Electrical and Electronics Engineering publications abstract of: 01-2018 sorted by title, page: 2

» A Time-Based Receiver With 2-Tap Decision Feedback Equalizer for Single-Ended Mobile DRAM Interface
Abstract:
A time-based (TB) receiver (RX) with a 2-tap TB decision feedback equalizer (DFE) is proposed for mobile DRAM interface. The TB RX consists of a voltage-to-time converter (VTC), a TB DFE, and a time comparator. The VTC converts the RX input voltage to a time difference between two VTC outputs by using the difference in clock-to-Q delays between two latches with different input offset voltages. The TB DFE inserts an additional delay to one of the two VTC outputs and bypasses the other VTC output to increase the time opening. The time comparator makes a decision with the first arriving edge of the two outputs of the TB DFE. While the feedback loop delay must be less than 1 UI for proper operation in the conventional voltage-based DFE, the TB DFE allows the feedback loop delay up to 1.43 UI in this paper. A transmitter (TX) transmits a single-ended signal of 200-mV swing by using an n-over-n voltage-mode driver. The transceiver in a 65-nm CMOS process achieves a 12.5 Gb/s with a 0.8-V supply through a 15-inch FR-4 channel of 14-dB loss. The TX and RX chip consume 4.3 and 3.4 mA, respectively. The energy efficiency is 0.49 pJ/b.
Autors: Il-Min Yi;Min-Kyun Chae;Seok-Hun Hyun;Seung-Jun Bae;Jung-Hwan Choi;Seong-Jin Jang;Byungsub Kim;Jae-Yoon Sim;Hong-June Park;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 144 - 154
Publisher: IEEE
 
» A Time-Efficient CMOS-Memristive Programmable Circuit Realizing Logic Functions in Generalized AND–XOR Structures
Abstract:
This paper describes a CMOS-memristive programmable logic device connected to CMOS XOR gates (mPLD-XOR) for realizing multioutput functions well suited for two-level {NAND, AND, NOR, OR}-XOR-based design. This structure is a generalized form of AND–XOR logic where any combination of NAND, AND, NOR, and OR, and literals can replace the and level. For mPLD-XOR, the computational delay, which is measured as the number of clock cycles, equals the maximum number of inputs to any output XOR gate of a function assuming that the number of XOR gates is large enough to calculate the outputs of the function simultaneously. The input levels of functions are implemented with novel programmable diode gates, which rely on the diode-like behavior of self-rectifying memristors, and the output levels of functions are realized with CMOS modulo-two counters. As an example, the circuit implementation of a 3-bit adder and a 3-bit multiplier are presented. The size and performance of the implemented circuits are estimated and compared with those of the equivalent circuits realized with stateful logic gates. Adding a feedback circuit to the mPLD-XOR allows the implementation of a multilevel XOR logic network with any combination of sums, products, XORs, and literals at the input of any XOR gate. The mPLD-XOR with feedback can reduce the size and number of computational steps (clock cycles) in realizing logic functions, which makes it well suited for use in communication and parallel computing systems where fast arithmetic operations are demanding.
Autors: Muayad J. Aljafar;Marek A. Perkowski;John M. Acken;Robin Tan;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 23 - 36
Publisher: IEEE
 
» A Tri-Slope Gate Driving GaN DC–DC Converter With Spurious Noise Compression and Ringing Suppression for Automotive Applications
Abstract:
Targeting on electromagnetic interference (EMI) regulation and ringing suppression issues in automotive applications, this paper presents a gallium nitride (GaN)-based dc–dc converter operating at 10 MHz. A spurious noise compression technique compresses and re-distributes spurious switching noise within a defined frequency sideband, achieving EMI noise reduction at main switching frequency and its harmonics. Meanwhile, a tri-slope gate driver is designed to control voltage and current slew rates of GaN switches for effective ringing suppression, which is adaptive to load and input voltage changes. Tailored for high switching frequency and high-efficiency operation, the dynamic level shifters achieve about 0.8-ns propagation delay and near-zero quiescent current. Fabricated in a 0.35-m Bipolar-CMOS-DMOS process, the converter accomplishes an EMI noise reduction of 40.5 dBV and suppresses ringing by 79.3%. The converter retains above 60% efficiency over 96.6% of its 6-W power range, with a peak efficiency of 85.5% at 1.5-W load.
Autors: Xugang Ke;Joseph Sankman;Yingping Chen;Lenian He;D. Brian Ma;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 247 - 260
Publisher: IEEE
 
» A Two-level Traffic Light Control Strategy for Preventing Incident-Based Urban Traffic Congestion
Abstract:
This work designs a two-level strategy at signalized intersections for preventing incident-based urban traffic congestion by adopting additional traffic warning lights. The first-level one is a ban signal strategy that is used to stop the traffic flow driving toward some directions, and the second-level one is a warning signal strategy that gives traffic flow a recommendation of not driving to some directions. As a visual and mathematical formalism for modeling discrete-event dynamic systems, timed Petri nets are utilized to describe the cooperation between traffic lights and warning lights, and then verify their correctness. A two-way rectangular grid network is modeled via a cell transmission model. The effectiveness of the proposed two-level strategy is evaluated through simulations in the grid network. The results reveal the influences of some major parameters, such as the route-changing rates of vehicles, operation time interval of the proposed strategy, and traffic density of the traffic network on a congestion dissipation process. The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.
Autors: Liang Qi;MengChu Zhou;WenJing Luan;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 13 - 24
Publisher: IEEE
 
» A Two-Phase Multiobjective Sparse Unmixing Approach for Hyperspectral Data
Abstract:
With the sparse unmixing becoming increasingly popular recently, some advanced regularization algorithms have been proposed for settling this problem. However, they are limited by their “decision ahead of solution” attribute, i.e., the regularization parameters must be preset before the solution is obtained. In this paper, the sparse unmixing problem is first formulated as a two-phase multiobjective problem. The first phase simultaneously minimizes the unmixing residuals and the number of estimated endmembers for automatically finding the real active endmembers from the spectral library. A decomposition-based endmember selection algorithm considering the gene exchange in the population is specially designed for better and quicker search of the decision space. This algorithm can obtain a set of nondominated solutions for better decision of the active endmembers, which are important for the subsequent calculation of the abundance matrix. The second phase concurrently minimizes the unmixing residuals and the total variation term for estimating a preferable abundance matrix. A local search strategy based on the multiplicative update rule is designed in the evolution process for better approximation of the Pareto front. The experimental results on the synthetic as well as the real data reveal that the proposed framework has a better performance in finding the real active endmembers and estimating their corresponding abundances than some advanced regularization algorithms.
Autors: Xiangming Jiang;Maoguo Gong;Hao Li;Mingyang Zhang;Jun Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 508 - 523
Publisher: IEEE
 
» A Two-Step Sensing Circuit for the Hysteresis Loop Selector-Based Resistive Non-Volatile Memory Arrays
Abstract:
A high selectivity semiconductor selector is the key component in the ultra-high density and low power 3-D resistive non-volatile memory array. The state-of-art selectors suffer from various issues including low selectivity, high OFF current, and low ON current, which significantly limit the array size and performance. Recently, a hysteresis loop (HL) selector with the high selectivity, moderate ON voltage and large HL window was developed to address the high leakage current issue. In this brief, a two-step sensing scheme is proposed to minimize the read disturbance and sensing power. The proposed two-step sensing circuit could achieve 25-ns fast sensing speed with 3.92-uW low sensing power.
Autors: Kejie Huang;Wei He;Rong Zhao;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 101 - 105
Publisher: IEEE
 
» A Utility-Aware Visual Approach for Anonymizing Multi-Attribute Tabular Data
Abstract:
Sharing data for public usage requires sanitization to prevent sensitive information from leaking. Previous studies have presented methods for creating privacy preserving visualizations. However, few of them provide sufficient feedback to users on how much utility is reduced (or preserved) during such a process. To address this, we design a visual interface along with a data manipulation pipeline that allows users to gauge utility loss while interactively and iteratively handling privacy issues in their data. Widely known and discussed types of privacy models, i.e., syntactic anonymity and differential privacy, are integrated and compared under different use case scenarios. Case study results on a variety of examples demonstrate the effectiveness of our approach.
Autors: Xumeng Wang;Jia-Kai Chou;Wei Chen;Huihua Guan;Wenlong Chen;Tianyi Lao;Kwan-Liu Ma;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 351 - 360
Publisher: IEEE
 
» A Virtual Reality Visualization Tool for Neuron Tracing
Abstract:
Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists.
Autors: Will Usher;Pavol Klacansky;Frederick Federer;Peer-Timo Bremer;Aaron Knoll;Jeff Yarch;Alessandra Angelucci;Valerio Pascucci;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 994 - 1003
Publisher: IEEE
 
» A Wavelet Decomposition and Polynomial Fitting-Based Method for the Estimation of Time-Varying Residual Motion Error in Airborne Interferometric SAR
Abstract:
Compensating the residual motion error (RME) is very important in airborne interferometric synthetic aperture radar (InSAR). In this paper, the wavelet decomposition and polynomial fitting-based (WDPF) method is proposed for detecting and correcting the RME. Wavelet decomposition with root-mean-square error (RMSE) change ratio-based decomposition scale identification is used to detect the RME from the differential interferogram. Polynomial fitting in combination with robust estimation-based least squares is used to absorb the incidence-angle-dependent and topography-dependent components of the RME. A simulated experiment was conducted to test the proposed WDPF method. High-precision RME (with an RMSE of 0.0375 rad) was obtained, which can meet the requirements of InSAR. Real-data L- and P-band InSAR experiments were also performed to test the WDPF method. The results confirmed that the WDPF method can effectively correct the RME for the interferogram. The RMSE of the estimated digital elevation model (DEM) was reduced from 8.03 to 3.46 m and 8.18 to 3.10 m for the L- and P-band interferograms, respectively. Finally, the effects of the external DEM error and polarization on the RME calibration were investigated. The results indicated that the global InSAR DEM products can fulfill the requirement of differential interferogram generation for the WDPF method, and the multipolarization interferograms can help to reduce the effect of the topographic error phase on RME estimation.
Autors: Hai Qiang Fu;Jian Jun Zhu;Chang Cheng Wang;Hui Qiang Wang;Rong Zhao;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 49 - 59
Publisher: IEEE
 
» A Wearable Amperometric Biosensor on a Cotton Fabric for Lactate
Abstract:
The development of new bioelectronic sensors could enable significant advances in clinical analysis, environmental monitoring, and defense. Cotton fabric is a wearable material, which can contact the skin closely. Here, we demonstrate for the first time the development of a wearable amperometric biosensor on a cotton fabric for the detection of lactate. The sensor is constructed by printing carbon graphite ink and Ag/AgCl ink on a cotton fabric as the working, reference, and counter electrode. Via the immobilization of lactate oxidase, the sensor shows a sensitive detection of lactate with a detection range of 0.05–1.5 mM and a rapid measuring time of around 5 min. We anticipate that these results could open exciting opportunities for fundamental studies and practical applications of wearable bioelectronics in areas ranging from healthcare to defense.
Autors: Xiaojin Luo;Hongrui Yu;Yue Cui;
Appeared in: IEEE Electron Device Letters
Publication date: Jan 2018, volume: 39, issue:1, pages: 123 - 126
Publisher: IEEE
 
» A Wearable Device to Support the Pull Test for Postural Instability Assessment in Parkinson’s Disease
Abstract:
The pull test (PT) is a common practice to assess the postural instability of patients with Parkinson’s disease. Postural instability is a serious issue for elderly and people with neurological disease, which can cause falls. The implementation of the PT consists in observing the user response after providing a tug to the patients’ shoulders, in order to displace the center of gravity from its neutral position. The validity of the test can be compromised by a nonstandard backward tug provided to the patient. The solution proposed in this paper consists of a low-cost multisensor system allowing an instrumented estimation of the input solicitation. Moreover, the system provides supplementary information on the user postural stability, by means of a set of features extracted from the user stabilogram. A wide set of experiments have been performed to assess the system capability to provide a rough classification between stable and unstable behaviors. Results obtained demonstrate the validity of the approach proposed, with very low rates of false positive and false negative.
Autors: Bruno Andò;Salvatore Baglio;Vincenzo Marletta;Antonio Pistorio;Valeria Dibilio;Giovanni Mostile;Alessandra Nicoletti;Mario Zappia;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 218 - 228
Publisher: IEEE
 
» A Wideband Dual-Polarized Omnidirectional Antenna for Base Station/WLAN
Abstract:
A wideband dual-polarized omnidirectional antenna is proposed for mobile communication base station and 2.4 GHz wireless local area network applications. An integrated design is achieved by combining an inverted-cone monopole for vertical polarization (VP) and a modified cross bow-tie dipole for horizontal polarization (HP). The proposed antenna has a compact size because the HP element acts as the HP radiating element and the ground plane for the VP element simultaneously. The proposed VP and HP antennas are excited by a Sub-Miniature-A connector and a broadband feeding network, respectively. The overall volume of the proposed antenna is only (with being the wavelength of the lowest frequency). Simulation results show that the dual-polarized omnidirectional antenna achieves a bandwidth (for dB) of about 41.5% (1.64–2.5 GHz) with an isolation of at least 25 dB and the gain variations at the center frequency in the horizontal plane are 0.7 dB for VP and 2.3 dB for HP. The good agreements between the simulation and measured results validate the proposed design.
Autors: Jun Wang;Lei Zhao;Zhang-Cheng Hao;Jian-Ming Jin;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 81 - 87
Publisher: IEEE
 
» A Wideband SiGe BiCMOS Frequency Doubler With 6.5-dBm Peak Output Power for Millimeter-Wave Signal Sources
Abstract:
This paper presents a balanced frequency doubler with 6.5-dBm peak output power at 204 GHz in 130-nm SiGe BiCMOS technology (/250 GHz). To convert the single-ended input signal to a differential signal for balanced operation, an on-chip transformer-based balun is employed. Detailed design procedure and compensation techniques to lower the imbalance at the output ports, based on mixed mode S parameters are proposed and verified analytically and through electromagnetic simulations. The use of optimized harmonic reflectors at the input port results in a 2-dBm increase in output power without sacrificing the bandwidth of interest. The measured conversion loss of the frequency doubler is 9 dB with 6-dBm input power at 204-GHz output. The measured peak output power is 6.5 dBm with an on-chip power amplifier stage. The 3-dB output power bandwidth is measured to be wider than 50 GHz (170–220 GHz). The total chip area of the doubler is 0.09 mm2 and the dc power consumption is 90 mW from a 1.8-V supply, which corresponds to a 5% collector efficiency.
Autors: Kefei Wu;Sriram Muralidharan;Mona Mostafa Hella;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 187 - 200
Publisher: IEEE
 
» A Wideband Variable Gain LNA With High OIP3 for 5G Using 40-nm Bulk CMOS
Abstract:
This letter presents a CMOS wideband variable gain LNA for 28-GHz 5G integrated phased-array transceivers preserving high third-order intercept point (OIP3) at all gain settings. The prototype LNA has three stages providing digitally controlled gain optimized for higher IIP3 at lower gain. The stages are coupled together using double-tuned transformers for maximum group delay flatness. Fabricated in a 40-nm CMOS process, it achieves 18–26 dB gain at 1-dB gain step with 12–14.5 dBm OIP3 and 3.3–4.3 dB noise figure, while consuming 21.5–31.4 mW across 26–33 GHz frequency range. The root-mean-square error of the gain steps is less than 0.38 dB.
Autors: Mohamed Elkholy;Sherif Shakib;Jeremy Dunworth;Vladimir Aparin;Kamran Entesari;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 64 - 66
Publisher: IEEE
 
» A Wideband, Low-Noise Accelerometer for Sonar Wave Detection
Abstract:
This paper presents the development of a high-performance micromachined capacitive accelerometer for detection of sonar waves. The device is intended to replace existing hydrophones in towed array sonar systems, and thus, needs to meet stringent performance requirements on noise, bandwidth, and dynamic range, among others. The in-plane, single-axis accelerometer is designed based on a mode-tuning structural platform. A frame was used instead of a solid plate for the proof-mass of the device, allowing us to push undesired vibration modes beyond the operating bandwidth of the device while enabling us to employ a portion of the area for capacitive sensing elements. The designed accelerometer was fabricated on a silicon-on-insulator wafer with 100- device layer with capacitive gaps of . The sensitivity of the accelerometer is 4 V/g with a noise spectral density of better than . The fundamental resonant frequency of the device is 4.4 kHz. The open-loop dynamic range of the accelerometer, while operating at atmospheric pressure, is better than 135 dB with a cross-axis sensitivity of less than 30 dB.
Autors: Fatemeh Edalafar;Soheil Azimi;Abdul Qader Ahsan Qureshi;Bahareh Yaghootkar;Andrew Keast;Wolfgang Friedrich;Albert M. Leung;Behraad Bahreyni;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 508 - 516
Publisher: IEEE
 
» ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
Abstract:
While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance-and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models.
Autors: Minsuk Kahng;Pierre Y. Andrews;Aditya Kalro;Duen Horng (Polo) Chau;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 88 - 97
Publisher: IEEE
 
» Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells
Abstract:
This paper presents Abstractocyte, a system for the visual analysis of astrocytes and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. The study of astrocytes has immense potential for understanding brain function. However, their complex and widely-branching structure requires high-resolution electron microscopy imaging and makes visualization and analysis challenging. Furthermore, the structure and function of astrocytes is very different from neurons, and therefore requires the development of new visualization and analysis tools. With Abstractocyte, biologists can explore the morphology of astrocytes using various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. We define a novel, conceptual 2D abstraction space for jointly visualizing astrocytes and neurons. Neuroscientists can choose a specific joint visualization as a point in this space. Interactively moving this point allows them to smoothly transition between different abstraction levels in an intuitive manner. In contrast to simply switching between different visualizations, this preserves the visual context and correlations throughout the transition. Users can smoothly navigate from concrete, highly-detailed 3D views to simplified and abstracted 2D views. In addition to investigating astrocytes, neurons, and their relationships, we enable the interactive analysis of the distribution of glycogen, which is of high importance to neuroscientists. We describe the design of Abstractocyte, and present three case studies in which neuroscientists have successfully used our system to assess astrocytic coverage of synapses, glycogen distribution in relation to synapses, and astrocytic-mitochondria coverage.
Autors: Haneen Mohammed;Ali K. Al-Awami;Johanna Beyer;Corrado Cali;Pierre Magistretti;Hanspeter Pfister;Markus Hadwiger;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 853 - 861
Publisher: IEEE
 
» Accelerating Persistent Scatterer Pixel Selection for InSAR Processing
Abstract:
Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technology used for estimating the displacement of an object on the ground or the earth's surface itself. Persistent Scatterer-InSAR (PS-InSAR) is a category of time series algorithms enabling high resolution monitoring. PS-InSAR relies on successful selection of points that appear stable across a set of satellite images taken over time. This paper presents PtSel, a new algorithm for selecting these points, a problem known as Persistent Scatterer Selection. The key advantage of PtSel over the key existing techniques is that it does not require model assumptions, yet preserves solution accuracy. Motivated by the abundance of parallelism the algorithm exposes, we have implemented it for GPUs. Our evaluation using real-world data shows that the GPU implementation not only offers superior performance but also scales linearly with GPU count and workload size. We compare the GPU implementation and a parallel CPU implementation: a consumer grade GPU offers 18x speedup over a 16-core Ivy Bridge Xeon System, while four GPUs offer 65x speedup. The GPU solution consumes 28x less energy than the CPU-only solution. Additionally, we present a comparison with the most widely used PS-interferometry software package StaMPS, in terms of point selection coverage and precision.
Autors: Tahsin Reza;Aaron Zimmer;José Manuel Delgado Blasco;Parwant Ghuman;Tanuj Kr Aasawat;Matei Ripeanu;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Jan 2018, volume: 29, issue:1, pages: 16 - 30
Publisher: IEEE
 
» Accuracy Directly Controlled Fast Direct Solution of General ${mathcal{ H}}^{2}$ -Matrices and Its Application to Solving Electrodynamic Volume Integral Equations
Abstract:
The dense matrix resulting from an integral equation (IE)-based solution of Maxwell’s equations can be compactly represented by an -matrix. Given a general dense -matrix, prevailing fast direct solutions involve approximations whose accuracy can only be indirectly controlled. In this paper, we propose new direct solution algorithms whose accuracy is directly controlled, including both factorization and inversion, for solving general -matrices. Different from the recursive inverse performed in existing -based direct solutions, this new direct solution is a one-way traversal of the cluster tree from the leaf level all the way up to the root level. The underlying multiplications and additions are carried out as they are without using formatted multiplications and additions whose accuracy cannot be directly controlled. The cluster bases and their rank of the original matrix are also updated level by level based on prescribed accuracy, without increasing computational complexity, to take into account the contributions of fill-ins generated during the direct solution procedure. For constant-rank -matrices, the proposed direct solution has a strict complexity in both time and memory. For rank that linearly grows with the electrical size, the complexity of the proposed direct solution is in factorization and inversion time, and <- nline-formula> $O(N)$ in solution time and memory for solving volume IEs (VIEs). Rapid direct solutions of electrodynamic VIEs involving millions of unknowns have been obtained on a single CPU core with directly controlled accuracy. Comparisons with state-of-the-art -based direct VIE solvers have also demonstrated the advantages of the proposed direct solution in accuracy control, as well as achieving better accuracy with much less CPU time.
Autors: Miaomiao Ma;Dan Jiao;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 35 - 48
Publisher: IEEE
 
» Accuracy Enhancement for Noninvasive Glucose Estimation Using Dual-Wavelength Photoacoustic Measurements and Kernel-Based Calibration
Abstract:
Frequent monitoring of blood glucose levels is an essential part of diabetes care, but the invasiveness of current devices deters regular measurement. Noninvasive measurement techniques are painless to implement and rely on changes in sample properties to estimate glucose concentration. However, such methods are affected by the presence of different biomolecules, resulting in an increased estimation error and necessitating calibration to obtain accurate glucose concentration estimates. The use of photoacoustic spectroscopy for continuous noninvasive glucose monitoring is studied through measurements on different sample media. In vitro photoacoustic measurements taken from aqueous glucose solutions, solutions of glucose and hemoglobin, and whole blood samples at multiple excitation wavelengths show amplitude and area-based signal features to rise with the increase in sample glucose concentration. The calibration of photoacoustic measurements from glucose solutions using Gaussian kernel-based regression results in a root mean square error (RMSE), mean absolute difference (MAD), and mean absolute relative difference (MARD) of 7.64 mg/dl, 5.23 mg/dl, and 2.07%, respectively. Kernel-based calibration also performs well on solutions of glucose and hemoglobin, and whole blood samples, resulting in lower estimation errors than that of previous efforts and with glucose estimates being in the acceptable zones of a Clarke error grid (CEG). It allows for individual calibration of photoacoustic measurements in vivo, resulting in an RMSE, MAD, and MARD of 19.46 mg/dl, 10.79 mg/dl, and 7.01%, respectively, with 89.80% of the estimates being within Zone A of the CEG. The improvement in estimation accuracy with dual-wavelength photoacoustic measurements and kernel-based calibration would enable continuous noninvasive glucose monitoring, facilitating improved diabetic care.
Autors: Praful P. Pai;Arijit De;Swapna Banerjee;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 126 - 136
Publisher: IEEE
 
» Achieving Full-Duplex Communication: Magnetless Parametric Circulators for Full-Duplex Communication Systems
Abstract:
In a crowded electromagnetic spectrum with ever-increasing demand for higher data rates to enable multimedia-rich applications and services, the efficient use of wireless resources becomes crucial. For this reason, full-duplex communication [1]-[4], which increases the capacity of transmission channels by operating the uplink and downlink simultaneously on the same frequency channel (see Figure 1), is returning to the spotlight after decades of being presumed impractical. This long-held assumption resulted mainly from the need for large isolation (IX) between the transmit (Tx) and receive (Rx) nodes [also known as self-interference cancellation (SIC)], which typically needs to be greater than 100 dB, a challenging task that requires several innovations at the network and physical layer levels.
Autors: Ahmed Kord;Dimitrios L. Sounas;Andrea Alù;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 84 - 90
Publisher: IEEE
 
» Acoustic Radiation Force-Induced Creep–Recovery (ARFICR): A Noninvasive Method to Characterize Tissue Viscoelasticity
Abstract:
Ultrasound shear wave elastography is a promising noninvasive, low cost, and clinically viable tool for liver fibrosis staging. Current shear wave imaging technologies on clinical ultrasound scanners ignore shear wave dispersion and use a single group velocity measured over the shear wave bandwidth to estimate tissue elasticity. The center frequency and bandwidth of shear waves induced by acoustic radiation force depend on the ultrasound push beam (push duration, -number, etc.) and the viscoelasticity of the medium, and therefore are different across scanners from different vendors. As a result, scanners from different vendors may give different tissue elasticity measurements within the same patient. Various methods have been proposed to evaluate shear wave dispersion to better estimate tissue viscoelasticity. A rheological model such as the Kelvin–Voigt model is typically fitted to the shear wave dispersion to solve for the elasticity and viscosity of tissue. However, these rheological models impose strong assumptions about frequency dependence of elasticity and viscosity. Here, we propose a new method called Acoustic Radiation Force Induced Creep-Recovery (ARFICR) capable of quantifying rheological model-independent measurements of elasticity and viscosity for more robust tissue health assessment. In ARFICR, the creep-recovery time signal at the focus of the push beam is used to calculate the relative elasticity and viscosity (scaled by an unknown constant) over a wide frequency range. Shear waves generated during the ARFICR measurement are also detected and used to calculate the shear wave velocity at its center frequency, which is then used to calibrate the relative elasticity and viscosity to absolute elasticity and viscosity. In this paper, finite-element method simulations and experiments in tissue mimicking phantoms are used to validate and characterize the exte- t of viscoelastic quantification of ARFICR. The results suggest that ARFICR can measure tissue viscoelasticity reliably. Moreover, the results showed the strong frequency dependence of viscoelastic parameters in tissue mimicking phantoms and healthy liver.
Autors: Carolina Amador Carrascal;Shigao Chen;Matthew W. Urban;James F. Greenleaf;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Jan 2018, volume: 65, issue:1, pages: 3 - 13
Publisher: IEEE
 
» Actionable Analytics for Software Engineering
Abstract:
Although intensive research on software analytics has been going on for nearly a decade, a repeated complaint in software analytics is that industrial practitioners find it hard to apply the results generated from data science. This theme issue aims to reflect on actionable analytics for software engineering and to document a catalog of success stories in which analytics has been proven actionable and useful, in some significant way, in an organization. This issue features five articles covering promising analytical methods for improving change triage, strategic maintenance, and team robustness, as well as the success stories of applying analytical tools during an organizational transformation.
Autors: Ye Yang;Davide Falessi;Tim Menzies;Jairus Hihn;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 51 - 53
Publisher: IEEE
 
» Actionable Analytics for Strategic Maintenance of Critical Software: An Industry Experience Report
Abstract:
NASA has been successfully sustaining the continuous operation of its critical navigation software systems for over 12 years. To accomplish this, NASA scientists must continuously monitor their process, report on current system quality, forecast maintenance effort, and sustain required staffing levels. This report presents some examples of the use of a robust software metrics and analytics program that enables actionable strategic maintenance management of a critical system (Monte) in a timely, economical, and risk-controlled fashion. This article is part of a special issue on Actionable Analytics for Software Engineering.
Autors: Dan Port;Bill Taber;
Appeared in: IEEE Software
Publication date: Jan 2018, volume: 35, issue:1, pages: 58 - 63
Publisher: IEEE
 
» Active Learning-Based Optimized Training Library Generation for Object-Oriented Image Classification
Abstract:
In this paper, we introduce an active learning (AL)-based object training library generation for a multiclassifier object-oriented image analysis (OOIA) system. While several AL approaches do exist for pixel-based training library generation and for hyperspectral image classification, there is no standard training library generation strategy for OOIA of very high spatial resolution images. Given a sufficient number of training samples, supervised classification is the method of choice for image classification. However, this strategy becomes computationally expensive with the increase in the number of classes or the number of images to be classified. The above-mentioned issue is solved in this proposed method, where an optimized training library of objects (superpixels) is generated based on a batch mode AL approach. A softmax classifier is used as a detector in this method, which helps in determining the right samples to be chosen for library updation. To this end, we construct a multiclassifier system with max-voting decision to classify an image at pixel level. This algorithm was applied on three different very high-resolution airborne data sets, each with varying complexity in terms of variations in geographical context, sensors, illumination, and view angles. Our method has empirically outperformed the traditional OOIA by producing equivalent accuracy with a training library that is orders of magnitude smaller. In addition, the most distinctive ability of the algorithm is experienced in the most heterogeneous data set, where its performance in terms of accuracy is around twice the performance of the traditional method in the same situation. The generality of this classification strategy is proved through its performance on multispectral images and for cross-domain application. Finally, the robustness of this method is identified by comparing its performance with an alternative AL approach—self-learning-based semisupervised SVM. The capability- of the proposed method to handle highly heterogeneous data is identified as the primary reason for its robustness.
Autors: Rajeswari Balasubramaniam;Srivalsan Namboodiri;Rama Rao Nidamanuri;Rama Krishna Sai Subrahmanyam Gorthi;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Jan 2018, volume: 56, issue:1, pages: 575 - 585
Publisher: IEEE
 
» Active Reading of Visualizations
Abstract:
We investigate whether the notion of active reading for text might be usefully applied to visualizations. Through a qualitative study we explored whether people apply observable active reading techniques when reading paper-based node-link visualizations. Participants used a range of physical actions while reading, and from these we synthesized an initial set of active reading techniques for visualizations. To learn more about the potential impact such techniques may have on visualization reading, we implemented support for one type of physical action from our observations (making freeform marks) in an interactive node-link visualization. Results from our quantitative study of this implementation show that interactive support for active reading techniques can improve the accuracy of performing low-level visualization tasks. Together, our studies suggest that the active reading space is ripe for research exploration within visualization and can lead to new interactions that make for a more flexible and effective visualization reading experience.
Autors: Jagoda Walny;Samuel Huron;Charles Perin;Tiffany Wun;Richard Pusch;Sheelagh Carpendale;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 770 - 780
Publisher: IEEE
 
» Active Self-Paced Learning for Cost-Effective and Progressive Face Identification
Abstract:
This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets. Then, a number of candidates are selected from the unannotated samples for classifier updating, in which we apply the current classifiers ranking the samples by the prediction confidence. In particular, our approach utilizes the high-confidence and low-confidence samples in the self-paced and the active user-query way, respectively. The neural nets are later fine-tuned based on the updated classifiers. Such heuristic implementation is formulated as solving a concise active SPL optimization problem, which also advances the SPL development by supplementing a rational dynamic curriculum constraint. The new model finely accords with the “instructor-student-collaborative” learning mode in human education. The advantages of this proposed framework are two-folds: i) The required number of annotated samples is significantly decreased while the comparable performance is guaranteed. A dramatic reduction of user effort is also achieved over other state-of-the-art active learning techniques. ii) The mixture of SPL and AL effectively improves not only the classifier accuracy compared to existing AL/SPL methods but also the robustness against noisy data. We evaluate our framework on two challenging datasets, which include hundreds of persons under diverse conditions, and demonstrate very promising results. Please find the code of this project at: http://h- p.sysu.edu.cn/projects/aspl/.
Autors: Liang Lin;Keze Wang;Deyu Meng;Wangmeng Zuo;Lei Zhang;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Jan 2018, volume: 40, issue:1, pages: 7 - 19
Publisher: IEEE
 
» Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization
Abstract:
Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature.
Autors: G. Elisabeta Marai;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 913 - 922
Publisher: IEEE
 
» Ad Astra Diplomacy [Spectral lines]
Abstract:
In the 2015 science fiction blockbuster The Martian, the United States makes a rushed effort to send life-sustaining provisions to its marooned astronaut on the Red Planet. Alas, the attempt fails when NASA's resupply rocket explodes shortly after liftoff. But officials with China’s national space program save the day when they offer the services of a previously secret Chinese rocket that is capable of ferrying the needed materials. The Martian movie and the book on which it is based have been hailed for their many realistic technical details.
Autors: David Schneider;
Appeared in: IEEE Spectrum
Publication date: Jan 2018, volume: 55, issue:1, pages: 6 - 6
Publisher: IEEE
 
» Adaptive Analog Function Computation via Fading Multiple-Access Channels
Abstract:
In this letter, we propose an adaptive analog function computation (AFC) via fading multiple-access channels in which multiple sensors simultaneously send their observations and then the fusion center computes the desired function via the superposition property of wireless channels. In particular, each sensor adaptively sends its observation to the fusion center based on its causal channel state information (CSI). Numerical results show that the adaptive AFC significantly outperforms the conventional non-adaptive AFC in terms of the outage probability of function estimation error. The adaptive AFC operates in a fully distributed manner with local and causal CSI, applicable to various practical sensor network applications.
Autors: Sang-Woon Jeon;Bang Chul Jung;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 213 - 216
Publisher: IEEE
 
» Adaptive Compressed Sensing Using Intra-Scale Variable Density Sampling
Abstract:
Adaptive sensing has the potential to achieve near optimal performance by using current measurements to design subsequential sensing vectors. Existing adaptive sensing methods are usually based on recursive bisection or known structures of certain sparse representations. They suffer from either wasting extra measurements for detecting large coefficients, or missing these coefficients because of violations of these structures. In this paper, intra-scale variable density sampling (InVDS) is presented to capture the heterogeneous property of coefficients. First, Latin hypercube sampling with good uniformity is employed to find areas containing large coefficients. Then, the neighborhoods of largest coefficients are measured according to the block-sparsity or clustering property. Finally, the denoising-based approximate message passing algorithm is introduced to enhance the performance of image reconstruction. The probability that our sampling method fails to obtain large coefficients is analyzed. The superiority of InVDS is validated by numerical experiments with wavelet, discrete cosine, and Hadamard transforms.
Autors: Jiying Liu;Cong Ling;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 547 - 558
Publisher: IEEE
 
» Adaptive Critic-Based Event-Triggered Control for HVAC System
Abstract:
The heating, ventilation, and air conditioning system is an important component for achieving desired thermal condition in rooms or spaces in buildings, office complex, or airports. This paper proposes a real-time event-triggered adaptive critic controller for generating near optimal control actions to achieve desired temperatures. The desired temperatures may have variable or fixed values over time. The real-time controller is designed in two phases. Initially event-triggered control actions are generated by linear quadratic regulator for small period while the actor-critic network of controller is trained. Later, adaptive critic controller takes over for event-based actions. Hence, the event triggering conditions for both general linear and nonlinear discrete time systems using Lyapunov stability analysis are derived in this paper. The event-based actor-critic network weight update formulation and ultimate boundedness of parameters are also presented in this paper. The proposed approach has been validated for different and common temperature sets for four zones, where the control execution events are minimized to 20 and 26, respectively.
Autors: Narendra Kumar Dhar;Nishchal Kumar Verma;Laxmidhar Behera;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 178 - 188
Publisher: IEEE
 
» Adaptive Estimation of Quantiles in a Simulation Model
Abstract:
Let be an valued random variable, let be a measurable function and set . Given a sample of of size , we consider the problem of estimating the quantile of of a given level . A method for choosing the parameter of a surrogate model of is introduced, and it is shown that the corresponding surrogate quantile estimate achieves the rate of convergence bounded by the sum of the minimal rate of convergence of the quantile estimates corresponding to the given surrogate estimates and a term of order . The finite sample size behavior of this quantile estimate is illustrated by applying it to simulated data and to a quantile estimation problem in mechanical engineering.
Autors: Michael Kohler;Adam Krzyżak;
Appeared in: IEEE Transactions on Information Theory
Publication date: Jan 2018, volume: 64, issue:1, pages: 501 - 512
Publisher: IEEE
 
» Adaptive Fuzzy Logic Control of Fuel-Cell-Battery Hybrid Systems for Electric Vehicles
Abstract:
In this paper, we propose an adaptive control approach with fuzzy logic parameter tuning (AFLPT) for the energy management of electric vehicles that are using fuel cell battery hybrid systems. The controller is adaptive to different driving conditions including normal, regenerative, and overload conditions. Specifically, the power flow between the fuel cell (FC) and the Li-ion battery is controlled in real time to maintain the battery state of charge (SOC) at a desirable level while satisfying the FC dynamic constraints. For guaranteeing performance in different driving conditions, the FLPT is integrated with the adaptive controller. Moreover, theoretical properties of the designed controller are analyzed. Simulation and experiment results illustrate the effectiveness of the proposed strategy for FC-battery hybrid systems in electric vehicles.
Autors: Jian Chen;Chenfeng Xu;Chengshuai Wu;Weihua Xu;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 292 - 300
Publisher: IEEE
 
» Adaptive Online Monitoring of Voltage Stability Margin via Local Regression
Abstract:
An online voltage stability margin (VSM) monitoring approach based on local regression and adaptive database is proposed. Considering the increasing variability and uncertainty of power system operation, this approach utilizes the locality of underlying pattern between VSM and reactive power reserve (RPR), and can adapt to the changing condition of system. LASSO is tailored to solve the local regression problem so as to mitigate the curse of dimensionality for large scale system. Along with the VSM prediction, its confidence interval is also estimated simultaneously in a simple but effective way, and utilized as an evidence to trigger the database updating. IEEE 30-bus system and a 60,000-bus large system are used to test and demonstrate the proposed approach. The results show that the proposed approach can be successfully employed in online voltage stability monitoring for real size systems, and the adaptivity of model and data endows the proposed approach with the advantage in the circumstances where large and unforeseen changes of system condition are inevitable.
Autors: Shiyang Li;Venkataramana Ajjarapu;Miodrag Djukanovic;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 701 - 713
Publisher: IEEE
 
» Adaptive Policy for Load Frequency Control
Abstract:
Till date, various load frequency control (LFC) schemes have been reported and every scheme has its own way of disturbance rejection capability. Utilizing some of them together may bring improved performance. Keeping this fact in mind, an adaptive control policy is proposed in this letter. The policy incorporates the concept of enhancing and lowering the controller activity by assigning them weights at every instance throughout the operation. Thus, there is no need to go for a new LFC scheme until required, and a guaranteed improved performance would be achieved. Different case studies including single and multi-area power systems have been conducted to verify the accuracy and efficiency of the proposed method.
Autors: Sandeep Hanwate;Yogesh V. Hote;Sahaj Saxena;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1142 - 1144
Publisher: IEEE
 
» Adaptive Relay Selection and Power Allocation for OFDM Cooperative Underwater Acoustic Systems
Abstract:
The increasing use of relays in underwater acoustic (UWA) communications is a driving force to explore efficient techniques that can significantly improve the system performance. To fully exploit the benefits of cooperative systems, efficient management of resources including relays and power is required. In this paper, both optimal relay selection and power loading issues are investigated for an orthogonal frequency division multiplexing (OFDM) cooperative transmission over UWA channel. In our analysis, we consider amplify-and-forward (AF) relaying with perfect channel state information (CSI) at the source, relay, and destination nodes. Moreover, we assume sparse and frequency-selective Rician fading in the presence of colored Gaussian ambient noise. Unlike previous works on this topic, in our study, the power of noise is not identical for all subcarriers at both the relay and destination nodes. We solve two optimization problems that rely on the minimization of the bit error rate (BER) and maximization of the system capacity. In each problem, both optimal relay selection and power loading issues are addressed in two dependent phases. In the first phase, an unconstrained optimization problem is solved to determine the optimal relay out of multiple relays vertically located at different depths of water. We adopt all-subcarrier (AS) basis approach in our OFDM-based transmission model in which a single relay is engaged to transmit the entire OFDM block to the destination. In the second phase, after selecting the optimal relay, another optimization problem is solved to obtain the optimal power allocation. This is jointly done at both the source and relay nodes under total power constraint and fixed subcarrier rate. Extensive simulations are conducted to evaluate the performance of proposed algorithms under different scenarios.
Autors: Abdollah Doosti-Aref;Ataollah Ebrahimzadeh;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 1 - 15
Publisher: IEEE
 
» Adaptive Resource Allocation and Provisioning in Multi-Service Cloud Environments
Abstract:
In the current cloud business environment, the cloud provider (CP) can provide a means for offering the required quality of service (QoS) for multiple classes of clients. We consider the cloud market where various resources such as CPUs, memory, and storage in the form of Virtual Machine (VM) instances can be provisioned and then leased to clients with QoS guarantees. Unlike existing works, we propose a novel Service Level Agreement (SLA) framework for cloud computing, in which a price control parameter is used to meet QoS demands for all classes in the market. The framework uses reinforcement learning (RL) to derive a VM hiring policy that can adapt to changes in the system to guarantee the QoS for all client classes. These changes include: service cost, system capacity, and the demand for service. In exhibiting solutions, when the CP leases more VMs to a class of clients, the QoS is degraded for other classes due to an inadequate number of VMs. However, our approach integrates computing resources adaptation with service admission control based on the RL model. To the best of our knowledge, this study is the first attempt that facilitates this integration to enhance the CP's profit and avoid SLA violation. Numerical analysis stresses the ability of our approach to avoid SLA violation while maximizing the CP's profit under varying cloud environment conditions.
Autors: Ayoub Alsarhan;Awni Itradat;Ahmed Y. Al-Dubai;Albert Y. Zomaya;Geyong Min;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Jan 2018, volume: 29, issue:1, pages: 31 - 42
Publisher: IEEE
 
» ADP-MAC: An Adaptive and Dynamic Polling-Based MAC Protocol for Wireless Sensor Networks
Abstract:
Channel polling activity in MAC protocols of wireless sensor network (WSN) significantly governs energy, delay, and lifetime of the network, and therefore, it is required to adjust the polling intervals in accordance with the incoming traffic patterns. In this paper, an asynchronous duty-cycle-based MAC protocol: adaptive and dynamic polling-MAC (ADP-MAC) has been developed. This paper took a novel approach of switching the polling interval distribution of the receiver nodes by monitoring the co-efficient of variation of the incoming traffic. To represent different applications of WSN, constant-bit rate, Poisson, and Bursty arrivals have been used, whereas three types of polling distributions: deterministic, exponential, and dynamic have been studied. The performance parameters, such as energy, delay, and packet loss, are used to evaluate ADP-MAC against an established protocol synchronized channel polling-MAC (SCP-MAC). The major finding of this paper is that when the traffic arrival and polling interval distribution of ADP-MAC are in conformance, the performance in terms of both delay and energy turns out to be the best. Furthermore, ADP-MAC has been found to outperform SCP-MAC for each type of arrivals.
Autors: Shama Siddiqui;Sayeed Ghani;Anwar Ahmed Khan;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 860 - 874
Publisher: IEEE
 
» Advanced Boundary Electrode Modeling for tES and Parallel tES/EEG
Abstract:
This paper explores advanced electrode modeling in the context of separate and parallel transcranial electrical stimulation (tES) and electroencephalography (EEG) measurements. We focus on boundary condition-based approaches that do not necessitate adding auxiliary elements, e.g., sponges, to the computational domain. In particular, we investigate the complete electrode model (CEM) which incorporates a detailed description of the skin-electrode interface including its contact surface, impedance, and normal current distribution. The CEM can be applied for both tES and EEG electrodes which are advantageous when a parallel system is used. In comparison to the CEM, we test two important reduced approaches: the gap model (GAP) and the point electrode model (PEM). We aim to find out the differences of these approaches for a realistic numerical setting based on the stimulation of the auditory cortex. The results obtained suggest, among other things, that GAP and GAP/PEM are sufficiently accurate for the practical application of tES and parallel tES/EEG, respectively. Differences between CEM and GAP were observed mainly in the skin compartment, where only CEM explains the heating effects characteristic to tES.
Autors: Sampsa Pursiainen;Britte Agsten;Sven Wagner;Carsten H. Wolters;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 37 - 44
Publisher: IEEE
 
» Advanced Deep-Learning Techniques for Salient and Category-Specific Object Detection: A Survey
Abstract:
Object detection, including objectness detection (OD), salient object detection (SOD), and category-specific object detection (COD), is one of the most fundamental yet challenging problems in the computer vision community. Over the last several decades, great efforts have been made by researchers to tackle this problem, due to its broad range of applications for other computer vision tasks such as activity or event recognition, content-based image retrieval and scene understanding, etc. While numerous methods have been presented in recent years, a comprehensive review for the proposed high-quality object detection techniques, especially for those based on advanced deep-learning techniques, is still lacking. To this end, this article delves into the recent progress in this research field, including 1) definitions, motivations, and tasks of each subdirection; 2) modern techniques and essential research trends; 3) benchmark data sets and evaluation metrics; and 4) comparisons and analysis of the experimental results. More importantly, we will reveal the underlying relationship among OD, SOD, and COD and discuss in detail some open questions as well as point out several unsolved challenges and promising future works.
Autors: Junwei Han;Dingwen Zhang;Gong Cheng;Nian Liu;Dong Xu;
Appeared in: IEEE Signal Processing Magazine
Publication date: Jan 2018, volume: 35, issue:1, pages: 84 - 100
Publisher: IEEE
 
» Advanced Modeling Techniques [Book/Software Reviews]
Abstract:
The text covers both theoretical and practical aspects of behavioral modeling and DPD for RF PAs and wireless transmitters. It is authored by three highly respected researchers in the field. The book is organized into ten chapters. Each of the book’s chapters is complemented with software tools available through the Wiley website (www.wiley.com/go/Ghannouchi/Behavioral). The simulation software allows users to apply the theories presented in the book to solve real problems. This book will be a very valuable resource for design engineers, industrial engineers, applications engineers, postgraduate students, and researchers working on PA modeling, linearization, and design.
Autors: Anding Zhu;
Appeared in: IEEE Microwave Magazine
Publication date: Jan 2018, volume: 19, issue:1, pages: 112 - 114
Publisher: IEEE
 
» Agile Laser Beam Deflection With High Steering Precision and Angular Resolution Using Liquid Crystal Optical Phased Array
Abstract:
To improve the steering precision and angular resolution of liquid-crystal optical phased array, in this paper, we proposed a modified periodic phase controlled method to realize a continuous scanning with a constant angular resolution of less than 20 μrad, meanwhile, its precision is less than 5 μrad (rms). Also, another method we proposed is called subaperture coherence that can realize even better angular resolution less than 5 μrad, which is the limitation of our measurement instrument.
Autors: Xiangru Wang;Liang Wu;Caidong Xiong;Man Li;Qinggui Tan;Jiyang Shang;Shuanghong Wu;Qi Qiu;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 26 - 28
Publisher: IEEE
 
» Air-Quality Monitoring in an Urban Area in the Tropical Andes
Abstract:
Manizales is a tropical Andean city in Colombia that has obtained outstanding achievements in the continuous and effective monitoring of the air quality. This article describes the air-quality monitoring system of Manizales and its corresponding data center, which is a system designed to perform a periodic vigilance of the concentration of the main air contaminants. The structure of one data warehouse is explained, along with the components of monitoring networks, equipments, and technological tools and processes that allow the acquisition, storage, processing, and analysis of the air-quality data.
Autors: Liliana Romo-Melo;Beatriz Aristizabal;Mauricio Orozco-Alzate;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 34 - 39
Publisher: IEEE
 
» Airspace Collision Risk Hot-Spot Identification using Clustering Models
Abstract:
A key safety indicator for airspace is its collision risk estimate, which is compared against a target level of safety to provide a quantitative basis for judging the safety of operations in airspace. However, this quantitative basis fails to provide any insight regarding the magnitude, location, and timing of the risk of collision, distributed within a given airspace. In this paper, we propose a methodology for the identification of collision risk hot spots in a given airspace. The proposed methodology consists of processing air traffic data and developing traffic routes based on entry and exit points within the airspace. These routes and other flight information are then used to project air-traffic crossings and cluster potential collisions. The proposed method then estimates the collision risk for each identified cluster, culminating in risk assessment for the entire airspace. The model extends and adopts the state-of-the art clustering models, systemically identifies airspace collision risk hot spots, and further analyses hot spots by analyzing cluster features (number of points and contribution to overall risk) with flight levels and time of day. Experiments were conducted using one-month traffic data (25 440 flights) from Bahrain en-route airspace. By visualizing crossing points and clustering them in a 2-D geographic information system model we are able to identify collision risk hot spots, which contribute significantly to overall collision risk.
Autors: Minh-Ha Nguyen;Sameer Alam;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 48 - 57
Publisher: IEEE
 
» Algebraic Certificates of (Semi)Definiteness for Polynomials Over Fields Containing the Rationals
Abstract:
Sum of squares (SOS) decompositions for positive semidefinite polynomials are usually computed numerically, using convex optimization solvers. The precision of the decompositions can be improved by increasing the number of digits used in the computations, but, when the number of variables is greater than the length (i.e., the minimum number of squares needed for the decomposition) of the polynomial, it is difficult to obtain an exact SOS decomposition with the existing methods. A new algorithm, which works well in “almost all” such cases, is proposed here. The results of randomly generated experiments are reported to compare the proposed algorithm with those based on convex optimization.
Autors: Laura Menini;Corrado Possieri;Antonio Tornambè;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Jan 2018, volume: 63, issue:1, pages: 158 - 173
Publisher: IEEE
 
» Aliens From Planet Pittsburgh: How Two Young Roboticists From Carnegie Mellon Pioneered Digital Lighting
Abstract:
The show started at twilight. On a balmy evening last February outside Tasmania’s Museum of Old and New Art I sat spellbound, leaning back on a granite bench gazing up at a large white fiberglass canopy that floated several meters above my head. Light projected onto it began to gradually morph from one gorgeous hue to another. Lilac deepened to purple, then shifted to burnt orange, to chartreuse green, and on it went. Meanwhile, through a rectangular aperture cut in the middle of the canopy, the darkening sky seemed mysteriously to lose depth, becoming a flat plane of color that looked as if it had been painted on the ceiling. The interplay between artificial and natural light was hallucinatory: as the hue of the former changed, so apparently did that of the latter. In a silence punctured only by the raucous laughing of a pair of kookaburras the program shimmered on, ending after perhaps an hour, when the sky had become pitch black. A truly magical experience, one that I shall remember as long as I live (Figs. 13).
Autors: Bob Johnstone;
Appeared in: Proceedings of the IEEE
Publication date: Jan 2018, volume: 106, issue:1, pages: 201 - 208
Publisher: IEEE
 
» Aligning the Light Without Channel State Information for Visible Light Communications
Abstract:
The use of light-emitting diodes (LEDs) for ambient illumination leads to visible light communications (VLC) as a promising technology for providing both constant lighting and high-speed wireless services in indoor environments. Since multiple LED sources can be transmitted to several users, this scenario naturally forms a multiple-user multiple-input single-output system. In this sense, transmit precoding (TPC) schemes based on channel state information at the transmitter (CSIT) originally devised for radio-frequency (RF) systems have been proposed for their implementation in VLC. However, beyond providing CSIT or the need for cooperation among transmitters, which also result challenging in RF systems, there are several constraints such as the non-negativity of the transmitted signal or providing constant illumination that hamper the performance of TPC schemes in VLC. Considering these constraints, this paper explores the use of blind interference alignment (BIA) for achieving multiplexing gain without CSIT or cooperation among LED lights. To do that, we devise the concept of reconfigurable photodetector that allows switching among distinct and linearly independent channel responses. Simulation results show that the use of BIA in VLC systems schemes based on the proposed reconfigurable photodetector results suitable for VLC systems.
Autors: Máximo Morales-Céspedes;Martha Cecilia Paredes-Paredes;Ana García Armada;Luc Vandendorpe;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Jan 2018, volume: 36, issue:1, pages: 91 - 105
Publisher: IEEE
 
» Allocation of Frequency Control Reserves and Its Impact on Wear and Tear on a Hydropower Fleet
Abstract:
Power systems are making a transition from purely technical, centrally planned systems to market based, decentralized systems. The need for balancing power and frequency control reserves are increasing, partially due to variable renewable production, which gives an opportunity for new incomes but also a challenge in terms of changed modes of operation with risk for reduced lifetime for controllable power plants. This paper investigates how the allocation of a sold volume of frequency control reserves within a large hydropower production fleet can affect the costs of providing primary and secondary reserves, in terms of its impact on wear and fatigue, production losses, and the quality of the delivered frequency control. The results show that for primary control, low static gain in the governors results in poor quality and a large amount of load cycles of the units. High static gain, on the other hand, increases the production losses. The control work of the fleet can be reduced by using a proper balance of primary and secondary control gain on each unit, although the intuitive results from linear models exaggerate this effect. Automatic secondary control improves the system frequency quality but also increases the wear.
Autors: Linn Saarinen;Per Norrlund;Weijia Yang;Urban Lundin;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 430 - 439
Publisher: IEEE
 
» Always-On 12-nW Acoustic Sensing and Object Recognition Microsystem for Unattended Ground Sensor Nodes
Abstract:
This paper presents an ultra-low power acoustic sensing and object recognition microsystem for Internet of Things applications. The microsystem is targeted for unattended ground sensor nodes where long-term (decades) life time is desired without the need for battery replacement. The system incorporates an microelectromechanical systems microphone as a frontend sensor along with active circuitry to identify target objects. We introduce an algorithm-circuit cross optimization to realize a 12-nW stand-alone microsystem that integrates the analog frontend with the digital backend signal classifier. The frequency-domain analysis of target audio signals reveals that the system can operate with a relatively low bandwidth (<500 Hz) and SNR (>3 dB) which significantly relaxes power constraints on both analog frontend and digital backend circuits. To further relax the current requirement of the preceding amplifier, we propose an 8-bit SAR-analog-to-digital converter that is designed to have a highly reduced sampling capacitance (<50 fF). For the digital backend, we propose a feature extractor using the serialized tones-of-interest discrete Fourier transform, replacing a conventional high-power/area-consuming parallel feature extraction using the fast Fourier transform. This approach reduces area and thus leakage power which often dominates the overall power consumption. The proposed system successfully identifies a number of target objects including an electrical generator, a small car, and a truck with >95% reliability and consumes only 12 nW with continuous monitoring.
Autors: Seokhyeon Jeong;Yu Chen;Taekwang Jang;Julius Ming-Lin Tsai;David Blaauw;Hun-Seok Kim;Dennis Sylvester;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 261 - 274
Publisher: IEEE
 
» Amine-Functionalized Fe2O3–SiO2 Core–Shell Nanoparticles With Tunable Sizes
Abstract:
Iron oxide magnetic nanoparticles (MNPs) coated with uniform silica shell were synthesized through thermal decomposition and inverse microemulsion methods. The iron oxide MNPs were further coated with silica shells through hydrolysis reaction. For the resulting core–shell MNPs, size regulation of both the magnetic core and the porous shell were achieved, enabling the modulation of their magnetic properties and magnetic interactions. Core–shell MNPs were finally functionalized with amine groups, and immobilized on gold surface due to charge-neutral amine/gold interactions. It was observed that the immobilization process was enhanced under external magnetic field.
Autors: Yun Teng;Chengpeng Jiang;Antonio Ruotolo;Philip W. T. Pong;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 69 - 77
Publisher: IEEE
 
» Amplitude and Frequency Estimation of Exponentially Decaying Sinusoids
Abstract:
An online method for amplitude and frequency estimation of exponentially decaying sinusoids is proposed with a moving-window discrete Fourier transform (MWDFT) filter and frequency-locked loop. The tuned filter characteristics of MWDFT is modified into more flat characteristic around the center frequency with negative feedback, which increases the bandwidth of the filter. An adaptive sampling pulse adjustment mechanism is incorporated in the proposed structure for online estimation of frequency. Hence, the frequency error was exploited to achieve synchronization between in-phase component of MWDFT and input signal of estimation. The amplitude is estimated in online from the in-phase and quadrature-phase components of MWDFT. The performance of the proposed method is compared with the existing techniques and experimentally validated on single-link flexible manipulator system for the online estimation of frequency and amplitude of tip deflection signal. The experimental investigation prove that the proposed online technique performs well over the existing techniques.
Autors: Shikha Tomar;Parasuraman Sumathi;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 229 - 237
Publisher: IEEE
 
» An $E$ -Band Analog Predistorter and Power Amplifier MMIC Chipset
Abstract:
An analog predistorter and power amplifier (PA) MMIC chipset has been designed to improve the overall linearity for applications in wireless communication at the -band. The circuits have been implemented in a commercial 0.1 InGaAs pHEMT process. The PA delivers an output referred 1-dB gain compression (OP1 dB) of 24 dBm, saturated output power of 27 dBm, and OIP3 of 32 dBm between 71 and 76 GHz. In combination with the analog predistortion circuit, the combined chipset improves carrier to third-order intermodulation ratio by 20 dB at an average output power of 21 dBm and at the same time increasing the OP1 dB by 2 dB to 26 dBm.
Autors: Marcus Gavell;Göran Granström;Christian Fager;Sten E. Gunnarsson;Mattias Ferndahl;Herbert Zirath;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 31 - 33
Publisher: IEEE
 
» An 11-Bit 250-nW 10-kS/s SAR ADC With Doubled Input Range for Biomedical Applications
Abstract:
This paper presents a low-power, area-efficient 11-b single-ended successive-approximation-register (SAR) analog-to-digital converter (ADC) targeted for biomedical applications. The design features an energy-efficient switching technique with an error cancelling capacitor network. The input range is twice the reference voltage. The ADC’s loading of the previous stage is reduced by using a single-ended structure, and by eliminating the largest capacitor in the array. The common mode voltage of the input signal can be used as reference voltage. All building blocks were designed in subthreshold for power efficiency, with an asynchronous self-controlled SAR logic. The ADC was fabricated in 0.18 – CMOS 2P4M process. The measured peak SNDR was 60.5 dB, the SFDR was 72 dB, the DNL +0.6/−0.37 LSB, and the INL +0.94/−0.89 LSB. The total power consumption was 250 nW from 0.75-V supply voltage.
Autors: Mahmoud Sadollahi;Koichi Hamashita;Kazuki Sobue;Gabor C. Temes;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 61 - 73
Publisher: IEEE
 
» An 8-Gb 12-Gb/s/pin GDDR5X DRAM for Cost-Effective High-Performance Applications
Abstract:
The graphic DRAM interface standard GDDR5X is developed as an evolutionary extension to the widely available GDDR5. The implementation presented here achieves a data rate of 12 Gb/s/pin on a single-ended signaling interface with 32 IOs for a total memory bandwidth of 48 GB/s. The GDDR5X DRAM relies on the quad data rate operation enabled by a phase-locked loop (PLL), a receiver with a pre-amplifier in a dual-regulation loop and a one-tap digital feedback equalizer (DFE). To support lower performance modes, an additional GDDR5-like operation is provided, which bypasses the PLL. The interface is realized on a conventional high-volume DRAM process to provide a cost-efficient, discrete package 8-Gb DRAM for high-performance graphic cards and compute applications.
Autors: Martin Brox;Mani Balakrishnan;Martin Broschwitz;Cristian Chetreanu;Stefan Dietrich;Fabien Funfrock;Marcos Alvarez Gonzalez;Thomas Hein;Eugen Huber;Daniel Lauber;Milena Ivanov;Maksim Kuzmenka;Christian N. Mohr;Juan Ocon Garrido;Swetha Padaraju;Sven Pi
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 134 - 143
Publisher: IEEE
 
» An E-band Double-Balanced Subharmonic Mixer With High Conversion Gain and Low Power in 90-nm CMOS Process
Abstract:
In this letter, an E-band double-balanced subharmonic down conversion mixer is presented. The proposed mixer demonstrates a conversion gain (CG) of 5.3 ~ 9 dB at RF frequencies 70–88 GHz under local oscillator (LO) power −4 dBm. The input 1-dB compression power (IP1 dB) and the input third-order intercept point (IIP3) at RF frequency of 77 GHz are −13 and −3 dBm, respectively. The 2LO-to-RF isolations of RF frequencies 70–88 GHz are all better than 40 dB. The overall dc power consumption (dc bias with injecting LO power) is 5 mW. The mixer is fabricated in a TSMC 90-nm CMOS process and it occupies an area of 0.3195 mm2. By applying weak-inversion region to generate subharmonic mixing function and with the combination of LO gate-pumped operation and source-pumped operation, this proposed mixer achieves high CG and low LO power with low dc power consumption among the published subharmonic mixers.
Autors: Yi-Ching Wu;Huei Wang;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 70 - 72
Publisher: IEEE
 
» An f-P/Q Droop Control in Cascaded-Type Microgrid
Abstract:
In cascaded-type microgrid, the synchronization and power balance of distributed generators become two new issues that needs to be addressed urgently. To that end, an f-P/Q droop control is proposed in this letter, and its stability is analyzed as well. This proposed droop control is capable to achieve power balance under both resistive-inductive and resistive-capacitive loads autonomously. Compared with the inverse power factor droop control, an obvious advantage consists in extending the scope of application. Finally, the feasibility of the proposed method is verified by simulation results.
Autors: Yao Sun;Guangze Shi;Xing Li;Wenbin Yuan;Mei Su;Hua Han;Xiaochao Hou;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1136 - 1138
Publisher: IEEE
 
» An Achievable Throughput Scaling Law of Wireless Device-to-Device Caching Networks With Distributed MIMO and Hierarchical Cooperations
Abstract:
In this paper, we propose a new caching scheme for a random wireless device-to-device (D2D) network of nodes with local caches, where each node intends to download files from a prefixed library via D2D links. Our proposed caching delivery includes two stages, employing distributed MIMO and hierarchical cooperations, respectively. The distributed MIMO is applied to the first stage between source nodes and neighbors of the destination node. The induced multiplexing gain and diversity gain increase the number of simultaneous transmissions, improving the throughput of the network. The hierarchical cooperations are applied to the second stage to facilitate the transmissions between the destination node and its neighbors. The two stages together exploit spatial degrees of freedom as well as spatial reuse. We develop an uncoded random caching placement strategy to serve this cooperative caching delivery. Analytical results show that the average aggregate throughput of the network scales almost linearly with , with a vanishing outage probability. Furthermore, we derive an explicit expression of the optimal throughput as a function of system parameters, such as pathloss factor under a target outage probability. Analytical and numerical results demonstrate that our proposed scheme outperforms existing ones when the local cache size is limited.
Autors: Jiajia Guo;Jinhong Yuan;Jian Zhang;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Jan 2018, volume: 17, issue:1, pages: 492 - 505
Publisher: IEEE
 
» An Actively Detuned Wireless Power Receiver With Public Key Cryptographic Authentication and Dynamic Power Allocation
Abstract:
This paper presents a CMOS resonant wireless charging receiver with an active detuning mechanism for controlling the received power, without using any passive components being switched in and out. This detuning mechanism is first combined with an on-chip elliptic curve accelerator that achieves /elliptic curve scalar multiplication and in-band telemetry for authenticating a wireless charger using elliptic curve cryptography, with up to rejection at the output of the receiver. Second, equitable power distribution between two receivers coupled to the same charger is demonstrated by controlled detuning of the closer receiver. The system can overcome up to a 4:1 asymmetry in distance to the charger between two receivers. Implemented in 0.18- CMOS, the receiver IC delivers 520-mW peak output power and 74% peak end-to-end efficiency in the tuned mode.
Autors: Nachiket Desai;Chiraag Juvekar;Shubham Chandak;Anantha P. Chandrakasan;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 236 - 246
Publisher: IEEE
 
» An Adaptively Truncated Clutter-Statistics-Based Two-Parameter CFAR Detector in SAR Imagery
Abstract:
Traditional constant false alarm rate (CFAR) detectors suffer probability of detection (PD) degradation influenced by the outliers such as interfering ship targets, side lobes, and ghosts, especially in crowded harbors and busy shipping lines. In this paper, a new two-parameter CFAR detector based on adaptively truncated clutter statistics (TS-LNCFAR) is proposed. The new two-parameter CFAR detector uses log-normal as the statistical model; by adaptive-threshold-based clutter truncation in the background window, the outliers are removed from the clutter samples, while the real clutter is preserved to the largest degree. The log-normal model is accurately built using the truncated clutter statistics through the maximum-likelihood estimator. Compared with traditional CFAR detectors, the parameter estimation is more accurate, and TS-LNCFAR has a better false alarm regulation property and a high PD in a multiple-target environment. Furthermore, the parameter estimation and threshold calculation do not need iterative numerical calculation, and TS-LNCFAR has a high computational efficiency. The superiority of the proposed TS-LNCFAR detector is validated on the multilook Envisat-ASAR and TerraSAR-X data.
Autors: Jiaqiu Ai;Xuezhi Yang;Jitao Song;Zhangyu Dong;Lu Jia;Fang Zhou;
Appeared in: IEEE Journal of Oceanic Engineering
Publication date: Jan 2018, volume: 43, issue:1, pages: 267 - 279
Publisher: IEEE
 
» An Algorithm of an X-ray Hit Allocation to a Single Pixel in a Cluster and Its Test-Circuit Implementation
Abstract:
An on-chip implementable algorithm for allocation of an X-ray photon imprint, called a hit, to a single pixel in the presence of charge sharing in a highly segmented pixel detector is described. Its proof-of-principle implementation is also given supported by the results of tests using a highly collimated X-ray photon beam from a synchrotron source. The algorithm handles asynchronous arrivals of X-ray photons. Activation of groups of pixels, comparisons of peak amplitudes of pulses within an active neighborhood and finally latching of the results of these comparisons constitute the three procedural steps of the algorithm. A grouping of pixels to one virtual pixel, that recovers composite signals and event driven strobes, to control comparisons of fractional signals between neighboring pixels are the actuators of the algorithm. The circuitry necessary to implement the algorithm requires an extensive inter-pixel connection grid of analog and digital signals, that are exchanged between pixels. A test-circuit implementation of the algorithm was achieved with a small array of pixels and the device was exposed to an 8 keV highly collimated to a diameter of 3- X-ray beam. The results of these tests are given in this paper assessing physical implementation of the algorithm.
Autors: Grzegorz W. Deptuch;Farah Fahim;Paweł Gryboś;Jim Hoff;Scott Holm;Piotr Maj;David Peter Siddons;Piotr Kmon;Marcel Trimpl;Tom Zimmerman;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Jan 2018, volume: 65, issue:1, pages: 185 - 197
Publisher: IEEE
 
» An Analog-Assisted Tri-Loop Digital Low-Dropout Regulator
Abstract:
This paper presents an analog-assisted (AA) output-capacitor-free digital low-dropout (D-LDO) regulator with tri-loop control. For responding to instant load transients, the proposed high-pass AA loop momentarily adjusts the unit current of the power switch array, and significantly reduces the voltage spikes. In the proposed D-LDO, the overall 512 output current steps are divided into three sub-sections controlled by coarse/fine loops with carry-in/out operations. Therefore, the required shift register (SR) length is reduced, and a 9-bit output current resolution is realized by using only 28-SR bits. Besides, the coarse-tuning loop helps to reduce the recovery time, while the fine-tuning loop improves the output accuracy. To eliminate the limit cycle oscillation and reduce the quiescent current, a freeze mode is added after the fine-tuning operation. To reduce the output glitches and the recovery time, a nonlinear coarse word control is designed for the carry-in/out operations. The D-LDO is fabricated in a 65-nm general purpose CMOS process. A maximum voltage undershoot/overshoot of 105 mV is measured with a 10-mA/1-ns load step and a total capacitor of only 100 pF. Thus, the resulting figure-of-merit is 0.23 ps.
Autors: Mo Huang;Yan Lu;Seng-Pan U;Rui P. Martins;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 20 - 34
Publisher: IEEE
 
» An Analytical Model to Characterize the Spatiotemporal Propagation of Information Under Vehicle-to-Vehicle Communications
Abstract:
Modeling the spatiotemporal propagation characteristics of information under vehicle-to-vehicle communications is critical for developing information-enabled applications to improve traffic safety and mobility. Existing analytical approaches assume instantaneous information flow propagation to simplify the communication constraints arising from the traffic flow dynamics. Consequently, information flow propagation characteristics such as the information flow propagation wave have not been analyzed. They are necessary to describe the interactions with the underlying traffic flow dynamics. An analytical model, which integrates an epidemic model with a traffic flow model, is developed to account for such interactions. The proposed model is able to capture the dynamics of information flow and traffic flow in an integrated formulation that circumvents key analytical and numerical challenges. Results from computational experiments demonstrate the effectiveness of the proposed model and its ability to describe the dynamic characteristics of information flow propagation along with the traffic flow dynamics.
Autors: Yong Hoon Kim;Srinivas Peeta;Xiaozheng He;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Jan 2018, volume: 19, issue:1, pages: 3 - 12
Publisher: IEEE
 
» An Architecture for Large-Area Sensor Acquisition Using Frequency-Hopping ZnO TFT DCOs
Abstract:
Hybrid systems combine large-area electronics (LAE) with silicon-CMOS ICs for sensing and computation, respectively. In such systems, interfacing a large number of distributed LAE sensors with the CMOS domain poses a key limitation. This paper presents an architecture that aims to greatly reduce both the number of physical connections and the time for accessing all of the sensors. Each sensor modulates the amplitude of a thin-film transistor (TFT) digitally controlled oscillator (DCO). All DCO outputs are combined, but each follows a unique frequency-hopping pattern (controlled by a code from CMOS), allowing recovery of the individual sensors. The architecture enables much greater scalability of sensors for a given number of connections than active-matrix and binary-addressing schemes. For demonstration, an 18-element large-area force-sensing system is demonstrated based on zinc-oxide (ZnO) TFT DCOs with a frequency-hopping rate of 4.2 kHz. Acquisition error 62 mVrms is achieved over 30 weight patterns.
Autors: Yasmin Afsar;Tiffany Moy;Nicholas Brady;Sigurd Wagner;James C. Sturm;Naveen Verma;
Appeared in: IEEE Journal of Solid-State Circuits
Publication date: Jan 2018, volume: 53, issue:1, pages: 297 - 308
Publisher: IEEE
 
» An Area-Efficient BIRA With 1-D Spare Segments
Abstract:
The growing capacity and density of embedded memories increases the probability of defects and affects the yield. To improve the yield, built-in redundancy analysis (BIRA) has been developed to replace faulty cells with healthy redundant cells. BIRA requires a high repair rate and a feasible hardware size for implementation. Although many BIRAs have been proposed, most of them still demonstrate a low repair rate or a large required hardware size. The proposed BIRA employs an intuitive algorithm with a small-area analyzer that uses 1-D spare segments in the 2-D spare structure. Because most faults in the memory are single faults, spare segments can be used to efficiently allocate redundancies. In terms of the yield, 1-D spare segments are effective when used with an intuitive algorithm that can be implemented with a small hardware overhead. Experimental results show that the proposed BIRA has a higher repair rate and relatively low hardware overhead than state-of-the-art BIRAs and has the advantages of 1-D spare segments.
Autors: Donghyun Kim;Hayoung Lee;Sungho Kang;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 206 - 210
Publisher: IEEE
 
» An Autonomous Intelligent Music Teacher
Abstract:
The attempted combination of music and artificial intelligence (AI) has been viewed as the jamming together of two puzzle pieces that are not meant to fit together. It is the opinion of some musicians that music is a purely human feat, a proficiency that computers will never be able to achieve. Several members of the AI community, however, have fought this mindset with their belief that music is, in more ways than one, founded on mathematics. What computers lack in emotions, they make up for with computational capabilities.
Autors: Lavanya Aprameya;
Appeared in: IEEE Potentials
Publication date: Jan 2018, volume: 37, issue:1, pages: 10 - 14
Publisher: IEEE
 
» An Effective Compressed-Sensing Inspired Deterministic Algorithm for Sparse Array Synthesis
Abstract:
The aim of this paper is to discuss a novel technique for sparse array synthesis. The synthesis strategy is based on a sparse-forcing algorithm using an improvement of the reweighted minimization proposed in the framework of the compressed-sensing literature, specifically modified in order to tailor both linear and conformal array synthesis problems. The numerical examples show that the proposed algorithm improves the results provided by concurrent techniques, reducing the number of radiating elements and/or the computational effort.
Autors: Daniele Pinchera;Marco Donald Migliore;Fulvio Schettino;Mario Lucido;Gaetano Panariello;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Jan 2018, volume: 66, issue:1, pages: 149 - 159
Publisher: IEEE
 
» An Efficient and Reconfigurable Synchronous Neuron Model
Abstract:
This brief presents a reconfigurable and efficient 2-D neuron model capable of extending to higher dimensions. The model is applied to the Izhikevich and FitzHugh-Nagumo neuron models as 2-D case studies and to the Hindmarsh-Rose model as a 3-D case study. Hardware synthesis and physical implementations show that the resulting circuits can reproduce neural dynamics with acceptable precision and considerably low hardware overhead compared to previously published piecewise linear models.
Autors: Hamid Soleimani;E. M. Drakakise;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 91 - 95
Publisher: IEEE
 
» An Efficient Channel Scanning Scheme With Dual-Interfaces for Seamless Handoff in IEEE 802.11 WLANs
Abstract:
In this letter, we propose an efficient channel scanning scheme for IEEE 802.11 WLANs to reduce the handoff delay. The proposed scheme is fundamentally different from existing channel scanning schemes in that access points (APs), not mobile stations, switch channels. Specifically, each AP is equipped with dual wireless network interfaces, one of which is used for normal AP operations and the other is dedicated to the channel scanning assistance. In this circumstance, mobile stations do not perform active scans and stay on their operating channel, while APs switch channels and broadcast beacon frames by using the additional interface. Thus, mobile stations can maintain up-to-date information on neighboring APs without scanning other channels. Consequently, the service disruption during channel scanning is eliminated and the quality of ongoing data communication is not degraded. Our performance evaluation results show that the proposed scheme outperforms existing channel scanning schemes.
Autors: Jae-Pil Jeong;Young Deok Park;Young-Joo Suh;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 169 - 172
Publisher: IEEE
 
» An Efficient Fault-Tolerance Design for Integer Parallel Matrix–Vector Multiplications
Abstract:
Parallel matrix processing is a typical operation in many systems, and in particular matrix–vector multiplication (MVM) is one of the most common operations in the modern digital signal processing and digital communication systems. This paper proposes a fault-tolerant design for integer parallel MVMs. The scheme combines ideas from error correction codes with the self-checking capability of MVM. Field-programmable gate array evaluation shows that the proposed scheme can significantly reduce the overheads compared to the protection of each MVM on its own. Therefore, the proposed technique can be used to reduce the cost of providing fault tolerance in practical implementations.
Autors: Zhen Gao;Qingqing Jing;Yumeng Li;Pedro Reviriego;Juan Antonio Maestro;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 211 - 215
Publisher: IEEE
 
» An Efficient Prediction-Based User Recruitment for Mobile Crowdsensing
Abstract:
Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their smart devices to cooperatively perform a large-scale sensing job. One of the users’ main concerns is the cost of data uploading, which affects their willingness to participate in a crowdsensing task. In this paper, we propose an efficient Prediction-based User Recruitment for mobile crowdsEnsing (PURE), which separates the users into two groups corresponding to different price plans: Pay as you go (PAYG) and Pay monthly (PAYM). By regarding the PAYM users as destinations, the minimizing cost problem goes to recruiting the users that have the largest contact probability with a destination. We first propose a semi-Markov model to determine the probability distribution of user arrival time at points of interest (PoIs) and then get the inter-user contact probability. Next, an efficient prediction-based user-recruitment strategy for mobile crowdsensing is proposed to minimize the data uploading cost. We then propose PURE-DF by extending PURE to a case in which we address the tradeoff between the delivery ratio of sensing data and the recruiter number according to Delegation Forwarding. We conduct extensive simulations based on three widely-used real-world traces: roma/taxi, epfl, and geolife. The results show that, compared with other recruitment strategies, PURE achieves a lower recruitment payment and PURE-DF achieves the highest delivery efficiency.
Autors: En Wang;Yongjian Yang;Jie Wu;Wenbin Liu;Xingbo Wang;
Appeared in: IEEE Transactions on Mobile Computing
Publication date: Jan 2018, volume: 17, issue:1, pages: 16 - 28
Publisher: IEEE
 
» An Efficient Structure of Marx Generator Using Buck–Boost Converter
Abstract:
In this paper, a new structure of Marx generator (MG) based on buck–boost converter is proposed to generate high-voltage pulses. In this structure, a single-phase inverter is employed to supply parallel diode–capacitor units by positive and negative values of the input dc source (). The main contribution of this paper is proposing a new switching strategy, by which a group of capacitors are charged properly. Finally, the charged capacitors are connected in series such that the output voltage is equal to summation of the capacitors’ voltages. Considering specified value of the output voltage, the number of circuit elements in the proposed structure is reduced in comparison with other topologies of unipolar MG. Furthermore, voltage rating of switches and diodes in the proposed topology is lower than that of other unipolar MG structures. Design of the structure ensures that there is no need to connect the switches in series, when the number of stages is increased. To verify the performance of the proposed MG structure, simulation has been carried out in MATLAB/Simulink. Furthermore, a prototype of the proposed structure has been implemented in the lab. The simulation and experimental results confirm the capability of the structure for generating high-voltage pulses.
Autors: Mehdi Taherian;Mehdi Allahbakhshi;Ebrahim Farjah;Hadi Givi;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Jan 2018, volume: 46, issue:1, pages: 117 - 126
Publisher: IEEE
 
» An Embedded Real-Time Processing Platform for Optogenetic Neuroprosthetic Applications
Abstract:
Optogenetics offers a powerful new approach for controlling neural circuits. It has numerous applications in both basic and clinical science. These applications require stimulating devices with small processors that can perform real-time neural signal processing, deliver high-intensity light with high spatial and temporal resolution, and do not consume a lot of power. In this paper, we demonstrate the implementation of neuronal models in a platform consisting of an embedded system module and a portable digital light processing projector. As a replacement for damaged neural circuitry, the embedded module processes neural signals and then directs the projector to optogenetically activate a downstream neural pathway. We present a design in the context of stimulating circuits in the visual system, but the approach is feasible for a broad range of biomedical applications.
Autors: Boyuan Yan;Sheila Nirenberg;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Jan 2018, volume: 26, issue:1, pages: 233 - 243
Publisher: IEEE
 
» An Energy Efficient Schedule for IEEE 802.15.4/ZigBee Cluster Tree WSN with Multiple Collision Domains and Period Crossing Constraint
Abstract:
Cluster scheduling respecting collision avoidance is a complex problem in cluster-tree wireless sensor networks (WSNs). The difficulty of the problem also increases significantly when the traffic is organized as time-constrained data flows with opposite directions. Thus, in this paper, we seek a collision-free cluster schedule that meets all the data flow deadlines as given in time units. In this context, we have found an elegant approach that expresses the deadline of each flow as an integer number of the length of the schedule period (i.e., period crossing constraints). Consequently, the data flow timeliness requirements become easier to be tackled. Due to the scarce resources of the WSNs, the minimization of the energy consumption of the nodes is a problem of paramount importance. Therefore, the objective is to maximize the lifetime of the network by maximizing the time when the nodes stay in low-power mode. In this paper, we present a novel heuristic scheduling algorithm to obtain the desired schedule. The algorithm is based on very interesting formulations of graph theory problems. Thus, it is efficient in both computational time (instances with thousands of devices are solved in a short time) and solution quality (evaluated over smaller size instances while comparing it with optimal solutions obtained by integer linear programming).
Autors: Aasem Ahmad;Zdeněk Hanzálek;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Jan 2018, volume: 14, issue:1, pages: 12 - 23
Publisher: IEEE
 
» An Energy-Efficient DAC Switching Method for SAR ADCs
Abstract:
This brief presents a capacitor switching technique to reduce the power consumption in successive approximation register (SAR) analog-to-digital converters (ADCs). The proposed method ideally does not consume any switching energy in digital-to-analog converter and for a 10-bit ADC; it achieves 87% reduction in the total capacitor area compared to the conventional SAR ADC. In addition, the accuracy of the proposed SAR ADC does not depend on the accuracy of the mid-level reference voltage (). Moreover, the common-mode input voltage of the comparator will remain constant. The proposed ADC is simulated in a 90-nm CMOS technology with sampling rate of 100 kS/s and resolution of 10-bit. The simulation results achieve an 8.5 effective number of bits with about 0.5- power consumption resulting in a FoM of 9.76 fJ/conversion-step.
Autors: Tayebeh Yousefi;Alireza Dabbaghian;Mohammad Yavari;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Jan 2018, volume: 65, issue:1, pages: 41 - 45
Publisher: IEEE
 
» An Energy-Efficient Programmable Manycore Accelerator for Personalized Biomedical Applications
Abstract:
Wearable personalized health monitoring systems can offer a cost-effective solution for human health care. These systems must constantly monitor patients’ physiological signals and provide highly accurate, and quick processing and delivery of the vast amount of data within a limited power and area footprint. These personalized biomedical applications require sampling and processing multiple streams of physiological signals with a varying number of channels and sampling rates. The processing typically consists of feature extraction, data fusion, and classification stages that require a large number of digital signal processing (DSP) and machine learning (ML) kernels. In response to these requirements, in this paper, a tiny, energy-efficient, and domain-specific manycore accelerator referred to as power-efficient nanoclusters (PENC) is proposed to map and execute the kernels of these applications. Simulation results show that the PENC is able to reduce energy consumption by up to 80% and 25% for DSP and ML kernels, respectively, when optimally parallelized. In addition, we fully implemented three compute-intensive personalized biomedical applications, namely, multichannel seizure detection, multiphysiological stress detection, and standalone tongue drive system (sTDS), to evaluate the proposed manycore performance relative to commodity embedded CPU, graphical processing unit (GPU), and field-programmable gate array (FPGA)-based implementations. For these three case studies, the energy consumption and the performance of the proposed PENC manycore, when acting as an accelerator along with an Intel Atom processor as a host, are compared with the existing commercial off-the-shelf general-purpose, customizable, and programmable embedded platforms, including Intel Atom, Xilinx Artix-7 FPGA, and NVIDIA TK1 advanced RISC machine -A15 and K1 GPU system on a chip. For these applications, the PENC manycore is able to sign- ficantly improve throughput and energy efficiency by up to and , respectively. For the most computational intensive application of seizure detection, the PENC manycore is able to achieve a throughput of 15.22 giga-operations-per-second (GOPs), which is a improvement in throughput over custom FPGA solution. For stress detection, the PENC achieves a throughput of 21.36 GOPs and an energy efficiency of 4.23 GOP/J, which is and better over FPGA implementation, respectively. For the sTDS application, the PENC improves a throughput by and an energy efficiency by over FPGA implementation.
Autors: Adwaya Kulkarni;Adam Page;Nasrin Attaran;Ali Jafari;Maria Malik;Houman Homayoun;Tinoosh Mohsenin;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 96 - 109
Publisher: IEEE
 
» An Error Model for Mapping Forest Cover and Forest Cover Change Using L-Band SAR
Abstract:
We present an error model for forest cover mapping and change detection with L-band synthetic aperture radar (SAR), which considers measurement noise, forest height, number of images available, and imaging conditions. When applied to a multiseasonal set of Advanced Land Observing Satellite Phased-Array type L-band SAR images acquired over a forest site in southern Sweden, the error model, which is founded on a semiempirical model, suggests that a bitemporal set of cross-polarized L-band backscatter observations is sufficient to detect a forest cover loss of 50% at hectare scale for mature forests. The error probability increases when using co-polarization images, images acquired under adverse imaging conditions, or when detecting forest cover change in a forest of low height. The availability of multitemporal L-band observations is expected to improve forest cover retrieval and change detection, albeit highly correlated forest cover retrieval errors between images acquired within narrow time intervals (e.g., months) pose a limit on the improvements that can be achieved.
Autors: Oliver Cartus;Paul Siqueira;Josef Kellndorfer;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 107 - 111
Publisher: IEEE
 
» An Explicit Non-Malleable Extraction Scheme for Quantum Randomness Amplification With Two Untrusted Devices
Abstract:
Quantum random number is a particularly important physical resource both for quantum communication and quantum cryptography. Quantum randomness amplification, as a key technology in quantum random number generation, has a significant counterintuitive effect: one can amplify weak randomness to almost perfect randomness by quantum systems, which is impossible in classical cryptography. In this letter, we propose an explicit quantum randomness amplification scheme with two untrusted devices, from which we could extract one single perfect random bit from weak random bits. An explicit non-malleable two-source extractor is introduced to extract perfect randomness from two independent min-entropy sources, which are derived from a Bell test with two untrusted devices. The universally composable security of the proposed protocol is proved.
Autors: Mingfeng Xu;Wei Pan;Lianshan Yan;Bin Luo;Xihua Zou;Liyue Zhang;Penghua Mu;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 85 - 88
Publisher: IEEE
 
» An Extended IEEE 118-Bus Test System With High Renewable Penetration
Abstract:
This article describes a new publicly available version of the IEEE 118–bus test system, named NREL-118. The database is based on the transmission representation (buses and lines) of the IEEE 118-bus test system, with a reconfigured generation representation using three regions of the US Western Interconnection from the latest Western Electricity Coordination Council (WECC) 2024 Common Case [Transmission expansion planning home and GridView WECC database]. Time-synchronous hourly load, wind, and solar time series are provided for one year. The public database presented and described in this manuscript will allow researchers to model a test power system using detailed transmission, generation, load, wind, and solar data. This database includes key additional features that add to the current IEEE 118-bus test model, such as the inclusion of ten generation technologies with different heat rate functions, minimum stable levels and ramping rates, GHG emissions rates, regulation and contingency reserves, and hourly time series data for one full year for load, wind, and solar generation.
Autors: Ivonne Peña;Carlo Brancucci Martinez-Anido;Bri-Mathias Hodge;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 281 - 289
Publisher: IEEE
 
» An Extension of Reduced Disjunctive Model for Multi-Stage Security-Constrained Transmission Expansion Planning
Abstract:
This letter presents an extension of reduced disjunctive model to consider N-1 criterion in multi-stage transmission expansion planning (TEP). This extension is realized by exactly linearizing nonlinear terms induced by N-1 contingency constraints. Compared with the traditional approach, the extended RDM reduces the number of binary variables and constraints. Numerical results of three test systems indicate that the proposed approach significantly improves the computational performance without sacrificing the optimality of TEP problem.
Autors: Yao Zhang;Jianxue Wang;Yunhao Li;Xiuli Wang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1092 - 1094
Publisher: IEEE
 
» An FPGA-Based Phase Measurement System
Abstract:
Phase measurement is required in electronic applications where a synchronous relationship between the signals needs to be preserved. Traditional electronic systems used for time measurement are designed using a classical mixed-signal approach. With the advent of reconfigurable hardware such as field-programmable gate arrays (FPGAs), it is more advantageous for designers to opt for all-digital architecture. Most high-speed serial transceivers of the FPGA circuitry do not ensure the same chip latency after each power cycle, reset cycle, or firmware upgrade. These cause uncertainty of phase relationship between the recovered signals. To address the need to register minute phase shift changes inside an FPGA, we propose a design for phase measurement logic core having resolution and precision in the range of a few picoseconds. The working principle is based on subsample accumulation using systematic sampling over the phase detector signal. The phase measurement logic can operate over a wide range of digital clock frequencies, ranging from a few kilohertz to the maximum frequency that is supported within the FPGA fabric. A mathematical model is developed to illustrate the operating principle of the design. The VLSI architecture is designed for the logic core. We also discussed the procedure of the phase measurement system, the calibration sequence involved, followed by the performance of the design in terms of accuracy, precision, and resolution.
Autors: Jubin Mitra;Tapan K. Nayak;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 133 - 142
Publisher: IEEE
 
» An FPGA-Based Test System for RRAM Technology Characterization
Abstract:
Resistive random access memory (RRAM) technologies have recently gained large attention from the academic and industrial research communities. Significant efforts have been made to enhance the performance of the memory stacks from both communities through the design, simulation, and fabrication of novel devices. In this context, improvements can only be confirmed through a thorough device characterization process. Here comes a gap between industry and academia that usually lacks high-end test equipment to perform systematic device characterizations. In this paper, we propose a solution to fill this gap by introducing an easy, affordable, and effective field programmable gate array based RRAM characterization system.
Autors: Armando Biscontini;Maxime Thammasack;Giovanni De Micheli;Pierre-Emmanuel Gaillardon;
Appeared in: IEEE Transactions on Nanotechnology
Publication date: Jan 2018, volume: 17, issue:1, pages: 177 - 183
Publisher: IEEE
 
» An Imprecise Stopping Criterion Based on In-Between Layers Partial Syndromes
Abstract:
In this letter, we address the issue of early stopping criterion for layered LDPC decoders, aiming at more safeness with low hardware cost and minimum latency. We introduce a new on-the-fly measure in the decoder, called in-between layers partial syndrome, and define a family of stopping criteria, with different tradeoffs among complexity, latency, and performance. Numerical results show that our stopping criteria surpass existing solutions, and can be as safe as the full-syndrome detection, down to frame error rates (FERs) as low as FER = .
Autors: D. Declercq;V. Savin;O. Boncalo;F. Ghaffari;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 13 - 16
Publisher: IEEE
 
» An Improved Genetic Algorithm for Multiobjective Optimization of Helical Coil Electromagnetic Launchers
Abstract:
Helical coil electromagnetic launchers (HEMLs) using motion-induced commutation strategy solve the problem of synchronization control perfectly. HEMLs have the advantages of symmetric structure, high load impedance, and high energy conversion efficiency. If the structural and launch parameters can be designed reasonably and multiobjective optimization of the velocity, efficiency, and power can be achieved, HEMLs can meet the requirements of multimission applications such as the high-velocity coilgun, electromagnetic mortar, and electromagnetic catapult. In this paper, an improved adaptive genetic algorithm (AGA) based on the solution-reservation strategy to solve the multiobjective optimization problem for HEMLs is presented. The circuit model of the HEML is established and the governing equations are derived. The circuit parameters such as projectile mass, resistance, inductance, and inductance gradient are calculated according to the structural parameters of coils. The classical Runge–Kutta method and the trapezoidal quadrature formula are used to solve the governing equations, besides deriving the velocity, efficiency, and power of the launcher. The AGA is developed in MATLAB. The range of the launch voltage U is 500–5000 V and the number of turns N in coils is 1–500. After the evolution of 14 generations, five noninferior solutions subject to the constraints of temperature rise, launch time, and length are obtained. These different HEML structures can satisfy many different launch applications.
Autors: Dong Yang;Zhenxiang Liu;Ting Shu;Lijia Yang;Jianming Ouyang;Zhi Shen;
Appeared in: IEEE Transactions on Plasma Science
Publication date: Jan 2018, volume: 46, issue:1, pages: 127 - 133
Publisher: IEEE
 
» An Improved Polymer Shell Encapsulated Fiber Laser Hydrophone
Abstract:
Fiber laser hydrophones engineered either with a direct polymer coating over the laser or a coating over a mechanically enclosed laser have many practical limitations. Notably, damages can occur due to the differential strain and the complexity involved in the fabrication of the mechanical enclosure and micropositioning it over the laser. This paper proposes a simpler fiber laser hydrophone encapsulated in a polymer shell with enhanced sensitivity and broad bandwidth. The significant factors that influence the hydrophone and its acoustic performance are studied in detail using a 2-D-axisymmetric finite-element analysis (FEA) and analytical methods. The obtained experimental results are found to corroborate those of the analytical and FEA methods. The method of fabricating the hydrophones and the measurements are found to be repeatable. A sensitivity of −155 dB ref. 1 V/Pa with a bandwidth of 6 kHz was obtained from our experiments and can further be tuned to the requirements.
Autors: K. Vivek;R. Rajesh;C. V. Sreehari;T. Santhanakrishnan;S. Sham Kumar;T. V. Praveen;R. S. Arun Sundar;K. P. B. Moosad;
Appeared in: IEEE Sensors Journal
Publication date: Jan 2018, volume: 18, issue:2, pages: 589 - 595
Publisher: IEEE
 
» An Improved Real-Time Short-Term Voltage Stability Monitoring Method Based on Phase Rectification
Abstract:
In this letter, an improved real-time, short-term voltage stability monitoring method is introduced. The impact of voltage magnitude oscillation on the calculation of the Lyapunov exponent is analyzed, and a phase rectification method to eliminate the negative influence of oscillation is proposed. The simulation work was conducted on the provincial power grid at Guangdong in China. Based on our simulation results, the proposed method is expected to improve the effectiveness of short-term voltage stability monitoring.
Autors: Huaichang Ge;Qinglai Guo;Hongbin Sun;Bin Wang;Boming Zhang;Junlei Liu;Yinguo Yang;Feng Qian;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 1068 - 1070
Publisher: IEEE
 
» An Information Bottleneck Approach to Optimize the Dictionary of Visual Data
Abstract:
In this paper, we propose a novel information theoretic approach to obtain compact and discriminative dictionary of visual data. This approach squeezes discriminative information from the dictionary for efficient representation using information bottleneck. The dictionary is optimized from the initial sparse dictionary, which is learned from action data. In this, a constraint information optimization problem is formulated in which mutual information between the initial and optimized dictionary is minimized while maximizing mutual information between optimized dictionary and class labels. We use an effective similarity measure, Jensen–Shannon divergence with adaptive weightages, for class distributions of each dictionary atom. These adaptive weightages are obtained based on the usage of the dictionary atom among different classes. The resultant dictionary becomes discriminative and compact, while retaining maximum information with fewer atoms. Using simple reconstruction error, we test computational efficiency of the proposed method without compromising classification accuracy on popular benchmark datasets. It is further demonstrated how efficiently discriminative information is retained by comparing the classification performance of the dictionary before and after the removal of redundant dictionary atoms.
Autors: Shyju Wilson;C. Krishna Mohan;
Appeared in: IEEE Transactions on Multimedia
Publication date: Jan 2018, volume: 20, issue:1, pages: 96 - 106
Publisher: IEEE
 
» An InGaN/GaN MQWs Solar Cell Improved By a Surficial GaN Nanostructure as Light Traps
Abstract:
The InGaN/GaN multi-quantum-wells (MQWs) solar cells employing the surficial GaN nanostructure as light traps were investigated. The performance of the InGaN/GaN MQWs solar cell with nano holes surface shows an obvious advantage over that with nano poles, much less than the planar one. From the measurements of EQE and photoluminescence spectra, the enhancement of photoelectric response contributes to the device performances. Because the effective light absorption is increased, the conversion efficiency significantly improves from 1.02% (planar surface) up to 2.235% (nano holes surface). Although the performance is still low, it is exactly an effective method to enhance the conversion efficiency via introducing nanostructures on the surface of the InGaN/GaN MQWs cells.
Autors: Zhen Bi;Daniel Bacon-Brown;Fengyu Du;Jinfeng Zhang;Shengrui Xu;Peixian Li;Jincheng Zhang;Yiping Zhan;Yue Hao;
Appeared in: IEEE Photonics Technology Letters
Publication date: Jan 2018, volume: 30, issue:1, pages: 83 - 86
Publisher: IEEE
 
» An Injection-Locked-Based FMCW Transmitter With Synthetic Bandwidth Technique
Abstract:
An injection-locked-based frequency-modulated continuous-wave (FMCW) transmitter using a synthetic bandwidth technique is presented. A wideband chirp is synthesized by combining the up-converted narrowband chirp with different adjacent carrier frequencies. This is achieved by mixing a narrowband direct digital synthesis chirp with a fast-switching subharmonic injection-locked oscillator (SHILO). The use of SHILO allows fast switching at sub-10 ns and provides better phase noise performance than phase-locked loops due to its much wider loop bandwidth. The key idea is demonstrated at 4 GHz by generating two subband chirps with about 300-MHz bandwidth each, achieving a synthetic bandwidth of 600 MHz. The measured impulse response shows a resolution of 32 cm (Hamming) with a sidelobe level of −25 dBc and very accurate range estimates with accuracy of ±0.5 cm.
Autors: Siegfred Balon;Koenraad Mouthaan;Chun-Huat Heng;Zhi Ning Chen;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Jan 2018, volume: 28, issue:1, pages: 55 - 57
Publisher: IEEE
 
» An Intelligent System Approach for Probabilistic Volume Rendering Using Hierarchical 3D Convolutional Sparse Coding
Abstract:
In this paper, we propose a novel machine learning-based voxel classification method for highly-accurate volume rendering. Unlike conventional voxel classification methods that incorporate intensity-based features, the proposed method employs dictionary based features learned directly from the input data using hierarchical multi-scale 3D convolutional sparse coding, a novel extension of the state-of-the-art learning-based sparse feature representation method. The proposed approach automatically generates high-dimensional feature vectors in up to 75 dimensions, which are then fed into an intelligent system built on a random forest classifier for accurately classifying voxels from only a handful of selection scribbles made directly on the input data by the user. We apply the probabilistic transfer function to further customize and refine the rendered result. The proposed method is more intuitive to use and more robust to noise in comparison with conventional intensity-based classification methods. We evaluate the proposed method using several synthetic and real-world volume datasets, and demonstrate the methods usability through a user study.
Autors: Tran Minh Quan;Junyoung Choi;Haejin Jeong;Won-Ki Jeong;
Appeared in: IEEE Transactions on Visualization and Computer Graphics
Publication date: Jan 2018, volume: 24, issue:1, pages: 964 - 973
Publisher: IEEE
 
» An Iterative Check Polytope Projection Algorithm for ADMM-Based LP Decoding of LDPC Codes
Abstract:
Alternating direction method of multipliers (ADMM) is a popular technique for linear-programming decoding of low-density parity-check codes. The computational complexity of ADMM is dominated by the Euclidean projection of a real-valued vector onto a parity-check polytope. Existing algorithms for such a projection all require sorting operations, which happen to be the most complex part of the projection. In this letter, we propose an iterative algorithm, without sorting operation, for projection onto the parity-check polytope. The proposed algorithm has a worst case complexity linear in the input dimension compared with the super-linear complexity of existing algorithms.
Autors: Haoyuan Wei;Amir H. Banihashemi;
Appeared in: IEEE Communications Letters
Publication date: Jan 2018, volume: 22, issue:1, pages: 29 - 32
Publisher: IEEE
 
» An LTI Model-Based Study on Reflected Power Canceler for FMCW Radars
Abstract:
Frequency modulation continuous wave (FMCW) radar receivers generally suffer from transmitter leakage due to insufficient TX-to-RX isolation. One of the effective approaches to solving this problem is using reflected power cancelers (RPCs) that cancel the leakage from the transmitter adaptively. In this paper, a linear time invariant (LTI) model of the RPC is derived in order to carry out a comprehensive study of the mechanism of leakage cancelation and output noise performance for CW radar applications. Loop frequency responses for receiving signal, loop stability, and the influence of dc offset of IQ mixer are analyzed by a simplified transfer function. A detailed noise model of the RPC is established based on the LTI model to study the output noise components of the RPC under a large incident leakage, then the internal noise cancelation mechanism is elucidated. A prototype with its operating frequency range from 820 to 1020 MHz at UHF band is implemented. Measured loop frequency responses are in agreement with simulation results obtained with the proposed model. Furthermore, measured cancelation ratios for leakages of different ramp rates comply with the normalized power gain at corresponding frequency offsets. The input-referred receiving noise of the RPC prototype is measured to be −155 dBm/Hz at 100-kHz offset under +10-dBm incident leakage power. The proposed LTI model provides a useful tool for the design of high-performance RPC for FMCW systems in different application environments.
Autors: Yunlong Pan;Jinping Xu;Wenbo Wang;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 509 - 521
Publisher: IEEE
 
» An MR-Based Model for Cardio-Respiratory Motion Compensation of Overlays in X-Ray Fluoroscopy
Abstract:
In X-ray fluoroscopy, static overlays are used to visualize soft tissue. We propose a system for cardiac and respiratory motion compensation of these overlays. It consists of a 3-D motion model created from real-time magnetic resonance (MR) imaging. Multiple sagittal slices are acquired and retrospectively stacked to consistent 3-D volumes. Slice stacking considers cardiac information derived from the ECG and respiratory information extracted from the images. Additionally, temporal smoothness of the stacking is enhanced. Motion is estimated from the MR volumes using deformable 3-D/3-D registration. The motion model itself is a linear direct correspondence model using the same surrogate signals as slice stacking. In X-ray fluoroscopy, only the surrogate signals need to be extracted to apply the motion model and animate the overlay in real time. For evaluation, points are manually annotated in oblique MR slices and in contrast-enhanced X-ray images. The 2-D Euclidean distance of these points is reduced from 3.85 to 2.75 mm in MR and from 3.0 to 1.8 mm in X-ray compared with the static baseline. Furthermore, the motion-compensated overlays are shown qualitatively as images and videos.
Autors: Peter Fischer;Anthony Faranesh;Thomas Pohl;Andreas Maier;Toby Rogers;Kanishka Ratnayaka;Robert Lederman;Joachim Hornegger;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Jan 2018, volume: 37, issue:1, pages: 47 - 60
Publisher: IEEE
 
» An Optical Voltage Sensor Based on Wedge Interference
Abstract:
The optical voltage sensor (OVS) based on the Pockels effect and its light intensity detection mode has a limitation of half-wave voltage and optical power correlation. In this paper, a new type of OVS which can achieve linear measurements of a wide range electrooptic (EO) phase delay was proposed. It uses a crystal wedge to convert EO phase delay to a displacement image of light stripes, and an image acquisition system that captures the spot and calculates the displacement. Mathematical derivation regarding the linear relationship between the stripes displacement and phase delay is given; a suitable image sensor and a stripe location algorithm are selected. Experimental verification is carried out, and several key issues are discussed. Compared with light intensity detection mode, the experimental results show that this measuring mode is independent of light source. An imaging mode also offers a large dynamic range and a good linear measurement of EO phase delay in the range of 291° with a measurement error of less than 0.5%. This mode is not limited by the half-wave voltage of crystal. Temperature drift errors on measurement results are also reduced.
Autors: Dujing Wang;Nan Xie;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Jan 2018, volume: 67, issue:1, pages: 57 - 64
Publisher: IEEE
 
» An Optimized Segmented Quasi-Memoryless Nonlinear Behavioral Modeling Approach for RF Power Amplifiers
Abstract:
This paper presents an optimized segmented modeling approach using a new quasi-memoryless (QM) behavioral model (BM) that allows for RF power amplifier (RF PA) modeling over a range of different solid state PA technologies. The presented model is a combination of an existing semiphysical amplitude-modulation-to-amplitude-modulation (AM/AM) memoryless BM, which correctly predicts third-order intermodulation distortion (3rd IMD) response in the small signal region, with the newly proposed amplitude-modulation-to-phase-modulation (AM/PM) model derived from the existing AM/AM model. Using the segmentation and optimization methods, performance comparisons with this new model are presented, showing normalized mean squared error AM/PM improvements up to 20 dB, as well as over 5-dB improvement in predicting the 3rd IMD using the proposed model. Comparisons against other well-known QM BMs are conducted using measured data as well as with data presented in the literature. The effects of these improvements on linearizer performance are also evaluated. The model significantly improves system-level modeling by allowing designers to accurately predict system performance using various RF PA devices over a range of technologies, based on data available through manufacturers’ data or simple tests.
Autors: Paul O. Fisher;Said F. Al-Sarawi;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 294 - 305
Publisher: IEEE
 
» An Original Smart-Grids Test Bed to Teach Feeder Automation Functions in a Distribution Grid
Abstract:
This paper proposes the description of an original smart-grids test bed aimed at teaching novel feeder automation functions to students from both university and industry origins. With this test bed, a lab class proposes to students, first, to develop feeder automation functions using scientific software and, then, to experiment by practically testing them on an emulated distribution grid platform, called PREDIS. This platform includes real medium-voltage reduced-scale loads, generators, and a supervisory control and data acquisition system. The presented lab class is part of a dedicated complete pedagogic module with lectures and experiments. Through the development, the tests and the deployments of their own solutions in an actual distribution grid, the students learn by doing from theory to practice the complete chain of smart-grids solutions: from the electrical to the communication layers.
Autors: Marie Cécile Alvarez-Herault;Antoine Labonne;Sellé Touré;Thierry Braconnier;Vincent Debusschere;Raphael Caire;Nouredine Hadjsaid;
Appeared in: IEEE Transactions on Power Systems
Publication date: Jan 2018, volume: 33, issue:1, pages: 373 - 385
Publisher: IEEE
 
» An RF-Powered Transceiver Exploiting Sample and Hold Operation on the Received Carrier
Abstract:
This paper presents an RF-powered transceiver for wireless sensor network applications. The circuit is composed of an RF energy harvesting system, implemented by means of a threshold-compensated multistage rectifier, power management unit, and phase-locked loop (PLL)-based RF front end. Initially, the PLL in closed-loop condition locks the voltage-controlled oscillator (VCO) to a multiple of the RF input frequency and allows frequency-shift keying (FSK) data recovery. Then, the PLL feedback loop is opened and the VCO signal is used to generate the uplink carrier, thus enabling active transmission without requiring external quartz for frequency reference. This approach overcomes the reader self-jamming drawback that greatly limits the operating range of backscattering-based RF-powered devices. Moreover, uplink and downlink operations are performed by exploiting a single carrier frequency according to a half-duplex communication scheme, which results in a low-complexity and low-cost wireless solution. The circuit was fabricated in a 130-nm CMOS technology and operates with a minimum input power as low as −18.8 dBm. It supports the FSK and ASK demodulation and OOK data transmission in the industrial scientific and medical band at 915 MHz.
Autors: Giuseppe Papotto;Nunzio Greco;Alessandro Finocchiaro;Ranieri Guerra;Santo Leotta;Giuseppe Palmisano;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Jan 2018, volume: 66, issue:1, pages: 396 - 409
Publisher: IEEE
 
» An Ultralow Power Subthreshold CMOS Voltage Reference Without Requiring Resistors or BJTs
Abstract:
This brief presents a novel ultralow power CMOS voltage reference (CVR) with only 4.6-nW power consumption. In the proposed CVR circuit, the proportional-to-absolute-temperature voltage is generated by feeding the leakage current of a zero- nMOS transistor to two diode-connected nMOS transistors in series, both of which are in subthreshold region; while the complementary-to-absolute-temperature voltage is created by using the body diodes of another nMOS transistor. Consequently, low-power operation can be achieved without requiring resistors or bipolar junction transistors, leading to small chip area consumption. The proposed CVR circuit is fabricated in a standard 0.18- CMOS process. Measurement results show that the prototype design is capable of providing a 755 mV typical reference voltage with 34 ppm/°C from −15 °C to 140 °C. Moreover, the typical power consumption is only 4.6 nW at room temperature and the active area is only 0.0598 mm2.
Autors: Yang Liu;Chenchang Zhan;Lidan Wang;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 201 - 205
Publisher: IEEE
 
» An Uncooled Microbolometer Infrared Imager With a Shutter-Based Successive-Approximation Calibration Loop
Abstract:
The size and power dissipation of an infrared imaging system can be reduced by the use of uncooled microbolometers; but the nonuniformity of the microbolometer makes such imaging systems heavily reliant on complicated calibration techniques, incurring an overhead which is particularly significant in low-cost, compact devices. We therefore propose a shutter-based successive-approximation calibration loop, which avoids the need to implement correction tables in software on an external processor. Prototype imager, consisting of an pixel infrared focal-plane array and readout circuitry, has been implemented, and the experimental results confirm that our on-chip autocalibration approach compensates effectively for fixed pattern noise caused by the nonuniformity of the microbolometers.
Autors: Yujin Park;Junghee Yun;Dongchul Park;Sangwoo Kim;Suhwan Kim;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Jan 2018, volume: 26, issue:1, pages: 122 - 132
Publisher: IEEE
 
» An Unsupervised Convolutional Feature Fusion Network for Deep Representation of Remote Sensing Images
Abstract:
Unsupervised learning of a convolutional neural network (CNN) is a feasible method to represent and classify remote sensing images, where labeling the observed data to prepare training samples is a highly expensive and time-consuming task. In this letter, we propose an unsupervised convolutional feature fusion network to formulate an easy-to-train but effective CNN representation of remote sensing images. The efficiency and effectiveness are derived from the following two aspects. First, the proposed method trains a deep CNN through unsupervised learning of each CNN layer in a greedy layer-wise manner, which makes the training relatively easy and efficient. Second, the feature fusion strategy in the proposed network can effectively use both the information from individual layers and the important interactions between different layers. As a result, the proposed network requires only several layers to obtain comparable or even better results than very deep networks. The experiments on unsupervised deep representations and the classification of remote sensing images demonstrate the efficiency and effectiveness of the proposed method.
Autors: Yang Yu;Zhiqiang Gong;Cheng Wang;Ping Zhong;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Jan 2018, volume: 15, issue:1, pages: 23 - 27
Publisher: IEEE
 

Publication archives by date

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

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

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

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

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

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

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

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

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

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

 
0-C     D-L     M-R     S-Z