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16,000 | Please write an abstract with title: High Efficiency Laser-Sustained Plasma Source, and key words: plasma technology, laser-sustained plasma, UV radiance. Abstract: Laser-sustained plasma (LSP) featured by high radiance in the ultraviolet (UV) spectral range is found to be powerful in high resolution inspection and spectroscopy applications. In this paper, we demonstrate significant enhancement of power conversion efficiency in LSP excited by focused orthogonal laser beams. The "reservoir" boundary formed by the laser field traps the high temperature zone of the plasma. LSP with UV radiance >20% conversion efficiency has been achieved experimentally, which is the highest reported value to our knowledge. This work paves a novel way of generating high radiance UV sources by spatial manipulation of excitation laser beam. |
16,001 | Please write an abstract with title: Efficient Random Access Protocol for Multi SIM Multi Standby Devices in 5G and B5G Networks, and key words: Performance evaluation, 5G mobile communication, Simulation, Hidden Markov models, Radiofrequency integrated circuits, Delays, Internet of Things. Abstract: Multi SIM (Multi Subscriber Identity Module) Multi Standby (MSMS) feature-enabled devices have gained huge popularity among smartphone users as it offers the flexibility to use multiple SIM cards of the same or different operators on the same handheld device. To reduce cost, these MSMS devices are predominantly built with a single Radio Frequency Integrated Circuit (RFIC), restricting Protocol Stack Unit (PSU) of only one SIM to communicate with the cellular network at a time. Random Access (RA) procedure in MSMS devices experiences two delays: (i) typical RACH contention time, (ii) the PSU wait time to get RFIC to transmit RA messages. IoT (Internet of Things) devices, Single SIM, and Multi SIM Multi Active (MSMA, with an equal number of SIMs and RFICs) smartphones do not have the above second delay. As a result, MSMS device with a single RFIC has to face both delays to get network access even in 5G and future networks. To improve RA performance of MSMS devices, we propose a novel algorithm called, Network Assisted Random Access for MSMS (NARAM), which enables the 5G network to estimate the prevailing congestion levels using Hidden Markov Model (HMM) and reduce the first delay by tuning the network configuration appropriately. The simulation results reveal that the MSMS RA delay reduced by 8% from legacy. Furthermore, the RA failure rate of MSMS devices dropped by 23% when compared to the legacy. |
16,002 | Please write an abstract with title: Design and Simulation of a Low PDP Full Adder by Combining Majority Function and TGDI Technique in CNTFET Technology, and key words: Power demand, Simulation, Voltage, Logic gates, Capacitance, Software, CNTFETs. Abstract: In this study, a full adder based on the transmission gate diffusion input (TGDI) technique and majority function is presented in carbon nanotube field-effect transistor (CNTFET) technology. The proposed design consists of 18 transistors and is simulated using HSPICE software at a voltage of 0.8 V, a frequency of500 MHz, and a load capacitance of 1 fF in 32 nm technology. The simulation results show the reasonable performance of the sum and carry output signals as well as the improvement in power consumption, latency, power-delay product (PDP), and energy-delay product (EDP). The power consumption and delay of the proposed design are, respectively, 697 nW and 13.8 ps, which result in a PDP of 9.67 fJ and an EDP of 1.34 $\times 10^{-28}$ Js. |
16,003 | Please write an abstract with title: Synthesis of Two Classes of Acoustic Surface-Wave Filter Tap Weights, and key words: Filters, Transfer functions, Chebyshev approximation, Fingers, Attenuation, Passband, Acoustic transducers, Frequency response, Poles and zeros, H infinity control. Abstract: Techniques are presented for the synthesis of interdigital acoustic surface-wave filter tap weights so as to give transfer functions having a Chebyshev stopband attenuation characteristic with a specified minimum attenuation, along with a single-peaked or a Chebyshev double-peaked passband characteristic. The techniques first give the gain zero locations, and as a result are very flexible. Linear phase or minimum or maximum phase-shift characteristics are obtainable. The transfer function can be factored into two sets of zeros which can be realized as two separate anodized transducers which, when operated with a multistrip coupler, will give the desired overall transfer function. Also, it is shown that the class of designs having a double-peaked passband can be realized in the form of an unanodized phase-reversal transducer (PRT) in cascade with a second transducer having very smooth anodization and no phase reversals. The fact that such designs have such smooth anodization with relatively few small taps can help in obtaining precision performance. |
16,004 | Please write an abstract with title: Kernelized Correlation Filtering algorithm fused with Kalman Filter, and key words: Solid modeling, Machine learning algorithms, Target tracking, Weapons, Filtering algorithms, Cameras, Kalman filters. Abstract: The KCF algorithm updates the model by sampling each frame of the image. When the object is obscured by the object, the wrong sample will be introduced in the model update, making the tracking effect worse or even the target lost. Aiming at the above problems, KCF algorithm is fused with Kalman filter. But in fact, the target motion in the image is nonlinear due to the translation and rotation of the camera, while Kalman filter can only deal with the linear motion of the target. Through the transformation of world coordinate system - camera coordinate system - image coordinate system - pixel coordinate system, the two-dimensional coordinates of the target in the pixel coordinate system of KCF algorithm are converted into the three-dimensional coordinates in the world coordinate system by combining the distance from the camera to the target and the camera's attitude angle and offset. The nonlinear motion of the target in the image is converted into the linear motion in the world coordinate system. According to the assumed target motion model, the Kalman filter is used to estimate the optimal three-dimensional coordinates of the target, and then the target position is converted into the target position modifier in the KCF algorithm. The experimental results show that the improved algorithm is more robust than KCF when the target is occluded. |
16,005 | Please write an abstract with title: Thermal Stress Oriented Dispatch Strategy for Paralleled Grid-Connected Converters in Electric Vehicle Charging Stations, and key words: Reactive power, Digital twin, Switching frequency, Prototypes, Electric vehicle charging, Real-time systems, Temperature control. Abstract: The severe thermal stress is justified to be one major failure cause in power semiconductor devices. Most of the previous thermal stress reduction methods only scope on the local controller level for the individual converter. In the proposed method, a centralized system level strategy is designed to deal with the varying charging profiles in the electric vehicle charging station, where the proposed dispatch algorithm makes full use of the local control level thermal stress reduction methods, including the reactive power injection and the switching frequency variation, to adjust the power loss and reshape the thermal profiles for multiple grid-connected converters. The proposed thermal stress oriented dispatch (TSOD) strategy is described in this paper and its superior performance on the junction temperature profiles is validated through a real-time model-in-the-loop testing and a digital twin experimental prototype. |
16,006 | Please write an abstract with title: Oxidation of Eu in BaMgAl/sub 10/O/sub 17/:Eu/sup 2+/ blue phosphor for plasma display panel (PDP), and key words: Oxidation, Phosphors, Electromagnetic wave absorption, Solid state circuits, Thermal quenching, Heating, Paramagnetic resonance, Neutrons, Magnetic flux, Heat treatment. Abstract: The blue phosphor, BaMgAl/sub 10/O/sub 17/:Eu/sup 2+/ showing a blue emission band at,about 450 nm were prepared by solid state reaction of BaCO/sub 3/, Al/sub 2/O/sub 3/, MgO and Eu/sub 2/O/sub 3/ with AlF/sub 3/ as a flux. The thermal quenching of BaMgAl/sub 10/O/sub 17/:Eu/sup 2+/ phosphor significantly reduces the intensity of the blue emission. It is reduced by an amount of 50% after heating at around 800/spl deg/C for 1 hr. The red emission in the 580/spl sim/720 nm region of /sup 5/D/sub 0//spl rarr//sup 7/F/sub 1/ and /sup 5/D/sub 0//spl rarr//sup 7/F/sub 2/ transition of Eu/sup 3+/ is produced from the phosphor heated above 1,100/spl square/. The EPR spectrum also reveals that some part of Eu/sup 2+/ ions are oxidized to trivalent ions above 1,100/spl square/ at around 90 and 140 mT. This oxidation evidence is also detected from XANES absorption spectra for L/sub 111/ shell of Eu ions: an absorption peak is at 6,977 eV of Eu/sup 2+/ and 6,984 eV of Eu/sup 3+/. The combined X-ray and neutron data suggests that the new phase of EuMgAl/sub 11/O/sub 19/ magnetoplumbite structure may be formed by heat treatment. |
16,007 | Please write an abstract with title: Instrument meteorological conditions (IMC) certification of the MH-60S helicopter common cockpit, and key words: Instruments, Meteorology, Certification, Helicopters, Aerospace electronics, Military aircraft, Hardware, Testing, Procurement, Costing. Abstract: The US Navy Helicopter Master Plan detailed a type/model/series (T/M/S) reduction of current helicopter inventory from eight to two (ME-60R and MH-60S). The goal of this T/M/S reduction was procurement and operating cost reduction, improved warfighting capability, and reduction in manpower and infrastructure requirements. Cost reductions were facilitated with development and implementation of the common cockpit (CC), a fully integrated, software-driven, glass cockpit, which was installed in both helicopters. The CC employed mission specific software designed to enable efficient operation in all areas of the multi-mission spectrum. The CC was designed for the MH-60R/MH-60S aircraft as the interface for all aircraft mission equipment. Each of the unique mission sets was integrated through a network interface. There were four network tiers: the flight avionics segment (FAS), the mission avionics segment (MAS), the stores/self-defense avionics segment (SAS), and the mission support segment (MSS). Naval Air Systems Command (NAVAIR) competency AIR-4.0P was responsible for the issuance of all Naval aircraft flight clearances. As the NM-60S CC was equipped with a fully integrated, software-driven system, a means of achieving an IFR/IMC clearance was required. A four phased approach to obtaining an instrument flight regulations/instrument meteorological conditions (IFR/IMC) flight clearance was developed. This phased approach used a combination of FAA and Navy processes. The phases included laboratory, ground and flight evaluations of a fixed aircraft software/hardware configuration. All avionics hardware and software were evaluated for functionality, latency and integration. Phases I, II, and III were comprehensive qualification tests that were conducted during Navy Developmental Testing (DT-IIA). Phase IV was specific to the IFR/IMC clearance and is the focus of this paper. Technical challenges including unbalanced aircraft pitot static system, mismatched airspeed and altitude display time constants, and operator system interface (OSI) software problems were identified and corrected during the certification test. Successful completion of the IMC certification has resulted in fleet wide clearance for the MH-60S to operate in IFR/IMC. |
16,008 | Please write an abstract with title: The Effect of Frequency Droop Damping on System Parameters and Battery Sizing During Load Change Condition, and key words: Damping, Costs, EMTP, Power system stability, Stability analysis, Inverters, Batteries. Abstract: Inverter-based resources (IBR) have been widely studied for their advantages on the current power systems. This increase in the penetration of renewable energy has raised some concerns about the stability of the existing grid. Historically, power systems are dominated by synchronous generators that can easily react to system instability due to high inertia and damping characteristics. However, with IBR, the control of the inverter plays a crucial role in contributing to the system stability and enhancing the functionality of the inverters. One of these novel control methods is droop control. Droop characteristics are used to control voltage, frequency, and active and reactive power. This paper presents the impact of frequency droop damping on system frequency, real power, and the rate of change of frequency with distributed energy resources. Also, battery sizing is suggested based on the results. The results also show the need for optimal selection for the frequency droop damping to fulfill the appropriate battery size in terms of cost and performance. The simulations are carried out in an electromagnetic transient program (EMTP). |
16,009 | Please write an abstract with title: Integrated Sensing Arrays Based on Organic Electrochemical Transistors, and key words: Sensors, Transistors, Biosensors, Plastics, Logic gates, Electrodes, Capacitance, Physiology. Abstract: Organic electrochemical transistors (OECTs), as one of the most promising sensing techniques, have shown various advantages compared to traditional means, which include ultra-high sensitivity, low driving voltage, and excellent biocompatibility for different bioelectrical and biochemical sensing. Moreover, to fully unleash the potential of OECT sensors, integrated sensing systems, especially OECT-based sensing arrays, are widely investigated due to spatiotemporal resolution, mechanical flexibility, high optical transparency, low power dissipation, and ease of fabrication. These advantages are attributed to the unique working mechanism of OECT, novel mixed ionic-electronic (semi)conductors, adaptable device geometry/structure, etc. In this review, advances in OECT-based sensing systems are systematically summarized, with a focus on the OECT-based sensing array. Furthermore, perspectives, concerning stability, cut-off frequency, integrating density, and power dissipation, are discussed based on recent studies on OECTs and their relevant sensor arrays. Last, a summary and an outlook of this field are provided. |
16,010 | Please write an abstract with title: Satellite Image Fusion Using an Iterative Ihs-Based Approach, and key words: Wavelet transforms, Visualization, Satellites, Image color analysis, Pansharpening, Distortion, Iterative methods. Abstract: Intensity-Hue-Saturation (IHS) method is a pansharpening method belonging to the spectral class methods. In this class of methods, the multispectral image undergoes a spectral transformation and then one of the resulting components is totally replaced by the panchromatic image, hence leading to a significant color distortion. To alleviate this shortcoming, in the literature, the wavelet transform is often integrated to the spectral methods in order to transfer only the spatial details of the panchromatic image. Furthermore, the spatial information quantity transferred during the fusion is usually defined by the resolution ratio between the multispectral and panchromatic images. However, this is not necessarily the optimal way to generate the best fused image. In this paper, we propose an iterative IHS-based method (called IIHS), to continuously transfer the spatial information from the panchromatic image to the multispectral image while controling the perceptual quality of the fused image. Experiments on remote sensing images show that the proposed method presents the best visual and objective performances comparatively to the state-of-art IHS methods. |
16,011 | Please write an abstract with title: Empowered PG in Forex Trading, and key words: Training, Learning (artificial intelligence), Forecasting, Computational modeling, Contracts, Telecommunications, Information technology. Abstract: With the assumption that capital markets follow the semi-strong form of efficient market hypothesis (EMH), numerous efforts have been taken to defeat the non-stationary financial market, ranging from time series analysis, artificial intelligence for prices prediction, to automated decision making by reinforcement learning. This experiment integrated the power of time series forecasting of neural network with the competence of actions selecting of the reinforcement learning. CNN was trained first to predict future prices, and then it fed the output to the policy gradient (PG) model together with historical data to empower the trading decisions. The experiment was conducted on 30 minutes interval of EUR/USD pair in Forex between 2014 and 2018. Our experimental results showed that our model can achieve higher return in both train and validate samples than buy and hold strategy. |
16,012 | Please write an abstract with title: Driving in the Virtual: Towards Large-Scale Software-Defined Transportation Scene, and key words: Solid modeling, Virtual reality, Computational modeling, Road traffic, Computer vision, Cameras, Meteorology, Digital twins. Abstract: Image dataset plays an essential role in training the computer vision models. Compared with realistic datasets that are expensive to label and inflexible in number and scene, virtual datasets gradually show advantages and begin to act as a supplement in the training and validation of computer vision models. In this paper, we propose a pipeline for constructing artificial traffic scenes and generating virtual datasets based on an automatic driving simulation software from the perspective of parallel vision. Firstly, map data and simulation modeling elements like buildings are used to model the 3D artificial scene built upon a real environment. Furthermore, we use those artificial transportation scenes to automatically generate a large-scale and diverse dataset with the ground-truth label, which can provide service for computer vision tasks such as object detection and semantic segmentation. The environmental conditions and sensor properties in artificial scenes can be controlled flexibly and repeatedly. Finally, we show the detail and performance of creating virtual artificial scenes and generating the virtual dataset with low modeling time and highly accurate labeling, which does not depend on manual labeling and achieves a diverse dataset automatically and conveniently. |
16,013 | Please write an abstract with title: YOLO-R Based Mask Recognition System with Winograd Convolution Acceleration Chip, and key words: COVID-19, Convolution, Neural networks, Computer architecture, Real-time systems, Task analysis. Abstract: In this paper, we proposed “YOLO-R based mask recognition system with Winograd convolution acceleration chip.” In order to prevent the spread of COVID-19, we proposed a mask recognition system based on YOLO-R that adopted the CSP backbone architecture and used prediction refinement to predict, optimize, and obtain high recognition results. In addition, we designed the Winograd convolution acceleration chip to accelerate the operation of the YOLO-R neural network, so that the system can achieve real-time computing. |
16,014 | Please write an abstract with title: A Study of the Built Environment of Traditional Settlements Based on Geo-Information Technology: : A Case of Settlement Communities in Xiangfen, Shanxi, and key words: Technological innovation, Graphical models, Correlation, Cognition, Indexes, Cultural differences, Information technology. Abstract: Most traditional settlements originate from the concentration and integration of dwelling units, nurtured under the interaction of natural environment, socio-economic and cultural factors, and are significant carriers of local culture. The study focuses on traditional settlements in Xiangfen County of Shanxi Province, discussing spatial characteristics of the built environment through field investigation and geographic information technology analysis, involving factors such as scale, density, distribution direction and distribution pattern. The spatial features of the settlements are summarized, and the spatial autocorrelation index, average nearest neighbor index and kernel density index are analyzed, as well as the influencing aspects of the spatial pattern of the settlements, in order to explore comprehensive cognitions of settlements in macro dimension. The study aims to contribute to the regional conservation and development of settlements, and to summarize the methods for quantifying the spatial knowledge of the built environment of settlements in the regional dimension, which will contribute to the deeper knowledge of settlements. |
16,015 | Please write an abstract with title: Life tests on twisted pairs subjected to PWM-like voltages, and key words: Pulse width modulation, Life testing, Voltage, Partial discharges, Cable insulation, Wires, Pulse width modulation inverters, Ovens, Insulation testing, Performance evaluation. Abstract: This investigation regards the partial discharges (PD) ageing processes of motor winding insulation (enamelled wires) subjected to "fast rising and dropping" voltages, i.e. to a PWM controlled inverter drive voltage waveform. Twisted pair specimens were fed till failure by two different PWM like (and by a sinusoidal) voltages, at several voltage amplitudes, in presence of PD. The relevant life curves were traced and the PD were measured. The outcome evidenced that the life curves besides depending on the Vpp voltages they evidence a very strong connection with the relevant waveforms. |
16,016 | Please write an abstract with title: Identifiying Wastes for the Development of Lean Postal Services, and key words: Industries, Resistance, Manufacturing industries, Transportation, Focusing, Quality of service, Tools. Abstract: Lean is implemented in services aimed at improving the efficiency and quality of services. However, waste in the services industry is difficult to identify compared to the manufacturing industry. This study explores the type of waste in lean service. Finding from this study is expected to help lean managers and service managers identify the waste that can be eliminated or reduced in lean service. |
16,017 | Please write an abstract with title: Sub-micrometric vapor cell : a new tool for spectroscopy and atom-surface interaction, and key words: Spectroscopy, Atomic beams, Reflection, Atom lasers, Transient response, Optical pumping, Resonance, Anisotropic magnetoresistance, Absorption, Atom optics. Abstract: The paper presents the prospects offered by this new tool, the extremely thin vapor cells (ETC), for laser spectroscopy and studies of the atom-surface interaction. Transmission in an ETC is presently a tool for the wings spectroscopy of the doublet Cs (6P/sub 3/2//spl rarr/6D), in an attempt to study, at a very short distance from the surface (/spl sim/5 nm), possible level crossing effects between the sapphire-repelled Cs(6D/sub 5/2/) and the sapphire-attracted Cs(6D/sub 5/2/).A general breakthrough promised by the spectroscopic study of atom-surface interaction in an ETC is the fact that it permits to study cavity-QED effects with a 2-wall cavity with atom dipole fluuctuations undergoing multipl reflections. |
16,018 | Please write an abstract with title: Flame Hot Spot Tracking and Temperature Distribution of Combustion Flame Using New Technique, and key words: Temperature measurement, Electrical engineering, Temperature distribution, System performance, Fires, Imaging, Gray-scale. Abstract: This paper presents a temperature measurement tracking system of the combustion flame, modeling the position and velocity tracking system using a brushless DC (BLDC) motor, and hybrid controllers. The grayscale finite-scaled composites are reconstructed using a combination of imaging system approaches and two-color radiation thermal calculation. Limited the range of the flame, then determine the temperature distribution, finally determine and track the hot spot areas. The flame image reconstruction does not assume rotational symmetry in the flame structure, but relies on precise calculations of the grayscale components of the images using the two-color method. To assess the system's performance, a series of experiments were carried out on the combustion apparatus. The results revealed that the system had a high ability to follow the flame hot spot, with the controllers being able to track both position and speed. |
16,019 | Please write an abstract with title: Adaptive N-Step Technique for Real-Time Anomaly Detection in Smart Manufacturing, and key words: Manufacturing processes, Sociology, Forestry, Real-time systems, Fourth Industrial Revolution, Task analysis, Statistics. Abstract: Sensors installed at various assembly lines are becoming basic building blocks of industry 4.0 smart manufacturing environment. The data collected by sensors can be utilised to provide recommendation engine, automate the manufacturing process and also spot anomalies. Of these, automatic anomaly detection is a very significant task which detects misleading observations, data points, and/or events that deviate from the intended behaviour. The traditional approach to anomaly detection involves the use of more efficient and convoluted techniques to achieve higher accuracy. However, these techniques typically require much larger time and hence, is not suitable for real-time applications. In this work, an adaptive N-step anomaly detection technique is proposed wherein the number of steps (or modules) in the detection technique is based on the outlier percentage in the manufacturing process. A modular approach with techniques such as Density Based Spatial Clustering for Applications with Noise (DBSCAN), Isolation Forest (IF), Local Outlier Filter (LOF), etc., are used for automatic anomaly detection. Notably, the output of one step is fed as input to the next step, thereby making use of the knowledge gained in the previous step. The proposed adaptive approach results in >99% accuracy even when the outlier population is around 25%. Such high accuracy in real-time anomaly detection would serve as an important step towards having a Digital Twin model for smart manufacturing environment. |
16,020 | Please write an abstract with title: On the computational complexity of maintaining GPS clock in packet scheduling, and key words: Computational complexity, Global Positioning System, Clocks, Scheduling algorithm, Processor scheduling, Computer networks, Intelligent networks, Educational institutions, Channel allocation, Delay. Abstract: Packet scheduling is an important mechanism to provide QoS guarantees in data networks. A scheduling algorithm generally consists of two functions: one estimates how the GPS (general processor sharing) clock progresses with respect to the real time; the other decides the order of serving packets based on an estimation of their GPS start/finish times. In this work, we answer important open questions concerning the computational complexity of performing the first function. We systematically study the complexity of computing the GPS virtual start/finish times of the packets, which has long been believed to be /spl Omega/(n) per packet but has never been either proved or refuted. We also answer several other related questions such as "whether the complexity can be lower if the only thing that needs to be computed is the relative order of the GPS finish times of the packets rather than their exact values?". |
16,021 | Please write an abstract with title: Exploring the Properties of Points Generation Network, and key words: Three-dimensional displays, Image reconstruction, Shape, Training, Machine learning, Market research, Telephone sets. Abstract: With the development of deep learning, learning-based 3D reconstruction has attracted a substantial amount of attention and various single-image 3D reconstruction networks have been proposed. However, due to self-occlusion, the information captured in a single image is highly limited, resulting in inaccuracy and instability in reconstruction results. In this paper, a feature combination module is proposed to enable existing single-image 3D reconstruction networks to perform 3D reconstruction from multiview images. In addition, we study the impact of the number of the input multiview images as well as the network output points on reconstruction quality, in order to determine the required number of the input multiview images and the output points for reasonable reconstruction. In experiment, point cloud generations with different number of input images and output points are conducted. Experimental results show that the Chamfer distance decreases by 20%~30% with the optimal number of input multiview images of five and at least 1000 output points. |
16,022 | Please write an abstract with title: Nonstationary Industrial Process Monitoring Based on Stationary Projective Dictionary Learning, and key words: Machine learning, Process monitoring, Dictionaries, Feature extraction, Optimization, Data models, Temperature measurement. Abstract: Industrial data generally exhibit nonstationary features due to load changes, external disturbances, etc., which raise great challenges for process monitoring. Most existing methods for nonstationary process monitoring use a two-stage strategy, where stationary series are obtained via preprocessing, followed by feature extraction and modeling for the stationary series. However, the two-stage strategy treats preprocessing and feature extraction separately, which would obtain suboptimal features. This article develops the stationary projective dictionary learning (SPDL) method for monitoring nonstationary industrial processes. Specifically, nonstationary data are projected into a stationary subspace, overcoming the disadvantages of nonstationarity and improving the representation ability of the dictionary. Then, considering process data usually have temporal correlations, a novel self-expression constraint term is added to optimize the features so that it can describe the process data accurately. Finally, an iterative approach is proposed for joint optimization of the projection matrix and the dictionary, and the formulas for parameter estimation are derived in detail. After the projection matrix and the dictionary are obtained, the nonstationary data are projected and reconstructed, and the reconstruction error is adopted to design the monitoring statistic. Case studies on a numerical example, a nonstationary continuous stirred tank reactor (CSTR), and an industrial roasting process reveal that the proposed method is suitable for nonstationary industrial process monitoring. |
16,023 | Please write an abstract with title: Hydroxychloroquine's Influence on Hypoxic and Hypokalemic ventricle: An Insilico Perspective, and key words: Drugs, Pathology, Medical conditions, Perturbation methods, Lead, Electrocardiography, Ions. Abstract: Hydroxychloroquine (HCQ) has been widely used, irrespective of pre reported cardiotoxicity. This demands further investigation on the mechanisms of HCQ interaction under hypoxia without and with a pro-arrhythmic comor-bidity like hypokalemia in the ventricular tissue as well as its effects when excited with premature beats (PBs) to understand the possibility of arrhythmic occurrence. This is made possible by configuring a 2D transmural anisotropic ventricular tissue model consisting of endocardial, mid-myocardial and epicardial myocytes for mild and severe hypoxia, hypokalemia and HCQ conditions. Results show that along with a QT interval reduction, low amplitude or T-wave inversion is observed in mild and severe hypoxia conditions respectively. No significant adverse effect of HCQ is observed in both cases. Under hypokalemia, mild hypoxia creates notched T-waves. Including HCQ has the effect of increasing the QT interval and T-peak. In presence of PBs, arrhythmia is generated only in presence of hypokalemia. Further, severe hypoxia causes inverted T-waves and a shortened QT-interval in hypokalemic comor-bid configuration. In presence of PBs, reentry is created only on addition of hypokalemia. When treated with HCQ, no notable changes occurred. This in-silico ventricular model indicates that HCQ treatment has no significant adverse effect in presence of hypokalemia and hypoxia, except in the combination of mild hypoxia with hypokalemia condition where it initiated a re-entrant arrhythmia pattern. These results could help guide treatment with HCQ. |
16,024 | Please write an abstract with title: A new approach to achieve multiple packet reception for ad hoc networks, and key words: Ad hoc networks, Signal processing algorithms, Interference suppression, Multipath channels, Source separation, Microwave integrated circuits, Channel estimation, Transmitters, Media Access Protocol, Mobile ad hoc networks. Abstract: An algorithm for the recovery of multiple packets is proposed in this paper. The algorithm exploits the fact that every transmitter sends an implicit training sequence along with the information to accomplish multiple user equalization and interference suppression in the challenging scenario of an asynchronous random access ad hoc network. The proposed method has the advantage of allowing the transmission of complex data over time-dispersive multipath channels. A simulation example is presented that corroborates the interference suppression capabilities of the algorithm. |
16,025 | Please write an abstract with title: Influence on Stern Flaps in Resistance Performance of a Caterpillar Track Amphibious Vehicle, and key words: Mathematical model, Resistance, Marine vehicles, Immune system, Fluids, Sun, Tracking. Abstract: In order to reduce the resistance and increasing speed for a caterpillar track amphibious vehicle (CTAV), the stern flaps were applied and the influence was researched. Numerical simulations performed by STAR-CCM+ and model towing test reveal that stern flaps have greatly reduced the resistance, trim, and sinkage of the CTAV when the length Froude number is between 0.63 and 1.05. The length and flap angle were optimized by numerical simulation. In addition, the residual resistance plays a dominant role in resistance reduction, which contributes to more than 90% of the total resistance reduction. Installing stern flaps increase the vehicle waterline by 7% and enhance the virtual-length effect. Furthermore, the running attitude becomes steadier, thereby decreasing the trim and sinkage. Therefore the resistance performance of the CTAV can be enhanced by installing stern flaps with a proper length at an optimal flap angle. |
16,026 | Please write an abstract with title: Wideband patch antenna for 5-6 GHz WLAN applications, and key words: Broadband antennas, Patch antennas, Wireless LAN, Personal digital assistants, Microstrip antennas, Antenna measurements, Area measurement, Frequency measurement, Local area networks, Bandwidth. Abstract: A wideband microstrip patch antenna has been analyzed, designed, fabricated, and measured for wireless local area network (LAN) applications in the 5-6 GHz frequency range. The antenna is internal to the housing of a personal digital assistant (PDA), such as a PALM organizer and has the dimensions of 28 mm by 9 mm by 3 mm on an FR4 substrate. The antenna meets or exceeds the bandwidth requirements for the dual-band IEEE 802.11a wireless local area network (WLAN) applications (5.15-5.35 GHz and 5.725-5.825 GHz) within a 2:1 VSWR. |
16,027 | Please write an abstract with title: ConvCatb: An Attention-based CNN-CATBOOST Risk Prediction Model for Driving Safety, and key words: Machine learning algorithms, Roads, Vehicular ad hoc networks, Prediction algorithms, Real-time systems, Classification algorithms, Safety. Abstract: Risk prediction is one of the most important tasks in assistant and automatic driving. In recent years, by the help of VANET and various sensors in the cars, the status of cars and roads can be collected in real time and used for data-driven based driving risk prediction. However, it is challenging to predict the driving risk due to the complex relationship between multiple environment factors like location, weather, time etc. Thus, a deep learning model ConvCatb was proposed in this paper, which improves the attention mechanism to the traditional Convolutional Neural Networks, and combines the CatBoost algorithm to predict the current driving safety. The main idea is to emphasize the combination relationship between driving environment features through Non-local attention mechanism, and then use CatBoost to replace the softmax of CNN for classification. Finally, the experiment results show that the ConvCatb achieved superiorities in accuracy and F1-score, compared with existing schemes. |
16,028 | Please write an abstract with title: War Economy Analysis after Mortgage Crisis on Stock and Gold with Semi-Stock and Gold with Semi--Covariance Covariance Covariance, and key words: Economics, Correlation coefficient, Gold, Loans and mortgages, Analytical models, Measurement units, Correlation. Abstract: The statistics for a window of an engineering observation is called running window quantity. Running intra-covariance is a special case of running inter-covariance, when two variables are the same. The inter-covariance minus the geometric average of respected intra-covariances is called the pure inter-covariance. It gives you a cleaner association analysis compared with the running Pearson analysis. The normalization of covariance to standard deviation is called the Pearson correlation coefficient. The covariance for the region above or below the average is called semi-covariance (upper or down). Here we present a pure inter running semi-covariance, an accurate ReLU (Rectified Linear Unit) way of measuring the inter-non-linear correlation between variables excluding the intra-non-linear components. Our framework is applied to successfully analyze the association between war factors and the gold response. The result of our analyses of the 12 years after the 2007 Mortgage crisis on the war equipment companies' stock versus the gold suggests that stocks from different regions have a slightly different impact on the gold value that reflects the overall peaceful economic prosperities. |
16,029 | Please write an abstract with title: State-driven energy optimization in wireless sensor networks, and key words: Intelligent networks, Wireless sensor networks, Cost function, Telecommunications, Routing, Space technology, Quality of service, Testing, Energy consumption, Communications technology. Abstract: Most sensor network applications require quality of service guarantees on a network-wide basis, suggesting the need for global network cost optimization. The dynamic and nonuniform local states of individual nodes in sensor networks complicate global cost optimization. Here, we present an approach for optimizing global cost in sensor networks through greedy local decisions at each node, and we explore the benefits of this approach in reducing the idle listening at individual nodes in order to reduce the global network energy cost. We consider two representations for the local sensor node state: (1) number of descendants in the routing tree: and (2) number of descendants and duty cycle. For both state representations, we show through experiments on a testbed of 14 mica2 sensor nodes running ALPL that enabling nodes to set their listening mode according to their local state reduces global energy cost by 35% and provides more balanced energy consumption over the case of BMAC. |
16,030 | Please write an abstract with title: Mechanism for PJM Ancillary Service Market to Promote Flexible Resources, and key words: electricity market, spot market, ancillary service market, flexibility resources, pumped storage power station. Abstract: In order to stimulate flexible resources, there have been many changes in the rules of the PJM ancillary service market. Based on the relevant rules of PJM, this paper systematically analyzes the relevant electricity market operating prices in the past three years, and takes a pumped storage power station as an example to investigate its income in PJM. The research shows that: 1) Even if the ancillary service market has been reformed, the power market still maintains the basic logic with the day ahead market as the core. 2) PJM adopts regulation performance price to provide more returns for flexible resources, but its opportunity cost is only more accurate accounting without special incentives. |
16,031 | Please write an abstract with title: Concept of LIF Neuron Circuit for Rate Coding in Spike Neural Networks, and key words: Oscillators, Resistance, Neurons, Capacitors, Switches, Encoding, Resistors. Abstract: This brief presents a concept of leaky integrate-and-fire neuron (LIF) based on oscillator circuit for a spike neural network with firing rate coding. The circuit contains a switching element with an S-shaped current-voltage characteristic and two capacitors; a control resistor shunts one of the capacitors. The circuit is characterized by a strong dependence of the frequency of relaxation oscillations on the magnitude of the control resistor. The dependence has a sigmoid-like form, and we present an analytical method for dependence calculation. The circuit provides theoretical perspectives for the pairing of resistive sensors with a neural network and for creating neuromorphic devices with artificial intelligence. |
16,032 | Please write an abstract with title: Exploiting Event Cameras for Spatio-Temporal Prediction of Fast-Changing Trajectories, and key words: Cameras, Trajectory, Robot vision systems, Target tracking, Visualization. Abstract: This paper investigates trajectory prediction for robotics, to improve the interaction of robots with moving targets, such as catching a bouncing ball. Unexpected, highly-non-linear trajectories cannot easily be predicted with regression-based fitting procedures, therefore we apply state of the art machine learning, specifically based on Long-Short Term Memory (LSTM) architectures. In addition, fast moving targets are better sensed using event cameras, which produce an asynchronous output triggered by spatial change, rather than at fixed temporal intervals as with traditional cameras. We investigate how LSTM models can be adapted for event camera data, and in particular look at the benefit of using asynchronously sampled data. |
16,033 | Please write an abstract with title: Hot Region Selection Based on Selective Search and Modified Fuzzy C-Means in Remote Sensing Images, and key words: Remote sensing, Image segmentation, Feature extraction, Search methods, Gray-scale, Visualization, Object detection. Abstract: Hot region selection (HRS) is usually performed for larger scenes, especially in military target detection and battlefield situational awareness applications. Many state-of-the-art methods pay more attention on object detection. Although they can detect the region of interest in one image, these images are highly affected by illumination, rotation, and scale changes, which further increases the complexity of analysis compared to those obtained using standard remote sensing platforms. The study of HRS is of great importance in the analysis of remote sensing images. The current research focuses on the specific type of object area detection. A well-developed HRS needs to have three properties: uniform highlighting of the entire HRS, well-defined boundaries, and good robustness. Motivated by these requirements, a HRS method based on the selective search method and modified fuzzy c-means (FCM) in remote sensing images is proposed to address the detection of potential hot regions in large-scale remote sensing images. First, we create a Gaussian curvature filter to preprocess large scale remote sensing images. Second, a modified FCM segmentation method is utilized to segment the image. Third, an enhanced selective search method is adopted to establish well-defined boundaries for the HRS and to improve the immunity to noise. The geographic information is presented in this phase, which is conducive to improve the detection accuracy. In the experimental section, we compare our new method with four other extraction models on three data sets. The experimental results show that compared to the other competing models, the new model better defines the hot regions and obtains more entire boundaries in terms of Overlap and mAP. |
16,034 | Please write an abstract with title: AI Powered THz VLSI Testing Technology, and key words: Integrated circuits, Testing, Artificial intelligence, Pins, Transforms, Integrated circuit reliability. Abstract: Increasing complexity of digital and mixed-signal systems makes establishing the authenticity of a chip to be a challenging problem. We present a new terahertz testing technique for non-destructive identification of genuine integrated circuits, in package, in-situ and either with no or under bias, by measuring their response to scanning terahertz and sub-terahertz radiation at the circuit pins. This novel, patent pending non-invasive nondestructive technology when merged with Artificial Intelligence (AI) engine will evolve and self-improve with each test cycle. By establishing and AI processing of the THz scanning signatures of reliable devices and circuits and comparing this signatures with devices under test using AI, this technology could be also used for reliability and lifetime prediction. |
16,035 | Please write an abstract with title: A Fully Informative Phasor Measurement Unit for Distribution Networks With Harmonic Distortion, and key words: Harmonic analysis, Estimation, Power harmonic filters, Distribution networks, Performance evaluation, Phasor measurement units. Abstract: We introduce a fully informative distribution network phasor measurement unit (FI-DPMU), that is capable of performing a simultaneous estimation of phasor dynamics and harmonic components. This is in contrast with current state-of-the-art devices, that only provide information about the fundamental component of voltages/currents—by discriminating or filtering-out their harmonic content. The FI-DPMU hence represents a significant economical solution, since it bypasses the need to deploy power quality analyzers to retrieve full information about the network. To validate the accuracy of the FI-DPMU, we performed a hardware-in-the-loop implementation to emulate a distribution network that is subject to abrupt frequency variations and high harmonic distortion. The tests demonstrate that the FI-DPMU satisfies the standards of distribution network phasor measurement units (DPMUs), providing a real-time fast Fourier transform (FFT) as additional feature. Experimental results show a comparison between FI-DPMU measurement data with the information provided by a commercial DPMU. |
16,036 | Please write an abstract with title: Optimal Electricity Tariff Management in the Scope of Energy Management on University Campuses: Boğaziçi University Case Study, and key words: Costs, Law, ISO Standards, Standards organizations, Tariffs, Organizations, Planning. Abstract: Nowadays, with the increase in energy demand, many techniques penetrate into both the producer and consumer sides. One of the most important of these techniques is energy management. In this study, energy management, which is the umbrella term, is discussed as energy planning take as references ISO 50001, and optimal tariff management. Case studies are conducted for identifying optimal electricity tariffs. Results show that invoice costs can be saved at the rate of 2.93-3.71% by optimal tariff management that does not require any investment costs. |
16,037 | Please write an abstract with title: Correlation clustering, and key words: Clustering algorithms, Approximation algorithms, Computer science, Training data, Databases. Abstract: We consider the following clustering problem: we have a complete graph on n vertices (items), where each edge (u, /spl upsi/) is labeled either + or - depending on whether a and /spl upsi/ have been deemed to be similar or different. The goal is to produce a partition of the vertices (a clustering) that agrees as much as possible with the edge labels. That is, we want a clustering that maximizes the number of + edges within clusters, plus the number of - edges between clusters (equivalently, minimizes the number of disagreements: the number of - edges inside clusters plus the number of + edges between clusters). This formulation is motivated from a document clustering problem in which one has a pairwise similarity function f learned from past data, and the goal is to partition the current set of documents in a way that correlates with f as much as possible; it can also be viewed as a kind of "agnostic learning" problem. An interesting feature of this clustering formulation is that one does not need to specify the number of clusters k as a separate parameter, as in measures such as k-median or min-sum or min-max clustering. Instead, in our formulation, the optimal number of clusters could be any value between 1 and n, depending on the edge labels. We look at approximation algorithms for both minimizing disagreements and for maximizing agreements. For minimizing disagreements, we give a constant factor approximation. For maximizing agreements we give a PTAS. We also show how to extend some of these results to graphs with edge labels in [-1, +1], and give some results for the case of random noise. |
16,038 | Please write an abstract with title: Capacitor Voltage Estimation of MMC Using a Discrete-Time Sliding Mode Observer Based on Discrete Model Approach, and key words: Capacitors, Observers, Sensors, Estimation, Topology, Switches, Modulation. Abstract: The modular multilevel converter (MMC) is widely used for high and medium voltage applications due to its several advantages over other multilevel topologies. The number of voltage levels that can be obtained at the ac output can be increased at the expense of a greater number of submodule (SM) capacitors. As the capacitor voltages need to be monitored for voltage balancing, the MMC system requires a large number of voltage sensors. This increases capital investment for the MMC system and failure points due to increased hardware interfaces. So far, a few works have been reported that uses observation techniques to either completely eliminate or reduce the number of sensors. This article presents a discrete-time sliding mode observer (DTSMO) for estimating the capacitor voltages and thus possibly eliminating all the voltage sensors of the SM capacitors. A switching function-based discrete mathematical model is used for the design framework of the proposed DTSMO. The errors in observation are taken as important performance indicators under both transient and steady-state conditions. It has also been observed that the proposed DTSMO delivers robust performance in presence of parametric uncertainty of capacitance values. The control algorithm is simulated in MATLAB/Simulink to validate the performance of the proposed observer. It is further validated through experimental results in a hardware prototype. |
16,039 | Please write an abstract with title: Multishot Adversarial Network Decoding, and key words: network decoding, adversarial network, multishot capacity. Abstract: We investigate adversarial network coding and decoding focusing on the multishot regime. Errors can occur on a proper subset of the network edges and are modeled via an adversarial channel. The paper contains both bounds and capacity-achieving schemes for the Diamond Network and the Mirrored Diamond Network. We also initiate the study of the generalizations of these networks. |
16,040 | Please write an abstract with title: Efficient implementation of sphere demodulation, and key words: Demodulation, Maximum likelihood estimation, Vectors, Sorting, Additive noise, Ambient intelligence, Modems, Communication systems, Fading, Frequency. Abstract: We provide new results on the sphere demodulator (SD) and its new variant, the list sphere demodulator (LSD). A new reduced complexity SD algorithm is presented. We suggest implementing the necessary sorting of constellation symbols through a look up table. In addition, we propose the use of a modified QR algorithm which tries to begin the search in the layers which are "easier to demodulate". These improvements also apply to the recently published soft output LSD, in which we implement the list using the heap structure. |
16,041 | Please write an abstract with title: A Real-time Display Method for Ultrasound Color Flow Velocity Estimation, and key words: Displays, Ultrasonic imaging, Frequency estimation, Autocorrelation, Dynamic range, Blood, Table lookup, Signal resolution, Doppler shift, Biomedical imaging. Abstract: This paper proposes a new way for ultrasound color flow velocity estimation and display. This method sets up a mapping table which directly relates to the dynamic range of the velocity display by using an inverse mapping instead of calculating the arctangent value directly. This method is ideal for software implementation and offers an interactive way to user for changing the dynamic range of flow velocity to increase the display resolution. |
16,042 | Please write an abstract with title: Gamma Ray Effects on Organic Light-Emitting Diodes (OLEDs), and key words: Degradation, Performance evaluation, Gamma-ray effects, Current measurement, Lighting, Organic light emitting diodes, Cameras. Abstract: In this paper, total ionizing dose (TID) induced effects on OLED devices are investigated. Two fresh and one electrically stressed OLEDs were irradiated with Cobalt-60. Current-Voltage (I-V) and illumination measurements at different operation conditions were performed. The changes in both I-V characteristics and intensity behavior showcase the degree of immunity towards irradiation, making these devices particularly appealing for space applications. |
16,043 | Please write an abstract with title: A Soft-switching Step Down Converter for Point of Load Applications, and key words: Buck converters, Switching frequency, Electromagnetic interference, Soft switching, Switches, Voltage, Zero voltage switching. Abstract: A Pulse width modulation(PWM) controlled synchronous rectifier(SR) step down converter that can achieve zero voltage switching(ZVS) of the power switches is proposed in this paper. With a few components added in topology and controlling circuit, both the main switch and synchronous switch are operated in ZVS. Higher input voltage and higher efficiency can be achieved due to the soft switching, which further extends the application range of the nonisolated buck converter. Meanwhile, the converter can be operated at a fixed switching frequency, so the EMI filter is easy to design. Besides, a digital controlled scheme is proposed in this paper. In the end, A ZVS SR buck converter working at 500kHz with 30W output power is built and higher efficiency is shown compared with the traditional hard switching Buck converter. |
16,044 | Please write an abstract with title: Analysis of Drone Placement Strategies for Complete Interference Cancellation in Two-Cell NOMA CoMP Systems, and key words: NOMA, Interference cancellation, Unmanned aerial vehicles, Throughput, Base stations, Silicon carbide. Abstract: The use of unmanned aerial vehicles (UAV) as flying base stations is rapidly growing in the field of wireless communications to leverage the capacity of congested cells. This study considers a two-cell system where one of the cells is saturated, i.e. can no longer serve its users, and is supported by a UAV. The UAV positioning problem is investigated specifically to benefit from the interference cancellation properties available through the introduction of power-domain non-orthogonal multiple access (NOMA) techniques in coordinated multipoint (CoMP) systems. Indeed, adequate placement of the UAV can enable triple mutual successive interference cancellation (TMSIC) between a triplet of users, including a cell-edge and a cell-center user in each cell, to maximize system throughput or a mixture of throughput and TMSIC probability. The random line-of-sight/non-line-of-sight realizations of air-to-ground links between users and UAV are taken into account in the problem modeling, showing a significant improvement in performance compared to the conventional mean path loss model. The performance evaluation highlights the existing trade-offs between system capacity, fairness, and computational complexity of the investigated approaches. |
16,045 | Please write an abstract with title: Design and Implementation of Marine Datasets Based on DCGAN Network, and key words: Training, Knowledge engineering, Deep learning, Seminars, Analytical models, Wheels, Generative adversarial networks. Abstract: In this paper, the deep learning method is applied to the ship detection SAR datasets to enlarge the existing SAR images of ships.This paper first introduces the basic knowledge of convolutional neural networks, and also introduces the common convolutional neural network structure.Secondly, this paper introduces the generative adversarial network GAN,, analyzes the GAN principle and network structure according to the objective function, introduces the training method of the GAN model, and analyzes the advantages and disadvantages of GAN.This introduces the DCGAN network model that combines the above two, analyzes its basic knowledge and network structure, and the improvement of GAN model, and introduces the training process in detail.Finally, we compare the loss function images generated by DCGAN and GAN and summarize the lessons. |
16,046 | Please write an abstract with title: LSSVM Boiler Main Steam Temperature Anomaly Detection Algorithm Based on Improved SSA, and key words: Temperature, Machine learning algorithms, Search problems, Stability analysis, Classification algorithms, Anomaly detection, Thermal stability. Abstract: To address the problem of blindness in parameter selection of LSSVM model, this paper proposes to use the improved sparrow algorithm (CDE-SSA) for parameter search. First, the CDE-SSA algorithm is designed on the basis of the sparrow algorithm, and the chaos theory is integrated into the sparrow algorithm to establish the chaotic sparrow algorithm model for the shortcomings of the poor global search ability and unstable initialized sparrow distribution of the sparrow algorithm. To address the shortcomings of the way of discoverer position update in the algorithm, a new variational operator is used instead of the original one to improve the practicality of the algorithm. In order to balance the global search ability and local search ability in the first and second stages of the algorithm, the cosine factor is introduced to improve the proportional operator in the sparrow algorithm, and the information of the number of iterations is introduced into the iterative process. The performance of CDE-SSA algorithm is compared with PSO algorithm and SSA algorithm by testing functions, and the results show that CDE-SSA algorithm shows better performance in terms of search accuracy and search stability. Meanwhile, the CDE-SSA algorithm is used to optimize the LSSVM parameters and build the KPCA-CDE-SSA-LSSVM anomaly detection model, which is applied to the main steam temperature system anomaly detection scenario, and the detection accuracy reaches 98%, which proves the rationality of the algorithm proposed in this paper. |
16,047 | Please write an abstract with title: Research Progress and Development Trend of Reducing the Influence of Frequency Mutation on Power Grid, and key words: grid connection and operation safety and stability, electricity market, network compensation. Abstract: Under the background of the accelerating economic development, the traditional power grid and the production development of modern society have been difficult to meet the needs of modern society. Therefore, in order to better improve the timeliness of power grid management, it is necessary to integrate the current big data and information technology into the power grid management to strengthen the timeliness of fault detection and maintenance in the process of real-time monitoring. So as to provide more reliable power supply for daily production and life. This paper will analyze the research progress and development trend of reducing the impact of frequency mutation on power grid. |
16,048 | Please write an abstract with title: A Hybrid CNN-LSTM Architecture for Detection of Coronary Artery Disease from ECG, and key words: Electrocardiography, Heart rate variability, Feature extraction, Convolution, Time series analysis, Arteries, Morphology. Abstract: Coronary Artery Disease (CAD) causes significant global mortality. The recent development in artificial intelligence shows the feasibility of early non-invasive screening of several life- threatening cardiovascular diseases. However, such approaches have been less prolific in diagnosis of CAD due to lack of clinically known definite bio-marker. In this paper, we propose a novel neural network architecture that effectively combines two non-specific CAD markers, 1) anomalous morphology of Electrocardiogram (ECG) waveform and 2) abnormal Heart Rate Variability (HRV). A Convolutional Neural Network (CNN) structure is defined for extraction of morphological ECG features. Another composite structure is defined based on Long Short-Term Memory (LSTM) and a set of hand crafted statistical features for measuring the extent of HRV. The two independent bio-markers are subsequently combined in a hybrid CNN-LSTM architecture for classification of CAD. The proposed approach is evaluated on two datasets, a corpus, selected from the MIMIC II waveform dataset and a partially noisy in-house dataset, recorded using a low-cost ECG sensor. Results show that overall classification accuracy of 93% and 88% are achieved on the two datasets, which outperform the existing approaches. |
16,049 | Please write an abstract with title: Theoretical Limits of PHY and MAC for 5G Machine Type Communications, and key words: 5G mobile communication, Media Access Protocol, Throughput, Optimization, Interference, Physical layer. Abstract: In this paper, we describe the theoretic limits focusing them on the 5G performance issues, the physical layer and medium access control techniques and throughput limits in case of Machine-Type Communications. The Shannon’s limit of the wireless medium access control protocols is presented as a maximum rate of error-free data and overheads of the medium access control protocol in practical cases of machine-to-machine communications. That allows predicting traffic crowding depending on the input load. Finally, performance modeling of simplified control protocol with varied priority weights for data traffic is provided. |
16,050 | Please write an abstract with title: Evaluation of Grid Connected Electric Vehicle Impact in the Power Demand Curve with PI/ANN Controller, and key words: Lithium-ion batteries, Degradation, Temperature sensors, Vehicle-to-grid, Technological innovation, Absorption, Power quality. Abstract: This paper provides a complete analysis that is newest in development of electric cars (EVs) collaboration with power grid representing the future of smart grid design. This work elaborate study of a different control method in order to achieve the accurate control between electric vehicle and residential load connected to grid. As Electric Vehicles are equipped with Lithium ion battery which is more sensitive to overcharge and dip discharge and which leads to performance degradation due to unorganized absorption and injection of power into the grid. The EVs battery charging (G2V) and discharging (V2G) operation are must be synchronized in order maintain the power quality in the power grids. So, Seven modes of operation are used for G2V (Grid To vehicle) and V2G (Vehicle to Grid) operation to insure proper organize absorption and injection of power into grid by considering the load demand. The control algorithm for this modes also checks SOC of battery, grid demand, priority order between EV and the power difference required to flatten the demand curve. Depending upon all this factor G2V and V2G operation are performed. This proposed scheme modeled with conventional PI and ANN controller. The Comparative analysis between this two controllers are performed to ensure the proper flow of power when EVs connected to grid. This proposed methodology developed and simulated with help of MATLAB/Simulink. |
16,051 | Please write an abstract with title: A new in situ method for the measurement of ignition delays and the propagation of the ignition wave in gun charges, and key words: Ignition, Current measurement, Propagation delay, Guns, Propulsion, Chemical processes, Electrothermal launching, Safety, Performance evaluation, Weapons. Abstract: The physical and chemical phenomena involved in the ballistic process, both in conventional guns and in electrothermal-chemical (ETC) guns, are very complex, so that optimization of gun performance requires a detailed understanding of the influence of different parameters. The initial stage of propellant ignition is critical to the rest of the process, in terms of both performance (muzzle velocity, repeatability) and safety. A better understanding of the ignition stage is thus very important in achieving improved performance. In this paper, we propose a new method and ignition sensor aimed at providing direct experimental information about the propellant ignition process. We further report on measurements of the ignition delays, and the propagation of the "ignition wave", performed using these sensors in experimental devices such as closed bombs and gun simulators. |
16,052 | Please write an abstract with title: On the Minimal Recognizable Image Patch, and key words: Image recognition, Tools, Character recognition, Task analysis, Materials requirements planning. Abstract: In contrast to human vision, common recognition algorithms often fail on partially occluded images. We propose characterizing, empirically, the algorithmic limits by finding a minimal recognizable patch (MRP) that is by itself sufficient to recognize the image. A specialized deep network allows us to find the most informative patches of a given size, and serves as an experimental tool. A human vision study recently characterized related (but different) minimally recognizable configurations (MIRCs) [1], for which we specify computational analogues (denoted cMIRCs). The drop in human decision accuracy associated with size reduction of these MIRCs is substantial and sharp. Interestingly, such sharp reductions were also found for the computational versions we specified. |
16,053 | Please write an abstract with title: Heart rate variability analysis for patients with obstructive sleep apnea, and key words: Heart rate variability, Sleep apnea, Testing, Cardiology, Heart rate detection, Phase detection, Electrocardiography, Databases, Size control, Multidimensional systems. Abstract: Obstructive sleep apnea (OSA) is a common health concern associated with serious implications and increased cardiovascular morbidity and mortality. This study approaches the problem of identification OSA patients and detection of OSA phases on the basis of heart rate variability (HRV) analysis. Only a single ECG-channel is required for this purpose. We used data from the apnea ECG database:40 patients with documented OSA and 20 controls divided into a learning and a test set of equal size. Commonly used HRV measures as well as some novel parameters are tested. The results are compared by ROC-analysis and promising parameters are combined into a multidimensional vector and evaluated by means of a second order polynomial classifier. Best results are obtained from parameters calculated by time delay embedding and correlation analysis of the interbeat interval series. For the identification task, 95% sensitivity and 100% specificity are achieved on the independent test set. The detection task yields an average classification rate of almost 85%. |
16,054 | Please write an abstract with title: A knowledge graph-based method for modeling and analyzing the disaster risks of railway construction in the mountainous area of Southwest China, and key words: Knowledge engineering, Analytical models, Railway engineering, Correlation, Geology, Transportation, Rail transportation. Abstract: In the mountainous area of Southwest China, the railway engineering construction faces extremely complex and dangerous natural environment, in which the analysis of the potential correlations among disaster risk factors is a key step for the engineering design and safety assurance. In this paper, we present a network model based on knowledge graph to analyze and explore potential correlation relationships and risk chains among the geology, geography or environmental disasters risk factors. In our model, a knowledge graph is constructed where the nodes represent the disaster risk factors and edges represent the possible relationships among disaster risk factors. Furthermore, by defining the parameter matrix and topological indexes of the graph, we describe the potential correlation relationships among the disaster risk factors quantitatively. The result shows that in the southwest mountainous area China, some strong correlations exist among disaster factors. Moreover, some disasters are more likely to occur with other disasters so that some disaster risk chains form. The results provide a basis for the analysis and evaluation of disaster risks of railway engineering construction in the southwest mountainous area. |
16,055 | Please write an abstract with title: Development of Micro Hydro Power Plant Prototype as A Field Laboratory for Educational and Research Purposes, and key words: Electric potential, Renewable energy sources, Data analysis, Catalysts, Prototypes, Hydroelectric power generation, Fossil fuels. Abstract: The need for cheaper electricity generation rises as the price of fossil fuels is increasingly nowadays. Hydropower plant is one of the most efficient and environmentally friendly alternative power plant sources. In this research works, a prototype of small-scale hydro power plant known as micro hydro power plant (MHPP) was developed for educational and research purpose. The motivation of this work is based on there is no field laboratory could be used for students to study the concept and actively involved in electricity generation at Universiti Teknologi Malaysia (UTM) Johor Bahru campus, Malaysia. This work hopefully become the catalyst for further research regarding renewable energy source, particularly in MHPP research. The research flow for this work begins with feasibility activities to determine some potential sites for development of MHPP at UTM Johor Campus. There are 7 (seven) potential sites based on site visits and data analysis. From the data analysis, the most suitable site chosen for MPPP prototype development. The prototype was built based on the improved design. The results show that the constructed prototype is capable for generating electricity. This prototype can be used as a field laboratory and for educational and research purpose. |
16,056 | Please write an abstract with title: Hybrid Energy Storage using Battery and Ultra-capacitor for Electric Vehicle, and key words: Battery, Hybrid Energy Storage, Super/Ultra-capacitor. Abstract: The electrical energy storage is an factor which plays an important role from the era of electrical energy generation. The only option available for storage for a very long period were different form of electro-chemical energy storage device known as battery. But now an amalgamation of electrostatic device with chemical element is available for storage known as Ultra-capacitor (UC). Both the devices store the electrical energy in DC. The battery have high energy density while the UC have high power density. In case of smart grid the energy generated is varying due to the different environment conditions. This varying of energy supply from the smart grid to the battery and from the battery to the load reduces the reliability of the system. The Hybrid Energy Storage system (HESS) can provide reliability by providing the energy to the load from battery and UC. An electric vehicle (EV) is the emerging trend in automobile sector. HES installed in EV will increase the reliability of the vehicle energy storage system. The simulation results provided validates the above statement by providing the power for a 2 kW load with transients in it. |
16,057 | Please write an abstract with title: EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals, and key words: Electrodes, Convolution, Network topology, Benchmark testing, Feature extraction, Brain modeling, Electroencephalography. Abstract: Graph neural networks (GNN) are an emerging framework in the deep learning community. In most GNN applications, the graph topology of data samples is provided in the dataset. Specifically, the graph shift operator (GSO), which could be adjacency, graph Laplacian, or their normalizations, is known a priori. However we often have no knowledge of the grand-truth graph topology underlying real-world datasets. One example of this is to extract subject-invariant features from physiological electroencephalogram (EEG) to predict a cognitive task. Previous methods use electrode sites to represent a node in the graph and connect them in various ways to hand-engineer a GSO e.g., i) each pair of electrode sites is connected to form a complete graph, ii) a specific number of electrode sites are connected to form a k-nearest neighbor graph, iii) each pair of electrode site is connected only if the Euclidean distance is within a heuristic threshold. In this paper, we overcome this limitation by parameterizing the GSO using a multi-head attention mechanism to explore the functional neural connectivity subject to a cognitive task between different electrode sites, and simultaneously learn the unsupervised graph topology in conjunction with the parameters of graph convolutional kernels. |
16,058 | Please write an abstract with title: Lifespan-Balance-Based Energy-Efficient Routing for Rechargeable Wireless Sensor Networks, and key words: Routing, Wireless sensor networks, Energy efficiency, Quality of service, Sensors, Wireless communication, Optimization. Abstract: The rechargeable wireless sensor networks provide efficient data services for many applications in the Internet of Things (IoT), in which the sensors can be recharged continuously. Wireless recharging technology has been widely studied and applied. Reasonable energy allocation and identification of the nodes which need recharging in each round is key to the technology. According to dynamic recharging planning, it is crucial to improve energy efficiency in networks with excellent Quality of Service (QoS). Hence, a lifespan-balance-based energy-efficient routing is proposed. The optimization problem of maximizing recharging payoff is first designed and it is solved by our heuristic algorithm, which enables dynamic adjustment of the ratio of moving time to recharging time according to energy states of nodes. Then the QoS routing based on multi-hop strategy which integrates multiple related factors is designed. Finally, the indicator which contains energy supplement to quantify lifespan is designed. Combined with our QoS routing, the method of lifespan balance based on the global relay range regulation is proposed to maximize the minimum lifespan of all nodes intelligently. The simulation result shows that our algorithm can improve the energy efficiency with excellent QoS in the studied networks and prolong the network lifetime. |
16,059 | Please write an abstract with title: Anti-disturbance control of stochastic nonlinear systems based on extended state observer, and key words: Asymptotic stability, Adaptation models, Backstepping, Adaptive systems, Differential equations, Observers, Stability analysis. Abstract: In this paper, we study the controller design and stability analysis for a class of stochastic cascade nonlinear systems with external disturbances. The unmeasurable external disturbance is viewed as a extended state. In order to estimate the unmeasurable system states and the external disturbance, a new extended state observer (ESO) based on the Riccati differential equation is constructed. The stochastic inverse dynamics, the error dynamics of observer, and the ESO constitute a new stochastic nonlinear systems. Based on this new systems, an adaptive output feedback controller is proposed by combining stochastic input-to-state stability with backstepping design technique. The controller guaranteed that all the signals of the states are almost surely bounded and the states of the stochastic closed-loop system are globally asymptotically stable in probability. Finally, a simulation example is given to the validity of the proposed method. |
16,060 | Please write an abstract with title: The Importance of Colormaps, and key words: Image color analysis, Gray-scale, Ocean temperature, Data visualization, Vision defects, Temperature measurement, Rain. Abstract: Colormaps control the way data are understood when plotted because they map data values to color. When the colors used do not match the way humans perceive color, there can be a mismatch between interpretation and the data. Here I present relevant background information and provide suggestions to improve colormap choices. |
16,061 | Please write an abstract with title: Search System over e-Commerce Data for Business Users, and key words: Databases, Web pages, Machine learning, Writing, Internet, Electronic commerce, Web search. Abstract: Web search engines such as Google and Bing provide an easy and convenient way to find web pages that contain input keywords. This provides a user-friendly interface for non-technical users to explore the Web and find relevant data among thousands of Web pages. While numerous advancement has been made to store e-commerce data in the cloud, we have not seen great advancement in terms of search over such data. E-commerce data is usually stored as structured data in relational and graph databases. Thus, an answer to a query keyword is composed of different pieces of data stitched together. As of now, the main method to find answers over this structured data is through predefined search forms. However, these search forms are limited, and developing a new search form is time consuming and expensive. In this work, we present an easy way to explore structured e-commerce data for business users that eliminate the dependency to predefined forms. The new search system is similar to Google, in which the interface is essentially a text box, and non-technical business users enter input keywords into the system. The output is a portion of the data, that covers the input keywords. We propose a new ranking strategy based on machine learning to rank more relevant answers ahead of less relevant ones. Our experiments show this ranking strategy is successful in returning relevant answers. |
16,062 | Please write an abstract with title: Detection of asian hornet’s nest on drone acquired FLIR and color images using deep learning methods, and key words: Biological system modeling, Computational modeling, Neural networks, Color, Streaming media, Task analysis, Drones. Abstract: Asian hornets are considered a pest because of their dangerousness and their impact on the ecosystem. Detecting nests of this species is a difficult task, as they are found in the trees, hidden in the leaves. Our goal is to carry out this detection from images acquired by a drone. We propose in this work a new method, based on the advantages of visible spectrum and FLIR images. We compare two models of state-of-the-art neural networks (YOLO and Mask-RCNN) for this task. The results are presented from the two separate image sets, then by combining the network responses. To do this, a third dataset (for ensemble model) was built by simulating a FLIR acquisition simultaneous with the acquisition in the visible spectrum. Preliminary results show that the best strategy is to use Mask-RCNN on the ensemble model (detection rate of 93%). A discussion on the relevant information present in the images and on taking into account of this information by the networks is also proposed. |
16,063 | Please write an abstract with title: EMG Data Augmentation for Grasp Classification Using Generative Adversarial Networks, and key words: Deep learning, Transfer learning, Muscles, Generative adversarial networks, Fatigue, Electromyography, Robustness. Abstract: Electromyography (EMG) has been used as an interface for the control of robotic hands for decades but with the improvement of embedded electronics and decoding algorithms, many applications are now envisaged by companies. Deep learning has shown the possibility to increase decoding performance but it requires large amounts of data to show its full capabilities. However, recording such amounts of EMG signals face several issues since recording hours of data from patients is very time-consuming and can result in muscle fatigue. We explore a deep learning data augmentation strategy using generative adversarial networks (GANs) to create high-quality synthetic data to increase the performance of grasp classification. |
16,064 | Please write an abstract with title: A SPICE behavioral model for current-controlled magnetic inductors, and key words: SPICE, Inductors, Transformer cores, Magnetic cores, Saturation magnetization, Circuit faults, Magnetic circuits, Capacitors, Magnetic hysteresis, Manufacturing. Abstract: A new SPICE-compatible behavioral model for magnetic controlled inductors was developed and verified experimentally. The new model is based on the gyrator-capacitor scheme in which the nonlinear permeance is emulated by a nonlinear capacitor that is built by using a 'transformer' circuit. The gyrator-capacitor approach can be used to evaluate an arbitrary magnetic circuit, and the nonlinear 'transformer' circuit makes possible the modeling the nonlinearity of the ferromagnetic core. The core saturation and hysteresis are reproduced by applying the core manufacturer's data. A current-controlled inductor was used to test the proposed model. Close agreement was obtained between the simulation and experimental results. |
16,065 | Please write an abstract with title: Why hot chips are no longer "cool", and key words: Consumer products, Network servers, High-speed networks, Process design. Abstract: Chip and system designers are battling a two front war - extracting the last advantages from traditional semiconductor technology scaling on one front, while simultaneously working to contain skyrocketing chip power budgets on the other front. The impacts of this struggle are being felt across market segments far beyond the historic "low power" drivers in mobile consumer products. Today's battle has expanded to include high performance servers, high speed networking products, and highly integrated SoCs driving the latest home media and entertainment systems. This presentation will provide an overview of the business drivers that are forcing these problems to be addressed at all levels of design - process, chip, subsystem, and total system solution - as well as some of the innovative solutions that are being pursued to provide continuing improvements in real-world processor performance. |
16,066 | Please write an abstract with title: Optimizing address code generation for array-intensive DSP applications, and key words: Digital signal processing, Registers, Application software, Optimizing compilers, Parallel processing, Computer science, Design engineering, Embedded system, Array signal processing, Design optimization. Abstract: The application code size is a critical design factor for many embedded systems. Unfortunately, most available compilers optimize primarily for speed of execution rather than code density. As a result, the compiler-generated code can be much larger than necessary. In particular, in the DSP domain, the past research found that optimizing address code generation can be very important since address code can account for over 50% of all program bits. This paper presents a compiler-directed scheme to minimize the number of instructions to be generated to manipulate address registers found in DSP architectures. As opposed to most of the prior techniques that attempt to reduce the number of such instructions through careful address register assignment, this paper proposes modifying loop access patterns in array-intensive signal processing applications. In addition, it demonstrates how the proposed scheme can cooperate with a data layout optimizer for increasing its benefits further. We also discuss how optimizations that target effective address code generation can conflict with data locality-enhancing transformations. We evaluate the proposed approach using twelve array-intensive embedded applications. Our experimental results indicate that the proposed approach not only leads to significant reductions in code size but also outperforms prior efforts on reducing code size of array-intensive DSP applications. |
16,067 | Please write an abstract with title: Precise topography- and aperture-dependent motion compensation for airborne SAR, and key words: Motion compensation, Focusing, Synthetic aperture radar, Interferometry, Surfaces, Azimuth, Layout, Data processing, Sensor phenomena and characterization, Radar tracking. Abstract: Efficient synthetic aperture radar (SAR) processing algorithms are unable to exactly implement the aperture- and topography-dependent motion compensation due to the superposition of the synthetic apertures of several targets having different motion errors and potentially different topographic heights. Thus, during motion compensation, a reference level is assumed, resulting in residual phase errors that impact the focusing, geometric fidelity, and phase accuracy of the processed SAR images. This letter proposes a new short fast Fourier transform-based postprocessing methodology capable of efficient and precise compensation of these topography- and aperture-dependent residual phase errors. In addition to wide beamwidth (very high resolution) SAR systems, airborne repeat-pass interferometry especially benefits from this approach, as motion compensation can be significantly improved, especially in areas with high topographic changes. Repeat-pass interferometric data of the E-SAR system of the German Aerospace Center (DLR) are used to demonstrate the performance of the proposed approach. |
16,068 | Please write an abstract with title: Performance of nonlinear dispersive APML in high-order FDTD schemes, and key words: Dispersion, Finite difference methods, Time domain analysis, Nonlinear equations, Maxwell equations, Polarization, Magnetic fields, Anisotropic magnetoresistance, Perfectly matched layers, Integral equations. Abstract: A consistent reformulation of the anisotropic perfectly matched layer (APML) absorbing boundary has been presented for general nonlinear dispersive media. The APML is then adopted in the high-order finite-difference-based schemes, and improved absorption has been achieved. |
16,069 | Please write an abstract with title: Speaker-Independent Microphone Identification in Noisy Conditions, and key words: Training, Performance evaluation, Time-frequency analysis, Noise reduction, Robustness, Recording, Noise measurement. Abstract: This work proposes a method for source device identification from speech recordings that applies neural-network-based denoising, to mitigate the impact of counter-forensics attacks using noise injection. The method is evaluated by comparing the impact of denoising on three state-of-the-art features for microphone classification, determining their discriminating power with and without denoising being applied. The proposed framework achieves a significant performance increase for noisy material, and more generally, validates the usefulness of applying denoising prior to device identification for noisy recordings. |
16,070 | Please write an abstract with title: Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning Attack, and key words: Training, Machine learning algorithms, Signal processing algorithms, Machine learning, Speech processing, Optimization, Convergence. Abstract: This paper discusses formulations and algorithms which allow a number of agents to collectively solve problems involving both (non-convex) minimization and (concave) maximization operations. These problems have a number of interesting applications in information processing and machine learning, and in particular can be used to model an adversary learning problem called network data poisoning. We develop a number of algorithms to efficiently solve these non-convex min-max optimization problems, by combining techniques such as gradient tracking in the decentralized optimization literature and gradient descent-ascent schemes in the min-max optimization literature. Also, we establish convergence to a first order stationary point under certain conditions. Finally, we perform experiments to demonstrate that the proposed algorithms are effective in the data poisoning attack. |
16,071 | Please write an abstract with title: Applying Deep Learning in Mars Exploration: A Neural Network-based Study to Classify Martian Terrain Features, and key words: Deep learning, Mars, Dairy products, Space missions, Neurons, NASA, Market research. Abstract: The red planet has persisted in being the top destination for space exploration and has also fascinated researchers to experiment with frequently launched its dataset of images. NASA has launched various missions on the track of space expeditions to explore the surface and the environment of the potential life-sustaining planet. Among all the missions for capturing images of the Martian terrain, the HiRISE experiment has been successful in coming up with the best datasets featuring the surface of Mars. In this research study, the authors have targeted the classification of this high-quality image dataset produced as the outcome of the HiRISE using a deep learning model. The proposed model is convoluted and built with the help of neural network layers (neuron layers). Based on the classification, the authors were able to classify the images of 7 terrain features of Mars, namely Crater, Impact Ejecta, Bright Dune, Dark Dune, Slope Streak, Spider, and Swiss Cheese. And the classification accuracy achieved by the model is 94.8%. |
16,072 | Please write an abstract with title: A Real-Time Analysis of Human Performance in Interactive and Adaptive Mixed-Reality Simulation, and key words: Measurement, Adaptation models, Analytical models, Adaptive systems, Computational modeling, Virtual reality, Real-time systems. Abstract: Intelligent adaptive systems generally use inferential or computational methods to identify and adapt to the user’s internal state of interest. Toward an adaptive human-in-the-loop simulation, his article defines, implements, and validates an analytic scheme to estimate real-time, task-specific, and comprehensive human performance encompassing perception and action. The proposed scheme builds on the previous work of mixed reality (MR) simulation app designed to perform a virtual object-following task for screening and diagnosis of neurocognitive impairment. The proposed human performance model adopts the Fitts’ paradigm of speed-accuracy tradeoff in the context of continuous, rapid aimed movements. For validation, the performance quantification of eleven healthy subjects over two repeated sessions was statistically analyzed. The results potentially confirm a qualification of the metric in terms of stability (by not showing statistically significant variance over repetition), but for an accurate estimate of individual performance, the scheme needs to be adjusted with its segmentation threshold. |
16,073 | Please write an abstract with title: Software reliability estimation for modular software systems and its applications, and key words: Software reliability, Software systems, Application software, Computer architecture, Markov processes, Software testing, Analytical models, Logistics, Information management, System testing. Abstract: In this paper, an analytical model for estimating the reliability of a module-based software system is proposed. The model assumes that the software modules are heterogeneous and the transfers of control between modules follow a discrete time Markov process. Moreover, the failure process of an individual module is assumed to be a non-homogeneous Poisson process (NHPP), and the time-dependent behavior of corresponding testing effort is modeled by a logistic distribution. The author also demonstrates how this analytical approach can be employed to measure the reliability of a software system including multiple-input/multiple-output systems and heterogeneous software systems. |
16,074 | Please write an abstract with title: Digital frequency/phase offset correction for 60 GHz OFDM radio-over-fibre with unlocked fibre lasers, and key words: MILLIMETER WAVE, FIBRE WIRELESS, RADIO-OVER-FIBRE, OPTICAL FRONTHAUL. Abstract: Analog radio-over-fibre transmission is hindered by its sensitivity to frequency and phase fluctuations. This work presents a hybrid approach through digital frequency and phase offset estimation/correction, enabling optical heterodyne transmission of 60 GHz OFDM over 25km of fibre using two unlocked fibre lasers. |
16,075 | Please write an abstract with title: Trajectory Tracking Control of an Underwater Swimming Manipulator with State Constraints, and key words: Uncertainty, Trajectory tracking, Snake robots, Radial basis function networks, Manipulators, Robustness, Closed loop systems. Abstract: The underwater swimming manipulator is a new type of underwater vehicle manipulator composed of an underwater snake robot and several thrusters. In this paper, trajectory tracking control is considered for the USM system with state constraints and model uncertainties. The barrier Lyapunov function combined with the backstepping method is introduced to design an adaptive controller to guarantee the state constraints satisfaction. The radial basis function neural networks are employed to approximate the unknown system parameters and external disturbances to enhance the robustness of the system. By Lyapunov stability theory analysis, it is proved that the closed-loop system is semi-globally uniformly bounded. Furthermore, the effectiveness of the proposed method is verified with simulation. |
16,076 | Please write an abstract with title: Performance Comparison of Large-Scale Design-Optimized Non-Overlap and Overlap Winding Wound Rotor Synchronous Generators, and key words: Windings, Optimization, Stators, Stator windings, Rotors, Harmonic analysis, Torque. Abstract: The use of non-overlap windings rather than overlap windings is a topic for debate. Non-overlap windings are generally cheaper and easier to manufacture but result in a high amount of magnetomotive force sub- and higher-order harmonics. A strategy to reduce these harmonics has been previously published and this study aims to provide a performance comparison of a large-scale wound rotor synchronous generator with a modified non-overlap winding and a classical overlap winding. Hence, design optimisations of a 16/18 and 16/72 pole/slot grid-connected 3 MW wound rotor synchronous generator for medium-speed wind generation are conducted. The optimisations are performed using the modified method of feasible direction gradient-based optimisation because of its simplicity and fast results. Optimal solutions for the 16/18 and 16/72 3 MW models are obtained and the performance of the solutions compared. The results show that the 3 MW 16/18 model performs favourably against the 3 MW 16/72 model, especially regarding the lower active mass. |
16,077 | Please write an abstract with title: Fault Location on Point-to-Point HVDC Transmission System by the Electromagnetic Time-Reversal-Based Method, and key words: Resistance, HVDC transmission, Estimation, Europe, Fault location, Data models, Electromagnetics. Abstract: The fault location technique based on the electromagnetic time reversal (EMTR) theory has demonstrated great success on different kinds of power networks. Previous work has presented good results from its application on multiterminal HVDC systems, although the modelling considered in this work was not as realistic as possible. Since the method uses fault-induced electromagnetic transients, the modelling of the converter stations and the HVDC links can impact the results of the technique. This work thus brings a further evaluation of the EMTR-based fault-location method on a point-to-point HVDC transmission link upon simulation data, as the previous work, but using sophisticated modelling. The converter stations and the cable link are modelled with the most complete models available in EMTP-RV, to resemble the real condition of fault in the simulations. Pole-to-ground and pole-to-pole faults are simulated with different values of resistance at two different locations along with the cable link. The observed results show a great influence of the fault resistance, being the accuracy of the fault location estimation low only in some situations. |
16,078 | Please write an abstract with title: Resonance Measurement of Even and Odd Mode Propagation Constants in Coupled Microstrips, and key words: Resonance, Propagation constant, Microstrip, Strips, Inverters, RLC circuits, Reflection, Attenuation, Resonant frequency, Transmission lines. Abstract: The resonant properties of transmission-line resonators can be used to measure the line propagation constant. This technique is applied here to the even and odd modes of propagation of symmetrical pairs of coupled micro- strips. A sample measurement is presented and possible extensions in the use of the method are outlined. |
16,079 | Please write an abstract with title: Method for Mining Frequent Item Sets Considering Average Utility, and key words: Itemsets, Databases, Computational modeling, Decision making, Numerical models, Data mining, Informatics. Abstract: Data mining is used to determine helpful data and information from large data bases for decision making in different fields. In today's scenario, mining high-utility itemsets (HUIs) has become a current investigation area. In traditional method HUIs are found on the basis individual utility of an item-set, which in turn is calculated as the totality of the utilities of individual items. But the problem is that the above way of finding HUIs does not consider length of item-set into consideration, while calculating HUIs. In real world situations, it is desirable to calculate average utility while considering both the length of item-sets and their utilities. This paper proposes an algorithm to find the high average-utility item-sets (HAUIs) seeing both parameters i.e. length of itemsets and their utilities. A numerical example is devised to explain the proposed approach. Experiments on real life databases shows that suggested model can proficiently discover the total set of HAUIs. |
16,080 | Please write an abstract with title: Non-Gaussian Extensions for the Detection of Persistent Scatterers: Addressing the Limitations of Gaussian Models for InSAR Imagery, and key words: Deformable models, Analytical models, Shape, Radar detection, Detectors, Radar scattering, Radar imaging. Abstract: It is well-known that the backscatter of high-resolution Synthetic Aperture Radar (SAR) imagery is non-Gaussian in nature. As a result, corresponding heavy-tailed models have been successfully incorporated for the design of improved SAR target detectors. However, Gaussian-based detectors are largely still applied for selection of persistent scatterers (PS) in Interferometric Synthetic Aperture Radar (InSAR) imagery, and implications for the performance of PS techniques have not been well-studied. Here, we extend an existing Gaussian model for PS to incorporate non-Gaussian behavior. We then implement the model for PS detection and compare its performance to its Gaussian counterpart, finding that the non-Gaussian model finds a slightly denser network of PS. Further work will focus on analyzing the characteristics of this disparity, including its relationship with terrain and system parameters such as wavelength and bandwidth, and compare the estimated deformation from the non-Gaussian detector compared to an existing Gaussian-based model. Understanding the limitations of Gaussian models will inform the design of improved PS detectors to produce more complete deformation maps and enable the broader application of InSAR for challenging applications, such as observing small strain rates in natural terrain. |
16,081 | Please write an abstract with title: Designing learning objects with the ELO-tool, and key words: XML, Telematics, Educational technology, Computer science, Technological innovation, Internet, Computer science education, Content based retrieval, Standards development, Management training. Abstract: Technological innovations can be important factors for change. The Internet is one such and it has modified the way people live and interact. In education, the effect of this change is visible in the way educational materials are designed, developed and distributed, and in the roles played by the teacher/designer, the student and the content provider. Learning objects technology and supporting tools now permits the generation of on-line educational materials. We present a framework for the generation, integration and reuse of learning objects, intended to (a) resolve the limitations of existing tools (b) provide interoperability between learning objects, and (c) provide mechanisms to compose new learning objects from old. |
16,082 | Please write an abstract with title: Design of thermally-stable perpendicular media for 50-200 Gb/in/sup 2/, and key words: Predictive models, Demagnetization, Signal design, Noise level, Thermal stability, Magnetic recording. Abstract: Summary form only given. Thermally-activated decay of magnetization limits high-density magnetic recording. Five stable perpendicular media designs have been found for reliable data storage at 50-200 Gb/in/sup 2/. |
16,083 | Please write an abstract with title: Inverse neurovascular coupling and associated spreading depolarization models for traumatic brain injury, and key words: Couplings, Neurons, Muscles, Ions, Brain modeling, Mathematical models, Potassium. Abstract: The paper presents the mathematical model of cortical spreading depolarisation and its effect on inverse neurovascular coupling. The paper considers the potassium ion channels present in the neuron-astrocyte blood vascular network to access the role of potassium ions during spreading depolarisation and associated inverse neurovascular coupling. Simulation of our proposed mathematical model confirms the experimental results that an increase in concentration of potassium ions beyond 20mM in the perivascular space essentially leads to vasoconstriction and hence inverse neurovascular coupling. The propagatory nature of depolarizing potassium waves has been unraveled though our proposed mathematical model. |
16,084 | Please write an abstract with title: Analysis, simulation and testing of a novel 4-element current-source resonant inverter, and key words: Analytical models, Testing, Resonant inverters, Resonance, RLC circuits, Transient response, Circuit analysis, Steady-state, Impedance, Resonant frequency. Abstract: High-frequency resonant power converters are an attractive choice for high power density applications. Only resonant converters with 2 energy-storage elements have been studied and used for applications. However, some of the drawbacks of this class of converters (including poor load regulation, discontinuous mode operation and poor transient response) can be overcome by the judicious augmentation of the resonant circuit. This paper presents the results of a study performed on a novel 4-element current-source resonant inverter circuit. These include analytical results on its steady-state characteristics (including input impedance, resonant frequency, input-output transfer function, individual component voltage and current stresses, and efficiency). In addition, samples of analytically derived design charts, simulation results and experimental results are shown. They indicate that this resonant inverter has certain advantages over present ones. |
16,085 | Please write an abstract with title: Nonlinear adaptive prediction of complex-valued signals by complex-valued PRNN, and key words: Recurrent neural networks, Pipeline processing, Signal processing algorithms, Adaptive filters, Neurons, Adaptive signal processing, Neural networks, Multidimensional signal processing, Biomedical signal processing, Signal processing. Abstract: A complex-valued pipelined recurrent neural network (CPRNN) for nonlinear adaptive prediction of complex nonlinear and nonstationary signals is introduced. This architecture represents an extension of the recently proposed real-valued PRNN of Haykin and Li in 1995. To train the CPRNN, a complex-valued real time recurrent learning (CRTRL) algorithm is first derived for a single recurrent neural network (RNN). This algorithm is shown to be generic and applicable to general signals that have complex domain representations. The CRTRL is then extended to suit the modularity of the CPRNN architecture. Further, to cater to the possibly large dynamics of the input signals, a gradient adaptive amplitude of the nonlinearity within the neurons is introduced to give the adaptive amplitude CRTRL (AACRTRL). A comprehensive analysis of the architecture and associated learning algorithms is undertaken, including the role of the number of nested modules, number of neurons within the modules, and input memory of the CPRNN. Simulations on real-world and synthetic complex data support the proposed architecture and algorithms. |
16,086 | Please write an abstract with title: Integrated grating devices for optical networks, and key words: Gratings, Optical fiber networks, Optical materials, Integrated optics, Photonics, Optical control, Process control, Control systems, Optical devices, Signal processing. Abstract: At TRLabs, the photonics group is working on projects that have as their goal the demonstration of novel materials and integrated devices for optical networks. In this paper, we discuss two projects that involve the control and processing of optical signals by grating-based devices as well as the investigation of chalcogenide glasses as promising material systems for integrated optics. |
16,087 | Please write an abstract with title: 1-Bit Metasurface-Based Beam-Scanning Circularly Polarized Folded Reflector Antenna, and key words: Circular polarization, PIN diode, 1-bit phase encoding, beam scanning. Abstract: A circularly polarized (CP) and electronically reconfigurable folded reflector antenna (ERFRA), which has wide-angle beam scanning performance, is developed and demonstrated. The CP-ERFRA comprises a receiver-transmitter metasurface (RTMS), an electronically reconfigurable metasurface (ERMS), and a metallic patch acting as the feeding source. The RTMS completely reflects the x-polarized incident waves and transmits the y-polarized waves into CP waves, and the ERMS is formed by integrating two PIN diodes in each meta-atom. By controlling the on-off state of PIN diodes, the ERMS can achieve 1-bit phase encoding and linear polarization conversion. Due to these RTMS and ERMS properties, the ERFRA can generate CP radiation with beam-control ability. A 16 × 16 CP-ERFRA is fabricated and tested to verify the feasibility of the proposed design. The experimental results show that the beam scanning angle is up to ±50°, and the peak gain and aperture efficiency are 18.8 dBic and about 16.5%, respectively. |
16,088 | Please write an abstract with title: Transmission properties of conjugate-root pulses, and key words: Band pass filters, Matched filters, Intersymbol interference, Filtering, Pulse shaping methods, Noise reduction, Frequency domain analysis, Bandwidth, Piecewise linear techniques, Signal analysis. Abstract: A family of pulses has recently been reported by Xia that are intersymbol interference-free with and without matched filtering. Reportedly, such pulses are important for systems where both matched filter and unmatched receivers are used. The transmission characteristics of these pulses are compared to the more commonly used raised-cosine pulse for three different receiver scenarios. |
16,089 | Please write an abstract with title: Comparative application of the Crank-Nicolson and State-Space methods to the solution of nonlinear instantaneous eddy current and flux penetration problems in electrical machines, and key words: State-space methods, Eddy currents, Finite difference methods, Machinery, Magnetic flux, Permeability, Current density, Synchronous machines, Senior members, Eddy current testing. Abstract: Two numerical methods are presented and compared for solution of nonlinear instantaneous electromagnetic diffusion problems. Finite differences are used for discretization of space. The Crank-Nicolson and improved State-Space methods are used for time. A magnetic vector potential (m.v.p.) formulation is used, which is effective in simplifying programming implementation to electrical machinery problems with complex contours. The methods are applied to a practical example of eddy currents, flux penetration and losses, and are found to yield results which are in excellent agreement with experimental test data. The results include a vivid display of the distortive effect of magnetic non-linearity on eddy current and flux density wave forms. The comparative suitability of both methods are evaluated in light of their characteristics and results. |
16,090 | Please write an abstract with title: Self-Supervised Depth and Ego-Motion Estimation for Monocular Thermal Video Using Multi-Spectral Consistency Loss, and key words: Cameras, Image reconstruction, Temperature measurement, Loss measurement, Training, Pose estimation, Pipelines. Abstract: A thermal camera can robustly capture thermal radiation images under harsh light conditions such as night scenes, tunnels, and disaster scenarios. However, despite this advantage, neither depth nor ego-motion estimation research for the thermal camera have not been actively explored so far. In this paper, we propose a self-supervised learning method for depth and ego-motion estimation from thermal images. The proposed method exploits multi-spectral consistency that consists of temperature and photometric consistency loss. The temperature consistency loss provides a fundamental self-supervisory signal by reconstructing clipped and colorized thermal images. Additionally, we design a differentiable forward warping module that can transform the coordinate system of the estimated depth map and relative pose from thermal camera to visible camera. Based on the proposed module, the photometric consistency loss can provide complementary self-supervision to networks. Networks trained with the proposed method robustly estimate the depth and pose from monocular thermal video under low-light and even zero-light conditions. To the best of our knowledge, this is the first work to simultaneously estimate both depth and ego-motion from monocular thermal video in a self-supervised manner. |
16,091 | Please write an abstract with title: Wideband guided-mode resonance filters with low-loss material, and key words: Polyethylene, Absorption, Films, Simulation, Dielectric materials, Refractive index, Resonant frequency. Abstract: We report an all-dielectric single-layer guided-mode resonance filter (GMRF) operating in the wideband terahertz (THz) region. To obtain strong resonance in this region, a dielectric material must have a low refractive index and low absorption at wideband THz frequencies, and a high tensile strength (TS) is needed. Cyclic olefin copolymer (COC) films have a lower refractive index and lower absorption than polyethylene terephthalate (PET) films and a higher TS than polytetrafluoroethylene (PTFE) films. Thus, COC is a suitable dielectric material for wideband THz designs. The reported GMRF operates in the range of 0.576-2.759 THz, which agrees well with rigorous coupled-wave analysis (RCWA) simulation results. |
16,092 | Please write an abstract with title: A MEMS-based hybrid circuit having metallized cavity for Ku-band wireless communication, and key words: Circuits, Metallization, Wireless communication, Insertion loss, Inductors, Shunt (electrical), Capacitors, Microelectromechanical systems, Micromechanical devices, Silicon. Abstract: We present a hybrid circuit fabricated by means of MicroElectroMechanical System (MEMS) process technology. It has been newly developed as a component for the application to wireless communication system. The hybrid circuit consists of inductors and shunt capacitors, which have been fabricated on a silicon wafer. In our device, an etched 30 /spl mu/m deep cavity is utilized to minimize insertion losses of transmission lines for inductors. Moreover, the bottom of cavity is metallized for the ground biasing of shunt capacitors. Our metallized cavity structure and proposed fabrication process scheme for that have the advantages in terms of insertion loss issue and a variety of applicability in RF MEMS field. In S-parameter measurement, we obtained 2.03 dB and 2.18 dB as insertion losses and 21.63 dB as return loss at 12 GHz. The measured frequency characteristics are also well agreed with the simulation results. |
16,093 | Please write an abstract with title: Modeling and Hovering Control of 5-DoF Tilt-Birotor Robot, and key words: Robots, Mathematical model, Actuators, Force, Analytical models, Torque, Rotors. Abstract: This paper explores design, modeling and hovering control of a new under-actuated 5-DoF (degree of freedom) tilt-birotor robot. Specifically, the robot has an assembled inverted pendulum to be an extra actuating input in addition to a pair of tilt wings. Hence, it has a 5-DoF actuator control input vector: two motor thrusts, two tilt angles, and one tunable pendulum angle. We show the model analysis in terms of the Newton-Euler formulation and establish a key equation between the model control inputs and the actuator inputs. Based on that, we are able to achieve the hovering control task using an inner-outer-loop design. We also illustrate the results by numerical and experimental tests. |
16,094 | Please write an abstract with title: Reconstruction of Current Density Distribution in Low-Voltage Switching Devices Through TSVD and TGSVD Regularization, and key words: Current density, Low voltage, Current distribution, Switches, Mathematical model, Faces, Image reconstruction. Abstract: This article examined two regularization methods for reconstructing the arc current density distribution of a switching device in an arc-quenching chamber. The finite-element method (FEM) was used to discretize the current-flow region of the arc-quenching chamber. Both truncated generalized singular value decomposition (TGSVD) and truncated singular value decomposition (TSVD) regularization were used to reconstruct the current density distribution. TGSVD addressed the poor reconstruction accuracy caused by the ill-posedness of the Biot-Savart operator. Simulation results showed that the reconstruction of current density distribution was more accurate with higher signal-to-noise ratios (SNRs) and lower mean-square errors (MSEs). Both regularization methods were accurate with low noise levels, although the reconstruction accuracy of TGSVD was more sensitive to noise than that of TSVD regularization. |
16,095 | Please write an abstract with title: Experimental verification of a simulation model for extra-fast communication on twisted pair lines, and key words: Mechatronics, Power cables, Employment, Crosstalk, Modulation, Transmission line measurements, Modems. Abstract: Today, G.fast subscriber technology belongs to the most advanced access network technologies used in practice and it should be used for massive FTTx development. However, only the narrow band of G.fast subscriber lines is ready for practical deployment. Due to this fact, simulations and modeling of G.fast lines based on different transmission parameters and environment are important in order to estimate future access networks development. For that reason, it is important to implement additional parameters to provide more accurate and relevant modeling and simulations of real access networks and various types of G.fast transmission lines. This paper deals with modeling and simulations of G.fast lines in typical twisted pairs in industry environment. The article provides calculations and simulations of G.fast lines for various types of metallic cables and under different conditions, including specific profiles of crosstalk spectral densities. Next, these theoretical simulations are compared with real measurements, which increases the accuracy of the modeling. These presented models can be used to accurately estimate the performance of local networks under different conditions in practice. |
16,096 | Please write an abstract with title: Blockchain-Based Incentive Energy-Knowledge Trading in IoT: Joint Power Transfer and AI Design, and key words: Batteries, Artificial intelligence, Smart devices, Internet of Things, Wireless power transfer, Performance evaluation. Abstract: Recently, edge artificial intelligence techniques (e.g., federated edge learning) are emerged to unleash the potential of big data from Internet of Things (IoT). By learning knowledge on local devices, data privacy preserving and Quality of Service (QoS) are guaranteed. Nevertheless, the dilemma between the limited on-device battery capacities and the high energy demands in learning is not resolved. When the on-device battery is exhausted, the edge learning process will have to be interrupted. In this article, we propose a novel wirelessly powered edge intelligence (WPEG) framework, which aims to achieve a stable, robust, and sustainable edge intelligence by energy harvesting (EH) methods. First, we build a permissioned edge blockchain to secure the peer-to-peer (P2P) energy and knowledge sharing in our framework. To maximize edge intelligence efficiency, we then investigate the wirelessly powered multiagent edge learning model and design the optimal edge learning strategy. Moreover, by constructing a two-stage Stackelberg game, the underlying energy-knowledge trading incentive mechanisms are also proposed with the optimal economic incentives and power transmission strategies. Finally, simulation results show that our incentive strategies could optimize the utilities of both parties compared with classic schemes, and our optimal learning design could realize the optimal learning efficiency. |
16,097 | Please write an abstract with title: Regulated Power Supply with High Power Factor for Hyperspectral Imaging Applications, and key words: Power supplies, Lighting, Harmonic analysis, Power harmonic filters, Voltage control, Cameras, Distortion. Abstract: In Bachelor and Master's Thesis, it is highly advisable to involve students in research projects. Additionally, project-based approaches where several final degree theses are related could encourage the motivation of students. Especially in STEM (Science, Technology, Engineering and Mathematics) subjects, this divide-and-conquer strategy could lead in skills improvements of students in different, but related, fields. In this manuscript, we present the development of a controlled and highly stable power supply to be used as excitation of the light source of a hyperspectral imaging system. |
16,098 | Please write an abstract with title: A GAN-Based Image Transformation Scheme for Privacy-Preserving Deep Neural Networks, and key words: Visualization, Neural networks, Europe, Signal processing, Generative adversarial networks, Robustness, Image classification. Abstract: We propose a novel image transformation scheme using generative adversarial networks (GANs) for privacy-preserving deep neural networks (DNNs). The proposed scheme enables us not only to apply images without visual information to DNNs, but also to enhance robustness against ciphertext-only attacks (COAs) including DNN-based attacks. In this paper, the proposed transformation scheme is demonstrated to be able to protect visual information on plain images, and the visually-protected images are directly applied to DNNs for privacy-preserving image classification. Since the proposed scheme utilizes GANs, there is no need to manage encryption keys. In an image classification experiment, we evaluate the effectiveness of the proposed scheme in terms of classification accuracy and robustness against COAs. |
16,099 | Please write an abstract with title: Blind Source Separation and Sparse Bump Modelling of Time Frequency Representation of Eeg Signals: New Tools for Early Detection of Alzheimer's Disease, and key words: Blind source separation, Brain modeling, Time frequency analysis, Electroencephalography, Alzheimer's disease, Spatiotemporal phenomena, Probes, Neural networks, Sensitivity and specificity, Machine learning. Abstract: The early detection of Alzheimer’s disease (AD) is an important challenge. In this paper, we propose a novel method for early detection of AD using only electroencephalographic (EEG) recordings for patients with Mild Cognitive Impairment (MCI) without any clinical symptoms of the disease who later developed AD. In our method, first a blind source separation algorithm is applied to extract the most significant spatiotemporal uncorrelated components; afterward these components are wavelet transformed; subsequently the wavelets or more generally time frequency representation (TFR) is approximated with sparse bump modeling approach. Finally, reliable and discriminant features are selected and reduced with orthogonal forward regression and the random probe methods. The proposed features were finally fed to a simple neural network classifier. The presented method leads to a substantially improved performance (93% correctly classified - improved sensitivity and specificity) over classification results previously published on the same set of data. We hope that the new computational and machine learning tools provide some new insights in a wide range of clinical settings, both diagnostic and predictive. |
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