ID
int64 0
400k
| content
stringlengths 97
5.85k
|
|---|---|
1,600
|
Please write an abstract with title: Methods of Increasing the Energy Storage Density of Superconducting Flywheel, and key words: Flywheels, Stress, Energy storage, Magnetic levitation, High-temperature superconductors, Wheels, Statistics. Abstract: This paper presents methods of increasing the energy storage density of flywheel with superconducting magnetic bearing. The working principle of the flywheel energy storage system based on the superconducting magnetic bearing is studied. The circumferential and radial stresses of composite flywheel rotor at high velocity are analyzed. The optimization methods of the thickness distribution of the flywheel rim and the material selection of the flywheel in the multi-layer interference assembly with a certain size are given and used to maximize the energy storage density. Finally, the improved flywheel model is established, and the maximum energy storage density of the flywheel is increased by combining the above methods.
|
1,601
|
Please write an abstract with title: A practical rebinning-based method for patient motion compensation in SPECT imaging, and key words: Motion compensation, Single photon emission computed tomography, Motion detection, Image reconstruction, Data acquisition, Event detection, Cameras, Biomedical imaging, Medical diagnostic imaging, Degradation. Abstract: Single photon emission computed tomography (SPECT) studies require the patient to remain motionless for protracted period of time. But considerable patient discomfort can lead to patient motion, which will introduce the image artifacts and degrade resolution. If the patient motion can be detected, it is possible to compensate for the motion to reduce or eliminate the artifacts. In this paper a method based on visual-tracking-system (VTS) is presented to compensate for the patient motion during data acquisition. VTS will get the exact position and orientation that are independent of the SPECT system. During data acquisition each detected photon produces an event that is written to a file. Each event includes the photon location, energy and time. The list of events is adjusted by compensation algorithm to produce a corrected set of motion-free observations. In the compensation process, the projections can be repositioned and reconstructed with ordered subsets expectation maximization (OSEM) algorithm. By comparing the corrected result and uncorrected result our compensation method can be assessed.
|
1,602
|
Please write an abstract with title: In Remembrance of Gerald Burke [In Memoriam], and key words: Obituaries, Burke, Gerald. Abstract: Recounts the career and contributions of Gerald Burke.
|
1,603
|
Please write an abstract with title: Semi-supervised Learning Framework for UAV Detection, and key words: Radio frequency, Bluetooth, RF signals, Semisupervised learning, Fingerprint recognition, Feature extraction, Unmanned aerial vehicles. Abstract: The use of supervised learning with various sensing techniques such as audio, visual imaging, thermal sensing, RADAR, and radio frequency (RF) have been widely applied in the detection of unmanned aerial vehicles (UAV) in an environment. However, little or no attention has been given to the application of unsupervised or semi-supervised algorithms for UAV detection. In this paper, we propose a semi-supervised technique and architecture for detecting UAVs in an environment by exploiting the RF signals (i.e., fingerprints) between a UAV and its flight-controller communication under wireless inference such as Bluetooth and WiFi. By decomposing the RF signals using a two-level wavelet packet transform, we estimated the second moment statistic (i.e., variance) of the coefficients in each packet as a feature set. We developed a local outlier factor model as the UAV detection algorithm using the coefficient variances of the wavelet packets from WiFi and Bluetooth signals. When detecting the presence of RF-based UAV, we achieved an accuracy of 96.7% and 86% at a signal-to-noise ratio of 30 dB and 18 dB, respectively. The application of this approach is not limited to UAV detection as it can be extended to the detection of rogue RF devices in an environment.
|
1,604
|
Please write an abstract with title: Parallel Phylogenetic Inference, and key words: Phylogeny, Topology, Systematics, Sequences, Data analysis, DNA, Biology, Maximum likelihood estimation, Bifurcation, Parallel algorithms. Abstract: Recent advances in DNA sequencing technology have created large data sets upon which phylogenetic inference can be performed. However, current research is limited by the prohibitive time necessary to perform tree search on even a reasonably sized data set. Some parallel algorithms have been developed but the biological research community does not use them because they don’t trust the results from newly developed parallel software. This paper presents a new phylogenetic algorithm that allows existing, trusted phylogenetic software packages to be executed in parallel using the DOGMA parallel processing system. The results presented here indicate that data sets that currently take as much as 11 months to search using current algorithms, can be searched in as little as 2 hours using as few as 8 processors. This reduction in the time necessary to complete a phylogenetic search allows new research questions to be explored in many of the biological sciences.
|
1,605
|
Please write an abstract with title: A numerical approximation method for the valuation of multivariate contingent claims, and key words: Approximation methods, Cost accounting, Lattices, Stability, Pricing, Contingency management, Technology management, Engineering management, Production engineering, Investments. Abstract: A numerical approximation method for the valuation of multivariate contingent claims is presented. It extends the Trigeorgis' (1991) log-transformed binomial approach for one asset to more general case of several assets. The proposed method overcomes the problems of poor consistency, stability and efficiency inherent in the Boyle, Evinie and Gibbs (1989) approach. It can achieve the similar performance as that of the Ekvall (1996) approach while alleviates its difficulty in maintaining reasonable up- and down-jump sizes.
|
1,606
|
Please write an abstract with title: Research on Intelligent Operation and Maintenance System of Urban Rail Transit Vehicles Based on PHM Technology, and key words: Rails, Fault diagnosis, Data preprocessing, Maintenance engineering, Hardware, Real-time systems, Safety. Abstract: Based on the current situation of rail operation and maintenance of urban rail transit, combined with the technical system of fault diagnosis and health management (PHM), the operation and maintenance requirements of urban rail transit vehicles are investigated in depth. Due to the feasibility and superiority of PHM technology in rail operation and maintenance management, an intelligent operation and maintenance system for urban rail transit vehicles based on PHM technology is designed. Through PHM technology framework, the key hardware of the system is designed. Based on the hardware system, the vehicle information management module, operation day plan management module, data preprocessing module, health status identification module, operation and maintenance decision module and construction operation management module are established. The results show that the effectiveness of the designed system is proved through functional and performance tests, which provides solutions for the intelligent operation and maintenance of urban rail transit vehicles, and improves the safety and economy of operation and maintenance.
|
1,607
|
Please write an abstract with title: Receptive Field Size as a Key Design Parameter for Ultrasound Image Segmentation with U-Net, and key words: Kernel, Image segmentation, Neurons, Task analysis, Computer architecture, Ultrasonic imaging, Biomedical imaging. Abstract: Automatic and accurate segmentation of medical images is an important task due to the direct impact of this procedure on both disease diagnosis and treatment. Segmentation of ultrasound (US) imaging is particularly challenging due to the presence of speckle noise. Recent deep learning approaches have demonstrated remarkable findings in image segmentation tasks, including segmentation of US images. However, many of the newly proposed structures are either task specific and suffer from poor generalization, or are computationally expensive. In this paper, we show that the receptive field plays a more significant role in the network's performance compared to the network's depth or the number of parameters. We further show that by controlling the size of the receptive field, a deep network can instead be replaced by a shallow network.
|
1,608
|
Please write an abstract with title: Smart Logistics Across Smart Border, and key words: Bridges, Smart cities, Roads, Laboratories, Sharing economy, Throughput, Permeability. Abstract: This paper discusses how Smart Logistics could be linked with the Smart Border concept earlier proposed for the El Paso - Ciudad Juarez bi-national metropolitan area. The focus is on the international road and pedestrian bridges connecting these two cities as these were identified as bottlenecks for cross-border movement of goods and cross-border mobility of people. The proposal presents the basic strategic and operative framework. Examples of smart logistics measures that could be implemented on the border and beyond the border such as autonomous vehicles, micro depots and crowd shipping are presented and discussed. The paper shall be understood as the case for the cross-border logistics in relation to the Smart Border concept and as the starting point for further exploration.
|
1,609
|
Please write an abstract with title: Robust Speed Tracking Control of Permanent Magnet Synchronous Linear Motor Based on a Discrete-Time Sliding Mode Load Thrust Observer, and key words: Observers, Control systems, Switches, Permanent magnet motors, Mathematical models, Servomotors, Heuristic algorithms. Abstract: In this article, we proposed a discrete-time sliding mode load thrust observer to reduce the influence of load thrust mutation on the linear motor and improve the antiinterference ability and speed tracking performance of the system. First, the electrical and dynamic models of linear motor are established, and the limitation of conventional double-closed-loop control based on proportional integral (PI) algorithm is analyzed. Second, the extended state equation of velocity and load thrust is given and an improved sliding mode reaching law is designed to establish the discrete-time load thrust observer. Based on Lyapunov theory, the stability of the observer is proved. The observed load thrust is compensated to the controller in the form of feedforward. Finally, a series of comparative experiments were carried out. The experimental results show that compared with the PI control, the maximum speed fluctuation of this method is reduced by about 18.1% when the load changes between no-load and rated load. This means that the method in this article can effectively improve the antidisturbance ability of the system.
|
1,610
|
Please write an abstract with title: Deep Belief Network-based Fake Task Mitigation for Mobile Crowdsensing under Data Scarcity, and key words: Task analysis, Sensors, Machine learning, Principal component analysis, Batteries, Data models, Training. Abstract: Mobile crowdsensing (MCS) is a ubiquitous sensing paradigm that emerged in the form of”sensed data as a service” model in the Internet of Things Era. Distributed nature of MCS results in vulnerabilities at the MCS platforms as well as participating devices that provide sensory data services. Submission of fake tasks with the aim of clogging sensing server resources and draining participating device batteries is a crucial threat that has not been investigated well. In this paper, we provide a detailed analysis by modeling a deep belief network (DBN) when the available sensory data is scarce for analysis. With oversampling to cope with the class imbalance challenge, a Principal Component Analysis (PCA) module is implemented prior to the DBN and weights of various features of sensing tasks are analyzed under varying inputs. The experimental results show that the presented DBN-driven fake task mitigation detection of fake sensing tasks can ensure up to 0.92 accuracy, 0.943 precision and up to 0.928 F1 score outperforming prior work on MCS data with deep learning networks.
|
1,611
|
Please write an abstract with title: Area Coverage Aware Approach for Data Communication in UAVs Networks, and key words: Unmanned Aerial Vehicles, communication, UAVs network, FANET, k-means, clustering, mobility. Abstract: The high stability of Unmanned Aerial Vehicles (UAVs) and their agility in harsh areas have enabled their effectiveness in several applications in today's research and industrial communities. The proper coordination and collaboration of multiple UAVs wirelessly linked with a central entity as a Flying Ad hoc NETwork (FANET) is vital to organizing data and improving a wide range of tasks. Meanwhile, maintaining connectivity and coverage requirements remain the most critical issues that should be addressed for data communication and mobility patterns in the area of interest. However, there is a conflict between network connectivity and area coverage during network design and maintenance. The aim of this work is to investigate data communication over UAVs networks while optimizing area coverage and exploration. To this end, we propose a new Cluster-based Random Pheromone Zone (C-RDPZ) for data communication and mobility control in UAVs networks. The simulation of the proposed protocol carried out using Network Simulator 3 (NS3) has yielded convincing results in terms of energy consumption, area coverage, and data communication.
|
1,612
|
Please write an abstract with title: Iterative multiuser detection based on Monte Carlo probabilistic data association, and key words: Multiuser detection, Monte Carlo methods, Multiaccess communication, Personal digital assistants, Iterative decoding, Detectors, Multiple access interference, Communication channels, Signal processing, Iterative algorithms. Abstract: Multiple-access interference (MAI) has been considered as a major performance-limiting factor in the next-generation CDMA systems. Multiuser detection (MUD) methods have been proposed to mitigate the MAI from the co-channel users by incorporating the cross-correlation properties between users. Recently, two classes of emerging techniques, probabilistic data association (PDA) and Markov Chain Monte Carlo (MCMC) methods, have been applied to the multiuser detection. In this paper, we present a new method, named Monte Carlo PDA (MC-PDA), that incorporates the concepts of both to give a more reliable inference of the CDMA symbols by appropriately modelling and updating the MAI. The methodology is general and can be applied to other communication channels
|
1,613
|
Please write an abstract with title: The application of dynamic programming to optimal inventory control, and key words: Dynamic programming, Inventory control, Optimal control, Cost function, Differential equations, Machinery, Operations research, Councils, Medical control systems, Control systems. Abstract: This paper concerns a class of deterministic impulse control problems, arising in inventory control. A notable feature of the problem formulation is the presence of an end-point constraint. In consequence, the value function may be discontinuous. Viability theory provides a characterization of the value function as the unique lower semicontinuous solution to a Bensoussan-Lions type quasi-variational inequality (QVI), suitably interpreted for nondifferentiable, extended valued functions. Yet there are few examples in the literature of the use of this analytical machinery. This paper provides such an example. The example, which concerns a problem for which the value function is neither everywhere finite valued nor continuously differentiable on the interior of its effective domain, illustrates what is involved in calculating subdifferentials and checking satisfaction of QVI (in a generalized sense). This paper also provides a summary of the underlying theory, and gathers in the Appendix proofs of key results.
|
1,614
|
Please write an abstract with title: 5G NR Release 16 and Millimeter Wave Integrated Access and Backhaul, and key words: Phased arrays, Parity check codes, Gain, 5G mobile communication, Ultra reliable low latency communication, Vehicle-to-everything, Long Term Evolution. Abstract: The early deployments of the fifth generation (5G) New Radio (NR) cellular networks based on Release 15 of the Third Generation Partnership Project (3GPP) specification are taking place now. While the focus of Release 15 was enhanced mobile broadband (eMBB) services, Release 16 features are concurrently being developed to add or enhance services based on Release 15. Notable Release 16 features include ultra-reliable and low-latency connection (URLLC), NR vehicle-to-X (V2X), NR on unlicensed bands (NR-U), and integrated access and backhaul (IAB). In particular, IAB enables backhaul connectivity, without expensive fiber deployment, for fast, cost-effective, and dense millimeter-wave (mmWave) deployments. This paper examines Release 16 features and considers a link simulation of a 28 GHz NR IAB node using an 8x8 phased-array antenna. The phased-array radiation pattern is extracted through electromagnetic (EM) simulation and combined with NR link simulation. Bit-error rate (BER) is used to evaluate the link performance operating as an IAB node subjected to an interferer.
|
1,615
|
Please write an abstract with title: Characterisation and comparison of a cMUT versus a piezoelectric transducer for air applications, and key words: Piezoelectric transducers, Ultrasonic transducers, Diffraction, Tomography, Biomembranes, Linearity, Silicon, Polymers, Resonance, Resonant frequency. Abstract: The main objectives with this investigation are firstly to compare important parameters of a capacitive micromachined ultrasonic transducer (cMUT) for air applications with a corresponding piezoelectric ultrasonic transducer. Secondly, to characterise the cMUT's radiation field using light diffraction tomography. The cMUTs consist of a silicon backplate with small pyramid-shaped cavities and a metallised polymeric membrane. The piezoelectric transducers are nonfocused with a resonance frequency of 450 kHz. Time waveforms, FFT-spectra, S/N-ratio, linearity plots and distance working range are presented for different kinds of combinations of cavity size, membrane thickness and bias voltage. Pressure maps from light diffraction tomography measurements are also presented. The principal conclusions are that the cMUTs have comparable linearity and sensitivity but exhibit superior bandwidth to the compared piezoelectric transducers.
|
1,616
|
Please write an abstract with title: The Impact of Auditor Size and Abnormal Audit Fee upon Audit Quality: Large Sample Empirical Research Based on Regression Model, and key words: Economics, Companies, Data models, Proposals. Abstract: In the course of our country's economic development, the financial frauds and auditing failures remain rampant, which has aroused public attention and seriously deteriorated the healthy development of the capital market. The purpose of this research is to determine the factors affecting audit quality, and provide feasible and practical proposals to improve audit quality and promote the healthy development of the capital market. Aiming to Figure out the influence mechanism of abnormal audit fee on the audit quality, this empirical study investigates the influence of abnormal audit fee on the audit quality and the adjustment function of the audit firm size based on panel data from the Chinese A-Share listed companies from 2014 to 2018. We find abnormal audit fee is negatively and significantly associated with audit quality. Our results suggest that abnormal audit fee does harm to the audit quality, but auditor size plays a moderating role in their relationship, that is, large-size accounting firms can reduce the harm. Taking positive abnormal audit fee and negative abnormal audit fee into account, we find that both of them result in poor audit quality, while large-size accounting firms can reduce the effect as well.
|
1,617
|
Please write an abstract with title: Improvement of the Mathematical Model of Low-Frequency Electromagnetic Processes of Power Transformer using MATLAB/Simulink, and key words: Analytical models, Visualization, Computational modeling, Windings, Mathematical models, Power transformers, Electromagnetics. Abstract: The mathematical model of analysis of low-frequency electromagnetic transient in three-phase two-winding transformers in the MATLAB/Simulink modeling environment has been improved. The model adequately takes into account the electromagnetic connections between the windings and the magnetic circuit of the transformer, their electromagnetic parameters, the nonlinearity of the Weber-ampere characteristics of the magnetic circuit elements and power loss from hysteresis and eddy currents.
|
1,618
|
Please write an abstract with title: Improving Classification Results in Network Data Analysis using Interpretability Methods, and key words: Deep learning, Data analysis, Network intrusion detection, Production, Network security, Data models, Computer networks. Abstract: Developing network intrusion detection and prevention systems usually leverage a rule-based approach, which is derived from rules defined by network security experts who can utilize logic from both low and high network layers. However, in recent times, machine learning methods have also achieved promising results in developing Network Intrusion Detection Systems, and their popularity is steadily rising. Unfortunately, the usage of these machine learning methods in real-life problems has regularly proved that no good out-of-the-box solution exists for production or deployment. Also, due to the increasing volume and complexity of processed data that machine learning methods are faced with over time, improvements and adaptions are frequently required. As the problem at hand becomes more convoluted, so does the the nature of the applied solution. This complexity is further compounded by the fact that certain machine and deep learning methods intrinsically do not offer a way of understanding how they make decisions, effectively behaving like black boxes. All of this significantly lowers the understandability of implemented solutions in production environments that are already quite complex, which justifies the need of interpretability methods. While interpretability methods are commonly designed to be used by humans, in this paper we propose a way of improving a model's classification performance by applying data mining methods on explanation data generated by interpretability methods. The paper's main contribution is improving on a previously built network intrusion detection system through proposing an automated process of integrating explanations into original data with the purpose of improving the interpretability and score of the used machine learning model
|
1,619
|
Please write an abstract with title: A new approach based on a combination of integral equation and asymptotic techniques for solving electromagnetic scattering problems, and key words: Integral equations, Electromagnetic scattering, Fourier transforms, Current distribution, Frequency, Electromagnetic diffraction, Physical theory of diffraction, Boundary conditions, Current density, Strips. Abstract: We introduce a new approach for combining the integral equation and high frequency asymptotic techniques, e.g., the geometrical theory of diffraction. The method takes advantage of the fact that the Fourier transform of the unknown surface current distribution is proportional to the scattered far-field. A number of asymptotic methods are currently available that provide good approximation to this farfield in a convenient analytic form which is useful for deriving an initial estimate of the Fourier transform of the current distribution. An iterative scheme is developed for systematically improving the initial form of the high frequency asymptotic solution by manipulating the integral equation in the Fourier transform domain. A salient feature of the method is that it provides a convenient validity check of the solution for the surface current distribution by verifying that the scattered field it radiates indeed satisfies the boundary conditions at the surface of the scatterer. Another important feature of the method is that it yields both the induced surface current density and the far-field. Diffraction by a strip (two-dimensional problem) and diffraction by a thin plate (three-dimensional problem) are presented as illustrative examples that demonstrate the usefulness of the approach for handling a variety of electromagnetic scattering problems in the resonance region and above.
|
1,620
|
Please write an abstract with title: Full-Custom Design of Multiplicative Inverse for AES S-BOX using 4-Transistor XOR Gate, and key words: Software algorithms, Voltage, Logic gates, Software, Encryption, Power dissipation, Transistors. Abstract: The Multiplicative Inverse is the most intricate step involved in computation of Substitution-Box values for Private Key Encryption algorithms. It is the shared common step for encryption as well as decryption. Computing the Multiplicative Inverse of a value in Galois Field GF (p) for small numbers is an easy task which is straight away obtained from its computation tables. However, it is not convenient for higher values of p. Recent implementation of Multiplicative Inverse focuses on composite field arithmetic based approaches which uses lower order fields in its implementation. This paper presents Multiplicative Inverse design in composite field arithmetic using 4-transistor XOR gate to obtain a compact Substitution-Box module in 90 nm technology. The design requires a total of 442 transistors with average power dissipation of 3.75 watts at 0.6 supply voltage. The design shows a significant drop in transistor count by 43 % compared to previously published work.
|
1,621
|
Please write an abstract with title: Multi-objective optimization scheme for dynamic multicast groups, and key words: Telecommunication traffic, Routing, Load management, Computer science, Delay, Proposals, Multiprotocol label switching, Traffic control, Resource management, Bandwidth. Abstract: In this paper, we propose a multi-objective traffic engineering scheme using different distribution trees to dynamic multicast groups (in which egress nodes can change during the connection's lifetime). If a multicast tree is recomputed from scratch, it may consume a considerable amount of CPU time and all communication using the multicast tree will be temporarily interrupted. To alleviate these drawbacks we propose a dynamic optimization model that makes use of a previously computed multicast tree (static model) in order to add new egress nodes. Using these two models, our aim is to combine into a single aggregated metric, the following weighting objectives: maximum link utilization, hop count, total bandwidth consumption and total end-to-end delay. Moreover, our proposal solves the traffic split ratio for multiple trees. We compare the dynamic and static multicast routing models using SNOPT solver. The proposed approach can be applied in MPLS networks by allowing explicit routes to be established in multicast events.
|
1,622
|
Please write an abstract with title: Early Experience in Forecasting Blood Glucose Levels Using a Delayed and Auto-Regressive Jump Neural Network, and key words: Sugar, Blood, Diabetes, Insulin, Biological neural networks, Training. Abstract: Type 1 diabetes mellitus is a widespread chronic disease that, if not properly treated, can lead to short- and longterm complications. In recent years, continuous glucose monitoring has become very popular among patients since it allows to keep track of glucose levels for 24 hours. Nevertheless, hypo- and hyperglycemic events are still widely reported, motivating the development of methods that forecast blood glucose levels at given prediction horizons, which usually range from 15 to 30 minutes. However their application, regardless of the approaches adopted, is limited in practice by the fact that they usually need a long training time and other information gathered from the patients. To overcome these issues in this work we present a new neural network that extends the jump network model by introducing time delays from the input to the hidden layer and auto-regressive feedback from the output to the hidden layer. The proposed neural network shows promising results at 15, 20 and 30-minute prediction horizons, which are comparable to or slightly better than the results reported in the literature, although the training period used in this work is considerably shorter.
|
1,623
|
Please write an abstract with title: Noise Suppression of Artificial Intelligence Filter for Radio Frequency Interference, and key words: Low-pass filters, Biological neural networks, Noise reduction, Computer vision, Band-pass filters, Switches, Frequency measurement. Abstract: This paper discusses design of area effective radio frequency interference noise reduction for low-pass filter using as switched-capacitor (SC) architecture. For noise suppression, noise via the power/ground lines is a serious issue. One of the noise reduction technique is a fully differential SC insertion, since the time constant of SC filter affects the balance of the supply noise and the ground noise, the noise reduction becomes maximum at a certain time constant. A fully differential SC is adopted via the bilinear transform of the corresponding analogue RLC passive prototype. The proposed SC with artificial intelligence method to reach the largest possible input dynamic range and optimized layout, the method of dynamic range scaling and minimum capacitor scaling is used.
|
1,624
|
Please write an abstract with title: SVBR-Net: A Non-Blind Spatially Varying Defocus Blur Removal Network, and key words: Training, Degradation, Deep learning, Protocols, Convolution, Neural networks, Estimation. Abstract: Defocus blur is a physical consequence of the optical sensors used in most cameras. Although it can be used as a photographic style, it is commonly viewed as an image degradation modeled as the convolution of a sharp image with a spatially-varying blur kernel. Motivated by the advance of blur estimation methods in the past years, we propose a non-blind approach for image deblurring that can deal with spatially-varying kernels. We introduce two encoder-decoder sub-networks that are fed with the blurry image and the estimated blur map, respectively, and produce as output the deblurred (deconvolved) image. Each sub-network presents several skip connections that allow data propagation from layers spread apart, and also inter-subnetwork skip connections that ease the communication between the modules. The network is trained with synthetically blur kernels that are augmented to emulate blur maps produced by existing blur estimation methods, and our experimental results show that our method works well when combined with a variety of blur estimation methods. Our code will be available at https: //github.com/alikaraali/SVBR_Net_icip.
|
1,625
|
Please write an abstract with title: Improved hot-electron reliability in strained-Si nMOS, and key words: MOSFETs, Semiconductor device reliability, Charge carrier mobility, Charge carrier processes, Germanium materials/devices. Abstract: Strained-Si/relaxed-Si/sub 1-x/Ge/sub x/ structures provide a viable means of improving CMOS performance. For nMOS devices, the tensile strain in pseudomorphic Si on relaxed-Si/sub 1-x/Ge/sub x/ splits the six-fold degeneracy of the conduction band minimum, rendering increased electron mobility due to a lower in-plane effective mass and reduced intervalley scattering. In this paper, in addition to confirming enhanced performance for biaxial-strained-Si nMOS, we present hot-electron degradation characteristics for the first time, showing improvement over bulk Si.
|
1,626
|
Please write an abstract with title: Geolocation in mines with an impulse response fingerprinting technique and neural networks, and key words: Fingerprint recognition, Neural networks, Artificial neural networks, Rough surfaces, Surface roughness, Wideband, Mining industry, Indoor environments, Reflection, Diffraction. Abstract: The location of people, mobile terminals and equipment is highly desirable for operational enhancements in the mining industry. In an indoor environment such as a mine, the multipath caused by reflection, diffraction and diffusion on the rough sidewall surfaces, and the non-line of sight (NLOS) due to the blockage of the shortest direct path between transmitter and receiver are the main sources of range measurement errors. Unreliable measurements of location metrics such as received signal strengths (RSS), angles of arrival (AOA) and times of arrival (TOA) or time differences of arrival (TDOA), result in the deterioration of the positioning performance. Hence, alternatives to the traditional parametric geolocation techniques have to be considered. In this paper, we present a novel method for mobile station location using wideband channel measurement results applied to an artificial neural network (ANN). The proposed system, the wide band neural network-locate (WBNN-locate), learns off-line the location 'signatures' from the extracted location-dependent features of the measured channel impulse responses for line of sight (LOS) and non-line of sight (NLOS) situations. It then matches on-line the observation received from a mobile station against the learned set of 'signatures' to accurately locate its position. The location accuracy of the proposed system, applied in an underground mine, has been found to be 2 meters for 90% and 80% of trained and untrained data, respectively. Moreover, the proposed system may also be applicable to any other indoor situation and particularly in confined environments with characteristics similar to those of a mine (e.g. rough sidewalls surface).
|
1,627
|
Please write an abstract with title: Digital Video Manipulation Detection Technique Based on Compression Algorithms, and key words: Correlation, Image coding, Cameras, Technological innovation, Support vector machines, Forensics, Transform coding. Abstract: Digital images and videos play a very important role in everyday life. Nowadays, people have access the affordable mobile devices equipped with advanced integrated cameras and powerful image processing applications. Technological development facilitates not only the generation of multimedia content, but also the intentional modification of it, either with recreational or malicious purposes. This is where forensic techniques to detect manipulation of images and videos become essential. This paper proposes a forensic technique by analysing compression algorithms used by the H.264 coding. The presence of recompression uses information of macroblocks, a characteristic of the H.264-MPEG4 standard, and motion vectors. A Vector Support Machine is used to create the model that allows to accurately detect if a video has been recompressed.
|
1,628
|
Please write an abstract with title: Edge MLOps: An Automation Framework for AIoT Applications, and key words: Training, Cloud computing, Automation, Atmospheric modeling, Computational modeling, Pipelines, Collaborative work. Abstract: Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations and decision making. Edge computing is emerging to enable AIoT applications. In this paper, we develop an Edge MLOps framework for automating Machine Learning at the edge, enabling continuous model training, deployment, delivery and monitoring. To achieve this, we synergize cloud and edge environments. We experimentally validate our framework on a forecasting air quality situation. During validation, the framework showed stability and automatically retrained, integrated, and deployed models for specific environments when their performance deteriorated under a certain threshold.
|
1,629
|
Please write an abstract with title: Sequential parameter estimation using pseudoinverse, and key words: Parameter estimation, Covariance matrix, Filters, Observability, Statistics, NASA, Matrices. Abstract: This correspondence presents the method for solution of the parameter estimation problem in an entirely sequential fashion. In this procedure each measurement is processed as it is received, without regard to whether it and the prior measurements have established a minimal observable data set, or without the assumption a priori of a covariance matrix in the manner of the Kalman filter. During the period prior to the establishment of the minimal data set the estimate maintains the character of the pseudo-inverse constraint, that of minimum norm. In addition at each measurement, a parameter is available for deciding whether this measurement has increased the observability of the system.
|
1,630
|
Please write an abstract with title: An Undersampling Communication System Based on Compressive Sensing and In-Fiber Grating, and key words: Optical fiber communication, Optical fiber polarization, Diffraction, Communication systems, Optical polarization, Fiber gratings, Data communication. Abstract: An undersampling free-space optical (FSO) communication system based on compressive sensing (CS) and in-fiber grating is proposed. Our proposal drastically mitigates the data scale unfavorable issue and reduces the great amount of required data. Also, our proposal employs low-bandwidth and low-cost photodetectors (PDs) and analog-to-digital converters (ADCs) and decreases the cost of data detection. Besides, the data transmitted in the free space is encrypted, which enhances the security of the system. The in-fiber grating, which has the advantage of highly efficient thanks to its inherent compatibility with optical fiber links, plays the roles of light emitter, in-fiber polarizer, and light diffraction device, simultaneously. A sinusoidal radio frequency (RF) signal with a frequency of 1 GHz is utilized for a 2.4 m data transmission. And each PD with a bandwidth of 300 MHz is employed for detecting the transmitted signal on each channel. The proposal obtains data compression ratios of 25%, 15%, and 5% both in the temporal domain and frequency domain. Besides, a two-tone signal and a random RF signal are applied in the proposed FSO transmission for data transmission. Our proposal not only has the merits of secure, compact, stable, and highly efficient, but also has great potential in extremely secure situations, such as secured indoor and under water data communication.
|
1,631
|
Please write an abstract with title: Towards Personalized Deformable and Mix-supervised Model for Robust MR-US Registration, and key words: MR-US Registration, Deep Learning, Neural Network. Abstract: Registration and fusion of magnetic resonance (MR) and ultrasound (US) images remain challenging tasks due to the great intensity variation between two modalities and the lack of ground truth spatial correspondence. In this paper, we proposed a mix-supervised registration network, driven by main vessel segmentation labels and modality independent neighborhood descriptor (MIND) similarity metric. The accurate alignment of the main vessel labels can prompt the registration network focus on the region of interest and MIND similarity metric constraints global deformation. Vessel label and similarity measures can promote each other and produce satisfactory registration results. This framework connects a Rigid-Net and a Bspline-Net to generate the transformation parameters of rigid and deformable registration in one shot. The well-trained network is able to register dynamic 3D US images to the preoperative MR image in real time, correcting the motion caused by a patient's breathing. Experimental results show that the proposed method is effective for MR-US registration.
|
1,632
|
Please write an abstract with title: A new extraction technique for the series resistances of semiconductor devices based on the intrinsic properties of bias-dependent y-parameters [bipolar transistor examples], and key words: Semiconductor devices, Electrical resistance measurement, Testing, Data mining, Bipolar transistors, Paper technology, Analytical models, Size measurement, Frequency, Semiconductor device noise. Abstract: This paper presents an approach for the extraction of the series parasitics of semiconductor devices. The approach is based on the inherently different bias dependent behavior of y-parameters for a device with series parasitics compared to a device without series parasitics. The principles of this new method are verified analytically as well in simulations using the ADS Gummel-Poon model. In conclusion we have applied the proposed extraction method on measured data of DIMES-03 bipolar transistors of different sizes.
|
1,633
|
Please write an abstract with title: Inductive conductivity probe calibration, and key words: Equations, Probes, Sea measurements, Ocean temperature, Conductivity, Temperature sensors, Calibration, Acoustic measurements, Surface fitting, Temperature measurement. Abstract: The Naval Torpedo Station collaborated with the University of Washington, Department of Oceanography, to develop a calibration technique for inductive conductivity probes. The basically simple technique uses an empirical relationship between salinity, temperature and conductivity developed at the University. Development of the salinity-conductivity-temperature relationship is presented. Confinement of the external electrical field in a finite tank affects calibration as do discontinuities in the medium, such as a protective cage. Accuracy of calibration is assessed.
|
1,634
|
Please write an abstract with title: Audio-Mood Classification Using Acoustic-Textual Feature Fusion, and key words: Performance evaluation, Mood, Merging, Semantics, Music, Feature extraction. Abstract: Listeners browse songs based on artist or genre, but a significant amount of queries are based on emotions like happy, sad, calm etc. and therefore, automatic music mood classification is gaining importance. People search for songs based on the emotions they are feeling or the emotion they hope to feel. Audio-based techniques can achieve satisfying results, but part of the semantic information of songs resides exclusively in the lyrics. In this paper, we present a study on the fusion approach of music mood classification. As both audio and lyrical information is complimentary, creating a hybrid model to classify music based on mood provides enhanced accuracy. Where a single song might fall under two different categories based on audio or lyrical information, a hybrid model helps us achieve more accurate results by merging both the information. In this work, we extracted features using librosa from audio, used TF-IDF for text, and experimented with the Bi-LSTM network. The performance evaluation is done on corpus consists of 776 songs. The multimodal approach achieved average precision, recall and F1-score of 0.66, 0.65 and 0.65 respectively.
|
1,635
|
Please write an abstract with title: Research and Application of Generator Protection Based on Fiber Optical Current Transformer, and key words: Generators, Circuit faults, Current transformers, Optical fibers, Current measurement, Stator windings. Abstract: This paper introduces the basic principle of fibre optical current transformer (FOCT), and explains the advantages of FOCT compared with electromagnetic current transformer (CT). FOCT can be wound around the primary conductor in any shape, has high harmonic accuracy and doesn't suffer from saturation, thus a good solution for generator relay protection. As a common electrical fault within large generators, the inter-turn short circuit in field windings (ISCFW) is likely to cause earth faults between the field winding and the rotor body and magnetization of the main shaft without timely intervention. Steady-state unbalanced currents of even orders and fractional orders related with pole pairs inside phase windings are required to monitor the ISCFW. The inter-turn fault of stator windings may rapidly develop into a phase to phase fault, which seriously threatens the safety of the unit. Split-phase transverse differential current reflects the steady-state current imbalance inside the stator winding. Nevertheless, for most steam turbine generators and some hydro turbine generators, it is unable to obtain phase-segregated transverse differential current due to impossibility of installing branch current transformer in the narrow space inside the generator. However, FOCT which uses fibre optic cable as a sensor is installable within limited space to measure the current of each group of winding branches of each phase. FOCT furthers phase-segregated transverse differential protection, partial differential protection and online monitoring of the ISCFW, thus optimizing the generators protection scheme. In addition, operating speed and sensitivity of generator differential protection are improved based on the reliable measurement from FOCT. The proposed scheme is verified by an application on a 300MW generator at a pump-storage power plant. This is the first attempt of applying FOCT to the relay protection of generator set, which provides reference for further development and application of FOCT in power plant.
|
1,636
|
Please write an abstract with title: Performance Analysis of PID Affected Crystalline Silicon PV Module under Partial Shading Condition, and key words: Photovoltaic systems, Degradation, Conferences, Silicon, Performance analysis, Stress. Abstract: Potential-induced degradation (PID) significantly affects the performance of a photovoltaic (PV) module. In this paper, modeling and simulation of PID affected module are performed to unveil the insights of electrical losses and stresses resulting under partial shading conditions. PID is modeled using two diode model, taking into account the severity and nature (ohmic and non-ohmic) of PID shunting. Frequently observed shading patterns in a field are considered in the simulation. Results show that the predominantly ohmic nature of PID improves the module output under partial shading conditions, although it also leads to extreme reverse stresses across the shaded cell. In the case of non-ohmic PID, reverse stresses across the shaded cell are not much severe, leading to degradation in module power output. Perpendicular shading pattern to the cell string results in severe power loss, and with an increase in ohmic PID severity, reverse stresses across the shaded cells increase significantly. Failure of bypass diode leads to excess power loss and reverse stresses at shading percentage lower than critical shading.
|
1,637
|
Please write an abstract with title: Design and Development of Information Sharing and Analysis Center (ISAC) as an Information Sharing Platform, and key words: Authentication, Information sharing, Virtual machining, Real-time systems, Malware, Stakeholders, Servers. Abstract: Cyber attacks are the main focus highlighted in all countries globally, both private and public sectors. It is undeniable that every private and public sector has a significant role in the digital world and cybersecurity. It is a reason for every country to improve and develop everything in cyber technology behind defense or attack. One of the solutions offered is to build a platform that can be used to share information to improve a coordinated and structured cybersecurity defense strategy. Data information, a list of attacks and threats can help stakeholders in each sector identify threats, attacks, and incidents in the cyber world. Therefore, this research will develop a web-based Information Sharing and Analysis Center (ISAC) platform to collect information and view a list of attacks and threats in the cyber world. The list of attacks and threats will be obtained through the Malware Information Sharing Platform (MISP). A two-factor authentication method will be implemented on the login form in the development of the ISAC platform. Two-factor authentication is a method used to secure user data from attackers. The research method used in building this platform is Design Research Methodology (DRM) with a prototyping development method. The results of this study obtained an ISAC portal that can be used to share information and display a list of threats and attacks received from the MISP platform.
|
1,638
|
Please write an abstract with title: Timed workflow nets, and key words: Petri nets, Timing, Computer science, Councils, Workflow management software, Process control, Control systems, Humans, Real time systems, Cooperative systems. Abstract: In this paper, timed workflow nets are introduced, and a characterization of the soundness property for them is provided. This characterization is based on boundedness and liveness as for classical workflow nets. It is shown that the properties of boundedness and liveness for timed Petri nets can be reduced in linear time to the same properties for untimed Petri nets. Therefore, the soundness property for timed workflow nets can be checked as efficiently as for workflow nets.
|
1,639
|
Please write an abstract with title: Introducing a survey methodology for assessing LoRaWAN coverage in Smart Campus scenarios, and key words: Wireless communication, Performance evaluation, Energy consumption, Cloud computing, Logic gates, Complexity theory, Mobile nodes. Abstract: The LoRa is a Low Power Wide Area Network (LPWAN) technology. It has been proposed as a viable wireless connection method for the implementation of the Internet of Things (IoT), thanks to its wide coverage, low complexity and low energy consumption. Several studies ave been carried out about real coverage performance. In this article, a new test methodology for the experimental evaluation of LoRaWAN coverage within a smart campus is presented. The new approach consists in the definition of devices, method and procedures. The architecture of the mobile node is outlined. The survey procedure is based on a mapping phase, necessary to highlight the LoRaWAN coverage in the test area. Finally, a use case is described in the article: it is not intended for evaluating a specific implementation, but for assessing the suitability of the proposed methodology. The use case results demonstrate the effectiveness of the survey methodology in a real smart campus.
|
1,640
|
Please write an abstract with title: A 10-mW 3.6-Gbps I/O transmitter, and key words: Transmitters, Multiplexing, Power dissipation, Filters, Impedance matching, Signal design, Low voltage, Clocks, Energy consumption, Power supplies. Abstract: This paper describes a low-power self-terminated transmitter. A novel architecture is proposed to perform impedance matching and channel equalization with low power consumption. The test chip is fabricated using 0.18-/spl mu/m digital CMOS process with 1.8-V supply. The transmitter operates at 3.6 Gbps and consumes 9.66 mW. The total transmitter area is 0.072 mm/sup 2/.
|
1,641
|
Please write an abstract with title: Thrombolysis in the eyes of the continuous wavelet transform, and key words: Eyes, Continuous wavelet transforms, Frequency, Heart rate variability, Heart rate, Wavelet transforms, Myocardium, Equations, Ischemic pain, Spectral analysis. Abstract: Acute myocardial infarction (MI) is known to elicit autonomic responses, depending on its location: inferior-wall MI (Inf-MI) promotes vagal activation, and anterior-wall MI (Ant-MI) promotes sympathetic activation. Reperfusion is thus expected to induce an opposite shift in autonomic balance. We studied the patterns of heart rate variability (HRV), which reflect the autonomic response to reperfusion by applying a continuous wavelet transform (CWT). ECG traces, 3 h long, were obtained from 9 Ant-MI and 8 Inf-MI patients during acute MI. Marked alterations in HRV occurred in all reperfusion events. A shift in balance towards sympathetic predominance was found in all Inf-MI patients, and in 3 Ant-MI patients, while a shift towards vagal predominance was found in 6 Ant-MI patients (p<0.001). The CWT thus enables to study cardiac control during non-steady-state conditions, as exhibited during thrombolysis.
|
1,642
|
Please write an abstract with title: Steady-State and Transient Performance of Ion-Sensitive Electrodes Suitable for Wearable and Implantable Electro-Chemical Sensing, and key words: Ions, Electrodes, Mathematical model, Biomembranes, Steady-state, Temperature sensors, Temperature measurement. Abstract: Traditional Potentiometric Ion-selective Electrodes (ISE) are widely used in industrial and clinical settings. The simplicity and small footprint of ISE have encouraged their recent adoption as wearable/implantable sensors for personalized healthcare and precision agriculture, creating a new set of unique challenges absent in traditional ISE. In this paper, we develop a fundamental physics-based model to describe both steady-state and transient responses of ISE relevant for wearable/implantable sensors. The model is encapsulated in a “generalized Nernst formula” that explicitly accounts for the analyte density, time-dynamics of signal transduction, ion-selective membrane thickness, and other sensor parameters. The formula is validated numerically by self-consistent modeling of multispecies ion-transport and experimentally by interpreting the time dynamics and thickness dependence of thin-film solid-contact and graphene-based ISE sensors for measuring soil nitrate concentration. These fundamental results will support the accelerated development of ISE for wearable/implantable applications.
|
1,643
|
Please write an abstract with title: Coherent optical vector modulation for fiber radio using electrooptic microchip lasers, and key words: Optical modulation, Electrooptic modulators, Fiber lasers, Lasers and electrooptics, Microchip lasers, Optical fiber communication, Masers, Millimeter wave communication, Millimeter wave technology, Phase modulation. Abstract: Future communication systems will require high data rates and flexible modulation. Direct optical phase modulation of two microchip lasers by information-bearing signals allows for high-rate delivery via fiber to a basestation. At the basestation, the coherent optical signals are combined with a reference in a photodetector to produce a microwave/millimeter-wave carrier with arbitrary M-ary quadrature amplitude modulation, which can then be transmitted over a wireless channel. Rapid tuning of the microwave/millimeter-wave carrier, the modulation scheme, and the data rate is achievable through this method with no fixed oscillators at the basestation, thus providing for flexible architectures. Results show a high-quality carrier and, for 4- and 16-QAM, with data rates to 200 Mb/s. Extensions to higher data rates are discussed.
|
1,644
|
Please write an abstract with title: Machine Learning Intrusion Detection in Big Data Era: A Multi-Objective Approach for Longer Model Lifespans, and key words: Feature extraction, Intrusion detection, Data models, Big Data, Telecommunication traffic, IP networks, Real-time systems. Abstract: Despite highly accurate intrusion detection schemes based on machine learning (ML) reported in the literature, changes in network traffic behavior quickly yield low accuracy rates. An intrusion detection model update is not easily feasible due to the enormous amount of network traffic to be processed in near real-time for high-speed networks, in particular, under big data settings. In this paper, we propose a new scalable long-lasting intrusion detection architecture for the processing of network content and the building of a reliable ML-based intrusion detection model. Experiments performed through the analysis of five years of network traffic, about 20 TB of data, have shown that our approach extends the lifespan of our model by up to six weeks. That occurs because the average accuracy rate of our proposal lasted eight weeks after the training phase, and traditional ones reached only two weeks after the model building. Additionally, our proposal achieves up to 10 Gbps of detection throughput in a 20-core big data processing cluster.
|
1,645
|
Please write an abstract with title: Model Predictive Control of Four-Switch Buck-Boost Converter for Pulse Power Loads, and key words: Power supplies, Simulation, Capacitors, Power system dynamics, Predictive models, Cost function, Prediction algorithms. Abstract: In the DC microgrid power system, because of the limited total inertia of the system, the pulsed power load is particularly problematic. To decrease the unfriendly effect of pulsed power loads, a storage capacitor may be generally associated with the output terminal of the power supply. However, because of the strict voltage drop limit on the DC bus, the storage capacitor is greatly vast when the pulsed power load will be high. In this paper, a four-switch buck-boost (FSBB) built active capacitor converter (ACC) will be received set up of the storage capacitor, toward deliberately expanding its voltage ripple, then the capacity of the capacitor is extraordinarily diminished. To improve the dynamic response of the ACC, a finite control set model predictive control (FCS-MPC) scheme is utilized. A multi-constrained cost function is proposed to reduce the voltage drop on the DC bus. The predictive model of the converter and model predictive control algorithm is elaborated, followed by which Matlab/Simulink is conducted to verify the proposed model predictive control.
|
1,646
|
Please write an abstract with title: Near-Field Measurement Technique for Spacecraft Installed Low Frequency Antennas, and key words: Antenna measurements, Space vehicles, Dipole antennas, Electric variables measurement, Measurement techniques, Time measurement, Frequency measurement. Abstract: The ESA HERA-JUVENTAS mission relies on 50–100 MHz dipole antennas mounted on a CubeSat. The mission requires an accurate verification of the 3D co-polar and cross-polar directivity, gain, and matching. The performance verification of low gain antennas installed on space platforms at frequencies below 400MHz is a challenging task. The use of spherical nearfield measurement technique is the most suitable and accurate approach for low gain antennas. However, a well-designed conventional anechoic chamber, for indoor testing, equipped with suitable absorbers at the desired test frequencies would be large and thus expensive. In this paper, the so-called synthetic probe array technique to suitably shape the probe pattern for minimum illumination of the chamber walls will be presented. Its applicability to spherical near field measurements in the existing HERTZ testing facility at ESA/ESTEC will be discussed. A comprehensive theoretical study has been performed using fullwave simulation of the chamber and the spacecraft. Moreover, scaled measurements considering a 10:1 scaled model of the final scenario are currently under investigation to better verify the performance of the proposed measurement technique. Preliminary results obtained from the simulation analysis and the scaled tests are reported in this paper.
|
1,647
|
Please write an abstract with title: Voting shrinkage algorithm for Covariance Matrix Estimation and its application to portfolio selection, and key words: Portfolios, Covariance matrices, Estimation, Urban areas, Optimization, Stock markets, Reliability. Abstract: Reducing errors of covariance matrix estimation plays a very important role in many optimization problems, e.g., portfolio optimization. In this paper we propose a data-driven approach which basically combines the original framework of a popular approach named shrinkage estimation and cross-validation technique to adapt the shrinkage intensity with different levels of uncertainty of real data. Particularly, this approach can be applied well to asset management to enhance the quality of portfolio selection which is known as a huge area of research in modern portfolio theory. Experimental results carried out using the prices and volumes data of the Vietnamese stock market show that our proposed method can practically improve the quality and robustness of portfolio selection. Last but not least, we introduce an automatic backtesting system that can help us evaluate the portfolio based on various financial indicators in a real-time manner.
|
1,648
|
Please write an abstract with title: A Non-Local Enhanced Network for Image Restoration, and key words: Feature extraction, Task analysis, Image restoration, Image denoising, Data mining, Image resolution, Transform coding. Abstract: Non-local modules have been widely studied in image restoration (IR) tasks since they can learn long-range dependencies to enhance local features. However, most existing non-local modules still focus on extracting long-range dependencies within a single image or feature map. On the other hand, most IR methods simply employ a single type of non-local module in the network. A combination of various types of non-local modules to enhance local features can be more effective. In this paper, we propose a batch-wise non-local module to explore richer non-local dependencies within images. Furthermore, we combine various non-local extractors (different attention modules) with the proposed batch-wise non-local module as the Enhanced Batch-wise Non-local Attentive module (EBNA). Besides exploring richer non-local information, we build the Non-local and Local Information extracting Block (NLIB), in which we combine the EBNA with DEformable-Convolution Block (DECB) to utilize richer non-local and adaptive local information. Finally, We embed the NLIB within a U-net-like structure and build the Non-local Enhanced Network (NLENet). Extensive experiments on synthetic image denoising, real image denoising, JPEG artifacts removal, and real image super resolution tasks demonstrate that our proposed network achieves state-of-the-art performance on several IR benchmark datasets.
|
1,649
|
Please write an abstract with title: Finite element modeling and experimental analysis of bladder volume body surface monitoring method, and key words: Surface impedance, Solid modeling, Impedance measurement, Wearable computers, Bladder, Finite element analysis, Impedance. Abstract: Bladder dysfunction seriously affects people's quality of life. The accumulation of urine volume in the bladder changes the bladder volume, which changes the impedance of the hypogastrium. This paper constructs a finite element model of the hypogastrium and bladder, and the impedance of the hypogastrium at different volumes of the bladder is obtained by simulation. It also explains the causes of bladder impedance changes based on the current density distribution and designs the impedance acquisition circuit to carry out experimental data measurements on the subjects. The results show that changes in bladder volume affect the amplitude and phase of impedance in the hypogastrium. The model proposed in this paper can provide a theoretical basis for bladder urine volume body surface monitoring.
|
1,650
|
Please write an abstract with title: A Middleware for Managing the Heterogeneity of Data Provining from IoT Devices in Ambient Assisted Living Environments, and key words: Cloud computing, Middleware, Edge computing, Medical services, Servers, Computational modeling, Performance evaluation. Abstract: Internet of Things (IoT) has been growing exponentially in the commercial market in recent years. It is also a fact that people hold one or more computing devices at home. Many of them have been developed to operate through internet connectivity with cloud computing technologies that result in the demand for fast, robust, and secure services. In most cases, the lack of these services makes difficult the transfer of data to fulfill the devices' purposes. Under these conditions, an intermediate layer or middleware is needed to process, filter, and send data through a more efficient alternative. This paper presents the adaptive solution of a middleware architecture as an intermediate layer between smart devices and cloud computing to enhance the management of the heterogeneity of data provining from IoT devices. The proposed middleware provides easy configuration, adaptability, and bearability for different environments. Finally, this solution has been implemented in the healthcare domain, in which IoT solutions are deployed into Ambient Assisted Living (AAL) environments.
|
1,651
|
Please write an abstract with title: Active Deception Jamming Recognition in the Presence of Extended Target, and key words: Jamming, Radar, Feature extraction, Time-frequency analysis, Target recognition, Time-domain analysis, Frequency modulation. Abstract: Accurate sensing of the mainlobe active deception jamming is critical for radar antijamming and extended target detection in a complex electromagnetic environment. This letter, therefore, deals with the problem of multiple active deception jamming recognition in extended target settings. A residual convolutional neural network (CNN) with an attention mechanism-based radar active deception jamming recognition algorithm is proposed, leveraging a hybrid model to capture many rich features through multidomain feature fusion. The proposed method can outperform state-of-the-art methods in terms of recognition accuracy, model size (MS), and convergence speed. Experimental results demonstrate its effectiveness and robustness.
|
1,652
|
Please write an abstract with title: The multi-ring topology-high-performance group communication in peer-to-peer networks, and key words: Network topology, Intelligent networks, Peer to peer computing, Internet, Quality of service, Scalability, Application software, Bandwidth, Data communication, Buildings. Abstract: Emerging peer-to-peer applications require efficient group communication. However, current techniques for group communication are not optimal for peer-to-peer networks, which do not have group communication methods themselves. This paper presents the novel multiring topology, which is designed to meet requirements of high performance group communication in peer-to-peer networks. It improves data communication by applying several concepts: building overlay networks for each topic, a topology consisting of multiple rings, backup links and dual mode links. Experimental results provide evidence for improving performance and scalability of peer group communication.
|
1,653
|
Please write an abstract with title: Sequential and parallel cellular automata-based scheduling algorithms, and key words: Scheduling algorithm, Processor scheduling, Quantum computing, Genetic algorithms, Computer networks, Algorithm design and analysis, Parallel processing, Neural networks, Simulated annealing, Multiprocessing systems. Abstract: We present an approach to designing cellular automata-based multiprocessor scheduling algorithms in which extracting knowledge about the scheduling process occurs. We consider the simplest case when a multiprocessor system is limited to two-processors. To design cellular automata corresponding to a given program graph, we propose a generic definition of program graph neighborhood, transparent to the various kinds, sizes, and shapes of program graphs. The cellular automata-based scheduler works in two modes: learning mode and operation mode. Discovered rules are typically suitable for sequential cellular automata working as a scheduler, while the most interesting and promising feature of cellular automata are their massive parallelism. To overcome difficulties in evolving parallel cellular automata rules, we propose using coevolutionary genetic algorithm. Discovered this way, rules enable us to design effective parallel schedulers. We present a number of experimental results for both sequential and parallel scheduling algorithms discovered in the context of a cellular automata-based scheduling system.
|
1,654
|
Please write an abstract with title: Combining audio and video for video sequence indexing applications, and key words: Video sequences, Indexing, Layout, Gunshot detection systems, Video coding, Information retrieval, Visual databases, Audio databases, Explosions, Face detection. Abstract: We address the problem of detecting shots of subjects that are interviewed in news sequences. This is useful since usually these kinds of scenes contain important and reusable information that can be used for other news programs. In a previous paper, we presented a technique based on a priori knowledge of the editing techniques used in news sequences which allowed a fast search of news stories. We present a new shot descriptor technique which improves the previous search results by using a simple, yet efficient algorithm, based on the information contained in consecutive frames. Results are provided which prove the validity of the approach.
|
1,655
|
Please write an abstract with title: AI Based Crop Recommendations for Intensive Farming using WSN, and key words: Measurement, Wireless communication, Wireless sensor networks, Crops, Weather forecasting, Soil, Real-time systems. Abstract: AI’s promise in the field of researching and implementing intelligence in agricultural automation using WDN data is becoming increasingly important for developing intelligent solutions. Based on the projected rainfall, the resilience of the soil, and the history of the crop planted, a MEA is utilised in the proposed study to predict the type of crops that can be cultivated to acquire the maximum yield. Farmers will be provided with a user-friendly AGILE FARM web application to aid them in determining the sort of crop that can be cultivated depending on the specified parameters. Farmers will be given ideas on alternate sorts of crops that can be grown as a substitute to prevent the anticipated problems. Farmers can make their option depending on the available seeds, fertilizer, and cultivation history because the advice is not with one alternate crop. In the farm field and water bodies, a Wireless Sensor Network with a painless Mesh Topology will be used to collect vital metrics, which will be processed utilizing OCC boards to make precise predictions, and these data sets will be used for future forecasting. The planned work will significantly lessen the farmers’ real-time issues. When compared to other methods, the random forest machine learning algorithm gives good evaluation metrics such as R2, RMSD, MSD, MAD of 0.99, 0.22, 0.24, 0.122 with 99 percent accuracy. The farmer can acquire a satisfactory yield by planning the required crop while taking seasonal risk into account.
|
1,656
|
Please write an abstract with title: A sample truncation rule for product reliability estimation with multiple censoring data, and key words: Reliability, Estimation, Weibull distribution, Servomotors, Maintenance engineering, Exponential distribution, Shape. Abstract: For product reliability estimation in the condition of only some successfully operation times available, this paper presents an approach to estimate the location parameter of three-parameter Weibull distribution, as well as a criterion to construct an effective data set, i.e. to truncate the original sample into a beneficial sample of smaller size. Through comparing the estimated life distributions and reliabilities based on different sub-sets of the original one composed of all the available operation time records, a criterion is worked out to truncate the original sample of the censoring life data for reliability estimation. Lots of simulated data are generated by Monte Carlo sampling, by which the proposed criterion is testified.
|
1,657
|
Please write an abstract with title: A New Memory Module for Memory Intensive Applications, and key words: Acceleration, Circuit simulation, Supercomputers, Scattering, Global communication, Electrical engineering, Load flow, Sparse matrices, Bridge circuits, Microcomputers. Abstract: Some applications with gather / scatter operations are difficult to accelerate. These operations cause inefficient cache use in each processor and fine grain global communications in parallel systems. There are several applications with such characteristics particularly in electrical engineering. For examples, circuit simulation and power flow simulation with LU decomposition for random sparse matrix has such characteristics. This paper presents how to make inexpensive personal supercomputers to solve these problems. In order to get the merit of commercial-off-the-shelf (COTS) continuously after the death of vector supercomputer vendors, it is designed without any modification on CPU, bridge chips on motherboard and memory chips. Only plugging a new memory module with vector load / store function and communication functions make an inexpensive home-use personal computer into a node similar to Earth simulator's one. Applications with unit striding or indexed accesses are going to be accelerated. How to accelerate NAS CG is shown as an example.
|
1,658
|
Please write an abstract with title: Nonlinear analysis of the magnetic flux distribution in the magnetized magnet stabilized in air, and key words: Magnetic flux, Magnetic analysis, Saturation magnetization, Permanent magnets, Maxwell equations, Magnetic fields, Current density, Permeability, Demagnetization, Magnetic hysteresis. Abstract: A theoretical model for the relationship among magnetic quantities describing the one- versus two-dimensional field in a permanent magnet is developed. The model is applied to two problems: 1) determination of the direction of the residual magnetism and 2) finding the magnetic flux distribution in a magnet stabilized in air. The vector potential equation in a form unified for both problems is derived and transformed into a partial-difference algorithm. The numerical line-iteration procedure is described and used to solve these problems for a six-pole permanent magnet rotor of an electrical alternator.
|
1,659
|
Please write an abstract with title: MultiVision: Designing Analytical Dashboards with Deep Learning Based Recommendation, and key words: Data visualization, Visualization, Encoding, Deep learning, Tools, Measurement, Layout. Abstract: We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a tedious and time-consuming process to select meaningful combinations of data columns for creating charts. This process is further complicated by the needs of creating dashboards composed of multiple views that unveil different perspectives of data. Existing automated approaches for recommending multiple-view visualizations mainly build on manually crafted design rules, producing sub-optimal or irrelevant suggestions. To address this gap, we present a deep learning approach for selecting data columns and recommending multiple charts. More importantly, we integrate the deep learning models into a mixed-initiative system. Our model could make recommendations given optional user-input selections of data columns. The model, in turn, learns from provenance data of authoring logs in an offline manner. We compare our deep learning model with existing methods for visualization recommendation and conduct a user study to evaluate the usefulness of the system.
|
1,660
|
Please write an abstract with title: Research on Image Enhancement Technology of Locomotive Wheelset based on Image Equalization and Fuzzy Theory, and key words: Image segmentation, Automation, Digital images, Conferences, Wheels, Visual effects, Image enhancement. Abstract: The purpose of image enhancement is to improve the visual effect of the image. It is one of the hot spots of digital image enhancement technology to realize the enhancement effect by changing the contrast of gray scale. In this paper, a method of image contrast enhancement based on mean value segmentation is proposed, which is combined with pattern and image processing technology, to select the appropriate image gray membership function, and to select the threshold value of fuzzy theory and image processing by means of iteration and Otsu method, finally, the final image was decoded and the image was enhanced. In this paper, this technique is applied to the study of image enhancement of locomotive wheelset, and the image results of different processing methods are analyzed.
|
1,661
|
Please write an abstract with title: Four-Factor Polarity Switching Control for Synchronous Vibration Suppression of Active Magnetic Bearings Rigid Rotors System in the Full Rotational Speed Range, and key words: Rotors, Vibrations, Velocity control, Switches, Control systems, Low-pass filters, Frequency control. Abstract: In order to suppress the synchronous unbalance vibration of the active magnetic bearings (AMBs) rigid rotor system in the full rotational speed range, the polarity switching control (PSC) can effectively suppress the synchronous unbalance vibration of the AMBs-rigid rotor system before and after the rigid cylindrical mode frequency, and the impact of the switching polarity on the system was reduced by using a disturbance observer. However, considering the rigid conical mode, the PSC could not guarantee the synchronous unbalance vibration suppression of the AMBs-rigid rotor system in the full rotational speed range including the rigid cylindrical mode frequency and the rigid conical mode frequency, and the system stability also changes accordingly. This article proposes a synchronous unbalance vibration suppression method based on the four-factor PSC (4-FPSC), which adjusts four polarity factors to suppress the synchronous unbalance vibration before and after two rigid mode frequencies. Besides, the disturbance observer is also avoided. Finally, simulation and experiment results verify the 4-FPSC can effectively suppress the synchronous unbalance vibration of the AMBs-rigid rotor system in the full rotational speed range including the rigid cylindrical and conical mode frequencies.
|
1,662
|
Please write an abstract with title: Robust Person Gait Identification Based on Limited Radar Measurements Using Set-Based Discriminative Subspaces Learning, and key words: Gait recognition, Task analysis, Feature extraction, Radar, Training data, Legged locomotion, Radar measurements. Abstract: Building a robust and scalable radar-based person identification system that can accurately identify registered users and fast enroll new subjects at any time with only limited radar measurements is very desirable for real-world applications. Existing solutions, however, most resort to deep learning techniques that are heavily data-dependent and hard to scale once trained. To overcome these limitations, this article proposes a novel set-based discriminative subspaces learning (SDSL) approach and builds a high-performance gait recognition system based on it. Specifically, we model the system as a two-stage paradigm consisting of a feature embedding network for gait feature extraction, followed by an SDSL module for gait pattern modeling through low-dimensional linear subspace representing and subspaces discriminant learning. Finally, a nearest neighbor classifier (NNC) is adopted to perform person identification in the learned discriminant space by matching the subspace of a probe set with all subspaces in the gallery. Extensive experiments conducted on a radar gait dataset collected in a typical corridor scenario demonstrate not only the superiority of our model in both identification accuracy and scalability, but also its robustness against limited training data.
|
1,663
|
Please write an abstract with title: Optimal Energy Management for a Dual-motor All-wheel Drive Electric Vehicle Considering Battery Temperature, and key words: Torque, Simulation, Neural networks, Mechanical power transmission, Electric vehicles, Real-time systems, Mathematical models. Abstract: Facing with various driving condition, advanced dual-motor electric vehicle driven system is expected to perform better energy efficiency than single motor owing to its configurable working point. In this paper, a real-time energy management developed for a dual-motor four-wheel-drive battery electric vehicle is proposed to reduce the energy consumption while decrease battery temperature raise. First, the mathematical model of the proposed vehicle powertrain and battery thermal character are established. Then, dynamic programming is deployed to obtain the optimal torque distribution under series of standard driving cycles. To build the real-time controller, the control rules implying in the optimal control are analyzed and extracted with neural network and implemented online. Simulation results indicate that the proposed energy management strategy can efficiently reduce electricity consumption while realize lower battery temperature raise.
|
1,664
|
Please write an abstract with title: Driving schemes for a-Si and LTPS AMOLED displays, and key words: Active matrix organic light emitting diodes, Flat panel displays, Organic light emitting diodes, Thin film transistors, Circuit stability, Amorphous silicon, Temperature, Backplanes, Threshold voltage, Active matrix liquid crystal displays. Abstract: Design of stable active matrix organic light-emitting diode (AMOLED) displays comes with significant challenges that stem from the electrical property of the backplane materials, line parasitics in the matrix, and the opto-electronic property of the organic light-emitting diode (OLED). This paper reviews voltage and current programming schemes for AMOLEDs. Following a systematic review of pixel circuits, design considerations are examined for both current and voltage schemes with focus on stability and programming speed for both amorphous silicon (a-Si) and low temperature polysilicon (LTPS) pixel circuits. In particular, spatial parameter variations and stability, which hinder reliable operation of AMOLED display backplanes, are discussed. Analysis shows that while driving schemes reported hitherto maybe suitable for small and medium size displays, new schemes are critically needed for large-area high-resolution AMOLED displays.
|
1,665
|
Please write an abstract with title: Proceedings at one hundred and seventy-second ordinary general meeting, and key words: Voting, Heart, Power supplies, Fitting, Buildings. Abstract: (President) in the chair.
|
1,666
|
Please write an abstract with title: A Concept of Multiphase Dynamic Charging System with Constant Output Power for Electric Vehicles, and key words: Transmitters, Receivers, Power generation, Windings, Inductance, Inverters, Capacitors. Abstract: Dynamic charging of Electric Vehicles (EV) is a new initiative aimed at increasing EV uptake. However, pulsating output power along driving direction is one of the most serious problems of such technology. This paper proposes a new configuration that ensures constant power with minimum power electronics requirements. The proposed system utilizes multiple primary windings that guarantee a homogeneous mutual magnetic flux for the receiver along the driving direction. This results in a constant induced voltage and hence constant output power to charge the EV's battery. Structure layout for primary transmitters including ferrite cores and windings is suggested and theoretical analysis is conducted to draw conditions of each winding's current phase and amplitude for achieving constant output power. The effectiveness of the proposed system is analytically demonstrated and experimentally verified using a 3-kW laboratory prototype with three-phase system.
|
1,667
|
Please write an abstract with title: Reactive Load Prediction Based on a Long Short-Term Memory Neural Network, and key words: Reactive power, Logic gates, Power grids, Load modeling, Predictive models, Data models, Time series analysis. Abstract: Accurate reactive load prediction can improve the accuracy and process of reactive power optimization for power grids and improve the control effect. The changes in the bus reactive load and active load are not synchronous, the base of the reactive load is small, nonlinear changes are abundant, and it is difficult to mine the inherent data trends. In view of the above problems, this paper proposes a method for predicting bus reactive loads based on deep learning. A bus reactive load prediction model is constructed based on a dual-input long short-term memory neural network to mine the detailed characteristics of active and reactive load data. Active and reactive loads are used as input and output data for the dynamic modeling of load time series data to form integrated forecasts of bus active and reactive loads. The experimental results show that this method can accurately predict the reactive power load of buses, and the prediction accuracy is better than that of time series and general long short-term memory neural network prediction models.
|
1,668
|
Please write an abstract with title: Distributed device networks with security constraints, and key words: Distributed control, Collaborative work, Control systems, Manufacturing, Personal digital assistants, International collaboration, Monitoring, Industrial control, Computer networks, Supply chains. Abstract: In today's globalized business world, outsourcing, joint ventures, mobile and cross-border collaborations have led to work environments distributed across multiple organizational and geographical boundaries. The new requirements of portability, configurability and interoperability of distributed device networks put forward new challenges and security risks to the system's design and implementation. There are critical demands on highly secured collaborative control environments and security enhancing mechanisms for distributed device control, configuration, monitoring, and interoperation. This paper addresses the collaborative control issues of distributed device networks under open and dynamic environments. The security challenges of authenticity, integrity, confidentiality, and execution safety are considered as primary design constraints. By adopting policy-based network security technologies and XML processing technologies, two new modules of Secure Device Control Gateway and Security Agent are introduced into regular distributed device control networks to provide security and safety enhancing mechanisms. The core architectures, applied mechanisms, and implementation considerations are presented in detail in this paper.
|
1,669
|
Please write an abstract with title: A Zonal Volt/VAR Control Mechanism for High PV Penetration Distribution Systems, and key words: Reactive power, Sensitivity, Runtime, Correlation, Simulation, Clustering methods, Control systems. Abstract: This paper presents a zonal Volt/VAR control scheme for regulating voltage in unbalanced 3-phase distribution systems using inverter-based resources (IBR). First, the dependency between nodal voltage changes and IBR reactive power injections is derived via voltage sensitivity studies. Then, a fast-incremental clustering method is used to divide the distribution circuit into weakly-coupled zones based on correlations between nodal voltage sensitivities. The weak-coupling allows the voltage to be regulated independently within each zone using a rule-based voltage controller to dispatch IBR for voltage corrections. Simulation results on actual distribution feeder show that the proposed zone-based Volt/VAR control method maintains system voltages within their operational limits while reducing the runtime of the Volt/VAR controller from tens of second to a couple of milliseconds compared with centralized, optimization-based Volt/VAR control methods.
|
1,670
|
Please write an abstract with title: Multi-scale Retinal Vessel Tortuosity Measurement Based on Wavelet Transform, and key words: Wavelet transforms, Support vector machines, Pathology, Blood vessels, Wavelet analysis, Skeleton, Retinal vessels. Abstract: The presence of tortuosity in the retinal vessels is crucial in the diagnosis of ocular fundus disorders. There are numerous methods for computing the tortuosity of the retinal arteries available today, all of which have yielded impressive results. However, they usually divide vessels into smaller vascular structures to calculate local tortuosities, which are then weighted summed to get the global tortuosity of the entire vessel. The approach of local division on a two-dimensional image weakens local vessel tortuosity information and makes it unable to accurately portray the vessel's tortuosity. Hence, we propose a wavelet transform-based multi-scale approach for evaluating the tortuosity of fundus vessels in order to investigate the differences between normal and pathological vessels in terms of spatial tortuous properties. To acquire the skeleton of the fundus vessels, we apply the Zhang-Suen method to refine retinal vessel images segregated by experts. The vascular skeletons are then converted into one-dimension signals, on which we carry out a wavelet transform to yield vascular tortuosity of different scales, which is further evaluated with entropy. The results of the experiments reveal that the suggested tortuosity measure can effectively classify the curvature of blood vessel segments and blood vessel networks.
|
1,671
|
Please write an abstract with title: A general approach to natural language conversion, and key words: Natural languages, Natural language processing, Humans, Boats, Vocabulary, Speech, Dictionaries. Abstract: Natural language processing is a technique that includes both natural language understanding and natural language generation. Translating one natural language into another becomes complex due to structural difference, varieties of meanings, different forms of verbs etc. In this paper, a general algorithm has been developed which takes one natural language (i.e. English, German etc) as input and produces another natural language (i.e. Bengali, Japanese etc.) as output reserving the same expression. For understanding the input natural language, a smart-parse algorithm has been developed which unambiguously and efficiently generates a stack of the parse tree from the existing structure. After parsing, it incorporates itself with the knowledge base and dictionary and finally produces the corresponding targeted natural language. After fixing up the input and output natural language, it is possible to use this algorithm for translation after simple modification.
|
1,672
|
Please write an abstract with title: Joint Digital Online Compensation of TX and RX Time-Varying I/Q Mismatch and DC-Offset in mmWave Transceiver System, and key words: TV, Radio frequency, Estimation, Standards, Baseband, Clocks, Mixers. Abstract: Millimeter-wave (mmWave) RF and analog front-end circuits are very susceptible to chip process and temperature variation, which cause I/Q mismatch and DC offset. As a consequence, the system performance can be seriously degraded, especially in wideband multi-Gb/s systems. This paper proposes an online estimation and compensation in the baseband receiver end of a single carrier (SC) system for TX and RX frequency independent (FI) initial and time-varying (TV) I/Q mismatch and DC-offset. Based on specification of IEEE 802.11ay, the compensated image rejection ratio (IRR) performance of the TX and RX FI I/Q mismatch effects can be improved from 16.43 dB to 54.70 dB at SNR of 25.52 dB. Moreover, we propose a novel algorithm based on the Golay sequence for estimation and compensation to cancel TX and RX initial/TV DC-offset. The DC-offset in the I/Q channel is improved from −56.46 dB/−58.56 dB to −97.30 dB/−98.70 dB at SNR of 25.52 dB. In the hardware implementation, a four-time parallelism architecture are proposed to work at a 625 MHz clock rate with a 28-nm HPC_PLUS CMOS process under 64-QAM mode for 15 Gbps transmission. Using a clock gating control scheme for FI I/Q mismatch and DC-offset estimator, the total power of the proposed the module can be reduced from 59.5 mW to 32.7 mW. The gate count and power of the proposed estimation/compensation design are only 2.94% and 1.69% of the overall digital RX baseband gate count and power consumption.
|
1,673
|
Please write an abstract with title: Optimal Allocation of Electric Vehicle Charging Stations With Adopted Smart Charging/Discharging Schedule, and key words: Load modeling, Batteries, Resource management, Schedules, Uncertainty, State of charge. Abstract: Modeling and allocation of the Electric vehicles Charging Stations (EVCS) within the distribution network, as per the growing use of Electric vehicles (EVs) is a challenging task. In this paper, to manage the EVCS, first, with the aim of peak shaving, valley filling, and flattening the load curve of the network, the optimal planning of EV’s charging/discharging is devised. In this regard, after modeling involving random variables, a novel hybrid method, based on the Multi Objective Particle Swarm Optimization (MOPSO) optimization algorithm and sequential Monte Carlo simulation is presented. The purpose of the presented optimal charge/discharge schedule is to control the rate and time of charging/discharging of EVs. In the proposed model, various battery operation strategies, including Uncontrolled Charging Mode (UCM), Controlled Charging Mode (CCM), and Smart Charge/Discharge Mode (SCDM) are also considered. In the next step, in order to implement the charge/discharge schedule of the EVCS profitably, a new formulation is presented for the allocation of two EVCSs (administrative and residential EVCS). In the proposed formulation, various objective functions such as power loss reduction, reducing power purchases from the upstream network, reducing voltage deviation in buses, improving reliability is addressed. Moreover, to incentivize the owner to construct the EVCS with adopted charging/discharging schedule, the optimal profits sharing between Distribution System Operator (DSO) and EVCS owner is also performed. The proposed formulation is applied to a standard network (IEEE 69 buses) and encouraging results are achieved.
|
1,674
|
Please write an abstract with title: Defect Prediction of Relay Protection Systems Based on LSSVM-BNDT, and key words: Maintenance engineering, Protective relaying, Servers, Decision trees, Circuit faults, Support vector machines, Databases. Abstract: Accurate and robust defect diagnosis methods of relay protection systems could enhance power systems safety and prevent casualties. It is challenging for traditional defect diagnosis methods, such as Iterative Dichotomiser 3 (ID3) and Classifier 4.5 (C4.5), to effectively solve the problem with missing or ambiguous data that significantly affect the accuracy of diagnosis. To solve these challenges, a novel defect diagnosis method based on least square support vector machine Bayesian network decision tree (LSSVM-BNDT) is proposed in this article. LSSVM is first adopted to fill the missing data. Then, to deal with the nonexclusive ambiguous data, a multistate Bayesian network is integrated into a decision tree to make a posterior correction. The metrics of ten-fold receiver-operating characteristic cross validation and analysis of means are employed to evaluate the effectiveness of the proposed LSSVM-BNDT model. Cases studies are performed to analyze a variety of equipment, including remote terminal unit, measure and control devices, protective devices, merging units, interchangers, network analyzers, and fault recorders. Results show that the proposed LSSVM-BNDT has improved detection accuracy by up to 14.87% and 8.56% compared with the ID3 and C4.5 benchmark models, respectively.
|
1,675
|
Please write an abstract with title: On orientation and anisotropy estimation for online fingerprint authentication, and key words: Anisotropic magnetoresistance, Fingerprint recognition, Authentication, Feature extraction, Multimedia systems, Noise robustness, Biometrics, Image texture analysis, Protection, Fingers. Abstract: Local dominant orientation estimation is one of the most important operations in almost all automatic fingerprint authentication systems. Robust orientation and anisotropy estimation improves the system's reliability in handling low-quality fingerprints, which is crucial for the system's massive application such as securing multimedia. This paper analyzes the robustness of the orientation and anisotropy estimation methods and the effect of the modulus normalization on the estimation performance. A two-stage averaging framework with block-wise modulus handling is introduced to inherit the merits of the both linear and normalized averaging methods. We further propose to set the modulus of an orientation vector to be its anisotropy estimate instead of unity so that the orientation inconsistency of gradients is included in the second stage of averaging. These two measures improve the robustness of the fingerprint local dominant orientation estimation and lead to an anisotropy estimate that reflects the characteristics of fingerprint more effectively. In addition, the proposed approach is computationally efficient for online fingerprint authentication. Extensive experiments using both synthetic images and real fingerprints verify the feasibility of the proposed approach and demonstrate its robustness to noise and low-quality fingerprints.
|
1,676
|
Please write an abstract with title: Microfabricated capped channels for biomolecular motor-based transport, and key words: Micromotors, Resists, Microfluidics, Biological system modeling, Power system modeling, Force sensors, Power generation, Nanobioscience, Biological systems, Geometry. Abstract: Kinesins are molecular motors that transport intracellular cargo along microtubules and provide a model system for force generation that can be exploited for biomotor powered nano- and micro-machines. To use this biological system for microscale transport, the most common approach is to reverse the biological geometry and move microtubules along surfaces functionalized with kinesin motors. The microtubules then become potential transport vehicles for sensors and lab-on-a-chip applications. A key requirement for extracting useful work from this system is confinement and control of microtubule movements over kinesin-coated surfaces. The open channel approaches used to date are limited because microtubules that lose contact with the kinesin motors rapidly diffuse away. As a step toward making stand-alone devices incorporating kinesin motors and microtubules, we have developed methods to fabricate capped channels that provide three-dimensional microtubule confinement. We first tested the activity of kinesin motors on a range of surfaces and found that motors were functional on a number of hydrophilic surfaces and nonfunctional on hydrophobic surfaces. In this work, SU-8 photoresist is used to fabricate open channels and a layer of bisbenzocyclobutene (BCB) or dry-film photoresist is used to encapsulate the channels. To allow sample introduction, we fabricate a hierarchical series of microfluidic channels. In this approach, macroscale (/spl sim/250-/spl mu/m) channels in glass or silicon substrates are used to hold fine-gauge stainless steel tubing and allow connection to various fluid sources and intermediate scale (/spl sim/50-/spl mu/m) channels fabricated in thick (/spl sim/50-/spl mu/m) dry-film photoresist are used to connect the macroscale channels to microscale (1-15-/spl mu/m) SU-8 photoresist channels. This paper is the first demonstration of kinesin-based microtubule transport in enclosed microfluidic channels and provides an important step toward packaging these biomolecular motors into functional devices.
|
1,677
|
Please write an abstract with title: A Low-Voltage Robust Class-C VCO With Dual Digital Feedback Loops, and key words: Voltage-controlled oscillators, Robustness, Phase noise, Feedback loop, Steady-state, Voltage control. Abstract: This brief presents a low-supply-voltage robust class-C voltage-controlled oscillator (VCO) with the dual digital feedback loops. One is the digital adaptive bias loop (DABL) which is proposed to ensure startup robustness and improve the phase noise performance of the VCO. And the other is the digital amplitude control loop (DACL), which is adopted to stabilize the oscillation amplitude over process, voltage and temperature (PVT) variations. Moreover, a cooperative algorithm is also proposed in order to make the dual digital loops work properly. Besides, the offset canceling comparators are adopted to guarantee the stability of the digital loops. The proposed VCO is implemented in SMIC 0.18 μm CMOS process, achieving a phase noise of -123.3 dBc/Hz at 1 MHz offset from a 2.55 GHz carrier and a 2.2-2.7 GHz frequency tuning range. The figure-of-merit (FoM) is -190.4 dBc/Hz with the total power consumption less than 1.28 mW at the 0.8 V supply voltage.
|
1,678
|
Please write an abstract with title: SpoC: Spoofing Camera Fingerprints, and key words: Knowledge engineering, Image coding, Forensics, Detectors, Trademarks, Cameras, Generative adversarial networks. Abstract: Thanks to the fast progress in synthetic media generation, creating realistic false images has become very easy. Such images can be used to wrap rich fake news with enhanced credibility, spawning a new wave of high-impact, high-risk misinformation campaigns. Therefore, there is a fast-growing interest in reliable detectors of manipulated media. The most powerful detectors, to date, rely on the subtle traces left by any device on all images acquired by it. In particular, due to proprietary in-camera processes, like demosaicing or compression, each camera model leaves trademark traces that can be exploited for forensic analyses. The absence or distortion of such traces in the target image is a strong hint of manipulation. In this paper, we challenge such detectors to gain better insight into their vulnerabilities. This is an important study in order to build better forgery detectors able to face malicious attacks. Our proposal consists of a GAN-based approach that injects camera traces into synthetic images. Given a GAN-generated image, we insert the traces of a specific camera model into it and deceive state-of-the-art detectors into believing the image was acquired by that model. Likewise, we deceive independent detectors of synthetic GAN images into believing the image is real. Experiments prove the effectiveness of the proposed method in a wide array of conditions. Moreover, no prior information on the attacked detectors is needed, but only sample images from the target camera.
|
1,679
|
Please write an abstract with title: Ultrasonic Guided Wave Inversion Based on Deep Learning Restoration for Fingerprint Recognition, and key words: Fingerprint recognition, Image reconstruction, Tomography, Acoustics, Transmission line matrix methods, Sensors, Noise reduction. Abstract: As an established biometric authentication approach, fingerprint scanning has received considerable attention due to its high accuracy and reliability. In this article, the fingerprint reconstruction at any position is achieved in large physical domains, which monitors wavefield variations of plate-like structures within arrays through the ultrasonic guided wave. Accurate reconstruction and quantitative characterization of fingerprints are obtained using fast inversion tomography (FIT) based on the deep learning convolutional neural network (DLCNN). Parametric optimization is conducted to reveal submillimeter fingerprint minutiae, and a specific DLCNN model is proposed for the artifact removal in FIT reconstructions. The results prove that the FIT based on DLCNN restoration can significantly improve the imaging quality in terms of increased resolution, reduced reconstruction errors, and higher fingerprint matching confidence. The reconstruction also allows an exponential improvement in computational efficiency as a result of much-reduced sensor numbers. Several factors affecting the performance of the proposed reconstruction method are discussed at the end.
|
1,680
|
Please write an abstract with title: Scalable and Secure Architecture for Distributed IoT Systems, and key words: Malware, Computer architecture, Machine learning, Computer hacking. Abstract: Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. Due to their massive deployment and moderate security levels, those devices face a lot of security, management, and control challenges. Their classical centralized architecture is still cloaking vulnerabilities and anomalies that can be exploited by hackers for spying, eavesdropping, and taking control of the network. In this paper, we propose to improve the IoT architecture with additional security features using Artificial Intelligence (AI) and blockchain technology. We propose a novel architecture based on permissioned blockchain technology in order to build a scalable and decentralized end-to-end secure IoT system. Furthermore, we enhance the IoT system security with an AI-component at the gateway level to detect and classify suspected activities, malware, and cyber-attacks using machine learning techniques. Simulations and practical implementation show that the proposed architecture delivers high performance against cyber-attacks.
|
1,681
|
Please write an abstract with title: Experimental Performance Analysis of a Self-Driving Vehicle Using High-Definition Maps, and key words: Self-driving vehicles, Sensor Fusion. Abstract: In this paper, we present our first experimental results on self-driving vehicles using high-definition maps. We will start with the CAN bus based Drive-By-Wire subsystem, on board computers, and the sensors used in this study. Then, we discuss the sensor fusion and vehicle guidance algorithms, and finally present our experimental results. We also have a video recording of our experiment, and its YouTube link is shared in the paper. All of the experimental results and plots presented in the paper, and the video link refer to the same self-driving experiment that we did on the Florida Polytechnic University campus. The autonomous vehicle (AV) methodology adopted in this work has some similarities with the Cruise AV’s approach and the use of high definition (HD) maps. The research vehicle used in this work is equipped with radar, lidar, camera, GPS, and IMU sensors, but in this work we use only the GPS, wheel rotation and camera sensors. After presenting our first experimental AV results, we comment on sensor fusion related issues, and possible future steps for improvement.
|
1,682
|
Please write an abstract with title: Study of reliable via structure for Fan Out Panel Level Package (FoPLP), and key words: High-temperature superconductors, Fans, Shape, Reliability engineering, Structural engineering, Thermal stability, Stress. Abstract: The fan out technology has been recently introduced as an effective method to reduce a packaging cost and to minimize a package size by using a redistribution layer(RDL). Moreover, as the number of high-capacity ultra-small devices increases, transition to fan-out package technology (FOPKG) is an important for realizing fast signal speed and high capacity. To this end, one of the key parameters for FOPKG’s interconnection density and fine pitch is adopting the stacked fine via technology.In this paper, we propose the physical crack mode of the stacked via in the fan-out panel level package(FOPLP), and try to optimize structural integrity based on the crack generation mechanism. Physical crack in stacked vias occurs in two different modes: via-via interface crack, via-dielectric point crack. To investigate via-via interface crack, various via shapes were tested. As a result, vias with lower dimple showed better structural stability under temperature changing condition. For via-dielectric point crack, structural DOE for tapered via angle was performed, and an optimal angle with released stress between cu and dielectric could be found. Furthermore, it was found that physical crack occurs depending on via size. Thus, in order to secure reliability margin, a study was conducted to change in shape and reinforce the weak point.In summary, as a result of the above study, it could be possible to optimize the via structure. The package reliability tests (Pre-condition + TC / u-HAST, HTS) were successfully evaluated with a vehicle that is adopted by optimal triple stacked via structure. By using the stacked via optimized through this study, the characteristics of FOPKG can be further improved by high electrical performance and the reduction of package size.
|
1,683
|
Please write an abstract with title: Compact Rectifiers With Ultra-wide Input Power Range Based on Nonlinear Impedance Characteristics of Schottky Diodes, and key words: Impedance, Rectifiers, Schottky diodes, Transmission line measurements, Power transmission lines, Resistance, Radio frequency. Abstract: Two high-efficiency radio-frequency (RF) rectifiers with extended input power range are proposed by taking the advantage of nonlinear impedance characteristics of diodes. Each rectifier consists of two subrectifiers that operates at high- and low-power levels, respectively. A nonlinear power division strategy is applied to the input power level without any power dividers or couplers. A λ/8 transmission line is introduced to compensate the imaginary part of diode impedance. A λ/4 transmission line is applied to reverse the diode impedance variation with respect to the input power. Two rectifiers operating at 2.45 GHz are fabricated and measured. Rectifier I shows a RF-dc power conversion efficiency exceeding 50% over an input power range of 23.3 dB (from 6.5 to 29.8 dBm), with maximum efficiency 74.5% at 27 dBm input power. Rectifier II shows an input power range exceeding 50% over 31 dB (-1 to 30 dBm) with maximum efficiency of 68.5% at 28 dBm.
|
1,684
|
Please write an abstract with title: A Novel Three-phase Multilevel Inverter with Reduced Number of IGBTs, Developed for Drive Application, and key words: Induction motors, Simulation, Velocity control, Pulse width modulation, Multilevel inverters, Topology, Steady-state. Abstract: This paper exposes a new three-phase multilevel inverter (MLI) suitable for electrical motor drive applications, which consists of a cascade connection of basic cells. In this proposed three-phase topology, the ratio of the utilized power components against the generated levels is decremented that leads to decrement the cost and complexity of the converter. The converter is devoted to speed control of the induction motor (IM). One of the methods for speed control of the IM is the constant Volt-per-Hertz (constant V/f) control method. The multicarrier level-shifted pulse width modulation (LS-PWM) is applied to the new structure to obtain a high-quality output voltage, which helps to control the amplitude and frequency of output voltage by the sinusoidal reference signal. The simulation is carried out in MATLAB/SIMULINK environment. Furthermore, the simulation result and steady-state torque-time characteristics are presented. Besides, the comparison of introduced structure with some conventional MLIs is shown in terms of the number of switches.
|
1,685
|
Please write an abstract with title: Dynamic Hypergraph Convolutional Network, and key words: Correlation, Convolution, Conferences, Aggregates, Time series analysis, Collaboration, Feature extraction. Abstract: Hypergraph Convolutional Network (HCN) has be-come a proper choice for capturing high-order relationships. Existing HCN methods are tailored for static hypergraphs, which are unsuitable for the dynamic evolution in real-world scenarios. In this paper, we explore a dynamic HCN based on the attention mechanism (DyHCN) for time series prediction. It not only effectively exploits the spatial and temporal relationships in the dynamic hypergraph, but also continuously aggregates the temporal evolution cues of time-varying hypergraphs with the global and local embeddings. Specifically, these merits can be attributed to 1) dynamic hypergraph construction (DHC), which captures the feature of historical context content and provides a guideline for dynamic hypergraph construction; 2) spatio-temporal hypergraph convolution module (STHC), responsible for extracting the spatial and temporal relationships among nodes and hyperedges, and 3) collaborative prediction module (CP), for the overall time-varying hypergraphs embedding aggregation. Such modules endeavor to well learn feature embedding from nodes, hyperedges, and hypergraphs, which produces informative representations for downstream tasks. Experiments on three datasets including Tiingo, Stocktwits, and NYC-Taxi demonstrate that the proposed DyHCN achieves sound performance over existing cousins, and both STHC and CP modules play a key role in modeling the dynamic evolution property of hypergraphs.
|
1,686
|
Please write an abstract with title: A motion generation system for humanoid robots - Tai Chi motion, and key words: Humanoid robots, Computational efficiency, Motion control, Character generation, Intelligent robots, Computer science, Stability, Control theory, Optimization methods, Robot sensing systems. Abstract: This paper proposes a static posture based motion generation system for humanoid robots. The system generates a sequence of motion from given several postures, and the motion is smooth and stable in the balance. We have produced all the motions of Tai Chi Chuan by the system. Motion generation for humanoids has been studied mainly based on the dynamics. Dynamic based method has, however, some defects: e.g., numerous parameters which can not be always prepared, expensive computational cost and no guarantee that the motions are stable in balance. We have, thus studied less dependent-on-dynamics approach. A motion is described as a sequence of postures. Our system figure out if we need extra postures to insert stability. This method enables humanoid robot, HOAP-1 to do Tai Chi Chuan.
|
1,687
|
Please write an abstract with title: Quantitative characterization of event streams in analysis of hard real-time applications, and key words: Performance analysis, Streaming media, Real time systems, Embedded system, Concrete. Abstract: Many real-time embedded systems process event streams which are composed of a finite number of different event types. Each different event type on the stream would typically impose a different workload to the system, and thus the knowledge of possible correlations and dependencies between the different event types could be exploited to get tighter analytic performance estimations of the complete system. We propose an abstract stream model to characterize such an event stream. The model captures the needed information of all possible traces of a class of event streams and can hence be used to obtain hard bounded worst-case and best-case estimations of a system. We show how the proposed abstract stream model can be obtained from a concrete stream specification, and how it can be used for performance analysis. The applicability of our approach and its advantages over traditional worst-case performance analysis are shown in a case study of a multimedia application.
|
1,688
|
Please write an abstract with title: Predicting House Price in India Using Linear Regression Machine Learning Algorithms, and key words: Machine learning algorithms, Biological system modeling, Linear regression, Urban areas, Sociology, Prediction algorithms, Classification algorithms. Abstract: The price of house is increased every year according to the location and it indicates the current economic situation so there is a need for a system to predict house sales in the future for both buyer and the seller. Here we use dataset of India across different cities and having more than 68,613 entries of train data and 28000 test data of housing sales in whole, India. This analysis includes the effect of markdowns on the sales and the extent of effects on the sales by size, price, area etc. has been analyzed using different machine learning algorithms. Estimating home sales can help the developer determine the selling price of the home and the best time for the buyer to purchase the home. The output values of the algorithms are estimated based on the input characteristics from the data presented in the system and the analysis is a process. Physical conditions, concept and location are the three factors that determine the selling price of a home.An exact forecast of forthcoming development market interest, particularly the private market, is central imperative to strategy producers, as it could assist with forming procedures to develop/balance out the economy and fulfill the social requirements. In spite of that, a sensible forecast of future private interest is never a simple assignment, as it is represented by various social and monetary elements. In this paper, four proactive factor models are created and thought about for straightforwardly anticipating India private area a wide range of interest. In giving a scope of potential estimates, the model additionally gives a chance to the chief to practice judgment in choosing the most fitting figures. We depict the continuous internet based customer conduct expectation framework which predicts the clients buying aim when the client visits the site. To achieve the assignment, we rely upon meeting and guest data and we utilize gullible Bayes classifier, Logistic Regression, Neural Network, GBC, choice tree and arbitrary timberland research the dataset for furcating the buyer choice. Also, we use oversampling to work on the exhibition and the adaptability of the classifier. The outcomes show that irregular backwoods creates the higher precision and utilized different Algorithms. We study about the algorithm linear Regression taking a data set.
|
1,689
|
Please write an abstract with title: Filtering 180° Hybrid Coupler Using Dual Composite Right/Left-Handed Resonators, and key words: Antenna measurements, Couplings, Filtering, Resonator filters, Prototypes, Couplers, Propagation losses. Abstract: This paper proposes a new type of filtering 180° hybrid coupler using dual composite right/left-handed resonators. The dual composite right/left-handed resonator is composed of parallel-connected quasi-lumped inductor and capacitor. It thus has the flexibility for inductive and capacitive couplings which are required in a filtering 180° hybrid coupler. The filtering 180° hybrid coupler proposed in this paper is operated at 2.45 GHz. Full-wave simulated results as well as measured results are presented for validation. Both results show that the fabricated prototype has satisfactory bandpass response and isolation. The circuit is compact and occupies an area of 0.12 λg × 0.12 λg.
|
1,690
|
Please write an abstract with title: Substantiation of allocation of protected territories in Tomsk, and key words: Protection, Cities and towns, Environmental economics, Working environment noise, Psychology, Lakes, Cultural differences, Law, Legal factors. Abstract: One of the ways of the city environment's improvement is its gardening. Recreational zones serve for short-term or long rest of people, removal of weariness from industrial pressure, exhaustion from city noise and other negative influences of settlements.
|
1,691
|
Please write an abstract with title: Haptic Data: Compression and Transmission Protocols, and key words: Robot sensing systems, Sensors, Tactile Internet, Robot kinematics, Shape, Feature extraction, Skin. Abstract: The transmission of the haptic signals from the slave side to the master through the communication channel should have an acceptable quality. This chapter presents haptic signal characteristics along with their perception by machines and humans. A haptic interface consists of a mechanism, sensors, actuators and hardware to estimate the human movement and return the forces from the slave. The chapter also presents some works where the compression algorithm is used in the application layer of transmission protocols. This compression technique also uses Weber's perception rule to sample higher or lower. Multiplexing and synchronizing different media streams with the haptic stream is another essential requirement for the transport protocol to obtain a good Quality of Service. The main performance metrics for haptic transport protocols are returned delay time, packet loss, jitter and throughput.
|
1,692
|
Please write an abstract with title: Weighting Factors' Real-time Updating for Finite Control Set Model Predictive Control of Power Converters via Reinforcement Learning, and key words: Industrial electronics, Simulation, Conferences, Reinforcement learning, Real-time systems, Inverters, Predictive control. Abstract: The selection of weighting factors (WFs) is a common obstacle for the finite control set model predictive control (FCS MPC) of power converters. This paper proposes a generic approach to update the WFs via reinforcement learning (RL). The WFs' selection is self-taught online with full consideration of user-defined requirements. The trained policy is deployed to update the WFs in real-time. The self-taught process can be reactivated anytime in case of parametric variations or load change. This idea is verified on FCS MPC-regulated stand-alone inverters cascaded with LC input filters. Simulation results demonstrate that RL significantly improves the load-voltage tracking accuracy without sacrificing dc-link voltage stabilization.
|
1,693
|
Please write an abstract with title: Interference Rejection and Equalization for DS/CDMA Multiuser Communication, and key words: Multiaccess communication, Intersymbol interference, Mobile communication, Multipath channels, Multiple access interference, Time varying systems, Iterative methods, Iterative decoding, Filters, Cost function. Abstract: In direct-sequence code division multiple access (DS/CDMA) mobile communication systems with time-varying multipath channels, both intersymbol interference (ISI) and multiple-access interference (MAI) must be considered. It has been shown that iterative equalization and decoding method is an efficient technique to combat ISI. Based on this approach, we propose a turbo equalization-like receiver for multiuser DS/CDMA systems in multipath channels. The proposed MAI-rejection/ISI suppression filter is based on a cost function evaluated at the PN code despreader's and data detector's output. Besides, our scheme does not require a training signal. Simulation results show that the proposed iterative receiver performs better than that of non-iterative scheme, and the BER decreases with the number of iteration increases
|
1,694
|
Please write an abstract with title: Micromagnetic modeling of adjacent track erasure in longitudinal recording, and key words: Micromagnetics, Magnetic heads, Energy barrier, Magnetization, Anisotropic magnetoresistance, Random sequences, Degradation, Writing, Bit error rate, Testing. Abstract: Adjacent track erasure in longitudinal recording was studied using a micromagnetic model. The gap and fringe fields of two heads designed to work for 100 kTPI were used to write and erase a 31-bit pseudorandom sequence (PRS) in the main track. Comparisons on recording performance were made based on the calculated magnetization profile and the equalized PRS read back signal. It was shown that, for the case of a 3800-Oe fringe field, the quality of the transitions degraded drastically when the transitions were exposed to the fringe field more than 1000 times. On the other hand, a 2000-Oe fringe field left unaffected transitions even when the transitions were exposed to the field more than 100 000 times.
|
1,695
|
Please write an abstract with title: Software-only multiple variable length decoding for real-time video on MDSP, and key words: Decoding, Throughput, Table lookup, Embedded system, Feeds, Bit rate, Computer science, Application software, Motion compensation, Huffman coding. Abstract: We present the multiple variable length decode algorithm implemented in most video applications on MDSP. In our implementations we were able to decode multiple symbols per cycle. The implementation is efficient and is targeted towards memory constrained embedded systems. We have confirmed this algorithm in our implementations of H261/3, MPEG2/4 and achieved multifold speedup improvements against algorithms which can decode at the symbol rate only. This limits the decoding throughput capability of these algorithms. Most parallel decoding approaches use the length of the first codeword to detect the second codeword in parallel. By a single table lookup operation we detect multiple codewords without any detection mechanism.
|
1,696
|
Please write an abstract with title: Multi-Objective Trade-Off Quantification Based Design Optimization for Power Electronic Systems in More-Electric-Aircrafts, and key words: Capacitors, Reliability engineering, MOSFET, Measurement, Integrated circuit reliability, Switches, Rectifiers. Abstract: In this paper, a comprehensive formulation of reliability models for active and passive power components (i.e., capacitors and power semiconductor devices (MOSFETS)) of a regulated transformer rectifier unit (RTRU) for more electric aircraft application is presented. Additionally, the work focuses on the reliability analysis and evaluation at the system level for a non-modular discrete MOSFET based auxiliary power supply unit for more-electric-aircraft. A rigorous quantitative assessment of reliability, volume and power loss is carried out at the component level as well as system level, verifying how a particular design relates to the specific performance parameters. Keeping this as a motivation, this paper also focuses on studying and analyzing the inter-relation among reliability and other performance metrics such as power density and efficiency taking a 3kW RTRU as an example design. The major metrics under consideration for this study are the failure in time (FIT), mean time to failure (MTTF), power density, efficiency while keeping the eye on most failure prone elements of the power converter - capacitors and active power semiconductors. A comprehensive quantitative evaluation based on thermal management size, system reliability is done on choice of the switching semiconductors where the candidate pool includes Si and SiC MOSFET technologies. From the analysis on three different types of widely used capacitors - film, ceramic, aluminum electrolytic, it is concluded that the optimum choices of capacitors for high voltage DC link and low-voltage output belong to Aluminum and Ceramic types, respectively. Finally, the optimum selection of power stage components is derived from the extensive evaluation of the overall RTRU system in terms of system size and reliability.
|
1,697
|
Please write an abstract with title: Real-time face recognition for smart home applications, and key words: Face recognition, Smart homes, Face detection, Detectors, Facial features, Real time systems, Cameras, Hardware, TV, Robustness. Abstract: We propose a near real-time face recognition system for consumer/embedded applications. The system is embedded in an interconnected home environment and enables intelligent servicing by automatic identification of users. It consists of four processing steps: (1) face detection by stepwise pruning, (2) model-based facial feature extraction, (3) face normalization by affine warping, and (4) face recognition by discrimination analysis. The system has been applied in daily life rooms using ordinary cameras. Under these conditions, it achieves over 95% recognition rate and 4 frames/s processing speed.
|
1,698
|
Please write an abstract with title: A Multi-Service Model of Resources With the Neighboring Choice of Allocation Units, and key words: Optical switches, Optical network units, Analytical models, Resource management, Markov processes, Wavelength division multiplexing, Mathematical model. Abstract: This article discusses a discretized model of resources to which a mixture of multi-service traffic streams is offered. In the model the connections of individual traffic classes that require a large number of allocation units are always executed using adjacent allocation units. The necessity of occupying the adjacent allocation units is typical, for example, for elastic optical networks, in which these units are called frequency slots. The article proposes a new occupancy distribution specifically designed for these systems. The new occupancy distribution is based on an approximation of the service process by a reversible Markov process. Particular attention is given to the method for calculating the so-called conditional transition probability of the transitions between neighboring states in the Markov process. The analytical results of the modeling are compared with the results of simulations of corresponding network systems.
|
1,699
|
Please write an abstract with title: Film Review Sentiment Classification based on BiGRU and Attention, and key words: Deep learning, Time series analysis, Neural networks, Big Data, Feature extraction, Motion pictures, Data models. Abstract: Aiming at the problem of insufficient features extracted from film review data in traditional neural network models, combined with deep learning methods, this paper proposes a movie review sentiment classification model Roberta-BiGRU-ATT based on BiGRU and Attention. Firstly, Roberta model is used to extract feature representation of film review text to improve the ability of word vector representation. Secondly, the acqu32ired word features are inputed into BiGRU network to extract deeper features. Finally, the attention mechanism is introduced to highlight the target sentences and achieve the classification of film review texts. Experiments have proved that on the IMDB and SST data sets, the movie review sentiment classification model based on BiGRU and attention model has achieved better accuracy than other models.
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.