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7,000 | Please write an abstract with title: RENT—Repeated Elastic Net Technique for Feature Selection, and key words: Feature extraction, Stability criteria, Predictive models, Training, Training data, Task analysis, Data models. Abstract: Feature selection is an essential step in data science pipelines to reduce the complexity associated with large datasets. While much research on this topic focuses on optimizing predictive performance, few studies investigate stability in the context of the feature selection process. In this study, we present the Repeated Elastic Net Technique (RENT) for Feature Selection. RENT uses an ensemble of generalized linear models with elastic net regularization, each trained on distinct subsets of the training data. The feature selection is based on three criteria evaluating the weight distributions of features across all elementary models. This fact leads to the selection of features with high stability that improve the robustness of the final model. Furthermore, unlike established feature selectors, RENT provides valuable information for model interpretation concerning the identification of objects in the data that are difficult to predict during training. In our experiments, we benchmark RENT against six established feature selectors on eight multivariate datasets for binary classification and regression. In the experimental comparison, RENT shows a well-balanced trade-off between predictive performance and stability. Finally, we underline the additional interpretational value of RENT with an exploratory post-hoc analysis of a healthcare dataset. |
7,001 | Please write an abstract with title: A perturbation theory on statistical quantization effects in fixed-point DSP with non-stationary inputs, and key words: Quantization, Digital signal processing, Least squares approximation, Arithmetic, Digital systems, Adaptive filters, Statistical distributions, Finite impulse response filter, Nonlinear systems, Steady-state. Abstract: A quantitative characterization of statistical quantization effects in a discrete-time digital system is derived as a function of fixed-point data types. The analysis is based on a perturbation theory approach which assumes the quantization noise is a small deviation from the ideal characteristics and that the system does not contain decision-error propagation. The theory works for both linear and nonlinear digital systems with either stationary or nonstationary inputs. The approach is applied to an LMS adaptive filter in both the transient and steady state periods. |
7,002 | Please write an abstract with title: Capacity development by implementation of PLC trainings towards Industry 4.0, and key words: Training, Temperature measurement, Seminars, Temperature distribution, Schedules, Computer architecture, Benchmark testing. Abstract: The Asean Factori 4.0 project aims to contribute for the enhancement of education in the field of industrial automation in 6 Asian universities from Thailand, Laos and Cambodia. Specialists from 3 EU universities from France and Bulgaria have participated in the project. A Centre of excellence consisting of 6 distributed PLC labs will be developed in the 6 Asian universities. Specialists from the University of Ruse are involved in the development of two of the six PLC labs, as well as all training resources. The main objectives and the partner consortium of the project are presented in this paper. The organisation of the intensive ten days training for the Asian staff is analysed: programme, teaching schedule and materials. The pedagogical benchmark was designed based on the Beckhoff and Eaton-Moeller brands of PLCs and includes all learning sources for an intensive training course. The hardware architecture and the necessary software of the benchmark were specified in order to meet the expected functionalities and learning outcomes and is described in the paper. The training of the Asian staff is based on practical examples and aims the acquisition of new knowledge and skills about different types of PLCs, the architecture, characteristics and methods of programming of PLCs. The training is focused on a basic technical tool for automation of technological processes and industrial networks. Conclusions and planned future work in the project are presented in the paper. |
7,003 | Please write an abstract with title: Low-temperature soot incineration of diesel particulate filter using remote nonthermal plasma induced by a pulsed barrier discharge, and key words: Incineration, Filters, Plasma temperature, Diesel engines, Automotive engineering, Combustion, Carbon dioxide, Ceramics, Plasma density, Energy efficiency. Abstract: Regulations regarding automotive diesel engine emissions become more severe every year, and it is difficult to meet the requirements with only combustion improvement techniques. More effective post-processing technology is desired especially for particulate matter (PM), such as carbon soots. Although the use of a ceramic diesel particulate filter (DPF) is now a leading technology for PM removal, the problem exists for the soot removal or regeneration at low temperature, especially at cold start and engine brake operation. In the present study, a regeneration of a DPF is investigated using indirect or remote nonthermal plasma (NTP) method. The NTP-treated air is injected into exhaust gas, and the NO is oxidized to NO/sub 2/. The induced NO/sub 2/ and activated oxygen species are used to incinerate carbon soot deposited on the DPF. It is confirmed experimentally that the pressure drop decreases when the plasma is turned on and the regeneration of the DPF is possible at the low temperature of 300/spl deg/C. The specific energy density is 22 Wh/m/sup 3/ (= 78 J/L). Although the condition of the NTP is not optimized in the present study, further improvement is required in the energy efficiency. |
7,004 | Please write an abstract with title: Characterization and simulation of photodetector sensing elements based-on heterojunction and heterodimensional devices, and key words: Photodetectors, Heterojunctions, Spontaneous emission, Optical devices, Dark current, Current measurement, Integrated optoelectronics, Electron mobility, Indium gallium arsenide, Time factors. Abstract: In this paper, we deal with the properties of a family of optical devices based on heterojunction and heterodimensional structures, and investigate their main performance criteria (in terms of modelling, dark current, light response, high-speed measurements). The implementation of a device architecture that relies on structures of different physical dimensions has the purpose of maximising the physical benefits of lower dimensional systems. The advantages of electron transport in a reduced dimensional system make these devices good candidates for integrated optoelectronic applications. The performance of this type of device was simulated using an ISE-TCAD simulator. Physical models used include Shockley-Reed-Hall recombination, Auger recombination, field-dependent mobility, thermionic effects, heterointerfaces and surface density of state-effects, considering also the specific quantized nature of the two-dimensional electron gas. We compared the simulated characteristics of AlGaAs/GaAs-based devices with measurements and obtained a good match between our simulation results and measurement data. The results show that the chosen physical model applied using the 2D device simulation is viable for the study and development of device performances. We also took into account photoresponse measurements of AlGaAs and InGaAs materials based devices, in order to evaluate the behavior of devices under light. High speed time response measurements are given in the last part of this paper that indicate higher peak transient response is achieved in the presence of higher 2DEG density, without degradation of temporal behavior. Microwave measurements taken in the frequency domain conclude the picture of characterizations, allowing us to extract the elements of the equivalent circuit. |
7,005 | Please write an abstract with title: Numerical Solutions for Electric Field Lines and Breakdown Voltages in Superjunction-Like Power Devices, and key words: Numerical models, Insulators, Impact ionization, Computational modeling, Optimization, Design automation. Abstract: An accurate method for the evaluation of breakdown voltages (BVs) in the superjunction-like (SJ-like) power devices is presented. This brief investigates the conventional SJ (c-SJ), the insulator pillar SJ (I-SJ), and the high-permittivity ($\text{H}{k}$ ) structures. Based on the numerical calculations of the electric field line (EFL) distribution, the electric field profiles along the EFLs can be accurately obtained. This ensures the accurate determination of the impact ionization integrals and BV. The technology computer-aided design (TCAD) simulations confirm the validity of the proposed method. The proposed method could be of great significance for the optimization of the specific ON-resistance (${R} _{ \text {ON,sp}}$ ) and could provide a better understanding of the SJ-like power devices. |
7,006 | Please write an abstract with title: Electrical analysis of NRD components by a novel eigenvalue-tracking technique, and key words: Dielectrics, Integral equations, Transmission line matrix methods, Propagation constant, Resonant frequency, Integrated circuit technology, Eigenvalues and eigenfunctions, Resonance, Slabs, Periodic structures. Abstract: This paper presents a novel technique for the calculation of the proper modes of 2D or 3D nonradiating dielectric (NRD) components for mm-wave applications. The novelty of this technique is the use of an integral equation method, in conjunction with a special algorithm for solving the resulting homogeneous matrix problem. This algorithm consists in the tracking of the matrix eigenvalues in the complex plane, when varying either the frequency or the mode propagation constant, and proved to be faster and more reliable than standard approaches, based on the direct search of the determinant zeros. Its effectiveness is demonstrated through the determination of the dispersion diagram of an NRD guide and the calculation of the resonance frequencies of a dielectric resonator. |
7,007 | Please write an abstract with title: Band model approach for the magnetic stiffness within ferromagnetic thin films, and key words: Magnetic films, Magnetization, Transistors, Magnetic anisotropy, Perpendicular magnetic anisotropy, Surface treatment, Surface waves, Magnetic domains, Magnetic properties, Magnetic resonance. Abstract: The magnetic stiffness within ferromagnetic thin films, considered as a tendency of the film to be homogeneous with respect to the distribution of magnetization directions, is defined on the basis of the domain structure as well as of the spin wave theory. The transversal stiffness parameter in thin films is calculated by means of the band model approach within a Hartree-Fock type of approximation. This parameter depends on the film thickness and, what is particularly interesting, on the surface effects. |
7,008 | Please write an abstract with title: A Wafer-scale Manufacturing Pathway for Fine-grained Vertical 3D-IC Technology, and key words: Performance evaluation, Semiconductor device modeling, Industries, Solid modeling, Three-dimensional displays, Manufacturing processes, Integrated circuit interconnections. Abstract: Three-dimensional integrated circuits (3D-ICs) provide a feasible path for scaling CMOS technology in the foreseeable future. IMEC and IRDS roadmaps project that 3D integration is a key avenue for the IC industry beyond 2024. They project that some form of 3D-IC technology based on nanosheets/nanowires is likely to become mainstream soon. SkyBridge-3D-CMOS (S3DC) is one among the first vertical nanowire-based fine-grained 3D-IC directions which offers paradigm shift in technology scaling as well as design. Rather than die-die and layer-layer stacking, S3DC's core aspects, from device to circuit style to interconnect, are co-architected in a 3D fabric-centered manner building on a uniform 3D nanowire template. Nanowire-based 3D-IC technologies such as S3DC solve most of the traditional scaling issues of 2D-CMOS but present new manufacturing challenges because of their complex 3D geometry. Therefore, for these directions to become mainstream, a robust wafer-scale manufacturing pathway that addresses these challenges is vital. In this paper, we propose a wafer-scale manufacturing pathway aimed at developing and optimizing the manufacturing process flows of S3DC. Using physics-driven virtual process integration functionalized with design and process parameters, we obtained realistic 3D structures for all the underlying IC elements and finally combined them to build 3D standard cells in S3DC. Electrical characterization of resultant structures using process and device simulations were performed while considering the material properties and nanoscale physics effects. Circuit-level simulations accounting for device behavior using SPICE-compatible compact model and circuit interconnect parasitics were carried out to study the impact of variations in process steps such as patterning, lithography, etch, deposition on device and interconnect performance. Our bottom-up simulation results indicate that the proposed pathway is robust enough to be adopted for large-scale production thus paving the way for wide-spread adoption of vertical fine-grained 3D-IC technologies. |
7,009 | Please write an abstract with title: Initial Development of Low-cost Custom Spherical Measurement Range, and key words: Antenna measurements, Codes, Microcontrollers, Transforms, Programmable logic arrays, Three-dimensional printing, Frequency division multiplexing. Abstract: Initial development of a low-cost table-top spherical antenna measurement range is discussed. The structure of the system is fabricated with FDM 3D printing using PLA. Commercial off-the-shelf stepper motors and microcontrollers are used to achieve the 3-axes of control (ϕ, θ, and χ) for spherical scanning. The scan radius is made adjustable through the use of linear actuators. The fabricated range is tested using two similar wideband TEM horns and raw measured data is presented. For processing, a basic spherical near-field to far-field transform code is developed and validated using simulated data. Furthermore, the code is used for analysis of the error introduced by using a truncated measurement sphere with a relatively low-directivity AUT. Thoughts on improvements to both the fabricated and developed code are given. |
7,010 | Please write an abstract with title: Multichannel Signal Denoising Using Multivariate Variational Mode Decomposition With Subspace Projection, and key words: Noise reduction, Signal processing algorithms, Oscillators, Data mining, Wavelet transforms, Cost function. Abstract: This paper describes a novel multichannel signal denoising approach based on multivariate variational mode decomposition (MVMD). MVMD is the extended version of the variational mode decomposition (VMD) algorithm for multichannel data sets. Unlike previous MEMD (multivariate empirical mode decomposition)-based denoising methods, the proposed scheme not only has a precise mathematical framework but also can better align the common frequency modes of the signals. Therefore, it has good robustness for non-stationary signals with low SNR. Based on the similarity measurement between the probability density function (pdf) of the input signal and each mode by Hausdorff distance(HD), the interval thresholding and partial reconstruction denoising of band-limited intrinsic mode functions (BLIMFs) are performed in the algorithm. Besides, to take advantage of the characteristics of channel diversity, the subspace projection method is used to further denoise the multivariable signals. We demonstrate the effectiveness of the proposed approach through results obtained from extensive simulations involving test (synthetic) and real-world multivariate data set. |
7,011 | Please write an abstract with title: Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection for Autonomous Driving, and key words: Three-dimensional displays, Object detection, Feature extraction, Laser radar, Correlation, Decoding, Head. Abstract: The strong demand of autonomous driving in the industry has led to vigorous interest in 3D object detection and resulted in many excellent 3D object detection algorithms. However, the vast majority of algorithms only model single-frame data, ignoring the temporal clue in video sequence. In this work, we propose a new transformer, called Temporal-Channel Transformer (TCTR), to model the temporal-channel domain and spatial-wise relationships for video object detecting from Lidar data. As the special design of this transformer, the information encoded in the encoder is different from that in the decoder. The encoder encodes temporal-channel information of multiple frames while the decoder decodes the spatial-wise information for the current frame in a voxel-wise manner. Specifically, the temporal-channel encoder of the transformer is designed to encode the information of different channels and frames by utilizing the correlation among features from different channels and frames. On the other hand, the spatial decoder of the transformer decodes the information for each location of the current frame. Before conducting the object detection with detection head, a gate mechanism is further deployed for re-calibrating the features of current frame, which filters out the object-irrelevant information by repetitively refining the representation of target frame along with the up-sampling process. Experimental results reveal that TCTR achieves the state-of-the-art performance in grid voxel-based 3D object detection on the nuScenes benchmark. |
7,012 | Please write an abstract with title: Smart Managerial Performance Appraisal System Based on the Quantitative Index and Wavelet Data Mining, and key words: Analytical models, Automation, Digital systems, Wavelet analysis, Appraisal, Data mining, Indexes. Abstract: This paper studies smart managerial performance appraisal system based on the quantitative index and Wavelet data mining. Data multiplication and division operations and rounding operations are realized simply and quickly through data shift operations, and with this initial setting, it has then brought breakthrough changes to the design of digital systems and greatly promoted the monolithic and automation of digital system design improves the design cycle. More importantly, the wavelet analysis model is integrated to help creating the smart managerial performance appraisal system. Through the comparison simulation, the satisfactory performance is reflected. |
7,013 | Please write an abstract with title: Feasibility analysis of hexaphenoxy cyclotriphosphazene flame retardant for inhibiting electrical tree growth of epoxy resin, and key words: Heating systems, Insulation, Thermal decomposition, Raman scattering, Epoxy resins, Graphite, Flame retardants. Abstract: Epoxy resin (EP) with excellent electrical and mechanical properties was widely employed as the insulation structure in high-voltage (HV) power equipment. Due to its ultra-high electric field, the inevitable electrical tree aging phenomenon often occurs in the insulation materials, which seriously threatens the safe operation of power equipment. A flame retardant such as hexaphenoxy cyclotriphosphazene (HPCTP) can reduce the intensity of heat release during the thermal decomposition of epoxy groups and consume free radicals generated by the reaction of epoxy molecular chains with oxygen, which provides a potential possibility to inhibit the tree growth in the insulation materials. In this work, the electrical treeing characteristics of the HPCTP/EP composites under high electric field was studied. It's confirmed that the tree growth of HPCTP/EP composites was significantly inhibited by HPCTP. The tree initiation voltage and voltage life of the HPCTP/EP composites are both higher than those of the pure EP. The carbonization in the tree channel was effectively inhibited by HPCTP, which weakened the electric field at the tip of the tree channel, thereby prolonging the voltage life of the HPCTP/EP composites. |
7,014 | Please write an abstract with title: Linking Tacit Knowledge in the Pediatric Pain e-Mail Archives and Explicit Knowledge in PubMed, and key words: Joining processes, Pain, Yarn, Pediatrics, Electronic mail, Discussion forums, Continents, Web server, Computer science, Psychology. Abstract: The goal of this research is to provide a means by which the tacit knowledge in an e-mail archive can be browsed in an organized manner and linked directly to the explicit knowledge found in PubMed. The Pediatric Pain Mailing List (PPML) is an international Internet-based forum for informal discussion of any topic related to pain in children. There are now over seven hundred members, including clinicians, researchers and patients from at least forty countries on six continents. Currently, the archive contains more than ten thousand messages. This paper reports on SOM-based approaches to the taci-knowledge organization and an MMTx-based approach that links the e-mail threads directly into the MeSH hierarchy and links to PubMed. |
7,015 | Please write an abstract with title: An energy efficient transmitted-reference scheme for ultra wideband communications, and key words: Energy efficiency, Ultra wideband communication, RAKE receivers, Multipath channels, Fading, Ultra wideband technology, Pulse modulation, Amplitude modulation, Performance analysis, Analytical models. Abstract: Transmitted-reference (TR) receivers represent a low complexity alternative to RAKE receivers, which are widely used in ultra wideband (UWB) communications. Known TR schemes are not very energy efficient, since two pulses represent one bit value only. Therefore, we present a TR pulse interval amplitude modulation (PIAM) scheme which reduces the required energy per bit and a low complexity receiver structure for TR PIAM. We investigate the performance of TR 4PIAM analytically and by means of simulation and show that higher modulation alphabets can be adapted easily. Moreover, we show that there exists an optimal correlation length for transmission over multipath channels. |
7,016 | Please write an abstract with title: Microstrip tunnel-diode amplifiers using matched beam-lead diode pairs, and key words: Microstrip, Diodes, Circuits, Dynamic range, Radiofrequency amplifiers, Phased arrays, Structural beams, Switches, Noise figure, Laboratories. Abstract: A unique microstrip tunnel diode amplifier has been constructed to permit the direct comparison of push-pull and parallel operation using beam lead diodes. For narrow band operation the parallel arrangement provides equal or superior dynamic range. |
7,017 | Please write an abstract with title: Predicting Mind-Wandering with Facial Videos in Online Lectures, and key words: Webcams, Computational modeling, Conferences, Education, Predictive models, Data collection, Physiology. Abstract: The importance of online education has been brought to the forefront due to COVID. Understanding students’ attentional states are crucial for lecturers, but this could be more difficult in online settings than in physical classrooms. Existing methods that gauge online students’ attention status typically require specialized sensors such as eye-trackers and thus are not easily deployable to every student in real-world settings. To tackle this problem, we utilize facial video from student webcams for attention state prediction in online lectures. We conduct an experiment in the wild with 37 participants, resulting in a dataset consisting of 15 hours of lecture-taking students’ facial recordings with corresponding 1,100 attentional state probings. We present PAFE (Predicting Attention with Facial Expression), a facial-video-based framework for attentional state prediction that focuses on the vision-based representation of traditional physiological mind-wandering features related to partial drowsiness, emotion, and gaze. Our model only requires a single camera and outperforms gaze-only baselines. |
7,018 | Please write an abstract with title: Verifiable Decentralized Access Control for Distributed Databases, and key words: Authorization, Data privacy, Distributed ledger, Distributed databases, Knowledge discovery, Fabrics, Encryption. Abstract: Ahstract- The traditional centralized database management mode brings security and privacy issues to user data. In this paper, we propose a verifiable distributed database access control (VDAC) scheme based on the ciphertext policy attribute-based encryption (CP-ABE) and decentralized ledger technology (DLT). In the VDAC scheme, CP-ABE is used to achieve fine-grained access authorization control on user data, and DLT is employed to publish authorization parameters and guarantee their immutability. Particularly, the decentralized authorization mechanism for distributed database is realized by using Hyperledger fabric platform. Comparison analysis shows that the VDAC scheme not only provides verifiable database access control, but also protects user privacy and system security. Experimental results demonstrate the efficiency and practicality of the VDAC scheme. |
7,019 | Please write an abstract with title: Methodology for Identification of Quality of clean-Cut surface for IS2062HR sheet metal blanking using Random Forest, and key words: Decision making, Metals, Surface fitting, Surface roughness, Entropy, Rough surfaces, Indexes. Abstract: In the instance of sheet metal blanking, poor cut-surface quality of a blanked surface might cause fit difficulties in the assembly. Due to the uneven surface, cracks may occur, resulting in a loss of surface quality and dimensional precision. The quality of clean-cut surface is investigated using four parameters: punch penetration, shear angle, fracture angle, and burr height are considered for the present study. The depth of punch penetration is gradually raised to identify where the crack starts. Shear angle, fracture angle, and punch penetration following punching, as well as burr height, are considered input factors. On the power press, the uni-punch tool is utilized as a cutting tool, and the processing material is IS2062HR sheet metal. The objective of this work is to use the surface roughness value to classify cut-surface quality into three categories for decision making on fit for assembly operation. To forecast the quality of cut surface, a classification model is created using the Random Forst Classifier method of the Machine Learning approach. The Gini and Entropy index method revealed that the model is 93 percent accurate. |
7,020 | Please write an abstract with title: Transfer Learning-Assisted Prognosis of Alzheimer's Disease and Mild Cognitive Impairment Using Structural-MRI, and key words: Neuroimaging, Magnetic resonance imaging, Transfer learning, Brain cells, Prediction algorithms, Convolutional neural networks, Alzheimer's disease. Abstract: Alzheimer's is a neurodegenerative disease that damages human brain cells and causes dementia. When the brain cells gradually deteriorate, it leads to the inability to carry out everyday activities. While conventional machine learning (ML) has been shown to be efficient in assisting with AD diagnosis, relatively few research have examined the effectiveness of deep learning and transfer learning in this difficult challenge. We assessed the possibility of early recognition and prediction of Alzheimer's disease (AD) using pre-trained transfer-learning algorithms on structural brain MRI. Advances in artificial intelligence are assisting in the enhancement of early detection of Alzheimer's disease. Using open-source neuroimaging data, researchers have been able to construct programs that help in Alzheimer's diagnosis and prognosis. The presented study is based on an effective technique of applying transfer learning to classify the structural MRI (s-MRI) Axial brain scans by fine-tuning a pre-trained convolutional neural network (CNN), ResNet50, and VGG-16. We have taken s-MRI Axial data from an online available data repository Alzheimer's Disease Neuroimaging Initiative (ADNI). We implemented pre-trained model namely CNN, VGG-16 and ResNet50 trained on brain s-MRI axial scans to classify them into three classes: Cognitive Normal (CN), Mild cognitive impairment (MCI), and Alzheimer's disease (AD). Experiments show that ResNet50 outperformed CNN and VGG-60 with an accuracy of 95.30% on brain MRI axial scan for accurate and early prediction of AD and the onset of MCI. |
7,021 | Please write an abstract with title: Fabrication of Cost-Effective Reduced Graphene Oxide Based Parallel Grids Embedded Dye-Sensitized Solar Mini-Modules, and key words: Fabrication, Electrolytes, Photovoltaic systems, Silver, Graphene. Abstract: Cost-effective, parallel grids embedded dye-sensitized solar mini-modules were fabricated successfully by utilizing reduced graphene oxide (rGO) and rGO-silver (rGO-Ag) nanocomposites as grid current collectors. The pure rGO grids embedded dye-sensitized solar mini-module showed a maximum power conversion efficiency of 4.10% with improved fill factor, circumvented iodide/triiodide electrolyte corrosion, and reduced the module power loss significantly. Electrochemical impedance spectroscopy studies revealed that the 1:1 wt% ratio rGO-Ag nanocomposite grids improved the module's electron diffusion length, carrier mobility and lifetime, and produced a higher open-circuit voltage (Voc) as compared with the pure silver grids in the dye-sensitized solar mini-module. |
7,022 | Please write an abstract with title: Evolutionary Game Theory-Based Optimal Scheduling Strategy for Heterogeneous Computing, and key words: Heterogeneous computing, resource scheduling, game optimization, Stackelberg. Abstract: With the development of intelligent applications, simply relying on traditional single type of computing unit cannot efficiently satisfy diverse cloud requirements. The emergence of heterogeneous computing can efficiently achieve the adaptation of these intelligent applications by using different types of processing units such as Graphics Processing Unit (GPU) and Field Programmable Gate Array (FPGA). However, the trade-off between profit and costs in the process of scheduling heterogeneous computing resources is also an issue worthy of attention. To address this challenge, this work establishes a heterogeneous computing resource scheduling model based on Stackelberg differential game, which includes three roles Computing Power Trading Platforms (CPTPs), Heterogeneous Computing Service Providers (HCSPs), and Heterogeneous Computing Application Providers (HCAPs). The objective is to maximize utility function of CPTPs and HCSPs subject to rental ratio, pricing strategy and energy consumption of resource scheduling, which has proved that there exists a Stackelberg Nash Equilibrium (NE) solution. The Support Vector Machine based on Artificial Fish (SVM-AF) is proposed to predict the access times of heterogeneous computing applications. In addition, the distributed iteration method and Cauchy distribution is adopted to optimize the computing price strategy and improve its convergence performance. The simulation results show that compared with other strategies, the proposed strategy can effectively improve computing revenue of user experience and while reducing energy consumption in the process of resource scheduling. |
7,023 | Please write an abstract with title: Approaches to the Research of the Effectiveness of Information Processes, and key words: Automation, Stochastic processes, Process control, Control systems, Mathematical models, Energy efficiency, Task analysis. Abstract: The article deals with issues related to the research of the effectiveness of purposeful information processes. Approaches to evaluating the effectiveness of purposeful information processes based on the use of deterministic and stochastic selecting functions are proposed. The statement of the problem of achieving the guaranteed probability of the goal is considered. |
7,024 | Please write an abstract with title: Carbon-Based THz Microstrip Antenna Design: A Review, and key words: Microstrip antennas, Microstrip, Antenna radiation patterns, Microwave antennas, Reflector antennas, Antennas, Receiving antennas, Wireless communication, Terahertz wave imaging. Abstract: Increasing demands for high-speed wireless communication have stimulated the development of novel optoelectrical devices. Typically, terahertz (THz) wave, is much advantageous because of its relatively high-resolution transportation and strong penetrability property. One of the electromagnetic devices, the antenna, plays a key role in future THz devices. However, there are few review publishments related to carbon-based THz microstrip antenna designs. In this article, we list the basic figure of merits for evaluating antennas. We also show the developing microstrip antenna structures. Importantly, we summarize the current progress of THz microstrip antennas using different dimensional carbon materials, such as carbon nanotubes, graphene, and carbon foams. This review will lay a solid foundation for carbon-based THz microstrip antenna design, and furthermore provide novel sights for other THz antenna designs. |
7,025 | Please write an abstract with title: Measuring and improving software process in China, and key words: Software measurement, Software performance, Software quality, Costs, Programming, Particle measurements, Application software, Manufacturing industries, Technology management, Frequency. Abstract: Measurement is an important facility to support effective and reasonable management. Software development has its inherent property of high-dependency on the personal capability of software engineers that causes the variance and instability of software processes: Therefore measurement for software process has long been a challenge. This paper discusses the major problems in software process measurement, presents an active measurement model (AMM) to support software process improvement (SPI). Based on the AMM, software organizations can establish adaptive measurement process and execute the measure just close-related the process goals, which focuses on their particular business environment. Subsequently, some methods of establishing the adaptive measurement process and the appropriate software process performance baseline to support higher level quantitative management are suggested. The application and implementation of AMM and the related methods is introduced in the end. These works were integrated in a toolkit called SoftPM, which was used widely in China. |
7,026 | Please write an abstract with title: A unified relocatable SVC for open-cast lignite mining in Turkey, and key words: Static VAr compensators, Reactive power, PSCAD, EMTDC, SPICE, MATLAB, DC-DC power converters, AC motors, DC motors, Mathematical model. Abstract: Design and implementation of a unified, relocatable static VAr compensator (SVC) meeting the reactive power compensation needs of various coal enterprises of Turkey for open-cast lignite mining are presented. Design and sizing of SVCs are based on mains data for all possible connection points, load bus data recorded in the field, monthly electric bills, and simulations carried out on PSCAD/EMTDC, SPICE, and MATLAB. In addition to standard ac/dc converter and motor tools used in the modeling of electric excavators, actual load characteristics obtained from data collected in the field by means of a data acquisition system have been processed in PSCAD/EMTDC to find out reactive power demand of each load bus, and to optimize sizing of the SVC within the power-factor penalty limits imposed by electricity authorities. The SVC component ratings have been based upon the suitability to all possible loads under worst operating conditions, thus making sure that they can be operated for different loading conditions, minimizing stock requirements, and inspection and maintenance costs. The implemented systems are flexible and extendable in order to meet the future needs of coal enterprises. |
7,027 | Please write an abstract with title: Non-invasive gastric motility monitor: fast electrogastrogram (fEGG), and key words: Monitoring, Frequency, Muscles, Stomach, Abdomen, Data mining, Dogs, Surface morphology, Data acquisition, Neurons. Abstract: We propose a new analysis method to extract the motility information from the electrogastrogram signal that has been recorded at a higher sampling rate than conventional approaches. This technique utilizes a 4th order Butterworth bandpass filter in extracting the 50-80 cycles per minute (cpm) activity that was previously noted to represent the spike activity range of the cutaneous signals of dogs. Receiver operating characteristics (ROC) analyses have been applied to the processed data to compare the detection performance of our fEGG technique to conventional approaches that use the slow wave as the reference. The area under the ROC curve for the fEGG study was found to be 0.961 while for the slow wave was 0.686. We offer our method as a complementary one to existing methods. |
7,028 | Please write an abstract with title: Case Study of How to Help Manufacturing Enterprises Obtain Loan Through Supply Chain Documents on Blockchain Platform, and key words: Finance, Companies, Supply chains, Economics, Technological innovation. Abstract: Recent years, it has produced one trend to update the traditional business with the developing internet thinking and technology. In order to build the industrial ecosphere, which can attract more related partners, many companies try to push the layout of the bulk supply chain platform based on blockchain technology. The papers studies how to make full use of supply chain documents in digital assets. Based on risk and economic analysis, it makes research on the key points in the processes and provides the control measures to push the project innovation in order to help enterprises to obtain loan. At last, it compares the differences before and after the implementation. It shows the validity of receipts, storage and industry finance effectiveness can be further improved after implementation. |
7,029 | Please write an abstract with title: Least mean square method for LVDT signals processing, and key words: Least mean squares methods, Signal processing, Signal processing algorithms, Acceleration, Sensor phenomena and characterization, Transducers, Demodulation, Spectral analysis, Prototypes, Digital signal processing. Abstract: This paper describes an innovative approach for position, velocity and acceleration estimation using traditional inductive sensors such as LVDTs. These transducers have been considered thanks to their diffusions and performances; however, the same algorithm can be applied to any other kind of AC-excited sensor. It overcomes typical limits of traditional processing techniques, such as coherent demodulation or spectral analysis, implementing a least mean squares estimation of interesting variables. Some preliminary simulations have been conducted to evaluate algorithm functionalities. A working prototype, designed around a low-cost DSP from TI, has been realized to perform real world tests. |
7,030 | Please write an abstract with title: End-to-End Task-oriented Dialogue System Using Knowledge Filter and Attention Memory Pointer, and key words: Knowledge engineering, Asia, Task analysis, Context modeling. Abstract: The end-to-end neural model provides a more robust solution to generate responses than the traditional pipe-line method in the task-oriented dialogue system. However, it is challenging to incorporate the proper knowledge into the gen-erated response, especially when there are substantially related knowledge tuples. This paper proposes a knowledge filter and an attention memory pointer to improve the task-oriented dia-logue model. Specifically, the model uses the knowledge filter to obtain the knowledge tuples most relevant to the keywords of dialog context and builds the knowledge vector. Besides, the task-oriented dialogue model usually needs to copy objects from the correct knowledge tuples to form the question's an-swer. We define an attention memory pointer to help the model choose the correct knowledge tuples. Finally, we conduct ex-periments on the In-Car Assistant dataset. The experimental results show that our model can generate more accurate re-sponses than baseline models in automatic and human evaluations. |
7,031 | Please write an abstract with title: Standard frequency and time signal transmissions from the republic observatory, Johannesburg, and key words: Time-frequency analysis, Standards, Oscillators, Observatories. Abstract: Deviations of frequencies and time signals are with respect to the weighted mean of six quartz oscillators, and time signals from WWV over 20-day intervals. A positive frequency deviation indicates that the frequency was high. A time deviation of 010 indicates that the time pulses were 0.010 second late on WWV while 990 indicates that they were 0.010 second early. A value of 46.3 milliseconds has been adopted for the propagation time of radio signals between Washington and Johannesburg. |
7,032 | Please write an abstract with title: Data clustering by ant colony on a digraph, and key words: Clustering algorithms, Ant colony optimization, Particle swarm optimization, Cadaver, Computer science, Software algorithms, Testing, DNA, Birds, Marine animals. Abstract: An adaptive data clustering algorithm based on ant colony (ant-cluster) is presented. Enlightened by the self-organizing behavior of ant society, we assign acceptance rates on the directed edges of a pheromone digraph in ant-cluster system. The pheromone on the edges of the digraph is adaptively updated by the ants passing it. Some edges with less pheromone are progressively removed under a list of certain thresholds in the process. Strong connected components of the final digraph are extracted as clusters. The performance of ant-cluster is compared with classical K-means clustering algorithm and ACO clustering algorithm LF in terms of clustering quality and efficiency on several real datasets and clustering benchmarks. Experimental results indicate that the ant-cluster is able to find clusters faster with better clustering quality and is easier to implement than K-means and LF. |
7,033 | Please write an abstract with title: High-Brightness Wavelength Stabilized Diode Lasers for Sensor Systems and Non-Linear Frequency Conversion, and key words: Two dimensional displays. Abstract: High-brightness wavelength stabilized diode lasers emitting between 750nm and 1100nm with output powers up to 15W for sensor applications such as biomedical imaging and spectroscopy as well as for non-linear frequency conversion will be presented. |
7,034 | Please write an abstract with title: Optimal parameter estimation in a landslide motion model using the adjoint method, and key words: Terrain factors, Mathematical model, Cost function, Velocity measurement, Parameter estimation, Friction. Abstract: This work proposes an optimal approach for parameter estimation in a landslide motion, based on the so-called adjoint method. The system is described by an extended sliding-consolidation model composed of an ordinary differential equation and 1D parabolic partial differential equation that represents landslide motion and pore pressure evolution respectively. The key feature of this model is pore pressure feedback, which regulates landslide motion and leads to coupling between both differential equations. Parameters to be estimated include the friction and dilatancy angle of the material. The objective functional for the optimal estimation is composed of: i) a cost function defined as the least square error between measurements and related simulated values, and ii) a product of Lagrange variables and system dynamics. A variational approach is applied to get the gradients of the cost functional with respect to parameters to be estimated and adjoint model. The cost functional is optimized, employing the steepest descent method to estimate parameters. Finally, the presented optimal estimation method is validated on a simulated test case. |
7,035 | Please write an abstract with title: A Lattice-based Method for Mining Frequent Weighted Itemsets Using Diffset, and key words: Runtime, Itemsets, Databases, Lattices, Data compression, Virtual reality, Fingerprint recognition. Abstract: Mining Frequent Weighted Itemsets (FWIs) is an important problem in the field of data mining. Itemsets have different importance depending on their values in practical applications. Aiming at the problems of low efficiency in traditional pattern mining, a new method of weighted Node lattice (WN-lattice) in mining FWIs is proposed. This method includes three phases:(1) Building WN-lattice structure solve the high data compression. (2) A Diffset-based strategy for the efficient computation of the supports of inter-transaction patterns is described. Some theorems for pruning redundant itemsets quickly based on these theorems. (3) Frequent Weighted Itemsets Lattice Algorithm (FWIL) is described for directly mining FWIs using WN-lattice. The experimental results show the proposed approach FWIL is more efficient and more those used previously in terms of runtime, especially when run on very large and dense weighed databases. |
7,036 | Please write an abstract with title: An adaptive acoustic echo cancellation without double-talk detection, and key words: Echo cancellers, Acoustic signal detection, Adaptive filters, Microphones, Finite impulse response filter, Speech, Distortion, Adaptive algorithm, Loudspeakers, Predictive models. Abstract: The paper proposes a novel adaptive echo cancellation (AEC) without double talk detection (DTD) that can work stably under all operating models. This breaks through the restriction that all of the adaptive echo cancellations must have DTD currently. The novel AEC is accomplished by injecting a low-level broadband random training signal to the far-end signal before transmission into the local room, modeling adaptively the echo path by taking the training signal as the reference signal, removing the speech signal interference of the adaptive algorithm by an adaptive prediction filter (APF), and modifying the distortion of the reference signal due to the APF by a compensation filter (CPF). The computer simulations confirm the AEC without DTD can provide excellent echo cancellation effect under all operating models. |
7,037 | Please write an abstract with title: A Large Collection of Sentences Read Aloud by Vietnamese Learners of Japanese and Native Speaker's Reverse Shadowings, and key words: second language learning, foreign accent, shadowing, comprehensibility, shadowability, GOP, DTW. Abstract: The main objective of language learning is to acquire good communication skills in the target language. From this viewpoint, the primary goal of pronunciation training is to become able to speak in an intelligible-enough or comprehensible-enough pronunciation, not a native-sounding one. However, achieving such pronunciation is still not easy for many learners mainly because of their lack of opportunity to use the language they learn and to receive some feedbacks on intelligibility or comprehensibility from native listeners. In order to solve this problem, the authors previously proposed a novel method of native speakers' reverse shadowing and showed that the degree of inarticulation observed in native speakers' shadowings of learners' utterances can be used to estimate the comprehensibility of learners' speech. One major problem in our previous research however, was that the experiment was done on a relatively small scale; the number of learners was only six. For this reason, in this study, we carried out a larger collection of Japanese utterances read aloud by 60 Vietnamese learners and Japanese native speakers' shadowings of those utterances. An analysis of the subjective ratings done by the native speakers implies that some modifications we made from our previous experiment contribute to making the framework of native speakers' reverse shadowing more pedagogically effective. Further, a preliminary analysis of the recorded shadowings shows good correlations to listeners' perceived shadowability. |
7,038 | Please write an abstract with title: A 100 nm CMOS technology with "sidewall-notched" 40 nm transistors and SiC-capped Cu/VLK interconnects for high performance microprocessor applications, and key words: CMOS technology, Threshold voltage, Dielectrics, Lithography, Boron, Dry etching, MOS devices, Annealing, Manufacturing, Random access memory. Abstract: A 40 nm CMOS transistor, an ultra high density 6T SRAM cell, and 10-level Cu interconnects and very-low-k (VLK) dielectrics for high performance microprocessor applications are presented. Key process features are the following: (1) High-NA 193 nm photolithography with phase shift mask and optical proximity correction (OPC) allows 40 nm gate length and the smallest 6T SRAM cell (<1 /spl mu/m/sup 2/). (2) A unique transistor feature which is referred to as "sidewall-notched gate" enables an optimal pocket implant placement and suppresses variations of the notch width much better than poly-notched gate structure. (3) 1.1 nm nitrided oxide (1.9 nm inversion T/sub ox/) is used to achieve high drive current, and the thermal budget is reduced to suppress the boron penetration. (4) SiC-capped Cu/SiLK structure in 0.28 /spl mu/m pitch metal 1-4 layers realizes k/sub eff/ of 3.0. |
7,039 | Please write an abstract with title: Incremental communication for multilayer neural networks in a field programmable gate array, and key words: Multi-layer neural network, Neural networks, Intelligent networks, Field programmable gate arrays. Abstract: A neural network is a massively parallel distributed processor made up of simple processing units known as neurons. These neurons are organized in layers and every neuron in each layer is connected to each neuron in the adjacent layers. This connection architecture makes for an enormous number of communication links between neurons. This is an issue when considering a hardware implementation of a neural network since communication links requires costly hardware space. To overcome this space problem incremental communication for multilayer neural networks has been proposed. Incremental communication works by only communicating the change in value between neurons as opposed to the entire magnitude of the value. This allows for the values to be represented with a fewer number of bits, and thus communicated with narrower communication links. To validate and analyze this technique a neural network is designed and implemented using both an incremental and traditional communication approach. |
7,040 | Please write an abstract with title: Effect of LPG bending and its application in fiber accelerometer, and key words: Accelerometers, Capacitive sensors, Optical fiber theory, Optical fibers, Refractive index, Optical fiber devices, Optical fiber sensors, Stress, Fiber gratings, Absorption. Abstract: We discovered that the transmission spectra of bending long period fiber gratings (LPGs) exhibit a splitting of loss peaks. This phenomenon allows LPGs can be used as the strain sensors and the accelerometer. |
7,041 | Please write an abstract with title: ATTL: An Automated Targeted Transfer Learning with Deep Neural Networks, and key words: Training, Measurement, Adaptation models, Satellites, Machine learning algorithms, Transfer learning, Neural networks. Abstract: Success of machine learning algorithms hinges on access to labeled dataset. Obtaining a labeled dataset is an expensive, challenging and time-consuming process, leading to the development of transfer learning (TL) methodology. TL incorporates gained knowledge from a previously trained source model into specific yet similar task models with limited data domain coverage. In this paper, we propose an automated targeted transfer learning (ATTL) method to resolve the transferability between source and target with minimal data requirements. The ATTL method decides how much target data is essential for model training, along with selected source data, to obtain the skateholder's specified performance metrics. The ATTL framework optimizes the system to select minimal target data based on two approaches: combinatorial coverage and adaptive selection methodology, along with specific source data for fine-tuning given a pre-trained source model. We evaluated the ATTL method on the Kaggle's ‘planes in satellite imagery’ dataset and the results identified that acquiring a small number of intentionally well-chosen samples from the target environment can achieve model performance of 97% in comparison to the baseline transfer learning accuracy of 92%. |
7,042 | Please write an abstract with title: Speed sensorless direct torque control implementation in a current source inverter fed induction motor drive, and key words: Torque control, Inverters, Induction motor drives, Rotors, Stators, Current measurement, Electrical resistance measurement, Sensorless control, Voltage, Electromagnetic measurements. Abstract: In the paper one speed sensorless direct torque control (DTC) implementation in a current source inverter (CSI) fed induction motor drive is proposed. DTC of a CSI fed induction motor drive involves the direct control of the rotor flux linkage and the electromagnetic torque by applying the optimum current switching vectors. For sensorless control of the drive, an improved estimator is applied using stator voltages and currents. The stator current, voltage and resistance are not measured, but determined by a reconstruction from DC link measurements and the inverter switches states. This reduces the count of the sensors in the drive since the inputs for the flux estimator are reconstructed motor voltage and current obtained from the measured DC link values. An EMS offset estimator using simple technique based on the knowing states of the inverter switches compensates the offset of the pure integrator in the flux estimator. The angle of the rotor flux space vector, needed for the switching table, is determined from the referred rotor flux values and motor parameters used in the control algorithm are only the stator resistance and the transient inductance. Experiments are provided to confirm the performance of the proposed control algorithm. |
7,043 | Please write an abstract with title: Underwater Target Detection Method Based on Third Party Information Transfer Learning, and key words: Object detection, Correlation, Feature extraction, Knowledge based systems, Robots, Mechatronics, Electronic mail. Abstract: The complex underwater environment leads to a small number of samples and a serious lack of target information. To solve the above problems, this paper proposes an underwater target detection method based on third party information transfer learning (TITL). Firstly, the method obtains the targets feature description from the knowledge base as third-party information. Using the third-party information and target information fusion, constitute a new target domain. Solved the problem of low detection accuracy caused by insufficient target data. Secondly, according to the uneven distribution of underwater image features, this method introduces the feature distribution difference adaptive principle into integrated migration learning. This method reduces the time of feature mapping and ensures the accuracy of migration learning. Experimental results show that the algorithm is effective in the Underwater Target dataset compared with existing algorithms. |
7,044 | Please write an abstract with title: Distributed event-triggered control for frequency restoration in islanded microgrids with reduced trigger condition checking, and key words: Time-frequency analysis, Frequency estimation, Resilience, Reliability, Bandwidth, Automatic frequency control, Transient analysis. Abstract: For islanded microgrids (MGs), distributed control is regarded as a preferred alternative to centralized control for the frequency restoration of MGs. However, distributed control with successive communication restricts the efficiency and resilience of the control system. Towards this end, this paper proposed a distributed event-triggered control strategy for the frequency secondary control in islanded MGs. The proposed event-triggered control is Zeno behavior free and enables each DG update and propagate its state to neighboring DGs only when specific "event" occurs, which significantly reduces the communication burden. Compared with the existing event-triggered control, a trigger condition checking period of the proposed event-triggered control is provided to reduce the computation burden when checking the trigger condition. Furthermore, using the aperiodicity and intermittent properties of the communication, a simple detection principle is proposed to detect and isolate the compromised communication links in a timely and economic fashion, which improves the resilience of the system against FDI attacks. Finally, the control effectiveness of proposed control scheme is validated by the simulation results of the tests on a MG with 4 DGs. |
7,045 | Please write an abstract with title: Personality Dimensions Classification with EEG Analysis using Support Vector Machine, and key words: Electroencephalography, Support vector machines, Discrete wavelet transforms, Signal analysis, Feature extraction, Databases, Brain modeling. Abstract: Personality is the fundamental thing that forms the behavioral tendencies of each individuality in a situation. A common model used to describe personality is the big five personality that divides personality traits into five dimensions of neuroticism, extraversion, openness, agreeableness, and conscientiousness. Personality assessment through physiological signals offers objectivity and reliability of the test results due to the minimal role of test takers in the examination process. One widely recommended approach is signal-based analysis of electroencephalography (EEG). The EEG signal feature of the ASCERTAIN public database was extracted using discrete wavelet transform (DWT) and was classified using support vector machine (SVM) to determine personality dimensions. The results showed better performance compared to the application of other techniques on the same dataset with 69% and 75.9% accuracy to determine extraversion and neuroticism level, respectively. However, this accuracy still needs to be improved to generate reliable model. Increased data variability can be useful for understanding brain dynamic activity per individual. |
7,046 | Please write an abstract with title: Tiny Reservoir Computing for Extreme Learning of Motor Control, and key words: Motor drives, Magnetic flux, Torque, Magnetic field measurement, Artificial neural networks, Reinforcement learning, Reservoirs. Abstract: The electromechanical system of an electric machine controller represents a complex non-linear system that needs to adapt itself continuously over time, since factors as component aging and thermal derating tend to modify its behavior and performance. Algorithms based on Neural Networks (NN), and in particular Recurrent NN (RNN), are expected to improve the motor drive, due to their ability to approximate complex non-linear systems, and to cope with the time-varying nature of signals. This paper proposes a novel control technique which extends the Field Oriented Control (FOC) algorithm by means of Extreme Learning Machine (ELM) and Reservoir Computing (RC). In particular, we introduce a specifically developed NN, named Semi Binary Deep Echo State Networks (SB-DESN), to achieve good control accuracy with low complexity. This allows its deployment into cheap micro-controllers characterized by severe memory, computational, and power consumption constraints. The peculiar property of SB-DESN i.e., a fixed and predictable training complexity, makes it well suited for adoption into Reinforcement Learning on micro-controllers to ensure the continuous adaptability of the control over the time. Beyond the use of SB-DESN for speed, torque, and magnetic flux control, we propose a novel complexity optimization based on sparsity properties of inter-reservoir matrices, which reduces the memory footprint up to a factor 3.7 and the computational complexity up to a factor 2. This corresponds to a SB-DESN with only 2.5kB of memory footprint and an inference time of 20µs on STM32H7, which allows its deployment into mass market FOC solution. |
7,047 | Please write an abstract with title: 2003 IEEE PES General Meeting Call for Papers, and key words: Power markets, ISO, Power generation, Power engineering, Electricity supply industry deregulation, Power transmission lines, Surge protection, Costs, Electricity supply industry, Vehicles. Abstract: We describe an adaptive game representation of a deregulated power market consisting of an independent system operator (ISO) and power generators (players) who submit their offers to the ISO in the form of curves. The power generators do not know the costs, the offers, or the payoffs of their competitors and, therefore, they use an adaptive learning tool to compensate for their lack of knowledge in trying to maximize their profit. The ISO purchases energy from the generators, starting from the more economical offer in order to cover the electricity demand. Sequential iteration of the game for different numbers of participants and with varied adaptation and reaction capabilities are conducted in order to study the impact on spot price convergence and volatility, and the corresponding cost for the ISO. After repeated runs of the simulation model, many interesting phenomenon have been observed regarding the spot price behavior and the stability of the market. |
7,048 | Please write an abstract with title: An ontology-based framework for dynamic resource management in ubiquitous computing environments, and key words: Ontologies, Resource management, Ubiquitous computing, Vehicle dynamics, Middleware, Uncertainty, Semantic Web, Vehicles, Technology management, Actuators. Abstract: Ubiquitous computing applications are supported by sophisticated middleware components enabling dynamic discovery, invocation and management of resources, as well as reasoning in cases of uncertainty. This paper advocates semantic Web technologies as primary vehicles to achieve dynamic management of resources in ubiquitous computing infrastructures and services. We introduce a framework for implementing ubiquitous computing services comprising a large number of sensors and perceptive interfaces, emphasizing the role of knowledge bases for dynamic registration and invocation of resources. We present the use of ontology-based mechanisms for controlling sensors and actuators. Moreover, we describe the implementation of a knowledge base server that can leverage different ontology management systems, while also exposing a host to different client access interfaces. The introduced framework has been exploited in implementing real prototype ubiquitous computing services, which we also outline in the paper. |
7,049 | Please write an abstract with title: Electrically pumped SiGeSn microring lasers, and key words: Germanium, Laser excitation, Heat sinks, Substrates, Pump lasers, Strain, Photonics. Abstract: We report on electrically pumped SiGeSn microring lasers, strain relaxed by means of undercutting the underlying germanium virtual substrate. Opening of the gain stack in the middle of the disks allows additional strain relaxation while maintaining adequate heat sinking to the substrate. |
7,050 | Please write an abstract with title: One-dimensional photonic crystal: low noise light generation, and key words: Photonic crystals, Noise generators, Optical noise, Geometrical optics, Nonlinear optics. Abstract: Summary form only given, as follows. Simple geometries, such as one-dimensional photonic crystals, exhibit a great number of interesting effects in the classical and quantum optical domains. An overview of recent results is presented. In particular a discussion on low noise light generation with non-classical, nonlinear interaction is presented. |
7,051 | Please write an abstract with title: Limitations of Low PDL All-Fiber Large Band Fabry-Perot Filters, and key words: Page description languages, Fabry-Perot, Fiber gratings, Filters, Bragg gratings, Optical fiber polarization, Birefringence, Fiber lasers, Chirp modulation, Optical control. Abstract: Limitations of Fabry-Perot filters consisting of superimposed chirped fiber Bragg gratings in terms of PDL and FSR variations are addressed. FSR uniformity of ±3% and low PDL were attained with finesse up to 80. |
7,052 | Please write an abstract with title: Network Fault Tolerance by Means of Diverse Physical Layers, and key words: Wireless communication, Analytical models, Redundancy, Fault tolerant systems, Wires, Physical layer, Dynamic scheduling. Abstract: Wired networks are deployed in scenarios requiring the highest levels of performance in terms of reliability and timeliness. Unfortunately, broken wires might permanently compromise the network operation unless fault tolerance mechanisms are in place. Fault tolerance is commonly achieved by replicating the wired network components, but this paper examines the use of a wireless backup network, since the wireless physical layer (PHY) is not expected to display permanent failures due to broken wires. Two mechanisms at medium access control (MAC) level are presented to take advantage of the wireless backup network: one allocating redundancy statically and one dynamically. Without loss of generality, redundancy is applied using the standard mechanisms from IEEE 802.3 (Ethernet) and IEEE 802.11 (Wi-Fi). The performance increase added by the backup network is studied both analytically and by simulation, showing considerable improvements in a very compromised midsize wired network. |
7,053 | Please write an abstract with title: E-Challan Automation for RTO using OCR, and key words: Integrated optics, Law enforcement, Image processing, Prototypes, Production, Cameras, Optical imaging. Abstract: Diligent Traffic Enforcement is a major problem throughout India, often focusing on corruption and abuse; is the subject of major changes initiated by senior management of all traffic police institutions in India. Therefore, this paper proposes an effective e-challan production strategy using OCR (Optical Character recognition) where the challan ends using the online application. Scanning different number plates and downloading facts from the database and producing E-Challan. The E-Challan is a web platform that provides various types of support for monitoring and managing the traffic penalties and it also helps the users to overcome the problems that they face while paying for their challan during the traffic time. The E-challan Application is the interaction between HD Cameras and drivers with the use of an online platform. The driver who will breach the traffic rule, vehicle's number plate snapshot is captured automatically by the HD Camera located near a traffic light and traffic area through Image Processing technology and Artificial Intelligence, the software will automatically detect the vehicle owner for the penalty and then apply the suitable penalty against the vehicle owner in their account. With the help of this online prototype, the challan system becomes easy for the users by keeping it online. |
7,054 | Please write an abstract with title: Quantum Prescription of Electron Energy Loss Spectroscopy in Crystalline Films, and key words: Atomic measurements, Spectroscopy, Energy loss, Electric potential, Films, Quantum mechanics, Metals. Abstract: A quantum mechanical model is used to study the electron energy-loss spectroscopy (EELS) of crystalline noble metal films, which shows intrinsic features associated with their crystallographic orientation. Within the random-phase approximation, we employ a 1-D potential across the film that captures the main features of the electronic band structure of different facet orientation, and then accounting for the corresponding electron-spill out and the atomic-plane corrugation. Furthermore, we examine the role of the vertical transitions among quantum well states, which are related to the in-plane effective mass, which is typically used to fit the parabolic electron bands at the Fermi level. |
7,055 | Please write an abstract with title: A parametric study of thermal effects on the reliability of RF MEMS switches, and key words: Parametric study, Radiofrequency microelectromechanical systems, Switches, Communication switching, Thermal stresses, Temperature, Thermal resistance, Current density, Frequency estimation, Energy consumption. Abstract: The influence of thermal effects on the reliability of RF MEMS switches is investigated in this paper. Low power consumption and capacity to handle high power at very high frequency elevate the scope of RF MEMS in the field of satellite and mobile communication technology immensely. The reliability of these switches are still under consideration as they fail due to thermal stresses developed during operation. A significant temperature rise occurs while transmitting high power at high frequency. In this paper, we introduced design parameters and investigated their influence to improve the switch's resistance to acute thermal stresses. A three dimensional finite element model of RF MEMS switch was simulated. A current density model and a thermal model were coupled to calculate the current density, heat loss and temperature rise within the domain. The maximum frequency and power range that the switch can handle before buckling failure were estimated. |
7,056 | Please write an abstract with title: Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification, and key words: Feature extraction, Fuses, Visualization, Learning systems, Benchmark testing, Australia, Neural networks. Abstract: Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, which can be mapped to compute the similarity value. However, relevant parts of each image are detected independently without referring to the correlation on the other image. Also, region-based methods spatially position local features for their aligned similarities. In this article, we introduce the deep coattention-based comparator (DCC) to fuse codependent representations of paired images so as to correlate the best relevant parts and produce their relative representations accordingly. The proposed approach mimics the human foveation to detect the distinct regions concurrently across images and alternatively attends to fuse them into the similarity learning. Our comparator is capable of learning representations relative to a test shot and well-suited to reidentifying pedestrians in surveillance. We perform extensive experiments to provide the insights and demonstrate the state of the arts achieved by our method in benchmark data sets: 1.2 and 2.5 points gain in mean average precision (mAP) on DukeMTMC-reID and Market-1501, respectively. |
7,057 | Please write an abstract with title: Task Allocation and Trajectory Planning for Collaborative Adversarial Multi-UAVsystems, and key words: Multiple UAVs, Collaborative task allocation formatting, Cross and variable domains, Improved particle swarm algorithm, B-spline curve method. Abstract: A algorithm-based approach for cooperative task allocation in multi-UAV adversarial missions is proposed. Taking into account flight time., fuel consumption., and introducing adversarial benefits as the optimization objective., the task allocation optimization mathematical model is constructed., considering flight constraints of the UAVs. Subsequently., a CLPSO algorithm is proposed for solving the problem., which exhibits superior global search capability compared to existing PSO algorithms. First., the particle positions are encoded as a set of matrix vectors., from which a corresponding set of feasible task assignment solutions is decoded., achieving the discretization of the particle swarm algorithm solution. Next., the CLPSO is employed to calculate the individual best and global best solutions for the particles., determining the corresponding strike sequence. Finally., a B-spline curve is fitted to the obtained strike sequence to generate a smooth path that is suitable for UAV flight. Simulation experiments demonstrate that the proposed method effectively addresses the task allocation problem in heterogeneous multi-UAV collaborative adversarial scenarios. |
7,058 | Please write an abstract with title: A Lightweight Convolution Neural Network for Automatic Disasters Recognition, and key words: Training, Performance evaluation, Visualization, Image recognition, Convolution, Statistical analysis, Neural networks. Abstract: This paper proposed a lightweight, efficient Convolution Neural Network model for automatic disaster recognition from aerial images. The model consists of a stack of convolutions and dense layers, and training incorporates several augmentation and data pre-processing techniques to improve the model’s generalisation. The model is evaluated on standard performance matrices like accuracy, precision, recall and the F1-score. We compared the results with state-of-the-art models, achieving a substantial boost in performance. Additionally, we trained different model variants for the quantitative analysis on publicly available datasets. With only 3 MB in size, our model is easily deployable on embedded and resource-constrained devices. |
7,059 | Please write an abstract with title: Energy efficient air-to-ground communication networks with reconfigurable intelligent surface, and key words: Energy efficiency, Communication networks, Optimization, Wireless networks, Radio frequency, Information processing, Autonomous aerial vehicles. Abstract: Reconfigurable intelligent surface (RIS) assisted air-to-ground wireless powered communication networks (WPCNs) are constructed to promote the energy efficiency of the system, in which unmanned aerial vehicles (UAV) reflects energy towards the energy-constrained hybrid access points (HAP) through RIS. Subsequently, HAP uses the collected energy to communicate with users in blind areas through the RIS-UAV. By optimizing parameters such as charging time ratio, transmit power and phase shifts matrix, the energy efficiency for single and multiuser scenarios are maximized, respectively. The energy efficiency is modeled as a non-convex quadratic programming problem with inequality constraints in the single-user scenario. Then the problem is converted into an equivalent convex problem by using the Taylor expansion and convex approximation method. A joint optimization algorithm of power and phase shifts is proposed to obtain a feasible solution. The energy efficiency is modeled as a fractional programming problem with non-convex inequality constraints in the multi-user scenario, and the feasible solution is obtained by proposing an alternating algorithm. Finally, both two scenarios are compared with the system of traditional amplify-and-forward (AF) relay, respectively. Finally, the simulation results show that the proposed algorithms can provide up with 150% and 160% improvement of the energy efficiency in the single and multi-user scenarios, respectively, compared to the traditional AF relay. |
7,060 | Please write an abstract with title: Analytical studies supplementing the Smith chart, and key words: Transmission line theory, Electrical engineering education. Abstract: The study of transmission lines is basic in undergraduate electrical engineering education. In relevant courses, a key subject is the Smith chart (SC), which is a graphical device providing insight. This paper develops certain formulas that can further enhance students' understanding, including an unconventional set of conductance/susceptance transformation equations, as well as simplified versions useful for highly mismatched lines, where it is sometimes difficult to use the SC. All formulas are developed from well-known facts of transmission-line theory. SC interpretations of many of the analytical results are provided. The analytical investigations thus supplement the SC. For highly mismatched lines, the formulas bring out certain resemblances to the resonant series RLC circuit, thus providing an interesting connection to the familiar subject of ordinary circuit theory. Lastly, students can also benefit from the mathematical tools used herein; these include simple ideas of asymptotic analysis. |
7,061 | Please write an abstract with title: Offshore Surface Evaporation Duct Joint Inversion Algorithm Using Measured Dual-Frequency Sea Clutter, and key words: Clutter, Ducts, Radar clutter, Sea measurements, Linear programming, Optimization, Radar measurements. Abstract: In this article, high-precision joint inversion of evaporative duct based on the dual-frequency radar sea clutter data is analyzed to study the abnormal duct environmental phenomenon that occurs over offshore surfaces. As the information of duct environment retrieved by radars with different frequencies is inconsistent, a joint optimization model with dynamic penalty factor is proposed, which can improve the degree of conformity between the measured clutter power and the modeled clutter power. Then, a parallel crossover quantum particle swarm optimization algorithm is used to jointly invert the objective function, which adaptively processes the inputs involved in the crossover and effectively improves the convergence of the inversion. Compared with the single-frequency model commonly used in engineering, the average relative error of the duct height of the dual-frequency joint optimization model is reduced by 3.13%, and the average relative error of the duct intensity is reduced by 6.34%, verifying the effectiveness of this method. |
7,062 | Please write an abstract with title: 2-bit Terahertz Digitally Coding Metasurface Based on HEMT Switching Microstructure, and key words: Three-dimensional displays, Electromagnetic scattering, Beams, Switches, HEMTs, Metasurfaces, Encoding. Abstract: In this paper, we propose the design of a 2-bit digitally coding metasurface that can efficiently modulate scattered electromagnetic waves and realize different far-field beams. By integrating two independently varying high electron mobility transistors (HEMT) into the metamaterial unit, the metasurface has four phase responses of 0, π/2, π, and 3π/2, corresponding to the four fundamental digital elements “00”, “01”, “10” and “11”. By designing the coding sequence of different arrays of digital elements, the reflected beam can be arbitrarily controlled. This work facilitates the implementation of 3D terahertz beam steering. |
7,063 | Please write an abstract with title: Study on Evaluation Method of Driving Risk of New Energy Operating Vehicles, and key words: Analytical models, Statistical analysis, Transportation industry, Time series analysis, Decision making, Big Data, Data models. Abstract: This study proposes a method to evaluate the new energy operating vehicles driver's driving risk and driving style with non-predefined thresholds. Based on vehicle driving data and time series changes of drivers' driving behaviors, a driving behavior model diagram is established. Through driving behavior model diagram and driving risk comparative evaluation system, this paper quantitatively evaluates the individual driving behavior risks of different drivers, and helps the transportation industry to reduce risks. |
7,064 | Please write an abstract with title: Proportional Power-Sharing Control of Distributed Generators in Microgrids, and key words: Microgrids, Consensus algorithm, Voltage control, Transient analysis, Convergence, Renewable energy sources, Delays. Abstract: This research addresses distributed proportional power-sharing of inverter-based distributed generators (DGs) in microgrids under variations in the maximum power capacity of DGs. A microgrid can include renewable energy resources such as wind turbines, solar panels, fuel cells, etc. The intermittent nature of such energy resources causes variations in their maximum power capacities. Since DGs in microgrids can be regarded as multiagent-systems (MASs), a consensus algorithm is designed to have the DGs to generate their output power in proportion to their maximum capacities under capacity fluctuations. A change in power capacity of a DG triggers the consensus algorithm, which uses a communication map at the cyber layer to estimate the corresponding change. The convergence rate of the algorithm is analytically established and bounds on allowable capacity fluctuations are derived based on practical constraints. During the transient time of reaching a consensus, the delivered power may not match the load power demand. To eliminate this mismatch, a control law is augmented that consists of a finite-time consensus algorithm embedded within the overarching power-sharing consensus algorithm. The effectiveness of the distributed controller is assessed through simulation of a microgrid consisting of a realistic model of inverter-based DGs. Details of the microgrid model, its controller structures, and a comprehensive list of parameters are provided. |
7,065 | Please write an abstract with title: An Approach to Structured Parallel Programming Based on a Composition, and key words: Parallel programming, Programming profession, Pipelines, Binary trees, Yarn, Grid computing, Parallel processing, Software reusability, Application software, Software libraries. Abstract: This article presents a programming methodology based on High Level Parallel Compositions or CPAN (according to its Spanish acronym) within a methodological infrastructure made up of an environment of Parallel Objects, an approach to Structured Parallel Programming and the Object- Orientation paradigm. By means of the method application, the parallelization of commonly used communication patterns among processes is presented, which is initially constituted by the CPANs Farm, Pipe and TreeDV that represent, respectively, the patterns of communication Farm, Pipeline and Binary Tree, the latter one used within a parallel version of the design technique known as Divide and Conquer. As the programming environment used to derive the proposed CPANs, we use C++ and the POSIX standard for thread programming. |
7,066 | Please write an abstract with title: Electrostatic actuated interference filters as optical switches for projection display applications, and key words: Electrostatic interference, Optical filters, Optical switches, Displays, Optical modulation, Optical design, Optical reflection, Mirrors, Silicon, Biomembranes. Abstract: Optical elements for modulating light based on switchable interference filters are described. Such types of elements could be designed for use in reflection and, unlike micro mirrors, in transmission as well, which often simplifies the design of optical systems. Switching elements based on LPCVD silicon nitride membranes were developed for use in reflection. The switches show optimum performance around the wavelength they are designed for. Efficiencies (fractions of the incident light that is passing the switch) of bout 70% were measured for the design wavelength. First samples for use in trans-mission have been manufactured on quartz substrates. |
7,067 | Please write an abstract with title: Multiscale principal components analysis for image local orientation estimation, and key words: Principal component analysis, Image analysis, Electronics packaging, Maximum likelihood estimation, Noise robustness, Computational modeling, Singular value decomposition, Covariance matrix, Analytical models, Computer simulation. Abstract: This paper presents an image local orientation estimation method, which is based on a combination of two already well-known techniques: the principal component analysis (PCA) and the multiscale pyramid decomposition. The PCA analysis is applied to find the maximum likelihood (ML) estimate of the local orientation. The proposed technique is shown to enjoy excellent robustness against noise. We present both simulated and real image examples to demonstrate the proposed technique. |
7,068 | Please write an abstract with title: Computer vision meets visual analytics: Enabling 4D crime scene investigation from image and video data, and key words: 4D Reconstruction, Computer Vision, Crime Scene Investigation, Visual Exploration, Forensics. Abstract: In case of a crime or terrorist attack, nowadays much video footage is available from surveillance and mobile cameras recorded by witnesses. While immediate results can be crucial for the prevention of further incidents, the investigation of such events is typically very costly due to the human resources and time that are needed to process the mass data for an investigation. In this paper, we present an approach that creates a 4D reconstruction from mass data, which is a spatio-temporal reconstruction computed from all available images and video footage. The resulting 4D reconstruction gives investigators an intuitive overview of all camera locations and their viewing directions. It provides investigators the ability to view the original video or image footage at any specific point in time. Combined with an innovative 4D interface, our resulting 4D reconstruction enables investigators to view a crime scene in a way that is similar to watching a video where one can freely navigate in space and time. Furthermore, our approach augments the scene with automatic detections and their trajectories and enrich the crime scene with annotations serving as clues. |
7,069 | Please write an abstract with title: Understanding power system resilience by using neural networks analysis, and key words: Power flow, power tracing, neural networks, power system resilience, generation contribution. Abstract: With the rapid increase in the connection of distributed generation and anticipated new load (electric vehicles particularly), power system is facing new challenges. In order to understand the network resilience, the author uses power tracing to understand the contribution of the generations to the loads. A new approach (neural networks) is then used to learn the inter-related indices between the generation and the load. The results will be useful to indicate the network's resilience capability and improve power system recovery under emergencies. |
7,070 | Please write an abstract with title: Traffic distribution schemes for multi-homed mobile hotspots, and key words: Telecommunication traffic, Distributed computing, Vehicles, Traffic control, IP networks, Local area networks, Research and development, Mobile communication, Ground penetrating radar, 3G mobile communication. Abstract: Providing broadband Internet access in mobile hotspots (e.g. public transport vehicles) through high-speed on-board local area networks and mobile routers is becoming an increasingly popular area of research and development. Mobile hotspot operators can provide faster, cheaper, and more stable communication services to on-board passengers using the multihoming technique, whereby the mobile router is connected to a diverse array of wireless access technologies (e.g., GPRS, UMTS, CDMA, and 802.11) through a multiplicity of wireless service providers. For mobile hotspot operators, how to "best" distribute the user traffic among the set of available access networks; which may change frequently during the trip; becomes a challenging task. In this paper, we propose and compare two traffic distribution schemes: in-transit and pre-transit, which are designed to take the benefit of multi-homing. The intransit scheme computes optimum traffic distribution on-the-fly, while the pre-transit scheme exploits the repetitive route of a public transport vehicle and computes the whole set of traffic (re)distributions before the trip starts. The objective of the traffic distribution computations is to optimize the profit and performance for the mobile hotspot operator. Using a generic public transport mobility model, we provide results from a detailed simulation study of these two schemes under different user demands. |
7,071 | Please write an abstract with title: Eye typing off the shelf, and key words: Calibration, Robustness, Cameras, Hardware, Light emitting diodes, Image quality, Iris, Computer vision, Filtering algorithms, Geometry. Abstract: The goal of this work is using off-the-shelf components for gaze-based interaction, with focus on eye typing. Avoiding the use of dedicated hardware such as IR light emitters makes eye tracking significantly more difficult and requires robust methods capable of handling large changes in image quality. We employ an active-contour method to obtain robust iris tracking. The main strength of the method is that the contour model avoids explicit feature detection: contours are simply assumed to remove statistical dependencies on opposite sides of the contour. The contour model is utilized in an approach combining particle filtering with the EM algorithm. The method is robust against light changes and camera defocusing. For the purpose of determining where the user is looking calibrations is usually needed. The number of calibration points used in different methods varies from a few to several thousands, depending on the prior knowledge used on the setup and equipment We examine basic properties of gaze determination when the geometry of the camera, screen and user is unknown. In particular we present a lower bound on the number of calibration points needed for gaze determination on planar objects, and we examine degenerate configurations. Based on this lower bound we apply a simple calibration procedure, to facilitate button selections for fast on-screen typing. |
7,072 | Please write an abstract with title: Deep Learning-based Detection Methods for Covert Communications in E- Health Transmissions, and key words: Deep learning, Learning systems, Neural networks, Modulation, Telecommunication traffic, Medical services, Delays. Abstract: Despite the numerous advantages offered by e-health applications, healthcare data of patients are at huge risk, being targeted by several different types of digital menaces and attacks. Covert communications (or channels) are dramatic threats in e-health transmissions. A covert communication in fact establishes a secret path hidden within legitimate network traffic, and can be used for leaking patients' medical information, identity, personal data, and medical history. This paper focuses on covert timing channels, where the covert data are transmitted by modulating the inter-packets delays of overt transmitted data, proposing a deep learning-based method for the effective detection of such a dangerous threat. More in details, we first collect all the inter-arrival packet delays affected by a timing covert communication, and convert them into colored images (namely, into spectrograms). Then, we exploit image-based deep learning framework to implement an effective detection of such hidden communications. The results, obtained from simulated covert data traffic also in comparison with existing deep-learning methods, demonstrate the efficiency of the proposed method to detect and prevent this form of malicious e-health information transfer. |
7,073 | Please write an abstract with title: A Hybrid-Arm Modular Multilevel Converters Topology With DC Low Voltage Operation and Fault Ride-Through Capability for Unidirectional HVDC Bulk Power Transmission, and key words: Topology, Low voltage, Circuit faults, HVDC transmission, Power system stability, Reactive power. Abstract: In this paper, a novel hybrid-arm modular multilevel converters (HA-MMCs) topology with DC low voltage operation and fault ride-through capability is proposed for unidirectional HVDC bulk power transmission. The HA-MMCs topology is a combination of two types of converter arms: the half-bridge sub-module based arm (HBSM-arm) and the diagonal bridge sub-module based arm (DBSM-arm). Replacing the traditional HBSM-MMC, the HA-MMCs are operated in current and reactive power control modes during normal conditions and can work as the rectifier or the inverter. Since the DBSM can provide bipolar voltages with unipolar currents, the HA-MMCs need not change its control strategy under DC low voltage conditions caused by the high-impedance faults. Under DC pole-to-pole or pole-to-ground faults, the HA-MMCs can both clear the DC fault current and work as the static synchronous compensator (STATCOM) to provide reactive power to support the AC grid. Compared with other MMC topologies with DC fault ride-through capability, the HA-MMCs topology is more economical for significantly decreasing the number of power devices. The operation states, control strategy and DC low voltage operation capability of the HA-MMCs are presented and simulation results of the LCC-HA-MMC hybrid system using PSCAD/EMTDC validate the characteristics and advantages of the HA-MMCs. |
7,074 | Please write an abstract with title: Organizations Data Integrity Providing through Employee Behavioral Analysis Algorithms, and key words: Machine learning algorithms, Data analysis, Data integrity, Software algorithms, Machine learning, Organizations, Prediction algorithms. Abstract: This article discusses the development of mathematical support and software for detecting anomalous behavior of users based on biometric characteristics of their behavior analysis. One of the challenges in intelligent UBA (User Behavior Analytics) systems is acquisition of useful information from a large volumes of unstructured, unmatched data. Methods and algorithms of intelligent data processing and machine learning used in UBA/DSS systems help to work on a task of solving problems of data analysis of different directivities. It is proposed an application of machine learning methods in implementation of mobile UBA system. There was formed the list of the most significant factors submitted to the input of the analyzing methods during the study. Two approaches of detecting abnormal user behavior have been proposed. The application of machine learning techniques in intelligent UBA systems will make it possible to predict information risks and insider excfiltration of these organizations in advance. |
7,075 | Please write an abstract with title: Carrots or Sticks? The Effectiveness of Subsidies and Tolls in Congestion Games, and key words: Games, Finance, Routing, Sensitivity, Nickel, Optimized production technology, Sociology. Abstract: Are rewards or penalties more effective in influencing user behavior? This work compares the effectiveness of subsidies and tolls in incentivizing users in congestion games. The predominantly studied method of influencing user behavior in network routing problems is to institute taxes which alter users' observed costs in a manner that causes their self-interested choices to more closely align with a system-level objective. Another feasible method to accomplish the same goal is to subsidize the users' actions that are preferable from a system-level perspective. We show that, when users behave similarly and predictably, subsidies offer comparable performance guarantees to tolls while requiring smaller monetary transactions with users; however, in the presence of unknown player heterogeneity, subsidies fail to offer the same performance as tolls. We further investigate these relationships in affine congestion games, deriving explicit performance bounds under optimal tolls and subsidies with and without user heterogeneity; we show that the differences in performance can be significant. |
7,076 | Please write an abstract with title: Machine Learning Feature Based Job Scheduling for Distributed Machine Learning Clusters, and key words: Task analysis, Parallel processing, Servers, Scheduling, Data models, Training, Graphics processing units. Abstract: With the rapid proliferation of Machine Learning (ML) and Deep learning (DL) applications running on modern platforms, it is crucial to satisfy application performance requirements such as meeting deadline and ensuring accuracy. To this end, researchers have proposed several job schedulers for ML clusters. However, none of the previously proposed schedulers consider ML model parallelism, though it has been proposed as an approach to increase the efficiency of running large-scale ML and DL jobs. Thus, in this paper, we propose an ML job Feature based job Scheduling system (MLFS) for ML clusters running both data parallelism and model parallelism ML jobs. MLFS first uses a heuristic scheduling method that considers an ML job’s spatial and temporal features to determine task priority for job queue ordering in order to improve job completion time (JCT) and accuracy performance. It uses the data from the heuristic scheduling method for training a deep reinforcement learning (RL) model. After the RL model is well trained, it then switches to the RL method to automatically make decisions on job scheduling. In addition, MLFS has a system load control method that selects tasks from overloaded servers to move to underloaded servers based on task priority, and also intelligently removes the tasks that generate little or no improvement on the desired accuracy performance when the system is overloaded to improve JCT and accuracy by job deadline. Furthermore, we propose Optimal ML iteration stopping method that determines the proper time to stop training ML model when this model reaches the minimum loss value. Our real experiments and large-scale simulation based on real trace show that MLFS reduces JCT by up to 53% and makespan by up to 52%, and improves accuracy by up to 64% when compared with existing ML job schedulers. We also open sourced our code. |
7,077 | Please write an abstract with title: A Novel Multiport Modular Multilevel Converter for AC-DC Hybrid Distribution Power System, and key words: Power system measurements, Multilevel converters, Costs, Density measurement, Simulation, Distribution networks, Hybrid power systems. Abstract: The medium-voltage AC/DC (MVAC/MVDC) hybrid distribution network is progressively becoming a recent research focus with the massive access of distributed energy sources and electric vehicles. As the key enablers to connect MVAC and MVDC distribution girds, power-electronic-based stations usually adopt modular multilevel converter (MMC) due to its modularity and scalability. Unlike the conventional AC/DC converter with only one AC port, a multi-AC-port MMC (MACP-MMC) is proposed in this paper, in which multiple AC feeders can be interconnected via small-capacity interconnection ports. By means of coordinated control, the controllable and decoupling adjustment of active and reactive power on the lines can be realized. Besides, MACP-MMC also features simple structure, modularization, easy port expansion, low cost, and high power density. The operation principle, energy balance mechanism, and coordinated control strategies of the MACP-MMC are elaborated. Besides, its feasibility and effectiveness is verified by simulation results obtained from a 3-MVA model with three 10kV feeders. |
7,078 | Please write an abstract with title: RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups, and key words: Analytical models, Biological system modeling, Visual analytics, Computational modeling, Sociology, Data visualization, Atrial fibrillation. Abstract: Disease risk models can identify high-risk patients and help clinicians provide more personalized care. However, risk models de-veloped on one dataset may not generalize across diverse subpop-ulations of patients in different datasets and may have unexpected performance. It is challenging for clinical researchers to inspect risk models across different subgroups without any tools. Therefore, we developed an interactive visualization system called RMExplorer (Risk Model Explorer) to enable interactive risk model assessment. Specifically, the system allows users to define subgroups of patients by selecting clinical, demographic, or other characteristics, to ex-plore the performance and fairness of risk models on the subgroups, and to understand the feature contributions to risk scores. To demonstrate the usefulness of the tool, we conduct a case study, where we use RMExplorer to explore three atrial fibrillation risk models by applying them to the UK Biobank dataset of 445,329 individuals. RMExplorer can help researchers to evaluate the performance and biases of risk models on subpopulations of interest in their data. |
7,079 | Please write an abstract with title: Recursive Algorithms for Computing End-to-End Blocking in a Network with Arbitrary Routing Plan, and key words: Computer networks, Routing, Probability, Costs, Availability, Switching circuits, Telecommunication traffic, Force control, Communication switching, Communications Society. Abstract: This paper presents three recursive algorithms for computing end-to-end blocking probabilities in a network with alternate routing, based on link blocking probabilities. The only assumption made is the statistical independence of link blocking probabilities. The first algorithm applies to arbitrary routing plans. The second algorithm applies to single-loss-route routing plans which include predictive routing plans used in advanced private networks. The second algorithm is also applicable to solving the terminal-pair reliability problem. The third algorithm applies to tandem-node-matrix-generated routing plans which include hierarchical routing plans similar to those used in North American public toll network, AT&T's CCSA, EPSCS, and ETN networks. These three algorithms are progressively more efficient. |
7,080 | Please write an abstract with title: Automatic acoustic-phonetic analysis of vowels and sonorants, and key words: Speech processing, Labeling, Stress, Signal analysis, Signal design, Underwater vehicles, Iris, Steady-state, Signal processing algorithms, Algorithm design and analysis. Abstract: A technique has been developed to locate, define the boundaries of, and appropriately label steady-state voiced non-fricative areas of a continuous speech utterance. It uses advanced methods of pitch and formant tracking to provide the necessary acoustic parameters. The labeling algorithm compares the analyses with vowel-sonorant tables that incorporate some coarticulation phonemena based on current research. The sounds are discussed with respect to the stress of the vowels and the position of the sonorant, i.e., initial or final form. Results for four male subjects are presented. |
7,081 | Please write an abstract with title: Scintillation properties of LYSO crystals, and key words: Atomic measurements, Costs, Photonic crystals, Yttrium, Raw materials, Positron emission tomography, Crystalline materials, Chemicals, X-rays, Gamma ray detectors. Abstract: We evaluate the scintillator properties of LYSO (Lu/sub (2-x)/Y/sub x/SiO/sub 5/:Ce) crystals with the amount of lutetium ranging from 15 to 100%. The radii of the cations Lu/sup 3+/ and Y/sup 3+/ differ by only 5%, therefore, one can substitute yttrium for lutetium without changing the structure. The addition of yttrium has several advantages: the raw material Y/sub 2/O/sub 3/ is much cheaper than Lu/sub 2/O/sub 3/ and the melting point is up to 100/spl deg/C less. Since yttrium has a much lower atomic number and atomic mass than lutetium, LYSO crystals have a lower density and effective atomic number. This means that LYSO does not absorb X-rays as well as LSO. LYSO with 50% lutetium, however, has an effective atomic number that is just 11% less than LSO and the light yield of LYSO with 30% or more lutetium is roughly the same as that of LSO samples. LYSO scintillators with 50% or more lutetium could provide a more cost effective scintillator material for some applications. |
7,082 | Please write an abstract with title: Mechanism B I-V Symmetry for MIM Capacitors Used in Microelectronics, and key words: MIM capacitors, Microelectronics, Dielectrics, High-k dielectric materials. Abstract: The I-V characteristics of MIM capacitors tend to be asymmetrical. However, the I-V characteristics of MIM capacitors can sometimes be symmetrical because of two different mechanisms: Mechanism A and Mechanism B. For high-k MIM capacitors with ultrathin high-k dielectric, Mechanism B is the more likely mechanism. |
7,083 | Please write an abstract with title: Linear and nonlinear inversion of GPR data, and key words: Inverse problems, Image reconstruction, Cost function, Ground penetrating radar, Electromagnetic scattering, Application software, Laboratories, Robustness, Approximation methods, Measurement standards. Abstract: We discuss the linear and nonlinear inverse scattering problem. In cases where the Born approximation is valid, we obtain an inverse inverse problem, which is formulated as an optimization problem in terms of the unknown material contrast and the unknown contrast sources. The constitutive relation between these quantities acts as a regularizing constraint. A further regularization with a multiplicative regularization factor is discussed. In this regularization procedure the relative variation of the contrast is minimized as well. We illustrate the robustness of the inversion algorithm for a 2D problem, where we have all the views around the unknown object. In addition, some inversion results for the subsurface sensing problem, both in 2D and 3D, are presented. In the latter example, we show that a full nonlinear inversion scheme may improve the results. |
7,084 | Please write an abstract with title: Deep Networks Based Classification of COVID-19 Chest X-Ray Images, and key words: COVID-19, Support vector machines, Solid modeling, Feature extraction, Diagnostic radiography, X-ray imaging, Tuning. Abstract: The worldwide spread of COVID-19 (Corona virus) has been declared a global health crisis by WHO. In order to perform early diagnosis of COVID-19 infection a computer-aided diagnosis (CAD) system is of great importance. Chest X-ray radiographic imaging is a preferred diagnostic mean used by radiologists. Machine and deep learning algorithms have been found useful in many CAD equipped health care systems. In this paper, we present an approach to classify chest X-ray radiographic images into normal, COVID-19, and viral-pneumonia categories. The proposed approach performs feature extraction using pre-trained and fine tuned deep networks using transfer learning. A support vector machine (SVM) is trained using the extracted features and used for classification. We collect a dataset comprised of publicly available chest X-ray images from normal, COVID-19 and viral-pneumonia patients. Experimental results demonstrate that the proposed approach achieves 99.29% classification accuracy in case of COVID-19 images and an overall classification accuracy of 97.36%, which is better than most of the existing approaches. |
7,085 | Please write an abstract with title: HyperLogLog: Exponentially Bad in Adversarial Settings, and key words: Hash functions, Costs, Social networking (online), Memory management, Data structures, Internet, Security. Abstract: Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a naive approach, at the cost of some accuracy. This trade-off makes the HLL algorithm very attractive for a wide range of applications such as database management and network monitoring, where an exact count may not be needed. The HLL algorithm and variants of it are implemented in systems such as Redis and Google Big Query. Recently, the HLL algorithm has started to be proposed for use in scenarios where the inputs may be adversarially generated, for example counting social network users or detection of network scanning attacks. This prompts an examination of the performance of the HLL algorithm in the face of adversarial inputs. We show that in such a setting, the HLL algorithm's estimate of cardinality can be exponentially bad: when an adversary has access to the internals of the HLL algorithm and has some flexibility in choosing what inputs will be recorded, it can manipulate the cardinality estimate to be exponentially smaller than the true cardinality. We study both the original HLL algorithm and a more modern version of it (Ertl, 2017) that is used in Redis. We present experimental results confirming our theoretical analysis. Finally, we consider attack prevention: we show how to modify HLL in a simple way that provably prevents cardinality estimate manipulation attacks. |
7,086 | Please write an abstract with title: 5G Ring Antenna for Internet of Medical Things (IoMT) Applications, and key words: Wireless communication, Industries, Wireless sensor networks, Technological innovation, Medical devices, 5G mobile communication, Internet of Medical Things. Abstract: Advanced sensor and interconnect solutions are driving innovation in the wearable, wireless, and connected healthcare device industry. The implementation of 5G networks is expanding rapidly; hence, the Internet of Medical Things (IoMT) and medical technologies will require 5G antennas for wearable and wireless connectivity. This paper proposed a novel wideband Ring Antenna that is operational over a frequency band from 28GHz to 34GHz. The proposed antenna occupies a small size of (20x20x 1.5mm), and it has return loss (S11) values well below -15dB with VSWR below 3dB at most frequencies in the said band. The antenna gain reaches 8.6dBi at 34GHz and has gain values and stable radiation patterns that offer good coverage for indoor wireless communications. These features make the proposed design very suitable for wearable and wireless devices that are used for IoMT. |
7,087 | Please write an abstract with title: Grid services in action: grid enabled optimisation and design search, and key words: Design optimization, Design engineering, Data engineering, Computational fluid dynamics, Grid computing, Computer architecture, Data visualization, Computer science, Distributed computing, Resource management. Abstract: We are developing a Grid Enabled Optimisation and Design Search system (GEODISE). It offers grid-based access to a state-of-the-art collection of optimisation and design search tools, industrial strength analysis codes, and distributed computing and data resources. |
7,088 | Please write an abstract with title: Advances in Power Electronics, and key words: Power electronics, Packaging, Silicon, Gallium nitride, Photonic band gap, Silicon carbide, Technological innovation. Abstract: Power electronics is seeing significant growth due to electrification of transport, and carbon reduction using renewable energy. Innovations in devices (e.g. wide bandgap materials such as Silicon Carbide and Gallium Nitride) provide the opportunity to design smaller power electronic systems that are highly efficient. A key to realizing these benefits is innovations in packaging and design tools. Traditional materials and packaging architectures need to address the new environments that they will be subjected to higher temperatures, frequencies, and inductances, etc. New design and modelling approaches will be required to support innovations in packaging and reliability predictions. This paper details some of the recent advances in power electronics systems and details some of the challenges that need to be overcome. |
7,089 | Please write an abstract with title: Optimizing Ambulance Paths: Case Study of Red Cross Tripoli Branch, and key words: Roads, Urban areas, Timing, Shortest path problem, Dams, Tungsten, Software. Abstract: Red Cross, an international humanitarian organization, is involved in helping people suffering from hunger, war, diseases, or other problems. Reaching people who need help in using the own ambulances of the Red Cross. Due to congestion problems in Lebanon, the ambulances are sometimes late which threatens people's life. This paper aims to help the ambulances of the Red Cross in Tripoli Branch to promptly reach their urgencies in case of congestion and not. The problem is solved using Wolfram Mathematica 8.0 where the shortest path, in duration, is found. In the end, the shortest path is selected to be used by the Red Cross when there is congestion and another one is selected when there is not. |
7,090 | Please write an abstract with title: Improving CBS tool development with technological spaces, and key words: Space technology, Software engineering, Software systems, Systems engineering and theory, Computer architecture, Software performance, Programming, Design engineering, Object oriented modeling, Large-scale systems. Abstract: The complexity of computer based systems (CBSs) requires that multiple levels of abstraction be available to a designer in order to facilitate their formal specification. Generating final executable code from the model of the system is preferred to hand-coding the implementation, but this is seldom done in one step-usually there are several cascading transformations that eventually result in the executable system. We explain how the concept of the technological space (TS) can be used to define and describe the layers between cascading transformations, and the transformations themselves. TSs are also shown as a categorization that better distinguishes between a domain and the technology used to store information in a domain. |
7,091 | Please write an abstract with title: Efficient Deep Learning of Nonlinear Fiber-Optic Communications Using a Convolutional Recurrent Neural Network, and key words: Optical fibers, Integrated optics, Deep learning, Recurrent neural networks, Convolution, Computational modeling, Optical fiber networks. Abstract: Nonlinear channel impairments are a major obstacle in fiber-optic communication systems. To facilitate a higher data rate in these systems, the complexity of the underlying digital signal processing algorithms to compensate for these impairments must be reduced. Deep learning-based methods have proven successful in this area. However, the concept of computational complexity remains an open problem. In this paper, a low-complexity convolutional recurrent neural network (CNN + RNN) is considered for deep learning of the long-haul optical fiber communication systems where the channel is governed by the nonlinear Schrodinger equation. This approach reduces the computational complexity via balancing the computational load by capturing short-temporal distance features using strided convolution layers with ReLU activation, and the long-distance features using a many-to-one recurrent layer. We demonstrate that for a 16-QAM 100 G symbol/s system over 2000 km optical-link of 20 spans, the proposed approach achieves the bit-error-rate of the digital back-propagation (DBP) with substantially fewer floating-point operations (FLOPs) than the recently-proposed learned DBP, as well as the non-model-driven deep learning-based equalization methods using end-to-end MLP, CNN, RNN, and bi-RNN models. |
7,092 | Please write an abstract with title: Welding Seam Classification in the Automotive Industry using Deep Learning Algorithms, and key words: Deep learning, Industries, Visualization, Welding, Inspection, Feature extraction, Classification algorithms. Abstract: Welding seam inspection is key process in the automotive industry and should guarantee the quality required by the client. Visual inspection is achieved by the operator who checks each part manually, making the reliability highly improvable. That's why automating the visual inspection is needed in today's production process. Collecting data from inside the plant may not provide a balanced number of images between good welding seams and bad welding seams. In this article, we will compare a standard deep learning algorithm applied on raw data with data augmentation approaches. Our target is to reach an accuracy of 97 % on the defected reference parts. This target is reached on some welds, while it remains a challenge on other welds. |
7,093 | Please write an abstract with title: Combining Induction and Permanent Magnet Synchronous Machines in a Series-Connected Six-Phase Vector-Controlled Two-Motor Drive, and key words: Permanent magnet machines, Inverters, Current control, Stator windings, Voltage, Induction machines, Machine vector control, AC machines, Joining processes, Laboratories. Abstract: It has been shown recently that a number of multi-phase machines can be controlled independently, with the supply coming from a single multi-phase inverter, provided that the stator windings are connected in series in an appropriate manner. One such drive system is a two-motor drive, consisting of a symmetrical six-phase machine connected in series with a three-phase machine. The supply is provided from a six-phase current-controlled voltage source inverter (VSI). This paper examines operation of such a drive system when a six-phase symmetrical induction machine is connected in series with a three-phase permanent magnet synchronous machine (PMSM). Basic operating principles of the drive system are at first reviewed. This is followed by a brief description of the experimental system. An extensive presentation of experimental results, collected from a laboratory setup, is then provided. It is shown that a truly independent and decoupled vector control of the two machines results, although a single supply source is used. The two-motor drive system of the proposed structure is seen as a potentially viable industrial solution for applications requiring one high-power and one low-power machine |
7,094 | Please write an abstract with title: Superconducting levitated high speed ground transportation project in Japan, and key words: Land transportation, Magnetic levitation, Propulsion, Superconducting magnets, Tracking loops, Rail transportation, Power generation economics, Acceleration, Railway safety, Coils. Abstract: An outline of the magnetic levitation project in Japan is given. Research has been concentrated on levitation system utilizing electromagnetic repulsive force between a normal metal track and on-board superconducting magnets. Development of levitation magnets together with other items basic for a levitation system is given. |
7,095 | Please write an abstract with title: Fine-tuning techniques and data augmentation on transformer-based models for conversational texts and noisy user-generated content, and key words: Analytical models, Social networking (online), User-generated content, Transfer learning, Data models, Noise measurement, Task analysis. Abstract: Transfer learning and Transformer-based language models play important roles in modern natural language processing research community. In this paper, we propose Transformer model's fine-tuning and data augmentation (TMFTDA) techniques for conversational texts and noisy user-generated content. We use two NTCIR-15 tasks, namely the first Dialogue Evaluation (DialEval-1) task and the second Numeral Attachment in Financial Tweets (FinNum-2) task, to evaluate the efficacy of TMFTDA. Experimental results show that TMFTDA substantially outperforms the baselines model of Bidirectional Long Short-Term Memory (Bi-LSTM) in multi-turn dialogue system evaluation at DialEval-1's Dialogue Quality (DQ) and Nugget Detection (ND) subtasks. Moreover, TMFTDA performs to a satisfactory level at FinNum-2 with a model of Cross-lingual Language Models using a Robustly Optimized BERT Pretraining Approach (XLM-RoBERTa). The research contribution of this paper is that, we help shed some light on the usefulness of TMFTDA, for conversational texts and noisy user-generated content in social media text analytics. |
7,096 | Please write an abstract with title: Unconstrained monitoring of prevention of wandering the elderly, and key words: Monitoring, Senior citizens, Hospitals, Sensor systems, Switches, Foot, System testing, Dementia, Detectors, Gerontechnology. Abstract: Wandering demented patients are in danger of falling and injuring themselves without a caregiver's support. In this study, we developed an unconstrained monitoring system that notifies wandering in the elderly to their caregiver. The system consists of a step sensor that detects the contact on the floor, an interface for transmitting data to the caregivers and floor lighting. Foot switch was installed beside a subject's bed. When the wandering is detected caregiver is notified it by phone calling via a personal handy-phone system (PHS). The developed system was tested for three subjects and successfully detected the wandering of subjects. |
7,097 | Please write an abstract with title: Fuzzy Self-Tuning of Strictly Negative-Imaginary Controllers for Trajectory Tracking of a Quadcopter Unmanned Aerial Vehicle, and key words: Control systems, Uncertainty, Robustness, Real-time systems, Damping, Transfer functions, Fuzzy logic. Abstract: Robustness in the face of uncertainties is an integral part of designing a real-time control system. Based on negative imaginary (NI) systems theory, we design robust and adaptive control systems for accurate trajectory tracking of a quadcopter aerial vehicle. Considering the challenging dynamics of unmanned aerial vehicles, we employ knowledge-based fuzzy inference systems (FIS) to facilitate automatic tuning in our SNI controllers, leading to the development of adaptive SNI control systems. Unlike fixed-gain controllers that have no ability to adapt to the variations in environmental conditions or changes in the dynamics of the plant, our adaptive SNI controllers are able to perform self-tuning to constantly update their parameters. The concept of adaptive autopilots will enhance the ability of the closed-loop control systems to accommodate large uncertainties. To demonstrate their efficacy, we design and implement our adaptive SNI controllers in the three-position control loops of the AR.Drone quadcopter after conducting extensive computer simulations. We also perform a rigorous comparative study with respect to the performance of fixed-gain SNI controllers, fixed-gain NI systems, in addition to model-predictive-control systems, and proportional integral derivative (PID) control systems as our benchmarks. To complete the study, we conduct a stability analysis based on Kharitonov's Theorem. |
7,098 | Please write an abstract with title: High-performance, four-layer, wire-bonded, plastic ball grid array package for a 10 Gbps per lane backplane SerDes transceiver, and key words: Electronics packaging, Plastic packaging, Backplanes, Transceivers, Crosstalk, Connectors, Impedance, Reflection, Costs, Thermal resistance. Abstract: A high-performance package design was required for a SerDes-to-SerDes Mux chip for backplane applications using eight 1.0-3.125 Gbps lanes on the system side and four 1.0-10.0 Gbps lanes on the backplane side. Cost and thermal targets required that this chip be built with wirebond assembly in a four-layer, 19/spl times/19mm 324 ball Plastic Ball Grid Array. Preliminary simulations were used to define package layout rules. Final 3-D simulations on the completed design showed that at 3.125GHz return loss was less than -20dB. At 10GHz, insertion loss was less than -1.0dB and crosstalk less than -50dB. Thermal simulations showed a thermal resistance of 11/spl deg/C/W using thermal vias, 1 m/s airflow, 2oz Cu power planes, a heat spreader, and 0.5mm solder balls. |
7,099 | Please write an abstract with title: Flux compensated direct torque control of induction motor drives for low speed operation, and key words: Torque control, Induction motor drives, Stators, DC motors, Voltage, Induction motors, Linear feedback control systems, Commutation, Rotors, Motor drives. Abstract: Speed control of direct torque controlled (DTC) induction motor drives depends on effectively establishing the stator flux. However, it becomes difficult when the motor operates in the low speed region, because the voltage drop on the stator resistance is comparable with the input stator voltage. Therefore, this study proposes an easy but effective way to compensate the voltage drop on the stator resistance so that the stator flux can be constructed without identifying the stator resistance as done by most authors. As a result, motor torque is constructed due to the effective stator flux compensation, which makes the DTC applicable to induction motor drives in the low speed region. Moreover, a fixed-point digital signal processor (DSP)-based hardware experimental system is built to demonstrate the effectiveness of the proposed control method. |
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