Abstract: Adaptive fuzzy control via command filtering is proposed for uncertain strict-feedback nonlinear systems with unknown nonsymmetric dead-zone input signals in this paper. The command filtering is utilized to cope with the inherent explosion of the complexity problem of the classical backstepping method, and the error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. In addition, by utilizing the bound information of dead-zone slopes, a new adaptive fuzzy method that does not need to establish the inverse of the dead zone is presented for the unknown nonlinear systems. Compared with existing results, the advantages of the developed scheme are that the compensating signals are designed to eliminate the filtering errors and only one adaptive parameter is required, which will make the proposed control scheme more effective for practical systems. An example of position tracking control for the electromechanical system is given to demonstrate the usefulness and potential of the new design scheme.
Abstract: Most existing approaches to coexisting communication/radar systems assume that the radar and communication systems are coordinated, i.e., they share information, such as relative position, transmitted waveforms, and channel state. In this paper, we consider an uncoordinated scenario where a communication receiver is to operate in the presence of a number of radars, of which only a subset may be active, which poses the problem of estimating the active waveforms and the relevant parameters thereof, so as to cancel them prior to demodulation. Two algorithms are proposed for such a joint waveform estimation/data demodulation problem, both exploiting sparsity of a proper representation of the interference and of the vector containing the errors of the data block, so as to implement an iterative joint interference removal/data demodulation process. The former algorithm is based on classical on-grid compressed sensing, whereas the latter forces an atomic norm (AN) constraint: In both cases the radar parameters and the communication demodulation errors can be estimated by solving a convex problem. We also propose a way to improve the efficiency of the AN-based algorithm. The performance of these algorithms are demonstrated through extensive simulations, taking into account a variety of conditions concerning both the interferers and the respective channel states.
Autors: Le Zheng;Marco Lops;Xiaodong Wang;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Abstract: This paper deals with the problem of leader–follower formation control for a group of underactuated surface vessels with partially known control input functions. In the proposed scheme, the problem is formulated as an adaptive feedback control problem for aLine-Of-Sight (LOS) based formation configuration of a leader and a follower. To account for LOS and bearing angle time-varying constraints, asymmetric barrier Lyapunov functions are incorporated with the control design. Furthermore, in order to alleviate required velocity information on the leader, a reconstruction module is designed to estimate the vector velocity of this leader. This reconstruction is accomplished in finite time with zero error, which allows the injection of accurate estimation into the formation controller. The controller is then developed within the framework of the backstepping technique, with the parametric uncertainties and the unknown gains being estimated by a novel structure identifier. The overall closed-loop system, is proved to be semiglobally uniformly ultimately bounded by Lyapunov stability theory. Furthermore, we show under the proposed control scheme that the constraints requirement on the LOS range and bearing angle tracking errors are not violated during the formation process. Finally, the effectiveness and the robustness of the proposed strategy are exhibited through simulations.
Autors: Jawhar Ghommam;Maarouf Saad;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: This paper investigates X-ray pulsar navigation for earth–moon libration-point mission. A comprehensive analysis shows that abnormal measurements are inevitable and bring quite adverse effects for navigation results. To approach this problem, a new algorithm called robust square-root cubature Kalman filter is proposed. An innovation-based adaptive scale factor is introduced to adjust measurement noise covariance so that the adverse effects of abnormal measurements can be suppressed. Effectiveness of the proposed method is demonstrated in simulation results.
Autors: Yang Zhou;Panlong Wu;Xingxiu Li;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Abstract: This paper proposes an adaptive nonlinear disturbance observer (ANDO) for identification and control of a two-axis motion control system driven by two permanent-magnet linear synchronous motors servo drives. The proposed control scheme incorporates a feedback linearization controller (FLC), a new double-loop self-organizing recurrent wavelet neural network (DLSORWNN) controller, a robust controller, and an controller. First, an FLC is designed to stabilize the XY table system. Then, a nonlinear disturbance observer (NDO) is designed to estimate the nonlinear lumped parameter uncertainties that include the external disturbances, cross-coupled interference, and frictional force. However, the XY table performance is degraded by the NDO error due to parameter uncertainties. To improve the robustness, the ANDO is designed to attain this purpose. In addition, the robust controller is designed to recover the approximation error of the DLSORWNN, while the controller is specified such that the quadratic cost function is minimized and the worst-case effect of the NDO error must be attenuated below a desired attenuation level. The online adaptive control laws are derived using the Lyapunov stability analysis and control theory, so that the stability of the ANDO can be guaranteed. The experimental results show the improvements in disturbance suppression and parameter uncertainties, which illustrate the superiority of the ANDO control scheme.
Autors: Fayez F. M. El-Sousy;Khaled Ali Abuhasel;
Appeared in: IEEE Transactions on Industry Applications
Abstract: In this paper, we investigate the performance gains of adapting pilot spacing and power for carrier aggregation orthogonal frequency-division multiplexing (CA-OFDM) systems in nonstationary wireless channels. In current multiband CA-OFDM wireless networks, all component carriers use the same pilot density, which is designed for poor channel environments. This leads to unnecessary pilot overhead in good channel conditions and performance degradation in the worst channel conditions. We propose adaptation of pilot spacing and power using a codebook-based approach, where the transmitter and the receiver exchange information about the fading characteristics of the channel over a short period of time, which are stored as entries in a channel profile codebook. We present a heuristic algorithm that maximizes the achievable rate by finding the optimal pilot spacing and power from a set of candidate pilot configurations. We also analyze the computational complexity of our proposed algorithm and the feedback overhead. We describe methods to minimize the computation and feedback requirements for our algorithm in multiband CA scenarios and present simulation results in typical terrestrial and air-to-ground/air-to-air nonstationary channels. Our results show that significant performance gains can be achieved when adopting adaptive pilot spacing and power allocation in nonstationary channels. We also discuss important practical considerations and provide guidelines to implement adaptive pilot spacing in CA-OFDM systems.
Autors: Raghunandan M. Rao;Vuk Marojevic;Jeffrey H. Reed;
Appeared in: IEEE Transactions on Vehicular Technology
Abstract: Inter-cell interference coordination (ICIC) is a promising technique to improve the performance of frequency-domain packet scheduling (FDPS) in downlink LTE/LTE-A networks. However, it is difficult to maximize the performance of FDPS using static ICIC schemes because of insufficient consideration of signal-to-interference-and-noise ratio distribution and user fairness. On the other hand, dynamic ICIC schemes based on channel state information (CSI) also have difficulty presented in the excessive signaling overhead and X2 interface latency. In order to overcome these drawbacks, we introduce a new concept of ICIC problem based on geometric network information (GNI) and propose an adaptive sector coloring game (ASCG) as a decentralized solution of the GNI-based ICIC problem. Furthermore, we develop an ASCG with a dominant strategy space noted as ASCG-D to secure a stable solution through proving the existence of Nash equilibrium. The proposed scheme provides better performance in terms of system throughput gain of up to about 44.1%, and especially of up to about 221% for the worst 10% users than static ICIC schemes. Moreover, the performance of the CSI-based ICIC, which require too much computational load and signaling overhead, is only 13.0% and 5.6% higher than that of ASCG-D regarding the total user throughput and the worst 10% user throughput, respectively. The most interesting outcome is that the signaling overhead of ASCG-D is 1/144 of dynamic ICIC schemes’ one.
Abstract: Since operating conditions of power systems always change, the input and output signals of wide-area damping controller (WADC), which are selected at an operating point, may not be able to guarantee the damping effect at other operating points. This paper focuses on a new adaptive signal selection for WADC against several operating conditions, such as various load demands, control signal failure, line and generator outages, and effect of communication latency. The joint controllability and observability is used to determine the best input and output pairs of WADC at any operating points. Small-signal and transient stabilities study in the IEEE 50-machine system including renewable sources, i.e., wind and solar photovoltaic generators are conducted to evaluate the effect of the proposed method. Study result demonstrates that the WADC with the adaptive signal selection yields superior damping effect to the WADC with the fixed signal selection over wide range operations.
Autors: Tossaporn Surinkaew;Issarachai Ngamroo;
Appeared in: IEEE Transactions on Industrial Informatics
Abstract: This paper presents an adaptive autoreclosing concept for HVDC transmission systems with modular multilevel converters in full-bridge topology for single pole-to-ground faults. Since HVDC transmission will be used in the German energy transmission system to support the heavily loaded ac grid for energy transport over far distances, the interruption time has to be kept as short as possible to preserve system stability. Within the presented autoreclosing concept, the necessary interruption time is determined adaptively. After fault detection, the converter control drives the fault current to zero and injects a low-level ac current. The nonlinear interdependence between the fault arc resistance and the current is used to detect the final arc extinction and to start the voltage recovery, enabling a fast resumption of the power transmission. PSCAD|EMTDC is used to model the electric arc behavior and the dielectric recovery inside an exemplary point-to-point HVDC grid model as an evaluation of the concept. The minimum required ac current is identified related to the used fault detection method. Additionally, the influences of fault position, line length, and fault resistance on fault detection are investigated. The results show that the required interruption time can be determined adaptively for transmission line length up to 400 km.
Autors: Maximilian Stumpe;Philipp Ruffing;Patrick Wagner;Armin Schnettler;
Abstract: Finding correlations across multiple data sets in imaging and (epi)genomics is a common challenge. Sparse multiple canonical correlation analysis (SMCCA) is a multivariate model widely used to extract contributing features from each data while maximizing the cross-modality correlation. The model is achieved by using the combination of pairwise covariances between any two data sets. However, the scales of different pairwise covariances could be quite different and the direct combination of pairwise covariances in SMCCA is unfair. The problem of “unfair combination of pairwise covariances” restricts the power of SMCCA for feature selection. In this paper, we propose a novel formulation of SMCCA, called adaptive SMCCA, to overcome the problem by introducing adaptive weights when combining pairwise covariances. Both simulation and real-data analysis show the outperformance of adaptive SMCCA in terms of feature selection over conventional SMCCA and SMCCA with fixed weights. Large-scale numerical experiments show that adaptive SMCCA converges as fast as conventional SMCCA. When applying it to imaging (epi)genetics study of schizophrenia subjects, we can detect significant (epi)genetic variants and brain regions, which are consistent with other existing reports. In addition, several significant brain-development related pathways, e.g., neural tube development, are detected by our model, demonstrating imaging epigenetic association may be overlooked by conventional SMCCA. All these results demonstrate that adaptive SMCCA are well suited for detecting three-way or multiway correlations and thus can find widespread applications in multiple omics and imaging data integration.
Autors: Wenxing Hu;Dongdong Lin;Shaolong Cao;Jingyu Liu;Jiayu Chen;Vince D. Calhoun;Yu-Ping Wang;
Appeared in: IEEE Transactions on Biomedical Engineering
Abstract: In recent years, digital pre-distortion has emerged as a powerful approach to compensate linear and non-linear imperfections of the transmitter. Previous solutions are either based on factory calibration or use a local auxiliary receiver. Here, we present a digital pre-distortion architecture to compensate transmitter frequency response and I/Q skew, which relies upon a feedback from the far-end receiver and uses the signal propagated over the optical link. The effectiveness of the proposed solution is validated over different transmission systems for dual-polarization 64 QAM net 400 Gb/s and 16 QAM net 200 Gb/s signals.
Autors: Ginni Khanna;Bernhard Spinnler;Stefano Calabrò;Erik de Man;Yingkan Chen;Norbert Hanik;
Abstract: The letter presents the adsorption properties of CO, NH3, CH4, SO2, and H2S molecules over niobium doped graphene sheet (Nb/G). Using density functional theory, the optimum configuration and orientation of adsorbent molecules over the Nb/G surface are geometrically optimized, and adsorption energy, adsorption distance, Hirshfeld charge transfer, electron localization function, and the work function of Nb/G-molecule systems are calculated. CO and SO2 molecules over Nb/G show chemisorption, hence they have high reactivity towards Nb/G. Adsorption of NH3, CH4, and H2S on Nb/G shows physisorption as they are weakly adsorbed. The adsorption of these molecules indicates the suitability of Nb/G as a sensor. To understand the superiority of Nb/G over pristine graphene, comparison of adsorption properties was made between the two systems. The work function of Nb/G with adsorbed molecule suggests that the Fermi level of Nb/G surface may be controlled by the selection of appropriate adsorbent molecules. Therefore, Nb/G could be a good candidate for gas sensing application.
Autors: Jitendra Kumar;Harshal B. Nemade;P. K. Giri;
Abstract: This paper provides the guidelines for the practical development of novel advanced test beds for passive intermodulation (PIM) measurements. The proposed test beds show high performance and are flexible, allowing for the measurement of several PIM signals of different orders, with two or more input carriers. In contrast to classic test beds for satellite hardware, based on the cascaded connection of several elements, an integrated solution involving the minimum number of hardware pieces is proposed. The result is a lower number of flanged interconnections, thus reducing residual PIM level and insertion losses. In addition, return loss degradation and harmful spurious generation in the interconnections are also avoided. Measurement test beds for conducted and radiated PIM, in both transmitted and reflected directions, are discussed, highlighting the benefits and drawbacks of each configuration. Design guidelines for the key components are fully discussed. Illustrative application examples are also reported. Finally, excellent experimental results obtained from low-PIM measurement setups, working from C-band to Ka-band, are shown, thus fully confirming the validity of the proposed configurations.
Abstract: Examines the market for wireless sensor networks in the era and expansion of the Internet of Things. Over the past decade, the fast expansion of the Internet of Things (IoT) paradigm and wireless communication technologies has raised many scientific and engineering challenges that call for ingenious research efforts from both academia and industry. The IoT paradigm now covers several technologies beyond RFID and wireless sensor networks (WSNs). In fact, the number of potential application fields has already exceeded expectations. According to Cisco IBSG, more than 50 billion devices are expected to be connected to the Internet by 2020, with around 20 percent from the industry sector. Therefore, integrating the IoT concept and industrial WSNs (IWSNs) is an attractive choice for industrial processes, which may optimize operational efficiency, automation, maintenance, and rationalization. Moreover, IoT ensures large-scale interconnection between machines, computers, and people, enabling intelligent industrial operations. This emergent technological evolution has led to what has become the Industrial IoT (IIoT). IIoT will bring promising opportunities, along with new challenges.
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.
Abstract: Examines new optical technologies and applications. With recent advances in emerging fields such as silicon photonic integration and spatial-division multiplexing (SDM), optical communications and networking technologies demonstrated great success in supporting the ever increasing growth of data center networks. Meanwhile, the implementation of software- defined networking (SDN) is making optical communications networks (i.e., both fiber optic systems and optical wireless ones) more agile, programmable, and application-aware to provide short time to market and flexible service solutions. Moreover, we are also happy to witness attractive progress in optical camera communications, which can leverage the built-in cameras in smartphones to realize device-to-device communication. Finally, the development of optical communications and networking technologies always needs support from innovations in fundamental physics.
Abstract: One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature extractor and classifier can improve classification accuracy. In this letter, we construct three different convolutional neural networks with different sizes of receptive field, respectively. More importantly, we further propose a multilevel fusion method, which can make judgment by incorporating different levels’ information. The aerial image and two patches extracted from the image are fed to these three different networks, and then, a probability fusion model is established for final classification. The effectiveness of the proposed method is tested on a more challenging data set-AID that has 10000 high-resolution remote sensing images with 30 categories. Experimental results show that our multilevel fusion model gets a significant classification accuracy improvement over all state-of-the-art references.
Autors: Yunlong Yu;Fuxian Liu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Abstract: Inspired by the real needs of group decision problems, aggregation of ordered weighted averaging (OWA) operators is studied and discussed. Our results can be applied for data acting on any real interval, such as the standard scales and , bipolar scales and , etc. A direct aggregation is shown to be rather restrictive, allowing the convex combinations to be considered only, except the case of dimension n = 2. More general is the approach based on the aggregation of related cumulative weighting vectors. The piecewise linearity of OWA operators allows us to consider bilinear forms of aggregation of related weighting vectors. Several interesting examples yielding the link between the aggregation of OWA operators and the related ANDness and ORness measures are also included. Some possible applications and generalizations of our results are also discussed.
Abstract: This letter proposes an aggregation-assisted combining (AAC) for multiple-input multiple-output multiple automatic repeat request systems. The proposed AAC can be considered as a hybrid scheme of the symbol-level combining (SLC) and bit-level combining (BLC), which consists of the aggregation-assisted log-likelihood ratio (LLR) calculation and subsequent LLR combining stages. The aggregation-assisted LLR calculation stage is performed in a similar manner on the SLC except that the interference-to-noise reformulation is performed instead of the terminated-packet elimination; thus, the remaining interference from the terminated packets is regarded as additional noise. This additional noise can degrade the LLR quality from the aggregation-assisted LLR calculation stage. Therefore, the proposed AAC combines the currently calculated LLRs with the previously calculated LLRs similar to the BLC when the previously calculated LLRs have less LLR contaminations, i.e., they experience fewer numbers of terminated packets. The simulation results verify that the proposed AAC outperforms the BLC and even achieves a performance comparable with the SLC with simplified reception procedures.
Abstract: To solve the policy optimizing problem in many scenarios of smart wireless network management using a single universal algorithm, this letter proposes a universal learning framework, which is called AI framework based on deep reinforcement learning (DRL). This framework can also solve the problem that the state is painful to design in traditional RL. This AI framework adopts convolutional neural network and recurrent neural network to model the potential spatial features (i.e., location information) and sequential features from the raw wireless signal automatically. These features can be taken as the state definition of DRL. Meanwhile, this framework is suitable for many scenarios, such as resource management and access control due to DRL. The mean value of throughput, the standard deviation of throughput, and handover counts are used to evaluate its performance on the mobility management problem in the wireless local area network on a practical testbed. The results show that the framework gets significant improvements and learns intuitive features automatically.
Autors: Gang Cao;Zhaoming Lu;Xiangming Wen;Tao Lei;Zhiqun Hu;
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.
Abstract: Heterogeneous-ISA computing platforms have become ubiquitous, and will be used for diverse workloads which render static mappings of computation to processors inadequate. Dynamic mappings which adjust an application's usage in consideration of platform workload can reduce application latency and increase throughput for heterogeneous platforms. We introduce AIRA, a compiler and runtime for flexible execution of applications in CPU-GPU platforms. Using AIRA, we demonstrate up to a 3.78x speedup in benchmarks from Rodinia and Parboil, run with various workloads on a server-class platform. Additionally, AIRA is able to extract up to an 87 percent increase in platform throughput over a static mapping.
Autors: Robert Lyerly;Alastair Murray;Antonio Barbalace;Binoy Ravindran;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Abstract: In this paper, we present the results of an ~5-h airborne gamma-ray survey carried out over the Tyrrhenian Sea in which the height range (77–3066) m has been investigated. Gamma-ray spectroscopy measurements have been performed using the AGRS_16L detector, a module of four 4L NaI(Tl) crystals. The experimental setup was mounted on the Radgyro, a prototype aircraft designed for multisensorial acquisitions in the field of proximal remote sensing. By acquiring high-statistics spectra over the sea (i.e., in the absence of signals having geological origin) and by spanning a wide spectrum of altitudes, it has been possible to split the measured count rate into a constant aircraft component and a cosmic component exponentially increasing with increasing height. The monitoring of the count rate having pure cosmic origin in the >3-MeV energy region allowed to infer the background count rates in the 40K, 214Bi, and 208Tl photopeaks, which need to be subtracted in processing airborne gamma-ray data in order to estimate the potassium, uranium, and thorium abundances in the ground. Moreover, a calibration procedure has been carried out by implementing the CARI-6P and Excel-based program for calculating atmospheric cosmic ray spectrum dosimetry tools, according to which the annual cosmic effective dose to human population has been linearly related to the measured cosmic count rates.
Autors: Marica Baldoncini;Matteo Albéri;Carlo Bottardi;Brian Minty;Kassandra G. C. Raptis;Virginia Strati;Fabio Mantovani;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Abstract: Aircraft type recognition in remote sensing images is a meaningful task. It remains challenging due to the difficulty of obtaining appropriate representation of aircrafts for recognition. To solve this problem, we propose a novel aircraft type recognition framework based on deep convolutional neural networks. First, an aircraft segmentation network is designed to obtain refined aircraft segmentation results which provide significant details to distinguish different aircrafts. Then, a keypoints’ detection network is proposed to acquire aircrafts’ directions and bounding boxes, which are used to align the segmentation results. A new multirotation refinement method is carefully designed to further improve the keypoints’ precision. At last, we apply a template matching method to identify aircrafts, and the intersection over union is adopted to evaluate the similarity between segmentation results and templates. The proposed framework takes advantage of both shape and scale information of aircrafts for recognition. Experiments show that the proposed method outperforms the state-of-the-art methods and can achieve 95.6% accuracy on the challenging data set.
Abstract: Efficient all-inorganic silicon-quantum-dot (Si-QD) near-infrared light-emitting diodes (LEDs) have been fabricated by using nickel oxide (NiO) and zinc oxide (ZnO) as the transport layers of holes and electrons, respectively. It is found that the LED performance may be significantly improved by the atomic layer deposition of an Al2O3 interlayer between Si QDs and NiO. The improvement is due to the fact that the Al2O3 interlayer can not only suppress the exciton quenching induced by the traps at the NiO surface and the accumulated holes at the NiO/Si-QD interface, but also reduce the leakage of carriers. The optimum thickness of the Al2O3 interlayer is found to be ~5.7 nm, which leads to the increase of the optical power density by a factor of ~7 (from ~2 to /cm2) and that of the external quantum efficiency by a factor of ~10 (from ~0.01% to 0.1%) for the all-inorganic Si-QD near-infrared LED on glass. In addition, it is shown that the Al2O3 interlayer may also improve the performance of flexible all-inorganic Si-QD near-infrared LEDs on poly(ethylene terephthalate).
Abstract: Subspace clustering is an important problem in machine learning with many applications in computer vision and pattern recognition. Prior work has studied this problem using algebraic, iterative, statistical, low-rank and sparse representation techniques. While these methods have been applied to both linear and affine subspaces, theoretical results have only been established in the case of linear subspaces. For example, algebraic subspace clustering (ASC) is guaranteed to provide the correct clustering when the data points are in general position and the union of subspaces is transversal. In this paper we study in a rigorous fashion the properties of ASC in the case of affine subspaces. Using notions from algebraic geometry, we prove that the homogenization trick , which embeds points in a union of affine subspaces into points in a union of linear subspaces, preserves the general position of the points and the transversality of the union of subspaces in the embedded space, thus establishing the correctness of ASC for affine subspaces.
Autors: Manolis C. Tsakiris;René Vidal;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Abstract: Cyclic codes have been widely used in many applications of communication systems and data storage systems. This paper proposes a new procedure for decoding cyclic codes up to actual minimum distance. The decoding procedure consists of two steps: 1) computation of known syndromes and 2) computation of error positions and error values simultaneously. To do so, a matrix whose all entries are syndromes is called syndrome matrix. A matrix whose entries are either syndromes or the elements of a finite field is said to be partial syndrome matrix. In this paper, two novel methods are presented to determine error positions and error values simultaneously and directly. The first method uses a new partial syndrome matrix along with Gaussian elimination. The partial syndrome matrices for binary (respectively, ternary) cyclic codes of lengths from 69 to 99 (respectively, 16 to 37) are tabulated. For some cyclic codes, the partial syndrome matrices contain unknown syndromes; the second method constructs a matrix from a system of equations, which is generated by the determinants of different partial syndrome matrices and makes use of Gaussian elimination to determine its row rank. Many more cyclic codes beyond the Bose–Chaudhuri–Hocquenghem bound can be decoded with these methods.
Autors: Chong-Dao Lee;
Appeared in: IEEE Transactions on Information Theory
Abstract: A central question in information theory is to determine the maximum success probability that can be achieved in sending a fixed number of messages over a noisy channel. This was first studied in the pioneering work of Shannon, who established a simple expression characterizing this quantity in the limit of multiple independent uses of the channel. Here, we consider the general setting with only one use of the channel. We observe that the maximum success probability can be expressed as the maximum value of a submodular function. Using this connection, we establish the following results: 1) There is a simple greedy polynomial-time algorithm that computes a code achieving a -approximation of the maximum success probability. The factor can be improved arbitrarily close to 1 at the cost of slightly reducing the number of messages to be sent. Moreover, it is NP-hard to obtain an approximation ratio strictly better than for the problem of computing the maximum success probability. 2) Shared quantum entanglement between the sender and the receiver can increase the success probability by a factor of at most . In addition, this factor is tight if one allows an arbitrary non-signaling box between the sender and the receiver. 3) We give tight bounds on the one-shot performance of the meta-converse of Polyanskiy-Poor-Verdú.
Autors: Siddharth Barman;Omar Fawzi;
Appeared in: IEEE Transactions on Information Theory
Abstract: This article presents two new deterministic algorithms for constructing consensus trees. Given an input of phylogenetic trees with identical leaf label sets and leaves each, the first algorithm constructs the majority rule (+) consensus tree in time, which is optimal since the input size is , and the second one constructs the frequency difference consensus tree in time.
Abstract: We propose an all-fiber orbital angular momentum (OAM) generator/converter based on photonic crystal fiber (PCF). The PCF is designed to introduce a helical effective refractive index profile in order to achieve the OAM matching condition that is required to excite the OAM modes of an OAM-supporting fiber. The proposed design is compact, presents wideband operation, low loss and high OAM purity. It is of great interest to OAM-based telecommunication, and other OAM applications that use optical fibers.
Abstract: A novel all-fiber on-line Raman cell based on metal (silver)-lined capillary is proposed, which could collect reflection and transmission Raman signal simultaneously. In our configuration, two optical fiber tips are inserted into both sides of the hollow-core metal-lined capillary to form a Raman cell. The other ends of fiber tips are closely bound together as a Sagnac loop and coupled with a Raman probe. Each fiber tip not only works in reflection mode, but also acts as the collection lens for the transmission mode of the other side’s excitation. The hollow-core all-fiber structure could extend the interaction length between the samples and pump laser. Moreover, the Raman signal collection mechanism was significantly improved. With the combination of both Raman excitation modes, a Raman signal with two times of magnitude enhancement is observed in experiment and it agrees well with the theoretical analysis. We have also detected different concentrations (0.5–8 mg/mL) of antibiotic (Cefotaxime sodium, CTX), which proves that our proposed all-fiber and well-encapsulated Raman cell has tremendous potential for portable on-line rapid Raman biosensor.
Abstract: “Seeing through” occluders is one of the most important effects that can be achieved with synthetic aperture imaging. As well, the occlusion problem, a challenging task for many computer vision applications, can be easily handled. Synthetic aperture imaging takes advantage of the property that only objects on the focal plane are sharp. The resulting image that is obtained by averaging images from different views consists of blurry objects away from the focal plane and sharp objects on the focal plane. Removing the blurriness caused by defocusing in synthetic aperture images to achieve an all-in-focus “seeing through” image is a challenging research problem. In this paper, we propose a novel method to improve the image quality of synthetic aperture imaging using image matting via energy minimization by estimating the foreground and the background. In particular, we first estimate the out-of-focus region by focusing on the background objects in each camera view using energy minimization. Next, we utilize a labeling method to create a sharp “see through” synthetic aperture image of the hidden objects. Then, image matting is used to extract the alpha matte of the hidden objects. Finally, by compositing the hidden objects with the estimated background regions, a sharp “see through” synthetic aperture image is created. The experimental results show that the proposed method outperforms the traditional synthetic aperture imaging method  as well as its improved versions –, which simply dim and blur the area in the image that is out of focus, and a recent all-in-focus method . We show that both the occlud-
d objects and the background can be combined using our method to create a sharp synthetic aperture image.
Autors: Zhao Pei;Xida Chen;Yee-Hong Yang;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Abstract: In this work, a new all-polarization maintaining (PM) fiber loop mirror interferometer is proposed and validated as a temperature and mechanical vibration sensor. The scheme employs the arms of a PM coupler as communication fibers, fused with a relative angle of 45° to the sensing fiber. The length of the arms is equal, so their contribution in canceled, obtaining a total transfer function exclusively defined by the sensing fiber. The capabilities of the system as a sensor are tested, achieving mechanical vibration and temperature sensing without crosstalk between measurands. In this manner, vibration frequencies up to 1.5 kHz have been monitored using a commercial interrogator with a scan rate of 1 Hz and a technique based on the fast Fourier transform. Additionally, the immunity of the setup to external perturbations in the communication fibers is studied and compared to the conventional approach.
Abstract: In the last few years, a lot of researchers have proposed different methods, to solve the mathematical programming problem of matrix games with Atanassov's intuitionistic fuzzy payoffs. In this paper, the flaws of the existing methods for solving matrix games with Atanassov's intuitionistic fuzzy payoffs (matrix games in which payoffs are represented by Atanassov's intuitionistic fuzzy numbers) are pointed out. Also, to resolve these flaws, new methods (named as Ambika methods) are proposed to obtain the optimal strategies as well as minimum expected gain of Player I and maximum expected loss of Player II for matrix games with Atanassov's intuitionistic fuzzy payoffs. To illustrate proposed Ambika methods, some existing numerical problems of matrix games with Atanassov's intuitionistic fuzzy payoffs are solved by proposed Ambika methods.
Abstract: Rotary traveling wave oscillators use a transmission line connected as a closed loop as their resonant element. This allows the use of spatial degrees of freedom, not available in typical L–C oscillator topologies, in the design of the amplifier needed to sustain the oscillating mode. Here, we present a novel amplifier design that takes advantage of this extra degree of freedom to improve performance of RTWOs in two ways. If no precautions are taken then the oscillation can start in either a clockwise or anti-clockwise direction. The Phased amplifier, introduced here, forces one direction of oscillation with a measured probability of reverse oscillation of less than 0.43 ppm with a confidence level of 99%. No reverse oscillations were observed in 107 trials. This is accomplished by adding additional phase-dependent degeneration transistors and phase shifting the various amplifier inputs by taking them from different locations on the transmission line. Additionally, this amplifier design reduces the phase noise by reducing the amplifier noise during the time that the oscillator is most sensitive to phase perturbation, resulting in a 1.2-dB reduction in phase noise measured 1 MHz from the peak and a 2.9-dB improvement in the figure of merit.
Autors: Andrey Martchovsky;Kenneth D. Pedrotti;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Abstract: A new time-to-digital converter (TDC) with high resolution and high precision is designed and tested in this paper. The converter is realized by combining coarse clock counter with a two-stage delay-line loop shrinking interpolator (DLLSI) based on Vernier configuration, and its prototype has been implemented in a low-cost flash field-programmable gate array device SmartFusion A2F200M3F (Actel). Delay-line loops are used to achieve differential Vernier delay unit and directly shrink the time interval. In order to improve the resolution, decrease measurement time, and diminish the jitter of the cyclic pulse, a two-stage DLLSI method is proposed. The first-stage interpolator rapidly shrinks the measured time interval with low resolution, and the second-stage interpolator determines the final fine resolution. The resolutions are dependent on the entire delay time differences between two delay-line loops of each interpolator. The optimal resolutions are theoretically calculated, and statistic code density test is used to estimate the resolution of the implemented TDC. The implemented two-stage DLLSI has achieved 8.5-ps resolution with 42.4-ps standard deviation and 10-ns dynamic range. The maximum integral and differential nonlinearity errors are less than 7.8 and 3.1 ps.
Autors: Jie Zhang;Dongming Zhou;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Abstract: This paper presents an asynchronous-clocking successive approximation register (SAR) analog-to-digital converter (ADC) suitable for ultralow-power fine-precision sensor applications whose signal bandwidth is in the kilohertz range. The performance-limiting issues of comparator noise and capacitor mismatch in SAR ADC are resolved by a residue integration scheme combined with a dynamic element matching (DEM), achieving a high resolution without imposing extra burden on the design of residue amplifier and comparator. The prototype 16-bit 2 kS/s SAR ADC is fabricated using 180-nm CMOS process in an area of 0.68 mm2. Measurements show 84.6-dB signal to noise and distortion ratio and 98.2-dB spurious-free dynamic range at the Nyquist input frequency. The ADC dissipates 7.93 from supply voltage of 1.8 V and achieves a Schreier figure of merit of 165.6 dB.
Abstract: This paper presents a source-driver IC that actively compensates for inter-channel charging rate mismatch in an active-matrix organic light-emitting diode (OLED) display with ultra-thin bezel panel. Due to the limitation of the physical design, the resistances of the driver-to-column routing lines in the panel bezel differ across channels. To solve the luminance non-uniformity caused by resistance mismatch, a digitally controlled -degeneration technique embedded in the output buffer amplifier is proposed. Each driver channel independently compensates for different routing-line resistances, resulting in a charging rate with excellent uniformity. In addition, the bezel area can be desirably minimized without a zigzag wiring pattern. The prototype 240-channel source-driver IC was fabricated using 0.18- CMOS technology, and offers a 16.8M-color depth with 13-mW power consumption. With a real OLED display, the measured luminance uniformity under condition of 240-Hz frame rate was improved from % to % by the proposed scheme. The inter-channel output deviation was measured to be ±2.7 mV. The video play on 2.4-in OLED panel using a frame rate of 240 Hz was also successfully demonstrated with high display quality.
Abstract: An advanced silicon-on-insulator (SOI) pixel sensor with an anti-punch-through structure is proposed to suppress the effect of total ionizing dose (TID) and crosstalk between the electronics and the sensor. A buried p-well (BPW) and a buried n-well (BNW) are both connected to their respective voltages to shield SOI circuits from the sensor. BNW is used as an electrode with controllable potential, which provides similar functionality as middle silicon in double SOI (DSOI). The biased BPW and anti-punch-through implant are adopted to form a potential barrier to holes in BPW. The lateral electric fields induced by the sidewalls of the pixel accelerate electrons to the N+ charge collector. 2-D and 3-D physical-level simulations are presented to compare this structure with DSOI. The simulation results show that an appropriate operating biasing voltage under a fully depleted condition can be secured by adjusting the anti-punch-through doping. The TID effects, the parasitic capacitance between the electronics and the charge collector, and the charge collection efficiency have been studied.
Abstract: Anomaly detection (AD) is an important technique in hyperspectral data analysis that permits to distinguish rare objects with unknown spectral signatures that are particularly not abundant in a scene. In this paper, a novel algorithm for an accurate detection of anomalies in hyperspectral images with a low computational complexity, named ADALOC2, is proposed. It is based on two main processing stages. First, a set of characteristic pixels that best represent both anomaly and background classes are extracted applying orthogonal projection techniques. Second, the abundance maps associated to these pixels are estimated. Under the assumption that the anomaly class is composed of a scarce group of image pixels, rare targets can be identified from abundance maps characterized by a representation coefficient matrix with a large amount of almost zero elements. Unlike the other algorithms of the state of the art, the ADALOC2 algorithm has been specially designed for being efficiently implemented into parallel hardware devices for applications under real-time constraints. To achieve this, the ADALOC2 algorithm uses simple and highly parallelized operations, avoiding to perform complex matrix operations such as the computation of an inverse matrix or the extraction of eigenvalues and eigenvectors. An extensive set of simulations using the most representative state-of-the-art AD algorithms and both real and synthetic hyperspectral data sets have been conducted. Moreover, extra assessment metrics apart from classical receiver operating characteristic curves have been defined in order to make deeper comparisons. The obtained results clearly support the benefits of our proposal, both in terms of the accuracy of the detection results and the processing power demanded.
Autors: María Díaz;Raúl Guerra;Sebastián López;Roberto Sarmiento;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Abstract: We propose a new cellular network model that captures both deterministic and random aspects of base station (BS) deployments. Namely, the BS locations are modeled as the superposition of two independent stationary point processes: a random shifted grid with intensity and a Poisson point process (PPP) with intensity . Grid and PPP deployments are special cases with and , with actual deployments in between these two extremes, as we demonstrate with deployment data. Assuming that each user is associated with the BS that provides the strongest average received signal power, we obtain the probability that a typical user is associated with either a grid or PPP BS. Assuming Rayleigh fading channels, we derive the expression for the coverage probability of the typical user, resulting in the following observations. First, the association and the coverage probability of the typical user are fully characterized as functions of intensity ratio . Second, the user association is biased toward the BSs located on a grid. Finally, the proposed model predicts the coverage probability of the actual deployment with great accuracy.
Autors: Chang-Sik Choi;Jae Oh Woo;Jeffrey G. Andrews;
Abstract: A compact analytical drain current model considering the inversion layer and source depletion is developed for the gate-all-around (GAA) heterojunction tunneling FET (H-TFET) with staggered-gap alignment. Poisson’s equations are solved to obtain the continuous surface potential profile for the GAA H-TFET first, then the drain current is derived based on Kane’s model by using the tangent line approximation method, and finally, the model is verified by TCAD simulation using GaAs0.5Sb0.5/In0.53Ga0.47As GAA H-TFET and published data. The impacts of bias, gate oxide dielectric constant, and interface fixed charge on the surface potential, electric field, and – can be well predicted by the proposed model. The super-linear onset and saturation characteristics of – curves are also obtained.
Abstract: Wheeled mobile robots (WMR) have been deployed in Mars/Lunar exploration, military missions, and geological investigations, and they must handle rough and deformable terrains. The dynamics at the wheel–soil interface, including the wheel–terrain contact angle, wheel sinkage, and wheel–soil interaction forces and torque, are major factors in the entrapment of NASA SPIRIT MER and the subsequent mission failure. This paper presents an experimental apparatus that is developed to measure the wheel–terrain contact angle, wheel sinkage, and wheel–soil interaction forces and torque in real time to improve our understanding of the WMR mobility on soft and deformable terrains. A method for wheel sinkage evaluation is presented based on measuring the wheel–terrain contact angle. The wheel–soil interaction forces and torque are measured by installing a force/torque sensor along the axle of the apparatus. The proposed approach is implemented on a testbed, and the experimental results are used to evaluate it; they demonstrate the reliable detection of the wheel–terrain contact angle, wheel sinkage, and wheel–soil interaction forces and torque. Moreover, based on the measured wheel–terrain contact angle, the relative errors in the predicted wheel–soil interaction forces and torque are less than 8% compared with the experimental data.
Abstract: Artificial neurons and synapses are critical units for processing intricate information in neuromorphic systems. Memristors are frequently engineered as artificial synapses due to their simple structures, gradually changing conductance and high-density integration. However, few studies have designed memristors as artificial neurons. In this letter, we demonstrate an integration-and-fire artificial neuron based on a Ag/SiO2/Au threshold switching memristor. This neuron displays four critical features for action-potential-based computing: the all-or-nothing spiking of an action potential, threshold-driven spiking, a refractory period, and a strength-modulated frequency response. As a post-synaptic neuron, the designed neuron was demonstrated to be applicable to digit recognition. These results demonstrate that the developed artificial neuron can realize the basic functions of spiking neurons and has great potential for neuromorphic computing.
Abstract: This paper investigates the problem of event-triggered control for a class of fuzzy Markov jump systems with general switching policies. A novel event-triggered scheme is proposed to improve the transmission efficiency at each sampling instance. Each transition rate allows to be unknown, known, or only its uncertain domains value is known. With the help of a tailored technique to bind the uncertain terms and an asynchronous operation approach to tackle the fuzzy system and fuzzy controller, sufficient conditions for the resulting fuzzy Markovian jump systems are established in terms of coupled linear matrix inequalities. Finally, an example is given to illustrate the validity of the developed technique.
Autors: Jun Cheng;Ju H. Park;Lixian Zhang;Yanzheng Zhu;
Abstract: Tuning the kernel work-group size for GPUs is a challenging problem. In this paper, using the performance counters provided by GPUs, we characterize a large body of OpenCL kernels to identify the performance factors that affect the choice of a good work-group size. Based on the characterization, we realize that the most influential performance factors with regard to the work-group size include occupancy, coalesced global memory accesses, cache contention, and variation in the amount of workload in the kernel. By tackling the performance factors one by one, we propose auto-tuning techniques that selects the best work-group size and shape for GPU kernels. We show the effectiveness of our auto-tuner by evaluating it with a set of 54 OpenCL kernels on three different NVIDIA GPUs and one AMD GPU. On average, the auto-tuner needs to spend no more than 8 percent of the time required by an exhaustive search to find an optimal work-group size. The execution time of the selected sub-optimal work-group size is at most 1.14x slower than that of the optimal work-group size found by the exhaustive search, on average.
Autors: Thanh Tuan Dao;Jaejin Lee;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Abstract: We report on the implementation of an automated platform for detecting the presence of an antibody biomarker for human papillomavirus-associated oropharyngeal cancer from a single droplet of serum, in which a nanostructured photonic crystal surface is used to amplify the output of a fluorescence-linked immunosorbent assay. The platform is comprised of a microfluidic cartridge with integrated photonic crystal chips that interfaces with an assay instrument that automates the introduction of reagents, wash steps, and surface drying. Upon assay completion, the cartridge interfaces with a custom laser-scanning instrument that couples light into the photonic crystal at the optimal resonance condition for fluorescence enhancement. The instrument is used to measure the fluorescence intensity values of microarray spots corresponding to the biomarkers of interest, in addition to several experimental controls that verify correct functioning of the assay protocol. In this paper, we report both dose-response characterization of the system using anti-E7 antibody introduced at known concentrations into serum and characterization of a set of clinical samples from which results were compared with a conventional enzyme-linked immunosorbent assay performed in microplate format. The demonstrated capability represents a simple, rapid, automated, and high-sensitivity method for the multiplexed detection of protein biomarkers from a low-volume test sample.
Autors: Caitlin M. Race;Lydia E. Kwon;Myles T. Foreman;Qinglan Huang;Hakan Inan;Sailaja Kesiraju;Phuong Le;Sung Jun Lim;Andrew M. Smith;Richard C. Zangar;Utkan Demirci;Karen S. Anderson;Brian T. Cunningham;
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.
Abstract: This paper proposes a simple and effective method to reduce speed ripples of permanent magnet synchronous machines (PMSMs) under low-speed working conditions. The treated issue is related to the periodic torque ripples, which induce speed oscillations that deteriorate the drive performance. The main idea of the proposed method is to modify a conventional PMSM controller by superposing an appropriate compensation signal to the quadratic-current reference. The proposed approach allows the reduction of speed ripples at low speed through a simple compensation signal and does not require a hard calculation cost. A theoretical analysis is presented, and both simulation and experimental results are presented to validate the proposed compensation method.
Abstract: The time–frequency analysis tools, which are very useful for anomaly identification, reservoir characterization, seismic data processing, and interpretation, are widely used in discrete signal analysis. Among these methods, the generalized S transform (GST) is more flexible, because its analytical window can be self-adjusted according to the local frequency components of the selected discrete signal, besides there exist another two adjustable parameters to make it superior to the S transform (ST). But the amplitude-preserving ability is a little poor near the boundary because the analytical windows do not satisfy the partition of unity, which is a sufficient condition for amplitude-preserving time–frequency transforms. In order to make the GST with the amplitude-preserving ability, we first design a new analytical window, and then propose an amplitude-preserving GST (APGST), but with a higher computational cost. To accelerate the APGST, we provide two strategies: the 3 criterion in the probability theory is introduced to accelerate the analytical windows summation and a convolution operator is derived to accelerate the time integral or summation, which generates an efficient APGST (EAPGST). Finally, the proposed EAPGST is used for seismic data attenuation compensation to improve the vertical resolution. Detailed numerical examples are used to demonstrate the validity of the proposed EAPGST in amplitude preserving and high efficiency. Field data attenuation compensation result further proves its successful application in improving the vertical resolution. Besides, the proposed EAPGST can be easily extended into other applications in discrete signal analysis, and remote-sensing and seismology fields.
Autors: Benfeng Wang;Wenkai Lu;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Abstract: A dual-band transmitarray is proposed for downlink/uplink frequencies (12.5/14.25 GHz) of Ku-band satellite communications. The basic building block for the dual-band transmitarray is a three-dipole element. Such two elements are interlaced in orthogonal polarization for each frequency band independently. This element overwhelms the basic phase restriction of a simple dipole element, and 360° phase range can be achieved in both bands with a four-layer configuration. However, it is explored (theoretically and experimentally) that three layers are preferred to be used instead of four layers due to a compromise between the phase range and reflection loss. A high-gain three-layer dual-band orthogonally polarized transmitarray is designed successfully. The measured results match well with simulation results, and high gains of 31.0 and 31.8 dBi are achieved with aperture efficiencies of 45.0% and 41.3% at 12.5 and 14.25 GHz, respectively. It also achieves 1 dB gain bandwidths of 7.2% and 7.0% in both the downlink and uplink frequency bands, respectively.
Autors: Abdul Aziz;Fan Yang;Shenheng Xu;Maokun Li;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Abstract: In this letter, we investigate the lattice staggered multicarrier faster-than-Nyquist (MFTN) signaling. Specifically, we consider the time–frequency packing and optimal hexagonal lattice over additive white Gaussian noise channels. First, an efficient implementation of the lattice staggered MFTN based on the fast Fourier transform algorithm is proposed, and we show that the modulation and demodulation complexity could be substantially reduced. Furthermore, we consider, at the receiver, a low-complexity symbol-by-symbol detector. Our practical spectral efficiency and bit-error-rate performance investigation demonstrate that the MFTN with optimal hexagonal lattice outperforms the conventional rectangular lattice.
Abstract: Magnetic resonance electrical property tomography (MR-EPT) has significant potential for the estimation of the electrical properties (EPs) of tissue, which are essential for the calculation of specific absorption rates (SAR), a critical safety factor requiring monitoring and controlling in applications of ultrahigh field magnetic resonance imaging. In this paper, a novel, efficient method based on integral equations is proposed for the calculation of the EPs and the RF-coil-induced field. An inverse problem framework is first constructed to include the forward problem operator, while the EPs are reconstructed by using a nonlinear conjugate gradient method. The RF-coil-induced component is then calculated based on the achieved EPs and the forward operator. The proposed MR-EPT algorithm improves upon and differs from the existing methods in three aspects. First, a three-dimensional algorithm with improved efficiency is proposed. The higher efficiency arises from using a fast integral equation solver as well as an approximation of initial solution. Second, in addition to the EP values, the proposed method calculates the RF-coil-induced component, which is usually neglected in the existing MR-EPT algorithms. Here, we show that considering this field can significantly improve the accuracy of the SAR calculation. Finally, in contrast to differential approaches, the proposed method is more robust against noisy measurement of the transmit magnetic fields, because of the nature of the integral equations. The proposed method is verified through a full-
wave simulation and an anatomically accurate numerical brain model, demonstrating its accuracy and efficiency.
Autors: Lei Guo;Jin Jin;Chunyi Liu;Feng Liu;Stuart Crozier;
Appeared in: IEEE Transactions on Biomedical Engineering
Abstract: In this paper, the problem of tracking desired longitudinal and lateral motions for a vehicle is addressed here. Let us point out that a “good” modeling is often quite difficult or even impossible to obtain. It is due for example to parametric uncertainties, for the vehicle mass, inertia or for the interaction forces between the wheels and the road pavement. To overcome this type of difficulties, we consider a model-free control approach leading to “intelligent” controllers. The longitudinal and the lateral motions, on one hand, and the driving/braking torques and the steering wheel angle, on the other hand, are respectively the output and the input variables. An important part of this paper is dedicated to present simulation results with actual data. Actual data, used in MATLAB as reference trajectories, have been previously recorded with an instrumented Peugeot 406 experimental car. The simulation results show the efficiency of our approach. Some comparisons with a nonlinear flatness-based control in one hand, and with a classical PID control in another hand confirm this analysis. Other virtual data have been generated through the interconnected platform SiVIC/RTMaps, which is a virtual simulation platform for prototyping and validation of advanced driving assistance systems.
Abstract: Multiframe track-before-detect (MF-TBD) usually uses sliding-window-based batch processing, where a number of the latest data frames are jointly processed at each measurement time. The sliding window mechanism compromises the operating efficiency of MF-TBD by increasing both computational costs and memory requirements, thus, heavily restricting its application in practical problems. In this paper, an improved recursive implementation for MF-TBD is proposed. Unlike the sliding-window-based implementation, the proposed method calculates the merit function, a measure of the possibility that a state is target originated, of the current batch based on an approximated recursive relationship between the merit functions of consecutive batches. As a result, instead having to process the whole batch, at any given time only the latest frame needs to be processed. The recursive relationship is first derived for any arbitrary merit function, and then explored further with several typical merit functions that are used in MF-TBD. Both the theoretical analysis and simulation results demonstrate that the proposed method can achieve almost times reduction in computational complexity and memory requirements with negligible performance loss.
Abstract: Ride-sharing (RS) has great values in saving energy and alleviating traffic pressure. Existing studies can be improved for better efficiency. Therefore, we propose a new ride-sharing model, where each driver has a requirement that if the driver shares a ride with a rider, the shared route percentage (i.e., the ratio of the shared route's distance to the driver's total travel distance) exceeds an expectation rate of the driver, e.g., 0.8. We consider two variants of this problem. The first considers multiple drivers and multiple riders and aims to compute driver-rider pairs to maximize the overall shared route percentage (SRP). We model this problem as the maximum weighted bigraph matching problem, where the vertices are drivers and riders, edges are driver-rider pairs, and edge weights are driver-rider's SRP. However, it is rather expensive to compute the SRP values for large numbers of driver-rider pairs on road networks. To address this problem, we propose an efficient method to prune many unnecessary driver-rider pairs and avoid computing the SRP values for every pair. To improve the efficiency, we propose an approximate method with error bound guarantee. The basic idea is that we compute an upper bound and a lower bound for each driver-rider pair in constant time. Then, we estimate an upper bound and a lower bound of the graph matching. Next, we select some driver-rider pairs, compute their real shortest-route distance, and update the lower and upper bounds of the maximum graph matching. We repeat above steps until the ratio of the upper bound to the lower bound is not larger than a given approximate rate. The second considers multiple drivers and a single rider and aims to find the top- drivers for the rider with the largest SRP. We first prune a large -
umber of drivers that cannot meet the SRP requirements. Then, we propose a best-first algorithm that progressively selects the drivers with high probability to be in the top- results and prunes the drivers that cannot be in the top- results. Extensive experiments on real-world datasets demonstrate the superiority of our method.
Autors: Na Ta;Guoliang Li;Tianyu Zhao;Jianhua Feng;Hanchao Ma;Zhiguo Gong;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Abstract: An efficient self-powered synchronous electric charge extraction CMOS interface circuit dedicated to piezoelectric harvesters is proposed in this paper. Self-powered peak detection (PKD) and switch circuits are used to reduce quiescent current so that the backup or pre-charged power can be saved. A new low phase lag (LPL) PKD circuit is designed to improve the synchronous extraction efficiency, which only requires one detection capacitor to perform positive and negative PKD. The circuit can be set at general mode (G-mode) or LPL mode (LPL-mode). Under LPL-mode, the phase lag can be reduced typically by 50%, the synchronous extraction efficiency can obtained up to 94%, while the output power can reach when the piezoelectric transducer original open-circuit voltage V, which is 3.56 times of that of full-bridge rectifier standard energy harvesting circuit at the maximum power point. The minimum harvesting startup voltage is 1.7 V and is independent of the energy storage capacitor voltage . The harvesting efficiency can still reach 71.3% at V. The size of the active area is 0.5 mm2 in a 0.18- CMOS technology. Circuit may be invoked as a functional block for energy autonomous wireless sensor network node of the Internet of Things.
Autors: Ge Shi;Yinshui Xia;Xiudeng Wang;Libo Qian;Yidie Ye;Qing Li;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Abstract: Numerical methods are widely used to analyze and design microwave components for communication applications. In the implementation of any numerical technique, however, there are always a set of parameters that must be properly adjusted in order to obtain, at the same time, computational efficiency and numerical accuracy of the results. In this context, therefore, we focus in this paper on the multimode equivalent network formulation for waveguide devices, and we propose a more intuitive and efficient strategy for choosing these parameters. Following our approach, setting only one global numerical variable is sufficient to adjust automatically the specific convergence parameters of each discontinuity to give a specific level of numerical accuracy of the results. As a consequence, the computational efficiency is significantly increased. In addition, the user experience is significantly improved since our approach eliminates all lengthy convergence tests previously needed to assure good numerical accuracy. In addition to theory, we discuss in this paper a number of numerical results that clearly demonstrate how the new strategy is very effective, thereby fully validating the theoretical formulation.
Abstract: In this paper, an antenna system that is composed of eight radiating elements is presented. The eight elements consist of a set of four curved dipoles and another set of four straight dipoles, providing two diversity antenna structures. Each curved and straight dipole is designed to produce a focused gain pattern toward one dedicated quadrant. A parasitic printed reflector is introduced into the center section of the top layer of the proposed antenna to enhance the matching and the gain pattern redirection capabilities of each radiating element. In addition, the printed reflector further enhances the isolation between the various elements. The assessment of the proposed diversity antenna system is performed in a rich multipath environment for various propagation scenarios. A diversity gain between 16.5 and 19.1 dB is attained for a 1% probability level and by assuming a Rayleigh fading channel for both structures. The control of the feeding of the various elements for both diversity structures is achieved through the design and incorporation of four reconfigurable feeding networks within the antenna system. Fabrication and testing of various prototypes display very good agreement between the simulation and measured results, which validate the presented designs.
Autors: Youssef Tawk;Joseph Costantine;Christos G. Christodoulou;
Appeared in: IEEE Transactions on Antennas and Propagation
Abstract: A singly fed, electrically small, planar antenna that generates a quasi-isotropic radiation pattern is investigated. The antenna consists of a folded dipole, a pair of capacitively loaded loops (CLLs), and a coplanar stripline (CPS), which are printed on the top and bottom surfaces of a single-layer printed circuit board. Through near-field coupling with the driven CPS, the folded dipole and CLLs are both effectively excited and behave like an electric dipole and a magnetic dipole, respectively. A quasi-isotropic radiation pattern can therefore be obtained by combining the two orthogonal dipoles with the same radiation intensities and quadrature phases. To verify the idea, a prototype operating at 2.4 GHz is designed, fabricated, and measured. It has been shown that this electrically small antenna (0.165 × 0.164 × 0.006 λ3, ka = 0.73) has a −10 dB impedance bandwidth of 0.99%, a total efficiency of ∼90%, and a nearly isotropic pattern with the difference between the maximum and minimum radiated power densities given by ∼3 dB over the entire spherical radiating surface.
Autors: J. Ouyang;Y. M. Pan;S. Y. Zheng;P. F. Hu;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Abstract: Developing custom-built MR coils is a cumbersome task, in which an a priori prediction of the coils’ SNR performance, their sensitivity pattern, and their depth of penetration helps to greatly speed up the design process by reducing the required hardware manufacturing iterations. The simulation-based design flow presented in this paper takes the entire MR imaging process into account. That is, it includes all geometric and material properties of the coil and the phantom, the thermal noise as well as the target MR sequences. The proposed simulation-driven design flow is validated using a manufactured prototype coil, whose performance was optimized regarding its SNR performance, based on the presented design flow, by comparing the coil’s measured performance against the simulated results. In these experiments, the mean and the standard deviation of the relative error between the simulated and measured coil sensitivity pattern were found to be and . Moreover, the peak deviation between the simulated and measured voxel SNR was found to be less than 4%, indicating that simulations are in good accordance with the measured results, validating the proposed software-based design approach.
Autors: Andreas Horneff;Michael Eder;Erich Hell;Johannes Ulrici;Jörg Felder;Volker Rasche;Jens Anders;
Abstract: Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.
Autors: Mert Ergeneci;Kaan Gokcesu;Erhan Ertan;Panagiotis Kosmas;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Abstract: As cloud computing services have gained popularity, users view videos on websites (e.g., YouTube) to generate high CPU resource utilization and bandwidth for video streaming data centers. However, popular videos result in power-law features to cause imbalanced resource utilization. In addition, hotspot and idle servers generate extra power consumption in data centers. Previous studies considered to satisfy the requirements of users, provide faster access rates and save power consumption. However, fewer studies considered resource utilization with different popularity videos. Therefore, this paper proposes an energy efficient virtual machine (VM) management scheme with power-law features (VMPL). VMPL predicts the resource utilization of the video in the future based on the popularity, ensures enough resources for upcoming videos, and turns off idle servers for power saving. Simulation results validated by mathematical analysis show that VMPL has the best resource utilization and the lowest power consumption compared with Nash and Best-Fit algorithms.
Abstract: Image change detection (CD) is a challenging problem, particularly when images come from different sensors. In this paper, we present a novel and reliable CD model, which is first based on the estimation of a robust similarity-feature map generated from a pair of bitemporal heterogeneous remote sensing images. This similarity-feature map, which is supposed to represent the difference between the multitemporal multisensor images, is herein defined, by specifying a set of linear equality constraints, expressed for each pair of pixels existing in the before-and-after satellite images acquired through different modalities. An estimation of this overconstrained problem, also formulated as a nonlocal pairwise energy-based model, is then carried out, in the least square sense, by a fast linear-complexity algorithm based on a multidimensional scaling mapping technique. Finally, the fusion of different binary segmentation results, obtained from this similarity-feature map by different automatic thresholding algorithms, allows us to precisely and automatically classify the changed and unchanged regions. The proposed method is tested on satellite data sets acquired by real heterogeneous sensor, and the results obtained demonstrate the robustness of the proposed model compared with the best existing state-of-the-art multimodal CD methods recently proposed in the literature.
Autors: Redha Touati;Max Mignotte;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Abstract: Binary weight convolutional neural networks (BCNNs) can achieve near state-of-the-art classification accuracy and have far less computation complexity compared with traditional CNNs using high-precision weights. Due to their binary weights, BCNNs are well suited for vision-based Internet-of-Things systems being sensitive to power consumption. BCNNs make it possible to achieve very high throughput with moderate power dissipation. In this paper, an energy-efficient architecture for BCNNs is proposed. It fully exploits the binary weights and other hardware-friendly characteristics of BCNNs. A judicious processing schedule is proposed so that off-chip I/O access is minimized and activations are maximally reused. To significantly reduce the critical path delay, we introduce optimized compressor trees and approximate binary multipliers with two novel compensation schemes. The latter is able to save significant hardware resource, and almost no computation accuracy is compromised. Taking advantage of error resiliency of BCNNs, an innovative approximate adder is developed, which significantly reduces the silicon area and data path delay. Thorough error analysis and extensive experimental results on several data sets show that the approximate adders in the data path cause negligible accuracy loss. Moreover, algorithmic transformations for certain layers of BCNNs and a memory-efficient quantization scheme are incorporated to further reduce the energy cost and on-chip storage requirement. Finally, the proposed BCNN hardware architecture is implemented with the SMIC 130-nm technology. The postlayout results demonstrate that our design can achieve an energy efficiency over 2.0TOp/s/W when scaled to 65 nm, which is more than two times better than the prior art.
Autors: Yizhi Wang;Jun Lin;Zhongfeng Wang;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Abstract: One-class remote sensing classification refers to the situations when users are only interested in one specific land type without considering other types. The positive and unlabeled learning (PUL) algorithm, which trains a binary classifier from positive and unlabeled data, has been shown to be promising in one-class classification. The implementation of PUL by a single classifier has been investigated. However, implementing PUL using multiple classifiers and creating classifier ensembles based on PUL have not been studied. In this research, we investigate the implementations of PUL using several classifiers, including generalized linear model, generalized additive model, multivariate adaptive regression splines, maximum entropy, backpropagation neural network, and support vector machine, as well as three ensemble methods based on majority vote, weighted average, and weighted vote combination rules. These methods are applied in classifying the urban areas from four remote sensing imagery of different spatial resolutions, including aerial photograph, Landsat 8, WorldView-3, and Gaofen-1. Experimental results show that classifiers can successfully extract the urban areas with high accuracies, and the ensemble methods based on weighted average and weighted vote generally outperform the individual classifiers on different datasets. We conclude that PUL is a promising method in one-class remote sensing classification, and the classifier ensemble based on PUL can significantly improve the accuracy.
Autors: Ran Liu;Wenkai Li;Xiaoping Liu;Xingcheng Lu;Tianhong Li;Qinghua Guo;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Abstract: This paper develops a framework based on enhanced shadow-aided decision for multichannel synthetic aperture radar-based ground moving target indication system according to the relationships between the moving target and its shadow information in position, dimensions, and intensity. As a sort of feature information available, the moving target shadow may improve the ground target detection performance. A critical precondition for shadow utilization is to obtain the good detection performance for the moving target shadow. However, shadow detection performance will deteriorate inevitably as a result of target motion that blurs its shadow. To address this issue, a knowledge-aided shadow detection algorithm with adaptive thresholds is proposed to improve the shadow detection performance in the developed framework. Furthermore, the theoretical performance analysis is performed, which indicates that the proposed knowledge-aided shadow detection algorithm has a better performance than that of the conventional shadow detection algorithm with a fixed threshold. Finally, numerical simulation experiments are presented to demonstrate that the developed framework can obtain good results for extended ground moving target detection.
Abstract: The large number of electronics channels has become an issue to the further applications of micropattern gas detectors (MPGDs) and poses a big challenge for the integration, power consumption, cooling, and cost. Induced position encoding readout technique provides an attractive way to significantly reduce the number of readout channels. In this paper, we present an extensible induced position encoding readout method for MPGDs. The method is demonstrated by the Eulerian path of the graph theory. A standard encoding rule is provided, and a general formula of encoding and decoding for n channels is derived. Under the premise of such method, a 1-D induced position encoding readout prototyping board is designed on a cm2 thick gas electron multiplier, where 47 anode strips are readout by 15 encoded multiplexing channels. Verification tests are carried out on an 8-keV Cu X-ray source with 100- slit. The test results show a robust feasibility of the method and have a good spatial resolution and linearity in its position response. This method can dramatically reduce the number of readout channels, has potential to build large-area detectors, and can be easily adapted to other detectors like MPGDs.
Abstract: An extrapolation method was proposed to increase the calculation efficiency and the accuracy of the incident power and specific absorption rate (SAR) in resonant exposure setups. The stable incident power and SAR were derived by observing the oscillating -field envelope recorded during the finite-difference time-domain calculation. The extrapolation method was validated when applied to a waveguide loaded with two or four 35-mm-diameter Petri dishes at the -field maximum for the resonant exposure at 1800 MHz. With the extrapolation, the computational time was reduced by 80% to derive the incident power with the error reduction of 93%, as compared to the calculation with the current mechanism until the accepted wave stability. For the SAR, the computational time was reduced by 77%. With the proper position and weighting of the -field samples, the error of the averaged SAR in the cell monolayer was reduced from 4.62% to 1.31%. The proposed method applies to the scenario where the resonant frequency of the loaded setup drifts away from the driven frequency so that an oscillating -field envelope is available.
Autors: Jianxun Zhao;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Abstract: This paper discusses a method to enhance the dynamic range (DR) of a conventional CMOS image sensor in low- and high-light environment using in-pixel parametric amplification. The parametric amplification gives a linear and noiseless gain. The source follower in a conventional 4T pixel is used as a capacitor for charge amplification by varying its capacitance periodically. This reconfiguration helps in signal amplification without affecting the pixel fill factor drastically. The simulation results show that over 60-dB DR extension in the low and high illuminations can be achieved enhancing the total DR of the pixel to 120 dB.
Abstract: Sympathetic interaction between transformers is a quite normal phenomenon in power systems. For the purpose of preventing transformer differential protection relays from malfunction, this paper proposes a morphological method for the identification of sympathetic inrush, which is the first time when mathematical morphology is applied in this field. Since the waveform of differential current is symmetrical in an internal fault case while asymmetrical in a sympathetic inrush case, the proposed method uses a morphological operator to extract the peaks and valleys of the differential current to distinguish sympathetic inrush. Considering the possible current-transformer (CT) saturation conditions, this paper combines a morphological gradient with a weighted mathematical morphological operator to improve the effectiveness of the proposed method. The proposed method is evaluated on data collected from simulation cases established in PSCAD/EMTDC and from laboratory experiments, respectively. Identification results have verified that by comparing with the traditional second harmonic restrain method, the proposed method can distinguish sympathetic inrush from an internal fault current more accurately and more effectively, even when the CT is fully saturated.
Autors: A. Q. Zhang;T. Y. Ji;M. S. Li;Q. H. Wu;L. L. Zhang;
Abstract: This paper considers the problem of multipath ghosts elimination for the through-wall radar imaging. We formulate a discrete signal model in the presence of first-order multipath, and propose an imaging dictionary based algorithm to suppress the multipath ghosts. Specifically, first, several estimated images are obtained via two different kinds of imaging dictionaries for the focus delays related to the direct propagation path and the multipaths, respectively. We find that all the estimated images possess large values around the genuine target positions and the multipath ghosts of them do not overlap with each other. Then, based on this feature, these images are fused via incoherent multiplication image fusion method to yield a multipath ghosts free image. Finally, the simulation and real data are used to prove the validity of the proposed approach.
Abstract: This paper proposes an improved subdomain model of squirrel-cage induction machines (SCIMs) with imposed stator currents. This new model enables to accurately compute electromagnetic quantities such as air-gap flux density, instantaneous torque and forces, and electromotive force including all harmonic contents. The first improvement is to explicitly account for rotor motion with time-stepping technique. The second improvement consists in modeling the skin effect in rotor bars by considering each space harmonic of the stator magnetomotive force separately. Eddy currents in rotor bars are therefore “skin limited” and not “resistance limited.” The results are then validated with linear transient finite-element analysis for both no-load and load cases, taking a topology of squirrel-cage machine already used in the previous references. The time and spatial harmonic content of all electromagnetic quantities is also validated by comparison with analytical expressions. The computation time is a hundred times lower than finite element as it does not require achieving a numerical transient first, and the resolution for a time step is shorter. Thanks to its computational efficiency and intrinsic mesh insensitivity, this method is particularly suited to magnetic forces computation and vibroacoustic analysis of SCIMs.
Autors: Emile Devillers;Jean Le Besnerais;Thierry Lubin;Michel Hecquet;Jean-Philippe Lecointe;
Abstract: A grid-supportive two-stage three-phase three-wire solar photovoltaic (SPV) system is presented in this paper, wherein a boost converter is used as a first stage to serve the function of maximum power point tracking and a three-leg voltage source converter is used to feed the extracted SPV energy, along with the supporting distribution system for improvement in the power quality. The harmonics elimination, grid currents balancing, and compensation for nonactive part of the load currents are extra features offered by the proposed system other than conventional features of the solar inverter. The true power reflecting part of the load current is estimated using an improved adjustable step adaptive neuron-based control approach. Moreover, a feed-forward term is added as photovoltaic (PV) array contribution to grid currents, which helps in fast dynamic response due to ambience changes. The output of which is a current component reflected on grid side to instantaneously regulate the dc-link voltage. In the proposed approach, the load, PV array, and loss contributions are kept decoupled. The feasibility of the proposed control algorithm is confirmed via experimental results.
Autors: Bhim Singh;Chinmay Jain;Anmol Bansal;
Appeared in: IEEE Transactions on Industry Applications
Abstract: A cooperative cognitive radio network (CRN) with improved energy detection-based spectrum sensing is analyzed in various fading scenarios. Generalized multipath (Nakagami-) fading and enriched multipath (Nakagami-) fading models are considered along with two other general fading distributions, i.e., - and - distributions. For spectrum sensing, instead of conventional power 2-based detection method, the arbitrary power -based improved energy detector is used. The impact of the cognitive user mobility on the performance of the improved energy detector is investigated. Specifically, the statistics for the received signal are derived over various fading environments. The performance of the considered CRN system is evaluated in terms of probability of false alarm, probability of missed detection, and receiver operating characteristics (ROC) curves. Moreover, the area under the ROC curve is also obtained. Simulation results are provided to corroborate the theoretical results derived in this paper.
Autors: Lokesh Gahane;Prabhat Kumar Sharma;Neeraj Varshney;Theodoros A. Tsiftsis;Preetam Kumar;
Abstract: A small signal model of a multi-infeed high-voltage direct current (HVdc) transmission system containing a line commutated converter (LCC) and a voltage source converter (VSC) is developed. This model represents the LCC and VSC converters as operational impedances as seen from the converter ac busbar. This permits the converters to be included in the effective short-circuit ratio (ESCR) calculations. The resulting ESCR is referred to in this paper as the “Impedance based Effective Short Circuit Ratio” (IESCR). It is shown that the maximum power transfer limit (referred to as the maximum available power or MAP) of the converters is better predicted by this index compared to the conventional ESCR which ignores the operational impedances of the converters. The question also arises as to how close to this theoretical maximum power transfer limit can the HVdc system operate. Using the small-signal model, it is shown that with commonly used control strategies, the predicted MAP can only be achieved by reducing the controller gains. The results are validated using detailed electromagnetic transients simulation of the multi-infeed VSC-LCC system.
Autors: Xiaojun Ni;Aniruddha M. Gole;Chengyong Zhao;Chunyi Guo;
Abstract: We proposed an improved phase-based method by using a filtering window on the low-coherence interferogram. Through theoretical derivation and numerical simulation, we prove the correction of our proposed method that the fringe phase can be demodulated nondestructively after applying a symmetrical filtering window nearby the envelope peak, and our method can enhance system SNR. Since fringe overlap phenomenon arising from narrow bandwidth occurs frequently in single-mode sensing system, this method is especially applicable to remote sensing wherein the localization of interference fringe is difficult using traditional phase-based methods. To verify this method, an experiment with a single-mode fiber Fabry-Perot air pressure sensing system was carried out. The experiment results showed that the precision using our method decreased to less than 0.053 in full 280 kPa pressure scale and the sensing distance extended to 20 km, which were apparently superior to traditional phase-based methods.
Autors: Kun Liu;Dongdong Ju;Shuang Wang;Junfeng Jiang;Mengnan Xiao;Xue Wang;Tiegen Liu;
Abstract: An RF CMOS model incorporating an improved substrate coupling network is developed. The proposed model focuses on characterizing the nonlinear phase of S12 when a transistor is under zero-bias condition. In addition, a corresponding parameter extraction technique of the model is proposed. To validate this model, a set of transistors fabricated in a commercial 90-nm CMOS process is investigated under multibias conditions. Comparison between measurement and calculation results shows that good agreement has been achieved, which indicates that the proposed model can accurately characterize the performance of transistors up to 66 GHz.
Abstract: Despite the advancement of the tremor assessment systems, the current technology still lacks a method that can objectively characterize tremors in relative segmental movements. This paper presents a measurement system, which quantifies multi-degrees-of-freedom coupled relative motions of hand–arm tremor, in terms of joint angular displacement. In-laboratory validity and reliability tests of the system algorithm to provide joint angular displacement was carried out by using the two-degrees-of-freedom tremor simulator with incremental rotary encoder systems installed. The statistical analyses show that the developed system has high validity results and comparable reliability performances using the rotary encoder system as the reference. In the clinical trials, the system was tested on 38 Parkinson’s disease patients. The system readings were correlated with the observational tremor ratings of six trained medical doctors. The moderate to very high clinical correlations of the system readings in measuring rest, postural and task-specific tremors add merits to the degree of readiness of the developed tremor measurement system in a routine clinical setting and/or intervention trial for tremor amelioration.
Autors: Ping Yi Chan;Zaidi Mohd Ripin;Sanihah Abdul Halim;John Tharakan;Mustapha Muzaimi;Kwang Sheng Ng;Muhammad Imran Kamarudin;Gaik Bee Eow;Jyh Yung Hor;Kenny Tan;Chun Fai Cheah;Nelson Soong;Linda Then;Ahmad Shukri Yahya;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Abstract: We consider the transmission of a common message from a transmitter to three receivers over a broadcast channel, referred to as a multicast channel in this case. All the receivers are allowed to cooperate with each other over full-duplex non-orthogonal cooperation links. We investigate the information-theoretic upper and lower bounds on the transmission rate. In particular, we propose a three-receiver fully interactive cooperation scheme (3FC) based on superpositions of compress-forward (CF) and decode-forward (DF) at the receivers. In the 3FC scheme, the receivers interactively perform CF simultaneously to initiate the scheme, and then DF sequentially to allow a correlation of each layer of the DF superposition in cooperation with the transmitter toward the next receiver in the chain to improve the achievable rate. The analysis leads to a closed-form expression that allows for numerical evaluation, and also gives some insight on key points to design interactive schemes. The numerical results provided in the Gaussian case show that the proposed scheme outperforms the existing schemes and show the benefits of interaction.
Autors: Victor Exposito;Sheng Yang;Nicolas Gresset;
Appeared in: IEEE Transactions on Wireless Communications
Abstract: In the purpose of improving the complexity and the security of chaotic communication system, a novel electro-optical intensity chaotic system using electrical mutual injection with nonlinear transmission function is proposed. The electro-optical intensity chaotic system consisting of two delay feedback branches in a serial configuration extends keys space scale. The dynamic characteristics of the proposed system are investigated by means of the bifurcation diagram, the largest Lyapunov exponents, and the permutation entropy, and the security are also analyzed through the autocorrelation function and the delayed mutual information. The simulation results show that the proposed system can acquire higher complexity and the better security, compared with the recent ones. The scheme allows the system to enter chaos with a low gain and the time-delay concealed effectively due to a nonlinear transmission function. Besides, the communication synchronization on basis of the proposed system is discussed. It comes to a conclusion that the proposed chaotic system has potential applications in secure communications.
Abstract: In this paper, we describe and evaluate a new monitor that uses inertial navigation system (INS) measurements to detect spoofing attacks on global navigation satellite system (GNSS) receivers. Spoofing detection is accomplished by monitoring the Kalman filter innovations in a tightly coupled INS/GNSS mechanization. Monitor performance is evaluated against worst case spoofing attacks, including spoofers capable of tracking vehicle position. There are two main contributions of this paper. The first is a mathematical framework to quantify postmonitor spoofing integrity risk. The second is an analytical expression of the worst case sequence of spoofed GNSS signals. We then apply these to an example spoofing attack on a Boeing 747 on final approach. The results show that GNSS spoofing is easily detected, with high integrity, unless the spoofer's position-tracking devices have unrealistic, near-perfect accuracy, and no delays.
Abstract: Surface deformations caused by underground mining are time-dependent and highly nonlinear, and can result in progressive damage to surface structures during underground extraction. However, the previous methods based on the interferometric synthetic aperture radar (InSAR) technique are generally incapable of accurately predicting the mining-induced dynamic deformations occurring during the entire period of underground extraction, due to the inaccurate model parameters inverted under the condition of ignoring the horizontal motions of the InSAR-derived measurements and the model errors for predicting dynamic deformations. Consequently, the risk of mining-related structural damage cannot be reliably assessed based on the deformations predicted by the previous InSAR-based methods. To overcome this limitation, we propose a novel method that combines InSAR with a new mining deformation model: the temporal probability integral method (TPIM). Theoretically, the integration of InSAR and TPIM allows the InSAR-TPIM to accurately predict mining-induced dynamic deformations occurring in the entire period of underground extraction. Furthermore, InSAR-TPIM can reliably assess mining-related progressive structural damage based on the predicted dynamic deformations. However, these advantages cannot be achieved by the previous InSAR-based methods. The Qianyingzi coal mining area of China is selected to test the proposed method. The results demonstrate that the accuracies of the predicted dynamic deformations are about 0.030 and 0.041 m in the horizontal and vertical directions, respectively, which can meet the accuracy requirements of mining-induced dynamic deformation prediction. Furthermore, the comparison between the potential structural damage predicted by the proposed method and the previous InSAR-based methods indicates that the damage risks of around 131 buildings (43.9% of the 298 buildings) are underestimated by the previous InSAR-base-
Abstract: Research and development (R&D) projects are crucial for semiconductor companies to maintain growth, profitability, and competitiveness. Integrated circuit (IC) design is capital intensive and continuously migrates to new technologies to meet various market demands. Moreover, the scheduling of selected R&D projects that enables technology roadmap involving complicated interrelationships, while competing for similar resources. Focusing on realistic needs, this paper aims to propose an integrated approach for selecting IC design projects for R&D portfolios and scheduling the selected projects simultaneously. In particular, a hybrid autotuning multiobjective genetic algorithm was developed to solve large sized problem instances. An empirical study was conducted at a leading IC design service company in Taiwan to test the validity of the proposed approach. The proposed algorithm was compared with conventional approaches for both convergence and diversity. The results have shown the practical viability of this approach in efficiently and effectively generating near-optimal portfolio alternatives for portfolio selection. The approach also enables the scheduling of the selected projects to achieve R&D portfolio objectives. The developed solution was fully implemented and adopted by the company.
Autors: Chen-Fu Chien;Nhat-To Huynh;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Abstract: This paper proposes a unique integrated and isolated dual-output dc–dc resonant converter, which can interface both HV traction batteries and LV loads. In addition, the proposed topology is bidirectional, capable of delivering power from HV traction batteries to the grid for vehicle-to-grid (V2G) applications. To increase the power density of the converter, the dual-output dc–dc resonant converter combines magnetic components of resonant networks into a single three-winding electromagnetically integrated transformer. The resonant converter uses a half-bridge topology with split capacitors as the resonant network components to further reduce the size of a converter. The variable dc-link voltage strategy is utilized to enhance the efficiency over the entire output voltage range. A 3.3-kW converter is designed and developed for validation of various operation modes, including grid-to-vehicle, V2G, and HV-to-LV charging.
Abstract: An integrated fiber Michelson interferometer (MI) based on an asymmetrical twin-core fiber (TCF) cascaded with a side-hole fiber (SHF) for multiparameter sensing is proposed and demonstrated. The asymmetrical TCF consists of a centric core and an eccentric core with same refractive index. The centric core of the TCF is aligned with the core of the SHF and the eccentric core is aligned with one air hole of the SHF. Because the eccentric core of the TCF is off the axis of the fiber, a bend or twist will cause a variation of the optical path difference of the MI, which makes the MI structure be suitable for twist and vector curvature measurements. Experimental results show that the bending sensitivities of the sensor are −6.968 and 6.978 nm/m−1 at the bending directions of 0° and 180° in the curvature ranges of 0–10.708 m−1, respectively, and the twist sensitivity of the sensor is 0.639 nm/(rad/m) in the twist ranges of 0–7.44 rad/m. The structure is also sensitive to strain and temperature, and the strain and temperature sensitivities of the interferometer are 1.36 pm/ and 10.37 pm/°C, respectively.
Abstract: This communication presents a novel integrated antenna system for cognitive radio (CR) applications. The design consists of a compact four-element reconfigurable annular slot-based multiple-input-multiple-output (MIMO) antenna system integrated within an ultrawideband (UWB) sensing antenna. All the antenna elements are planar in structure and designed on a single substrate (RO-4350) with dimensions mm3. The frequency reconfigurable slot-based MIMO antenna system is tuned over a wide frequency band from 1.77 to 2.51 GHz while the UWB sensing antenna is covering from 0.75 to 7.65 GHz The proposed antenna system is suitable for CR enabled wireless devices. The envelop correlation coefficient did not exceed 0.248 in the entire operating band of the MIMO antenna part. The maximum measured gain of the MIMO antenna is 3.2 dBi with a maximum efficiency of 81%.
Autors: Rifaqat Hussain;Mohammad S. Sharawi;Atif Shamim;
Appeared in: IEEE Transactions on Antennas and Propagation
Abstract: This paper presents the integration of a diplexer with a corporate feed network of a high gain slot array antenna at the Ka-band. A hybrid diplexer-splitter with a novel architecture is proposed to have compatibility for its direct integration with the feed network of the array antenna. A seventh-order hybrid diplexer-splitter is successfully integrated into a corporate feed network of a slot array antenna. The proposed integrated diplexer-antenna module consists of three distinct metal layers without the need of electrical contacts between the different layers based on the recently introduced gap waveguide technology. The designed module has two channels of 650-MHz bandwidths each with center frequencies 28.21 and 29.21 GHz. The fabricated prototype provides good radiation and input impedance characteristics. The measured input reflection coefficients for both Tx/Rx ports are better than −13 dB with the measured antenna efficiency better than 60% in the designed passband, which includes the losses in the diplexer.
Autors: Abbas Vosoogh;Milad Sharifi Sorkherizi;Ashraf Uz Zaman;Jian Yang;Ahmed A. Kishk;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Abstract: This letter presents a single-mode tunable laser operating in the -band. The facetless design, along with a regrowth-free fabrication that does not require high-resolution lithography techniques, contributes to make the laser a suitable candidate for monolithic integration with other components. Tuning is demonstrated over a range of 47 nm, with side-mode suppression ratio values over 30 dB and a linewidth of 800 kHz.
Autors: Ludovic Caro;Mohamad Dernaika;Niall P. Kelly;Padraic E. Morrissey;Justin K. Alexander;Frank H. Peters;
Abstract: Inter-cloud is an approach that facilitates scalable resource provisioning across multiple cloud infrastructures. In this paper, we focus on the performance optimization of Infrastructure as a Service (IaaS) using the meta-scheduling paradigm to achieve an improved job scheduling across multiple clouds. We propose a novel inter-cloud job scheduling framework and implement policies to optimize performance of participating clouds. The framework, named as Inter-Cloud Meta-Scheduling (ICMS), is based on a novel message exchange mechanism to allow optimization of job scheduling metrics. The resulting system offers improved flexibility, robustness and decentralization. We implemented a toolkit named “Simulating the Inter-Cloud” (SimIC) to perform the design and implementation of different inter-cloud entities and policies in the ICMS framework. An experimental analysis is produced for job executions in inter-cloud and a performance is presented for a number of parameters such as job execution, makespan, and turnaround times. The results highlight that the overall performance of individual clouds for selected parameters and configuration is improved when these are brought together under the proposed ICMS framework.
Abstract: The reduction of road congestion requires intuitive urban congestion-control platforms that can facilitate transport stakeholders in decision making. Interactive ITS visual analytics tools can be of significant assistance, through their real-time interactive visualizations, supported by advanced data analysis algorithms. In this paper, an interactive visual analytics platform is introduced that allows the exploration of historical data and the prediction of future traffic through a unified interactive interface. The platform is backed by several data analysis techniques, such as road behavioral visualization and clustering, anomaly detection, and traffic prediction, allowing the exploration of behavioral similarities between roads, the visual detection of unusual events, the testing of hypotheses, and the prediction of traffic flow after hypothetical incidents imposed by the human operator. The accuracy of the prediction algorithms is verified through benchmark comparisons, while the applicability of the proposed toolkit in facilitating decision making is demonstrated in a variety of use case scenarios, using real traffic and incident data sets.
Abstract: In this paper, we examine the relationship between justice dimensions (procedural, distributive, and interactional justice) and conflict (task and relationship) in buyer–supplier relationships. We develop a nuanced understanding of how justice dimensions reduce task and relationship conflict in buyer–supplier relationships. In addition, we hypothesize that task conflict mediates the relationship between justice dimensions and relationship conflict. We also hypothesize that the effect of justice dimensions on conflict is contingent on the buyer–supplier cultural distance and the degree of autonomy provided to the supplier. Based on primary data on buyer–supplier relationships, our results show that procedural and interactional justice dimensions are more important than distributive fairness. Furthermore, managers can reduce the relationship conflict by mitigating task conflict, which has not been asserted in the buyer–supplier relationship literature. Our results suggest that supplier autonomy and cultural distance, as contextual variables, influence the relationship between interactional justice and conflict dimensions, but they do not influence the relationship between procedural or distributive justice and conflict dimensions. We discuss the relative importance and role of the three justice dimensions in mitigating relational conflicts in buyer–supplier relationships, and implications of our results to theory as well as practice.
Autors: Ravi Srinivasan;Sriram Narayanan;Ram Narasimhan;
Appeared in: IEEE Transactions on Engineering Management
Abstract: A new isolated current-fed zero-current switched (ZCS) front-end dc/dc converter based multilevel inverter is proposed for multi-input applications. The proposed front-end converter with only two controllable switches integrates two different renewable energy sources, resulting in an advantageous compact structure and low conduction losses. The ZCS turn-off is achieved in both the controllable switches with the proposed modulation scheme. The converter maintains ZCS turn-off under a wide load, as well as input voltage variations by employing frequency modulation along with a variable duty ratio technique. Simple structure, soft switching, high gain, and automatic load regulation make the converter structure novel for simultaneous power management in multi-input renewable energy applications. Converter operation and design guidelines have been outlined. A laboratory prototype of the proposed converter is developed and tested at 300-W power level. Simulations and experimental results demonstrate the robust performance of the converter under load, as well as input source voltage variations.
Autors: Naresh Kumar Reddi;Manoj R. Ramteke;Hiralal M. Suryawanshi;Koteswararao Kothapalli;Snehal P. Gawande;
Appeared in: IEEE Transactions on Industry Applications
Abstract: The dc tap or dc transformer will play an important role in interfacing different voltages of dc links in dc grids. This paper presents an isolated resonant mode modular converter (RMMC) with flexible modulation and assorted configurations to satisfy a wide variety of interface requirements for medium-voltage dc (MVdc) networks. The transformerless RMMC, as introduced in the literature, implemented a restricted modulation scheme leading to a very limited range of step ratio and the diode rectifier resulted in unidirectional power flow. Both of these limitations are removed in this proposal and galvanic isolation has also been added. Moreover, this new RMMC approach can serve as a building block for variety of configurations. Two such derived topologies are given, which inherently balance the voltage and current between different constituent circuits and realize the high power rating conversion for very low or very high step-ratio application. The theoretical analysis is validated by a set of full-scale simulations and a downscaled experimental prototype. The results illustrate that this isolated RMMC and its derivatives have promising features for dc taps or dc transformers in MVdc applications.
Autors: Xin Xiang;Xiaotian Zhang;Geraint P. Chaffey;Timothy C. Green;
Abstract: Inspired by the recent advances in deep learning, we propose a novel iterative belief propagation – convolutional neural network (BP-CNN) architecture for channel decoding under correlated noise. This architecture concatenates a trained CNN with a standard BP decoder. The standard BP decoder is used to estimate the coded bits, followed by a CNN to remove the estimation errors of the BP decoder and obtain a more accurate estimation of the channel noise. Iterating between BP and CNN will gradually improve the decoding SNR and, hence, result in better decoding performance. To train a well-behaved CNN model, we define a new loss function that involves not only the accuracy of the noise estimation but also the normality test for the estimation errors, i.e., to measure how likely the estimation errors follow a Gaussian distribution. The introduction of the normality test to the CNN training shapes the residual noise distribution and further reduces the bit error rate of the iterative decoding, compared to using the standard quadratic loss function. We carry out extensive experiments to analyze and verify the proposed framework.1
Code is available at https://github.com/liangfei-info/Iterative-BP-CNN.
Autors: Fei Liang;Cong Shen;Feng Wu;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Abstract: Nowadays, the simulation tools used to perform power system analysis are evolving into the many-core computation era; some of these techniques propose to tear the power system network into several subnetworks (islands) for its parallel processing. The island's detection is an issue considered by the power flow analysis due to management activities such as feeder reconfiguration, fault detection, and isolation, among others, that generate topological changes. These methods include graph theory, checking the circuit breaker status and on-site measurements, decision trees, frequency deviation, and pattern recognition, among other techniques, which are focused to detect topology changes that may generate islands and affect the state estimation of the system. In contrast, other techniques such as the approximate minimum degree perform a reorganization of the matrix that describes the network components and their connectivity, looking to factorizing the matrix to solve the power flow problem. These techniques are very functional and efficient; however, some of them require detailed information of the network, and are addressed to cover meshed and radial network configurations separately. This paper presents an iterative algorithm that uses the compressed coordinate branch-to-node matrix for detecting, classifying, and grouping islands within sparse matrixes, describing mesh or radial networks. This algorithm is a valuable tool to simplify islands location and can be implemented using any programing language due to its simplicity. This method is used in Distribution System Simulator - Real Time Version (DSSim-RT), which is a simulator based in OpenDSS, for tearing the power system network to allow the multithread power flow analysis of distribution sys-
ems in real time.
Autors: Davis Montenegro;Gustavo A. Ramos;Seddik Bacha;
Appeared in: IEEE Transactions on Industry Applications
Abstract: If a nominally L-shaped sensor-array's two legs are not exactly perpendicular, its azimuth-polar direction-of-arrival estimation would be degraded. This paper quantifies this degradation via a deterministic Cramér–Rao bound analysis of the direction-finding error variance.
Autors: Dominic Makaa Kitavi;Kainam Thomas Wong;Chun-Chiu Hung;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Abstract: Efficient communication through a multi-hop network with packet loss requires random linear network coding schemes with low computation cost and high throughput. In this paper, we propose a low-density parity-check (LDPC)-based framework for constructing chunked code, a variation of random linear network code with low encoding/decoding computational cost and small coefficient vector overhead. Two classes of chunked codes with LDPC structures, named uniform LDPC-chunked codes and overlapped LDPC-chunked (OLC) codes, are studied under a general chunk transfer matrix model. ULC codes achieve rates close to the optimum and perform better than existing chunked codes that employ parity-check constraints. OLC codes are overlapped chunked codes, where it is not necessary to generate new packets for encoding, and demonstrate much higher rates in certain scenarios than the state-of-the-art designs of overlapped chunked codes. These results justifies the feasibility of this LDPC approach for communication through multi-hop networks with packet loss.
Abstract: This paper presents an IC implementation of on-chip learning neuromorphic autoencoder unit in a form of rate-based spiking neural network. With a current-mode signaling scheme embedded in a 500 × 500 6b SRAM-based memory, the proposed architecture achieves simultaneous processing of multiplications and accumulations. In addition, a transposable memory read for both forward and backward propagations and a virtual lookup table are also proposed to perform an unsupervised learning of restricted Boltzmann machine. The IC is fabricated using 28-nm CMOS process and is verified in a three-layer network of encoder–decoder pair for training and recovery of images with two-dimensional pixels. With a dataset of 50 digits, the IC shows a normalized root mean square error of 0.078. Measured energy efficiencies are 4.46 pJ per synaptic operation for inference and 19.26 pJ per synaptic weight update for learning, respectively. The learning performance is also estimated by simulations if the proposed hardware architecture is extended to apply to a batch training of 60 000 MNIST datasets.
Abstract: In order to real-time online monitoring the reaction substrates for biological processes, we designed an on-line Fourier transform infrared spectrometer measurement system, which has the advantages of low cost, simple and compact structure, good reliability, and strong shock resistance compared with the traditional Fourier transform infrared spectrometer. This system consists of two core components, i.e., a high-performance interferometer and an attenuated total reflectance (ATR) probe. In the interferometer, we 1) combined corner cube mirrors and flat mirrors to avoid tilting of the moving mirror; 2) set 60° incident angle to the ZnSe beam splitter to improve the luminous flux; 3) shared folded optical path with both the infrared light and the reference laser to improve compactness in structure; and 4) drive the moving mirror by a parallelogram swing flexible support module to make it move smoothly. In the ATR probe, we utilized two large diameter and inner coating light pipes to transmit the incident and outgoing light to enhance the luminous flux further. We also simulated the optical system and did some off-line and online measurement experiments. The results show the spectrometer has satisfactory reliability, large luminous flux, and online measurement capability. It can be real-time online monitoring the biological process through measuring the concentration of the related bioreactor reactant. The online analysis has wide application prospects in biological, chemical testing, material analysis, and many other fields.