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10,700 | Please write an abstract with title: Smart Visual Sensing for Overcrowding in COVID-19 Infected Cities Using Modified Deep Transfer Learning, and key words: Monitoring, Feature extraction, Decision making, COVID-19, Videos, Statistics, Sociology. Abstract: Currently, COVID-19 is circulating in crowded places as an infectious disease. COVID-19 can be prevented from spreading rapidly in crowded areas by implementing multiple strategies. The use of unmanned aerial vehicles (UAVs) as sensing devices can be useful in detecting overcrowding events. Accordingly, in this article, we introduce a real-time system for identifying overcrowding due to events such as congestion and abnormal behavior. For the first time, a monitoring approach is proposed to detect overcrowding through the UAV and social monitoring system (SMS). We have significantly improved identification by selecting the best features from the water cycle algorithm (WCA) and making decisions based on deep transfer learning. According to the analysis of the UAV videos, the average accuracy is estimated at 96.55%. Experimental results demonstrate that the proposed approach is capable of detecting overcrowding based on UAV videos' frames and SMS's communication even in challenging conditions. |
10,701 | Please write an abstract with title: Robust Decentralized and Distributed Estimation of a Correlated Parameter Vector in MIMO-OFDM Wireless Sensor Networks, and key words: Estimation, Wireless sensor networks, Quantization (signal), Uncertainty, Correlation, OFDM, Wireless communication. Abstract: An optimal precoder design is conceived for the decentralized estimation of an unknown spatially as well as temporally correlated parameter vector in a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) based wireless sensor network (WSN). Furthermore, exploiting the temporal correlation present in the parameter vector, a rate-distortion theory based framework is developed for the optimal quantization of the sensor observations so that the resultant distortion is minimized for a given bit-budget. Subsequently, optimal precoders are also developed that minimize the sum-MSE (SMSE) for the scenario of transmitting quantized observations. In order to reduce the computational complexity of the decentralized framework, distributed precoder design algorithms are also developed which design precoders using the consensus based alternating direction method of multipliers (ADMM), wherein each SN determines its precoders without any central coordination by the fusion center. Finally, new robust MIMO precoder designs are proposed for practical scenarios operating in the face of channel state information (CSI) uncertainty. Our simulation results demonstrate the improved performance of the proposed schemes and corroborate our analytical formulations. |
10,702 | Please write an abstract with title: A Distributed Array Antenna System, and key words: Antenna arrays, Space stations, Phased arrays, Antenna accessories, Frequency conversion, Radio frequency, Microwave antenna arrays, Microwave antennas, High power amplifiers, Reliability engineering. Abstract: The Space Station communication system will use microwave frequency radio links to carry digitized information from sender to receiver. The ability of the antenna system to meet stringent requirements on coverage zones, multiple users, and reliability will play an important part in the overall multiple access communication system. This paper will describe the configuration of a multibeam conformal phased array antenna and the individual microwave integrated components incorporated into this antenna system. |
10,703 | Please write an abstract with title: Approximate Nonlinear Discrete-Time Models Based on B-Spline Functions, and key words: Splines (mathematics), Nonlinear dynamical systems, Numerical models, Mathematical model, Taylor series. Abstract: We consider the discretization of continuous-time nonlinear systems described by normal forms. In particular, we consider the case when the input to the system is generated by a B-spline hold device to obtain an approximate discrete-time model. It is shown that the corresponding sampled-data model and its accuracy (measured in terms of the local truncation error) depend on the smoothness of the input and on the applied integration strategy, namely, the truncated Taylor series expansion. Moreover, the sampling zero dynamics of the discrete-time model are asymptotically characterized as the sampling period goes to zero, and it is shown that these zero dynamics converge to the asymptotic sampling zeros of the linear case. |
10,704 | Please write an abstract with title: Polarised TOPSAR operational model of internal wave generation mechanism, and key words: Polarization, Sea surface, Digital elevation models, Continuous wavelet transforms, Surface waves, Surface topography, Radar detection, Sea measurements, Wavelet transforms, Frequency estimation. Abstract: The generation mechanism of internal waves can be investigated by polarised SAR data. The integration between digital elevation model and Canny algorithm will be more useful for automatic detection of internal waves. The aim of this paper is to understand the generation mechanism of internal waves in shallow water of Malaysian coastal waters. The continuous wavelet transform is used to estimate energy and wavelengths within solution peaks from the detect internal wave. The Doppler radar was used to model the speed of internal wave. This study shows that the polarized P/sub HH/ band is more suitable for internal wave detection compared to L/sub HH/ and C/sub vv/ bands. It can be concluded that polarised SAR data could be used to understand the generation mechanism of internal waves. It can said that internal waves on the shallow waters of Malaysia are generated by strong tidal current flow over the irregular bottom topography. |
10,705 | Please write an abstract with title: A novel ICI cancellation scheme to reduce both frequency offset and IQ imbalance effects in OFDM, and key words: OFDM, Throughput, Robustness, Radio transmitters, Phase noise, Oscillators, Fading, Frequency diversity, Intelligent networks, Computer science. Abstract: The performance of orthogonal frequency division multiplexing (OFDM) system degrades due to intercarrier interference (ICI). Recently, a simple ICI self-cancellation scheme has been proposed to reduce ICI due to frequency offset errors. Despite its 50% throughput loss, it is very effective in cancelling ICI. However, it does not remove the constant phase error, which has a considerable influence on the error performance of the OFDM system depending on the modulation scheme used. We propose new cancellation schemes, namely adjacent conjugate symbol repetition (ASSR) and symmetric conjugate symbol repetition (SCSR), to eliminate this phase error while reducing ICI. The proposed SCSR also eliminates the in-phase and quadrature (IQ) imbalance effects completely. Analytical results show that SCSR offers an average carrier-to-interference ratio (CIR) gain of 10 dB for the normalized frequency offset of 0.1 over that of conventional scheme. We evaluate the error performance of 16-QAM with various frequency offset and IQ-imbalance impairments and demonstrate SCSR's robustness to these impairments. |
10,706 | Please write an abstract with title: Object Detection Using Dual Graph Network, and key words: Knowledge engineering, Visualization, Semantics, Directed graphs, Object detection, Detectors, Feature extraction. Abstract: Most object detection methods focus only on the local information near the region proposal and ignore the object's global semantic relation and local spatial relation information, resulting in limited performance. To capture and explore these important relations, we propose a detection method based on a graph convolutional network (GCN). Two independent relation graph networks are used to obtain the global semantic information of the object in labels and the local spatial information in images. Semantic relation networks can implicitly acquire global knowledge, and by constructing a directed graph on the dataset, each node is represented by the word embedding of labels and then sent to the GCN to obtain high-level semantic representation. The spatial relation network encodes the relation by the positional relation module and the visual connection module, and enriches the object features through local key information from objects. The feature representation is further improved by aggregating the outputs of the two networks. Instead of directly disseminating visual features in the network, the dual-graph network explores more advanced feature information, giving the detector the ability to obtain key relations in labels and region proposals. Experiments on the PASCAL VOC and MS COCO datasets demonstrate that key relation information significantly improve the performance of detection with better ability to detect small objects and reasonable boduning box. The results on COCO dataset demonstrate our method obtains around 32.3% improvement on AP in terms of small objects. |
10,707 | Please write an abstract with title: Weighted Nonlinear Dynamic System for Deep Extraction of Nonlinear Dynamic Latent Variables and Industrial Application, and key words: Feature extraction, Nonlinear dynamical systems, Correlation, Microwave integrated circuits, Data models, Informatics, Machine learning. Abstract: Soft sensor plays an increasingly important role in modern industrial processes for estimating key quality variables which are hard to measure. With the development of deep learning technologies, soft sensors based on the deep learning methods have drawn great attention. Aiming to predict key quality variables, a supervised weighted nonlinear dynamic system (WNDS) model aided by the maximal information coefficient (MIC) is proposed in this article. The variational autoencoder is employed into the system for extracting nonlinear dynamic features. The supervised WNDS model can simultaneously analyze the correlations between variables and the relationships between historical samples and present samples. Furthermore, the proposed method is extended to a semisupervised form, in order to handle the imbalanced numbers between routinely recorded process data and limited labeled quality data. The prediction performance is validated by an industrial case. |
10,708 | Please write an abstract with title: Machine Learning Algorithm Analysis for Detecting and Classification Faults in Power Transmission System, and key words: Support vector machines, Machine learning algorithms, Power transmission lines, Power transmission, Prediction algorithms, Propagation losses, Classification algorithms. Abstract: The importance of Power Transmission System PTS fault detection and classification is increasing day by day as because consumption of electricity is increasing. Short circuit fault in Power Transmission Line Network PTLN can cause severe damage to the power transmission system as well as economic loss. Power Transmission System requires new methods to detect and classify fault behaviour to prevent it from heavy damage. Machine Learning ML algorithms can be very effective to classify and detect various types of faults within the PTLN. There are variety of ML algorithms to recognise and classify the faults but as complexity of PTS is increasing day by day, reliability of these algorithms is decreasing. This study uses various types of ML algorithms to generate predictive models to evaluate what kind of algorithm is more appropriate to recognise and classify faults within the PTLN. Faults investigated in this research work include (L-L) double line fault, (L-L-L) three phase fault, (L-G) line to ground fault, (L-L-G) double line to ground fault, and (L-L-L-G) three phase fault with the involvement of the ground. The data was evaluated using six (06) ML algorithms that are Decision Tree, Support Vector Machine (SVM), K-Nearest Neighbor (Knn), Random Forest, XGBoost (XGB) and Naive Bayes (NB) for recognise of fault and classification within the PTLN. The performance of ML algorithms obtained by comparing the results and determine which algorithm is fast and more accurate. These results can be used to create more effective ML algorithms for PTS. The results indicate that the application of ML algorithms for PTS task could improve the PTLN yield and save time for technical teams. |
10,709 | Please write an abstract with title: Performance Evaluation of SD-WAN Deployment for XYZ Enterprise Company in Indonesia, and key words: Wide area networks, Multiprotocol label switching, Standards organizations, Bandwidth, Switches, Virtual private networks, Broadband communication. Abstract: Internet use has been exceptional during the previous several decades. As a result, Wide Area Network (WAN), employed in all types of inter-data center, enterprise, and carrier networks, has become a vital infrastructure since it serves as one of the internet's most crucial transmission mediums. However, due to the transfer of enterprise data to the cloud, internet traffic in the future is changing. As a result, traditional WAN connectivity will be inadequate. One of the viable solutions to this is to implement Software-Defined WAN (SD-WAN) for enterprises, particularly in Business-to-Business (B2B). SD-WAN replaces existing Multi-Protocol Label Switching (MPLS) with multi-broadband internet with high bandwidth, encrypted with Virtual Private Network (VPN) IP Sec standard, and simplifies branch management with a single dashboard covering multiple branches. This study aims to evaluate the performance of deploying SD-WAN on mining enterprises' public links such as Direct Internet Access (DIA), fixed broadband, and 4G LTE, and private links, namely, Very Small Aperture Terminal (VSAT) and Multi-Protocol Layer Switching (MPLS), by utilizing SD-WAN's architecture and scenarios testing with the head office in Jakarta and branch office in Balikpapan. The results obtained that SD-WAN works appropriately when one of the multiple links is down. Meanwhile, when multiple links are down, the SD-WAN can still access a Voice over IP (VoIP) and video conference between the head office in Jakarta and a branch office in Balikpapan. |
10,710 | Please write an abstract with title: Reliability Enhancement of Synchrophasor-Based DTR system considering N-1 contingency for PMU placement, and key words: Transmission line measurements, Phasor measurement units, Information and communication technology, Smart grids, Safety, Reliability, Wide area measurements. Abstract: The cyber power network has become more intelligent and efficient because of the integration of information and communication technology (ICT) infrastructure. By combining intelligent infrastructure such as phasor measurement units (PMUs), smart sensors, and other two-way communication and monitoring capabilities, this enhances reliability and sustainability. They do, however, have some disadvantages, such as component and communication network failures, as well as cyber breaches, which might compromise the existing network’s reliability. Dynamic Thermal Rating (DTR) systems which is a smart grid technology, improves existing line ratings by allowing them to be increased based on several parameters without violating line safety requirements. Thus, this paper presents a DTR system that uses PMUs to implement Wide Area Monitoring (WAM) functions and investigates the impact of PMU failures and line outages on cyber-physical network reliability. The study uses a Monte Carlo simulation-based method to carry out the investigation on the IEEE RTS while considering the impacts of seven and thirteen PMUs. The test network is modified to emphasize the benefits of ICTs and the findings show that using PMUs enhances reliability greatly. While the use of seven PMUs offers reliability improvement by 53.15%, the use of 13 PMUs offers more significant improvement (by 95.79%) because a single line outage will not affect network observability. |
10,711 | Please write an abstract with title: A Fundamental Experiment on Contact Position Estimation on Vision based Dome-type Soft Tactile Sensor using Ready-made Medium, and key words: Tactile sensors, Cameras, Estimation, Service robots, Deep learning. Abstract: Tactile sensors are critical components in robotics fields. Recently, soft tactile sensor utilizing vision is actively developed for safe human machine interaction. Some researches use novel custom-made medium in order to achieve tactile sensing. Deep learning can recognize pattern from any vision data when it has sufficient dataset, i.e., the system does not require specific pattern embedded hardware for the pattern recognition. To achieve soft tactile sensor's economical application for robot fingers, this paper presents a fundamental experiment on contract position estimation on vision based dome-type soft tactile sensor utilizing ready-made silicon as a medium and convolutional neural network. In order to estimate and classify the contact position, convolutional neural network (CNN) was applied. The modified VGGNet architecture was coded using Tensorflow and Keras. 1000 images were taken to train the modified VGG network; 200 images were taken for each neutral, left, right, lower, upper direction. For each direction, fingertip, pencil, ruler, and table corner were utilized to capture various situations. After checking the results of the test set, the trained model was applied to the embedded board and checked the contact position estimation in real-time. The experiment showed high accuracy on classifying the con-tact position of the vision based dome-type soft tactile sensor in real time. This contact position estimation system will be critical for the finger-typed robots since the system is reasonably small and it will reduce significant amount of manufacturing cost for the safe human machine interaction system. For the future work, we will acquire more image data and apply more advanced network architecture to improve accuracy. |
10,712 | Please write an abstract with title: High birefringence liquid crystal mixtures for laser beam steering, and key words: Birefringence, Liquid crystals, Beam steering, Viscosity, Adaptive optics, Phased arrays, Optical arrays, Optical devices, Optical fiber networks, Adaptive arrays. Abstract: Summary form only given. Optical phased arrays (OPA) represent a versatile device for laser beam steering, adaptive optics, electronic lens, and network switching. An applied stepwise voltage creates a phase grating inside the liquid crystal (LC) media that deflects the incoming laser beam to a programmable angle with high precision and high energy efficiency. LC mixtures with /spl Delta/n/spl ges/0.4 and low viscosity, wide nematic range, low operating voltage and good UV stability are particularly desirable. Tolane liquid crystals exhibit a reasonably high /spl Delta/n, low viscosity, and good chemical, photo and thermal stability. The same properties are also found in isothiocyanates. Therefore, coupling tolane and NCS groups should lead to a high birefringence and large dielectric anisotropy while preserving a relatively low viscosity. |
10,713 | Please write an abstract with title: A method for realizing high-precision monitoring of satellite clock based on BeiDou's co-satellite RDSS and RNSS signals, and key words: Satellites, Satellite broadcasting, Mathematical model, Receivers, Atomic clocks, Monitoring. Abstract: The paper focuses the use RDSS and RNSS signal of the BeiDou satellite to realize the precision satellite clock monitoring method. This paper analyzes the frequency transfer relationship of RDSS/RNSS which is the co-satellite of BeiDou's GEO satellites, establishes the relevant frequency transfer equation, and proposes a satellite clock precision monitoring algorithm using RDSS/RNSS signals' carrier phase combination in the MCS (Master Control Station). The paper verified the method by computer simulation. Compared with the traditional pseudo-range-based method, the method has the advantages of not relying on satellite ephemeris and higher precision. |
10,714 | Please write an abstract with title: A new method for composite system annualized reliability indices based on genetic algorithms, and key words: Interconnected systems, Genetic algorithms, Power system reliability, Sampling methods, State-space methods, Power system modeling, Load flow, Load modeling, System testing, Power generation. Abstract: This paper presents a genetic algorithms (GA) based method for state sampling of composite power system. Sampled states are used to assess annualized reliability indices. In the proposed method GA intelligently searches the enormous state space of a power system to find the most probable states contributing to system failure. Binary encoded GA is used to represent system states. Through its fitness function GA is able to trace failure states in a more intelligent manner than conventional methods. A linearized optimization load flow model is used for evaluation of sampled states. The model takes into consideration importance of load in calculating load curtailment at different buses in order to obtain a unique solution for each state. The full set of composite system adequacy indices and load bus indices is calculated. The proposed method is applied to a sample test system to be validated. Obtained results are compared with other conventional methods. |
10,715 | Please write an abstract with title: Contribution of NOMA Signalling to Practical Multibeam Satellite Deployments, and key words: Measurement, NOMA, Satellites, Space communications, Multimedia systems, Conferences, Modulation. Abstract: This work explores the contribution of Non-Orthogonal Multiple Access (NOMA) signalling to improve some relevant metrics of a multibeam satellite downlink. Users are paired to exploit Signal-to-Noise Ratio (SNR) imbalances coming from the coexistence of different types of terminals, and they can be flexibly allocated to the beams, thus relaxing the cell boundaries of the satellite footprint. Different practical considerations are accommodated, such as a spatially non-uniform traffic demand, non-linear amplification effects, and the use of the DVB-S2X air interface. Results show how higher traffic volumes can be channelized by the satellite, thanks to the additional bit rates which are generated for the strong users under the superposition of signals, with carefully designed power levels for DVB-S2X modulation and coding schemes in the presence of non-linear impairments. |
10,716 | Please write an abstract with title: Integrated Circuit Compatible Surface Acoustic Wave Devices On Gallium Arsenide, and key words: Surface acoustic wave devices, Acoustic waves, Gallium arsenide, Surface acoustic waves, Materials science and technology, Microwave integrated circuits, Charge coupled devices, Digital integrated circuits, Integrated circuit technology, MESFETs. Abstract: Improvements in gallium arsenide materials technology have led to the rapid development of GaAs MIC, CCD, and digital IC technologies in the last several years. In this paper we consider the additional capabilities afforded by the inherent piezoelectric properties of GaAs. The primary emphasis of the work is on surface acoustic wave (SAW) device configurations using MESFET and Schottky-barrier diode fabrication techniques which are compatible with the eventual monolithic integration of electronic devices on the same substrate. The GaAs SAW technology described here provides a means for achieving electronically variable delay, high-Q resonator structures for VHF/UHF oscillator frequency control, and real-time signal processing operations such as convolution and correlation. Prototype device designs and performance are described, includlng two-port GaAs SAW resonators with Q's as large as 13 000 at 118 MHz and a programmable GaAs SAW PSK correlator capable of signal correlation at 10-MHz chip rates. Further GaAs SAW device development required for increasing the operating frequency range to 500 MHz and processing bandwidth to 100 MHz is indicated. |
10,717 | Please write an abstract with title: A real-time model for COVID19 face-mask identification with “YOLOv4”, and key words: COVID-19, Deep learning, Epidemics, Face recognition, Surveillance, Government, Object detection. Abstract: At the beginning of 2020 WHO declared COVID19 as an epidemic; healthcare industries experts and academicians from worldwide are working in the directions to surveillance the daily behaviors of the citizens to combat the COVID-19 cases. In India, we thank the government for performing its outperformed active measures and spontaneous compliance to follow the policy of wearing masks when moving out to any public places; it entails active real-time monitoring to supervise the citizens by governments. In this process, real-time face-mask identification is a very challenging task of computer vision. And the absence of accurate datasets for this problem is a critical hard problem to solve. To address this bottleneck, we are proposing our real-time deep learning face-mask identification technique with annotated class labels with bounding boxes which have its real-time application to assist the governments to control and prevent the spread of these epidemics in its supervision. Our model is very robust and effective to classify the real-time images and videos for face mask detection with accuracy and average precision. The proposed model substitutes the manual surveillance with the object detection method using YOLOv4 supported on a deep learning approach to monitor the crowd accurately even if they change their respective locations. The experiment identify or classify the object within any dataset to distinguish the images or videos with two class labels such as “with-mask” and “without-mask” with approximately 98.26% accuracy, mAP of 68.28%, recall of 77%, and precision of 57%. |
10,718 | Please write an abstract with title: Performance Analysis of a Solar Energized Air-Conditioning System, and key words: Radiation effects, Torque, Pollution, Carbon dioxide, Power system harmonics, Batteries, Pollution measurement. Abstract: High contaminated input current and excessive carbon emission in the air conditioning system (AConS) is a serious issue which arises heating in distribution systems and surroundings and not good. To address the severity of this issue, it is proposed here to use the Sun energy to energize AConS. During the absence of Sun or at low intensity level, a battery is incorporated in the system to maintain the constant voltage. The system is designed using simulink and various performance parameters such as torque and speed are being measured and discussed in detail to meet the requirements of conventional AConS. |
10,719 | Please write an abstract with title: Optimizing Embedded Industrial Safety Systems Based on Time-of-flight Depth Imaging, and key words: Measurement, Power demand, Three-dimensional displays, Power measurement, Cameras, Throughput, Real-time systems. Abstract: Time-of-flight camera systems provide rapid, low-latency depth imaging. In the context of industrial safety, they can be employed to replace costly and inflexible physical safety installations with virtual safety volumes, monitored by time-of-flight cameras which turn off dangerous systems when unknown objects enter specified bounding volumes.In this context, the 3D point-shape collision detection algorithm has to be highly optimized for very specific goals. These include high real-time (worst case) performance, low power consumption and acceptable thermal characteristics, ideally with low-cost and well-established embedded hardware.We present our work in the INPACT project, which explores various algorithmic and parallelization-based methods of improving the performance, responsiveness and reliability of such systems. Our experiments are are based on a setup allowing long-term measurement of multiple thermal sampling points as well as fine-grained power consumption information and of course performance and throughput metrics. |
10,720 | Please write an abstract with title: Load pocket forecasting software, and key words: Load forecasting, Probability distribution, Power system planning, Power industry, Weather forecasting, Load modeling, State estimation, Distributed computing, Mathematics, Software tools. Abstract: In this paper we describe the load pocket forecasting software that can be used by electric utilities to estimate and forecast the load growth in different service areas. The software builds statistical load models for various service areas (load pockets), estimates weather-normalized loads, estimates the ratios between the actual peak loads and the loads that would happened on designed days (weather normalized factors), and estimates the next year peak load. In particular, the software can be used to calculate the probability distributions of the next year peak loads for different load pockets. The software can be used for area planning purposes. The software contains user's tools to design new load pockets and to modify the existing ones. |
10,721 | Please write an abstract with title: Enabling Large-Scale Correlated Electronic Structure Calculations: Scaling the RI-MP2 Method on Summit, and key words: Codes, Tensors, Quantum chemistry, Heuristic algorithms, Graphics processing units, Clustering algorithms, Supercomputers. Abstract: Second-order Møller-Plesset perturbation theory using the Resolution-of-the-Identity approximation (RI-MP2) is a state-of-the-art approach to accurately estimate many-body electronic correlation effects. This is critical for predicting the physicochemical properties of complex molecular systems; however, the scale of these calculations is limited by their extremely high computational cost. In this paper, a novel many-GPU algorithm and implementation of a molecular-fragmentation-based RI-MP2 method are presented that enable correlated calculations on over 180,000 electrons and 45,000 atoms using up to the entire Summit supercomputer in 12 minutes. The implementation demonstrates remarkable speedups with respect to other current GPU and CPU codes, excellent strong scalability on Summit achieving 89.1% parallel efficiency on 4600 nodes, and shows nearly-ideal weak scaling up to 612 nodes. This work makes feasible ab initio correlated quantum chemistry calculations on significantly larger molecular scales than before on both large supercomputing systems and on commodity clusters, with a potential for major impact on progress in chemical, physical, biological and engineering sciences. |
10,722 | Please write an abstract with title: Peer identification in wireless and sensor networks using signal properties, and key words: Wireless sensor networks, Intelligent networks, Signal processing, Peer to peer computing, Ad hoc networks, Communication system security, Authentication, Data security, Intelligent sensors, Collaboration. Abstract: In this paper, we investigate methods to determine a transmitting peer node's location using signal properties and trusted-peer collaboration. We then consider how this location information can establish peer identity confidence. Specifically, we consider using signal direction, signal strength, and collaboration to establish the transmitter's location with sufficient precision to enable identification through location. Network density, node characteristics such as size and speed, and communication capabilities are all considered in our analysis |
10,723 | Please write an abstract with title: Parametric localization of multiple incoherently distributed sources using covariance fitting, and key words: Sensor arrays, Covariance matrix, Parameter estimation, Direction of arrival estimation, Radar scattering, Approximation algorithms, Costs, Array signal processing, Multiple signal classification, Sonar. Abstract: A new algorithm for parametric localization of multiple incoherently distributed sources is proposed. Our algorithm is based on an approximation of the array covariance matrix using central and non-central moments of the source angular power densities. Based on this approximation, a new computationally simple covariance fitting-based technique is proposed to estimate these moments. The source parameters are then obtained from the moment estimates. Compared to earlier algorithms, our technique has lower computational cost and obtains the parameter estimates in a closed form. Also, it can be applied to scenarios with multiple sources that may have different angular power densities while other known methods are not applicable to such scenarios. |
10,724 | Please write an abstract with title: Tunable coherent IR and FIR sources utilizing modulational instability, and key words: Finite impulse response filter, Frequency, Fiber nonlinear optics, Optical modulation, Signal generators, Nonlinear optics, Optical pumping, Kerr effect, Optical fiber dispersion, Amplitude modulation. Abstract: A new tunable coherent infrared (IR) source is presented. It utilizes the sideband produced by modulational instability of an optical signal in a fiber which results from a combination of anomalous dispersion and the nonlinear Kerr effect. The generated frequency is in proportion to the square root of the optical pump signal. A coherent IR signal is generated by extracting the sideband. |
10,725 | Please write an abstract with title: Analysis of Coaxial Line Discontinuities by Boundary Relaxation, and key words: Coaxial components, Capacitance, Differential equations, Frequency, Strips, Difference equations, Partial differential equations, Acceleration, Finite difference methods, Application software. Abstract: Discontinuities in coaxial lines may in general be represented in equivalent networks by lumped capacitances. The calculation of discontinuity capacitance is possible by means of mode-matching techniques for very simple discontinuities; for more complex cases, direct numerical methods are preferable. A new numerical technique is presented for solving the field problem in a region bounded on two sides by infinitely extending coaxial lines. The approach used is to define operators by means of which the potentials at a given cross-sectional plane of the coaxial line are related to potentials at another plane. The problem of a discontinuity region between two infinitely long lines is thereby converted into a finite problem with prescribed boundary operators in place of boundary values. Standard methods may be used to solve the problem in a finite region. Subsequent reformulation of the discontinuity capacitance in terms of stored energy permits calculation of this capacitance from the potential values in only a minimal region. The resulting computer programs are at least an order of magnitude faster than previously published ones. |
10,726 | Please write an abstract with title: A Deep Learning-based Generic Solder Defect Detection System, and key words: Training, Industries, Adaptation models, Costs, Image color analysis, Production, Optical imaging. Abstract: Automated optical inspection (AOI) is essential in the electronic manufacturing production line. Strict screening rules lead to a high false alarm rate of AOI. Many industries use AI models to classify defects. The lack of flawed data and the uneven distribution of categories is a big challenge for model training. Furthermore, the AI model must be retrained when adding new production line data, and the time cost is high. In order to reduce the false alarm rate and improve the generalization of the AI model, we build a deep learning- based generic solder defect detection system (GSDD) to classify defects into seven types. In GSDD, the color gradation adjustment module solves the problem of color difference, and the data augmentation module solves the problem of variable data. In the experiment, we use the data set provided by the enterprise to evaluate the accuracy of the model to 96%, and the model can be applied to different machines. Thus, GSDD is a general model and can efficiently detect defects. |
10,727 | Please write an abstract with title: Streaming-Aware Cellular Resource Allocation for UHD Video Streaming over Ultra Dense Network, and key words: Cellular networks, Tuners, 5G mobile communication, Streaming media, Programming, Master-slave, Complexity theory. Abstract: Ultra-High-Definition (UHD) videos have absorbed great attention in recent years. However, as they are of significant size, streaming them require an extremely high bandwidth to achieve a good quality of experience, which poses a great challenge on the current cellular networks. Realizing the great potentials of coordinated multi-point joint transmission (JT-CoMP) in 5G Ultra Dense Network, we propose a novel Tuner framework for the UHD video streaming service. In this framework, we strive to design an efficient algorithm for VBS sleeping and VBS grouping to maximize the data rates of overall video users while reducing the overhead of cellular networks. To this end, we provide a comprehensive framework model and formulate a single-timescale VBS sleeping & grouping problem. We design a novel master-slave based algorithm to solve the formulated mixed-integer programming problem optimally with low complexity. In addition, we extend it to facilitate the more practical setting, i.e., two-timescale VBS sleeping & grouping. Extensive simulations validate the superior performance of our framework in various system settings. |
10,728 | Please write an abstract with title: Control Method of Grid Rudder Correction Fuze based on Terminal Sliding Mode Control, and key words: Torque, Trajectory, Sliding mode control, Projectiles, Friction, Force, Electromagnetics. Abstract: The existing roll angle control methods of 2D trajectory correction fuze have some disadvantages, such as strong model dependence, poor engineering realizability, uncontrollable response time and sizeable steady-state error. According to the aerodynamic characteristics of grid rudder fuze, a grid rudder correction fuze control method based on Terminal sliding mode control was proposed. The second-order nonlinear system of grid rudder fuze roll Angle control was established, and the Terminal sliding mode controller of grid rudder fuze roll Angle correction was designed. At the same time, the stability and rapidity of the control system were guaranteed, and the strong anti-interference ability was shown. The standard is that the fuze roll Angle stability error accuracy is less than 3° and the control time is less than 3S. Theoretical analysis and simulation show that the control method of grid rudder correction fuze based on Terminal sliding mode control can meet the requirements of grid rudder correction system for fuze roll Angle control. Compared with the general sliding mode variable structure control, the response time of the control system is controllable, and the control system has stronger robustness. |
10,729 | Please write an abstract with title: New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation, and key words: Phasor measurement units, Kalman filters, Time measurement, Power systems, Mathematical model, Frequency estimation. Abstract: This article presents a new Kalman filter (KF) approach to power system state estimation (SE) based on phasor measurement units (PMUs), in which the knowledge of the system frequency is exploited to ensure the accuracy of the estimated quantities even under off-nominal conditions. In the proposed solution, the frequency is added as a new state variable to be estimated so that its value can be known with lower uncertainty, thus leading to more accurate estimates also for node voltages and branch currents. All the frequency measurements available from PMUs can be exploited through the presented method to improve the estimation. In order to assess the benefits given by the integration of the frequency knowledge, the performance of the new approach is compared to different SE methodologies, by means of simulations carried out on the New England IEEE 39-bus system under different realistic operating conditions and measurement configurations. Performed tests take into account, in particular, the possible occurrence of off-nominal frequency conditions, highlighting the issues associated with traditional PMU-based KF approaches and proving the effectiveness of the proposed solution. |
10,730 | Please write an abstract with title: Performance Analysis of Resampling and Ensemble Learning Methods on Diabetes Detection as Imbalanced Dataset, and key words: Electrical engineering, Deep learning, Education, Diabetes, Performance analysis, Classification algorithms, Ensemble learning. Abstract: Early detection of diabetes is essential to reducing a high mortality rate. Early detection can be made by studying the possibility of diabetes from the variables obtained in the data of diabetes patients. How to diagnose a patient with medical data becomes a challenge because these are usually imbalanced, where negative cases severely outnumber positive cases. For preprocessing the imbalanced data, this paper designs an algorithm using resampling techniques combined with an ensemble learning algorithm. There are some oversampling techniques ADASYN, ROS, and SMOTE. Whereas, the undersampling techniques are RUS, Tomek, and ENN. The combined techniques like SMOTE-ENN and SMOTE-Tomek are also used to handle highly imbalanced dataset diabetes. Then, the ensemble learning algorithm that is used is Random Forest, Bagging, AdaBoost, and XGBoost. Based on the experimental results, the best performance is using SMOTE-ENN with AdaBoost, with a recall score of 0.7330 even though the F1-Score of this model is 0.6459. AdaBoost Classifier also has good and stable results with various types of resampling. By using SMOTE-ENN, the recall score of the model increased by 0.1819 and the F1 score decreased by 0.2000 from the original model result. The higher sensitivity/recall is more important in medical diagnoses to correctly identify patients with disease than the F1 Score. |
10,731 | Please write an abstract with title: Age of Information for Short-Packet Covert Communication, and key words: Measurement, Closed-form solutions, Information age, Linear programming. Abstract: In this letter, we develop a new framework to jointly characterize covertness and timeliness of short-packet communications, in which a new metric named covert age of information (CAoI) is first proposed and then a closed-form expression for the average CAoI is derived. Our examination explicitly reveals the tradeoff between communication covertness and timeliness affected by the block-length, transmit power and prior transmission probability. Multiple transmission designs are tackled in order to minimize the average CAoI subject to covertness constraint, where the resultant differences relative to the designs with traditional metrics (e.g., effective covert rate, AoI) as objective functions are clarified. Our examination demonstrates that the optimal block-length is not the largest one, which is optimal in delay-constrained covert communication without considering the communication timeliness, and the optimal prior transmission probability may not be 1/2, which has been widely assumed in the literature of covert communications. |
10,732 | Please write an abstract with title: Study of on-line monitoring method of partial discharge for power transformers based on RFCT and microstrip antenna, and key words: Microstrip antennas, Monitoring, Partial discharges, Power transformers, Microstrip components, Oil insulation, Power transformer insulation, Pulse transformers, EMP radiation effects, Pulse modulation. Abstract: It is an important means for partial discharge (PD) on-line monitoring of oil-immersed power transformers in order to evaluating the insulation condition. Radio frequency current transducers (RFCT) are applied to couple the PD pulse current signal, and the difference-balance pairs (one of three-phase bushing-tap grounding terminals respectively corresponded with the neutral or iron core terminal) are selected, and high speed data acquisition card is adopt to sample the PD signal (>10MS/s) from the balance pair, and further amplitude modulation, phase modulation and difference arithmetic is designed, then external electromagnetic interference is effectively suppressed and it is propitious to extracting PD pulses and judge the PD occurrence place. The wideband PD couplers based on microstrip antenna are also applied to detect the high frequency PD pulse signal. Four sensors are installed at the special parts on the transformer where PD electromagnetic wave signal can be received, then the signal is transmitted to the input analog channel of the oscilloscope (>IGS/s). So single PD waveform analysis throughout more wide frequency band can be done, and further PD fault location can also be realized. The PD on-line monitoring system based on the above two monitoring methods for in-service transformer has also been developed and installed at one main transformer in a plant (220/18RV, 360MVA, three phase and dual winding) |
10,733 | Please write an abstract with title: A Massive MIMO Signal Detection Method Based on ZF Method, and key words: Shape, Imaging, Massive MIMO, Mean square error methods, Matrices, Reliability, Iterative methods. Abstract: The 5th generation communication technology(5G) is becoming more and more significant so that almost major economies in the world has invested numerous resource in the construction of communication technology. However, Massive MIMO which is one of the 5G core technology bumps into an inevitable challenge how to calculate the inverse of large-scale more efficiently and apace. There are many method based on iterative algorithm in convergence condition such as Gauss-Seidel method. All of those methods relay on the short way of the special shape matrix to reckon inverse. They can not work well in inadequate iterations. Hence, we propose a novel zero-forcing method to solve the problem about how to reckon inverse in another way based on matrix inversion lemma and dismantling matrix. |
10,734 | Please write an abstract with title: Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition, and key words: Gesture recognition, Training, Real-time systems, Heuristic algorithms, Electrodes, Clustering algorithms, Electromyography. Abstract: Surface electromyography (sEMG) provides an intuitive and non-invasive interface from which to control machines. However, preserving the myoelectric control system's performance over multiple days is challenging, due to the transient nature of the signals obtained with this recording technique. In practice, if the system is to remain usable, a time-consuming and periodic recalibration is necessary. In the case where the sEMG interface is employed every few days, the user might need to do this recalibration before every use. Thus, severely limiting the practicality of such a control method. Consequently, this paper proposes tackling the especially challenging task of unsupervised adaptation of sEMG signals, when multiple days have elapsed between each recording, by introducing Self-Calibrating Asynchronous Domain Adversarial Neural Network (SCADANN). SCADANN is compared with two state-of-the-art self-calibrating algorithms developed specifically for deep learning within the context of EMG-based gesture recognition and three state-of-the-art domain adversarial algorithms. The comparison is made both on an offline and a dynamic dataset (20 participants per dataset), using two different deep network architectures with two different input modalities (temporal-spatial descriptors and spectrograms). Overall, SCADANN is shown to substantially and systematically improves classification performances over no recalibration and obtains the highest average accuracy for all tested cases across all methods. |
10,735 | Please write an abstract with title: Spectral Features derived from Single Frequency Filter for Multispeaker Localization, and key words: Time delay estimation, Multispeaker localization, Single frequency filter, Cross correlation. Abstract: In this paper, we present a multispeaker localization method using the time delay estimates obtained from the spectral features derived from the single frequency filter (SFF) representation. The mixture signals are transformed into SFF domain from which the temporal envelopes are extracted at each frequency. Subsequently, the spectral features such as mean and variance of temporal envelopes across frequencies are correlated for extracting the time delay estimates. Since these features emphasize the high SNR regions of the mixtures, correlation of the corresponding features across the channels leads to robust delay estimates in real acoustic environments. We study the efficacy of the developed approach by comparing its performance with the existing correlation based time delay estimation techniques. Both, a standard data set recorded in real-room acoustic environments and simulated data set are used for evaluations. It is observed that the localization performance of the proposed algorithm closely matches the performance of a state-of-the-art correlation approach and outperforms other approaches. |
10,736 | Please write an abstract with title: Theoretical Investigation of Photoacoustics From Cancer Cells: Modified Models, and key words: Cancer, Absorption, Melanoma, Mathematical model, Finite element analysis, Prognostics and health management, Nanoparticles. Abstract: Photoacoustic (PA) technology has wide applications in cell study. However, photoacoustics from cancer cells lacks adequate understanding. Here, we establish two modified models for theoretical investigation of photoacoustics from cancer cells. The first model is based on endogenous absorbers of cancer cells, which can be measured by label-free PA microscopy. Different from previous studies about PA for cancer cells that are limited to melanoma cells, our model considers general cancer cells. Further, the feasibility of cancer cell cycle analysis via PA spectrum analysis is demonstrated. The second model is based on exogenous absorbers, e.g., nanoparticles (NPs), in cancer cells. The interactions between NPs and cells in PA signal generation are considered. The nucleus-to-cytoplasm ratio, refractive index, cellular uptake of NPs, NPs size heterogeneity and cell size are modeled to evaluate the contribution of each factor to the change of PA signal amplitudes, which is valuable to guide experiments for cancer cell identification by utilizing different PA signal amplitudes between normal cells and cancer cells. In conclusion, our study comprehensively investigates photoacoustics from cancer cells, which lays theoretical groundwork for future research on PA techniques for cancer cells and is expected to be useful for cancer diagnosis, treatment, and prognosis. |
10,737 | Please write an abstract with title: A design of chaos synchronizing system using adaptive observer, and key words: Chaos, Adaptive systems, Chaotic communication, Programmable control, Adaptive control, Observers, Systems engineering and theory, Communication system control, Broadband communication, Modeling. Abstract: This paper discusses how to synchronize chaotic systems by using adaptive observers. Chaos synchronization using observers has been proposed if the parameters of a master system are given. The method with adaptive structure an advantage that synchronization can be achieved even if the parameters are unknown. A Proposed controller consists of an adaptive structure and a state estimator. Some numerical elements are presented to verify the proposed method. |
10,738 | Please write an abstract with title: Planar Electrical Capacitance Tomography with Hexagonal Sensor, and key words: Electrodes, Sensitivity, Transmission line matrix methods, Permittivity measurement, Capacitance, Size measurement, Electrical capacitance tomography. Abstract: As a non-radiative, non-invasive, and nondestructive detection technique, the planar electrical capacitance tomography (PECT) has been employed for the defect detection of composite materials. Usually, the PECT sensor of square electrode array has been frequently investigated and discussed, due to its simplicity in the structure and modeling. In this paper, a PECT sensor of the hexagonal electrode array is proposed, which aims to offer better sensitivity and image quality. The hexagonal sensor has been evaluated and compared with the square sensor by numerical and experimental tests. The parameters of mean square error (MSE) and correlation coefficient (CC) indicate that the dielectric distribution images could be significantly improved. In addition, the hexagonal sensor tends to demonstrate better capability in discriminating the defect of smaller size. |
10,739 | Please write an abstract with title: Slow Wave Propagation in Generalized Cylindrical Waveguides Loaded with a Semiconductor, and key words: Loaded waveguides, Semiconductor waveguides, Electromagnetic waveguides, Conductivity, Millimeter wave technology, Microstrip, Slabs, Millimeter wave propagation, Dielectrics and electrical insulation, Propagation constant. Abstract: For a parallel-plate waveguide and a microstrip line loaded with a semiconductor slab of resistive or active character the complex propagation constant gamma is determined. Gamma is found for higher order branches for microwave and millimeter-wave frequencies between 10 and 140 GHz, representing a very comprehensive study of phase velocity slowing. An assessment of slowing in generalized cylindrical waveguide structures at millimeter-wave frequencies is obtained from this study. |
10,740 | Please write an abstract with title: Securing organizational internal e-learning development, and key words: Electronic learning, Educational technology, Computer aided instruction, Distance learning, Internet, Application software, Education, Educational institutions, Business, Information management. Abstract: Organizations worldwide are now seeking more innovative and efficient ways to deliver training to their geographically dispersed workforce, and with traditional training methods, companies generally spend more money on transporting and housing trainees than on actual training programs. E-learning has the capacity to reduce these costs significantly and enabled organizations to secured their product or service knowledge. This paper focuses on how organization can secure their internal e-learning development and advocate combination of technological approaches. It also provides a framework on how organization /or academic institution should make a rational decision regarding the implementation of e-learning. The question posed by this paper is that: can organizations improve their e-learning while also securing higher level of knowledge based?. |
10,741 | Please write an abstract with title: Early stages on the graphitization of electrostatically generated PAN nanofibers, and key words: Optical fiber sensors, Gold, Optical fiber testing, Scanning electron microscopy, Electrostatic measurements, Conductivity measurement, Scanning probe microscopy, Temperature measurement, Thermal conductivity, Substrates. Abstract: Carbon nanofibers were produced from polyacrylonitrile/N, N-Dimethyl Formamide (PAN/DMF) precursor solution using electrospinning and vacuum pyrolysis at temperatures from 773 K to 1273 K for 0.5, 2, and 5 hours, respectively. Their conductance was measured. It was found that the conductivity increases sharply with the pyrolysis temperature, and increases considerably with pyrolysis time at the lower pyrolysis temperatures of 873, 973 and 1073 K, but varies, less obviously, with pyrolysis time at the higher pyrolysis temperatures of 1173 and 1273 K. |
10,742 | Please write an abstract with title: Space Vector Modulation for High-Power Three-Level NPC Rectifiers Without Even Order Harmonics, and key words: Rectifiers, Support vector machines, Digital modulation, Space vector pulse width modulation, Pulse width modulation converters, Voltage, Guidelines, North America, Frequency conversion, Harmonic analysis. Abstract: Space vector modulation (SVM) is a preferred PWM scheme for multilevel converters mainly due to its flexibility, easy digital implementation and good harmonic profile. However, the conventional SVM scheme normally produces even-order voltage/current harmonics at the rectifier inputs. The even-order harmonic currents are strictly regulated by the harmonic guidelines such as the IEEE Standards 519-1992 in North America. In this paper, the mechanism of even-order harmonic generation is analyzed, and a new SVM scheme that has the ability to eliminate these harmonics is proposed for three-level neutral point clamped (NPC) rectifiers. The harmonic profile of both schemes is investigated by computer simulation. The effectiveness of the proposed scheme is experimentally verified |
10,743 | Please write an abstract with title: ALScA: A Framework for Using Auxiliary Learning Side-Channel Attacks to Model PUFs, and key words: Task analysis, Mathematical models, Side-channel attacks, Computer architecture, Predictive models, Resists, Neural networks. Abstract: Physical unclonable functions (PUFs) have emerged as potent hardware primitives owing to their intrinsic properties of being secret key-free, clone-proof, and lightweight. However, PUFs cannot avoid the threats of machine learning modeling and side-channel attacks (SCAs). Nevertheless, almost all attacks neglect the correlations between the mathematical model and side-channel models introduced by PUF internal parameters; thus, such attacks fail to exploit related data and struggle in modeling complex PUFs. To address this problem, we propose a framework for using auxiliary learning SCAs to model strong PUFs by learning multiple related tasks together. Side-channel information predictions are introduced as auxiliary tasks to facilitate the primary task of predicting response. The parameters hard for the primary task to learn can be shared by the auxiliary tasks that learn the same parameters more straightforwardly. Based on the proposed framework, we design a specific auxiliary learning power SCA that employs power level prediction as the auxiliary task. The proposed attack is implemented with the hard-parameter sharing and hierarchy sharing deep neural networks. Experimental results demonstrate that the proposed attack succeeds in modeling XOR APUF, MPUF, and iPUF and outperforms the state-of-the-art methods in modeling MPUF and iPUF. We evaluate the influences of task relatedness, architecture, and loss weight ratio. Furthermore, we propose a fine-grained classification-based method to generate the auxiliary task with an enhanced relationship to the primary task. According to the response, the class corresponding to a specific side-channel state is further divided into two subclasses. Experimental results demonstrate that the generated auxiliary task promotes performance and alleviates the adverse effects of improper architecture and parameters. |
10,744 | Please write an abstract with title: Application of Big Data Analysis to Foresight the Future: A Review of Opportunities, Approaches, and New Research Directions, and key words: Systematics, Soft sensors, Decision making, Companies, Production, Big Data, Strategic planning. Abstract: This study aims to explore the relationship between data science or what is known as big data and the information specialists who deal with this data and their role in analyzing it to support the decision-making process. It also seeks to introduce modern trends in big data and the skills necessary to benefit from it professionally. This study is a qualitative study based on a systematic review of previous literature. Previous studies were reviewed to identify visible and hidden opportunities due to the foresight future models to use big data in favor of planning for future. The study adopted the descriptive approach in terms of production analysis. Explain the role of data science “big data” in strategic planning and decision-making at professional institutions and companies. The study results indicate the essential and conflicting part of big data in guiding the decisions of large companies and institutions and its positive role in developing products and increasing the efficiency and profits of these companies. In order to make the most of this data, it is necessary to seek the assistance of qualified data experts in different fields who can formulate this data in a way that helps to make logical and accurate decisions and develop strategic plans. The importance of big data in the process of strategic planning and decision-making. Correspondingly, propose the practical foresight approaches to using big data to produce significant strategic planning. |
10,745 | Please write an abstract with title: Japanese 2,000M Deep Submergence Research Vehicle "SHINKAI 2000" System, and key words: Underwater vehicles, Marine vehicles, Oceans, Marine technology, Vehicle safety, Government, Biological system modeling, Geophysics, Minerals, Inspection. Abstract: JAMSTEC (Japan Marine Science and Technology Center) has developed and built up a 2,000m deep submergence research vehicle system. This system is consisted of the submergence vehicle "SHINKAI 2000", her support ship "NATSUSHIMA" and the shoreside base and these make themselves to be a trinity so that the research operations will be carried out safely and efficiently. The construction of this system will be accomplished on the end of October 1981 and thereafter the training of crew using this system and also the research operation will be done. Besides this system, the training simulator for training the submersible crew has also been developed and constructed for safe and sure operation of submersible. In this paper research/development, the principal characteristics and features of the submersible system and the outline of the training simulator are shown. |
10,746 | Please write an abstract with title: Target Detection and Recognition of Radar spectrum Image Based on Yolov5 algorithm, and key words: Training, Deep learning, Target recognition, Radar detection, Signal processing algorithms, Object detection, Millimeter wave radar. Abstract: The vehicle-mounted millimeter-wave radars have been widely mounted on modern smart cars, which greatly improves the accuracy of collecting surrounding environmental information, but driverless cars have higher requirements for safety [1]. Therefore, improving the performance of vehicle-mounted millimeter-wave radars is particularly important. Traditional vehicle-mounted millimeter-wave radars determine target information through the transmission and reception of echoes [2]. In the signal processing process, it is greatly affected by the outside world and it is difficult to maintain high accuracy. Therefore, a radar spectrum image detection method based on deep learning is proposed to quickly identify objects corresponding to the spectrum.First, the vehicle-mounted millimeter radar spectrum mat format data is extracted [3], make the dataset for training, then adjust and optimize the YOLOv5 model according to the situation of the data set, and identify the spectral image using the optimized a training model. In the experiment, 11635 pictures were divided into training set and test set at 9:1, and the average mAP of various targets reached 93.9%, thus detecting the radar echo spectrum based on deep learning and achieving good results. The proposed spectral target detection method [4] can be applied to vehicle-mounted millimeter-wave radar. |
10,747 | Please write an abstract with title: Coupling of CT and PET-18F-FDG Imaging in Arteries with Calcification, and key words: Computed tomography, Veins, Senior citizens, Atherosclerosis, Imaging phantoms, Image decomposition, Arteries. Abstract: PET imaging of arteries is drastically dominated by the emission of activity from blood. In addition, the artery wall (2.3 mm) is thin in comparison to the whole artery section and is thus subject to partial volume effect (PVE). In fact, the whole artery area which has a diameter of 38 mm for the abdominal aorta is affected by PVE. Currently, 18F-FDG uptake in the artery is evaluated by means of standard uptake value (SUV) and tissue-to-blood ratio (TBR). In the case of TBR, the activity in blood is defined from an image of a vein. In the present work, the dynamic 18F-FDG images were decomposed with factor analysis (FA) in images of blood and tissue. Artery images were corrected for PVE with recovery factors deduced from a phantom. Eight subjects were imaged with CT and PET in dynamic mode. Five subjects were under medication for atherosclerosis. The tissue and blood images were used for SUV and TBR calculation and compared to the usual values obtained from the measured images. SUV and TBR were classified based on five levels of intensity of the artery calcifications on CT images and on the extent of the calcifications. SUV and TBR extracted from the decomposed images provided more accurate values than those deduced from the measured images. The method can be used in staging of atherosclerosis disease in elderly and it can be useful in the clinic with imaging in reduced time. |
10,748 | Please write an abstract with title: 3D Vision Sensing for Grasp Planning: A New, Robust and Affordable Structured Light Approach, and key words: Robot vision systems, Hardware, Noise robustness, Shape, Robot sensing systems, White noise, Layout, Testing, Digital cameras, Head. Abstract: In this paper we present a new approach to 3D shape acquisition. This implementation enables a robot arm to move the scan unit over the object without the scan unit being tracked. The chosen structured light approach uses an initially unknown white noise pattern that can easily be projected with any fixed pattern projection system. Object points are acquired on the basis of finding correspondences in the pattern in the camera image of the current scene. This is achieved by using a fast SSD correlation algorithm. In the current test setup we are using a standard video beamer and a standard digital camera, but we have also set up a scan head for fixation on a robots’ wrist. The special requirements of this miniaturized system will be explained as well as our implementation. Our approach reduces hardware complexity to a minimum using only one calibrated camera and one calibrated fixed pattern projector. In this paper we present the whole system also including the calibration procedure. The focus will be on the hardware setup, but we also give an introduction to the software methods used. |
10,749 | Please write an abstract with title: Towards a Maturity Model for Learning Analytics Adoption An Overview of its Levels and Areas, and key words: Analytical models, Data models, Organizations, Education, Data analysis, Task analysis, Standards organizations. Abstract: Learning Analytics is a new field in education whose adoption can bring benefits for teaching and learning processes. However, many higher education institutions may not be ready to start using learning analytics due to challenges such as organizational culture, infrastructure, and privacy. In this context, Maturity Models (MMs) can support institutions to systematize their processes, enabling them to progress successively in the learning analytics adoption. MMs are used in different fields to support the improvement of processes, describing them in terms of maturity levels, and identifying enhancements that could lead an organization to higher levels of such maturity. Thus, this paper presents an outline of a MM for Learning Analytics adoption in higher education institutions, describing its levels and areas, together with its development methodology. |
10,750 | Please write an abstract with title: Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC, and key words: Throughput, Benchmark testing, Runtime, Kernel, Optimization, Graphics processing units, Electric breakdown. Abstract: Recently there has been a rapidly growing demand for faster machine learning (ML) processing in data centers and migration of ML inference applications to edge devices. These developments have prompted both industry and academia to explore custom accelerators to optimize ML executions for performance and power. However, identifying which accelerator is best equipped for performing a particular ML task is challenging, especially given the growing range of ML tasks, the number of target environments, and the limited number of integrated modeling tools. To tackle this issue, it is of paramount importance to provide the computer architecture research community with a common framework capable of performing a comprehensive, uniform, and fair comparison across different accelerator designs targeting a particular ML task. To this aim, we propose a new framework named TFLITE-SOC (System On Chip) that integrates a lightweight system modeling library (SystemC) for fast design space exploration of custom ML accelerators into the build/execution environment of Tensorflow Lite (TFLite), a highly popular ML framework for ML inference. Using this approach, we are able to model and evaluate new accelerators developed in SystemC by leveraging the language's hierarchical design capabilities, resulting in faster design prototyping. Furthermore, any accelerator designed using TFLITE-SOC can be benchmarked for inference with any DNN model compatible with TFLite, which enables end-to-end DNN processing and detailed (i.e., per DNN layer) performance analysis. In addition to providing rapid prototyping, integrated benchmarking, and a range of platform configurations, TFLITE-SOC offers comprehensive performance analysis of accelerator occupancy and execution time breakdown as well as a rich set of modules that can be used by new accelerators to implement scaling up studies and optimized memory transfer protocols. We present our framework and demonstrate its utility by considering the design space of a TPU-like systolic array and describing possible directions for optimization. Using a compression technique, we implement an optimization targeting reducing the memory traffic between DRAM and on-device buffers. Compared to the baseline accelerator, our optimized design shows up to 1.26× speedup on accelerated operations and up to 1.19× speedup on end-to-end DNN execution. |
10,751 | Please write an abstract with title: 1.3 /spl mu/m laterally gain coupled tunable distributed feedback lasers based on GaInNAs, and key words: Distributed feedback devices, Optical coupling, Tunable circuits and devices, Laser feedback, Gratings, Laser tuning, Waveguide lasers, Laser modes, Fiber lasers, Wavelength division multiplexing. Abstract: We have investigated tunable distributed feedback lasers based on GaInNAs/GaAs. We demonstrated continuously tunable devices with side mode suppression ratios of about 35 dB. |
10,752 | Please write an abstract with title: TMM-Nets: Transferred Multi- to Mono-Modal Generation for Lupus Retinopathy Diagnosis, and key words: Lesions, Transfer learning, Retinopathy, Image synthesis, Training, Data models, Biomedical imaging. Abstract: Rare diseases, which are severely underrepresented in basic and clinical research, can particularly benefit from machine learning techniques. However, current learning-based approaches usually focus on either mono-modal image data or matched multi-modal data, whereas the diagnosis of rare diseases necessitates the aggregation of unstructured and unmatched multi-modal image data due to their rare and diverse nature. In this study, we therefore propose diagnosis-guided multi-to-mono modal generation networks (TMM-Nets) along with training and testing procedures. TMM-Nets can transfer data from multiple sources to a single modality for diagnostic data structurization. To demonstrate their potential in the context of rare diseases, TMM-Nets were deployed to diagnose the lupus retinopathy (LR-SLE), leveraging unmatched regular and ultra-wide-field fundus images for transfer learning. The TMM-Nets encoded the transfer learning from diabetic retinopathy to LR-SLE based on the similarity of the fundus lesions. In addition, a lesion-aware multi-scale attention mechanism was developed for clinical alerts, enabling TMM-Nets not only to inform patient care, but also to provide insights consistent with those of clinicians. An adversarial strategy was also developed to refine multi- to mono-modal image generation based on diagnostic results and the data distribution to enhance the data augmentation performance. Compared to the baseline model, the TMM-Nets showed 35.19% and 33.56% F1 score improvements on the test and external validation sets, respectively. In addition, the TMM-Nets can be used to develop diagnostic models for other rare diseases. |
10,753 | Please write an abstract with title: Stress Evaluation of Non-Isolated Converters Modified into Processing Partial Power, and key words: Power system measurements, Density measurement, Simulation, Hardware, Mathematical model, Inductors, Stress. Abstract: Partial power processing circuits handle only a portion of the power that is handled by the converter system and a sizable portion of the power goes from the source to the load directly. This helps to reduce the size of the converter and its cost. It also improves power density and minimises losses, leading to better efficiency. Such converters generally have an isolation between the source and the load using a transformer or a coupled inductor. A connection is made between the primary and secondary sides converting them into a partial power configuration. This paper analyses the voltage and current stresses on the switches of a partial power processing converter constructed using flyback, forward, isolated CuK, isolated Zeta and isolated Sepic converters, validates them with simulation results and brings out the improvement obtained in the stress levels. A comparative assessment is finally made across all these converter configurations. |
10,754 | Please write an abstract with title: Carbon neutral planning for high percentage of renewable power systems considering WIPP as inertia support, and key words: Graphics, Renewable energy sources, Incineration, Conferences, Power system planning, Color, Planning. Abstract: The current inertia problem in high percentage renewable energy power systems is prominent. To address this problem, this paper proposes a carbon-neutral power system planning scheme that applies Waste incineration power plant (WIPP) for inertia support in high proportional renewable energy systems, taking into account the demand for carbon neutrality. Firstly, we analyze the operating characteristics and inertia characteristics of waste-to-energy plants, then we combine the inertia characteristics of high proportional renewable energy systems, and finally we carry out the power system carbon neutral planning. The effectiveness of the proposed method is verified by ieee-24 algorithm simulation. |
10,755 | Please write an abstract with title: Sparse Feature Learning for Human Activity Recognition, and key words: Deep learning, Legged locomotion, Convolution, Activity recognition, Predictive models, Data models, Smart phones. Abstract: In this paper, we propose an end-to-end deep learning model for human activity recognition. Our model is equipped with sparse learning, which absorbs a greater number of classes without making a significant change in the size of the model while sustaining the accuracy of existing classes. In addition, our model is lightweight than state-of-the-art models as we have utilized FCN-LSTM (Fully convolution network - Long Short-term Memory). Our model predicts human activities such as walking, walking-upstairs, walking-downstairs, sitting, standing, and laying (total 6 classes). For validation of our deep learning model, we have utilized a well-known opensource dataset such as the UCIHAR-dataset, which contains collections of smart-phones data of 30-subjects performing different activities with a smartphone. We evaluated the model using sparse learning and have shown that our model outperforms in learning features with few epochs with high accuracy and compact size, and efficient inference time correspondingly. |
10,756 | Please write an abstract with title: 10 tech companies for the next 10 years, and key words: Displays, Technological innovation, Retina, Instruments, Digital integrated circuits, Microcomputers, Integrated circuit technology, Venture capital, Telecommunications, Robots. Abstract: The paper presents a list of the 10 most daring tech start-ups. The field was narrowed down by considering technological innovations in conjunction with the people who have bet on them: people, unlike new ideas, have track records that can be vetted. The 10 companies are as follows: (1) Microvision Inc.; (2) Cybernetix; (3) Lumileds Lighting LLC; (4) MeshNetworks Inc.; (5) Magiq Technologies Inc.; (6) Nantero Inc.; (7) Picsel Technologies Ltd.; (8) Crossbow Technology Inc.; (9) Microchips Inc.; and (10) Semikron International. |
10,757 | Please write an abstract with title: Rate-compatible low-density parity-check codes for digital subscriber lines, and key words: Parity check codes, DSL, Decoding, Turbo codes, Convolutional codes, Performance gain, Laboratories, Design methodology, Communication channels, Delay. Abstract: Rate-compatible low-density parity-check (LDPC) codes obtained from the class of array LDPC codes are presented. The design methodology described herein retains practical advantages of array LDPC codes such as excellent performance and efficient encodability across all the codes in a rate-compatible family. Different codes in the rate-compatible family can be specified by a small number of parameters and constructed algebraically with a small amount of preprocessing. The rate-compatible codes can be decoded using a generic decoder architecture, leading to efficient implementations. These properties make the codes attractive for use in DSL systems that need to support a large number of code parameters to cope with channel variability. |
10,758 | Please write an abstract with title: New ways in engineering education for a sustainable and smart future, and key words: Education, Automation, Engineering education, Technological innovation, Electrical engineering, Knowledge engineering, Sustainable development. Abstract: This Innovative Practice Full Paper presents a constructivist concept for engineering education for non-technical students. Global challenges and transformation processes lead to a rapid increase in problems at the boundary between technical and non-technical disciplines in higher education. Furthermore, new fields of work emerge due to the digital transformation. Graduates need to be prepared to identify and describe problems and to develop appropriate solutions in teams in order to contribute to change processes related to the future in a smart world. Engineering sciences have to take up the challenge to provide suitable educational programs for a broader target group, i.e. non-technical students, especially in light of the current shortage of qualified specialists. This paper contributes twofold to that discourse on transformation processes in Engineering Education: (1) by the development of a theory-based teaching and learning concept on electrical engineering for this special target group of non-technical students; and (2) by presenting the implementation of the undergraduate (bachelor) course with innovative project-based laboratory experiments. |
10,759 | Please write an abstract with title: Matrix Capsule Convolutional Projection for Deep Feature Learning, and key words: Task analysis, Object detection, Training, Convolution, Semantics, Mathematical model, Encoding. Abstract: Capsule projection network (CapProNet) has shown its ability to obtain semantic information, and spatial structural information from the raw images. However, the vector capsule of CapProNet has limitations in representing semantic information due to ignoring local information. Besides, the number of trainable parameters also increases greatly with the dimension of the feature vector. To that end, we propose a matrix capsule convolution projection (MCCP) module by replacing the feature vector with a feature matrix, of which each column represents a local feature. The feature matrix is then convoluted by columns into capsule subspaces to decrease the number of trainable parameters effectively. Furthermore, the CapDetNet is designed to explore the structural information encoding of the MCCP module based on object detection task. Experimental results demonstrate that the proposed MCCP outperforms the baselines in image classification, and CapDetNet achieves the 2.3% performance gain in object detection. |
10,760 | Please write an abstract with title: Design of a Multistage X Band Power Amplifier, and key words: Power measurement, Power demand, Transmitters, Power amplifiers, HEMTs, Length measurement, Market research. Abstract: This paper aims to design a multistage X band Power Amplifier design using a GaN HEMT active device from CREE-CGHV1J006D. The given amplifier is designed for a frequency 11.7 GHz. The output power of the three stage power amplifier was 4.8 W with Power Added Efficiency (PAE) close to 35%. This design is intended for space applications where a power amplifier module in the transmitter is the most power consuming device and, hence, should be able to minimize the power consumption with a better efficiency possible. |
10,761 | Please write an abstract with title: Spatial non-cooperative object detection based on deep learning, and key words: Deep learning, Automation, Object detection, Detectors, Spatial databases. Abstract: Vision-based spatial non-cooperative object detection is an significant technical support for intelligent on-orbit services, however, the development of related research in this field is relatively slow. Therefore, A tiny spatial non-cooperative object detection (SNCOD) dataset has been constructed, which is the basis of further study. At the same time, we introduce several state-of-the-art deep learning based detection models to explore their generalization ability in the field of aerospace. The experiment results illustrate that all the detectors adopted in this paper can perform well on our SNCOD dataset, even achieve 0.977 mAP. In addition, we explore the challenges for SNCOD, which would significantly enlighten future research. |
10,762 | Please write an abstract with title: A Dual-Attention-Based Neural Network for See-Through Driving Decision, and key words: Knowledge engineering, Vehicular and wireless technologies, Neural networks, Decision making, Feature extraction, Cognition, Hazards. Abstract: The existing end-to-end methods make driving decisions mainly based on the vehicle's own perceived data, which cannot avoid hazards in blind zones. To fill this gap, vehicles should cooperate to construct a comprehensive environment perception by sharing information among each other, equipping each vehicle with see-through ability. While bringing more perceived information, data from other sources may also interfere feature selection and make decision making more difcult. To solve this problem, we propose a dual-attention-based neural network by utilizing two different attention modules. The first module is designed for each source to eliminate redundant features in perception and generate cognitive information for sharing. Since the influences of different cognition on the decision making are different under different circumstances, the second module is used to discriminate the importance of different cognition and focus on the dominant one as needed. Guided by the dual-attention-weighted features, the proposed network extracts the most salient features from the multi-source data, which leads to a signicant reduction of false response in steering angle controlling. Extensive experiments have demonstrated the superior performance of our proposed method, as compared with several state-of-the-arts. |
10,763 | Please write an abstract with title: Tremor Waveform Extraction and Automatic Location With Neural Network Interpretation, and key words: Spectrogram, Earthquakes, Convolutional neural networks, Training, Standards, Licenses, Feature extraction. Abstract: Active faults release tectonic stress imposed by plate motion through a spectrum of slip modes, from slow, aseismic slip, to dynamic, seismic events. Slow earthquakes are often associated with tectonic tremor, nonimpulsive signals that can easily be buried in seismic noise and go undetected. We present a new methodology aimed at improving the detection and location of tremors hidden within seismic noise. After identifying tremors with a classic convolutional neural network (CNN), we rely on neural network attribution to extract core tremor signatures. We observe that the signals resulting from the neural network attribution analysis correspond to a waveform traveling in the Earth’s crust and mantle at wavespeeds consistent with seismological estimates. We then use these waveforms signatures to locate the source of tremors with standard array-based techniques. We apply this method to the Cascadia subduction zone, where we identify tremor patches consistent with existing catalogs. This approach allows us to extract small signals hidden within the noise, and to locate more tremors than in existing catalogs. |
10,764 | Please write an abstract with title: Low-power CMOS VCO and its divide-by-2 dividers with quadrature outputs for 5 GHz/2.5 GHz WLAN transceivers, and key words: Voltage-controlled oscillators, Wireless LAN, Transceivers, Dual band, Inductors, Diodes, Circuit optimization, Injection-locked oscillators, Spirals, Frequency conversion. Abstract: A low power CMOS VCO and its divide-by-2 dividers with quadrature outputs for 5 GHz/2.5 GHz dual band WLAN transceivers are proposed. The VCO is a differential LC oscillator based on an on-chip symmetrical spiral inductor and differential diode. Divide-by-2 dividers with quadrature outputs are implemented by using ILFD (injection-locked frequency divider) techniques. The ILFD structure is similar to that of the VCO to keep its tracking range wide enough. Inductors are optimized by using ASITIC, and differential diodes are designed by careful layout. Due to differential LC tanks and ILFD techniques, power consumption is low. The circuit is implemented in a 0.18 /spl mu/m CMOS process. HSPICE and SpectreRF simulations show that the proposed circuit could produce 5 GHz/2.5 GHz dual band LO signals with a wide tuning range with low phase noise. 2.5 GHz LO signals are quadrature with almost no phase error and no amplitude mismatching. It consumes less than 5.3 mW in the tuning range at VDD=1.5 V. The area is only 1.0/spl times/1.0 mm/sup 2/. |
10,765 | Please write an abstract with title: On finding feasible solutions for the delay constrained group multicast routing problem, and key words: Delay, Routing. Abstract: Group multicasting is a generalization of multicasting whereby every member of a group is allowed to multicast messages to other members that belong to the same group. In this paper, we study the problem of finding feasible solutions for the delay constrained group multicast routing problem (DCGMRP). The routing problem in this case involves the construction of a set of delay bounded multicast trees with bandwidth requirements, one for each member of the group, for multicasting messages to other members of the group. We first show that the problem is NP-complete. Next, we propose a heuristic algorithm to find feasible solutions for this problem. Simulation results show that our proposed algorithm is able to achieve a high probability of finding feasible solutions for DCGMRP, whenever one exists. |
10,766 | Please write an abstract with title: Optimization for Parameter of PID Based on DNA Genetic Algorithm, and key words: Genetic algorithms, Control systems, Three-term control, Stability, DNA computing, Optimization methods, Encoding, Biological information theory, Algorithm design and analysis, Optimal control. Abstract: PID control schemes have been widely used in most of control system for a long time. However, it is still a very important problem how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. On the other hand, in the last ten years, DNA computing is attracted as one method which gives us suitable answers for optimization problems. A new DNA encoding method based genetic algorithm is proposed based on the structure and the genetic mechanism of biological DNA. The structure of DNA genetic algorithm is provided, it is applied into the optimal design of PID controller system. The simulation results show excellent self learning capability of DNA genetic algorithm. |
10,767 | Please write an abstract with title: A Hybrid Control Strategy Based on Lagging Reactive Power Compensation for Vienna-Type Rectifier, and key words: Switches, Reactive power, Distortion, Modulation, Transportation, Hybrid power systems, Voltage control. Abstract: The Vienna-type rectifier is widely used in many applications due to the merits of controllable dc-link voltage, realizable three-level operation, and compact size. However, the input currents near the zero-crossing point are distorted inevitably due to its special topology. Based on the analysis of the causes of current distortion, a lagging reactive power compensation method is proposed. The d-q-axis current models are developed, and two finite-time current controllers are designed to enhance the interference suppression performance. The asymptotic convergence of the d-q-axis current systems is proved, respectively. In addition, neutral point potential balancing is achieved by employing a proportional controller without increasing the cost of the system. The validity of the proposed hybrid control strategy has been verified by simulation and experimental results. Compared with the conventional strategy, this new hybrid control strategy can help to achieve excellent performance and stronger disturbance rejection. |
10,768 | Please write an abstract with title: Multiple quantum wells for mode-locking, and key words: Laser mode locking, Quantum well lasers, Quantum well devices, Semiconductor lasers, Pump lasers, Gallium arsenide, Laser excitation, Laser feedback, Mirrors, Semiconductor diodes. Abstract: Mode-locking at wavelengths ranging from 750 nm to 1100 nm is achieved with proper adjustment of multiple-quantum-well composition. In flashlamp Nd:YAG laser with multiple-quantum-wells 25 ps pulses are reported. |
10,769 | Please write an abstract with title: Study on the Influence of Load Imbalance on Current Carrying Capacity of Power Transmission Equipment in Distribution Network, and key words: Oil insulation, Temperature, Power transformer insulation, Oils, Windings. Abstract: Distribution network undertakes the important task of safe and stable transmission of electric energy to users. Among them, distribution transformer is the indispensable main equipment. However, with the vigorous development of industry and commerce, a large number of non-uniform random loads are connected to the power grid, thus bringing the three-phase unbalance in distribution network. The increase of additional loss and hot spot temperature of transformer are caused by three-phase unbalance. High winding hot spot temperature can accelerate the thermal aging speed of insulating materials and reduce insulation performance, thereby reduce transformer output and load capacity. In this paper, the influence of three-phase unbalance on load carrying capacity of distribution transformer is studied. The relationship between relative load factor and hot spot temperature is established under normal periodic load, long term emergency load and short term emergency load. The results show that three-phase unbalance has a great direct impact on transformer load capacity. |
10,770 | Please write an abstract with title: Development of high-temperature superconducting transformers for railway applications, and key words: High temperature superconductors, Rail transportation, Testing, Phase transformers, Transformer cores, Impedance, Conductors, Cooling, Nitrogen, Thermal loading. Abstract: We describe the high-temperature superconducting (HTS) transformer project run by Siemens. The project started in October 1996 and ended in September 2001. The aim of the project was to show the future prospects for superconducting railway transformers. To study the principle behavior of such a transformer, as a first step we designed, constructed and tested a nominal single-phase transformer of 100 kVA, 50 Hz, 5.5 kV/1.1 kV. After this was successfully tested, we started the design and construction of a single-phase transformer of 1 MVA, 50 Hz, 25 kV/1.4 kV. This unit already has the full ratings of a commercial transformer in many respects, e.g., power range, nominal voltage, 2-limb core with horizontal orientation, two secondary windings and an impedance of 25% at nominal current. Further innovative features are transposed conductor and a closed cooling cycle with sub-cooled nitrogen. The report describes the 1-MVA transformer's detailed design, and presents the results of electrical and thermal transformer routine tests (e.g., measurement of load losses and no-load losses). The conclusion highlights the future perspective of HTS transformers for railway applications. |
10,771 | Please write an abstract with title: A graph-spectral approach to surface segmentation, and key words: Surface topography, Gaussian processes, Image segmentation, Computer science, Pixel, Computer vision, Surface fitting, Size control, Q measurement, Face detection. Abstract: In this paper we describe a graph-spectral method for 3D surface segmentation from 2D imagery. The method locates patches by finding groups of pixels that can be connected using a curvature minimising path. The path is the steady state Markov chain on transition probability matrix. We provide two methods for computing this matrix. The first uses the information provided by the field of surface normals extracted from the 2D intensity image using shape-from-shading. Here we compute the elements of the transition matrix using the change in surface normal directions to estimate the normal curvature. The second approach uses the raw image brightness together with a Lambertian reflectance model to make estimates of curvature. We compare the surface segmentations delivered by these two methods with those obtained using shape-index maximal patches. |
10,772 | Please write an abstract with title: Vision-guided Collision Avoidance Through Deep Reinforcement Learning, and key words: Conferences, Reinforcement learning, Robustness, Indoor environment, Collision avoidance, Task analysis, Drones. Abstract: Collision avoidance is a crucial task in vision-guided autonomous navigation. Traditional solutions tend to be computationally expensive and difficult to adapt to new environments. In this work, we propose a novel collision avoidance solution for autonomous drones. Formulated under a deep reinforcement learning framework, our model relies on a pair of margin reward functions to ensure the drones fly smoothly while greatly reducing the chance of collision. Additional reward functions are designed to attract the drones to fly towards their destinations, as well as to follow predefined routes. Experiments using indoor simulation environments demonstrate the effectiveness of our overall design and the individual components. |
10,773 | Please write an abstract with title: A Machine Learning Model for Detecting Respiratory Problems using Voice Recognition, and key words: Diseases, Machine learning, Speech recognition, Training, Testing, Emotion recognition. Abstract: The paper provides an overview of the development and intelligent voice data analysis from a machine learning perspective; a historical, state-of-the-art view and a view on some future trends in the field of artificial intelligence. The paper describes some areas within voice recognition domain which seem to be important for applying machine learning in medical diagnosis.This describes a recently developed method of detecting respiratory problems quickly by recognizing the changes in voice over time. Machine learning algorithms are applied here. |
10,774 | Please write an abstract with title: Development of an Extended Reality Simulator for Basic Life Support Training, and key words: Training, Virtual reality, Tracking, Headphones, X reality, Extended reality, Defibrillation. Abstract: Objective: Extended Reality (XR) is a simultaneous combination of the virtual and real world. This paper presents the details of the framework and development methods for an XR basic life support (XR-BLS) simulator, as well as the results of an expert usability survey. Methods: The XR-BLS simulator was created by employing a half-torso manikin in a virtual reality environment and using BLS education data that is in line with the 2020 American Heart Association guidelines. A head-mounted display (HMD) and hand-tracking device were used to perform chest compressions and ventilation and to enable the use of an automated external defibrillator in a virtual environment. A usability study of the XR-BLS simulator through an expert survey was also conducted. The survey consisted of a total of 8 items: 3, 2, and 2 questions about the ease of use of XR-BLS, delivery of training, and artificial intelligence (AI) instructor in the simulator, respectively. Results: The XR simulator was developed, and the expert survey showed that it was easy to use, the BLS training was well delivered, and the interaction with the AI instructor was clear and understandable. Discussion/Conclusion: The XR-BLS simulator is useful as it can conduct BLS education without requiring instructors and trainees to gather. |
10,775 | Please write an abstract with title: Energy Management of the Power-Split Hybrid Electric City Bus Based on the Stochastic Model Predictive Control, and key words: Ice, Energy management, Torque, Batteries, State of charge, Neural networks. Abstract: The energy management strategy of hybrid electric vehicles is of significant importance to improve the fuel economy. In this regard, two energy management strategies are designed for power-split hybrid electric city bus (HECB), which are based on the linear time-varying stochastic model predictive control (LTV-SMPC) and stochastic model predictive control based on Pontriagin’s minimum principle (PMP-SMPC). In the present study, the Markov chain and long short-term memory (LSTM) forecast demand torque and velocity respectively are applied to establish a combination forecast model. Then several processes, including linear approximation, processing simplified control model, the proposed nonlinear vehicle model is converted into a linear time-varying model. Meanwhile, the energy management problem in a linear quadratic programming problem is solved. Considering linearization error and limitations of the quadratic optimization, Pontriagin’s minimum principle (PMP) is applied to optimize the nonlinear model predictive control. Based on the reference theory, the range of coordinated variables is derived, and the optimal coordination variable is searched by dichotomy to realize the rolling optimization of the model predictive control (MPC). Finally, the effectiveness of the proposed energy management strategy is verified by simulating several case studies. Obtained results show that compared with the rule-based (RB) control strategy, the fuel economy of LTV-SMPC and PMP-SMPC increases by 8.79% and 14.42%, respectively. Meanwhile, it is concluded that the two strategies have real-time computing potential. |
10,776 | Please write an abstract with title: Double Wound Inductor Design Optimization for the Flying Capacitor Multilevel Flyback Converter using a Modified, T-Model Magnetic Equivalent Circuit, and key words: Geometry, Multilevel converters, Buck converters, Capacitors, Transformer cores, Tools, Magnetic analysis. Abstract: The flying capacitor multilevel flyback converter (FCMFC) utilizes a flyback transformer in conjunction with multiple switch-diode-capacitor (SDC) stages to improve operation of the basic flyback converter for DC-DC power conversion. This work explores the multi-objective optimization of the double-wound inductor of the 200W FCMFC. The core geometry will be optimized for various multilevel converters to yield the most efficient and lightweight inductor. The optimized inductor design exhibited 0.73W loss and corresponded to a basic flyback two level converter while the lightest design of 35g corresponded to a five level FCMFC. While the flyback inductor was most efficient, it was also the heaviest with an anticipated mass of 186.25g, compared to the 35g inductor that only exhibits a loss of 1.11W. All multilevel converters follow the Pareto optimal front making SDC stages a useful design variable for the magnetic optimization of a flyback converter. |
10,777 | Please write an abstract with title: Intrusion Location Technology of Sagnac Distributed Fiber Optical Sensing System Based on Deep Learning, and key words: Optical fiber sensors, Sensors, Sagnac interferometers, Optical interferometry, Optical fiber cables, Optical scattering, Optical fiber networks. Abstract: For distributed fiber optical sensing based on Sagnac effect, the intrusion is usually located by notch frequency. However, the notch spectrum is the comprehensive result of the intrusion, so when multiple disturbances simultaneously intrude from different positions of the sensing fiber, it is impossible to establish a mathematical expression between the intrusion position and the notch frequency, this leads to the problem of multi-point intrusion localization. Therefore, in this paper, deep learning technology is used to locate multiple disturbing points in Sagnac distributed optical fiber sensing system, and the related specific technologies of deep learning applying to Sagnac distributed optical fiber sensing are studied. First, according to the characteristics of the system, a network structure based on the regression probability distribution is proposed, second, a loss function is constructed. The results show that the trained model can realize the positioning of multiple and single intrusion points. |
10,778 | Please write an abstract with title: Enabling the Digital Transformation of the Workforce: A Digital Engineering Competency Framework, and key words: Training, Industries, Knowledge engineering, Analytical models, Digital transformation, Benchmark testing, Tools. Abstract: This paper describes the goals, approaches, initial results, and preliminary implementation of WRT-1006, a multiphase research task within the Systems Engineering Research Center (SERC). Evidence across the Services and industry has affirmed digital engineering is a critical practice necessary to support acquisition in an environment of increasing global challenges, dynamic threats, rapidly evolving technologies, and increasing life expectancy of our systems currently in operation. Digital engineering updates the systems engineering practices to take full advantage of computational technology, modeling, data analytics, and data sciences. The Department of Defense's vision for digital engineering is to modernize how the Department designs, develops, delivers, operates, and sustains systems, while continuing to practice systems engineering efficiently and effectively. Digital transformation is fundamentally changing the way acquisition and engineering are performed across a wide range of government agencies, industries, and academia. As the Department of Defense (DoD) transitions to digital engineering, there is a need to develop and maintain an acquisition workforce and culture that is literate in model-based engineering, competent in digital engineering models, methods, processes, tools, and understands digital artifacts across the acquisition lifecycle. One of the critical steps that was identified to enable this digital transformation is the development of a competency model that can be used to modernize the workforce. This paper outlines the results after completion of Phase 1 of WRT-1006, which concluded in the initial release of the Digital Engineering Competency Framework (DECF) by SERC, and the initial Phase 2 efforts of implementing the framework as a benchmark for the content of a digital engineering training curriculum. The purpose of the DECF is to provide clear guidance for the DoD acquisition workforce, in particular the engineering acquisition workforce, through clearly defined competencies that illuminate the knowledge, skills, abilities, and behaviors required for digital engineering professionals. The approach taken to develop the DECF drew from existing competency models in fields neighboring digital engineering and from the feedback of experienced practicing digital engineering community. The initial version of the DECF v.1.0 was released as a key WRT1006 Phase 1 result with confidence in the maturity of the structure and general content. The overarching structure of the DECF v.1.0 consists of competency areas, proficiency levels within the competency, and constituting knowledge, skills, abilities, and behaviors (KSABs). Now that this benchmark is established, the second phase of our project involves the comparison of the DECF to the existing Defense Acquisition University (DAU) curriculum to determine what elements of such existing curriculum already support the competencies in the model. This is a bidirectional analysis that will both identify gaps in the training curriculum and potentially identify curriculum content that should be incorporated into the competency model. Although this project is specifically applying the DECF to the acquisition process, the model has applications in any area that will implement Digital Engineering initiatives. Furthermore, this framework has additional use cases that will be explored further including hiring for Digital Engineering positions and ensuring the current work force has the necessary skillsets to adequately implement a digital transformation. |
10,779 | Please write an abstract with title: A High-Efficiency Self-Synchronous RF-DC Rectifier With a Fixed Broadband Phase Offset, and key words: Logic gates, Wireless communication, Transistors, Radio frequency, Integrated circuit modeling, Microwave transistors, Gallium nitride. Abstract: This letter presents a broadband self-driving radio frequency-to-direct current (RF-dc) rectifier design realized on the CG2H40010F Cree's GaN device. First, the transistor modeling parameters for the reverse-biased I-V characteristics have been obtained to achieve the high-frequency rectification at negative drain biasing. Besides, an enhanced self-synchronization is achieved across the operating bandwidth through an additional microstrip open-stub line at the gate input matching network. Thus, an additional line maintains a fixed 180° phase offset between drain and gate voltages. Finally, the rectifier efficiency of >60% has been measured from 2.65 to 2.95 GHz for 10-W RF input power. The designed rectifier has been outperformed the recent designs in terms of operational bandwidth (300 MHz) and rectification efficiency. |
10,780 | Please write an abstract with title: Influence of crystalline structure on micromagnetic domain formation, and key words: Crystallization, Micromagnetics, Magnetic separation, Filters, Iron, Wires, Thick films, Couplings, Magnetic domain walls, Magnetic force microscopy. Abstract: Summary form only given. The role of crystalline structure in domain wall formation is investigated. Permalloy polycrystal, Fe bcc crystal and Co fcc crystal wire junction structures were observed in both demagnetised and remanent states using magnetic force microscopy (MFM). The differences in the domain configurations are presented. |
10,781 | Please write an abstract with title: Merging Position and Force Control into a Single Control Structure: One Step towards Smart Actuating System, and key words: Trajectory tracking, Force, Switches, Aerospace electronics, Control systems, Mechanical systems, Force control. Abstract: The paper discusses a control strategy that merges position and force control into a single control structure. The structure, denoted as the universal motion controller in our previous work, can be utilized to build a smart actuating system that runs a mechanical system with n degrees of freedom. A smart actuating system has an integrated controller and it can be used in plug-and-play fashion for different trajectory tracking and force control tasks, defined either in configuration space, or in the task space. The only input of the actuating system is the attraction force in configuration space. Based on the attraction force, the smart actuating system is capable of imposing input forces to the mechanical system that will ensure execution of a specified task. |
10,782 | Please write an abstract with title: Optimal Reactive Power Dispatch With Discrete Controllers Using a Branch-and-Bound Algorithm: A Semidefinite Relaxation Approach, and key words: Reactive power, Relaxation methods, Power generation dispatch, Steady-state, Matrix decomposition, Linear matrix inequalities. Abstract: In this paper, a methodology to solve the optimal reactive power dispatch (ORPD) in electric power systems (EPS), considering discrete controllers, is proposed. Discrete controllers, such as the tap position of on-load tap changing (OLTC) transformers and switchable reactive shunt compensation, are optimized by the proposed method. A semidefinite relaxation (SDR) of the ORPD problem and a branch-and-bound (B&B) algorithm have been fully deployed. A new formulation is presented for the OLTC transformers to obtain a connected structure of the semidefinite programming (SDP) matrices. The customized B&B algorithm deals with the discrete nature of the binary control variables. Moreover, in order to enhance the convexification, valid inequalities called lifted nonlinear cuts (NLC) are implemented in the SDR. Additionally, a chordal decomposition technique is used to improve the computational performance. Finally, the B&B algorithm is used to solve the mixed-integer semidefinite programming problem. Several benchmarks have been used to show the accuracy and scalability of the proposed method, and convergence analysis shows that near-global optimal solutions are generated with small relaxation gaps. |
10,783 | Please write an abstract with title: High-speed Wavelength-dependent Speckle Generator Applied to Compressive Video Sensing, and key words: Image coding, Speckle, Lasers and electrooptics, Generators, Sensors, Electrooptical waveguides. Abstract: A high-speed wavelength-dependent speckle generator with the refreshing rate up to 100MHz is proposed. This can be used for compressive video sensing for recovering high-speed moving scenes from one blurred image. |
10,784 | Please write an abstract with title: LUCAS - an expert system for intelligent fault management and alarm correlation, and key words: Expert systems, Intelligent systems, Communication system control, Modems, Communication networks, Floods, Storms, Filtering, Decision making, Intelligent networks. Abstract: The amount of control data flowing across modem communication networks is rapidly increasing. Huge streams of data are flooding the operation and maintenance center (OMC). Thus the operator needs a management system that converts these massive data storms to manageable magnitudes. To achieve this an intelligent alarm filtering system is required to interpret the data stream, thereby simplifying the decision-making process and shortening the operator's reaction time. Such an intelligent tool is the first step on the way to achieving knowledge-based network management. An event correlation tool, called Lucent Correlated Alarm Simulator (LUCAS) has been designed as a prototype for GSM networks. This paper gives an insight into the conception of the tool's architecture and in particular describes the algorithm used for the correlation engine. |
10,785 | Please write an abstract with title: EEG Signal Analysis for Emotional Classification, and key words: Electrodes, Recurrent neural networks, Time series analysis, Scalp, Speech recognition, Electroencephalography, Classification algorithms. Abstract: Electroencephalography (EEG) uses electrodes to assess neuronal activity in various brain areas. Emotion is a state that encompasses human feelings, thoughts, and behavior, and it may be found in all aspects of daily life. The proposed study reviews the deep learning techniques for automatically extracting the spatial elements, which explain the functional link between EEG data at distinct electrodes. The proposed work of this study is to examine single and ensemble approaches for classifying emotional events using EEG inspiration information. The dataset which is generated through business product known as MUSE EEG headband with 4 electrode resolution, support on some states of mind recognized via cognitive behavioral learning, grouped into three feasible states which include effective, neutral, and poor. High-quality and terrible emotional states are invoked the use of video clips with evident valence, in addition to neutral resting information and not using a stimulation, eager about one minute in keeping with consultation. Five indicators have been recovered from EEG headbands using the desired set of traits. Of the set of 2548 capabilities, a subset of 63 capabilities, selected based on their statistics benefit values, have been shown to be the handiest whilst utilized with ensemble classifiers along with Gated Recurrent gadgets and long brief-time period reminiscence in Recurrent Neural Networks. As it uses sequential RNN’s are significantly used in natural language and speech recognition packages to method time series facts. A basic accuracy of approximately ninety seven.18% of checking out accuracy for GRU and 95.13% accuracy for LSTM has been received. |
10,786 | Please write an abstract with title: Fully Distributed Control of Linear Systems With Optimal Cost on Directed Topologies, and key words: Protocols, Topology, Optimization, Optimal control, Laplace equations, Asymptotic stability, Riccati equations. Abstract: This brief investigates the fully distributed optimal control of linear multi-agent systems on generally directed topologies. Considering the existence of disturbances, a dynamical sliding-mode control protocol is designed. The optimization of energy-cost performance is achieved by solving a topology-free algebraic Riccati equation. The presented control protocol is independent with the global information of topologies, and each agent can manage its protocol in a fully distributed way. A numerical example is finally reported to show the efficiency of presented protocol. |
10,787 | Please write an abstract with title: Co-Designing an OpenMP GPU Runtime and Optimizations for Near-Zero Overhead Execution, and key words: Distributed processing, Runtime, Codes, Runtime library, Semantics, Graphics processing units, Prototypes. Abstract: GPU accelerators are ubiquitous in modern HPC systems. To program them, users have the choice between vendor-specific, native programming models, such as CUDA, which provide simple parallelism semantics with minimal runtime support, or portable alternatives, such as OpenMP, which offer rich parallel semantics and feature an extensive runtime library to support execution. While the operations of such a runtime can easily limit performance and drain resources, it was to some degree regarded an unavoidable overhead. In this work we present a co-design methodology for optimizing applications using a specifically crafted OpenMP GPU runtime such that most use cases induce near-zero overhead. Specifically, our approach exposes runtime semantics and state to the compiler such that optimization effectively eliminating abstractions and runtime state from the final binary. With the help of user provided assumptions we can further optimize common patterns that otherwise increase resource consumption. We evaluated our prototype build on top of the LLVM/OpenMP GPU offloading infrastructure with multiple HPC proxy applications and benchmarks. Comparison of CUDA, the original OpenMP runtime, and our co-designed alternative show that, by our approach, performance is significantly improved and resource consumption is significantly lowered. Oftentimes we can closely match the CUDA implementation without sacrificing the versatility and portability of OpenMP. |
10,788 | Please write an abstract with title: An environment for collaborative iteration planning, and key words: Collaboration, Meeting planning, Process planning, Collaborative work, Technology planning, Collaborative software, Computer science, Councils, Project management, Monitoring. Abstract: Existing project planning software for agile development processes offers limited support for face-to-face, synchronous collaboration. In this paper, we describe an environment, AgilePlanner, that supports team collaboration during planning meetings. Our approach utilizes advanced technologies of pen computing and digital tabletops to create a collaborative work environment to emulate project planning using index cards. It combines the benefits of paper index cards with those of traditional desktop planning solutions. AgilePlanner is intended as an integral resource in the planning process. |
10,789 | Please write an abstract with title: Personal health data identity authentication matching scheme based on blockchain, and key words: Smart cards, Data privacy, Biometrics (access control), Biological system modeling, Data security, Smart contracts, Authentication. Abstract: Although medical informatization is gradually improving, the security and privacy of personal health data are still vulnerable to threats under the traditional electronic data storage mode. At the same time, when an individual goes to a medical institution to see a doctor, the individual is not present, and the personal health data does not match the individual’s identity, resulting in a medical accident. In severe cases, it may even threaten the safety of the individual’s life. In addition, patients can not extract the existing personal health data in real time when the smart card is lost. In response to the above problems, a blockchain-based personal health data identity authentication matching scheme is proposed, which has the characteristics of data immutability and decentralization. Using fuzzy extraction technology to extract personal biometrics to generate random keys can effectively solve the problem of biometrics being unusable after the biometrics are leaked. Through smart contracts, the random key can be authenticated to achieve identity matching. The security performance analysis of the model shows that the proposed solution has security attributes such as anti-man-in-the-middle attack and anti-replay attack, and can realize anti-tampering of personal health data, and effectively protect privacy; under the premise of ensuring data security, through intelligent the contract performs access control, and personal health data can be accurately authenticated and matched with personal identity. |
10,790 | Please write an abstract with title: Performance Analysis of Grid Integrated PV Based Distributed Generation with Maximum Power Point Tracking, and key words: Maximum power point trackers, Support vector machines, Photovoltaic systems, Analytical models, Renewable energy sources, Reactive power, Simulation. Abstract: Distributed generation (DG) has received more recognition due to the limitations of conventional power generation. The grid-connected inverter of DG is usually connected with renewable energy sources (RES)s. Here, a photovoltaic (PV) array is used as a DG source with maximum power point tracking implemented by the P&O algorithm. The role of DG is to supply adequate power to support the grid, which is effectively controlled using the Comprehensive Power Quality Evaluation (CPQE) technique. Here, MATLAB-based simulation of proposed PV-based DG with maximum power extraction algorithm is presented. Simulation analysis of proposed PV-based two-level inverter DG clearly depicts satisfactory behavior. |
10,791 | Please write an abstract with title: Personalization of Information using Graph Convolutional Network, and key words: Automation, Fitting, Web pages, Search engines, Network architecture, Prediction algorithms, Telecommunication computing. Abstract: There exists several researches that have been done on link-based search engines for instance, Clever and Google. They involve the use of link structure to getprecise results. Generally, search engines based on link structure give users high-quality results than search engines which are text based. However, those search engines encounter difficulty producing the result fitting to a specific user’s profile. Personalization means knowing the user intimately enough to not only meet their needs but also predict them. This paper presents an analogy to a personalized search engine using an already existing GCN (Graph Convolutional Network) architecture on (Cora) the paper citation dataset (similar to web pages) and additionally followed by KNN algorithm to rank the personalized citations in best consonance with a user’s profile. |
10,792 | Please write an abstract with title: Electric Field Induced Second Harmonic Generation In Silicon Waveguides: the role of the disorder, and key words: Geometry, PIN photodiodes, Waveguide junctions, Europe, Frequency conversion, Silicon, Electric fields. Abstract: One way to achieve a second-order susceptibility χ (2) in Si is by exploiting a third-order nonlinear effect, the Electric Field Induced Second Harmonic Generation (EFISHG) [1] . This phenomenon, through the use of a constant electric field ( E DC ) within the waveguide generated by lateral p-i-n junctions, gives rise to a χ (2) proportional to the electric field, $\chi _{{\text{EFISH}}}^{(2)} = 3{\chi ^{(3)}}{E_{{\text{DC}}}}$ . In [2] , [3] we have shown that using an interdigitated poling structure to satisfy the quasi phase matching condition required for SHG results in an increase in the generation efficiency ( η ) compared to a simple configuration, see Fig. 1 . The presence of disorder in the waveguide and poling geometry was also shown to cause a widening of the η spectrum. |
10,793 | Please write an abstract with title: Compressed Data Collection Method for Wireless Sensor Networks Based on Optimized Dictionary Updating Learning, and key words: Sensors, Data collection, Wireless sensor networks, Dictionaries, Energy consumption, Data models, Mathematical model. Abstract: Wireless sensor networks (WSNs) is composed of a large number of tiny sensors. These energy-constrained sensors are deployed in a variety of environments to collect data such as temperature, humidity, and light intensity. Therefore, how to suppress the impact of environmental noise on the collection accuracy and extend the lifetime of WSNs is one of the prominent issues. This article proposes an optimized dictionary updating learning-based compressed data collection algorithm (ODUL-CDC) to suppress the impact of environmental noise on the accuracy of WSNs data collection and extend the life cycle of WSNs. The proposed algorithm uses the dictionary learning method to obtain a sparse dictionary by learning from the training data. The collection error caused by environmental noise is positively correlated with the degree of self-coherence of the sparse dictionary. Therefore, the self-coherence penalty term is introduced during the dictionary updating process, which can reduce the over-fitting of the training data in the dictionary learning process. Moreover, the self-coherence penalty term endows the learned sparse dictionary with a low-self-coherence structure. Experimental and simulation results show that, as compared with discrete cosine transform(DCT), K-SVD and IDL learning-based data collection methods, the proposed algorithm exhibits the highest increase in recovery accuracy of 3.2% in the signal-to-noise ratio (SNR) range of 30-50 dB, the sampling ratio range of 25%-40% and the sparsity range from 3 to 30. Furthermore, the energy consumption is significantly less than that of the compared methods, which helps improve the network lifetime. |
10,794 | Please write an abstract with title: Mesh Simplification With Appearance-Driven Optimizations, and key words: Image edge detection, Solid modeling, Three-dimensional displays, Computational modeling, Measurement, Surface texture, Optimization. Abstract: In this work, we propose a novel solution for simplifying texture-mapped three-dimensional (3D) meshes. It simplifies a 3D triangular mesh to optimally preserve the visual appearance of the original texture-mapped model at reduced vertex budgets. While taking the prevalent strategy of iterative edge contraction, the proposed scheme is novel in that it takes into account the local texture image characteristics when prioritizing local mesh simplification operators, and conducts closed-form optimization when computing the texture coordinates of each replacement vertex. Outstanding performance of the proposed scheme is demonstrated both qualitatively and quantitatively by experimental results. Further, validity of the proposed algorithmic components is well proved through ablation study. |
10,795 | Please write an abstract with title: Improved antlion Optimizer algorithm base on Dynamic random hill-climbing mechanism, and key words: Heuristic algorithms, Benchmark testing, Search problems, Robustness, Information technology, Optimization, Numerical stability. Abstract: In this paper, a dynamic random hill-climbing mechanism is proposed to solve the problems that the ant lion optimization algorithm is easy to fall into the local optimal. The algorithm adjusts the position of ant lion by hill-climbing mechanism to enhance the ability to jump out of local optimal. In addition, the global search ability of the algorithm is improved by dynamically hill-climbing mechanism by balancing exploration and development ability. The performance of the proposed algorithm is evaluated on 7 benchmark function and compared with original ALO and an improved ant lion optimization algorithm. The experimental results prove that the proposed algorithm can effectively improve the performance of the algorithm. |
10,796 | Please write an abstract with title: Optimizing the Snake Model Using Honey-Bee Mating Algorithm for Road Extraction from Very High-Resolution Satellite Images, and key words: Support vector machines, Satellites, Roads, Image edge detection, Estimation, Feature extraction, Numerical models. Abstract: Many geospatial applications rely on the extraction of spatial features, including road networks, from very high-resolution (VHR) satellite images. Researchers have developed many algorithms to achieve this goal, the majority of which are based on image fusion, fuzzy logic, and active contour models. The snake model is among the most widely used methods for road extraction by active contours. In most studies, an initial curve close to available roads is manually defined or based on prior knowledge. These methods also require manual adjustment of the snake model parameters, which is time-consuming. In order to address these limitations, this study proposes an algorithm for extracting roads from VHR satellite images in a semi-urban area that optimizes snake models by Honey-Bee Mating Optimization (HBMO). Based on a support vector machine and some image processing analysis, the presented method can extract an accurate initial curve, as well. According to the results of the experiments, the proposed approach not only eliminates the shortcomings of the snake model but also increases the accuracy of road extraction by 10% in all three study areas compared to the traditional snake method. |
10,797 | Please write an abstract with title: Video-based sign recognition using self-organizing subunits, and key words: Handicapped aids, Hidden Markov models, Vocabulary, Natural languages, Speech recognition, Computer science, Computer errors, Mouth, Cameras, Layout. Abstract: This paper deals with the automatic recognition of German signs. The statistical approach is based on the Bayes decision rule for minimum error rate. Following speech recognition system designs, which are in general based on phonemes, here the idea of an automatic sign language recognition system using subunits rather than models for whole signs is outlined. The advantage of such a system will be a future reduction of necessary training material. Furthermore, a simplified enlargement of the existing vocabulary is expected, as new signs can be added to the vocabulary database without re-training the existing hidden Markov models (HMMs) for subunits. Since it is difficult to define subunits for sign language, this approach employs totally self-organized subunits. In first experiences a recognition accuracy of 92,5% was achieved for 100 signs, which were previously trained. For 50 new signs an accuracy of 81% was achieved without retraining of subunit-HMMs. |
10,798 | Please write an abstract with title: Federated Learning with Heterogeneous Quantization, and key words: Quantization (signal), Upper bound, Computational modeling, Aggregates, Collaborative work, Servers, Convergence. Abstract: Quantization of local model updates before uploading to the parameter server is a primary solution to reduce the communication overhead in federated learning. However, prior literature always assumes homogeneous quantization for all clients, while in reality devices are heterogeneous and they support different levels of quantization precision. This heterogeneity of quantization poses a new challenge: fine-quantized model updates are more accurate than coarse-quantized ones, and how to optimally aggregate them at the server is an unsolved problem. In this paper, we propose FEDHQ: Federated Learning with Heterogeneous Quantization. In particular, FEDHQ allocates different weights to clients by minimizing the convergence rate upper bound, which is a function of quantization errors of all clients. We derive the convergence rate of FEDHQ under strongly convex loss functions. To further accelerate the convergence, the instantaneous quantization error is computed and piggybacked when each client uploads the local model update, and the server dynamically calculates the weight accordingly for the current round. Numerical experiments demonstrate the performance advantages of FEDHQ+ over conventional FEDAVG with standard equal weights and a heuristic scheme which assigns weights linearly proportional to the clients’ quantization precision. |
10,799 | Please write an abstract with title: A Novel Three Dimensional (3D) Winding Structure for Planar Transformers, and key words: Resistance, Three-dimensional displays, Windings, Resonant frequency, Resonant converters, Transformers, Frequency conversion. Abstract: This paper presents a novel 3D planar transformer winding structure. The proposed winding structure achieves low AC resistance without multiple interleaving between primary and secondary windings. The parasitic capacitance between primary and secondary windings are significantly reduced by the proposed structure. The 3D finite element analysis (FEA) has proven effective current sharing between all paralleled traces. The proposed 3D winding structure is applied to a 3.2 kW 500 kHz LLC resonant converter and >98% efficiency is demonstrated. |
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