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Please write an abstract with title: The piezo-resistive effect in silicon for arbitrary crystal orientation [package stress induced integrated resistor/MOSFET drift minimization], and key words: Silicon, Resistors, Electronics packaging, Integrated circuit packaging, Mechanical sensors, Genetic expression, Tensile stress, Anisotropic magnetoresistance, Visualization, MOSFETs. Abstract: The piezo-resistive effect describes the change of resistance due to mechanical stress. Although known for a long time it is not so evident which wafer orientation and which layout minimizes resistance drifts due to stress changes. To this end, a general expression describing the piezo-resistance effect for arbitrary orientation in cubic crystal systems is deduced. Assuming the series connection of two nominally equal resistances with different directions of current flow, we discuss the influence of various components of the stress tensor on the total resistance. For the case of practical relevance with dominant in-plane normal and shear stresses, the two resistances should be oriented perpendicular to each other ("L-layout"). The highly anisotropic behavior is visualized for the first time by use of 3D plots. Practical conclusions are drawn how to minimize drift of electronic parameters caused by package related mechanical stress on integrated resistors and MOS transistors.
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Please write an abstract with title: DANCE: Differentiable Accelerator/Network Co-Exploration, and key words: Measurement, Heart, Backpropagation, Costs, Design automation, Neural networks, Network architecture. Abstract: This work presents DANCE, a differentiable approach towards the co-exploration of hardware accelerator and network architecture design. At the heart of DANCE is a differentiable evaluator network. By modeling the hardware evaluation software with a neural network, the relation between the accelerator design and the hardware metrics becomes differentiable, allowing the search to be performed with backpropagation. Compared to the naive existing approaches, our method performs co-exploration in a significantly shorter time, while achieving superior accuracy and hardware cost metrics.
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399,102 |
Please write an abstract with title: A Ku-Band −200.2-dBc/Hz FoMT Low-Power Low-Phase-Noise LC-VCO IC with a Novel Feedback Circuit Using the Leakage Current, and key words: Integrated circuits, Wireless communication, Phase noise, Power demand, Power measurement, Feedback circuits, Current measurement. Abstract: A Ku-band low-power low-phase-noise LC-VCO IC with a novel feedback circuit is presented in this paper. The novel feedback circuit controls a bias voltage to the VCO core circuit to reduce the dc power consumption and guarantees the robust start-up of the oscillation. The leakage current is utilized to drive the feedback circuit so that the dc power consumption in the feedback circuit is suppressed. The proposed Ku-band LC- VCO IC has exhibited a measured phase noise of −133.9 dBc/Hz, an FoM of −192.0 dBc/Hz, and an FoMT of −200.2 dBc/Hz under the maximum total power consumption of 2.98 mW.
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399,103 |
Please write an abstract with title: An optimal control system with data mining method for saving electricity, and key words: Optimal control, Data mining, Production facilities, Energy consumption, Energy conservation, Control systems, Costs, Prediction algorithms, Predictive models, Predictive control. Abstract: An energy conservation optimal control system using information network is presented in the paper. The special feature of the control system is to control total equipments in a factory for energy conservation at low cost using information networks. The control strategy consists of 2 parts. (1) Data mining algorithm to examine energy consumption for a factory. (2) Optimal control algorithm to control many manipulating values at the same time. The algorithm adopts model predictive control method. The system performance is tested through energy consumption simulations for the factory whose model is proved by the comparison with measured data for 1 month. Finally the system was proved to decrease energy consumption by more than 8% that is our final goal.
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399,104 |
Please write an abstract with title: The Effect of Secondary Reflections on the Quality of Layers Thickness Assessment Using UWB GPR Signals, and key words: Antenna measurements, Dipole antennas, Directive antennas, Reflector antennas, Reflection, Ultra wideband antennas, Testing. Abstract: The paper presents the results of experimental studies on the effect of secondary reflections arising from the registration of ultra-wideband ground-penetrating radar signals when the antenna unit is located in close to the external boundary of the probed medium. In this case, when using the standard calibration procedure to obtain the parameters of the sensing signal and then measuring the signals reflected from the medium under study, it is necessary first of all to investigate the effect of such secondary reflections on the resulting data sets. When formulating and solving such problem, it is necessary to take into account the specific features of real antennas and the shape of the pulse signals radiated and received by them. The main goal of the experiments is to study the influence of the distance between the antennas and the surface of the examined medium and the subsequent optimization of the measurement technique for signals reflected from plane-layered media. An analysis of the obtained experimental results shows the possibility of further improving the quality of non-destructive testing of road pavements and other constructions using pulsed UWB georadars.
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399,105 |
Please write an abstract with title: An Unconditionally Stable Conformal LOD-FDTD Method for Curved PEC Objects and its Application to EMC Problems, and key words: Finite difference methods, Time-domain analysis, Numerical stability, Stability criteria, Solid modeling, Electromagnetics, Electromagnetic compatibility. Abstract: The traditional finite-difference time-domain (FDTD) method is constrained by the Courant–Friedrich–Levy condition and suffers from the notorious staircase error in electromagnetic simulations. This article proposes a 3-D conformal locally one-dimensional FDTD (CLOD-FDTD) method to address the two issues for modeling perfectly electrical conducting (PEC) objects. By considering the partially filled cells, the proposed CLOD-FDTD method can significantly improve the accuracy compared with the traditional locally one-dimensional FDTD (LOD-FDTD) method and the FDTD method. At the same time, the proposed method preserves unconditional stability, which is analyzed and numerically validated using the von Neumann method. Significant gains in central processing unit time are achieved by using large time steps without sacrificing accuracy. Two numerical examples, including a PEC cylinder and a missile, are used to verify its accuracy and efficiency with different meshes and time steps. It can be found from these examples that the CLOD-FDTD method shows better accuracy and can improve the efficiency compared with those of the traditional FDTD method and the traditional LOD-FDTD method.
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399,106 |
Please write an abstract with title: Cybersecurity Analytics using Smart Inverters in Power Distribution System: Proactive Intrusion Detection and Corrective Control Framework, and key words: cyber-physical resiliency, cybersecurity, anomaly detection, smart inverters, model predictive control. Abstract: Power grids with increasing number of distributed energy resources (DERs) equipped with fleet of smart devices are exposed to malicious attacks. These malicious actions can ultimately cause a large-scale blackout if these subversive activities are not prevented, detected, or promptly addressed. Power grids are being threatened by a category of cyber-physical attacks, which target both the physical and cyber layers of the system. This paper proposes an autonomous detection and corrective control framework consisting of two algorithms to identify anomalies and provide a corrective action on the distribution system using smart inverters. The proposed framework detects the inverter abnormal behaviors and identifies them as cyber-physical attack or internal failure of the inverter. A model predictive control (MPC) scheme is proposed to detect the inverter internal failure. In the case of inverter failure, the proposed MPC scheme adopts corrective actions to restore the inverter operation with a pre-defined power injection set-points. Additionally, this paper proposes a cyber-physical attack detection mechanism, based on measurements from a geographic community of smart devices. The proposed framework continuously assists the supervisory control and data acquisition (SCADA) system to differentiate anomalies on the distribution system and decide the appropriate control actions for the entire grid.
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399,107 |
Please write an abstract with title: Multi-Task Learning in Autonomous Driving Scenarios Via Adaptive Feature Refinement Networks, and key words: Deep learning, Adaptive systems, Pose estimation, Cameras, Task analysis, Optical flow, Autonomous vehicles. Abstract: Many deep learning applications benefit from multi-task learning with several related objectives. In autonomous driving scenarios, being able to accurately infer motion and spatial information is essential for scene understanding. In this paper, we combine an adaptive feature refinement module and a unified framework for joint learning of optical flow, depth and camera pose estimation in an unsupervised manner. The feature refinement module is embedded into motion estimation and depth prediction sub-networks, which can exploit more channel-wise relationships and contextual information for feature learning. Given a monocular video, our network firstly estimates depth and camera motion, and calculates rigid optical flow. Then, we design an auxiliary flow network for inferring non-rigid flow fields. In addition, a forward-backward consistency check is adopted for occlusion reasoning. Extensive experiments on KITTI dataset demonstrate that the proposed method achieves potential results comparing to recent deep learning networks.
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399,108 |
Please write an abstract with title: Impact of Dynamic Pricing in Residential Load Scheduling and Energy Management, and key words: Schedules, Costs, Tariffs, Pricing, Optimal scheduling, Peak to average power ratio, Dynamic scheduling. Abstract: Power consumption schedule can shift the loads from peak hours and redistribute them across a day based on user time preferences. This can indirectly help the utility to improve the load curve. It also helps the residential user to reduce the total electric bill as well. In India, electric billing has fixed energy charges based on the unit the user consumes. Demand-side management can introduce dynamic pricing, so the cost of power consumption is reduced. It motivates the consumer to schedule their load. This paper proposes to minimize the cost of electrical energy by optimal scheduling of home appliances in residential homes using mixed-integer linear programming. It reduces the peak-to-average ratio resulting in a reduction of stress on utility. The paper also discusses the benefit of time of use pricing and real-time pricing over a flat tariff system in the Indian electricity market.
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399,109 |
Please write an abstract with title: Design of residue-to-binary converter for a new 5-moduli superset residue number system, and key words: Dynamic range, Table lookup, Arithmetic, Signal processing algorithms, Delay, Embedded system, Adders, Throughput, Energy consumption, Very large scale integration. Abstract: This paper presents an efficient residue-to-binary (R/B) conversion algorithm for a new 5-moduli superset {2/sup n/-1, 2/sup n/, 2/sup n/+1, 2/sup n+1/-1, 2/sup n-1/-1} residue number system (RNS) when n is even. The new moduli set is provided for larger dynamic range and higher parallelism. Our R/B conversion algorithm is based on a 4-moduli set R/B converter and the mixed-radix conversion (MRC) technique. The proposed architecture is built around full adders, which can be easily pipelined to achieve high throughput rate. Our investigations show that the resulting architecture is notably more efficient than that proposed for an existing 5-moduli set RNS in terms of area, delay and power consumption.
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399,110 |
Please write an abstract with title: Finite Element Analysis of Slow-Wave Schottky Printed Line, and key words: Finite element methods, Attenuation, Microstrip, Schottky barriers, Insulation, Coplanar transmission lines, Transmission line matrix methods, Integral equations, Propagation constant, Circuits. Abstract: The Schottky contacted slow-wave structure is analyzed for the first time without use of a layered model approximation for the localized depletion region. A general finite element code is developed for the analysis. Both microstrip and coplanar configurations are studied.
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399,111 |
Please write an abstract with title: Robust Secure Energy Efficient Beamforming for mmWave UAV Communications With Jittering, and key words: Autonomous aerial vehicles, Uncertainty, Azimuth, Millimeter wave communication, Array signal processing, Transmitting antennas, Power demand. Abstract: This letter proposes a robust secure and energy efficient beamforming (BF) scheme for a millimeter-wave unmanned aerial vehicle (UAV) communication system with imperfect angle-of-departure (AoD) estimation of air-to-ground channel caused by jittering. Specifically, an optimization problem is formulated to maximize the worst-case secrecy energy efficiency (SEE), defined as the ratio of the sum achievable secrecy rate (ASR) to the total power consumption, subject to the UAV transmit power constraint. Due to the difficulty in solving this problem arisen from the AoD uncertainties and the non-convex structures of SEE and ASR, we first adopt the discretization method to simplify AoD uncertainties to a deterministic form and then exploit the successive convex approximation approach with auxiliary variables to convert the original problem into a convex one. Finally, an iterative algorithm is designed to obtain the suboptimal solution. Numerical results are provided to confirm the effectiveness and superiority of the proposed robust BF scheme compared to some benchmark schemes.
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399,112 |
Please write an abstract with title: Extreme learning machine tuning by original sine cosine algorithm, and key words: Training, Analytical models, Extreme learning machines, Computational modeling, Neurons, Metaheuristics, Benchmark testing. Abstract: Extreme learning machine (ELM) is a revolutionary approach for training single-hidden layer feedforward neural networks that combines both high performance and rapid learning speed. Because the input weights and hidden neurons biases are randomly initialized and stay fixed during the process of learning, and the output weights are analytically calculated. ELM produces high generalization capability with a huge number of hidden neurons. The sine cosine method was presented in this study for tuning the input weights and hidden biases. The suggested method is named SCA-ELM, and it selects the input weights and hidden biases using SCA while determining the output weights using the Moore-Penrose (MP) generalized inverse, The aim is to improve the original extreme learning machine algorithm.The suggested methodologies were evaluated on several benchmark classification data sets, and compared with other recent state-of-art algorithms. Simulations reveal that the suggested method outperforms the other alternatives in the comparative analysis.
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399,113 |
Please write an abstract with title: A simple method for producing floating semiconductor inductors, and key words: Inductors, Circuit simulation, Inductance, Impedance, Solid state circuits, Logic devices, Gyrators, Capacitance, Switching circuits. Abstract: A simple method for simulating floating inductances in integrated circuits is described in this correspondence. The principle of simulating inductance is the impedance conversion. Since the characteristics of this simulated inductance are independent of the active parameters of transistors, excellent temperature characteristics and high reproducibility are obtained.
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399,114 |
Please write an abstract with title: Research on the Application of 5G MEC Based on Support Vector Machine in Cloud Side Cooperative Construction of Security Special Video Cloud Management System, and key words: Support vector machines, Industries, Cloud computing, 5G mobile communication, Multimedia systems, Computer architecture, Streaming media. Abstract: Security industry is a sunrise industry. Video surveillance system is a subsystem of security system and an important part of technical defense. IT has matured with the development of IT technologies such as multimedia technology, codec technology and network technology. Nowadays, most of the video analysis and management processes are manual or semi-automatic, which is difficult to meet the real-time requirements, and the utilization rate of video information is low. In this paper, the architecture of mobile edge computing technology is analyzed, and a cascaded two-tier support vector machine is designed. The first tier uses two-class support vector machine to find local features in test images, and the second tier uses multi-class support vector machine to find the categories of images. Using the advantages of cloud computing architecture, it provides users with scalable, flexible and centrally integrated video management, video access and video storage services.
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399,115 |
Please write an abstract with title: Track Fastener Detection Based on Improved YOLOv4-Tiny Network, and key words: Convolution, Neural networks, Transportation, Fasteners, Inspection, Maintenance engineering, Rail transportation. Abstract: Track fasteners on the railway tracks are extremely critical to ensure the safe operation of the railway transportation system. Fast and accurate fastener detection is of great significance for improving the inspection efficiency of railway tracks. However, the existing fastener detection methods have the problem that the detection accuracy and detection speed of the model cannot be well balanced. In this paper, we present a track fastener detection method, which is based on the YOLOv4-Tiny deep convolution neural network. Specifically, data augmentation technology is applied to resolve imbalanced samples, the swish activation function is applied to track fastener detection, and the optimized detection model is deployed in Jetson Xavier NX embedded platform. The experimental results show that the proposed method can effectively improve the accuracy and speed of fastener detection. It paves the way for the real-time track inspection tools to reduce track inspection cost and improve track safety.
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399,116 |
Please write an abstract with title: Telecom Software, Network Virtualization, and Software Defined Networks, and key words: Special issues and sections, Software defined networking, 5G mobile communication, Security, Radio access networks, Computer architecture, Virtualization. Abstract: The articles in this special section focus on telecommunications software, network virtualization, and software defined networks. (SDN) Network softwarization is changing how we build and operate communication networks. It is expected to enable the fifth-generation (5G) networks to provide logically-independent and fully programmable network slices by flexibly, efficiently and securely partitioning the network infrastructure. End-to-end network services are then dynamically provisioned on those slices to meet the diverse requirements of vertical industries. Extensive research and development effort is currently being conducted to explore several aspects of network softwarization including network architecture, management frameworks, and open-source software. The fourth issue of the “Telecom Software, Network Virtualization, and Software Defined Networks” Series features five papers that deal with critical challenges related to 5G networks, such as network slicing, security and trust, access and usage control, service development and opensource tools deployment.
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399,117 |
Please write an abstract with title: Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models, and key words: Deep learning, Measurement, Training, Adaptation models, Biological system modeling, Computational modeling, Watermarking. Abstract: Deep learning models, especially those large-scale and high-performance ones, can be very costly to train, demanding a considerable amount of data and computational resources. As a result, deep learning models have become one of the most valuable assets in modern artificial intelligence. Unauthorized duplication or reproduction of deep learning models can lead to copyright infringement and cause huge economic losses to model owners, calling for effective copyright protection techniques. Existing protection techniques are mostly based on watermarking, which embeds an owner-specified watermark into the model. While being able to provide exact ownership verification, these techniques are 1) invasive, i.e., they need to tamper with the training process, which may affect the model utility or introduce new security risks into the model; 2) prone to adaptive attacks that attempt to remove/replace the watermark or adversarially block the retrieval of the watermark; and 3) not robust to the emerging model extraction attacks. Latest fingerprinting work on deep learning models, though being non-invasive, also falls short when facing the diverse and ever-growing attack scenarios.In this paper, we propose a novel testing framework for deep learning copyright protection: DEEPJUDGE. DEEPJUDGE quantitatively tests the similarities between two deep learning models: a victim model and a suspect model. It leverages a diverse set of testing metrics and efficient test case generation algorithms to produce a chain of supporting evidence to help determine whether a suspect model is a copy of the victim model. Advantages of DEEPJUDGE include: 1) non-invasive, as it works directly on the model and does not tamper with the training process; 2) efficient, as it only needs a small set of seed test cases and a quick scan of the two models; 3) flexible, i.e., it can easily incorporate new testing metrics or test case generation methods to obtain more confident and robust judgement; and 4) fairly robust to model extraction attacks and adaptive attacks. We verify the effectiveness of DEEPJUDGE under three typical copyright infringement scenarios, including model finetuning, pruning and extraction, via extensive experiments on both image classification and speech recognition datasets with a variety of model architectures.
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399,118 |
Please write an abstract with title: Outage Performance in Cooperative IoT Networks with Energy Harvesting, and key words: Relays, Signal to noise ratio, Power system reliability, Probability, Wireless communication, NOMA, Energy harvesting. Abstract: In this paper, we consider a wireless-powered cooperative communication network (WPCCN) consisting of one access point (A), one Power Beacon (B), one source and one relay. In contrast to conventional cooperative networks, the source and relay in the considered network have no embedded energy supply. They need to rely on the energy harvested from B for their cooperative information transmission. We adopt a harvest-then-cooperate protocol in an urban environment, where the source and relay harvest energy from the signals broadcasted by B in the downlink and work cooperatively in the uplink for the sources information transmission. Non-orthogonal multiple access (NOMA) technique is applied in the extension for two-user scenario. Outage probability is explored in low and high signal to noise ratio (SNR) regimes. The impact of the distance between the nodes are extensively investigated.
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399,119 |
Please write an abstract with title: Dry-Coupled Airborne Ultrasonic Inspection Using Coded Excitation, and key words: Transducers, Liquids, Ultrasonic variables measurement, Inspection, Acoustics, Unmanned aerial vehicles, Signal to noise ratio. Abstract: Unmanned Aerial Vehicles (UAVs) offer significant potential benefits to the inspection of large-scale facilities due to their ability to access areas where manual inspection is not practical. Ultrasonic inspections typically utilise acoustic couplant, placed between the specimen and transducer surfaces, to eliminate any air gap and enable acoustic energy propagation. Conventional ultrasonic inspection UAVs contain a mechanical system to deliver a small quantity of liquid couplant between the transducer and inspection surface. Such mechanisms increase the system payload, resulting in the reduction of UAV flight endurance and inspection efficiency. Any couplant remaining on the surface may also increase the risk of corrosion. Instead of a liquid couplant layer, dry-coupled ultrasonic transducers utilise a thin layer of rubberised material. However, the acoustic characteristics of the conformable materials typically result in dry-coupled transducers with a lower Signal-to-Noise Ratio (SNR) than liquid-coupled sensors. Coded excitation, a pulse compression technology, improves SNR without sacrificing the measurement acquisition rate, as is the case with signal averaging. This paper explores the potential for application of coded excitation to maintain the SNR aboard a UAV deploying a dry-coupled transducer.
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399,120 |
Please write an abstract with title: Characterizing Social Marketing Behavior of E-commerce Celebrities and Predicting Their Value, and key words: Social network services, Feature extraction, Business, Atmospheric measurements, Particle measurements, Blogs, Machine learning. Abstract: With the rapid development of online social networks, marketing through online social platforms attracts a lot of attention. Recently, a special social marketing method is prevailing, i.e., e-commerce celebrities(ECs). ECs run their social network accounts to attract followers and then sell products to them directly. While the sales of ECs have dominated the e-commerce marketing in China, there is, however, a lack of accurate measurement and model about it. In this paper, we first conduct a large-scale cross-platform measurement on two of the biggest online social network platforms and e-commerce platforms in China, i.e., Sina Weibo and Taobao. We then characterize the typical behavioral patterns of ECs and build a machine learning model to quantitatively represent the relationship between the social network behavior and their product sale volumes. Experimental results show that we can accurately predict an EC's sale volume based on the 41 social network behavior features (F1 score can reach 0.83). Furthermore, we obtain the top-10 most important features that affect the sales. Our measurement and modeling results provide beneficial insights in understanding and optimizing social marketing for ECs.
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399,121 |
Please write an abstract with title: Generalized minimum variance with pole assignment controller modified for practical applications, and key words: Polynomials, Control systems, Force control, Industrial control, Random sequences, Delay effects, Electrical equipment industry, Manufacturing industries, Instruments, Manufacturing processes. Abstract: Among self-tuning controllers, the explicit type is the most commonly used in industrial applications due to its simple structure; on the other hand the implicit structures are less attractive because of their largest structural complexity. This work presents a modification to the generalized minimum variance with pole assignment controller. The modification pretends to simplify the original algorithm and to make easier its implementation in practical projects, conserving most of the original attributes.
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399,122 |
Please write an abstract with title: Deep Reinforcement Learning-Based Joint User Association and CU–DU Placement in O-RAN, and key words: Delays, Costs, Bandwidth, Resource management, Copper, Optimization, Indexes. Abstract: Open Radio Access Networks (O-RAN) architecture is based on disaggregation, virtualization, openness, and intelligence. These features allow the RAN network functions (NFs) to be split into Central Unit (CU), Distributed Unit (DU), and Radio Unit (RU); and deployed on open hardware and cloud nodes as Virtualized Network Functions (VNFs) or Containerized Network Functions (CNFs). In this paper, we propose strategies for the placement of CU and DU network functions in the regional and edge O-Cloud nodes while jointly associating the users to RUs. The aim is to minimize the end-to-end delay of users and minimize the cost of O-RAN deployment. Thus, we first formulate the end-to-end delay, the cost, and the constraints. We then model the problem as a multi-objective optimization problem The optimization formulation consists of a huge number of constraints and variables. To provide a solution to the problem, we develop the corresponding Markov Decision Problem (MDP) and propose a Deep Q-Network (DQN)-based algorithm. The simulation results demonstrate that our proposed scheme reduces the average user delay up to 40% and the deployment cost up to 20% with respect to our baselines.
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399,123 |
Please write an abstract with title: Fully Soft-switched Non-isolated High Step-down DC/DC Converter with Minimum Component Count, and key words: Buck converters, Prototypes, Switches, High-voltage techniques, Voltage, Zero voltage switching, Semiconductor diodes. Abstract: A fully soft-switched high step-down converter with minimum number of passive and active components is presented in this paper, which is suitable for non-isolated DC/DC applications. High voltage conversion ratio is achieved by a pair of coupled inductors while zero voltage switching condition for the main switch along with zero current switching condition for the main diode at turn-off are provided by adding only an auxiliary active switch and a coupled inductor to the basic buck converter. Thus, the converter is optimum in terms of component count among the soft-switched high step-down converters. The mentioned converter advantages have contributed to the realization of high efficiency. To confirm the theoretical operation and analysis of the converter, a laboratory prototype circuit is implemented for 155-to-24V at 100W and 100kHz.
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399,124 |
Please write an abstract with title: Analog IC Design Using Precomputed Lookup Tables: Challenges and Solutions, and key words: Table lookup, MOSFET, Knowledge based systems, Integrated circuit modeling, Inverse problems, Systematics. Abstract: Design productivity remains an important aspect in the analog integrated circuit design industry, as growing competition and shorter design cycles pressure the traditional flow that involves time-consuming manual iterations in a circuit simulator. This paper describes innovations within an alternative framework that uses precomputed look-up tables (LUTs) to enable fast and accurate evaluation of circuit sizing scenarios without a simulator in the loop. It lets the designer explore and understand the design space boundaries in a systematic setting, thus supporting informed decision making and architectural innovation that is difficult to attain with fully automated, black-box sizing tools. Our discussion begins with an overview of the LUT-based design paradigm and its two primary variants: inverse design (finding design parameters that meet the specifications) and forward evaluation (sweeping design parameters to search the design space). In support of the latter, the core of our work focuses on improving the accuracy and speed of LUT access, enabling millions of queries within seconds on a standard computer. Large improvements over prior art are enabled using enhanced interpolation methods, which allow for a relatively large LUT grid spacing (hence small memory footprint) and yet accurate parameter lookup. We evaluate the efficacy of the proposed methods using two classical analog circuits, a bandgap reference and a folded cascode amplifier. In the bandgap example, we observe less than 1 ppm error between the LUT-predicted temperature coefficient and circuit simulation. In the folded-cascode example, one million design points are generated in only 4 seconds, providing the designer with useful maps that delineate the reachability of certain target specifications.
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399,125 |
Please write an abstract with title: Top-level Scene Information Extraction from Eye-level View Images, and key words: Legged locomotion, Image segmentation, Focusing, Predictive models, Information retrieval, Control systems, Real-time systems. Abstract: People tracking and trajectory prediction generate more research interest recently given the advancement of autonomous devices. To obtain accurate results, the behaviour modelling needs to take into consideration the interactions people have with the environment. This paper proposes a method to extract scene information from 2D eye-level images which can then be passed to a trajectory prediction system. It combines a bird-eye view perspective transformation with a segmentation technique to identify global obstacles and possible walking areas.
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399,126 |
Please write an abstract with title: A fully integrated 5.3 GHz, 2.4V, 0.3 W SiGe-bipolar power amplifier with 50/spl Omega/ output, and key words: Power amplifiers, Impedance matching, Radiofrequency amplifiers, Transformers, Integrated circuit technology, Capacitors, Radio frequency, Circuit synthesis, Driver circuits, Resonance. Abstract: A radio frequency power amplifier for 4.8-5.7 GHz has been realized in a 0.25 /spl mu/m SiGe-bipolar technology. The balanced 2-stage push pull power amplifier uses two on chip transformers as input-balun and for interstage matching. Further it uses three coils for the integrated LC-output balun and the rf-choke. Thus the power amplifier is free of any external components. At 1.0V, 1.5V, 2.4V supply voltages output powers of 17.7 dBm, 21.6 dBm, 25dBm are achieved at 5.3 GHz. The respective power added efficiency is 15.6%, 22.4%, 24%. The small-signal gain is 26dB.
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399,127 |
Please write an abstract with title: Energy optimal set-points for coupled systems using their topology, and key words: Optimization, Mathematical model, Topology, Hysteresis, Data models, Interconnected systems, Information technology. Abstract: Energy efficiency is an emerging topic for companies in the industrial sector. The optimization of existing machines by advanced control is increasingly approached. For interconnected systems, we present a general procedure to include topology knowledge in an automated set-point optimization routine. This paper demonstrates an exemplary algorithm, applied to a parallel connection of two chillers for test purposes.
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399,128 |
Please write an abstract with title: Transient Analysis of the Block Least Mean Squares Algorithm, and key words: Adaptation models, Prediction algorithms, Stochastic processes, Transient analysis, Standards, Task analysis. Abstract: It is known that adaptive filtering algorithms may tackle relevant communication tasks. In order to reduce the adaptation rate, the least mean squares algorithm and its normalized version may be implemented in a block manner, so that the filter coefficients are adjusted once per each output block. This letter advances a stochastic model that is able to predict the learning capabilities of time-domain block extensions of these algorithms, and demonstrates that their behaviour is not governed by trivial generalizations of the rules presented by standard implementations. The devised model decouples the radial and angular distribution of input data for the sake of emphasizing the factors that drive the algorithms learning behaviour. Both algorithms are demonstrated to solve a local and deterministic optimization problem. This novel point of view is employed to derive new versions of these algorithms that are able to enhance asymptotic performance by the usage of coefficient reusing techniques. Theoretical results reveal good adherence to simulated learning curves and the proposed algorithms outperform the standard ones in steady-state.
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399,129 |
Please write an abstract with title: Exploring Causal Effect of Personal Financial Activities by Social Media Influences, and key words: Social networking (online), Computational modeling, Multimedia Web sites, Blogs, Psychology, Information technology. Abstract: Social network (SN) applications such as Facebook, Twitter, Instagram, etc. provide many facilities that allow the user to connect, follow one another, share content, and influence them to engage in various activities in their personal lives. Sometimes it impacts their habits such as online buying, restaurant checkin, traveling, etc. Existing researchers have used a variety of approaches to identify these impacts on various topics, including fitness, psychological health, and so on. However, there is very few research that has been done for investigating individual expenditures. Thus, in this paper, we aim to 1) investigate the relationship between social media use and personal financial activities, 2) estimate personal expenditure based on various social media aspects such as checking into restaurants, buying clothes, traveling to new locations, doing something entertaining, and so on. We collected data through an online survey using social network platforms such as Facebook. We apply a causal model using propensity score-based inverse probability treatment weighting (IPTW) and a doubly robust estimator. We evaluate our approach by refuting the outcome. Finally, we find that social media usage has a significant impact on spending patterns.
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399,130 |
Please write an abstract with title: Application of multi-conductor transmission lines on the transient analysis in power substation, and key words: Power transmission lines, Multiconductor transmission lines, Transient analysis, Substations, Power system modeling, Power system transients, Electromagnetic transients, Finite difference methods, Pulse power systems, Power system analysis computing. Abstract: Some structures in a power system can be modeled as multi-conductor transmission lines or transmission line in order to analyze the transient process when the switches are operated or electromagnetic pulse is imposed. In this paper the modeling of a transmission line and its finite difference time domain (FDTD) method are researched, and then extended to the transmission line network and nonuniform line. After the method is tested, some examples are finally analyzed in order to predict the transient voltage in power substations.
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399,131 |
Please write an abstract with title: Using Artificial Intelligence Technology for Decision Support System in Audit Risk Assessment: A Review Paper, and key words: Support vector machines, Machine learning algorithms, Neural networks, Machine learning, Risk management, Data mining, Artificial intelligence. Abstract: Artificial Intelligence (AI) has a significant impact in the disruptive era. An audit is an area that is affected. The application of AI in internal audits comes from a need to make better-added value, a demand to overcome the traditional audit’s limitation and adapt to the new way of working in the pandemic Covid-19. Risk assessment has a primary role in audit planning and has become a factor that affects the efficiency and effectiveness of the audit. This paper aims to create insight into AI implementation in auditing, especially in risk assessment, including models and algorithms. In addition, it is hoped that new perspectives are formed on how to build decision-making or to problem-solve in auditing through the relationship between the current availability of big data and AI, including data mining and machine learning. This review study showed that risk assessment in auditing became significantly easier using AI technology. The auditor can identify the riskiest audit areas by detecting or predicting, and minimizing audit risks using AI. Classification algorithms such as logistic regression, decision trees, neural networks, and support vector machines can be used to detect or predict. Moreover, another technique that can be utilized is combining it with expert systems or fuzzy theory.
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399,132 |
Please write an abstract with title: Development of a Knowledge Base on the Topics of Theoretical Electrical Engineering Using Software Tools for Analysis and Generation of Collections of WIKI Articles, and key words: Training, Electrical engineering, Electronic publishing, Costs, Knowledge based systems, Information services, Internet. Abstract: The paper discusses issues related to the development of modern computer training tools. The use of artificial intelligence methods opens up new possibilities in the creation of computer-aided training tools and knowledge bases in various problem (subject) areas. It is proposed to solve these problems with the help of the developed software module for analysis and generation of wiki article collections for creating computer-based training aids using the knowledge base on theoretical foundations of electrical engineering as an example.
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399,133 |
Please write an abstract with title: Chipping and wearing in MEMS inertial sensors: effects on stability and predictive analysis through test structures, and key words: Friction, Sensors, Micromechanical devices, Oscillators, Stability analysis, Thermal stability, Q-factor. Abstract: Impacts between fixed and moving parts in capacitive MEMS inertial sensors can generate debris and wear that undermine the device stability. This work investigates the effects of impacts and friction between rotors and stoppers through dedicated test structures. After modeling the scenario, considering the impact kinetic energy and the tensile/ compressive nominal strength of silicon, different stopper topologies and collision angles are studied. Results show how impact kinetic energies, up to 40 nJ (velocities in the 1-3 m/s range for typical inertial sensor masses), correlate with silicon rupture and provide first guidelines for robust sensors design.
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399,134 |
Please write an abstract with title: Simultaneous all-optical 3R regeneration of multiple WDM channels, and key words: Wavelength division multiplexing, Repeaters, Ultrafast optics, Optical distortion, Optical pulse shaping, Optical interferometry, Nonlinear optics, Optical fiber polarization, Jitter, Optical fiber communication. Abstract: A 3R (re-timing, re-amplifying, and re-shaping) regeneration system is proposed, for the first time, to process multiple WDM (wavelength-division-multiplexing) channels simultaneously Its re-timing capability is investigated by applying polarization-scrambling-induced jitter. Jitter tolerance up to 0.5UI/sub pp/ is demonstrated.
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399,135 |
Please write an abstract with title: Effect of thermal damage on the in vitro optical and fluorescence characteristics of liver tissues, and key words: In vitro, Fluorescence, Liver, Optical feedback, Reflectivity, Coagulation, Biomedical optical imaging, Spectroscopy, Optical recording, Radio frequency. Abstract: Thermal energy generated by radio-frequency current or other means may be employed in treating liver tumors by means of thermal coagulation when conventional resection is impossible. Currently, these thermal energy-based therapeutic procedures suffer from the lack of an adequate feedback control system, making it difficult to determine the optimal therapeutic endpoint. In this study, the potential of optical spectroscopy to provide such an objective endpoint for these procedures is presented. Freshly harvested canine liver samples were exposed to 50°C, 60°C, and 70°C water baths for times ranging from 0 to 60 min. Transmission and reflectance were measured from each sample using an integrating sphere and the optical properties of each sample were accordingly derived. Excitation-emission matrices were recorded from the samples using a spectrofluorometer to identify the intrinsic fluorescence characteristics of native and thermally coagulated liver tissues. In addition, fluorescence and diffuse reflectance spectra were separately obtained from the samples prepared using a portable spectroscopic system. Results of this study show that fluorescence and optical properties of liver tissues exhibit clear and consistent changes through the thermal coagulation process. Specifically, the primary peak in the fluorescence spectra from liver tissues shifts from 480 nm in the native state to 510 nm in the fully coagulated state. In addition, a three- to fourfold increase in the absolute intensity of the diffuse reflectance spectra is observed upon complete coagulation of liver tissues. These dynamic spectral features indicate that fluorescence and diffuse reflectance spectroscopy may provide a direct measure of the biochemical and structural changes associated with tissue thermal damage in the liver.
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399,136 |
Please write an abstract with title: Unsupervised Discriminative Learning of Sounds for Audio Event Classification, and key words: Training, Visualization, Conferences, Signal processing, Benchmark testing, Data models, Acoustics. Abstract: Recent progress in network-based audio event classification has shown the benefit of pre-training models on visual data such as ImageNet. While this process allows knowledge transfer across different domains, training a model on large-scale visual datasets is time consuming. On several audio event classification benchmarks, we show a fast and effective alternative that pre-trains the model unsupervised, only on audio data and yet delivers on-par performance with ImageNet pre-training. Furthermore, we show that our discriminative audio learning can be used to transfer knowledge across audio datasets and optionally include ImageNet pre-training.
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399,137 |
Please write an abstract with title: Direct Dual Energy CT Material Decomposition Using Noise2Noise Prior, and key words: Training, Statistical analysis, Computed tomography, Noise reduction, Training data, Reconstruction algorithms, Iterative algorithms. Abstract: Dual energy computed tomography (DECT) can provide material decomposition capability, which can be useful for many clinical diagnosis applications. But the decomposed images can be very noisy due to the dose limit in the scanning and the ill-condition of decomposition process. Recently Noise2Noise framework shows its potential on restoring images by using only noisy data. Inspired by this, we proposed an iterative DECT reconstruction algorithm with a Noise2Noise prior. The algorithm directly estimates material images from projection data and thus can significantly reduce possible bias which may occur in other post-smoothen methods. The Noise2Noise prior was built by a deep neural network, which did NOT need external data for training. The data fidelity term and the Noise2Noise network are alternatively optimized respectively using separable quadratic surrogate (SQS) and Adam algorithm. The method was validated both on simulation data and real clinical data. Quantitative analysis demonstrates the method's promising performance on denoising, bias avoiding and detail reservation.
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399,138 |
Please write an abstract with title: Non-invasive Deception Detection in Videos Using Machine Learning Techniques, and key words: Support vector machines, Visualization, Transient response, Law enforcement, Video sequences, Neural networks, Feature extraction. Abstract: Deception detection has important clinical and legal implica-tions. Detecting deception is very effective in criminal investiga-tions, finding fake news, jurisprudence, law enforcement, and national security. Still, a reliable and Noninvasive deception technique is in progress. Deception detection using visual data is one of the most explored topics for burgeoning researchers. Several studies have been conducted on detecting deception using visual data. But most of them are based on courtroom trial data or mock criminal scenarios. In this paper, we have explored factual data set to identify deception from the subject’s natural response to truth and lie by analyzing Facial Action Units (FAU). Firstly, we selected apex frames of a video sequence and incepted all possible feature sets. Secondly, we analyzed the result of five machine learning classifiers on selected important features for detecting deception. We observed that Support Vector Machine with Radial Basis Function kernel (SVM-RBF), outperformed among all with 61.54% cross-validated accuracy.
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399,139 |
Please write an abstract with title: Integration of air traffic control user interfaces, and key words: Air traffic control, User interfaces, Displays, Radar, Prototypes, Workstations, Control systems, Underwater communication, Surveillance, Communication system traffic control. Abstract: Communication and surveillance capabilities in oceanic air traffic control are improving and the amount of air traffic increases significantly over the next decades. This requires new systems and procedures to be incorporated into the oceanic air traffic controller workstation. The Icelandic Civil Aviation Administration (ICAA) is looking at ways to integrate the current set of user interfaces used at Reykjavik Oceanic Center in an effort to increase controller performance. The workstation consists of three different user interfaces, the flight data processing systems (FDPS), which presents electronic flight strips to the controller, the radar display, which displays radar data and the situation display, which is a backup system for the FDPS system. Three approaches for integration are presented and claims analysis used to select between them. The result of the claims analysis and controllers' preference was a spatial display where the FDPS system is integrated into the radar display. A paper prototype was created and presented to qualified air traffic controllers in order to get feedback on the prototype design as well as the transition from a temporal display to spatial display. This paper discusses the prototype design and the results from two user-testing sessions at ICAA.
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399,140 |
Please write an abstract with title: The new evaluation method of eco products using the eco-efficiency index (Factor X) by consideration of MET, and key words: Economics, Environmental factors. Abstract: For a sustainable society it has been indispensable that dematerialization and economic growth largely depended on improvement in eco-efficiency. Mitsubishi Electric Corporation is engaged in a balanced reduction of environmental impact based on the concept of MET (effective use of Material and Energy, and evasion of Toxicity) in its manufacturing process and throughout its lifecycle of the product including material procurement and use, recycling and disposal of the product after use. It has adopted a unique calculating method of "Factor X", widely received as an eco-efficiency index of a product. This paper describes the concept of calculation of the product eco-efficiency index and introduces some examples that make the base of the undertakings for DFE (Design For Environment).
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399,141 |
Please write an abstract with title: Market models and pricing mechanisms in a multihop wireless hotspot network, and key words: Pricing, Intelligent networks, Spread spectrum communication, Base stations, Relays, Humans, Computer science, Airports, Mobile communication, Throughput. Abstract: Multihop wireless hotspot network [A. Balachandran et al., (2003), F. Fitzek et al., (2003), Y-D. Lin et al., (1999), K-C. Wang et al., (2003)] has been recently proposed to extend the coverage area of a base station. However, with selfish nodes in the network, multihop packet forwarding cannot take place without an incentive mechanism. In this paper, we adopt the "pay for service" incentive model, i.e., clients pay the relaying nodes for their packet forwarding service. Our focus in this paper is to determine a "fair" pricing for packet forwarding. To this end, we model the system as a market where the pricing for packet forwarding is determined by demand and supply. Depending on the network communication scenario, the market models are different. We classify the network into four different scenarios and propose different pricing mechanisms for them. Our simulation results show that the pricing mechanisms are able to guide the market into an equilibrium state quickly. We also show that maintaining communication among the relaying nodes is important for a stable market pricing.
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399,142 |
Please write an abstract with title: A New Deep Complex-Valued Single-Iteration Fuzzy System for Predictive Modelling, and key words: Dimensionality reduction, Machine learning algorithms, Neural networks, Stochastic processes, Predictive models, Prediction algorithms, Fuzzy systems. Abstract: Numerical prediction is an important application field of machine learning. However, the current mainstream relating to deep network solutions can be computationally taxing, whereas fuzzy systems may also prove to be inefficient for high dimensional systems. Combining the notion of complex-valued neural network and the Wang-Mendel (WM) fuzzy algorithm, we propose a new complex-valued Wang-Mendel (CVWM) method, which reduces the rule-base of fuzzy systems to the scale of its square root. Further, by introducing the concept of a hierarchical fuzzy system, a deep complex-valued single-iteration fuzzy system (DCVSF) that can be trained with only one iteration and can effectively process high-dimensional data is also elicited. In addition, for sparse data, t-distributed stochastic neighbor embedding (t-SNE) dimensionality reduction is introduced to increase data density. The experimental results show that both CVWM and DCVSF exhibit competitive nonlinear modeling capabilities.
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399,143 |
Please write an abstract with title: Multiport characteristics of a wide-band cavity backed annular patch antenna for multipolarization operations, and key words: Broadband antennas, Patch antennas, Reflection, Frequency response, Bandwidth, Scattering, Antenna measurements, Reflector antennas, Antenna feeds, Moment methods. Abstract: This paper focuses on the multiport characterization of antennas. In particular, special attention is given to the cavity backed annular patch antenna (CABAPA) for multipolarization operations. We will show that the reflection coefficient is not the best representative parameter to determine the frequency response of the multiport antenna and its radiation performance. Therefore, we seek a new generalized parameter that conveys the frequency response of multiport antennas. The total active reflection coefficient (TARC) is introduced as the square root of the sum of all incident powers at the ports minus radiated power, divided by the sum of all incident powers at the ports. The TARC is a function of frequency and is a real number between zero and one. With this definition we can characterize the multiport antenna's frequency bandwidth and radiation performance. A method for calculating the TARC is detailed for different port excitations directly from the scattering matrix of the antenna and independent of the feeding network. First, the CABAPA is analyzed by the method of moments. Next, the corresponding scattering matrix is employed to calculate the TARC for different polarizations. The calculated results, when compared to the measured results, show good agreement. The measured -10 dB TARC bandwidth of the CABAPA is 30% compared with 68% as measured using only the s/sub 11/.
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399,144 |
Please write an abstract with title: Wave Scattering from a Modulated Rough Surface, and key words: Correlation, Surface waves, Scattering, Modulation, Radar, Radar scattering, Predictive models. Abstract: We illustrate the wave scattering from a multiscale rough surface modeled by a modulated correlation function. The modulation ratio, defined as the ratio of baseband correlation length and the modulated length, determines the degree of multiscale roughness. The dependence of bistatic scattering on the modulation ratio are investigated. Numerical results show that without considering the multiscale roughness, the scattering coefficients are overestimated at a small incident angle region but underestimated at a large scattering region. Radar wave scattering from multiscale rough surface is highly frequency selective. As an application example, we compare the model predictions with two independent sets of measurement data. The results demonstrate that the model predictions with modulation effects are in good agreement with the measurement data.
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399,145 |
Please write an abstract with title: Speckle Reconstruction with Corruption through Multimode Fibers using Deep Learning, and key words: Speckle, Optical fibers, Optical fiber dispersion, Optical fiber networks, Image reconstruction, Machine learning. Abstract: We present for the first time a deep learning approach toward speckle reconstruction with corruption through a multimode fiber (MMF) with a long length. Our experiments demonstrate that a small partly or randomly corrupted speckle can be reconstructed into its intact speckle over a 1km 100μm-core step-index MMF.
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399,146 |
Please write an abstract with title: Coherently Combined DFB Laser Array Chip With Reduced Relative Intensity Noise, and key words: Semiconductor laser arrays, Measurement by laser beam, Laser stability, Laser noise, Waveguide lasers, Laser theory, Fiber lasers. Abstract: The relative intensity noise (RIN) behavior of coherently combined DFB laser array by injection locking is experimentally investigated. A monolithically integrated four-element DFB laser array with a splitter and an output coupler is fabricated, and the frequency stabilities of the DFB lasers are improved to ensure a stable injection locking of DFB laser array by a master laser. It is demonstrated that the RIN of the coherently combined laser array is reduced by almost 20 dB at low frequencies compared with the free-running state. The results indicate that monolithic integration of DFB laser array under injection locking can help improve the RIN performance by eliminating variation in coupling delays and phase jitters.
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399,147 |
Please write an abstract with title: Radio and optical observations of the possible AE Aqr twin, LAMOST J024048.51+195226.9, and key words: accretion, accretion discs, stars: jets, novae, cataclysmic variables, white dwarfs, radio continuum: stars. Abstract: It was recently proposed that the cataclysmic variable (CV) LAMOST J024048.51+195226.9 may be a twin to the unique magnetic propeller system AE Aqr. If this is the case, two predictions are that it should display a short period white dwarf spin modulation, and that it should be a bright radio source. We obtained follow-up optical and radio observations of this CV, in order to see if this holds true. Our optical high-speed photometry does not reveal a white dwarf spin signal, but lacks the sensitivity to detect a modulation similar to the 33 s spin signal seen in AE Aqr. We detect the source in the radio, and measure a radio luminosity similar to that of AE Aqr and close to the highest so far reported for a CV. We also find good evidence for radio variability on a time-scale of tens of minutes. Optical polarimetric observations produce no detection of linear or circular polarization. While we are not able to provide compelling evidence, our observations are all consistent with this object being a propeller system.
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399,148 |
Please write an abstract with title: Photonic Long-Short Term Memory Neural Networks with Analog Memory, and key words: Conferences, Neural networks, Bandwidth, Analog memory, Photonics. Abstract: A Photonic implementation is proposed for the Long-Short Term Memory neural network, offering fundamental speed and bandwidth advantages over digital electronic implementations. Integrated analog memory for photonics is designed as a component of this network.
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399,149 |
Please write an abstract with title: Simulation calculation and influence factor analysis of induced voltage of metal sheath, and key words: Solid modeling, Electric potential, Analytical models, Voltage, High-voltage techniques, Software, Safety. Abstract: The current in the core of the single-core high-voltage cable will induce the alternating magnetic field around it, and the cable metal sheath will induce the induced voltage under the action of the magnetic field. Higher induced voltage will affect the normal operation of the cable and the safety of the operations staff. In this paper, a three-dimensional corrugated aluminum sheath model is constructed according to the actual cable, and the results are compared with the two-dimensional model, in the case of horizontal laying and triangular laying, the error is within 0.009V/m, so a two-dimensional model can be used to simplify the calculation. The error between the two-dimensional model and theoretical calculation is within 0.005V/m under the two laying conditions, which verifies the correctness of the simulation value. In this paper, the effect of unbalance of current on induced voltage is analyzed. When the phase angle is unbalance, the induced voltage of other phases increases sharply. On the basis of double circuit calculation formula, the induced voltage of three circuits and four circuits is calculated by superposition method. The induced voltage of more phases can be superimposed according to this method. The intermediate distance can be appropriately increased to reduce the side phase induced voltage during four-loop laying. The results of the discussion have reference significance for cable laying in practical engineering.
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399,150 |
Please write an abstract with title: FusionNet: Coarse-to-Fine Extrinsic Calibration Network of LiDAR and Camera with Hierarchical Point-pixel Fusion, and key words: Point cloud compression, Adaptation models, Laser radar, Sensor phenomena and characterization, Sensor fusion, Feature extraction, Cameras. Abstract: In this paper, we propose a novel network, Fusion-Net, which can estimate the extrinsic calibration matrix between LiDAR and a monocular RGB camera with high accuracy and robustness. FusionNet is a coarse-to-fine method, providing an online and end-to-end solution that can automatically detect and correct the decalibration without any specially designed targets or environments. First, the network applies deep-learning-based technologies to extract the features of LiDAR point clouds and RGB images. Then a novel method is adopted to fuse the features got from different sensors by projecting LiDAR features onto RGB feature maps, searching for the RGB features with the projected points as centers and concatenating the extracted RGB features with LiDAR features. To increase the accuracy, we apply a coarse-to-fine method in the network, by transforming LiDAR points and estimating the extrinsic calibration matrices from the coarse scale to the fine scale. The network is trained on random artificial decalibration matrices. Compared to existing approaches, our method doesn't need to train additional iterative networks, but it can also adapt to different ranges of decalibration.
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399,151 |
Please write an abstract with title: Probabilistic Neural-Kernel Tensor Decomposition, and key words: Tensors, Uncertainty, Neural networks, Probabilistic logic, Prediction algorithms, Complexity theory, Kernel. Abstract: Tensor decomposition is a fundamental framework to model and analyze multiway data, which are ubiquitous in real-world applications. A critical challenge of tensor decomposition is to capture a variety of complex relationships/interactions while avoiding overfitting the data that are usually very sparse. Although numerous tensor decomposition methods have been proposed, they are mostly based on a multilinear form and hence are incapable of estimating more complex, nonlinear relationships. To address the challenge, we propose POND, PrObabilistic Neural-kernel tensor Decomposition that unifies the self-adaptation of Bayes nonparametric function learning and the expressive power of neural networks. POND uses Gaussian processes (GPs) to model the hidden relationships and can automatically detect their complexity in tensors, preventing both underfitting and overfitting. POND then incorporates convolutional neural networks to construct the GP kernel to greatly promote the capability of estimating highly nonlinear relationships. To scale POND to large data, we use the sparse variational GP framework and reparameterization trick to develop an efficient stochastic variational learning algorithm. On both synthetic and real-world benchmark datasets, POND often exhibits better predictive performance than the state-of-the-art nonlinear tensor decomposition methods. In addition, as a Bayesian approach, POND provides the posterior distribution of the latent factors, and hence can conveniently quantify their uncertainty and the confidence levels for predictions.
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399,152 |
Please write an abstract with title: Ambiguity and what to do about it [requirements engineering], and key words: Context, Humans, Engineering management, Programming profession, Feedback, Airports, Counting circuits. Abstract: A major concern of most software customers, managers, and requirements engineers is to remove ambiguity in communication of requirements and specifications. The most obvious solution is to try to anticipate all possible misunderstandings and write the requirements perfectly precisely. In practice, this does not work. This talk explains why it does not work, and offers easy, inexpensive methods for removing ambiguity - methods that anyone can do. The fundamental principle is to add redundancy, especially redundancy relating to context. High-bandwidth, informal communication is always a necessary supplement to formal, mathematical expressions. As software development is in essence the creation of formal, executable descriptions for the informal domains where our intents lie, we explore many ways to break up this process into small stages, allowing programmers and customers to detect ambiguity through real-world feedback.
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399,153 |
Please write an abstract with title: Efficient and Secure Blockchain System for Digital Content Trading, and key words: Blockchain, Copyright protection, Consensus algorithm, Privacy, Forgery, Distributed databases. Abstract: Blockchain is attracting attention as a new solution for problems such as illegal copying, profit distribution, and forgery and falsification in the digital content trading environment, which has become an essential asset in the information age. However, one problem is that it is difficult to propagate digital content to the blockchain network because of a limited capacity to upload to the blockchain. The integrity and transparency of blockchain are also considered as weak points in terms of privacy. In this paper, we propose a new blockchain system, the secret block-based blockchain (SBBC), to address the problems with the blockchain system in the digital content trading environment. SBBC is composed of off-chain and on-chain network components. Off-chain is the part that allows trading digital content through the authentication phase. The digital content that is traded has a digital fingerprint inserted, so if an illegal leak occurs, the destination can be tracked. In addition, the content is encrypted and traded, and only the rightful user can use the digital content, thus ensuring income for the legitimate content author. Next, the on-chain network is licensed to use digital content, and a verification process using a consensus algorithm is performed. The licensed consumer creates a secret block of their transaction and records it only on their ledger. In a private part, secret block creation ensures privacy and solves the network overload that can occur when uploading digital content to the blockchain. Finally, through the verification and agreement of all blockchain participants, a public block is created and recorded in the ledger to finalize the transaction. Consequently, we propose the SBBC system suitable for digital content trading environments and a safe and reliable system through a consensus algorithm in such environments.
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399,154 |
Please write an abstract with title: Deep Learning for Predicting CD-SEMS of NEMS Devices, and key words: Training, Semiconductor device modeling, Deep learning, Nanoelectromechanical systems, Lithography, Predictive models, Data models. Abstract: This paper presents an AI model that predicts the process output from photolithography and plasma etching based on CD-SEM data. This contrasts with physics-based models that are used in conventional TCAD tools. A large dataset was generated consisting of nanostructure CD-SEMs (~150,000) from outcomes of an ASML DUV lithography stepper and an Oxford Cobra ICP plasma etcher. The AI model is an Image-to-Image Translation deep learning algorithm that learns from a training set of the CD-SEMs. This deep learning model enables an evolving TCAD model in which layouts can be actively modified as data from the cleanroom is collected continuously. This model can be helpful to improve yield and device homogeneity and performance, hence time to market, for advanced sub-micron NEMS and MEMS. This nature of this dataset ensures the applicability of the presented algorithms to academic and industrial cleanrooms.
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399,155 |
Please write an abstract with title: Robustness of spatial averaging equalization methods: a statistical approach, and key words: Robustness, Microphones, Position measurement, Student members, Speech, Linear systems, Acoustic reflection, Frequency response, Frequency measurement. Abstract: Traditionally, room response equalization is performed to improve sound quality at a given listener. However, room responses vary with source and listener positions. Hence, in a multiple listener environment, equalization may be performed through spatial averaging of room responses. However, the performance of averaging based equalization, at the listeners may be affected when listener position changes. In this paper, we present a statistical approach to map variations in listener positions to performance of spatial averaging based equalization. The results indicate that, for the analyzed listener configurations, the zone of equalization depends on distance of microphones from a source and the frequencies in the sound.
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399,156 |
Please write an abstract with title: OpinionRank: Trustworthy Website Detection Using Three Valued Subjective Logic, and key words: Hypertext systems, Web pages, Big Data, Internet, Search engines, Web search, Engines. Abstract: For a web search engine, it is critical to design a mechanism to promote trustworthy websites and eliminate spam ones in the searching results. In this paper, we propose the OpinionRank algorithm to compute the trustworthiness of a website and identify trustworthy ones with high trust values. OpinionRank is essentially a breadth-first-search based algorithm that starts from an existing set of trustworthy websites, also called seeds. Because seeds play a vital role in OpinionRank, we put forward a novel seed selection scheme, named HarMean PageRank algorithm. HarMean combines the results of two seed selection algorithms, i.e. High PageRank and Inverse PageRank, to rank websites based on their trustworthiness. After trustworthy seeds are chosen, OpinionRank iteratively computes the trustworthiness of every website, leveraging trust propagation and trust combination. Using the public dataset WEBSPAM-UK2006, we validate OpinionRank and HarMean PageRank, analyze the impact of seed selection, and evaluate the convergence speed of OpinionRank. Experimental results indicate that OpinionRank can detect more trustworthy websites with fewer seeds, when compared to three state-of-the-art solutions, TrustRank, GoodRank, and Enhanced OpinionWalk algorithms.
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399,157 |
Please write an abstract with title: Coded Caching and Spatial Multiplexing Gain Trade-off in Dynamic MISO Networks, and key words: Wireless communication, Unicast, Conferences, Phantoms, Signal processing, Multicast communication, MISO communication. Abstract: The global caching gain of multi-antenna coded caching techniques can be also mostly achieved in dynamic network setups, where the cache contents of users are dictated by a central server, and each user can freely join or leave the network at any moment. In the dynamic setup, users are assigned to a limited set of caching profiles and the non-uniformness in the number of users assigned to each profile is compensated during the delivery phase by either adding phantom users for multicasting or serving a subset of users with unicast transmissions. In this paper, we perform a thorough analysis and provide closed-form representations of the achievable degrees of freedom (DoF) in such hybrid schemes, and assess the inherent trade-off between the global caching and spatial multiplexing gains caused by either adding phantom users or serving parts of the data through unicasting.
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399,158 |
Please write an abstract with title: BPNN Based Indoor Fingerprinting Localization Algorithm Against Environmental Fluctuations, and key words: Location awareness, Euclidean distance, Databases, Sensors, Neural networks, Wireless sensor networks, Parameter estimation. Abstract: For mobile users, the ability to accurately acquire their own location is critical. By locating, mobile users can get information about their environment and access location-related services. RSS fingerprint-based indoor localization method collects a training database of measurement fingerprints and uses a machine learning classifier to determine a person’s location from a new fingerprint. However, as the environment changes over time due to furniture or other objects being moved, the new fingerprints diverge from those in the original database. Therefore, an RSS-difference based localization system is designed to deal with the above problem. This method combines back-propagation neural network (BPNN) and weighted K-Nearest Neighbor (WKNN) method to improve the fingerprint similarity based indoor location method (FSIL). We train BPNN in the off-line stage to obtain the optimal BPNN parameter settings. In the online stage, K nearest neighbor points are firstly selected based on the improved FSIL algorithm, and then the difference of signal strength values between the K nearest neighbor points and the target user is input into the BPNN network, to obtain the Euclidean distance between the K nearest neighbor points and the target user, and finally the WKNN algorithm is used to obtain the user’s ultimate location. Simulation experiments based on the LDPL model and the Wireless Insite software, as well as the test results based on the indoor localization dataset IPIN2016, show that the localization accuracy in complex indoor scenarios can be improved by at least 11% when using the method proposed in this paper.
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399,159 |
Please write an abstract with title: Low-frequency electronic gate detection for the counting and sizing of cells, bacteria, and colloidal particles in liquids, and key words: Microorganisms, Frequency, Liquids, Capacitance, Biomedical measurements, Pulse amplifiers, Impedance, Electrochemical processes, Particle measurements, Size measurement. Abstract: Low-frequency (LF) electronic gating is proposed for the detection and sizing of cells, bacteria, and colloidal particles in liquids. LF gating avoids the disturbing effects of electrolysis inherent to dc-operated systems and the poor sensitivity of high-frequency gating. The technique is intended for continuous operation on-line, in chromatography-like experiments.
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399,160 |
Please write an abstract with title: A Model-Free Approach to Distributed Transmit Beamforming, and key words: Array signal processing, Mobile agents, Signal processing algorithms, Linear programming, Numerical models, Acoustic beams, Antenna arrays. Abstract: This paper presents a model-free solution to distributed transmit beamforming using mobile agents. Each agent is equipped with an antenna and the agents represent the individual elements in an antenna array. The agents are tasked to coordinate their relative location, phase offsets, and amplitude to construct a desired beam-pattern. As a prospective solution, we propose a model-free optimization algorithm based on real-time feedback that does not require a model that maps the control parameters (relative location, phase offsets, and amplitude) to a radiation pattern. We evaluate the performance of proposed approach for different motion constraints. Numerical results are presented to validate the theory.
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399,161 |
Please write an abstract with title: Multi-layer, mission-aware QoS management techniques for IP applications in a joint battlespace infosphere, and key words: Quality of service, Software prototyping, Prototypes, Application software, Unmanned aerial vehicles, Computer architecture, Software quality, Routing protocols, Mobile ad hoc networks, Software algorithms. Abstract: This paper presents an overall architecture and prototype for mission-based network management in a joint battlespace infosphere (JBI) that combines application, network, and MAC-layer QoS management. It describes an MBNM prototype system for an air force cooperative attack mission with swarms of unmanned aerial vehicles. The prototype implementation uses BBN's quality objects (QuO) software framework to develop a UAV imagery application that adapts its behavior based on mission-state and network-state in order to meet its required end-to-end quality of service; SRC's wireless ad hoc routing protocol (WARP) to implement a bandwidth-based MANET routing algorithm; and the common open policy service (COPS) as the policy distribution mechanism.
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399,162 |
Please write an abstract with title: Augmented reality to assist teleoperation working with reduced visual conditions, and key words: Augmented reality, Layout, Robots, TV, Optical sensors, Optical feedback, Automatic control, Control engineering computing, Robotics and automation, Operating systems. Abstract: Teleoperation in harsh environments has to tackle the problem of working with images of poor quality, as the visual feedback means for the human operator. This paper describes a procedure for image augmentation, based on the models of the scene elements, which are built from the images acquired in a previous phase, before the execution of the task, when the visual environment conditions are still good enough.
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399,163 |
Please write an abstract with title: Sea relay and weather towers, and key words: Poles and towers, Sea surface, Electronic ballasts, Tail, Stability, Power generation, Microwave devices, Power generation economics, Cables, Relays. Abstract: The sea relay and weather tower is to overcome problems in communicating by microwave, radio, or sonic waves in water. The system is arranged to interconnect signals received by one means to transmission equipment of each of the three methods stated. The tower is floated horizontally to its location and erected using ballast. The microwave tower is hydraulically ejected into position. The lower end of the tower is at the sonic clear channel depth. Because its buoyancy comes from such a depth, the tower is not affected by wave motion. Each tower may be manned or unmanned. The more obvious uses of these towers are as weather stations; communications between land masses; and submarine communication.
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399,164 |
Please write an abstract with title: Quartz crystal microbalance (QCM) sensor for ammonia gas using clay/polyelectrolyte layer-by-layer self-assembly film, and key words: Gas detectors, Self-assembly, Transistors, Robustness, Nanoporous materials, Assembly, Electrodes, Casting, Humidity, Crystalline materials. Abstract: An ammonia gas sensor which has a high sensitivity in robust conditions has been investigated. A nanoporous thin film consisting of polyelectrolytes and sheet particulate /spl alpha/-ZrP was assembled by a layer-by-layer self assembly method on the electrode of a quartz crystal microbalance (QCM). This QCM sensor showed an eight times higher sensitivity than that of QCM deposited with /spl alpha/-ZrP by a casting method in low relative humidity. This means that the polyelectrolytes worked not only as a stabilizer to form a porous structure, but also as a material to keep moisture. Consequently, we considered that the gas sensitivity of the thin film is increased for other hydrophilic gases.
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399,165 |
Please write an abstract with title: Cross-modal Hashing Retrieval Based on Density Clustering, and key words: Semantics, Correlation, Clustering algorithms, Binary codes, Computational efficiency, Training data, Benchmark testing. Abstract: Cross-modal hashing retrieval methods have attracted much attention for their effectiveness and efficiency. However, most of the existing hashing methods have the problem of how to precisely learn potential correlations between different modalities from binary codes with minimal loss. In addition, solving binary codes in different modalities is an NP-hard problem. To overcome these challenges, we initially propose a novel adaptive fast cross-modal hashing retrieval method under the inspiration of DBSCAN clustering algorithm, named Cross-modal Hashing Retrieval Based on Density Clustering(DCCH). DCCH utilizes the global density correlation between different modalities to select representative instances to replace the entire data precisely. Furthermore, DCCH excludes the adverse effects of noise points and leverages the discrete optimization process to obtain hash functions. The extensive experiments show that DCCH is superior to other state-of-the-art cross-modal methods on three benchmark bimodal datasets, i.e., Wiki, MIRFlickr and NUS-WIDE. Therefore, the experimental results also prove that our method DCCH is comparatively usable and efficient.
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399,166 |
Please write an abstract with title: Supercontinuum Generation in Dispersion-Engineered PECVD SiN Waveguides for a Yb-Fiber Laser Frequency Comb, and key words: Optical waveguides, Silicon compounds, Dispersion, Waveguide lasers, Optical interferometry, Nonlinear optics, Optimized production technology. Abstract: We present the development of a self-referencing Yb-fiber laser frequency comb based on octave-spanning supercontinuum generation from dispersion-engineered silicon nitride waveguides, fabricated with the standard, readily available plasma-enhanced chemical vapor deposition (PECVD) process.
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399,167 |
Please write an abstract with title: Formulation of INL and DNL yield estimation in current-steering D/A converters, and key words: Yield estimation, Linearity, Signal resolution, Cost function, Energy consumption, Digital-analog conversion, Signal processing, Gaussian distribution, Voltage, Calibration. Abstract: Current source mismatch is a major source of nonlinearity in current-steering digital-to-analog converters (DAC). In order to achieve a given linearity specification at a given yield level, it is essential that the designer determine the:: minimum required matching accuracy of the unit current sources. Monte-Carlo simulations are very time-consuming and provide the designer with little insight to choose proper DAC architectures and make tradeoff between design specifications. The limited mathematical formulations that have appeared in the literature are based on nonstandard linearity definitions or oversimplifying statistical assumptions. In this paper, simple formulas are obtained that accurately describe the relationship between nonlinearity, bits of resolution, minimum required matching accuracy, and yield, which make it possible to optimize the DAC structure and achieve high performance with less cost and power consumption.
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399,168 |
Please write an abstract with title: Tactile Grasp Stability Classification Based on Graph Convolutional Networks, and key words: Support vector machines, Electrodes, Torque, Convolution, Force, Fingers, Grasping. Abstract: One of the challenges for robots to grasp unknown objects is to predict whether objects will fall at the beginning of grasping. Evaluating robotic grasp state accurately and efficiently is a significant step to address this issue. In this paper, based on the different fusion approaches of multi-sensor tactile signals, we propose two novel methods based on Graph Convolution Network (GCN) for robotic stability classification. Specifically, we propose two deep learning methods including GCN based on data-level fusion (GCN-DF) and GCN based on feature-level fusion (GCN-FF). We explore the optimal parameters for transforming sensor signals into a graph structure. Furthermore, we verify the effectiveness of the proposed methods on the BioTac Grasp Stability (BiGS) dataset. The experimental results prove that the proposed approaches achieve higher classification accuracy than Support Vector Machine (SVM) and Long Short-Term Memory (LSTM).
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399,169 |
Please write an abstract with title: Reliable Edge Computing Architectures for Crowdsensing Applications, and key words: Cloud computing, Crowdsensing, Computer network reliability, Computer architecture, Quality of service, Reliability engineering, Reliability. Abstract: Edge computing has opened the door to a wide range of opportunities in the field of crowdsensing. Processing that happens close to the end devices has many advantages over those that take place at the cloud, such as lower latency and near real-time computation. However, research on the reliability of edge-computing paradigms is important if we wish to maintain the Quality of Service (QoS). This paper aims to review research studies that emphasize reliability in edge-computing architectures. We will discuss various approaches that researchers have taken to tackle resilience in Internet of Things (IoT) networks. Thus, we will be able to gauge the status of IoT reliability research. We have divided the research studies based on the approach taken by researchers in proposing suitable models. The majority of literature analyzes networks based on layers, such as edge, fog, cloud, etc. These proposed architectures can support edge-computing practices. Crowdsensing can utilize reliable edge-computing architectures to develop improved systems and procedures. Studies on reliability are crucial since edge-computing architectures have found applications in mission-critical areas such as healthcare. Reliability studies is also important for the manufacture of energy-efficient systems. This is because if a system has a reliable design, then less time will be spent on its maintenance. Hence, the applications of this study are not limited to crowdsensing.
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399,170 |
Please write an abstract with title: A Probability-Based Algorithm for Electric Vehicle Behaviour in a Microgrid with Renewable Energy and Storage Devices, and key words: State of charge, Indexes, Batteries, Degradation, Probabilistic logic, Microgrids. Abstract: The recent growth in the use of Electric Vehicles (EVs) in transportation systems has increased their importance in electrical power systems. In unison, new entities and ways of operating electrical power systems have emerged. An example of this is the concept of microgrid. In this paper, a probability-based algorithm is developed to simulate the behaviour of EVs. This algorithm is based on data of initial State of Charge (SOC), plugin/out times, types of vehicles and chargers. The algorithm uses the Monte Carlo method to perform its simulations. Also, a two-stage stochastic energy scheduling model for a Microgrid (MG) is proposed to make a day-ahead optimal decision in the first stage. Real-time operations, including wind/solar power, baseload demand and the EV demand variability, are minimised in the second stage. Finally, the model is tested in a case study to verify its correct behaviour and applicability. The case study is implemented using profiles obtained from historical data and the algorithm developed for that purpose.
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399,171 |
Please write an abstract with title: Information Capacity Analysis of DMC under Spherical Biological System, and key words: Bandwidth, Nanobioscience, Transmitters, Receivers, Biological system modeling, Signal processing. Abstract: Molecular Communication (MC) has been evolved as a new paradigm of communication due to its bio and nano compatibility. Its application in the healthcare includes detection and monitoring of bimolecular disease along with intelligent drug delivery. However, like any communication system information capacity is of prime concern. In this paper we have proposed novel information theoretic analysis of MC system. In particular analytical expression of information capacity is presented by considering spherical biological system. It is noteworthy to mention that concentration Green function (CGF) has been used to derive the proposed expression of capacity. Proposed expression is novel and never presented in the literature till the date. Also, Numerical analysis shows perfect agreement with the theoretical back ground of MC.
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399,172 |
Please write an abstract with title: Improved polarimetric SAR classification by application of terrain azimuth slope corrections, and key words: Azimuth, Polarization, Radiometry, Instruments, L-band, Radar cross section, Optical scattering, Surface topography, Vegetation mapping, Statistics. Abstract: In polarimetric SAR imagery, along-track or azimuth slopes cause a shift in the polarization orientation angles. By estimating the orientation angle shift, Schuler et al. have been able to generate topographic models in good agreement with DEMs produced by other means. An improved method for estimating the orientation angle was developed by Lee et al. along with a unified analysis of available techniques. Another way to view this work is as a means of correcting the polarimetric SAR imagery for the terrain-induced slope effects in order to improve the accuracy of geophysical parameters derived from the SAR imagery. In this paper the techniques of Lee et al. are used to correct C and L-band polarimetric AIRSAR imagery taken in 1996 over the flanks of Mt Tongariro, New Zealand. We then use the corrected and uncorrected data in classification schemes and compare the results to demonstrate the effects of the azimuth slope corrections. The volcanic Mt Tongariro provides a rich variety of surface slopes, and a variety of vegetation is present including exotic forest, native forest, scrub, grasses and bare ground. Class statistics extracted from fore- and back-slopes (in the azimuth direction) are observed to cluster more tightly than for uncorrected data. This effect is more pronounced for L-band than for C-band. The largest effects were seen in targets of low polarisation entropy such as exotic forest. These corrections result in a modest improvement in the overall classification accuracies.
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399,173 |
Please write an abstract with title: Comparison of Surge Impedance Model and Electromagnetic Field Model of Transmission Tower, and key words: Poles and towers, Impedance, Surges, Surge protection, Electromagnetic fields, Power transmission lines, Power systems. Abstract: Since the tower surge impedance model plays a very important role in the lightning protection calculation of transmission lines, scholars at home and abroad have given a large number of tower surge impedance models, but the differences are very large. In this paper, the electromagnetic field model of a typical tower is established. Through electromagnetic field calculation, the tower surge impedance is obtained and compared with the calculation results of the existing formula. The calculation result shows that when the rise time of the injected current becomes shorter, the refraction and reflection signal are easier to distinguish. Therefore, the impulse impedance of the tower calculated by the electromagnetic field method will tend to the actual surge impedance. The surge impedance calculation result obtained by the formula proposed by Visacro is the closest to the electromagnetic field simulation result, which can truly show the true transient characteristics of the tower.
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399,174 |
Please write an abstract with title: Ray Tracing Structured AMR Data Using ExaBricks, and key words: Rendering (computer graphics), Computational modeling, Ray tracing, Data models, Adaptation models, Octrees. Abstract: Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however, efficiently rendering such data remains a challenge. We present an efficient approach for volume- and iso-surface ray tracing of Structured AMR data on GPU-equipped workstations, using a combination of two different data structures. Together, these data structures allow a ray tracing based renderer to quickly determine which segments along the ray need to be integrated and at what frequency, while also providing quick access to all data values required for a smooth sample reconstruction kernel. Our method makes use of the RTX ray tracing hardware for surface rendering, ray marching, space skipping, and adaptive sampling; and allows for interactive changes to the transfer function and implicit iso-surfacing thresholds. We demonstrate that our method achieves high performance with little memory overhead, enabling interactive high quality rendering of complex AMR data sets on individual GPU workstations.
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399,175 |
Please write an abstract with title: Regional lung ventilation from volumetric CT scans using image warping functions, and key words: Lungs, Ventilation, Computed tomography, Diseases, Xenon, Time measurement, Pathology, Image registration, Cities and towns, Biomedical imaging. Abstract: We describe a unique method to determine regional lung ventilation non-invasively. In this study, lungs of two sheep were imaged utilizing a multi-detector row CT while maintaining the lungs at different lung inflations in prone and supine positions. Analysis of cross-sections was then performed on the subjects. We made use of a warping function to map lung regions at different lung volumes based on a set of user-defined landmarks, and validated the warping functions using a set of implanted metal markers. The change in Hounsfield units within smaller lung regions was then used to calculate the percentage air content and regional ventilation.
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399,176 |
Please write an abstract with title: Effects of Transcutaneous Electric Nerve Stimulation on Upper Extremity Proprioceptive Function, and key words: Arm, Humans, Stroke, Stroke Rehabilitation, Transcutaneous Electric Nerve Stimulation, Upper Extremity. Abstract: Electrical stimulation of the vagus nerve has been shown to enhance cortical plasticity and may benefit upper extremity rehabilitation following stroke. As an initial step towards assessing the potential of other craniocervical nerves as neuromodulation targets during rehabilitation, we explored the ability of non-invasive stimulation of cervical spine afferents, paired with a proprioceptive discrimination task, to improve sensory function in neurologically intact human subjects. On each trial, subjects' arms were moved by a robot from a test position, along a random path, to a judgment position located 1-4 cm away. Subjects responded `same' if the judgment position was the same as the test or `different' if it was not. These responses were used to compute proprioceptive sensitivity and bias. Three groups of 20 subjects received transcutaneous electric nerve stimulation to the C3/C4 cervical spine at one of three frequencies (30 Hz, 300 Hz, 3 kHz) for 10 minutes prior to task performance. A fourth group served as a sham. We found a statistically significant interaction between stimulation frequency and displacement distance on proprioceptive sensitivity. In summary, stimulation of cervical spine afferents may enhance arm proprioceptive function, though in unimpaired subjects these gains depend on both stimulation frequency and discrimination distance.
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399,177 |
Please write an abstract with title: D-SHIELD: DISTRIBUTED SPACECRAFT WITH HEURISTIC INTELLIGENCE TO ENABLE LOGISTICAL DECISIONS, and key words: Space vehicles, Instruments, Payloads, Satellite broadcasting, Extraterrestrial measurements, Schedules, NASA. Abstract: D-SHIELD is a suite of scalable software tools that helps schedule payload operations of a large constellation, with multiple payloads per and across spacecraft, such that the collection of observational data and their downlink, constrained by the constellation constraints (orbital mechanics), resources (e.g., power) and subsystems (e.g., attitude control), results in maximum science value for a selected use case. Constellation topology, spacecraft and ground network characteristics can be imported from design tools or existing constellations and can serve as elements of an operations design tool. D-SHIELD will include a science simulator to inform the scheduler of the predictive value of observations or operational decisions. Autonomous, realtime re-scheduling based on past observations needs improved data assimilation methods within the simulator.
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399,178 |
Please write an abstract with title: A space-division time-division multiple access scheme for high throughput provisioning in WLANs, and key words: Throughput, Directive antennas, Directional antennas, Wireless LAN, Space technology, Costs, Robustness, Media Access Protocol, Access protocols, Time division multiple access. Abstract: Directional antennas may dramatically increase the capacity of a wireless LAN by allowing several stations to simultaneously communicate. Since deployment of directive/smart antennas on the customer's terminals is awkward (for technological, cost, robustness, and convenience reasons) it is of interest to deploy advanced antenna solutions only at the access point. When omnidirectional transmissions are used at the mobile stations, the asynchronous nature of the 802.11 MAC handshake structurally limits the possibility to exploit spatial reuse. Significant throughput enhancements can be achieved only at the expense of redesigning (part of) the 802.11 MAC protocol: mainly a form of synchronization is required. This paper addresses this problem and proposes a novel solution, devised to operate in the above scenario. The system operation is based on the joint usage of space division and time division multiple access techniques. A synchronous time-division structure avoids unwanted interference among different antenna coverage regions. Backward compatibility with legacy IEEE 802.11 terminals is also accounted for.
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399,179 |
Please write an abstract with title: Robust and Fast Ship Detection In SAR Images With Complex Backgrounds Based on EfficientDet Model, and key words: Deep learning, Performance evaluation, Visualization, Satellites, Computational modeling, Imaging, Radar polarimetry. Abstract: Synthetic aperture radar (SAR) is one of the most important active imaging systems used in remote sensing. Thanks to SAR and deep learning methods, ship detection can be performed with high performances in recent years. However, using the images of different satellites with changing ship sizes and detecting the ships under complex backgrounds are two challenging tasks that decrease ship detection performance. Since the dimensions of the satellite images are quite high, it is also important to use a fast and lightweight deep learning model. In this paper, we propose the usage of EfficientDet-D0 model to provide a robust and fast solution to the above problems. Experiments were carried out on the Ship-Detection-Dataset that includes nearly 40,000 image patches from Sentinel-1 and Gaofen-3 satellites. EfficientDet-D0 model was compared with Faster R-CNN, RetinaNet, and SSD-MobileNetv2 in terms of 13 different performance metrics, computation times, and visual comparison. The results demonstrate that EfficienDet-D0 model provides the most robust solution to the complex background and multiscale ship size problems.
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399,180 |
Please write an abstract with title: Second-order DOA estimation from digitally modulated signals, and key words: Direction of arrival estimation, Digital modulation, Context, Signal to noise ratio, Linear antenna arrays, AWGN, Apertures, Interference, Array signal processing, Random variables. Abstract: The paper deals with the problem of estimating the direction-of-arrival (DOA) of multiple digitally-modulated sources. This problem arises naturally when studying positioning applications in the context of cellular systems. The formulation of the optimal second-order tracker is found to depend on the transmitted symbols distribution for medium-to-high signal-to-noise ratios (SNR). Simulations show that the common Gaussian assumption yields significant losses for moderate SNRs if the sources impinge from similar angles and/or the aperture is short. In these circumstances the multiuser interference (MUI) plays a prominent role and MUI-resistant techniques are evaluated.
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399,181 |
Please write an abstract with title: Onboard science software enabling future space science and space weather missions, and key words: Space missions, Space vehicles, Magnetosphere, Plasma measurements, Physics, Availability, Data processing, Probes, Magnetic analysis, Magnetic sensors. Abstract: On the path towards an operational Space Weather System are science missions involving as many as 100 spacecraft (Magnetospheric Constellation, DRACO, 2010). Multiple spacecraft are required to measure the macro, meso, and micro scale plasma physics that underlies Geospace phenomena. To be feasible, however, multiple spacecraft missions must be no more costly to operate than single spacecraft missions are today. Furthermore, communication availability places severe constraints on an entire mission architecture and hampers the resolution, coverage, timeliness, and hence, usefulness of spacecraft data. To address some of these constraints, we have been studying the possibility of performing some science data processing functions on board a pathfinding mission in NASA's Solar-Terrestrial Probe Line, Magnetospheric Multi Scale (MMS, 2008). Our multi level approach to developing an onboard science analysis system for potential use onboard the MMS mission will enhance MMS science by improving sensor coverage and by returning to Earth high-resolution data that would otherwise be discarded or not generated. Results of our work using Space Physics data sets from previous missions illustrate our approach.
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399,182 |
Please write an abstract with title: Intelligent Spectrum Occupancy Prediction for Realistic Measurements: GRU based Approach, and key words: Training, Recurrent neural networks, Atmospheric measurements, Wireless networks, Simulation, Urban areas, Sea measurements. Abstract: Cognitive radio (CR) technology has always been a research hotspot in the wireless communications field as it has the potential to significantly improve system capacity at the cost of increased processing time and power consumption, which represent highly critical performance indicators (CPI) towards next-generation wireless networks. In particular, the main problem in the CR-based communication links resides in the prediction of spectrum availability in accordance with strict secondary user (SU) CPIs requirements, which is not achievable through the traditional approaches. In this work, we design a novel hierarchical spectrum prediction model, taking advantage from the recurrent neural network (RNN) with the focus on the gated recurrent unit network (GRU). Specifically, the proposed system architecture offers an accrue prediction on the spectrum availability for the SU considering the prior information of the primary user (PU). The performance of the proposed design is illustrated through extensive simulation results. Specifically, real spectrum measurements gathered from Doha, in Qatar are performed to assess the performance accuracy of the designed architecture. In particular different from the conventional scheme that uses a binary representation of spectrum occupancy (idle is “0” and occupied is “1”), we perform training and prediction over the minimum and maximum recorded measurements.
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399,183 |
Please write an abstract with title: Unidirectional operation of quantum-dot ring lasers, and key words: Ring lasers, Waveguide lasers, Optical waveguides, Semiconductor lasers, Threshold current, Laser stability, Laser beam cutting, Indium gallium arsenide, Quantum dots, Photodiodes. Abstract: First monolithically integrated ridge-waveguide InAs/InGaAs quantum-dot ring lasers are fabricated and characterized. Enhanced by a forward biased S-section waveguide, stable traveling-wave (unidirectional) operation with record suppression ratio of counterpropagating waves approaching 30 dB is demonstrated.
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399,184 |
Please write an abstract with title: South African institute of electrical engineers, and key words: Employment, Maintenance engineering, Layout, Government. Abstract: Employers desirous of obtaining the services of Electrical Engineers, Electrical Tradesmen, and Men or Learners for electrical work, may specify their requirements by means of advertisements in this column, and
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399,185 |
Please write an abstract with title: Determination of the Optimal Sample Size for Measurement in a Coaxial Transmission Line, and key words: Power transmission lines, Permittivity measurement, Wavelength measurement, Permeability measurement, Biomedical measurement, Length measurement, Transmission line measurements. Abstract: The article presents the results of measuring samples of material of various lengths. The electrodynamic parameters of the NiZn based ferrite material based on zinc nickel monoferrite were measured using a coaxial transmission line in the frequency range 8 - 12 GHz. For this group of materials, it is important to know the electrodynamic characteristics. In this regard, it is necessary to study the properties of the materials obtained in different frequency ranges. The manufacture of new materials is a laborious and complex process. It is not always possible to obtain the required amount of the required material for measurement in order to fill the entire transmission line completely. Samples of material of different lengths were made: from 0.06$\lambda$ to 1.08$\lambda$. Based on the obtained dependences, it can be seen that with increasing sample length, the obtained values begin to converge to certain values. It is shown that the length of the material sample in the coaxial transmission line, for more accurate values, should be equal to or greater than the wavelength of the middle of the frequency range.
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399,186 |
Please write an abstract with title: Global Dynamics of MEMS Resonators under Superharmonic Excitation, and key words: Micromechanical devices, Frequency, Resonance, Voltage, Microsensors, Q factor, Electrostatics, Damping, Resonator filters, Power harmonic filters. Abstract: We present a methodology to simulate the transient and steady-state dynamics of microbeams undergoing small or large motions actuated by combined DC and AC loads. We use our methodology to simulate the dynamics of MEMS resonators excited near half their fundamental natural frequencies (superharmonic excitation). We present results showing the effect of varying the DC bias, the damping, and the AC excitation amplitude on the frequency-response curves. Weshow that the dynamic pull-in phenomenon can occur for a superharmonic excitation at an electric load much lower than that predicted based on static analysis.
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399,187 |
Please write an abstract with title: Development of a self learning system for the Shakuhachi using information technology, and key words: Learning systems, Information technology, Instruments, Data mining, Art, Space technology, Frequency, Educational institutions, Oral communication, Visualization. Abstract: In this paper, the development of a self learning system of a Japanese traditional musical instrument "the Shakuhachi" is described. This system encourage the young to learn and acquire the skill of this instrument using information technology.
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399,188 |
Please write an abstract with title: A Knowledge Reasoning Algorithm Based on Network Structure and Representation Learning, and key words: Knowledge engineering, Semantics, Cognition, Adaptation models, Gravity, Computers, Electronic mail. Abstract: Representation learning of knowledge graphs is widely used in the field of artificial intelligence, but it is currently far from comprehensive. All previous translation-based models ignore the multi-relational network structure attributes. Inspired by the law of gravitation, a novel algorithm strTransE proposed by us to integrate the network structure attributes into representation learning. In strTransE, the relation is the gravity between entities. The magnitude of gravity is determined by the weight of the entity. In order to solve the gravitational quantification, we introduced the network structure attribute to represent the weight of the entity. Experimental results on datasets WN18 and FB15K show that, our algorithm achieves significant and continuous improvements in link prediction.
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399,189 |
Please write an abstract with title: Algorithm of task-allocation based on realizing at the lowest cost in multimobile robot system, and key words: Costs, Mobile robots, Material storage, Materials testing, System testing, Robotics and automation, Contracts, Light rail systems, Automatic control, Local area networks. Abstract: The popular and several restricted forms of task allocation issue are NP problems. It searches a feasible matching scheme to realize corresponding object models. This paper adopted Hungarian algorithm to realize task allocation of the robots based on two-dimensional assignment problem aiming at multimobile robot system. It resolves the problem for the robot how to get the tasks and realize them at minimal cost And we designed an emulational test bed based on the multi-robot material flow system of the storages and docks which made distributed programming using LAN. Then we made some emulational experiments on Hungarian algorithm and compared it with the other algorithms.
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399,190 |
Please write an abstract with title: Propagating Magnetic Waves in Epitaxial YIG, and key words: Slabs, Magnetostatic waves, Garnet films, Demagnetization, Magnetic field measurement, Surface waves, Chemical vapor deposition, Thick films, Thickness measurement, Magnetic resonance. Abstract: The theoretical work of Damon and Eshbach leads to the prediction of magnetostatic surface and volume wave propagation in ferromagnetic slabs. Experimental work of Brundle and Freedman with slabs of flux-grown YIG have demonstrated the existence of both these wave classes. In this paper we report the use of YIG films grown by the method of chemical vapor deposition (CVD) on gadolinium gallium garnet to generate such waves. CVD allows films with thickness orders of magnitude smaller than those fabricated from flux-grown material to be obtained. The advantage of such thin films is the uniformity of internal dc field that can be obtained. Figure 1 is a plot of the demagnetizing field in a 1 cm x 0.5 cm YIG slab of varying thickness as calculated from the analysis of Joseph and Schlomann. The external dc field is along the z-axis. The demagnetization variation is shown along this direction from the face to the center of the slab. For a 10 micron thick film, approximately 60 percent of the distance along the z-axis varies by less than 1.0 oe and 95 percent by less than 10 oe. This is about two orders of magnitude less than a slab of 1 mm thickness, which is a typical thickness used by previous investigators. Measurements were made on epitaxial YIG films ranging in thickness from 4 microns to 50 microns. The ferromagnetic resonance linewidth of these epitaxial films has been measured and found to be typically 1.5 oe at X-band, when the bias field is applied perpendicular to the film plane.
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399,191 |
Please write an abstract with title: A 1-Watt, 8-17 GHz FET Power Amplifier, and key words: Power amplifiers, Temperature, High power amplifiers, Power generation, Microwave FETs, Gain, Circuits, Frequency, Regulators, Hermetic seals. Abstract: Design and performance of a compact size 1-Watt, 8-17 GHz, 38 +- 3 dB gain FET amplifier for airborne ECM applications is described. The amplifier with a gain temperature compensation PIN diode stage and a bias regulator is packaged in 1.1 x 0.5 x 3.65 inches hermetically sealed housing.
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399,192 |
Please write an abstract with title: Systolic ROM arrays for implementing RNS FIR filters, and key words: Read only memory, Finite impulse response filter, Very large scale integration, Systolic arrays, Parallel processing, Pipeline processing, Clocks, Fabrication, Nearest neighbor searches, Digital signal processing. Abstract: The Residue Number System (RNS), its concept, computational power, and applications have been investigated in the past [1,6,7]. Most of the studies have resulted in realizations suitable for discrete implementation [2,8]. This paper introduces a linear systolic array architecture for an RNS based FIR filter suitable for VLSI fabrication. The array, which is completely pipelined, consists of modular cells which only communicate to their nearest neighbor. The connected cells constitute a linear systolic array, and the construction of the cell is such that it can be programmed to function in many different DSP tasks. The final result is the construction of a linear systolic ROM that effectively replaces the previously used discrete ROM arrays.
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399,193 |
Please write an abstract with title: Median cascaded canceller using reiterative processing, and key words: Convergence, Covariance matrix, Clutter, Training data, Signal to noise ratio, Jamming, Radar antennas, Robustness, Interference cancellation, Signal processing. Abstract: A novel, robust adaptive processor is introduced, based on reiterative application of the median cascaded canceller (MCC). The MCC, though a highly robust adaptive processor, has a convergence rate that generally is dependent on the effective rank of the interference-plus-noise covariance matrix. The reiterative median cascaded canceller (RMCC) introduced here exhibits the highly desirable combination of 1) convergence-robustness to outliers/targets in adaptive weight training data, like the MCC, and 2) fast convergence performance independent of the interference-plus-noise covariance matrix and at a rate commensurate with the sample matrix inversion (SMI) algorithm, unlike the MCC. Both simulated data as well as measured airborne radar data from the MCARM space-time adaptive processing (STAP) database are used to show performance enhancements. It is concluded that the RMCC adaptive processor is a highly robust replacement for the SMI adaptive processor and all its equivalent implementations.
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399,194 |
Please write an abstract with title: 3D physics-based reconstruction of serially acquired slices, and key words: Deformable models, Image reconstruction, Shape, Biomedical imaging, Image registration, Finite element methods, Integrated circuit modeling, Informatics, Artificial intelligence, Information analysis. Abstract: This paper presents an accurate, computationally efficient, fast and fully-automated algorithm for the alignment of 2D serially acquired sections forming a 3D volume. The method accounts for the main shortcomings of 3D image alignment: corrupted data (cuts and tears), dissimilarities or discontinuities between slices and missing slices. The approach relies on the determination of inter-slice correspondences. The features used for correspondence are extracted by a 2D physics-based deformable model parameterizing the object shape. Correspondence affinities and global constraints render the method efficient and reliable. The method has been evaluated on real images and the experimental results demonstrate its accuracy, as reconstruction errors are smaller than 1 degree in rotation and smaller than 1 pixel in translation.
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399,195 |
Please write an abstract with title: Theory and simulation of vector control based on rotor position orientation of rare-earth permanent magnet motor, and key words: Machine vector control, Rotors, Permanent magnet motors, DC motors, Magnetic flux, Air gaps, Torque, Magnetic analysis, Stator windings, Equations. Abstract: Since the rare-earth permanent materials were invented, all kinds of PM motors and their relevant control methods have been booming. Requirements on high efficiency and flexible control systems are the core of its development. Vector control method based on rotor position orientation of rare-earth PM is presented under this case, and it has so many control qualifies that general DC motor and PM motor cannot reach. This paper gives results and analysis on simulation of a real PM motor by using this control method, and gets conclusion that this control method makes PM motor has the qualifies like that of a general DC motor. A concept of state flow-chart is induced in this paper to judge the feasibility and the integrality of a control system.
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399,196 |
Please write an abstract with title: Guided Beam Waves Between Parallel Concave Reflectors, and key words: Lenses, Optical waveguides, Dielectrics, Phase transformers, Attenuation, Conductors, Optical propagation, Propagation losses, Optical reflection, Gaussian approximation. Abstract: A new guided beam wave transmission system is proposed here, which is composed of two parallel concave reflectors. The principle is a combination of waveguide and beam wave transmission. The shape of the reflector cross section and the corresponding mode functions were obtained. Attenuation due to wall current and limited aperture of the reflectors were calculated. Experiments were made to confirm the modes and the attenuation. One of the remarkable features of this transmission system is its field distribution, which is concentrated into a belt-shaped space between reflectors. Considering this feature, this system seems to be effectively applied to the railways as a medium for obstacle detection and communication.
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399,197 |
Please write an abstract with title: Imperfect channel state information in MIMO-transmission, and key words: Channel state information, MIMO, Land mobile radio, Downlink, Signal processing, Degradation, Transmitting antennas, Singular value decomposition, Covariance matrix, Gaussian noise. Abstract: A specially favorable MIMO-based concept for future mobile radio systems consists in the application of joint detection (JD) in the uplink and joint transmission (JT) in the downlink. By this, all the computationally complex signal processing is shifted to the base station (BS), resulting in low complexity mobile stations (MS). Both JD and JT require channel knowledge at the BS which, if time division duplexing is applied, can be obtained by training signal based channel estimation in the uplink. Unfortunately, channel estimates are never perfect, which leads to performance degradations if these channel estimates instead of perfect channel knowledge are used for JD or JT. A novel analytical analysis of these performance degradations is presented.
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399,198 |
Please write an abstract with title: Utilization of Image Processing Strategy to Detect Crack on Walls, and key words: Meters, Image segmentation, Image resolution, Maintenance engineering, Software, Mathematical model, Matlab. Abstract: The development of cracks on wall structures has drawn researchers' attention to work on an effective way to detect and resolve it. This paper proposes a method of detecting cracks on wall structure through a series of image processing. The series of image processing included: image conversion from Red, Green, Blue (RGB) model to grayscale; image enhancement; image segmentation; and noise removal. The simulation was run using MATLAB software. The results obtained showed the crack on a wall as well as its length in meters.
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399,199 |
Please write an abstract with title: AutoFS: Automated Feature Selection via Diversity-Aware Interactive Reinforcement Learning, and key words: Training, Automation, Navigation, Reinforcement learning, Feature extraction, Space exploration, Decision trees. Abstract: In this paper, we study the problem of balancing effectiveness and efficiency in automated feature selection. Feature selection is to find the optimal feature subset from large-scale feature space, and is a fundamental intelligence for machine learning and predictive analysis. After exploring many feature selection methods, we observe a computational dilemma: 1) traditional feature selection methods (e.g., K-Best, decision tree based ranking, mRMR) are mostly efficient, but difficult to identify the best subset; 2) the emerging reinforced feature selection methods automatically navigate feature space to explore the best subset, but are usually inefficient. Are automation and efficiency always apart from each other? Can we bridge the gap between effectiveness and efficiency under automation? Motivated by such a computational dilemma, this study is to develop a novel feature space navigation method. To that end, we propose an Interactive Reinforced Feature Selection (IRFS) framework that guides agents by not just self-exploration experience, but also diverse external skilled trainers to accelerate learning for feature exploration. Specifically, we formulate the feature selection problem into an interactive reinforcement learning framework. In this framework, we first model two trainers skilled at different searching strategies: (1) KBest based trainer; (2) Decision Tree based trainer. We then develop two strategies: (1) to identify assertive and hesitant agents to diversify agent training, and (2) to enable the two trainers to take the teaching role in different stages to fuse the experience of the trainers and diversify teaching process. Such a hybrid teaching strategy can help agents to learn broader knowledge, and thereafter be more effective. Finally, we present extensive experiments on real-world datasets to demonstrate the improved performances of our method: more efficient than reinforced selection and more effective than classic feature selection.
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