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12,700 | Please write an abstract with title: AUTOSAR Classic Platform Flexibility Managing the complexity of distributed embedded software development : Invited Talk, and key words: Industries, Software architecture, Software algorithms, Companies, Tools, Programming, Software. Abstract: AUTOSAR Classic Platform is a well-established industry standard for model-based and layered software development in the automotive industry. Formally defined interfaces between the individual software components simplify independent development- and testing. However, the nowadays readily available multi-core microcontrollers allow for increasingly larger and more complex application software. It makes sense to have parts of it developed by partner companies or subcontractors, which are specialized on a specific matter or algorithm. Such a distributed development over several company-internal teams or even companies is hard to achieve. This is mainly because of the inherently static configuration of AUTOSAR Classic Platform, which requires a precise definition of a software component's provided and required data and services. Furthermore, the ECU integrator needs to create a binary of the overall embedded software, a process which is quite sensitive to accidentally brought in incompatibilities in data- and services exchanged respectively used between the software components. Classic Platform Flexibility addresses these challenges and, on top, offers further use cases for the distributed software development. The main changes it brings are enhanced flexibility during development and stronger formalization regarding data and services produced- and consumed by the application components. This is achieved by adding another granularity-layer to the AUTOSAR Classic model: The Software Cluster. Software Clusters are intended to contain one or several software components, the middleware for data exchange and service invocation and, depending on the role of a Cluster, also parts of the AUTOSAR Basic Software, which provides the various services and handles ECU-external communication via the fieldbuses. Software Clusters are self-contained parts of the overall embedded software and can be built independently. This changes integration of the overall embedded software of an ECU from a classical build process to simply programming of the Software Clusters in their binary form to the ECU and establishing the connections of their interfaces with a so-called Connector tool. |
12,701 | Please write an abstract with title: Enhancing Security by Identifying Facial Check-in using Deep Convolutional Neural Network, and key words: Training, Face recognition, Process control, Manuals, Regulation, Safety, Security. Abstract: Facial recognition is widely being used in many applications. In this research face recognition-based facial identification systems have been implemented to identify the person’s identity whether he/she is an insider or outsider. The system will act as a tool for strengthening the safety of any organization and can also monitor in/out attendance. The proposed system aims to also prevent imperfections of manually taking attendance and allows better accuracy. Solving the problems that arose in the regulation of the old system. A combined OpenCV and deep convolutional neural networks techniques have been used to build the model. The purpose of this research is to create a face database of known people that will help to identify individuals. The developed model validated with known images and resulted accuracy is 90% and for unknown around 60%. The time of facial recognition is also recorded as a person’s time of entry and date for validation and verification. |
12,702 | Please write an abstract with title: mmWave Lens-Based MIMO System for Suppressing Small-Scale Fading and Shadowing, and key words: Array signal processing, MIMO communication, Shadow mapping, Fading channels, Antenna arrays, Lenses. Abstract: In this paper, we propose a generalized millimeter-Wave (mmWave) reconfigurable antenna multiple-input multiple-output (RA-MIMO) architecture that takes advantage of lens antennas. The considered antennas can generate multiple independent beams simultaneously using a single RF chain. This property, together with RA-MIMO, is used to combat small-scale fading and shadowing in mmWave bands. To this end, first, we derive a channel matrix for RA-MIMO. Then, we use rate-one space-time block codes (STBCs), together with phase-shifters at the receive reconfigurable antennas, to suppress the effect of small-scale fading. We consider two kinds of phase shifters: i) ideal which is error-free and ii) digital which adds quantization error. The goal of phase-shifters is to convert a complex-valued channel matrix into real-valued. Hence, it is possible to use rate-one STBCs for any dimension of RA-MIMO. We investigate diversity gain and derive an upper bound for symbol error rate in cases of ideal and digital phase-shifters. We show that RA-MIMO achieves the full-diversity gain with ideal phase-shifters and the full-diversity gain for digital phase-shifters when the number of quantization bits is higher than one. We investigate RA-MIMO in the presence of shadowing. Our analysis demonstrates that, by increasing the dimension of RA-MIMO, the outage probability decreases which means the effect of shadowing decreases. Numerical results verify our theoretical derivations. |
12,703 | Please write an abstract with title: SigPrep: Open Source Web-Based Prework for Signals and Systems [SP Education], and key words: Geometry, Differential equations, RLC circuits, Focusing, Education. Abstract: An introductory course in signals requires a wide background of prerequisites covering complex numbers, series, calculus, and basic mathematical logic. Students often fail to engage with the material and find the course difficult because they do not recall the prerequisites. Time and curricular constraints usually limit in-class review. To address these issues, we present SigPrep, a set of open source, web-based preparatory modules for introductory courses in signals. SigPrep is designed as a preclass assignment that students can do independently at a self-set pace. SigPrep is designed in WeBWorK, a widely used platform for free, open source problems for science and math classes. Using WeBWorK features, SigPrep provides students instant feedback and linkages to relevant external e-learning resources as a refresher for concepts in which they fail to exhibit adequate proficiency. Instructors are also able to track students? progress and performance. We outline the pedagogical design of SigPrep, which provides problems of particular relevance and applicability covering prerequisites for signals classes. Finally, we share results and feedback from our own experience with using SigPrep as part of our teaching of an introductory class on signals. |
12,704 | Please write an abstract with title: Sound monitoring system of operating machines in power plant, and key words: Condition monitoring, Power generation, Computer errors, Power system relaying, Hardware, Microphones, Programming, Packaging machines, Software libraries, Loudspeakers. Abstract: Despite the current technology in place, the power plant operator's job is still very demanding. Even most minor of operating errors can lead to distar. This paper introduces a sound detection system which is used to detect unusual sounds and relay the sound information of the operating machine's status to the plant operators. The hardware system consists of microphones, the multichannel A/D converter, the sound track audio DSP24, and Pentium IV PC. The Visual C++ and matlab of program languages are used for the software development. They comprise packages of functions that are WavelnOpen, MmioOpen, WaveOutOpen, and PostThread Message which are all under the Window 2000 multimedia library. We developed the real-time multichannel sound monitoring algorithm consisting of 3 classes which save files, output the sound files to the speakers, and control the threads. The frequency characteristics of the major operating machines in the plant are reported. |
12,705 | Please write an abstract with title: A 2 Gbps Custom LVDS Transceiver for the ARCADIA Project, and key words: Current measurement, Receivers, Jitter, Capacitance, CMOS technology, Transceivers, Frequency measurement. Abstract: In the scope of the ARCADIA project, a set of custom LVDS driver and receiver has been fabricated in a 110 nm CMOS technology for the ARCADIA first Main Demonstrator chip (MD1), a 512x512 monolithic, fully depleted pixel matrix. The link is designed to provide a data rate of 2 Gbps and implements a control over the driver current in order to meet the needs of a low-power mode foreseen for the MD1. This paper will present the results from the characterization of the receiver/driver in a loopback configuration, and compare them to simulations. |
12,706 | Please write an abstract with title: Design and Implementation of a Smart Solid-State Transformer Based Power Converter for Solar PV System, and key words: Bridges, Photovoltaic systems, Prototypes, Switches, Inverters, Pulse shaping methods, Power harmonic filters. Abstract: Solid state transformer (SST) is considered as an emerging technology for efficient and flexible grid integration of renewable and distributed energy sources. This paper presents design and implementation of a smart SST based power electronic converter that enables efficient grid integration of solar photovoltaic (PV) system. The designed prototype includes solar PV module, SST with dual active bridges (DAB), inverter and LCL filter. The proposed SST based system with associated controllers are implemented in Matlab/SimpowerSystem and a smaller prototype is developed using the required hardware and dSpace DSP system. The simulation and experimental results confirm that the designed SST based converter system can integrate solar PV module into grid efficiently, with the LCL filter showing good reduction of unwanted harmonics. The use of high-frequency transformer and SST provide cost savings and further avenues of control to a high-power converter through reduction in transformer size and cost, taking advantage of current pulse shaping to dictate power transfer characteristics and direction. The SST with dual active bridge increases in efficiency and power transfer depending on the relative phase angle between each Active Bridge switching. |
12,707 | Please write an abstract with title: The Hydrocuff Sensor Position Analysis for Assessing Therespiration Effect in Measuring Hemodynamics and Blood Pressure, and key words: Oscillators, Hemodynamics, Atmospheric measurements, Particle measurements, Thumb, Wrist. Abstract: The article raises the pressing topic of the hemodynamic parameters and associated errors analysis, modern methods of the pulse wave accepting and analysis are considered The relationship between systems within the human body is noted. The most important indicators of the body normal functioning are noted. The factors affecting the final values of hemodynamic parameters are described. The hydrouff method for recording a pulse wave curve is presented. The conducted experimental studies to identify the most informative sensorlocation with minimal losses in the amplitude-frequency characteristics of the recorded pulse wave signal are illustrated. The research results analysis and processing were performed using LabVIEW software. Graphic processing was carried out using MATLAB R2017b software. The pulse wave signals taken from various parts of the body were studied, it was concluded that to determine the hemodynamic parameters and blood pressure, it is sufficient to use a hydrocuff sensor fixed on the index finger. The respiratory system effect on the pulse wave amplitude-frequency characteristics has been experimentally confirmed. It is concluded that a number of studies are needed to learn the in formativeness of the respiratory signal involved in the formation of the pulse wave contour for the indirect assessment of the state of not only the cardiovascular system, but also the human respiratory system. |
12,708 | Please write an abstract with title: Forecast Municipal Solid Waste Generation in Sri Lanka, and key words: Solids, Predictive models, Solid modeling, Forestry, Artificial neural networks, Biological system modeling, Linear regression. Abstract: Municipal Solid Waste Management (MSWM) is one of the primary tasks of metropolitan local authorities in developing countries. For efficient and effective waste management schemes and scheduling, accurate forecast of Municipal Solid Waste (MSW) generation is essential, due to the uncertainties and unavailability of sufficient MSW generation information and resources in developing countries. The objectives of this paper are to identify influential variables that affect the amount of MSW generation and to predict the future MSW in Sri Lanka by consuming linear, nonlinear models, and machine learning techniques and propose a model for forecast future MSW generation using influential variables. Socio-economic data and waste generation data are collected from the Department of Census and Statistics and the National Solid Waste Management Support Center. Data preparation is done with substitute missing values by average values. Pearson correlation and Principal Component Analysis is used to finding correlation among influential variables. Linear model, Non-linear model, and machine learning model are used to forecast municipal solid waste generation in Sri Lanka. Relatively Linear regression analysis, artificial neural network (ANN), and Random forest used as a linear model, Non-linear model, and machine learning model. Relatively Correlation coefficient of linear regression classification, random forest classification, and ANN are R2=0.6973, R2=0.9608, and R2=0.9923. Based on the correlation coefficient, ANN provides higher accurate results than linear regression and random forest models. Based on the analyzed result, proposed a model for forecast future MSW generation with four influential variables that are municipal solid waste generation, total population, GDP growth rate, and Crude birth rate. |
12,709 | Please write an abstract with title: Waveguide and Gas: the Advent of a New Tool for Photonics, and key words: Optical fibers, Europe, Tools, Optical fiber communication, Brillouin scattering, Photonics. Abstract: The realisation of hollow-core fibres and nano-waveguides offers a unique opportunity to optimise the interactions between light and a gaseous medium. Stimulated Brillouin scattering is exploited to achieve unprecedented levels of amplification and to realise efficient all-optical processing. |
12,710 | Please write an abstract with title: Mirror-based silicon-photonics vertical I/O with coupling efficiency enhancement for standard single-mode fiber, and key words: SI PHOTONICS, VERTICAL I/O, CURVED MIRROR, SINGLE-MODE FIBER, BROADBAND. Abstract: A broadband, low polarization-dependent silicon-photonics vertical coupling was demonstrated based on an integrated curved mirror. Owing to its lens function, coupling efficiency between a silicon inverse taper waveguide and a standard single-mode fiber was enhanced by 1.4 and 3.4 dB for TE and TM polarization. |
12,711 | Please write an abstract with title: Geometric Deep Learning Unlocks the Underlying Physics of Nanostructures, and key words: Nanostructures, Support vector machines, Training, Machine learning, Physics, Neural networks, Convergence. Abstract: We present a learning-based technique to develop a reliable tool for discovering the underlying physics and feasibility of achieving different type of responses in electromagnetic nanostructures. |
12,712 | Please write an abstract with title: Agents Based Load Balancing with Component Distribution Capability, and key words: Load management, Computer networks, Computational modeling, Mobile agents, Workstations, Distributed computing, Distributed processing, Microprocessors, Delay, Research and development. Abstract: Distributed processing has become inevitable in many areas today. It can be found in localized systems like multiprocessor computers, in client-server network configurations, in computer clusters or in widely dispersed systems like the Internet. Development of effective techniques for task distribution is considered as one of the biggest issues in parallel and distributed operating environment. Over the past years, a number of load balancing methods has been proposed. This paper describes simulation used for methods comparison. Contrary to the vast of known methods, which are based on client/server technology, a few recent methods are based on mobile agents. This article gives short review of achievements in this area and describes simulation used for agents based load balancing methods comparison. The paper also suggests enhancement in load balancing: mobile agents could include fresh node into the system by installing and starting necessary software components. |
12,713 | Please write an abstract with title: A Review of Cyber Security and Blockchain, and key words: Systematics, Memory, Smart homes, Public key cryptography, Blockchains, Safety, Security. Abstract: Since the introduction of the Blockchain in Satoshi Nakamoto's study in 2008, Blockchain has become one of the foremost often mentioned ways to secure information storage and transfers for the trustless. This article is based on a literature review of decentralized technology and peer-to-peer systems that represents a scientific analysis of the most frequently adopted blockchain security applications in the usage of the Blockchain for cyber security functions. The findings indicate that the Internet of Things (IoT) and networks, machine visualization, and public-key cryptography hands themselves innovative to blockchain applications, just like safe storage of Personally Identifiable Information or online applications and certification schemes. This is a well-timed study based on systematic studies from several scientific journals. It will be an additional mild assessment of future prospects in Blockchain and cyber security research and blockchain security for AI data, including the safety of Blockchain in IoT and sidechain safety. |
12,714 | Please write an abstract with title: Fast Optical Switch Utilizing Coherent Detection Enabled by Cooperative Filtering of Transmission Signal and Local Oscillator (LO) Wavelength Sourced from an LO Bank, and key words: Optical fibers, Local oscillators, Filtering, Optical switches, Coherence, Optical fiber communication, Optical fiber filters. Abstract: We propose cooperative filtering scheme for transmission signals and LO channels from an LO bank; this yields 50% filter chip-size reduction and fast (3.2μs) switching. 1,856×1,856 optical switching of 128-Gb/s DP-QPSK signals is successfully demonstrated. |
12,715 | Please write an abstract with title: Power profile manipulation: a new approach for reducing test application time under power constraints, and key words: Time factors, Circuit testing, System testing, Power dissipation, Concurrent computing, Scheduling algorithm, Nondestructive testing, Minimization, Benchmark testing, CMOS integrated circuits. Abstract: This paper proposes a power profile manipulation approach which merges two distinct research directions in low power testing: minimization of test power dissipation and test application time reduction under power constraints. It is shown how complementary techniques can be easily combined through this approach to significantly increase test concurrency under power constraints. This is achieved in two steps: in the first step power dissipation is considered a design objective and, consequently, it is minimized; results are further exploited in the second step, when power becomes a design constraint under which the test application time is reduced. A distinctive feature of the proposed power profile manipulation approach is that it can be included in, and consequently improve, any existing power constrained test scheduling algorithm. Extensive experimental results using benchmark circuits, considering test-per-clock, as well as test-per-scan schemes, show that by integrating the proposed power profile manipulation approach into any existing power constrained test scheduling algorithm, savings up to 41 % in test application time are achieved. |
12,716 | Please write an abstract with title: A New Efficient and Accurate Measurement System for Microwave Human Head Imaging Applications, and key words: Microwave measurement, Antenna measurements, Microwave integrated circuits, Solid modeling, Head, Three-dimensional displays, Millimeter wave measurements. Abstract: A new efficient and accurate measurement system is proposed, aiming to improve the efficiency and accuracy of the existing microwave human head imaging (MHHI) system. The system is consisted of a non-coplanar antenna array in an adjustable platform, a RF 1-pole 16-throw(1P16T) switching subsystem and a vector network analyzer (VNA). The measurement results show that when a spherical heterogeneity with a diameter of 20mm is placed in a 3D printed human head model, our system can accurately detect the heterogeneity within 4 minutes, demonstrating its potential for real-time MHHI. |
12,717 | Please write an abstract with title: Contribution of R&D and Innovation in Technology Based Startups in India, and key words: Technology Based Startups, R&D, Innovation, Machine Learning. Abstract: In a fast-paced world where technology is changing rapidly and entrepreneurship is getting exponentially celebrated each successive day, it is a major requirement to throw light on the features that affect those startups which have a technological foundation. The need to assess and evaluate these features arises from the fact that the upcoming generation will be heavily dependent on technology and to ease veterans and novices in the field of entrepreneurship to generate significant revenue. This paper aims to investigate the contribution of Research and Development (R&D) and Innovation in technology-based startups in the Indian context. In today's world, technology-based businesses play a crucial role in fostering innovation, job creation, and economic development. We examine the link between R&D and Innovation and Revenue Growth through the utilization of Machine Learning. We draw a comparative study between different Regression models to determine the most accurate outcome for revenue generation. Our findings indicate that R&D and innovation have a substantial favorable effect on the revenue growth of India's technology-based companies, hence concluding that they should be seen as key criteria for the development of technology-based firms, and investing in them might provide favorable results. |
12,718 | Please write an abstract with title: Pavement Roughness Estimated by RGB-D Sensor Based on Three-Dimensional Reconstruction, and key words: Point cloud compression, Visualization, Solid modeling, Costs, Roads, Data collection, Surface roughness. Abstract: The measurement of the pavement roughness and the detection of road defects are two important tasks in highway engineering. In view of the high cost of pavement data collection, this research proposes a method to calculate the pavement roughness by using the economical RGB-D sensor on the mobile terminal through three-dimensional reconstruction. We propose a joint filtering algorithm based on weight judgment for the depth image restoration and a direct method for the pose estimation based on optimizing normalization coefficients of the image blocks. We calculate the pavement roughness through the three-dimensional pavement model generated by point cloud registration. Results show that the method proposed in this paper can accurately calculate the pavement roughness of different roads, and the accuracy is above 90%. |
12,719 | Please write an abstract with title: Multidimensional pseudo-maximum-likelihood pitch estimation, and key words: Multidimensional systems, Frequency estimation, Speech analysis, Speech processing, Degradation, Cepstrum, Spectral analysis, Frequency conversion, Smoothing methods, Error correction. Abstract: An estimator algorithm for the pitch of voiced speech is presented, based on the following sequence of operations: 1) linear-prediction inverse filtering; 2) short-time spectral analysis by a bank of bandpass filters; 3) envelope extraction on the filter outputs; 4) period determination on the parallel envelopes considered as a multicomponent vector signal, using an algorithm described in a previous work. Results of a comparative evaluation indicate superior immunity to added noise and to bandlimiting with loss of the fundamental component. |
12,720 | Please write an abstract with title: Development of Representative Driving Cycle for Switch Locomotive Based on Self-organizing Feature Map, and key words: Acceleration, Switches, Interpolation, Kalman filters, Principal component analysis, State estimation, Frequency measurement. Abstract: Driving cycles are widely used in testing fuel consumption and vehicle emission. To develop a representative driving cycle for Chinese switch locomotives, 224 day's driving data of assembling mode and transfer mode is collected. Linear interpolation and Kalman filter are applied to re-sample data with fixed sampling frequency and eliminate measurement deviation, respectively. Then, divide all driving data by idle start point into microtrips. This paper proposed nine characteristic parameters to quantify features of microtrips. Principal component analysis is used for decreasing the dimensions of characteristic parameters matrix. The candidate microtrips are chosen by self-organizing feature map (SOFM) according to three principal components. Finally, pick up several microtrips to synthesis representative driving cycles for switch locomotives. |
12,721 | Please write an abstract with title: A Simple Cache Coherence Scheme for Integrated CPU-GPU Systems, and key words: Protocols, Design automation, Costs, Multiprocessor interconnection, Graphics processing units, Coherence, Hardware. Abstract: This paper presents a novel approach to accelerate applications running on integrated CPU-GPU systems. Many integrated CPU-GPU systems use cache-coherent shared memory to communicate. For example, after CPU produces data for GPU, the GPU may pull the data into its cache when it accesses the data. In such a pull-based approach, data resides in a shared cache until the GPU accesses it, resulting in long load latency on a first GPU access to a cache line. In this work, we propose a new, push-based, coherence mechanism that explicitly exploits the CPU and GPU producer-consumer relationship by automatically moving data from CPU to GPU last-level cache. The proposed mechanism results in a dramatic reduction of the GPU L2 cache miss rate in general, and a consequent increase in overall performance. Our experiments show that the proposed scheme can increase performance by up to 37%, with typical improvements in the 5–7% range. We find that even when tested applications do not benefit from the proposed approach, their performance does not decrease with our technique. While we demonstrate how the proposed scheme can co-exist with traditional cache coherence mechanisms, we argue that it could also be used as a simpler replacement for existing protocols. |
12,722 | Please write an abstract with title: Performance of multicode DS/CDMA with noncoherent M-ary orthogonal modulation in multipath fading channels, and key words: Multiaccess communication, Fading, Bit error rate, Performance analysis, Analytical models, Rayleigh channels, Transceivers, Mobile communication, Interference, Gaussian approximation. Abstract: This paper presents the performance analysis and simulation of a multicode DS/CDMA system with noncoherent M-ary modulation, operating over a Rayleigh or Nakagami fading environment. This type of transceiver is specified for the reverse link of the IS-95B and cdma2000 (Radio configurations 1 and 2) systems, and is intended to serve high-rate applications such as data transfer and video communications. After a statistical characterization of the interference terms, we make use of the Gaussian approximation (GA) in order to obtain the bit error rate (BER). However, unlike other analyses relying on the GA, in our derivation we take into account the fact that all the codes transmitted by a mobile user fade in unison. As demonstrated via computer simulations, this fact is crucial to obtain a reliable estimate of the BER, especially when equal-gain combining (EGC) is used at the receiver. |
12,723 | Please write an abstract with title: Magnetic Field Calculation of Distribution Transformer with Finite Element Method, and key words: Magnetic flux density, Analytical models, Magnetic field measurement, Transformer cores, Transformers, Silicon, Loss measurement. Abstract: Transformer noise is closely relative with the magnetic field distribution in the core. In this paper, the nonlinear B-H curve of a new-type silicon steel sheet is measured. The finite element model of the distribution transformer is built to analyze the magnetic field distribution in the core. The winding current is used as the excitation source. Magnetic flux density comparison between two types of silicon steel sheets is conducted. The result shows that the core assembled with the new kind silicon steel sheet B18R065 has lower maximum magnetic flux density, which is much proper for low-noise transformer design. The proposed model is useful for further vibration and acoustic analysis of distribution transformer. |
12,724 | Please write an abstract with title: Twitter Sentiment Analysis Using BERT, and key words: Training, Sentiment analysis, Social networking (online), Bit error rate, Transfer learning, Blogs, Semantics. Abstract: Sentiment analysis (SA) in social networks is an important research area. In Twitter, popular information that is either facts or opinions is propagated throughout the network. Unlike normal documents, the restricted length of the messages along with constant changing internet slangs on Twitter had become a challenge for researchers. Bidirectional Encoder Representations from Transformers (BERT) represents the latest technology of pre-trained language models which have recently advanced a wide range of natural language processing (NLP) tasks. This paper aims to develop a proposed model using BERT for sentiment analysis tasks. This paper fine-tunes BERT with a single layer added on the top for the SA task. With fully connected neural network reaching state of the art results using simple tips preventing it from over-fitting and enabling it to be fine-tuned easily on such downstream task. The proposed method is implemented and few sets of features are tested. The model model showed that usage of stop-words inside the dataset does hinder the performance of the classifier and that by separating the positive tweets and negative tweets to extract the topics and the keywords, it achieves a better result than combining the positive and negative tweets together. Experimental results also showed the change in model performance when k random topics are selected out of a total of t topics. |
12,725 | Please write an abstract with title: Scheduling Active and Accelerated Recovery to Combat Aging in Integrated Circuits, and key words: Semiconductor device measurement, Schedules, Medical devices, Accelerated aging, Integrated circuit interconnections, Reliability engineering, Silicon. Abstract: As semiconductor chips are widely adopted in mission- or safety-critical application domains, and as the scale of these chips increases dramatically with heterogeneous integration, there is a growing interest in extending the silicon lifetime. This is especially true in scenarios like automotive, data center or medical devices. Even in consumer electronics like cell phones, the cost of the design drives up the necessity of designing highly reliable chips that last longer. Chip aging, a device-level degradation mechanism, has been a major threat to silicon lifetime. It happens to all major parts of a computing system, such as computation/memory, interconnects, and storage. This paper demonstrates this with the most critical and dominant aging phenomena, BTI, EM, and flash wearout. Although each unique aging phenomenon is characterized in its own way, damages are all caused when the design is subjected to some forms of electric stress, either voltage or current. In this paper, we look into all these major aging effects from a global view, in which we analyze the commonalities and propose to schedule the active and accelerated periods proactively to fundamentally “attack the cause” instead of “attack the symptom We present experimental results and implementation details, followed by a global scheduler that aims to conduct “scheduled recovery” in an all-in-one fashion. |
12,726 | Please write an abstract with title: A Waveguide Based Terahertz Variable Attenuator, and key words: Attenuators, Waveguide components, Instruments, Optical device fabrication, Metals, Attenuation, Microwave frequencies. Abstract: A variable attenuator is a critical component at microwave and terahertz frequencies to adjust the signal path loss-gain settings in the system. This facilitates designers and engineers to determine the optimum performance of their measurement systems and instruments. Attenuators, both fixed and tunable, are readily available at microwave frequencies however at submillimeter-wave and terahertz frequencies, design and fabrication are very challenging because such components need to be integrated with compact metal waveguide packaged sub-systems and instruments. In this work, we demonstrate a novel waveguide based variable attenuator at WR1.5 band (500-750 GHz) using a metal coated silicon slab. A piezo electric motor is used to control the position of the slab on the path of the incoming electromagnetic signal to achieve variable attenuation. The amount of attenuation is determined by the volume of silicon slab inside the waveguide and the absorption coefficient of the metal coating. |
12,727 | Please write an abstract with title: Per-survivor processing-based decoding for space-time trellis code, and key words: Convolutional codes, Maximum likelihood decoding, Partial transmit sequences, Wireless communication, Interpolation, Filters, Least squares approximation, Maximum likelihood detection, Maximum likelihood estimation, Fading. Abstract: The problem of adaptive decoding of space-time trellis codes on time-variant wireless channels is considered. We show that per-survivor processing (PSP) can be adopted to obtain approximated adaptive maximum-likelihood sequence detection (MLSD) of space-time trellis codes when there is no periodically inserted orthogonal pilot sequence. Then we propose a self-tuning least mean square (LMS)-based PSP decoder and a second-order LMS-based one. The former has the advantage that there are only fading rate-independent parameters to be predetermined, while the latter can offer fairly good performance on moderately fast time-varying channels. |
12,728 | Please write an abstract with title: Performance Evaluation of Ad-Hoc Networks in Static & Mobile Environment, and key words: Routing protocols, Wireless sensor networks, Routing, Internet of Things, Mobile ad hoc networks. Abstract: The Internet Protocol version 6 (IPv6) based routing protocol for low power and lossy networks (RPL) is used for routing in the static networks such as wireless sensor networks (WSNs) and internet of things (IoT). The research is going on to implement the RPL for mobile networks like vehicular ad-hoc network (VANET) and mobile ad-hoc network (MANET). These networks are infrastructure less and self-configuration is required to connect these mobile devices. There are some limitations of the RPL when the network is dense and mobility is introduced in it. For the solution of this problem, this paper presents the performance evaluation of RPL in the mobile network and comparison is performed with the static network. The implementation is done on the Contiki environment and results are analyzed on Cooja (network simulator). It is observed that the RPL performance depends strongly on number of sender nodes, sink nodes, and also on the inclusion of mobility to the nodes. The metric values increase with more packet loss with increasing the number of nodes in the network. Further the increase in number of sink nodes provides lesser packet loss, retransmission, and the energy consumption. The introduced mobility increases the network energy consumption. |
12,729 | Please write an abstract with title: Sensorless controls of a 7-phase bi-harmonic Surface-mounted PM Machine, and key words: Torque, Surface waves, Soft sensors, Windings, Rotors, Sensorless control, Harmonic analysis. Abstract: This paper deals with the position sensorless controls of a seven-phase bi-harmonic Surface-mounted PM machine. Due to its tooth-concentrated winding and its particular magnet segmentation, this fault-tolerant machine is characterized by an electromotive force (emf) for which the fundamental and the third harmonic are of the same order. This specificity should improve the ability of the machine to operate without position sensor. Furthermore, as the virtual machines (denoted h1, h3 and h5 machines) that are used to control the 7-phase machine have quasi-sinewave back-emfs, several so-called emf-methods to sense the rotor position are available. For h1, h3 and h1h3 controls with a Phase-locked Loop (PLL) to estimate the position, the time simulations of the drive confirm the ability of the machine to operate without position sensor while ensuring low torque ripple and quite unchanged current waveforms. An experimental evidence of this property is given for sensorless h3-control (where the back-emf fundamental is used to sense the position). |
12,730 | Please write an abstract with title: Metasurface Bound States in the Continuum Spectrum Fitting Based on Coupled Mode Theory, and key words: Couplings, Power transmission lines, Fitting, Scattering, Metasurfaces, Electromagnetics. Abstract: In this paper, a method based on coupling theory is proposed which can be used to fit bound states in the continuum (BIC) or quasi-Bound states in the continuum (quasi-BIC) curve. Compared with the preceding theory (the coupling of the bright mode and one dark mode), we use two bright modes and phase calculation so that this method can calculate a relatively high value of Q. We fitted three different Q values of lower Q, middle Q and higher Q and found that an excellent fitting effect could be obtained. And our method is more beseem for BIC or quasi-BIC, which can accurately predict the scattering spectra of quasi-BIC. |
12,731 | Please write an abstract with title: Fleet-sizing of Autonomous Vehicles based on Queueing Modeling for Transportation Service in Tourist Spot, and key words: Industries, Costs, Transportation, Minimization, Information and communication technology, Time factors, Autonomous vehicles. Abstract: In this paper, we suggest fleet-sizing of autonomous vehicle based on queueing modeling for transportation service in tourist spot. On providing transportation service with autonomous vehicles to tourist, a large number of autonomous vehicles cause more user satisfaction and require more investment. Contrariwise a smaller number of autonomous vehicles cost little investment and less user satisfaction. In other words, there are trade-off relation between user's satisfaction and investment. Therefore, we applied queueing modeling to fleet-sizing to minimize investor's investment and to satisfy user satisfaction. Operators and investors of tourist spot can obtain suitable number of autonomous vehicles for their environment by using this fleet-sizing. |
12,732 | Please write an abstract with title: A Drift-Resilient Hardware Implementation of Neural Accelerators Based on Phase Change Memory Devices, and key words: Phase change materials, Hardware, Neurons, Biological neural networks, Programming, Artificial intelligence, Voltage measurement. Abstract: Memory devices, such as the phase change memory (PCM), have recently shown significant breakthroughs in terms of compactness, 3-D stacking capability, and speed up for deep learning neural accelerators. However, PCM is affected by the conductance drift, which prevents a precise definition of the synaptic weights in artificial neural networks. Here, we propose an efficient system-level methodology to develop drift-resilient multilayer perceptron (MLP) networks. The procedure guarantees high testing accuracy under conductance drift of the devices and enables the use of only positive weights. We validate the methodology using MNIST, rand-MNIST, and Fashion-MNIST datasets, thus offering a roadmap for the implementation of integrated nonvolatile memory-based neural networks. We finally analyze the proposed architecture in terms of throughput and energy efficiency. This work highlights the relevance of robust PCM-based design of neural networks for improving the computational capability and optimizing energetic efficiency. |
12,733 | Please write an abstract with title: Converging on the optimal attainment of requirements, and key words: Costs, Navigation, Feathers, Propulsion, Laboratories, Computer science, Technology planning, Humans, Iterative methods, Time factors. Abstract: Planning for the optimal attainment of requirements is an important early lifecycle activity. However, such planning is difficult when dealing with competing requirements, limited resources, and the incompleteness of information available at requirements time. A novel approach to requirements optimization is described. A requirements interaction model is executed to randomly sample the space of options. This produces a large amount of data, which is then condensed by a summarization tool. The result is a small list of critical decisions (i.e., those most influential in leading towards the desired optimum). This focuses human experts' attention on a relatively few decisions and makes them aware of major alternatives. This approach is iterative. Each iteration allows experts to select from among the major alternatives. In successive iterations the execution and summarization modules are run again, but each time further constrained by the decisions made in previous iteration. In the case study shown here, out of 99 yes/no decisions (approximately 10/sup 30/ possibilities), five iterations were sufficient to find and make the 30 key ones. |
12,734 | Please write an abstract with title: Monitoring of soil moisture and vegetation water content variations in boreal forest from C-band SAR data, and key words: Monitoring, Soil moisture, Vegetation, Minerals, Backscatter, Biomass, Space technology, Radar remote sensing, Materials testing, Snow. Abstract: The response of ERS-2 SAR to changes in soil and forest canopy moisture is investigated at a boreal forest test region in Finland. An inversion approach to estimate moisture characteristics from SAR data is applied. The method requires that a priori information on forest biomass (stem volume) and soil type distribution is available. The inversion technique provides estimates that are here, in addition to backscattering signatures, directly compared with daily in situ moisture values. The results indicate that time-series of C-band radar observations can be used for the monitoring of boreal forest moisture variations. Especially, the detection of the driest and the wettest conditions on mineral soil sites appears to be a feasible application even for single channel radar. The obtained SAR-based soil moisture estimates showed an RMSE level of 6% units against the in situ data for pine-dominated mineral soil sites. |
12,735 | Please write an abstract with title: Spatial Load Distribution Law Based on Geographic Feature Extraction and Non-parametric Kernel Density Estimation, and key words: Urban areas, Land use planning, Estimation, Distribution networks, Feature extraction, Spatial databases, Planning. Abstract: The research on spatial load is of great significance to distribution network planning. The existing research focuses on the study of spatial load prediction, but the study of various spatial load distribution law is not sufficient. Hence, a research method of spatial load distribution based on geographic feature extraction and non-parametric kernel density estimation is proposed in the paper. Firstly, the functional communities are generated according to the actual land use of a certain place, the geographic feature information of the functional communities is extracted, and the land use types are given. Then, a clustering algorithm is applied to classify the functional communities according to the extracted information. After that, the non-parametric kernel density estimation method is used to extract the typical distribution characteristics of the load density of functional communities of different geographical categories and different land-use types. Finally, the distribution characteristics are analyzed to derive the distribution patterns of various spatial loads in the research area. The reasonableness and practicality of this method are verified by the simulation of various spatial load distribution law in a certain geographical area of a first-tier city. |
12,736 | Please write an abstract with title: Spatial relationships in electrostimulation: application to electromagnetic field standards, and key words: Electromagnetic fields, Nerve fibers, Ice, Standards development, Magnetic analysis, Magnetic stimulation, Silver, Springs, Electromagnetic modeling, Measurement standards. Abstract: Spatial relationships in electrostimulation are examined with a myelinated nerve model. Excitation thresholds are determined for: 1) terminated axon within a locally constant electric field; 2) bent axon within a locally constant field; and 3) a field of finite extent over the affected axon. For application to electromagnetic field standards, the minimum excitation threshold of the in situ electric field applies to a straight, terminated axon; a field measurement averaging distance of 5 mm is recommended. |
12,737 | Please write an abstract with title: Simulation of Heat Transfer Characteristics on Palm Oil as Electrical Insulating Material Using Finite Difference Method, and key words: Temperature, Oils, Windings, Oil insulation, Software, Heat transfer, Power transformer insulation. Abstract: The purpose of this research work is to study the heat transfer characteristics of palm oil as insulating material using finite difference method (FDM). Analysis and investigations of several heat transfer characteristics of palm oil were performed to determine the heat transfer performance of this oil. The characteristics obtained is then compared to other insulating oils to determine the performance of the insulating material. The simulation was done using Computational Fluid Dynamics (CFD) software that uses finite difference method concept that could perform 2D simulation to visualize the heat transfer characteristics inside the design of 2D transformer model geometry. The winding temperature is set into initial condition under full load temperature. The fluids properties of insulating material such as density, viscosity, thermal conductivity and specific heat capacity are set as constant, respectively. The simulation is set to constant running time of 30 minutes with interval of 5 minutes. The heat transfer characteristics such as fluid temperature, winding temperature, velocity profile, density and viscosity, heat flux from the winding and heat transfer characteristics are defined as variables, respectively. The results shows significant decrease of fluid and winding temperature of a transformer with palm oil as insulating material and has better heat transfer performance than other vegetative oils. |
12,738 | Please write an abstract with title: Logarithmic Observation of Feature Depth for Image-Based Visual Servoing, and key words: Observers, Reduced order systems, Convergence, Visual servoing, Robots. Abstract: Due to the robustness to robot modeling and camera calibration errors and avoidance of complete target geometry, image-based visual servoing has always been an important topic in the fields such as robotics, computer vision and so forth. When the image information obtained by the camera is mapped to the robotic task space to design the servoing control law, the resulting interaction matrix, which links the spatial velocity of the camera to the temporal variation of the selected image features, depends on the unknown feature depths. The use of inaccurate feature depths may influence the stability and robustness of the controller, and even cause the failure of the task. In this article, based on the perspective camera model, by employing the principle of reduced order observer, a novel logarithmic observer is presented for on-line recovery of feature depth. Compared with the typical observers now available, the presented observer offers several advantages: global convergence, a faster convergence rate of error structure than exponential error structure, a less restricted observability condition and greater robustness against measurements with noise. The comparison results of numerical simulations indicate the superiority of the presented observer, and real experiments with Kinect v2 sensor further validate the effectiveness of the presented observer in practical situation. Note to Practitioners—This article was motivated by the depth problem in the image-based visual servoing scheme, but it can also be used in other situations where the image depth information is needed, such as 3D reconstruction, robot navigation, etc. The existing depth acquisition methods include TOF sensors, stereo vision, depth observers and so on. However, TOF sensors are sensitive to light conditions, and the mounting space of stereo vision is slightly large, and there is contradiction between observation performance and computational complexity in most existing observers. In this article, a novel structure of logarithmic reduced order observer is described in detail, which can be utilized to estimate the depth information of images easily. The simulations and experiments verify the good performance of the observer. The limitations of the given observer are that the estimation accuracy is not very good under weak excitation, and the camera needs to be calibrated in advance. Future work will focus on overcoming these two limitations. |
12,739 | Please write an abstract with title: Effect of evaporative cooling of stator core on electromagnetic field of large horizontal generator, and key words: Stator cores, Cooling, Layout, Stator windings, Prototypes, Generators, Iron. Abstract: The capacity growth of flow-bulb hydrogenerator is limited by heat dissipation conditions. As an efficient cooling method, evaporative cooling technology has been successfully applied to giant hydrogenators. However, due to the size limitation, the evaporation cooling technology which is directly cooled the stator winding in the vertical hydrogenerator cannot applied to the flow-bulb hydrogenerator. This paper introduces a kind of stator iron core evaporative cooling technology, and analyzes its influence of the layout of the cooling tubes on the electromagnetic field. This paper takes a 50MW generator which has been put into operation as the prototype, and sets up four kinds of cooling tubes layout schemes. The electromagnetic field simulation based on time-step finite element method is used to compare these schemes with the prototype. The calculation results show that the reasonably arranged cooling tubes can not only enhance the cooling effect but also not greatly increase the stator iron loss, which is beneficial to improve the capacity. |
12,740 | Please write an abstract with title: Improving Noise Robust Automatic Speech Recognition with Single-Channel Time-Domain Enhancement Network, and key words: Training, Training data, Speech enhancement, Signal processing, Noise robustness, Time-domain analysis, Automatic speech recognition. Abstract: With the advent of deep learning, research on noise-robust automatic speech recognition (ASR) has progressed rapidly. However, ASR performance in noisy conditions of single-channel systems remains unsatisfactory. Indeed, most single-channel speech enhancement (SE) methods (denoising) have brought only limited performance gains over state-of-the-art ASR back-end trained on multi-condition training data. Recently, there has been much research on neural network-based SE methods working in the time-domain showing levels of performance never attained before. However, it has not been established whether the high enhancement performance achieved by such time-domain approaches could be translated into ASR. In this paper, we show that a single-channel time-domain denoising approach can significantly improve ASR performance, providing more than 30 % relative word error reduction over a strong ASR back-end on the real evaluation data of the single-channel track of the CHiME-4 dataset. These positive results demonstrate that single-channel noise reduction can still improve ASR performance, which should open the door to more research in that direction. |
12,741 | Please write an abstract with title: Secure IoT Device Architecture Using TrustZone, and key words: Engines, Monitoring, Computer architecture, Software, Software measurement, Semantics. Abstract: IoT realizes efficient system such as smart cities, smart factories, and smart agriculture. However, there are risks of cyber attacks against the IoT with the potential to cause serious damage. To protect the IoT systems, protection of the entire system including end-point IoT devices is essential. However, existing software-based protection is insufficient against recent sophisticated attackers who disable or bypass security mechanisms. In this paper, to ensure correct operations of security mechanisms, we propose a secure IoT device architecture using TrustZone. A monitoring engine can be protected from attacks by deploying the engine in a secure world which is isolated from a non-secure. Here, a problem is that each secure and non-secure world has its own virtual memory and OS, thus the monitoring engine in the secure world cannot directly monitor software in the non-secure world. To cope with the semantic gap between the non-secure world and the secure world, the proposed architecture has two monitoring engines: a monitoring engine in the non-secure world for measuring software in the non-secure world and a monitoring engine in secure world for attesting the engine in non-secure world. Moreover, we implement the architecture and show the proposed architecture is feasible on the basis of its evaluation results. |
12,742 | Please write an abstract with title: Identity Authentication in Two-Subject Environments Using Microwave Doppler Radar and Machine Learning Classifiers, and key words: Authentication, Radar, Feature extraction, Receivers, Heuristic algorithms, Radar antennas, Microwave theory and techniques. Abstract: Identity authentication based on Doppler radar respiration sensing is gaining attention as it requires neither contact nor line of sight and does not give rise to privacy concerns associated with video imaging. Prior research demonstrating the recognition of individuals has been limited to isolated single-subject scenarios. When two equidistant subjects are present, identification is more challenging due to the interference of respiration motion patterns in the reflected radar signal. In this research, respiratory signature separation techniques are functionally combined with machine learning (ML) classifiers for reliable subject identity authentication. An improved version of the dynamic segmentation algorithm (peak search and triangulation) was proposed, which can extract distinguishable airflow profile-related features (exhale area, inhale area, inhale/exhale speed, and breathing depth) for medium-scale experiments of 20 different participants to examine the feasibility of extraction of an individual’s respiratory features from a combined mixture of motions for subjects. Independent component analysis with the joint approximation of diagonalization of eigenmatrices (ICA-JADE) algorithm was employed to isolate individual respiratory signatures from combined mixtures of breathing patterns. The extracted hyperfeature sets were then evaluated by integrating two different popular ML classifiers, k-nearest neighbor (KNN) and support vector machine (SVM), for subject authentication. Accuracies of 97.5% for two-subject experiments and 98.33% for single-subject experiments were achieved, which supersedes the performance of prior reported methods. The proposed identity authentication approach has several potential applications, including security/surveillance, the Internet-of-Things (IoT) applications, virtual reality, and health monitoring. |
12,743 | Please write an abstract with title: Two-dimensional polarization switching of lithium niobate, and key words: Lithium niobate, Etching, Shape, Electrodes, Photonic crystals, Nonlinear optics, Substrates, Optical polarization, Optical refraction, Optical variables control. Abstract: Summary form only given. We report a two-step oxidation and switching process on Z-cut congruent grown LiNbO/sub 3/. By employing the polarization-induced positive charge effect at the inverted surface domain boundary, we enable a 2D differential switching mechanism that can lead to the formation of a 2D, /spl chi//sup (2)/ nonlinear LiNbO/sub 3/ photonic crystal of arbitrary domain shape. |
12,744 | Please write an abstract with title: Interdigital Capacitors and Their Application to Lumped-Element Microwave Integrated Circuits, and key words: Capacitors, Application specific integrated circuits, Microwave integrated circuits, Low pass filters, Capacitance, Dielectric substrates, Circuit analysis, Frequency response, Computational geometry, Conductors. Abstract: An analysis of the frequency response of interdigital capacitors, which leads to an optimal design, is given along with an expression for their static gap capacitance. The capacitor Q is given in terms of its geometry which consists of a planar interdigital thin-filrn conductor deposited on the surface of a relatively high dielectric constant substrate. Capacitance values ranging from 0.1 to 10 pF at L band with measured Q's in excess of 400 are realizable using 2-mil line and space widths on a 99.5-percent alumina substrate with a dielectric constant of 10.3. Experimental results obtained with a lumped-constant nine-section S-band Chebyscheff low-pass filter realized using spiral inductors and optimal designed interdigital capacitors are shown to be in excellent agreement with theory. The filter had less than 0.8-dB insertion loss and greater than 25dB return loss in the passband. The filter occupies an area 6.50 by 200 roils on a 24-mil-thick substrate. |
12,745 | Please write an abstract with title: Physiological Features of Cardiac Ventricle and Valve Dynamics from Wearable Radio-Frequency Sensors, and key words: Radio frequency, Signal processing, Valves, Feature extraction, Timing, Reliability, Biomedical monitoring. Abstract: Early detection of cardiovascular diseases via non-invasive, convenient, and continuous monitoring is crucial to reducing preventable deaths. This paper illustrates such monitoring using wearable near-field radio-frequency sensors to analyze ventricle and valve transients, which can be used as indicators of myriad cardiac disorders. We applied a novel vector injection signal processing method to improve timing consistency in ventricular contraction, ventricular relaxation, and valve opening extraction. The median relative timing error in valve opening detection was 14.7ms and 37.8ms for semilunar and atrioventricular valves, respectively, as benchmarked by the S1 and S2 heart sounds from a synchronous phonocardiogram. Clinical Relevance— No wearable sensor currently exists to conveniently and reliably evaluate ventricular and valvular dynamics, specifically valvular opening. Beyond extraction of the heart rate and its variation, the method in this paper has the potential to enable non-invasive measurements of detailed cardiac cycle timing features including valve openings, isovolumetric contraction/relaxation times, and ejection periods, improving the monitoring of patient health away from clinical healthcare centers. |
12,746 | Please write an abstract with title: A System Level Approach for Online Junction Temperature Measurement of SiC MOSFETs Using Turn-On Delay Time, and key words: Temperature measurement, Delays, Logic gates, Junctions, Resistance, MOSFET, Silicon carbide. Abstract: In this paper, a new online junction temperature monitoring approach for SiC MOSFETs is proposed by measuring the turn-on delay time using the system microcontroller and intelligent gate drive. Specifically, the intelligent gate drive converts the turn-on delay time to the pulse-width of a digital signal. Then the high-resolution capture module in the microcontroller (with 300 picoseconds resolution) is utilized to precisely measure the turn-on delay time. To improve the measurement sensitivity, the intelligent gate drive circuit implements a large gate resistance during the measurement period and immediately switches back to low gate resistance value for normal operations. A prototype is built, and the proposed circuit is tested in both double pulse switching tests and continuous converter operations. From the experimental results, an accurate junction temperature measurement is achieved in real-time with an error less than 1°C. |
12,747 | Please write an abstract with title: Initial Propulsion System Study for the Futuristic Hyperloop Transportation System: Design, Modeling, and Hardware in the Loop Verification, and key words: Propulsion, Synchronous motors, Mathematical models, Costs, Permanent magnet motors, Transportation, Inverters. Abstract: Recently, the proposal for a futuristic mode of transportation known as the Hyperloop has been popularized. Currently, there are only some reports regarding the design of the Hyperloop. More specifically, reports regarding the propulsion system design methodology for Hyperloop is minimal. Thus, this paper provides an initial steppingstone to modeling and simulation study for the propulsion system in a Hyperloop. The main contribution of this study is to provide a relatively simple design methodology for any future Hyperloop endeavors. This is shown using state of the art simulators to aid in designing the propulsion system. The design revolves around the linear synchronous motor based on field-oriented control through a three – phase inverter. PSIM is used to develop the model and design the full power system and controller. This includes the DC-DC converter, battery system model, three – phase inverter, and the motor controller. The motor used for modelling is a rotary permanent magnet synchronous motor. Finally, hardware in the loop technology is used to verify and validate the design. The controller design is tested through a Texas Instrument digital signal processor. The real time verification shows matching results with the offline simulation model. |
12,748 | Please write an abstract with title: The simulation of diffusion of innovations using new opinion dynamics, and key words: Technological innovation, Social sciences, Decision making, Entertainment industry, Media, Timing, Intelligent agents. Abstract: In this paper, we used Ishii et al.'s new opinion dynamics theory that includes both trust and distrust in human relationships to simulate the transition of opinions of new entrants. When the mass media had a uniform impact on the market, it is shown that people's opinion distribution is biased toward media-led. We have observed that the media affects those in the market first, and then new entrants. It has also been shown that when the connection between people is strong, they are more influenced by others. In other words, in order to make the opinions of consumers who enter the market later positive(adopt), it is shown that we need the consumers with positive opinions that exist in the market in advance, mass media that encourages adopt (stronger is preferable), and dense people network. |
12,749 | Please write an abstract with title: Hierarchically nested channels for fast squeezing interfaces with reduced thermal resistance [IC cooling applications], and key words: Thermal resistance, Application specific integrated circuits, Bonding, Thermal conductivity, Thermal loading, Electronics cooling, Conducting materials, Kinetic theory, Surface resistance, Flip chip. Abstract: We report a simple method to improve bondline formation kinetics by means of a hierarchical set of channels patterned into one of the surfaces. These channel arrays are used to improve the gap squeezing and cooling of single and multiple flip chip electronic modules with highly viscous fluids and thermal pastes. They allow a fast formation of thin gaps or bond lines by reducing the pressure gradient in the thermal interface material as it moves in and out of the gap. Models describing the dynamics of Newtonian fluids in these "hierarchically nested channel" (HNC) interfaces combine squeeze flow and Hagen-Poiseuille theories. Rapid bond line formation is demonstrated for Newtonian fluids and selected particle-filled pastes. Modeling of particle-laden polymeric pastes includes Bingham and Hershel-Bulkley fluid properties. Bond line formation and thermal resistance is improved particularly for high viscosity-high thermal conductivity interface materials created from higher volumetric particle loadings or for thermal interface materials with smaller filler particle diameters. |
12,750 | Please write an abstract with title: Reconfigurable receiver approach for 4G terminals and beyond, and key words: Wireless LAN, Radio frequency, 3G mobile communication, Communication standards, CMOS technology, Multiaccess communication, Baseband, Filters, Mixers, Low-noise amplifiers. Abstract: An overview on RF-front-end architectures and technologies for future reconfigurable mobile communication systems (4G-systems) is given. Favourable standard combinations are WCDMA and WLAN. RF front-end key components like low noise amplifiers, mixers, synthesizers and baseband variable gain amplifiers are treated, particularly with regard to reconfigurable systems. |
12,751 | Please write an abstract with title: Online Inverter Nonlinearity Compensation Method Based on Current Injection, and key words: Space vector pulse width modulation, Semiconductor device modeling, Voltage source inverters, Process control, Switches, Steady-state, Semiconductor diodes. Abstract: The non-linearity of the voltage source inverter (VSI) causes an error between the output voltage and the reference voltage, therefore introduces phase current harmonic interference. This paper proposes a method for online compensation of inverter nonlinear errors. The effect of parasitic capacitance is modeled by injecting increasing or decreasing current. The voltage drop of the semiconductor diode is obtained through the datasheet. Two non-linear functions are used to compensate for the above non-linear factors, the current loop control period and dead time are confirmed during the auto-tuning process. The method proposed in this paper does not require any additional filters that cause phase delay and reduced amplitude. The experimental results are obtained by a commercial permanent magnet synchronous motor (PMSM) drive platform based on a DSP controller. The experiments verify the proposed online compensation method. |
12,752 | Please write an abstract with title: Adaptive Energy Shaping Control of a Class of Nonlinear Soft Continuum Manipulators, and key words: Manipulators, Damping, Adaptation models, Computational modeling, Bending, Solid modeling, Prototypes. Abstract: Soft continuum manipulators are characterized by low stiffness that allows safe operation in unstructured environments but introduces underactuation. In addition, soft materials such as silicone rubber, which are commonly used for soft manipulators, are characterized by nonlinear stiffness, while pneumatic actuation can result in nonlinear damping. Consequently, achieving accurate control of these systems in the presence of disturbances is a challenging task. This article investigates the model-based adaptive control for soft continuum manipulators that have nonlinear uniform stiffness and nonlinear damping, that bend under the effect of internal pressure, and that are subject to time-varying disturbances. A rigid-link model with virtual elastic joints is employed for control purposes within the port-Hamiltonian framework. The effects of disturbances and model uncertainties are estimated adaptively. A nonlinear controller that regulates the tip orientation of the manipulator and that compensates the effects of disturbances and of model uncertainties is then constructed by using an energy shaping passivity-based approach. Stability conditions are discussed highlighting the beneficial role of nonlinear damping. The effectiveness of the controller is assessed with simulations and with experiments on a soft continuum manipulator prototype. |
12,753 | Please write an abstract with title: Cataracts and cell-phone radiation, and key words: Humans, Lenses, Electromagnetic radiation, Telephone sets, Eyes, Frequency, Polarization, Laboratories, Animals, Ear. Abstract: A concern that is often expressed about microwave radiation is the induction of cataracts. The formation of lens opacities in the eyes of laboratory animals following acute microwave exposure is well established. It is generally accepted that acute exposure to higher levels of CW radiation causes various degrees of lens opacification in laboratory animals at many microwave frequencies. However, the exact conditions under which these changes may occur in human beings are a subject of debate. Nevertheless, linear extrapolations of computed results indicate that the incident density required for the human eye to reach the cataractogenic threshold may only be slightly lower than that needed for rabbits. |
12,754 | Please write an abstract with title: Atypical event and typical pattern detection within complex systems, and key words: Event detection, Data analysis, Displays, Software algorithms, Clustering algorithms, Pattern analysis, Aerospace safety, Software packages, Data systems, Time measurement. Abstract: Algorithms have been developed to find typical patterns and atypical events within complex data systems. A software package called The Morning Report was developed in which these algorithms were applied to digital flight data for commercial airlines. These systems contain many sets of data with hundreds of variables being measured over time, generally resulting in many gigabytes of data to be analyzed. Using statistical and mathematically based algorithms this software identifies atypical flights as well as which flight parameters and which flight phases are atypical. These algorithms also cluster the flights into a finite number of distinct patterns. This clustering allows the flight analyst to focus on atypical flights as well as the typical flight patterns discovered, removing the need to explore each flight separately. The Morning Report software was designed to run each night, producing a report in the morning. This report identifies the characteristics of only the newly added flights, but it uses data from previous flights to help establish the baseline. The report consists of interactive analysis tools that allow for plotting of significant flight parameters for each atypical flight as compared to the typical flights, as well as plots that contrast a flight pattern of interest to any other flight pattern or to all patterns combined |
12,755 | Please write an abstract with title: Thermal control of Kerr microresonator soliton comb via an optical sideband, and key words: Phase noise, Time-frequency analysis, Optical solitons, Lasers and electrooptics, Amplitude modulation, Thermal noise, Optical pumping. Abstract: We demonstrate the thermal control of a microresonator soliton comb via an optical sideband, in which the detuning is passively fixed, enabling the robust and frequency-tunable soliton comb as well as the phase noise reduction. |
12,756 | Please write an abstract with title: Development of a high-current low-inductance crowbar switch for FRX-L, and key words: Switches, Capacitors, Coaxial cables, Testing, Laboratories, Breakdown voltage, Rails, Roentgenium, Performance evaluation, Magnetic fields. Abstract: The design and test results of a crowbar switch developed for the formation of long-lifetime field-reversed configurations are presented. These research efforts are being pursued at the FRX-L facility at Los Alamos National Laboratory using the "Colt" capacitor bank (a 36 /spl mu/F Shiva Star bank module capable of storing up to 250 kJ) and at the Air Force Research Laboratory using the "Formation" capacitor bank (consisting of three parallel banks identical to Colt). The crowbar switch design includes four Maxwell rail-gap switches mounted on a cable header that transitions from the capacitor bank bus plates to 48 RG 17/14 coaxial cables. For the testing performed at AFRL, a dummy load was set up to simulate the magnetic field coils of the actual experiment. Tests thus far have demonstrated the crowbarring of peak currents up to 1.25 MA. Breakdown within the cable header due to the initial high voltage applied from the bank has been successfully suppressed by the cable feed-through design, proper placement of Mylar sheets around the switch for insulation, and replacement of air in the header with SF/sub 6/. Timing for the triggering of the crowbar is somewhat critical, as inductance in the switch increases when the switch is triggered with lower voltages across the switch rails. At the higher bank charge voltages, the charge-flow ratings on the rail-gap switches are exceeded; however, other than requiring that the rail electrodes in the switches be cleaned more frequently, no detrimental effects have been observed from the excessive charge flow. |
12,757 | Please write an abstract with title: Deep Reinforcement Learning for DC-DC Converter Parameters Optimization, and key words: Training, Power system measurements, Optimization methods, DC-DC power converters, Reinforcement learning, Voltage, Data models. Abstract: Reinforcement learning (RL) is a type of machine learning in which an agent teaches itself by interacting with the environment. A RL-based parameter optimization method is proposed to improve the efficiency of a DC-DC power converter. More specifically, deep Q network (DQN) methods are utilized to optimize the power converter's parameter designs under current, voltage ripple, and volume limitations. Spice simulation is used to determine power losses on semiconductors. Combined with an optimal design of the inductor, the overall efficiency of power converters is obtained. The results show that an optimal design is obtained by using the DQN algorithm. |
12,758 | Please write an abstract with title: Temperature Driven Current–Voltage Characteristics of Ionic Liquid Type Intelligent Connection Device, and key words: Temperature measurement, Temperature, Temperature dependence, Electrodes, Ions, Microscopy, Current measurement. Abstract: The temperature dependence of an intelligent connection (IConnect) device, in which an ionic liquid (IL) plays an essential role in a memristive function is presented in this study. An appropriate choice of IL and dissolved metal ion species can control the volatility of the IL-IConnect device. The temperature dependence of the IL-IConnect device was strong, although the change in current–voltage characteristics was reversible in response to temperature variations. The device’s potential as a physical reservoir-computing device is studied. |
12,759 | Please write an abstract with title: Modelling and Testing of Emergency Braking in Autonomous Vehicles, and key words: Analytical models, Technological innovation, Computational modeling, Radar, Vision sensors, Mathematical models, Standards. Abstract: In this paper the autonomous emergency braking system (AEB) is implemented for autonomous and semiautonomous vehicles using the RADAR and the vision sensors with different angles of coverage present in the AEBTestBench in the ADAS toolkit in Matlab R2021b. Using this test bench we have simulated 5 different standard EURO NCAP AEB Test scenarios which are discussed in detail later in the paper. The conditions and the standards for these tests are in accordance with the established standards as per EURO NCAP and the simulation is correspondingly designed. The equations for the ego vehicle's time-to-collision(TTC), Forward Collision Warning (FCW) reaction time and the stopping time of the ego vehicle are mathematically modelled and their results are analysed for each of these 5 scenarios and any recurring errors are analysed and corrected, the results obtained allows us to test the efficiency of the AEB system. |
12,760 | Please write an abstract with title: An Incremental Training on Deep Learning Face Recognition for M-Learning Online Exam Proctoring, and key words: Training, Deep learning, Performance evaluation, Wireless communication, Visualization, Face recognition, Detectors. Abstract: The ability to provide an academic resource for a remote student has increased the use of m-learning in distance education. Online exams as a tool to measure the student's outcome need a proctoring method to detect cheats. Several methods had been proposed to fulfill these needs, from a no-proctoring exam to automatic online supervision. A visual verification during an online exam is required to verify a student took the exam, therefore a CNN-FR is used to do it. The problem that exists in face recognition is the system invariant against pose and lighting variations. In some proposed methods, an additional process such as image equalization and SURF features is executed to overcome the problems. In this paper, we proposed an incremental training process on face recognition training, so there will be no need to add another process so it will reduce the computation cost and time. To acquired high accuracy we've analyzed four different face detectors, which are Haar-cascade, LBP, MTCNN, and Yolo-face, as in face recognition a Facenet model was tested. The evaluation of the proposed method shows that a deep learning face detector has overcome the others, on the other hand, an incremental training of facenet model results in a smaller dataset size by 1% with a faster training time of 7% on Yolo-face face detector and 64% on MTCNN compared to batch training. The proposed method results in an equally high accuracy rate as in batch training (98%). |
12,761 | Please write an abstract with title: An evaluation of image noise variance for time-of-flight PET, and key words: Positron emission tomography, Image reconstruction, Image resolution, Nonlinear filters, Computed tomography, Performance gain, Smoothing methods, Thumb, Gain measurement, Noise measurement. Abstract: We describe a simple theoretical framework for linear time-of-flight (TOF) reconstruction and evaluate several alternative TOF filters. We implement a capability for direct computation of TOF noise variance images and evaluate the gain in image variance for TOF vs. non-TOF for 1.26 nsec TOF resolution on the Siemens biograph HiRez PET/CT. The variance calculation is validated by comparing to pixel variances computed from replicated synthetic data. TOF reconstruction does not give a uniform improvement in image noise variance, but improves variance more toward the periphery of an object than at its center. The TOF performance gain depends on how random coincidences are processed, and is greater when the randoms fraction is higher, or when randoms smoothing is not employed. We confirm that TOF gain is greater for larger objects than for smaller ones, but find discrepancies with the D/Deltax rule of thumb. With 1.26 nsec resolution on the HiRez, TOF image noise gain factors (non-TOF/TOF variance) range from 1.5 to 2.2 on the measured data at hand. We predict that an improvement in TOF resolution by a factor of 2 (to 600 psec) could improve image variance on this machine by an additional factor of 1.8. We find that confidence weighted TOF reconstruction under-performs non-TOF reconstruction for objects whose diameters are small compared to the TOF resolution |
12,762 | Please write an abstract with title: Hybrid workflow of Simulation and Deep Learning on HPC: A Case Study for Material Behavior Determination, and key words: Training, Materials science and technology, Scientific computing, Computational modeling, Simulation, Neural networks, Training data. Abstract: Nowadays, machine learning (ML), especially deep learning(DL) methods, provide ever more real-life solutions. However, the lack of training data is often a crucial issue for these learning algorithms, the performance accuracy of which relies on the amount and the quality of the available data. This is particularly true when applying ML/DL based methods for specific areas e.g. material characteristics identification, as it requires huge cost of time and manual power getting observational data from real life. In the mean while, simulations on HPC have already been commonly used in computational science due to the fact that it has the ability of generating sufficient and noise free data, which can be used for training the ML/DL based models. However, in order to achieve accurate simulation results the input parameters usually have to be determined and validated by a large number of tests. Furthermore, the evaluation and validation of such input parameters for the simulation often require a deep understanding of the domain specific knowledge, software and programming skills, which can in turn be solved by ML/DL based methods. In this paper, a novel hybrid workflow combining a multi-task neural network and the simulation on high performance computers(HPC) is proposed, which can address the problem of data sparsity and reduce the demand for expertise, resources, and time in determining the validated parameters for simulation. This work is demonstrated through experiments on determination of material behaviors, and the results prove a promising performance (MSE = 0.0386) through this workflow. |
12,763 | Please write an abstract with title: Fake-Face Image Classification using Improved Quantum-Inspired Evolutionary-based Feature Selection Method, and key words: Feature extraction, Evolutionary computation, Quantum computing, Deep learning, Clustering algorithms, Software, Manuals. Abstract: Deep learning models have been quite successful in discriminating synthesized or edited fake-face images. However, in the case of small training data, transfer-learning is rather preferable. This is a complex process for high dimensional feature space due to the curse of dimensionality. To mitigate the same, this paper proposes a new feature selection method for the classification of manually created fake-face images. In the proposed method, a pre-trained deep learning model is used to extract features of an image. Next, an optimal feature subset is selected from the extracted features through an improved quantum-inspired evolutionary algorithm. Lastly, the elicited features are considered to perform the classification. Experiments are conducted on a publicly available manually created fake-face image dataset, namely Real and Fake Face Detection by Yonsei University. The performance of the proposed method is compared with two methods in terms of classification accuracy and the number of selected features. The experimental comparisons exhibit that the proposed method achieves promising results among the considered methods. |
12,764 | Please write an abstract with title: Meta-Reinforcement Learning in Non-Stationary and Dynamic Environments, and key words: Task analysis, Training, Robots, Adaptation models, Multitasking, Inference algorithms, Gaussian mixture model. Abstract: In recent years, the subject of deep reinforcement learning (DRL) has developed very rapidly, and is now applied in various fields, such as decision making and control tasks. However, artificial agents trained with RL algorithms require great amounts of training data, unlike humans that are able to learn new skills from very few examples. The concept of meta-reinforcement learning (meta-RL) has been recently proposed to enable agents to learn similar but new skills from a small amount of experience by leveraging a set of tasks with a shared structure. Due to the task representation learning strategy with few-shot adaptation, most recent work is limited to narrow task distributions and stationary environments, where tasks do not change within episodes. In this work, we address those limitations and introduce a training strategy that is applicable to non-stationary environments, as well as a task representation based on Gaussian mixture models to model clustered task distributions. We evaluate our method on several continuous robotic control benchmarks. Compared with state-of-the-art literature that is only applicable to stationary environments with few-shot adaption, our algorithm first achieves competitive asymptotic performance and superior sample efficiency in stationary environments with zero-shot adaption. Second, our algorithm learns to perform successfully in non-stationary settings as well as a continual learning setting, while learning well-structured task representations. Last, our algorithm learns basic distinct behaviors and well-structured task representations in task distributions with multiple qualitatively distinct tasks. |
12,765 | Please write an abstract with title: Explainable Feature Embedding using Convolutional Neural Networks for Pathological Image Analysis, and key words: Pathology, Visualization, Solid modeling, Dictionaries, Image analysis, Vector quantization, Receivers. Abstract: The development of computer-assisted diagnosis (CAD) algorithms for pathological image analysis is an important research topic. Recently, convolutional neural networks (CNNs) have been used in several studies for the development of CAD algorithms. Such systems are required to be not only accurate but also explainable for their decisions, to ensure reliability. However, a limitation of using CNNs is that the basis of the decisions made by them are hardly interpretable by humans. Thus, in this paper, we present an explainable diagnosis method comprising two CNNs playing different roles. This method allows us to interpret the basis of the decisions made by the CNN from two perspectives: statistics and visualization. For the statistical explanation, the method constructs a dictionary of representative pathological features. It performs diagnoses based on the occurrence and importance of learned features referred from its dictionary. To construct the dictionary, we introduce a vector quantization scheme for CNN. For the visual interpretation, the method provides images of learned features embedded in a feature space as an index of the dictionary by generating them using a conditional autoregressive model. The experimental results showed that the proposed network learned pathological features that contributed to the diagnosis and yielded an area under the receiver operating curve (AUC) of approximately 0.93 for detecting atypical tissues in pathological images of the uterine cervix. Moreover, the proposed method demonstrated that it could provide visually interpretable images to show the rationales behind its decisions. Thus, the proposed method can serve as a valuable tool for pathological image analysis in terms of both its accuracy and explainability. |
12,766 | Please write an abstract with title: Concepts and techniques for short optical pulse characterization, and key words: Optical pulses, Pulse measurements, Chirp, Frequency measurement, Spectrogram, Optical interferometry, Ultrafast optics, Electric variables measurement, Delay, Optical filters. Abstract: The measurement of the electric field of short optical pulses is an active domain of research and development as many applications demand accurate characterization. Characterization techniques can be classified according to general concepts that condition their properties and implementation. The concepts of spectrography, interferometry and tomography are reviewed and examples of corresponding techniques are presented. |
12,767 | Please write an abstract with title: A 20–42-GHz IQ Receiver in 22-nm CMOS FD-SOI With 2.7–4.2-dB NF and −25-dBm IP1dB for Wideband 5G Systems, and key words: Wideband, Noise measurement, Receivers, Gain, Tuning, Transistors, Impedance. Abstract: This article presents a 20–42-GHz in-phase and quadrature (IQ) receiver in 22-nm CMOS fully depleted silicon on insulator (FD-SOI). The receiver includes a wideband low noise variable-gain amplifier (LN-VGA), double-balanced IQ mixers, wideband I/Q generation network and wideband local oscillator (LO) driver, low-pass filters, and wideband intermediate frequency (IF) amplifiers. The measured receiver has a peak conversion gain of 25.3 dB with a 3-dB bandwidth of 19.8–42 GHz and an I and Q bandwidth of 5.7 GHz and covers the 5G millimeter-wave (mm-wave) band. The measured single-sideband noise figure (NF) is 2.7–4.2 dB at 24–42 GHz with an IP1dB of −26 to −23 dBm. The I/Q downconverter consumes a total of 102 mW from 0.8- and 1.6-V supplies. The IP1dB can be improved by 5 dB with an NF degradation by only 1.2 dB using RF VGA gain control. At peak gain and −8-dB VGA setting, the receiver dynamic range is 64–68 dB for a 100-MHz bandwidth, which is very high for low power consumption. The gain and phase mismatch between the I and Q channels is < 0.6 dB and <6°, respectively. To the best of the authors’ knowledge, this is the first wideband I/Q receiver that covers the entire mm-wave 5G band based on GF 22-nm CMOS FD-SOI. The application area is multistandard multigigabit per second communication systems. |
12,768 | Please write an abstract with title: Behavior Recognition Algorithm Based on the Fusion of SE-R3D and LSTM Network, and key words: Feature extraction, Convolutional neural networks, Convolution, Data mining, Kernel, Training, Three-dimensional displays. Abstract: In view of the fact that the existing behavior recognition algorithms cannot fully extract abstract behavior features, this paper proposes a SE-R3D-LSTM behavior recognition algorithm based on 3D residual convolutional neural network (R3D), which integrates Squeeze-and-excitation network (SENet)and long short-term memory (LSTM). First of all, a residual module is added to the 3D Convolutional Neural Network (3D-CNN) to avoid problems such as gradient dispersion caused by the deepening of the network layer; Secondly, not only the global average pooling layer but also the global maximum pooling layer is used in the SENet network, which can fully extract global information and achieve feature calibration. In the meantime, expand the SENet network to three-dimensional, which can make the connection of the spatiotemporal feature channels closer. Afterwards, the 3D-SE module is introduced into the R3D network, which can enhance the effective spatiotemporal features and suppress the invalid spatiotemporal features; Since, because LSTM can perform timing modeling on high-level features and learn more effective feature information, the LSTM network is introduced into the SE-R3D network. Finally, Softmax is used for classification. Experimental results show that the recognition rate of the SE-R3D-LSTM network on the UCF101 data set reaches 96.5%. |
12,769 | Please write an abstract with title: Determining the optimal geometry of planar antenna arrays for joint estimating the coordinates of two signal sources on azimuth, and key words: Wireless communication, Time-frequency analysis, Shape, Receiving antennas, Directive antennas, Throughput, Telecommunications. Abstract: This paper describes a method for reducing errors in estimating the spatial coordinates of radio emission sources. The problem of increasing the accuracy of direction-of-arrival estimation is the most relevant due to the growth in the number of subscribers, as well as the decrease in the frequency resource, while at the same time limiting computing resources. Several approaches to solving this problem are known from the references. However, an approach based on the use of an expression for calculating the Cramer-Rao lower bound is promising. This expression defines the limit of direction-of arrival accuracy, below which no algorithm is able to fall. However, it is possible to lower this limit even lower. In this article, a new expression has been obtained that describes how the location of antenna elements in space affects the magnitude of errors in the direction finding of two signals. It is shown that this dependence is non-linear. Namely, the errors are determined through the difference of cosines from the coordinates of the antennas in the Cartesian system. Thus, antenna arrays have been obtained that can reduce the magnitude of direction-of arrival bearings errors. The paper presents the results of computer simulation to confirm the proposed approach. |
12,770 | Please write an abstract with title: Feature-Integrated Structural Optimization Design Method and Performance Evaluation for Hollow Slab Structures, and key words: Optimization, Reliability, Topology, Slabs, Load modeling, Indexes, Finite element analysis. Abstract: In view of the main contradiction between traditional topology optimization for basic theory research and the actual requirements of comprehensive performance for modern industrial products, a feature-integrated structural optimization design method with an appropriate reliability, a light weight, and excellent mechanical properties for continuum structures was established based on the reliability-based topology optimization of modified minimum weight with a displacement constraint (RBTO-MMWDC) model. Taking hollow slab structures as an example, a graphical user interface based on the optimization code was developed for practical applications. Furthermore, the topological layout of β =3.0 was selected for geometric model reconstruction and mechanical property evaluations were performed using the finite element method (FEM) and experiments. Compared with those of the traditional structure, the compression resistance and bending resistance properties of the optimized structure are improved by 29% and 75%, respectively, and the first-order natural frequency is increased by 101%. In addition, the results of the experiments are consistent with the simulation in terms of tendency. The bending resistance strength and stiffness of the optimized structure are improved by 61% and 55%, respectively. This study provides a theoretical reference and feasible solution for the feature-integrated design of continuum structures in engineering applications. |
12,771 | Please write an abstract with title: MMSE-OSIC Detection for the User Terminal in a LEO Multibeam Satellite Forward Link, and key words: Satellites, Simulation, Bit error rate, Low earth orbit satellites, Detectors, Receivers, Parity check codes. Abstract: Satellite communications are expected to collaborate with 5G techniques in the future. In this paper, a detector based on the minimum mean square error (MMSE) criterion is designed at the receiver of a LEO satellite system to cancel co-channel interference (CCI) in a predetermined order successively, which is called ordered successive interference cancellation (OSIC). In order to make the detector have stronger ability to mitigate interference, low density parity check (LDPC) coding and soft demodulation schemes are applied with the OSIC jointly to improve our proposed MMSE-OSIC detector's performance. In the simulation analysis, we present the bit error rate (BER) performance of our proposed detector in an AWGN channel. Numerical results show that compared to the results of the conventional detection in existing literatures, the MMSE-OSIC detector can reduce the BERs for fixed signal-to-noise ratio (SNR) values. It means our proposed detector can be employed at the receiver with high service availability and reliability guaranteed. |
12,772 | Please write an abstract with title: Calibration method of SOC characteristics of spacecraft battery pack simulator, and key words: Space vehicles, Estimation, Voltage, Batteries, Calibration, State of charge. Abstract: A significant parameter of the spacecraft battery pack simulator is the state of charge (SOC) parameter, which is one of the parameters that users are most concerned about during the use of the spacecraft battery pack simulator. Other parameters of the spacecraft battery pack simulator, such as terminal voltage, current, pressure, temperature, etc., are always given together with the value of the state of charge (SOC) in which they are located. The battery SOC parameter is a process quantity, and only one SOC estimation value can be obtained. In the battery simulation, the simulator gives the time-varying SOC value during the charging and discharging process according to the initial SOC state, charging and discharging conditions. Therefore, the time-varying SOC value given by the battery pack simulator must be accurately calibrated to ensure the accuracy of the battery pack simulator SOC change. |
12,773 | Please write an abstract with title: Longitudinal control of heavy trucks in mixed traffic: environmental and fuel economy considerations, and key words: Fuel economy, Traffic control, Vehicles, Pollution, Performance analysis, Analytical models, Testing, Acceleration, Programmable control, Adaptive control. Abstract: In this paper, longitudinal vehicle-following controllers for heavy trucks with different spacing policies are designed, analyzed, simulated, and experimentally tested, and their performance in mixed traffic with passenger vehicles is evaluated. A new vehicle-following controller for trucks, which has better properties than existing ones with respect to performance and impact on fuel economy and pollution during traffic disturbances, is developed. The response of trucks to disturbances caused by lead passenger vehicles is smooth due to the limited acceleration capabilities of trucks whether they are manual or equipped with adaptive cruise control (ACC) systems. Vehicles following the truck are therefore presented with a smoother speed trajectory to track. This filtering effect of trucks is shown to have beneficial effects on fuel economy and pollution. However, it creates large intervehicle gaps that invite cut-ins from neighboring lanes, creating additional disturbances. These cut-ins, under certain realistic scenarios, may reduce any benefits obtained by the smooth response of trucks as well as increase travel time. The results of this paper indicate possible benefits trucks may have in mixed traffic and also reinforces what is already known-that trucks could be detrimental to traffic flow |
12,774 | Please write an abstract with title: Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion Strategy, and key words: Image quality, Visualization, Databases, Semantics, Neural networks, Feature extraction, Quality assessment. Abstract: Image quality assessment (IQA) is very important for both end-users and service-providers since a high-quality image can significantly improve the user's quality of experience (QoE). Most existing blind image quality assessment (BIQA) models were developed for synthetically distorted images, however, they perform poorly on in-the-wild images, which are widely existed in various practical applications. In this paper, inspired by perceptual visual quality being affected by both low-level visual features and high-level semantic information, we propose an effective BIQA model for in-the-wild images by considering rich features extracted from the convolution neural network (CNN). Specifically, we propose a staircase structure to hierarchically integrate the features from intermediate layers of the CNN into the quality-aware feature representation, which enables the model to make full use of visual information from low-level to high-level and are more suitable for the in-the-wild IQA task. Experimental results show that the proposed model outperforms other state-of-the-art BIQA models on six in-the-wild IQA databases by a large margin. Moreover, the proposed model is flexible and can be replaced with popular CNN models to meet the various needs of practical applications. |
12,775 | Please write an abstract with title: Better Application of Bayesian Deep Learning to Diagnose Disease, and key words: Deep learning, Machine learning algorithms, Uncertainty, Sociology, Transforms, Tools, Prediction algorithms. Abstract: A significant, but challenging, phase in healthcare is detecting and predicting status for a complex human disease. By the year 2050, the global population over 60 years of age will be 2 billion, according to the World Health Organization. For most health conditions, age is the principal cause. For the analysis of multi-dimensional patient's data, machine learning provides a principled approach to develop and compare sophisticated, automated and objective algorithms. Massive public health problems and economic burdens have been generated by complex human diseases such as cancers, Alzheimer, Parkinson, Motor Neuron, cardiovascular, and respiratory diseases. Technically, deep learning concept is derived machine learning under AI (Artificial Intelligence) that follows the brain structure and function in processing data and decision making. Deep learning uses many layers of nonlinear processing units to work with complex data sets and can transform them to analyze the outcome. It has inspired a lot of interest in its use for medical imaging problems. In order to ensure patient safety by clinical diagnostics, Bayesian Deep Learning makes more precise and intelligent predictions.The goal of this research was to optimize and implement a better algorithm for deep learning. A research field for growth is to complement deep learning with Bayesian thought. The performance of the method proposed is dependent on the sensitivity, specificity, accuracy and precision of the algorithms. The current implementation supports showing that a mixture of deep learning algorithms can be found in the best model. Machine Learning tools such as Tensorflow 2.0, Scikit-Learn, Pandas, Matplotlib & numpy are used for execution with powerful Python in this proposed application. Bayesian Deep Learning's proposed approach has outperformed current methods of diagnosis & prediction and demonstrates high precision and great potential to develop clinical tools. With more than 98 percent accuracy, one prototype and 2 data sets are used for clinical diagnosis and predictions for cancer and diabetes. |
12,776 | Please write an abstract with title: A Project to Correct Mill Power Factor: The Selection and Deployment of a Second Capacitor Bank, and key words: Capacitors, Power harmonic filters, Harmonic analysis, Generators, Production, Load flow, Harmonic distortion. Abstract: Selecting the proper size capacitor bank for power factor correction at a pulp mill, with an existing capacitor bank in service, requires many hours of computer modeling and system simulations. This article discusses the calculations involved in specifying the capacitor bank and evaluates the system response to transient switching events involving the two capacitor banks. Finally, it provides a comparison of the results of the calculations with field measurements recorded during the commissioning of the new capacitor bank. |
12,777 | Please write an abstract with title: list-reviewer, and key words: IEEE. Abstract: The conference offers a note of thanks and lists its reviewers. |
12,778 | Please write an abstract with title: A Speech Emotion Recognition Solution-based on Support Vector Machine for Children with Autism Spectrum Disorder to Help Identify Human Emotions, and key words: Support vector machines, Emotion recognition, Autism, Computational modeling, Speech recognition, Feature extraction, Noise measurement. Abstract: Children who fall into the autism spectrum have difficulty communicating with others. In this work, a speech emotion recognition model has been developed to help children with Autism Spectrum Disorder (ASD) identify emotions in social interactions. The model is created using the Python programming language to develop a machine learning model based on the Support Vector Machine (SVM). SVM has proven to yield high accuracies when classifying inputs in speech processing. Individual audio databases are specifically designed to train models for the emotion recognition task. One such speech corpus is the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), which is used to train the model in this work. Acoustic feature extraction will be part of the pre-processing step utilizing Python libraries. The libROSA library is used in this work. The first 26 Mel-frequency Cepstral Coefficients (MFCCs) and the zero-crossing rate (ZCR) are extracted and used as the acoustic features to train the machine learning model. The final SVM model provided a test accuracy of 77%. This model also performed well when significant background noise was introduced to the RAVDESS audio recordings, for which it yielded a test accuracy of 64%. |
12,779 | Please write an abstract with title: State Assignment Using a New Embedding Method Based on an Intersecting Cube Theory, and key words: Equations, Hypercubes, Lattices, Minimization, Very large scale integration, Programmable logic arrays, Binary codes, Permission, Synthesizers, Flowcharts. Abstract: The controller state assignment methodology proposed here features two improvements over existing methods. First, a larger set of predictive minimizations in the control flowgraph is performed. Secondly, the embedding phase uses a new theory of intersecting cubes in the Boolean lattice. Practical results using the VLSI Technology Logic-Synthesizer on both PLA and multi-level logic demonstrate the effectiveness of the approach. |
12,780 | Please write an abstract with title: The optimum automatic thresholding using the phase of Zernike moments, and key words: Image edge detection, Polynomials, Histograms, Robust stability, Digital images, Fourier transforms, Pattern recognition, Neural networks, Noise level, Phase detection. Abstract: A new technique for automatic thresholding of images has been introduced. This technique is based on maximizing the correlation between Zernike moments' phases of the gray-level and binary images of the same objects. This technique of gray level thresholding is unimodal. Thresholding using Zernike moments would be of interest to pattern recognition applications where Zernike moments are used as features. The experimental results show that correlating the phases of Zernike moments yields the optimal threshold values. These results also indicate the robustness and stability of the technique when dealing with noisy sample images. |
12,781 | Please write an abstract with title: Personal Space Evaluation and Protection in Social VR, and key words: Three-dimensional displays, Conferences, Avatars, Design methodology, User interfaces. Abstract: Social VR has been widely promoted and popularized in recent years. Due to the immersion characteristic of VR, although people do not have physical contact in the virtual space, they still have judgements on distance and may feel annoyed when their personal space is intruded. Social VR users want to communicate with their virtual friends in the space. Meanwhile, keep a comfortable distance from other avatars and protect their personal space. In this paper, we evaluate user's perception and comfortable level of personal distance and compare four different methods to protect personal space in social VR. |
12,782 | Please write an abstract with title: Measurement Virtualization Technologies for Intelligent Information and Measurement Systems, and key words: Instruments, Computational modeling, Computer architecture, Internet of Things, Intelligent agents, Virtualization, Task analysis. Abstract: The article presents theoretical and methodological approaches to the formation of an ensemble of intelligent measurements for the tasks of metrological analysis and synthesis using virtual measuring circuits. A comparative analysis of measurement virtualization technologies for various platform solutions is presented. The procedures for integrating an ensemble of intelligent measurements into virtual measuring instruments are considered. The concept of an information-measuring system as a multi-agent system is presented. The concept of an intelligent agent for the tasks of reconfiguration of the measuring circuit has been introduced. |
12,783 | Please write an abstract with title: A Novel Electromagnetic Imaging Method for Nonweak Inhomogeneous Objects, and key words: Technological innovation, Inverse problems, Electromagnetic scattering, Imaging, Mixture models, Nonhomogeneous media, Numerical models. Abstract: Electromagnetic inverse scattering imaging of nonweak inhomogeneous objects is a non-linear and ill-posed problem, which makes effective reconstruction of the target difficult. To solve this problem, we propose a novel electromagnetic imaging method. Under the framework of Born iterative (BI) formulation, a Gaussian mixture model (GMM) is first constructed to exploit the inhomogeneity a priori information and then the variational Bayesian inference is conducted. In addition, the generalized approximate message passing method (GAMP) is used to decouple the likelihood function and further improve the calculation speed. Numerical experiments prove the effectiveness of the proposed method. |
12,784 | Please write an abstract with title: Design of 2-array microstrip patch antenna excited by waveguide endwall coupler, and key words: Microstrip antennas, Patch antennas, Millimeter wave technology, Waveguide transitions, Millimeter wave communication, Antennas and propagation, Millimeter wave circuits, Antenna feeds, Bandwidth, Planar arrays. Abstract: This paper describes the 2-array microstrip patch antenna using an aperture-coupled waveguide at 24 GHz. The antenna consists of a waveguide feed and two patches that are excited by the endwall coupler. This antenna has the gain of 12 dBi and the bandwidth of 2.4 GHz. Half power beamwidth is 30 degree on the E-plane and 68 degree on the H-plane. |
12,785 | Please write an abstract with title: Inverter for microturbines based on multiobjective genetic algorithm, and key words: Genetic algorithms, Fuzzy control, Pulse width modulation inverters, Fuzzy logic, Algorithm design and analysis, Power system harmonics, Turbines, Voltage, Pulse width modulation, Power generation. Abstract: In this paper, authors present a new design method for pulse width modulation inverters in microturbines by using a multiobjective genetic algorithm. The design problem is converted to an equivalent optimization problem, and then a multiobjective genetic algorithm is adopted to find a solution. The genetic algorithm is proposed to design a fuzzy controller. In this GA approach, an individual is constructed to represent the fuzzy controller. Multiobjective genetic algorithm confers a number of advantages over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions rather than a single solution estimate. This optimal fuzzy controller is suitable for the specific harmonic elimination PWM technology, as demonstrated by the examples given in this paper |
12,786 | Please write an abstract with title: Crucial and Redundant Shares and Compartments in Secret Sharing, and key words: Cryptography, Companies, Telematics, Computer science, Computer networks, Periodic structures, Mathematical model. Abstract: Secret sharing is the well-known problem of splitting a secret into multiple shares, which are distributed to shareholders. When enough or the correct combination of shareholders work together the secret can be restored. We introduce two new types of shares to the secret sharing scheme of Shamir. Crucial shares are always needed for the reconstruction of the secret, whereas mutual redundant shares only help once in reconstructing the secret. Further, we extend the idea of crucial and redundant shares to a compartmented secret sharing scheme. The scheme, which is based on Shamir's, allows distributing the secret to different compartments, that hold shareholders themselves. In each compartment, another secret sharing scheme can be applied. Using the modifications the overall complexity of general access structures realized through compartmented secret sharing schemes can be reduced. This improves the computational complexity. Also, the number of shares can be reduced and some complex access structures can be realized with ideal amount and size of shares. |
12,787 | Please write an abstract with title: An Extensive Analysis of Task Scheduling Algorithms Based on Fog Computing Qos Metrics, and key words: Measurement, Energy consumption, Costs, Scheduling algorithms, Heuristic algorithms, Quality of service, Smart grids. Abstract: Fog computing is an approach used by Cloud service providers to provide better performance and quality of services to their customers. Fog computing is a technique that works seamlessly between the users and the Cloud service providers. It is used for various applications like Smart cities, smart grids, and healthcare. This kind of application can generate variable lengths of tasks at the user layer to the fog layer. These generated tasks need to be properly assigned to the suitable fog nodes because all types of tasks are relatively connected with QoS metrics like makespan, reliability, latency, energy consumption etc.,. Many authors proposed various scheduling algorithms for allotment of tasks to the right fog nodes. This paper focused on reviewing various authors' work related to scheduling of the various types of tasks with fog nodes based on the metrics. These metrics are compared and analyzed with other scheduling algorithms metrics. This comparison and evaluation of different metrics are used to identify the impact of one metric on another metric, so that researchers can focus on optimized metrics during the scheduling of various tasks with fog nodes. |
12,788 | Please write an abstract with title: Performance analysis for multi-node decode-and-forward relaying in cooperative wireless networks, and key words: Performance analysis, Decoding, Relays, Wireless networks, Phase shift keying, Signal to noise ratio, Fasteners, Computer simulation, Computational modeling, Protocols. Abstract: We provide symbol-error-rate (SER) performance analysis for a multi-node wireless network employing a decode-and-forward cooperation strategy. An approximate expression for the SER of an N relay network with M-ary phase-shift-keying (M-PSK) signalling is derived at high enough signal-to-noise ratio (SNR). The approximation hinges on ignoring terms in the SER which are of order higher than (N+1) in the SNR. The validity of the derived approximate SER is justified through computer simulations for networks with different numbers of relays. The simulation results show that the approximation is tight at high SNR and that the cooperation protocol can achieve full diversity order equal to the number of cooperating terminals. |
12,789 | Please write an abstract with title: Offline optical character recognition (OCR) method: An effective method for scanned documents, and key words: Optical Character Recognition, Computer vision, Image Processing, Correlation. Abstract: Optical Character Recognition (OCR) is a major computer vision task by which characters of image are detected and recognized by comparing to training set images. Process of detecting character is one of the perplexing tasks in computer vision. This is because of input image often not correctly aligned or because of noise. This paper presents a complete Optical Character Recognition (OCR) system which is worked for English character mostly for Calibri font. This system first corrects skew of image if input image is not correctly aligned followed by noise reduction from input image. This process is passed through line and character segmentation that are passed into the recognition module and recognize characters. By experimenting with a set of 50 images, average achievement is 92%, 98% is for Calibri font. Moreover, the developed technique is computationally efficient and requires less time than other Optical character recognition system. |
12,790 | Please write an abstract with title: Electrophysiological Evidence of Gender differences in Chinese words recognition, and key words: Enterprise resource planning, Psychology, Neuroimaging, Electroencephalography, Surfaces, Magnetic resonance imaging, History, Diseases, Frequency conversion, Hospitals. Abstract: Event-related potentials were recorded in order to study gender difference in the brain processes of verbal recognition memory. 15 male and 15 female healthy volunteers received a Chinese words recognition task. Both males and females showed a positive-going parietal old/new effect, but females demonstrated larger P500 amplitudes and shorter P500 latency than males. Furthermore, the parietal old/new effect of males was significantly left-lateralized, while that of females showed more bilateral pattern. Only males elicited obvious frontally distributed old/new effect between 250 and 350 ms, which was negative-going and right-lateralized. These findings suggested that gender differences did exist in the recognition processing of Chinese words. Some of the gender differences could be interpreted as reflecting different interpreted as reflecting the involvement of different neural structures. In addition, males and females may use different strategies to make correct discrimination |
12,791 | Please write an abstract with title: Entropy- and complexity-constrained classified quantizer design for distributed image classification, and key words: Image classification, Spatial databases, Decision trees, Classification tree analysis, Image coding, Data mining, Shape, Multimedia systems, Multimedia databases, Image databases. Abstract: In this paper, we address the issue of feature encoding for distributed image classification systems. Such systems often extract a set of features such as color, texture and shape from the raw multimedia data automatically and store them as content descriptors. This content-based metadata supports a wider variety of queries than text-based metadata and thus provides a promising approach for efficient database access and management. When the size of the database becomes large and the number of clients connected to the server increases, the feature data requires a significant amount of storage space and transmission bandwidth. Thus it is useful to devise techniques to compress the features. In this paper, we propose an optimal design of a classified quantizer in a rate-distortion-complexity optimization framework. A decision tree classifier (DTC) is applied to classify the compressed data. We employ the generalized Breiman, Freidman, Olshen, and Stone (G-BFOS) algorithm to design the optimal pre-classifier, which is a pruned sub-tree of the decision tree, and to perform the optimal bit allocation among classes. The optimization is carried out based not only on a rate budget, but also on a coding complexity constraint. We illustrate this framework by showing a texture classification example. Our results show that by using a classified quantizer to encode the features, we are able to improve the percentage of correct classification also leads to a reduction of the number of images transmitted between server and client. |
12,792 | Please write an abstract with title: Secrecy Performance Analysis for An-Aided Linear ZFBF in MU-MIMO Systems with Limited Feedback, and key words: Performance analysis, Array signal processing, Transmitters, Downlink, Upper bound, Security, Signal to noise ratio. Abstract: Although there have been extensive works on artificial-noise-aided (AN-aided) secure transmission schemes for multi-antenna systems, there is still lack of study on the AN-aided scheme employing the widely used linear zero-forcing beamforming (ZFBF) for systems with multiple distributed users. Particularly, there is no analytical secrecy performance for general system settings with neither perfect nor imperfect channel state information of the legitimate users at the transmitter (CSIT). This paper considers the AN-aided ZFBF based on the quantized CSIT for secure communication in the downlink multiuser multi-antenna systems with an external multi-antenna eavesdropper. We develop an approximated closed-form lower bound on the ergodic rate of each legitimate user (LU), and also a closed-form upper bound on the maximum achievable ergodic rate for each LU's messages over the eavesdropper's channel without assuming any asymptotes for system parameters. Then, an approximated closed-form lower bound on the ergodic secrecy rate of each LU follows. Simulation results validate our analytical secrecy performance results and also the effectiveness of AN in enhancing the secrecy performance of linear ZFBF. |
12,793 | Please write an abstract with title: A Synthesis Approach to Acoustic Wave Ladder Filters and Duplexers Starting With Shunt Resonator, and key words: Chebyshev approximation, Resonant frequency, Capacitors, Inductors, Acoustic waves, Optimization, Prototypes. Abstract: In this article, we explore how acoustic wave filters starting with shunt resonator require particular reflection phase conditions to ensure that the synthesized filter is feasible. The position of transmission zeros (TZs) along with the phase of the objective filter function might lead to nonfeasible solutions where the first and last resonators require elements with positive reactance slope in the static branch, or equivalently, a nonphysical negative static capacitor. Since the reflection phase of a duplexer-oriented filter is fixed to reduce loading effects, the feasibility problem is solved by bringing the resonance frequency of the first resonator beyond the central frequency of the counter band. However, this entails surpassing the limits of the electromechanical coupling coefficient. We demonstrate how two reactive elements at the input overcome this resonance position limitation and provide a simple rule to decide the right topology. The position of the first TZ of duplexers will play an important role. Moreover, we provide rules on the reflection phase values that ensure that all resonators have a capacitive static branch. |
12,794 | Please write an abstract with title: Visual Sensor Network Task Scheduling Algorithm at Automated Container Terminal, and key words: Task analysis, Sensors, Containers, Visualization, Vision sensors, Wireless sensor networks, Scheduling algorithms. Abstract: The visual sensor network (VSN) is an important part of the automated container terminal. VSN present also a of problems such as the redundant number of visual sensors and limited computing resources. Different vision sensors are reported in literature when about computing resources (CR) reduced number of publications provides information about required CR as part of visual sensor network. In this context the paper propose solution that transforms the visual sensor network terminal task scheduling process into Markov Decision Process. Thus, a visual sensor network terminal task scheduling algorithm based on Deep-Q Learning is considered. In this algorithm, an innovative return value function is proposed to achieve better algorithm convergence. To verify the effectiveness of the model, several experiments were carried out under different conditions. The result shows that the recognition rate is improved by using the proposed algorithm. Based on considered method the number of visual sensors can be reduced, that conducts to a rational use of limited computing resources. At the same time cost reduction is also provided that is an important requirement of port operation optimization. |
12,795 | Please write an abstract with title: On Parametric Hardware Trojans, and key words: Visualization, Correlation, Taxonomy, Hardware, Semiconductor process modeling, Trojan horses, Mathematical model. Abstract: With the eminence of third party foundry practice, insertion of hardware trojans in ICs is becoming a major threat. Insertion techniques of these hardware trojans are getting easier with sophisticated yet expensive equipment. The same very equipment which was basically used for IC surgeries is used for inserting hardware trojans. This research brings in focus the stealthiest trojans of the decade - Parametric Hardware Trojans (PHTs). It also proposes a taxonomy to address PHTs. Related detection techniques for PHTs are also discussed and Side Channel Analysis based detection model is suggested as the most effective detecting techniques against PHTs. The efficiency of the proposed model is also checked through FPGA based simulation of PHTs. |
12,796 | Please write an abstract with title: Exploring deterministic frequency deviations with explainable AI, and key words: Costs, Europe, Power system stability, Predictive models, Data models, Power markets, Stability analysis. Abstract: Deterministic frequency deviations (DFDs) critically affect power grid frequency quality and power system stability. A better understanding of these events is urgently needed as frequency deviations raise the need for substantial control actions and thereby increase cost of operation. DFDs are partially explained by the rapid adjustment of power generation following the intervals of electricity trading, but this intuitive picture fails especially before and around noonday. In this article, we provide a detailed analysis of DFDs and their relation to external features using methods from eXplainable Artificial Intelligence. We establish a machine learning model that well describes the daily cycle of DFDs and elucidate key interdependencies using SHapley Additive exPlanations. Thereby, we identify solar ramps as critical to explain patterns in the Rate of Change of Frequency (RoCoF). |
12,797 | Please write an abstract with title: Reliability Evaluation for Manufacturing System Based on Dynamic Adaptive Fuzzy Reasoning Petri Net, and key words: Manufacturing systems, Reliability, Loading, Petri nets, Fuzzy reasoning, Real-time systems. Abstract: Due to failure, partial failure, or maintenance, the capacity of each machine is multi-state. Therefore, the limited relationship between the capacity of each machine and the input raw materials has to be considered. Additionally, in order to utilize the machine more effectively, the capacity of the buffers cannot be ignored, too. In this paper, a dynamic adaptive fuzzy reasoning Petri net is proposed to evaluate reliability of a manufacturing system with multiple production lines. Firstly, the model of manufacturing system is conducted, and from the perspective of demand, the minimum capacity vector and loading vector of each machine are determined. Secondly, knowledge representation and rules are formulated to establish weighted fuzzy petri nets. And the weighted fuzzy Petri net is adaptive based on the real-time level of buffers, the minimum capacity vector and loading vector. Moreover, the efficiency of product production can be improved while ensuring system reliability by adjusting the buffer level. Finally, a numerical experiment is used to demonstrate the application of our method. |
12,798 | Please write an abstract with title: Access Schemes for an IP-Over-WDM Metro Network, and key words: Wavelength division multiplexing, Access protocols, Optical packet switching, Optical receivers, Optical fiber networks, Media Access Protocol, Optical transmitters, Availability, Communication networks, Urban areas. Abstract: Novel distributed medium access protocols for a time-slotted WDM metro ring employing optical packet switching and supporting variable-length data packets like IP datagrams directly in the optical layer is proposed and compared with other schemes |
12,799 | Please write an abstract with title: AMERICA@UTN - Learning through Advanced Communication and Information Technology Resources and Means @UTN [1], and key words: Information technology, Space technology, Mobile communication, Education, Computer aided instruction, Communications technology, Educational technology, Information systems, Mobile computing, Technology planning. Abstract: The main goal of this project is to optimize the teaching/learning process by the proper use of mobile devices. To meet that goal, we are developing a new learning platform that will integrate existing applications into others specifically designed. Our purpose is to develop that platform based on the latest and most advanced Communication Means and Information Resources available which may allow universal access to the opportunities that distance education affords. So this is about a project which, resting on communicational possibilities offered by ubiquitously distributed networks (wired or wireless), will provide access to potential educators and students irrespective of their geographical location or the type of devices used (PC’s, Notebooks, Tablet PC’s, Pocket PC’s and Smart Phones). This project will provide: • A simple and effective interface capable of providing access to NICT-based distance learning services; • A platform that can be adapted to any kind of network irrespective of its physical structure or access speed. |
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