the data-hiding key, with the aid of spatial correlation in natural mesh models, the embedded data can be successfully extracted and the original mesh can be perfectly recovered. Experiments show that the proposed method has a high data-embedding payload, maintains high values of the decrypted meshes, and has low computational complexity.
Autors: Ruiqi Jiang;Hang Zhou;Weiming Zhang;Nenghai Yu;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 55 - 67
Publisher: IEEE
 
» Reviewers and Editors Appreciation 2017
Abstract:

On behalf of the Editorial Board, I would like to thank all our reviewers for their effort and dedication. As has already become customary, at the beginning of each year we recognize reviewers for their sustained and outstanding review contributions. The list of 2017 exemplary reviewers is provided below. We have a record of 145 exemplary reviewers.
Autors: Octavia A. Dobre;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 3 - 4
Publisher: IEEE
 
» Revised Test for Stochastic Diagnosability of Discrete-Event Systems
Abstract:
This paper provides revisions to the algorithms presented by Chen et al., 2013 for testing diagnosability of stochastic discrete-event systems. Additional new contributions include PSPACE-hardness of verifying strong stochastic diagnosability (referred as A-Diagnosability in Thorsley et al., 2005) and a necessary and sufficient condition for testing stochastic diagnosability (referred as AA-Diagnosability in Thorsley et al., 2005) that involves a new notion of probabilistic equivalence.

Note to Practitioners—Detecting system failures is essential prior to fault mitigation. For stochastic discrete-event systems, the property of stochastic diagnosability (S-Diagnosability) allows one to detect any system failure with arbitrarily small error bound and within bounded delay. This paper contributes by revising and extending the results in the previous work by Chen et al., 2013, regarding the verification of S-Diagnosability.

Autors: Jun Chen;Christoforos Keroglou;Christoforos N. Hadjicostis;Ratnesh Kumar;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 404 - 408
Publisher: IEEE
 
» Revisiting Stress Majorization as a Unified Framework for Interactive Constrained Graph Visualization
Abstract:
We present an improved stress majorization method that incorporates various constraints, including directional constraints without the necessity of solving a constraint optimization problem. This is achieved by reformulating the stress function to impose constraints on both the edge vectors and lengths instead of just on the edge lengths (node distances). This is a unified framework for both constrained and unconstrained graph visualizations, where we can model most existing layout constraints, as well as develop new ones such as the star shapes and cluster separation constraints within stress majorization. This improvement also allows us to parallelize computation with an efficient GPU conjugant gradient solver, which yields fast and stable solutions, even for large graphs. As a result, we allow the constraint-based exploration of large graphs with 10K nodes — an approach which previous methods cannot support.
Autors: Yunhai Wang;Yanyan Wang;Yinqi Sun;Lifeng Zhu;Kecheng Lu;Chi-Wing Fu;Michael Sedlmair;Oliver Deussen;Baoquan Chen;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 489 - 499
Publisher: IEEE
 
» Rewarding Work in IEEE IAS [Pathways]
Abstract:
Reports on the rewarding experiences of joining the IAS Society.
Autors: David Eng;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 116 - 117
Publisher: IEEE
 
» RF Characterization of an Integrated Microwave Photonic Circuit for Self-Interference Cancellation
Abstract:
We perform a full radio frequency (RF) characterization of the first integrated microwave photonic interference canceller. The photonic integrated circuit is one of the first to possess only RF inputs and outputs, with monolithically integrated optical sources and detectors. The characterization is important to developing an in-depth understanding of the integrated circuit’s effect on RF receivers. We characterize the circuit’s gain, noise figure, input intercept point, 1-dB compression point, and spurious-free dynamic range as functions of on-chip device bias points and frequency up to 6 GHz. We find that the circuit’s RF properties are almost exclusively determined by the directly modulated laser. Link gain is primarily driven by the laser slope efficiency. The noise figure is dominated by signal attenuation and laser relative intensity noise. The circuit nonlinearity is the third-order intermodulation product limited. With the exception of link gain, all properties improved with increasing laser bias, saturating at 30 mA. Meanwhile, all properties degraded with increasing frequency. External optical feedback from the reflections off of waveguide transitions in the monolithic circuit created operating points of high noise figure and low gain, and should be avoided during operation. The circuit can be improved by implementing a balanced link architecture to suppress the laser relative intensity noise and using external modulators to improve the link linearity and bandwidth.
Autors: Matthew P. Chang;Eric C. Blow;Monica Z. Lu;Jingyi Jenny Sun;Paul R. Prucnal;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 596 - 605
Publisher: IEEE
 
» RF Circuit Implementation of a Real-Time Frequency Spread Emulator
Abstract:
Despite their reliability, on-site measurements are time-consuming and costly actions for the evaluation of new devices. Channel emulators are widely utilized measurement instruments to generate desired environmental channel effects in laboratory environments. Within these instruments, baseband emulators are expensive, and reverberation chambers provide limited control of the channel. However, radio-frequency (RF) circuit implementation of channel emulators provides an affordable and easy tool to test performances of new systems and methods under different channel effects. In this paper, a new RF domain Doppler emulator, which is compact and easy to control, is presented for measuring signal characteristics under frequency dispersive channel conditions. The circuit has been implemented using variable attenuators, switches, and power splitters to emulate the Doppler spread of air-ground channels, and the performance is evaluated through measurements. It is observed that the emulator indeed generates the desired Doppler model close enough to replicate environmental channels for mobile applications in laboratory environments.
Autors: Murat Karabacak;Ahmed Hossam Mohammed;Mehmet Kemal Özdemir;Hüseyin Arslan;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 241 - 243
Publisher: IEEE
 
» RF Shimming and Improved SAR Safety for MRI at 7 T With Combined Eight-Element Stepped Impedance Resonators and Traveling-Wave Antenna
Abstract:
A remote transmission and detection for magnetic resonance imaging (MRI) at 7 T was validated by using a patch antenna that excites the traveling-wave (TW) modes guided by the radio frequency (RF) shield of the MRI system. In this paper, RF simulations were performed at 298 MHz for an eight-element stepped impedance resonators (SIRs) head volume coil combined with a patch antenna. The combined structure is loaded with both a cylindrical phantom and the Duke full-body human voxel model. An optimization routine was developed in MATLAB to provide homogenous field distributions with minimal 10 g averaged specific absorption rate (SAR) values within the phantom and the Duke human biological model. Before optimization, the TW approach achieved a more homogenous field distribution providing a large field of view along the propagation direction compared to the SIRs head volume coil. However, the corresponding peak local SAR values for the TW approach is about 2.4 times higher than those of the SIRs head volume coil. The transmission efficiency for the TW approach is higher than that of the SIRs head volume coil by 10–30% due to the coupling of the TW modes into the volume coil. The RF-shimming technique improves the field homogeneity for the combined approach by 42%, 48%, and 47% in the central axial, sagittal, and coronal slices, respectively, and satisfies the constraints of maximum local SAR in the human head for MRI at 7 T.
Autors: Ibrahim A. Elabyad;Tim Herrmann;Christian Bruns;Johannes Bernarding;Daniel Erni;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 540 - 555
Publisher: IEEE
 
» RF-Only Logic: an Area Efficient Logic Family for RF-Power Harvesting Applications
Abstract:
Reducing circuit design cost and eliminating over-design margin are the two challenges for advancing the Internet of Things (IoT). An RF-dc rectifier and storage capacitors consume 25% or more of the chip area for cost-sensitive power-harvesting-enabled IoT applications. In this paper, we explore a new circuit structure called RF-only logic that permits logic circuits to operate directly from an un-rectified RF source. By eliminating the need for RF-dc rectifier and storage capacitors, RF-only logic helps to reduce cost and design complexity for power-harvesting-enabled applications. The structure and operations of RF-only logic are presented. Its performance, power consumption, and robustness are analyzed through simulation and validated with measurement results. A standard cell library was developed for RF-only logic, and an algorithm was implemented to further improve area efficiency. A ring oscillator and two multipliers were fabricated in 0.13- CMOS as test structures. The ring oscillator was functionally measured with an RF supply voltage down to 100-mVrms at 1 GHz. The multipliers demonstrate performance improvement and overall area overhead of 16% by implementing the power-supply transistor sharing algorithm.
Autors: Wenxu Zhao;Peter Gadfort;Kirti Bhanushali;Paul D. Franzon;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 406 - 418
Publisher: IEEE
 
» Riccati-Based Design of Event-Triggered Controllers for Linear Systems With Delays
Abstract:
In event-triggered control (ETC) systems, the measured state or output of the plant is sent to the controller at so-called event times. In many ETC systems, these event times are generated based on a static function of the current state or output measurement of the system and its sampled-and-held version that is available to the controller. Hence, the event-generator does not include any dynamics of its own. In contrast, dynamic event-generators trigger events based on additional dynamic variables, whose dynamics depend on the state or output of the system. In this paper, we propose new static and dynamic continuous event-generators (which require continuous measuring of the plant output) and periodic event-generators (which only require periodic sampling of the plant output) for linear control systems with communication delays. All event-generators we propose lead to closed-loop systems which are globally exponentially stable with a guaranteed decay rate, -stable with a guaranteed -gain, and have a guaranteed positive minimum inter-event time. By using new Riccati-based analysis tools tailored to linear systems, the conservatism in our decay rate and -gain estimates is small. The dynamic event-generators even further reduce this conservatism, and as a result typically generate significantly fewer events than their static counterparts, while guaranteeing the same control performance. The benefits of these new event-generators are demonstrated via two numerical examples.
Autors: Dominicus Paulus Borgers;Victor Sebastiaan Dolk;W. P. M. H. Heemels;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 174 - 188
Publisher: IEEE
 
» RNN Models for Dynamic Matrix Inversion: A Control-Theoretical Perspective
Abstract:
In this paper, the existing recurrent neural network (RNN) models for solving zero-finding (e.g., matrix inversion) with time-varying parameters are revisited from the perspective of control and unified into a control-theoretical framework. Then, limitations on the activated functions of existing RNN models are pointed out and remedied with the aid of control-theoretical techniques. In addition, gradient-based RNNs, as the classical method for zero-finding, have been remolded to solve dynamic problems in manners free of errors and matrix inversions. Finally, computer simulations are conducted and analyzed to illustrate the efficacy and superiority of the modified RNN models designed from the perspective of control. The main contribution of this paper lies in the removal of the convex restriction and the elimination of the matrix inversion in existing RNN models for the dynamic matrix inversion. This work provides a systematic approach on exploiting control techniques to design RNN models for robustly and accurately solving algebraic equations.
Autors: Long Jin;Shuai Li;Bin Hu;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 189 - 199
Publisher: IEEE
 
» Road Grade Estimation With Vehicle-Based Inertial Measurement Unit and Orientation Filter
Abstract:
The information of the road grade is an important input for advanced driver assistance systems to improve the vehicle ride comfort, safety, and fuel consumption. Current approaches for road grade estimation in the literature have various disadvantages, e.g., they lack in resolution and sample rate or use data from a lot of sensors, often not from series production. This paper presents methods, which are based on filters that combine the measurements from an inexpensive gyroscope, accelerometer, and magnetometer to estimate the orientation of the sensor relative to the earth’s surface. The methods are evaluated using high-resolution road grade data as reference, which were acquired with an aircraft and the light detection and ranging technique. The road grade information, calculated in the vehicle in real-time, could be transmitted to a central database and merged with information of other vehicles. Therefore, digital maps for advanced driver assistance systems could be kept updated in very short intervals with high-resolution road grade information.
Autors: Jens Jauch;Johannes Masino;Tim Staiger;Frank Gauterin;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 781 - 789
Publisher: IEEE
 
» Robust and Low-Complexity Timing Synchronization for DCO-OFDM LiFi Systems
Abstract:
Light fidelity (LiFi), using light emitting devices such as light emitting diodes (LEDs) which are operating in the visible light spectrum between 400 and 800 THz, provides a new layer of wireless connectivity within existing heterogeneous radio frequency wireless networks. Link data rates of 10 Gbps from a single transmitter have been demonstrated under ideal laboratory conditions. Synchronization is one of these issues usually assumed to be ideal. However, in a practical deployment, this is no longer a valid assumption. Therefore, we propose for the first time a low-complexity maximum likelihood-based timing synchronization process that includes frame detection and sampling clock synchronization for direct current-biased optical orthogonal frequency division multiplexing LiFi systems. The proposed timing synchronization structure can reduce the high-complexity two-dimensional search to two low-complexity one-dimensional searches for frame detection and sampling clock synchronization. By employing a single training block, frame detection can be realized, and then sampling clock offset (SCO) and channels can be estimated jointly. We propose three frame detection approaches, which are robust against the combined effects of both SCO and the low-pass characteristic of LEDs. Furthermore, we derive the Cramér–Rao lower bounds (CRBs) of SCO and channel estimations, respectively. In order to minimize the CRBs and improve synchronization performance, a single training block is designed based on the optimization of training sequences, the selection of training length, and the selection of direct current (DC) bias. Therefore, the designed training block allows us to analyze the trade-offs between estimation accuracy, spectral efficiency, energy efficiency, and complexity. The proposed timing synchronization mechanism demonstrates low complexity and robustness benefits and provides performance significantly better than achieved with exist- ng methods.
Autors: Yufei Jiang;Yunlu Wang;Pan Cao;Majid Safari;John Thompson;Harald Haas;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 53 - 65
Publisher: IEEE
 
» Robust Attitude Estimation from Uncertain Observations of Inertial Sensors Using Covariance Inflated Multiplicative Extended Kalman Filter
Abstract:
This paper presents an attitude estimation method from uncertain observations of inertial sensors, which is highly robust against different uncertainties. The proposed method of covariance inflated multiplicative extended Kalman filter (CI-MEKF) takes the advantage of non-singularity of covariance in MEKF as well as a novel covariance inflation (CI) approach to fuse inconsistent information. The proposed CI approach compensates the undesired effect of magnetic distortion and body acceleration (as inherent biases of magnetometer and accelerometer sensors data, respectively) on the estimated attitude. Moreover, the CI-MEKF can accurately estimate the gyro bias. A number of simulation scenarios are designed to compare the performance of the proposed method with the state of the art in attitude estimation. The results show the proposed method outperforms the state of the art in terms of estimation accuracy and robustness. Moreover, the proposed CI-MEKF method is shown to be significantly robust against different uncertainties, such as large body acceleration, magnetic distortion, and errors, in the initial condition of the attitude.
Autors: Mostafa Ghobadi;Puneet Singla;Ehsan T. Esfahani;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 209 - 217
Publisher: IEEE
 
» Robust Cooperative Multicarrier Transmission Scheme for Optical Wireless Cellular Networks
Abstract:
Visible light communication (VLC) is a promising technology to achieve high data rates in heterogeneous scenarios. However, VLC strongly depends on the existence of a line-of-sight (LoS) link between transmitter and receiver to guarantee a good data rate performance, which is often a condition that is difficult to satisfy in practice. In this letter, a novel cooperative multicarrier transmission scheme is proposed, where neighboring attocells smartly cooperate to decrease the probability of blockage in the LoS link. This approach is compared to single-cell transmission schemes, obtaining notable gains in both received signal-to-interference-plus-noise ratio and cell data rate when blockage of the LoS link occurs toward the nearest base station.
Autors: Borja Genovés Guzmán;Alexis A. Dowhuszko;Víctor P. Gil Jiménez;Ana I. Pérez-Neira;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:2, pages: 197 - 200
Publisher: IEEE
 
» Robust Coordinated Transmission and Generation Expansion Planning Considering Ramping Requirements and Construction Periods
Abstract:
Two critical issues have arisen in transmission expansion planning with the rapid growth of wind power generation. First, severe power ramping events in daily operation due to the high variability of wind power generation pose great challenges to multi-year planning decision making. Second, the long construction periods of transmission lines may not be able to keep pace with the fast growing uncertainty due to the increasing integration of wind power generation. To address such issues, we propose a comprehensive robust planning model considering different resources, namely, transmission lines, generators, and FACTS devices. Various factors are taken into account, including flexibility requirements, construction period, and cost. We construct the hourly net load ramping uncertainty (HLRU) set to characterize the variation of hourly net load including wind power generation, and the annual net load duration curve uncertainty (LDCU) set for the uncertainty of normal annual net load duration curve. This results in a two-stage robust optimization model with two different types of uncertainty sets, which are decoupled into two different sets of subproblems to make the entire solution process tractable. Numerical simulations with real-world data show that the proposed model and solution method are effective in coordinating different flexible resources and rendering robust expansion planning strategies.
Autors: Jia Li;Zuyi Li;Feng Liu;Hongxing Ye;Xuemin Zhang;Shengwei Mei;Naichao Chang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 268 - 280
Publisher: IEEE
 
» Robust Deadbeat Control of an Induction Motor by Stable MRAS Speed and Stator Estimation
Abstract:
In this paper, a new sensorless deadbeat control method is proposed. In the deadbeat method, the desired voltage is calculated via the model of the induction motor and inverter (prediction model). This voltage impels the motor to track the references of the torque and flux in the next control interval. Robustness is an important issue about the deadbeat method. Two new techniques are used to reach a robust speed-independent sensorless deadbeat method. A speed-independent model is sued for prediction. Therefore, the estimated speed will not be used in the prediction model. It will reduce the drift error problem. Also, a new adaptive predictive method is proposed for simultaneous estimation of the stator resistance and speed. Only direct-axis equation is used in the adaptive method. This will reduce the calculation burden. The new adaptive function is achieved via the Lyapunov technique. The stability of the multiple-input multiple-output system for simultaneous adaptation is analyzed for the gain design problem. Simulation and experimental results in wide range of speed are depicted in order to verify the proposed method.
Autors: S. Alireza Davari;Fengxiang Wang;Ralph M. Kennel;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 200 - 209
Publisher: IEEE
 
» Robust Detection and Visualization of Jet-Stream Core Lines in Atmospheric Flow
Abstract:
Jet-streams, their core lines and their role in atmospheric dynamics have been subject to considerable meteorological research since the first half of the twentieth century. Yet, until today no consistent automated feature detection approach has been proposed to identify jet-stream core lines from 3D wind fields. Such 3D core lines can facilitate meteorological analyses previously not possible. Although jet-stream cores can be manually analyzed by meteorologists in 2D as height ridges in the wind speed field, to the best of our knowledge no automated ridge detection approach has been applied to jet-stream core detection. In this work, we -a team of visualization scientists and meteorologists-propose a method that exploits directional information in the wind field to extract core lines in a robust and numerically less involved manner than traditional 3D ridge detection. For the first time, we apply the extracted 3D core lines to meteorological analysis, considering real-world case studies and demonstrating our method's benefits for weather forecasting and meteorological research.
Autors: Michael Kern;Tim Hewson;Filip Sadlo;Rüdiger Westermann;Marc Rautenhaus;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 893 - 902
Publisher: IEEE
 
» Robust Dispatch of High Wind Power-Penetrated Power Systems Against Transient Instability
Abstract:
High-level wind power integration can dramatically affect a power system's dynamic performance and introduce significant uncertainties to system's operation. This paper proposes a robust dispatch method to optimize the power system's operation state while sustaining its transient stability with highly variable and stochastic wind power generation. The problem is first modeled as an augmented optimal power flow model with uncertain variables and differential-algebraic equations. Then, the stability constraints are converted to approximately-equivalent algebraic equations based on one-machine-infinite-bus equivalence technique and trajectory sensitivity analysis. Next, the uncertain wind power generation is represented by a small number of strategically selected testing scenarios. Finally, a decomposition-based computation strategy is developed to divide the original model into a master problem and a series of slave problems which are solved iteratively. Using industry-grade system dynamic models and simulation software, the proposed method is tested on the New England 39-bus system and Nordic32 system, showing high performance on economic optimality, stability robustness, and computational efficiency.
Autors: Yan Xu;Minghui Yin;Zhao Yang Dong;Rui Zhang;David J. Hill;Yuchen Zhang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 174 - 186
Publisher: IEEE
 
» Robust Ensemble Data Analytics for Incomplete PMU Measurements-Based Power System Stability Assessment
Abstract:
This letter proposes a new ensemble data-analytics model for PMU-based pre-contingency stability assessment (SA) considering incomplete data measurements. The model consists of a minimum number of single classifiers which are, respectively, trained by a strategically selected cluster of PMU measurements. Under any PMU missing scenario, the power grid observability from available PMUs can still be ensured to the maximum extent to maintain the SA accuracy. The proposed method is verified through both theoretical proof and numerical simulations.
Autors: Yuchen Zhang;Yan Xu;Zhao Yang Dong;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1124 - 1126
Publisher: IEEE
 
» Robust Guided Image Filtering Using Nonconvex Potentials
Abstract:
Filtering images using a guidance signal, a process called guided or joint image filtering, has been used in various tasks in computer vision and computational photography, particularly for noise reduction and joint upsampling. This uses an additional guidance signal as a structure prior, and transfers the structure of the guidance signal to an input image, restoring noisy or altered image structure. The main drawbacks of such a data-dependent framework are that it does not consider structural differences between guidance and input images, and that it is not robust to outliers. We propose a novel SD (for static/dynamic) filter to address these problems in a unified framework, and jointly leverage structural information from guidance and input images. Guided image filtering is formulated as a nonconvex optimization problem, which is solved by the majorize-minimization algorithm. The proposed algorithm converges quickly while guaranteeing a local minimum. The SD filter effectively controls the underlying image structure at different scales, and can handle a variety of types of data from different sensors. It is robust to outliers and other artifacts such as gradient reversal and global intensity shift, and has good edge-preserving smoothing properties. We demonstrate the flexibility and effectiveness of the proposed SD filter in a variety of applications, including depth upsampling, scale-space filtering, texture removal, flash/non-flash denoising, and RGB/NIR denoising.
Autors: Bumsub Ham;Minsu Cho;Jean Ponce;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 192 - 207
Publisher: IEEE
 
» Robust Harris Corner Matching Based on the Quasi-Homography Transform and Self-Adaptive Window for Wide-Baseline Stereo Images
Abstract:
Corner feature matching remains a difficult task for wide-baseline images because of viewpoint distortion, surface discontinuities, and partial occlusions. In this paper, we propose a robust Harris corner matching method based on the quasi-homography transform (QHT) and self-adaptive window. Our method is divided into three steps. First, high-quality Harris corners were extracted from stereo images using optimal detecting, and initial matches were simultaneously acquired by integrating complementary affine-invariant features and the scale-invariant feature transform descriptor. Second, the pair of fundamental matrices was estimated based on the initial matches and improved random sample consensus algorithm. Subsequently, the global QHT was produced by duplicate epipolar geometries. Third, conjugate Harris corners were obtained by combining QHT and normalized cross correlation, and the accuracy of the corresponding points was further improved based on self-adaptive least-squares matching (SALSM). Experiments on six groups of wide-baseline images demonstrate the effectiveness of the proposed method, and a comprehensive comparison with the existing corner matching algorithms indicates that our method has notable superiority in terms of accuracy and distribution. The main contribution of this paper is that the proposed global QHT can reduce the search range effectively for candidates, and the proposed SALSM can notably improve the accuracy of the corresponding corners.
Autors: Guobiao Yao;Jian Cui;Kazhong Deng;Li Zhang;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 559 - 574
Publisher: IEEE
 
» Robust Matrix Factorization by Majorization Minimization
Abstract:
-norm based low rank matrix factorization in the presence of missing data and outliers remains a hot topic in computer vision. Due to non-convexity and non-smoothness, all the existing methods either lack scalability or robustness, or have no theoretical guarantee on convergence. In this paper, we apply the Majorization Minimization technique to solve this problem. At each iteration, we upper bound the original function with a strongly convex surrogate. By minimizing the surrogate and updating the iterates accordingly, the objective function has sufficient decrease, which is stronger than just being non-increasing that other methods could offer. As a consequence, without extra assumptions, we prove that any limit point of the iterates is a stationary point of the objective function. In comparison, other methods either do not have such a convergence guarantee or require extra critical assumptions. Extensive experiments on both synthetic and real data sets testify to the effectiveness of our algorithm. The speed of our method is also highly competitive.
Autors: Zhouchen Lin;Chen Xu;Hongbin Zha;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 208 - 220
Publisher: IEEE
 
» Robust Optimization With Worst Case Sensitivity Analysis Applied to Array Synthesis and Antenna Designs
Abstract:
Tolerance analysis studies the impact of tolerances and uncertainties on design performance, which represents a key problem in practical implementation of electromagnetic designs. Building on a worst case error tolerance model, this paper proposes particle swarm optimization (PSO) as an approach of the worst case sensitivity analysis (WCSA). Several methods of WCSA have been compared, such as random search, vertex prediction, genetic algorithm, and PSO. PSO with the absorbing boundary condition is proven to be accurate and efficient by several benchmarks. This paper incorporates WCSA with optimization to offer a method which not only finds the optimized design, but also ensures 100% feasibility of the optimized design under the certain tolerance criteria. Linear and planar array synthesis and resonant antenna geometric design demonstrate that within the maximum tolerance given by the algorithm, the optimum solutions are 100% feasible.
Autors: Botian Zhang;Yahya Rahmat-Samii;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 160 - 171
Publisher: IEEE
 
» Robust Order Scheduling in the Discrete Manufacturing Industry: A Multiobjective Optimization Approach
Abstract:
Order scheduling is of vital importance in discrete manufacturing industries. This paper takes fashion industry as an example and discusses the robust order scheduling problem in the fashion industry. In the fashion industry, order scheduling focuses on the assignment of production orders to appropriate production lines. In reality, before a new order can be put into production, a series of activities known as preproduction events need to be completed. In addition, in real production process, owing to various uncertainties, the daily production quantity of each order is not always as expected. In this paper, by considering the preproduction events and the uncertainties in the daily production quantity, robust order scheduling problems in the fashion industry are investigated with the aid of a multiobjective evolutionary algorithm called nondominated sorting adaptive differential evolution (NSJADE). The experimental results illustrate that it is of paramount importance to consider preproduction events in order scheduling problems in the fashion industry. We also unveil that the existence of the uncertainties in the daily production quantity heavily affects the order scheduling.
Autors: Wei Du;Yang Tang;Sunney Yung Sun Leung; Le Tong;Athanasios V. Vasilakos;Feng Qian;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 253 - 264
Publisher: IEEE
 
» Robust Power System Security Assessment Under Uncertainties Using Bi-Level Optimization
Abstract:
Due to rapid expansions of renewable energy (RE) generations, it becomes more important to assess the feasibility of power system operation under limited controllable resources. Especially, exact evaluation of the system reserve for preserving system security is required under erroneous RE output predictions. This paper proposes a method to evaluate the size of the feasible region of power system operation in control space for the examination of the effective system reserve margin under uncertainties. Predicted RE and demands with their confidence intervals (CIs) are specified to formulate a problem for the evaluation of the size of the worst-case feasible region, where positive size implies feasibility, while negative, infeasibility. The method computes the degree of system security, which is referred to as “Robust Power System Security” in this paper. The problem is formulated as bi-level optimization, which is linearized and transformed into the mixed integer linear programming (MILP) problem. This is a new approach in the treatment of uncertainties. We use DC power flow and linear constrained dynamic economic dispatch problem to demonstrate the effectiveness of the proposed method. The proposed approach is useful in power system planning in analyzing the feasibility of dynamic real-time operation in future circumstance.
Autors: Naoto Yorino;Muhammad Abdillah;Yutaka Sasaki;Yoshifumi Zoka;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 352 - 362
Publisher: IEEE
 
» Robust Self-Calibrating nCPMG Acquisition: Application to Body Diffusion-Weighted Imaging
Abstract:
This paper demonstrates a robust diffusion-weighted single-shot fast spin echo (SS-FSE) sequence in the presence of significant off-resonance, which includes a variable-density acquisition and a self-calibrated reconstruction as improvements. A non-Carr–Purcell–Meiboom–Gill (nCPMG) SS-FSE acquisition stabilizes both the main and parasitic echo families for each echo. This preserves both the in-phase and quadrature components of the magnetization throughout the echo train. However, nCPMG SS-FSE also promotes aliasing of the quadrature component, which complicates reconstruction. A new acquisition and reconstruction approach is presented here, where the field-of-view is effectively doubled, but a partial k-space and variable density sampling is used to improve scan efficiency. The technique is presented in phantom scans to validate SNR and robustness against rapidly varying object phase. In vivo healthy volunteer examples and the clinical cases are demonstrated in abdominal imaging. This new approach provides comparable SNR to previous nCPMG acquisition techniques as well as providing more uniform apparent diffusion coefficient maps in phantom scans. In vivo scans suggest that this method is more robust against motion than previous approaches. The proposed reconstruction is an improvement to the nCPMG sequence as it is auto-calibrating and is justified to accurately treat the signal model for the nCPMG SS-FSE sequence.
Autors: Eric K. Gibbons;Patrick Le Roux;Shreyas S. Vasanawala;John M. Pauly;Adam B. Kerr;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 200 - 209
Publisher: IEEE
 
» Robust Stability Analysis of DC Microgrids With Constant Power Loads
Abstract:
This paper studies stability analysis of dc microgrids with uncertain constant power loads (CPLs). It is well known that CPLs have negative impedance effects, which may cause instability in a dc microgrid. Existing works often study the stability around a given equilibrium based on some nominal values of CPLs. However, in real applications, the equilibrium of a dc microgrid depends on the loading condition that often changes over time. Different from many previous results, this paper develops a framework that can analyze the DC microgrid stability for a given range of CPLs. The problem is formulated as a robust stability problem of a polytopic uncertain linear system. By exploiting the structure of the problem, we derive a set of sufficient conditions that can be efficiently checked by solving convex optimization problems to guarantee locally robust stability. The effectiveness and nonconservativeness of the proposed framework are demonstrated using simulation examples.
Autors: Jianzhe Liu;Wei Zhang;Giorgio Rizzoni;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 851 - 860
Publisher: IEEE
 
» Robust Unmixing of Dynamic Sequences Using Regions of Interest
Abstract:
In dynamic planar imaging, extraction of signals specific to structures is complicated by structures superposition. Due to overlapping, signals extraction with classic regions of interest (ROIs) methods suffers from inaccuracy, as extracted signals are a mixture of targeted signals. Partial volume effect raises the same issue in dynamic tomography. Source separation methods, such as factor analysis of dynamic sequences, have been developed to unmix such data. However, the underlying problem is underdetermined and the model used is not relevant in the whole image. This non-uniqueness issue was overcome by introducing prior knowledge, such as sparsity or smoothness, in the separation model. In practice, these methods are barely used because of the lack of reliability of their results. Previously developed methods aimed to be fully automatic, but efficiency can be improved with additional prior knowledge. Some methods using ROIs knowledge in a straightforward way have been proposed. In this paper, we propose an unmixing method, based on an objective function minimization and integrating these ROIs in a different and robust manner. The objective function promotes consistent solutions regarding ROIs while relaxing the model outside ROIs. In order to reduce user-dependent effects, ROIs are used as soft constraints in a robust way through the use of a distance matrix. Consistency, effectiveness, and robustness to the ROIs selection are demonstrated on a toy example, a highly realistic simulated renography data set and a clinical data set. Performance is compared with the competitive methods.
Autors: Marc Filippi;Michel Desvignes;Eric Moisan;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 306 - 315
Publisher: IEEE
 
» Robustness of Interdependent Power Grids and Communication Networks: A Complex Network Perspective
Abstract:
In this brief, by considering realistic network operational settings, we propose a novel model to investigate the cascading failures in interdependent power grids and communication networks. We perform a critical node analysis on single networks to identify the vital nodes from the perspective of network robustness. Moreover, we assess the robustness of an interdependent system composed of an Internet AS-level network and the IEEE 118 Bus. Our simulation results show that assortative coupling of node destructiveness is more robust for densely coupled networks, whereas disassortative coupling of node robustness and node destructiveness performs better for sparsely coupled cases.
Autors: Zhenhao Chen;Jiajing Wu;Yongxiang Xia;Xi Zhang;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 115 - 119
Publisher: IEEE
 
» Roll Steering of Yaw–Pitch Steered SAR for Reducing Ground–Target Pointing Error
Abstract:
While attitude steering in the yaw and pitch axes effectively minimizes a residual Doppler centroid in spaceborne synthetic aperture radar systems, it can induce a ground–target pointing error due to the steered radar boresight. In other words, the beams after steering may no longer illuminate the desired target. In this letter, a novel method is proposed to compensate for the target error. The roll angle and image start time, the two degrees of freedom that may be modified while maintaining the zero Doppler centroid condition, are utilized as control parameters. By correcting the roll and time, the associated target error can be significantly reduced. Two solutions are proposed in this letter. The first is a numerical accurate solution, and the second is an analytical approximate solution. One of the solutions can be implemented on-board after a tradeoff study is performed between the remaining target error and computational load. Simulation results verify that the target error is considerably reduced while the Doppler centroid is minimized with the proposed methods.
Autors: Sung-Hoon Mok;Hyochoong Bang;Boyeon Koh;Kang-Min Park;Henzeh Leeghim;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 38 - 42
Publisher: IEEE
 
» Rotor Speed-Free Estimation of the Frequency of the Center of Inertia
Abstract:
This letter proposes a formula to estimate the frequency of the center of inertia based exclusively on measures of bus frequencies, obtained, for example, from phasor measurement units, the network admittance matrix, and two parameters of synchronous generators, namely, the inertia constant and the internal reactance. The proposed formula can be utilized online and requires a highly reduced set of measures of bus frequencies. The letter discusses the theoretical background of the proposed expression and tests it with a 1479-bus model of the all-island Irish transmission system.
Autors: Federico Milano;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1153 - 1155
Publisher: IEEE
 
» Safe, Secure Executions at the Network Edge: Coordinating Cloud, Edge, and Fog Computing
Abstract:
System design where cyber-physical applications are securely coordinated from the cloud may simplify the development process. However, all private data are then pushed to these remote “swamps,” and human users lose actual control as compared to when the applications are executed directly on their devices. At the same time, computing at the network edge is still lacking support for such straightforward multidevice development, which is essential for a wide range of dynamic cyber-physical services. This article proposes a novel programming model as well as contributes the associated secure-connectivity framework for leveraging safe coordinated device proximity as an additional degree of freedom between the remote cloud and the safety-critical network edge, especially under uncertain environment constraints. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Autors: Niko Mäkitalo;Aleksandr Ometov;Joona Kannisto;Sergey Andreev;Yevgeni Koucheryavy;Tommi Mikkonen;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 30 - 37
Publisher: IEEE
 
» Safety and Security in Cyber-Physical Systems and Internet-of-Things Systems
Abstract:
Safety and security have traditionally been distinct problems in engineering and computer science. The introduction of computing elements to create cyber-physical systems (CPSs) has opened up a vast new range of potential problems that do not always show up on the radar of traditional engineers. Security, in contrast, is traditionally viewed as a data or communications security problem to be handled by computer scientists and/or computer engineers. Advances in CPSs and the Internet-of-Things (IoT) requires us to take a unified view of safety and security. This paper defines a safety/security threat model for CPSs and IoT systems and surveys emerging techniques which improve the safety and security of CPSs and IoT systems.
Autors: Marilyn Wolf;Dimitrios Serpanos;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 9 - 20
Publisher: IEEE
 
» Saliency-Aware Video Object Segmentation
Abstract:
Video saliency, aiming for estimation of a single dominant object in a sequence, offers strong object-level cues for unsupervised video object segmentation. In this paper, we present a geodesic distance based technique that provides reliable and temporally consistent saliency measurement of superpixels as a prior for pixel-wise labeling. Using undirected intra-frame and inter-frame graphs constructed from spatiotemporal edges or appearance and motion, and a skeleton abstraction step to further enhance saliency estimates, our method formulates the pixel-wise segmentation task as an energy minimization problem on a function that consists of unary terms of global foreground and background models, dynamic location models, and pairwise terms of label smoothness potentials. We perform extensive quantitative and qualitative experiments on benchmark datasets. Our method achieves superior performance in comparison to the current state-of-the-art in terms of accuracy and speed.
Autors: Wenguan Wang;Jianbing Shen;Ruigang Yang;Fatih Porikli;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 20 - 33
Publisher: IEEE
 
» San Diego's streetlights get smart
Abstract:
None of the people walking around San Diego's East Village neighborhood one recent afternoon were looking up at the streetlights (except me). And if they had, they likely wouldn't have noticed that some of these lights were a little thicker around the middle than others, or that some lanterns topping old-style lampposts had a clear glass panel here and there. But unbeknownst to the people below, those streetlights were looking- and listening-all around them, while also monitoring temperature, humidity, and other characteristics of the air.
Autors: Tekla S. Perry;
Appeared in: IEEE Spectrum
Publication date: Jan 2018, volume: 55, issue:1, pages: 30 - 31
Publisher: IEEE
 
» Scalable Content Delivery With Coded Caching in Multi-Antenna Fading Channels
Abstract:
We consider the content delivery problem in a fading multi-input single-output channel with cache-aided users. We are interested in the scalability of the equivalent content delivery rate when the number of users, , is large. Analytical results show that, using coded caching and wireless multicasting, without channel state information at the transmitter, linear scaling of the content delivery rate with respect to can be achieved in some different ways. First, if the multicast transmission spans over independent sub-channels, e.g., in quasi-static fading if , and in block fading or multi-carrier systems if , linear scaling can be obtained, when the product of the number of transmit antennas and the number of sub-channels scales logarithmically with . Second, even with a fixed number of antennas, we can achieve the linear scaling with a threshold-based user selection requiring only one-bit feedbacks from the users. When CSIT is available, we propose a mixed strategy that combines spatial multiplexing and multicasting. Numerical results show that, by optimizing the power split between spatial multiplexing and multicasting, we can achieve a significant gain of the content delivery rate with moderate cache size.
Autors: Khac-Hoang Ngo;Sheng Yang;Mari Kobayashi;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 548 - 562
Publisher: IEEE
 
» Scalable Deadlock-Free Deterministic Minimal-Path Routing Engine for InfiniBand-Based Dragonfly Networks
Abstract:
Dragonfly topologies are gathering great interest nowadays as one of the most promising interconnect options for High-Performance Computing (HPC) systems. However, Dragonflies contain physical cycles that may lead to traffic deadlocks unless the routing algorithm prevents them properly. In general, existing deadlock-free routing algorithms, either deterministic or adaptive, proposed for Dragonflies, use Virtual Channels (VCs) to prevent cyclic dependencies. However, these topology-aware algorithms are difficult to implement, or even unfeasible, in systems based on the InfiniBand (IB) architecture, which is nowadays the most widely used network technology in HPC systems. This is due to some limitations in the IB specification, specifically regarding the way Virtual Lanes (VLs), which are considered as similar to VCs, can be assigned to traffic flows. Indeed, none of the routing engines currently available in the official releases of the IB control software has been specifically proposed for Dragonflies. In this paper, we present a new deterministic, minimal-path routing for Dragonfly that prevents deadlocks using VLs according to the IB specification, so that it can be straightforwardly implemented in IB-based networks. We have called this proposal D3R (Deterministic Deadlock-free Dragonfly Routing). Specifically, D3R maps each route to a single, specific VL depending on the destination group, and according to a specific order, so that cyclic dependencies (so deadlocks) are prevented. D3R is scalable as it requires only 2 VLs to prevent deadlocks regardless of network size, i.e., fewer VLs than the required by the deadlock-free routing engines available in IB that are suitable for Dragonflies. Alternatively, D3R achieves higher throughput if an additional VL is used to reduce internal contention in the Dragonfly groups. We have implemented D3R as a new routing engine in OpenSM, the control software including the subnet manager in IB. We have evaluated D3R by means o- simulation and by experiments performed in a real IB-based cluster, the results showing that, in general, D3R outperforms other routing engines.
Autors: German Maglione-Mathey;Pedro Yebenes;Jesus Escudero-Sahuquillo;Pedro Javier Garcia;Francisco J. Quiles;Eitan Zahavi;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Jan 2018, volume: 29, issue:1, pages: 183 - 197
Publisher: IEEE
 
» Scalable Video Coding Based on User’s View for Real-Time Virtual Reality Applications
Abstract:
The transmission of virtual reality (VR) videos requires huge bandwidth, which brings great challenges for the system to implement real-time applications. This letter proposes a scalable full-panorama video coding method to adapt the insufficient bandwidth, in which user’s movement information is utilized as a feedback from the VR device to the video encoder. The regions that the user is interested in are first mapped and then coded in high quality, while the others in low quality. This different-quality coding is achieved through scalable high efficiency video coding (SHVC), which only makes limited modifications on the SHVC encoder and no modification on the SHVC decoder. In addition, full-panorama coding also avoids the reference problem in inter prediction and relieves the delay-sensitive problem. Experiments results show that our proposed method reduces approximately 87% bit rate with no significant decrease in quality of the region of interest in panorama.
Autors: Gang He;Jing Hu;Hao Jiang;Yunsong Li;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 25 - 28
Publisher: IEEE
 
» Scaling the CBRAM Switching Layer Diameter to 30 nm Improves Cycling Endurance
Abstract:
Control of cation injection into the switching layer of conductive-bridge random access memory (CBRAM) during switching is a critical factor for CBRAM reliability. Although extrinsic approaches such as the insertion of a transistor in series have proven effective, solutions intrinsic to the CBRAM itself, which are desired for high density cross-point or 3-D vertical memory arrays, are quite limited. In this letter, we show the significant improvement of cycling endurance for Cu-based CBRAM by scaling the switching layer area down to 30 nm in diameter. Further study suggests that the injection of excessive Cu ions into the switching layer is suppressed owing to spatial limitation during the formation of the conductive filament. These results indicate that the area scaling of the switching layer is an effective solution for achieving highly reliable CBRAM devices.
Autors: Shosuke Fujii;Jean Anne C. Incorvia;Fang Yuan;Shengjun Qin;Fei Hui;Yuanyuan Shi;Yang Chai;Mario Lanza;H.-S. Philip Wong;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 23 - 26
Publisher: IEEE
 
» Scanning the Issue
Abstract:
An Analytical Model to Characterize the Spatiotemporal Propagation of Information Under Vehicle-to-Vehicle Communications
Autors: Petros Ioannou;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 1 - 2
Publisher: IEEE
 
» Scanning The Issue
Abstract:
This special issue is devoted to the safety and security issues presented by cyber–physical systems (CPSs). CPSs use cyber software/hardware to perform real-time control on physical systems. Such systems are widely used in aerospace and automotive, medical, industrial, and critical infrastructure applications.
Autors: Marilyn Wolf;Dimitrios Serpanos;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 7 - 8
Publisher: IEEE
 
» Scattering by a Dielectric Sphere Buried in a Half-Space With a Slightly Rough Interface
Abstract:
Analytical expressions for the scattering coefficients of a dielectric sphere buried under a rough interface are presented. The proposed method combines the small perturbation method (SPM) and the Mie solution by using the expansion of plane waves in terms of vector spherical functions (VSFs) and vice versa. First, using SPM, the zeroth- and the first-order perturbative scattered fields of a rough interface for illuminations from above and below are derived. Using these solutions, the field transmitted to the lower half-space is determined as a spectrum of down-going plane waves. The scattered fields from the sphere are then calculated using the vector Mie solution. Subsequently, the VSFs are expanded in terms of up-going plane waves. These plane waves illuminate the interface, and using SPM, the scattered fields in the upper and lower regions are determined as infinite summations of plane waves. The reflected plane waves are once again scattered by the sphere and the scenario repeats. By inspecting the form of the fields resulting from the few first interactions of the sphere and the rough interface, a recursive form is obtained for the scattered fields. This recursive form is then used to rewrite the system of equations in a form containing all interactions in a single-step formulation. Accordingly, the zeroth- and the first-order closed-form scattered fields are obtained. The derived expressions are analytically and numerically validated. Finally, the numerical results for the case of the rough interface with sinusoidal profile are presented and briefly discussed.
Autors: Hasan Zamani;Ahad Tavakoli;Mojtaba Dehmollaian;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 347 - 359
Publisher: IEEE
 
» Scattering From 2-D Perfect Electromagnetic Conductor Rough Surface: Analysis With the Small Perturbation Method and the Small-Slope Approximation
Abstract:
We study the scattering of electromagnetic wave from a 2-D random rough surface that separates the vacuum from a perfect electromagnetic conductor (PEMC). We implement the first-order perturbation method and the first-order small-slope approximation and we establish the analytical expressions of the coherent and incoherent intensities. In contrast with the two special cases, the perfect electric conductor and the perfect magnetic conductor, the coherent intensity reflected by the PEMC has a cross-component. We also show that there is a depolarization in the incidence plane and that there are configurations, where the wave depolarization is complete and the incoherent intensity is reduced to its cross-component.
Autors: Saddek Afifi;Richard Dusséaux;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 340 - 346
Publisher: IEEE
 
» Scatterplots: Tasks, Data, and Designs
Abstract:
Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet these larger scales. This breadth of design options creates challenges for designers and practitioners who must select appropriate designs for particular analysis goals. In this paper, we help designers in making design choices for scatterplot visualizations. We survey the literature to catalog scatterplot-specific analysis tasks. We look at how data characteristics influence design decisions. We then survey scatterplot-like designs to understand the range of design options. Building upon these three organizations, we connect data characteristics, analysis tasks, and design choices in order to generate challenges, open questions, and example best practices for the effective design of scatterplots.
Autors: Alper Sarikaya;Michael Gleicher;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 402 - 412
Publisher: IEEE
 
» Scene-Adaptive Off-Road Detection Using a Monocular Camera
Abstract:
This paper studies vision-based road detection for a robot’s path following in off-road environments. We define the problem as detecting the region in front of the robot that is mechanically traversable (i.e., mechanical traversability), that is apt to be chosen by a human to drive through (i.e., human selection), and that extends for a distance to show the road’s direction, shape, or even network of the intersection ahead (i.e., far-field capability). An algorithm framework is designed that contains two parts: inference and learning. In inference, the problem is formulated as a consecutive road type classification and road region segmentation to address the diversity of terrain surfaces. In model learning, the robot is first driven by a human being, with image samples on the track of the robot being collected that meet the prerequisites of both mechanical traversability and human selection. Evaluation measures are defined to examine the three requirements of mechanical traversability, human selection, and far-field capability. The performances of the above aspects are demonstrated on a data set using LiDAR, track and manual references, which will be released together with this publication.
Autors: Jilin Mei;Yufeng Yu;Huijing Zhao;Hongbin Zha;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 242 - 253
Publisher: IEEE
 
» Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data
Abstract:
Molecular dynamics (MD) simulations are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry. Excessive super-sampling can alleviate this problem, but is prohibitively expensive. This paper presents a novel visualization method for large-scale particle data that addresses aliasing while enabling interactive high-quality rendering. We introduce the novel concept of screen-space normal distribution functions (S-NDFs) for particle data. S-NDFs represent the distribution of surface normals that map to a given pixel in screen space, which enables high-quality re-lighting without re-rendering particles. In order to facilitate interactive zooming, we cache S-NDFs in a screen-space mipmap (S-MIP). Together, these two concepts enable interactive, scale-consistent re-lighting and shading changes, as well as zooming, without having to re-sample the particle data. We show how our method facilitates the interactive exploration of real-world large-scale MD simulation data in different scenarios.
Autors: Mohamed Ibrahim;Patrick Wickenhäuser;Peter Rautek;Guido Reina;Markus Hadwiger;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 944 - 953
Publisher: IEEE
 
» SDNFV-Based Dynamic Network Function Deployment: Model and Mechanism
Abstract:
Oriented to the distinctive communication demands of diversified network applications, the current Internet should be able to provide special packet processing operations beyond simple packet forwarding. In this letter, we propose a dynamic network function deployment model based on Software Defined Networking and Network Function Virtualization to control and deploy diverse network functions in corresponding switches, so as to provide special-purpose communication features for different applications. We devise a dynamic network function deployment mechanism, which pre-deploys appropriate functions before they are massively requested according to the prediction, and real-timely deploys a few of new requested functions according to the current network status. The simulation results show that the proposed model is feasible and effective.
Autors: Chao Bu;Xingwei Wang;Min Huang;Keqin Li;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 93 - 96
Publisher: IEEE
 
» Search Result Diversity Evaluation Based on Intent Hierarchies
Abstract:
Search result diversification aims at returning diversified document lists to cover different user intents of a query. Existing diversity measures assume that the intents of a query are disjoint, and do not consider their relationships. In this paper, we introduce intent hierarchies to model the relationships between intents, and present four weighing schemes. Based on intent hierarchies, we propose several hierarchical measures that take into account the relationships between intents. We demonstrate the feasibility of hierarchical measures by using a new test collection based on TREC Web Track 2009-2013 diversity test collections and by using NTCIR-11 IMine test collection. Our main experimental findings are: (1) Hierarchical measures are more discriminative and intuitive than existing measures. In terms of intuitiveness, it is preferable for hierarchical measures to use the whole intent hierarchies than to use only the leaf nodes. (2) The types of intent hierarchies used affect the discriminative power and intuitiveness of hierarchical measures. We suggest the best type of intent hierarchies to be used according to whether the nonuniform weights are available. (3) To measure the benefits of the diversification algorithms which use automatically mined hierarchical intents, it is important to use hierarchical measures instead of existing measures.
Autors: Xiaojie Wang;Ji-Rong Wen;Zhicheng Dou;Tetsuya Sakai;Rui Zhang;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Jan 2018, volume: 30, issue:1, pages: 156 - 169
Publisher: IEEE
 
» Secrecy Outage Analysis Over Correlated Composite Nakagami- $m$ /Gamma Fading Channels
Abstract:
The secrecy systems operating over spatially correlated composite fading channels is analyzed in this letter. We adopt a multiplicative composite channel model for both the legitimate communication link and the link between the eavesdropper and the legitimate transmitter, consisting of Nakagami- distributed small-scale fading and shadowing (large-scale fading) modeled by the Gamma distribution. We consider the realistic case where small-scale fading between the links is independent, but shadowing is arbitrarily correlated, and present novel analytical expressions for the probability that the secrecy capacity falls below a target secrecy rate. The presented numerically evaluated results, verified by equivalent computer simulations, offer useful insights on the impact of the shadowing correlation and composite fading parameters on the system’s secrecy outage performance.
Autors: George C. Alexandropoulos;Kostas P. Peppas;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 77 - 80
Publisher: IEEE
 
» Secure Internet of Things Deployment in the Cement Industry: Guidance for Plant Managers
Abstract:
Always-on Internet-connected devices [the so-called Internet of Things (IoT)] have become common tools deployed throughout the cement industry. As plant managers employ more automation technologies, the implementation of more connected devices can lead to information security and personnel safety concerns. IoT devices provide significant value in cost reduction, increased efficiency, and greater visibility for all aspects of the business. Along with the benefits of the IoT infrastructure, there are significant security concerns and challenges present in the deployment of this new technology. Recent implementations of IoT devices have shown a significant gap between actual application and best practices, exposing an organization to risks such as sensitive data exfiltration, malicious attackers, and potential safety issues (including the loss of life). An awareness of these concerns and challenges provides guidance to plant managers for mitigating the security weaknesses contained within connected devices while still reaping the benefits of the IoT infrastructure.
Autors: Patrick McNeil;
Appeared in: IEEE Industry Applications Magazine
Publication date: Jan 2018, volume: 24, issue:1, pages: 14 - 23
Publisher: IEEE
 
» Secure Spatial Multiple Access Using Directional Modulation
Abstract:
In this paper, we introduce a secure multiple access scheme, which exploits the multipath structure of the channel to create a multi-user interference environment. The generated interference enables legitimate users to share time and frequency resources over spatially secure communication links. Utilizing directional modulation, we ensure secrecy for legitimate users against eavesdropping while preserving mutual confidentiality between the legitimate users themselves. Moreover, we introduce a complementary scheme for covering the non-selective channel case. The scheme uses directional modulation in coordinated multi-point transmission to provide location-specific secure communication to legitimate users. We characterize the achievable performance using a newly defined metric called vulnerable region. We provide analysis for the achievable secrecy rate, secrecy outage probability, and channel correlation effect on the secrecy performance for the proposed scheme. Furthermore, the effect of the channel spatial diversity, channel estimation error, and the number of legitimate users on the secrecy performance is studied.
Autors: Mohammed Hafez;Marwan Yusuf;Tamer Khattab;Tarek Elfouly;Hüseyin Arslan;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 563 - 573
Publisher: IEEE
 
» Security Constrained Unit Commitment Using Line Outage Distribution Factors
Abstract:
Security-constrained unit commitment (SCUC) problem is one of the necessary tools for system operators to make operational planning and real-time operation. The internalization of transmission network and security constraints (e.g., N-1 criterion) could lead to different decisions in the generation dispatch. However, the computational burden of this problem is challenging mainly due to its inherent large problem size. Therefore, this paper proposes an N-1 security constrained formulation based on the line outage distribution factors (LODF) instead of the one based on injection sensitivity factors (ISF). This formulation is at the same time more compact than analogous formulations for contingency constraints; hence, it presents a lower computational burden. The computational efficiency of the proposed formulation is shown by solving the SCUC of the IEEE 118 bus system with LODF and ISF. Additionally, an iterative methodology for filtering the active N-1 congestion constraints is detailed, and its implementation for large-scale systems is described. The results show that the proposed filter reduces the computational time by approximately 70% in comparison to the complete formulation of N-1 constraints in SCUC.
Autors: Diego A. Tejada-Arango;Pedro Sánchez-Martın;Andres Ramos;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 329 - 337
Publisher: IEEE
 
» Security Formalizations and Their Relationships for Encryption and Key Agreement in Information-Theoretic Cryptography
Abstract:
This paper analyzes the formalizations of information-theoretic security for the fundamental primitives in cryptography: symmetric-key encryption and key agreement. Revisiting the previous results, we can formalize information-theoretic security using different methods, by extending Shannon’s perfect secrecy, by information-theoretic analogues of indistinguishability and semantic security, and by the frameworks for composability of protocols. We show the relationships among the security formalizations and obtain the following results. First, in the case of encryption, there are significant gaps among the formalizations, and a certain type of relaxed perfect secrecy or a variant of information-theoretic indistinguishability is the strongest notion. Second, in the case of key agreement, there are significant gaps among the formalizations, and a certain type of relaxed perfect secrecy is the strongest notion. In particular, in both encryption and key agreement, the formalization of composable security is not stronger than any other formalizations. Furthermore, as an application of the relationships in encryption and key agreement, we simultaneously derive a family of lower bounds on the size of secret keys and security quantities required under the above formalizations, which also implies the importance and usefulness of the relationships.
Autors: Mitsugu Iwamoto;Kazuo Ohta;Junji Shikata;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 654 - 685
Publisher: IEEE
 
» Security-Constrained Optimal Scheduling of Transmission Outages With Load Curtailment
Abstract:
Transmission outage scheduling from a transmission facility owner's (TFO's) perspective in a deregulated electricity market has been one of the lesser explored topics in academia. This paper presents a security-constrained one-step optimal transmission outage scheduling model that can be used by any TFO. The proposed mixed-integer linear programming model incorporates a new load shedding methodology that allows transmission branches to radially connected and in-and-out connected buses to be taken out-of-service under outage and contingency conditions, which further improves its versatility. The proposed model is tested on two networks, a simple four-bus system and the 62-bus AltaLink 500 kV/240 kV backbone system in Alberta.
Autors: Jenny Liu;Mostafa Kazemi;Amir Motamedi;Hamidreza Zareipour;Jim Rippon;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 921 - 931
Publisher: IEEE
 
» Semantics-Preserving Cosynthesis of Cyber-Physical Systems
Abstract:
Software-based control of physical systems is common in domains such as automotive, avionics, and industrial automation. Safety of such systems is determined by control-theoretic properties such as stability, settling time, and peak overshoot. These properties strongly depend on the software code generated from high-level controller models, and the implementation of such code on an embedded platform. To ensure safety, the semantics of the system model considered for controller design must be faithfully preserved in the platform implementation. However, traditionally, controller design and implementation platform design are carried out in isolation, followed by their integration, which often relies on simulations to estimate the behavior of the controllers. Thus, safety properties that were proven at the model level using control-theoretic tools can no longer be established in an actual implementation. This makes the design of embedded control systems costly, error prone, and hinders certification. In this paper, we review recent efforts in control-platform cosynthesis techniques toward addressing this problem. Here, the control and the embedded systems communities have come together to adopt a cyber–physical system (CPS)-oriented design paradigm. This cosynthesis paradigm integrates the design of control algorithms and platform parameters within a holistic optimization framework and accounts for relevant details from both sides. We survey the evolution of design approaches for such cosynthesis and show how–the originally disjoint–controller and the platform design methods are gradually converging.
Autors: Debayan Roy;Licong Zhang;Wanli Chang;Sanjoy K. Mitter;Samarjit Chakraborty;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 171 - 200
Publisher: IEEE
 
» Semidefinite Programming Strong Converse Bounds for Classical Capacity
Abstract:
We investigate the classical communication over quantum channels when assisted by no-signaling and positive-partial-transpose-preserving (PPT) codes, for which both the optimal success probability of a given transmission rate and the one-shot -error capacity are formalized as semidefinite programs (SDPs). Based on this, we obtain improved SDP finite blocklength converse bounds of general quantum channels for entanglement-assisted codes and unassisted codes. Furthermore, we derive two SDP strong converse bounds for the classical capacity of general quantum channels: for any code with a rate exceeding either of the two bounds of the channel, the success probability vanishes exponentially fast as the number of channel uses increases. In particular, applying our efficiently computable bounds, we derive an improved upper bound on the classical capacity of the amplitude damping channel. We also establish the strong converse property for the classical and private capacities of a new class of quantum channels. We finally study the zero-error setting and provide efficiently computable upper bounds on the one-shot zero-error capacity of a general quantum channel.
Autors: Xin Wang;Wei Xie;Runyao Duan;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 640 - 653
Publisher: IEEE
 
» Semisupervised Classification of Polarimetric SAR Image via Superpixel Restrained Deep Neural Network
Abstract:
The classification of polarimetric synthetic aperture radar (PolSAR) image is of crucial significance for SAR applications. In this letter, a superpixel restrained deep neural network with multiple decisions (SRDNN-MDs) is proposed for PolSAR image classification, which not only extracts effective superpixel spatial features and degrades the influence of speckle noises but also deals with the limited training samples. First, the polarimetric features of coherency matrix and Yamaguchi decomposition are extracted as initial features, and superpixel segmentation is conducted on the Pauli color-coded image to acquire the superpixel averaged features. Then, an SRDNN based on sparse autoencoders is proposed to capture superpixel correlative features and reduce speckle noises. After that, MDs, including nonlocal decision and local decision, are developed to select credible testing samples. Finally, our deep network is updated by the extended training set to yield the final classification map. Experimental results demonstrate that the proposed SRDNN-MD yields higher accuracies compared with other related approaches, which indicate that the proposed method is able to capture superpixel correlative information and adds the information of unlabeled samples to improve the classification performance.
Autors: Jie Geng;Xiaorui Ma;Jianchao Fan;Hongyu Wang;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 122 - 126
Publisher: IEEE
 
» Sender-Jump Receiver-Wait: A Simple Blind Rendezvous Algorithm for Distributed Cognitive Radio Networks
Abstract:
Cognitive radio (CR) has emerged as an advanced and promising technology to exploit the wireless spectrum opportunistically. In cognitive radio networks (CRNs), any pairwise communicating nodes are required to rendezvous on a commonly available channel prior to exchange information. In the earlier research, the most popular method is selecting a Common Control Channel (CCC) in CRNs to establish the rendezvous. However, employing a CCC has many problems such as the control channel saturation, vulnerability to jamming attacks, and inapplicability to dynamic network scenarios. Therefore, the blind rendezvous, which requires neither CCC nor the information of the target user's available channels, has recently attracted a lot of research interests. As a contribution to this research area, in this paper we propose a Sender-Jump Receiver-Wait (SJ-RW) blind rendezvous algorithm, which has fully satisfied the following requirements: 1) guaranteeing rendezvous; 2) realizing full rendezvous diversity, i.e., any pair of users can rendezvous on all commonly available channels; 3) requiring no time-synchronization; 4) supporting both symmetric and asymmetric models; 5) supporting multi-user/multi-hop scenarios and 6) consuming short Time-to-Rendezvous (TTR). Theoretical analysis, computer simulations and experiment with testbed have validated the proposed SJ-RW algorithm.
Autors: Jiaxun Li;Haitao Zhao;Jibo Wei;Dongtang Ma;Li Zhou;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 183 - 196
Publisher: IEEE
 
» Sensing Characteristic of Arrayed Flexible Indium Gallium Zinc Oxide Lactate Biosensor Modified by GO and Magnetic Beads
Abstract:
In this study, the arrayed flexible indium gallium zinc oxide (IGZO) lactate biosensor was modified by graphene oxide (GO) and magnetic beads (MB). The biosensor has arrayed structure with six sensing windows. The arrayed structure with six IGZO windows was fabricated by using radio frequency sputtering system and screen-printed technology. The lactate enzyme was combined with GO and MB, and which was immobilized on the IGZO windows by the crossing-link method. The GO and MB could enhance the average sensitivity of the lactate biosensor, and the optimal content was also investigated. After that, the lactate biosensor was integrated in the microfluidic device, and the average sensitivity also could be enhanced by controlling the flow rate of test solution. Furthermore, the electrochemical reaction of different sensing films could be described by electrochemical impedance spectroscopy.
Autors: Jung-Chuan Chou;Hsiang-Yi Chen;Yi-Hung Liao;Chih-Hsien Lai;Siao-Jie Yan;Cian-Yi Wu;You-Xiang Wu;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 147 - 153
Publisher: IEEE
 
» Sensitivity Based Thevenin Index With Systematic Inclusion of Reactive Power Limits
Abstract:
This paper presents proof for the relation between the Local Thevenin Index (LTI), measured at a Phasor Measurement Unit (PMU), that is used as an indicator of voltage stability, and the system operating condition. The derivation establishes that there is a direct connection between the sensitivity and the LTI and provides a mathematically rigorous justification to use LTI as a static long-term voltage stability indicator of the entire system. A Sensitivity based Thevenin Index, calculated using wide area measurements, is proposed and it can be used at the control center to authenticate the LTI being received from PMUs, to safeguard against malicious and spurious data. The association between the sensitivity and the LTI can also be used to predict the effect of various what-if scenarios on the LTI. As a demonstration, the impact of generator limits on the LTI is predicted, enabling the operator to anticipate the abrupt change in LTI before the limits are reached. Results are described in detail for a 5-bus system, and verified on larger systems up to 300 buses, establishing the connection between the LTI and the sensitivities, and validating the prediction of impact of the generator reactive limits on the LTI.
Autors: Amarsagar Reddy Ramapuram Matavalam;Venkataramana Ajjarapu;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 932 - 942
Publisher: IEEE
 
» Sensor Integration-Based Approach for Automatic Fork Lift Trucks
Abstract:
In the industrial environment, the flow of materials is a complex and very expensive process. For reducing the expenses, it requires an effort to find favorable and flexible systems. Fork lift trucks are widely used in industries for transfer actions. The complexity of manually operated fork lift trucks shall be reduced by low cost automation. This paper deals with sensor interfaced automatic fork lifter for the effective materials flow. This fork-lift truck will identify the different pallets automatically based upon their surface color by the color sensor interfaced with it. The digital output of the color sensor varies with respect to the wavelength of the color. This output decides the selection or rejection of the pallets for loading as well as unloading anywhere. Line following technique is used for transportation between sections to avoid the complexity of conventional memory mapping technique.
Autors: T. Muthuramalingam;M. Mohamed Rabik;D. Saravanakumar;K. Jaswanth;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 736 - 740
Publisher: IEEE
 
» Sensor-Assisted Multi-View Face Recognition System on Smart Glass
Abstract:
Face recognition is a hot research topic with a variety of application possibilities, including video surveillance and mobile payment. It has been well researched in traditional computer vision community. However, new research issues arise when it comes to resource constrained devices, such as smart glasses, due to the overwhelming computation and energy requirements of the accurate face recognition methods. In this paper, we propose a robust and efficient sensor-assisted face recognition system on smart glasses by exploring the power of multimodal sensors including the camera and Inertial Measurement Unit (IMU) sensors. The system is based on a novel face recognition algorithm, namely Multi-view Sparse Representation Classification (MVSRC), by exploiting the prolific information among multi-view face images. To improve the efficiency of MVSRC on smart glasses, we propose two novel sampling optimization strategies using the less expensive inertial sensors. Our evaluations on public and private datasets show that the proposed method is up to 10 percent more accurate than the state-of-the-art multi-view face recognition methods while its computation cost is the same order as an efficient benchmark method (e.g., Eigenfaces). Finally, extensive real-world experiments show that our proposed system improves recognition accuracy by up to 15 percent while achieving the same level of system overhead compared to the existing face recognition system (OpenCV algorithms) on smart glasses.
Autors: Weitao Xu;Yiran Shen;Neil Bergmann;Wen Hu;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 197 - 210
Publisher: IEEE
 
» Sequence Synopsis: Optimize Visual Summary of Temporal Event Data
Abstract:
Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.
Autors: Yuanzhe Chen;Panpan Xu;Liu Ren;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 45 - 55
Publisher: IEEE
 
» Set-Membership-Based Fault Detection and Isolation for Robotic Assembly of Electrical Connectors
Abstract:
This paper addresses the fault detection and isolation (FDI) problem for robotic assembly of electrical connectors in the framework of set-membership. Both the fault-free and faulty cases of assembly are modeled by different switched linear models with known switching sequences, bounded parameters, and external disturbances. The locations of switching points of each model are assumed to be inside some areas but the accurate positions are not clear. Given current input/output data, the feasible parameter set of fault-free switched linear model is obtained by sequentially calculating an optimal ellipsoid. If the pair of data is not consistent with any possible submodel, a fault is then detected. The isolation of fault is realized by checking the consistency between the data sequence and each possible fault model one by one. The robustness of the proposed FDI algorithms is proved. The effectiveness of these algorithms is verified by the robotic assembly experiments of mating electrical connectors.

Note to Practitioners—In modern robotic assembly tasks, the industrial robots often need to manipulate tiny objects with complex structure. Electrical connectors are a typical kind of these objects and widely used in many industrial fields. To avoid damaging the fragile connectors and accelerate the assembly process, it is required to promptly detect and isolate the certain assembly fault in real time so that the robot can immediately implement an error recovery procedure according to the identified fault. The proposed set-membership-based fault detection and isolation (FDI) methodology satisfies both the timing and fault-isolation requirements for this kind of robotic assembly task. In terms of the set-membership theory, no false alarm will occur if there are sufficient training data for the proposed method. In addition, it turns out that the proposed method can signal an alarm faster than conventional residual-based FDI method from- plentiful experiments. Although only the robotic assembly of electrical connectors is investigated, our FDI method can also be applied in the assembly task of other small and complex parts. This is especially useful for increasing the productivity and promoting the automation level of electronic industries.

Autors: Jian Huang;Yuan Wang;Toshio Fukuda;
Appeared in: IEEE Transactions on Automation Science and Engineering
Publication date: Jan 2018, volume: 15, issue:1, pages: 160 - 171
Publisher: IEEE
 
» Setting Sail Toward a Bright Future [Presidents' Column]
Abstract:
Presents the President’s message for this issue of the publication.
Autors: Tom Brazil;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 11 - 19
Publisher: IEEE
 
» Ship Classification in TerraSAR-X Images With Convolutional Neural Networks
Abstract:
Synthetic aperture radar (SAR) is an important instrument for oceanographic observations, providing detailed information of oceans’ surface and artificial floating structures. Due to advances in SAR technology and deployment of new SAR satellites, an increasing amount of data is available, and the development of efficient classification systems based on deep learning is possible. A deep neural network has improved the state of the art in classification tasks of optical images, but its use in SAR classification problems has been less exploited. In this paper, a full workflow for SAR maritime targets detection and classification on TerraSAR-X high-resolution image is presented, and convolutional neural networks (CNNs) recently proposed in the literature are cross evaluated on a common data set composed of five maritime classes, namely, cargo, tanker, windmill, platform, and harbor structure. Based on experiments and tests, a multiple input resolution CNN model is proposed and its performance is evaluated. Our results indicate that CNNs are efficient models to perform maritime target classification in SAR images, and the combination of different input resolutions in the CNN model improves its ability to derive features, increasing the overall classification score.
Autors: Carlos Bentes;Domenico Velotto;Björn Tings;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Jan 2018, volume: 43, issue:1, pages: 258 - 266
Publisher: IEEE
 
» Short-Term Residential Load Forecasting Based on Resident Behaviour Learning
Abstract:
Residential load forecasting has been playing an increasingly important role in modern smart grids. Due to the variability of residents’ activities, individual residential loads are usually too volatile to forecast accurately. A long short-term memory-based deep-learning forecasting framework with appliance consumption sequences is proposed to address such volatile problem. It is shown that the forecasting accuracy can be notably improved by including appliance measurements in the training data. The effectiveness of the proposed method is validated through extensive comparison studies on a real-world dataset.
Autors: Weicong Kong;Zhao Yang Dong;David J. Hill;Fengji Luo;Yan Xu;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1087 - 1088
Publisher: IEEE
 
» SiC Trench MOSFET With Integrated Self-Assembled Three-Level Protection Schottky Barrier Diode
Abstract:
A silicon carbide (SiC) trench MOSFET (TMOS) with integrated three-level protection (TLP) Schottky barrier diode (SBD), named ITS-TMOS, is proposed and investigated by simulation. The device features the integrated TLP-SBD that remarkably improves body diode characteristics while guarantees excellent fundamental performance of TMOS. In the blocking state, the P-base region, the trench gate, and the P+ shield at the trench bottom serve as the TLP of the Schottky contact. Each protection assists in depleting the drift region beneath Schottky contact. Benefiting from the self-assembled TLP, the leakage current of the integrated body diode of the ITS-TMOS is significantly reduced. Moreover, the reverse turn-on voltage () and the gate charge () of the ITS-TMOS are 65% and 18% lower than those of the conventional TMOS, respectively. The improved overall performances make the SiC ITS-TMOS a competitive candidate for high-efficiency and high power density applications.
Autors: Xuan Li;Xing Tong;Alex Q. Huang;Hong Tao;Kun Zhou;Yifan Jiang;Junning Jiang;Xiaochuan Deng;Xu She;Bo Zhang;Yourun Zhang;Qi Tian;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Jan 2018, volume: 65, issue:1, pages: 347 - 351
Publisher: IEEE
 
» Signal Processing Powers Next-Generation Prosthetics: Researchers Investigate Techniques That Enable Artificial Limbs to Behave More Like Their Natural Counterparts [Special Reports]
Abstract:
Prosthetic limbs have improved significantly over the past several years, and signal processing has played a key role in allowing these devices to operate more smoothly and precisely on command. Now, researchers are taking the next step forward by using signal processing approaches and methods to develop prosthetics that not only function reliably and efficiently but give wearers more natural control over artificial arms, hands, and legs. Researchers at London’s Imperial College, for instance, have developed a prosthetic arm sensor technology that detects signals transmitted by nerves in the spinal cord. To control the prosthetic, the wearer simply has to think about controlling a phantom arm and imagine a simple maneuver, such as pinching two fingers together. The sensor technology then interprets electrical signals sent from the spine and uses them as commands. Existing robotic prosthetic arms are controlled by having the wearer twitch remaining muscles in his or her shoulder or arm. The new approach detects signals from spinal motor neurons in parts of the body that were left undamaged by the amputation
Autors: John Edwards;
Appeared in: IEEE Signal Processing Magazine
Publication date: Jan 2018, volume: 35, issue:1, pages: 13 - 16
Publisher: IEEE
 
» Significant Anatomy Detection Through Sparse Classification: A Comparative Study
Abstract:
We present a comparative study for discriminative anatomy detection in high dimensional neuroimaging data. While most studies solve this problem using mass univariate approaches, recent works show better accuracy and variable selection using a sparse classification model. Two types of image-based regularization methods have been proposed in the literature based on either a Graph Net (GN) model or a total variation (TV) model. These studies showed increased classification accuracy and interpretability of results when using image-based regularization, but did not look at the accuracy and quality of the recovered significant regions. In this paper, we theoretically prove bounds on the recovered sparse coefficients and the corresponding selected image regions in four models (two based on GN penalty and two based on TV penalty). Practically, we confirm the theoretical findings by measuring the accuracy of selected regions compared with ground truth on simulated data. We also evaluate the stability of recovered regions over cross-validation folds using real MRI data. Our findings show that the TV penalty is superior to the GN model. In addition, we showed that adding an l2 penalty improves the accuracy of estimated coefficients and selected significant regions for the both types of models.
Autors: Li Zhang;Dana Cobzas;Alan H. Wilman;Linglong Kong;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 128 - 137
Publisher: IEEE
 

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