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Data-driven electrical resistance tomography for robotic large-area tactile sensing

Science China(Information Sciences) 2024年第9期67卷 336-337页

作者： Wendong ZHENG Huaping LIU Xiaofeng LIU Fuchun SUN School of Electrical Engineering and Automation Tianjin University of Technology Department of Computer Science and Technology Tsinghua University Key Laboratory of Maritime Intelligent Cyberspace Technology (Hohai University) Ministry of Education

Tactile sensing plays a crucial role in enabling robots to safely interact with objects in dynamic environments [1].Given that potential physical contact can occur at any location during robot interaction, there is a ... 详细信息

关键词： Robot applications

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Widely Separated MIMO Radar Using Matrix Completion

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 180-196页

作者： Sun, Shunqiao Hu, Yunqiao Mishra, Kumar Vijay Petropulu, Athina P. The University of Alabama Department of Electrical and Computer Engineering TuscaloosaAL35487 United States United States DEVCOM Army Research Laboratory AdelphiMD20783 United States The State University of New Jersey Rutgers Department of Electrical and Computer Engineering PiscatawayNJ08854 United States

We present a low-complexity widely separated multiple-input-multiple-output (WS-MIMO) radar that samples the signals at each of its multiple receivers at reduced rates. We process the low-rate samples of all transmit-receive chains at each receiver as data matrices. We demonstrate that each of these matrices is low rank as long as the target moves slowly within a coherent processing interval. We leverage matrix completion (MC) to recover the missing samples of each receiver signal matrix at the common fusion center. Subsequently, we estimate the targets' positions and Doppler velocities via the maximum likelihood method. Our MC-based WS-MIMO (MC-WS-MIMO) approach recovers missing samples and thereafter target parameters at reduced rates without discretization of the parameter space. Our analysis using ambiguity functions shows that antenna geometry affects the performance of MC-WS-MIMO. Numerical experiments demonstrate reasonably accurate target localization at SNR of 20 dB and sampling rate reduction to 20%. © 2023 IEEE.

关键词： MIMO radar

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An 8-bit Quantized Globalization Model for Cat Skin Disease Detection Using Convolutional Neural Networks and TensorFlow Lite

An 8-bit Quantized Globalization Model for Cat Skin Disease ...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Trinanda Putra, Karisma Zidni, Hasan Turrizka, Rifdha Chu, Hsueh-Ting Vu, Dinh-Trung Prayitno Universitas Muhammadiyah Yogyakarta Department of Electrical Engineering Center of Artificial Intelligence and Robotics Studies Bantul Indonesia Institut Teknologi Bandung Department of Electrical Engineering Bandung Indonesia Universitas Muhammadiyah Yogyakarta Department of Electrical Engineering Bantul Indonesia Asia University Department of Computer Science and Information Engineering Taichung Taiwan Semarang State Polytechnic Department of Electrical Engineering Semarang Indonesia

ISBN: (纸本)9798350379839

Skin diseases are health issues that can be experienced by pets and potentially be transmitted from wild animals. However, current prediction systems predominantly rely on complex calculations that necessitate high computational power, making them challenging to deploy on mobile applications. Therefore, this study aims to optimize a skin disease detection system based on convolutional neural networks (CNN) using datasets from both wild and domestic cats. The quantized globalization model is a modified ResNet50 converted with TensorFlow Lite. This 8-bit quantization is necessary to develop a lightweight deep learning model that could operate on low-computational power units, such as smartphone or 8-bit edge computing devices. This study utilized a dataset comprising 343 images, categorized into six classes: five classes of diseases (abscesses, mange, ringworm, skin cancer, dermatitis) and one class for healthy skin. Next, the dataset was augmented to increase data variation and quantity. Subsequently, the dataset was trained on the ResNet-50 model and then converted to TensorFlow Lite with 8-bit integer data type. Finally, the quantized globalization model was validated using a separate 20% of the dataset. The validation results yielded an accuracy score of 0.930, a precision of 0.908, a recall of 0.902, and an F1-score of 0.903. Additionally, there was a significant 74.7% reduction in model size compared to the non-quantized version, demonstrating the efficiency and effectiveness of the quantization process in maintaining performance while substantially decreasing the computational resource requirements. © 2024 IEEE.

关键词： Convolutional neural networks

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Decentralized control in active distribution grids via supervised and reinforcement learning

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Energy and AI 2024年第2期16卷 137-149页

作者： Stavros Karagiannopoulos Petros Aristidou Gabriela Hug Audun Botterud Laboratory for Information and Decision Systems(LIDS) Massachusetts Institute of TechnologyCambridgeUSA EEH-Power Systems Laboratory ETH Zurichhysikstrasse 38092 ZurichSwitzerland Department of Electrical Engineering Computer Engineering&InformaticsCyprus

While moving towards a low-carbon, sustainable electricity system, distribution networks are expected to host a large share of distributed generators, such as photovoltaic units and wind turbines. These inverter-based resources are intermittent, but also controllable, and are expected to amplify the role of distribution networks together with other distributed energy resources, such as storage systems and controllable loads. The available control methods for these resources are typically categorized based on the available communication network into centralized, distributed, and decentralized or local. Standard local schemes are typically inefficient, whereas centralized approaches show implementation and cost concerns. This paper focuses on optimized decentralized control of distributed generators via supervised and reinforcement learning. We present existing state-of-the-art decentralized control schemes based on supervised learning, propose a new reinforcement learning scheme based on deep deterministic policy gradient, and compare the behavior of both decentralized and centralized methods in terms of computational effort, scalability, privacy awareness, ability to consider constraints, and overall optimality. We evaluate the performance of the examined schemes on a benchmark European low voltage test system. The results show that both supervised learning and reinforcement learning schemes effectively mitigate the operational issues faced by the distribution network.

关键词： Supervised learning Reinforcement learning Deep deterministic policy gradient Decentralized control Active distribution systems

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A Review on Cybersecurity Analysis,Attack Detection,and Attack Defense Methods in Cyber-physical Power Systems

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 727-743页

作者： Dajun Du Minggao Zhu Xue Li Minrui Fei Siqi Bu Lei Wu Kang Li Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA School of Electronic and Electrical Engineering University of LeedsLeeds LS29JTUK IEEE

Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and *** timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems(CPPSs).This paper presents a comprehensive review of some of the latest attack detection and defense ***,the vulnerabilities brought by some new information and communication technologies(ICTs)are analyzed,and their impacts on the security of CPPSs are *** malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework,and their features and negative impacts are ***,two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed,and their benefits and drawbacks are ***,two current mainstream attack defense methods including active defense and passive defense methods are comprehensively ***,the trends and challenges in attack detection and defense strategies in CPPSs are provided.

关键词： Cyber-physical power systems security threat attack detection attack defense state estimation machine learning

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EventLFM:event camera integrated Fourier light field microscopy for ultrafast 3D imaging

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Light(Science & Applications) 2024年第7期13卷 1401-1415页

作者： Ruipeng Guo Qianwan Yang Andrew S.Chang Guorong Hu Joseph Greene Christopher V.Gabel Sixian You Lei Tian Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Physiology and Biophysics Boston UniversityBostonMA 02215USA. Neurophotonics Center Boston UniversityBostonMA 02215USA. Research Laboratory of Electronics(RLE)in the Department of Electrical Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA. Department of Biomedical Engineering Boston UniversityBostonMA 02215USA

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological *** scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame *** address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging *** event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS *** further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by *** results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame ***,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving *** believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

关键词： field linking overcome

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Question Selection for Multi-Modal Code Search Synthesis using Probabilistic Version Spaces

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IEEE Transactions on Software engineering 2025年第06期51卷 1724-1744页

作者： Wu, Jiarong Jiang, Yanyan Wei, Lili Xu, Congying Cheung, Shing-Chi Xu, Chang The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong McGill University Department of Electrical and Computer Engineering Montreal Canada Nanjing University State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing China

Searching the occurrences of specific code patterns (code search) is a common task in software engineering, and programming by example (PBE) techniques have been applied to ease customizing code patterns. However, previous PBE tools only synthesize programs meeting the input-output examples, which may not always align with the user intent. To bridge this gap, this paper proposes Excalibur, a multi-modal (example and natural language description) and interactive synthesizer for code search. Excalibur ensures that the generated programs are correct for the provided examples (soundness) and include the user-intended program (bounded completeness). Furthermore, Excalibur helps the user identify the user-intended program through question-answer interaction. To minimize the required interaction efforts, question selection is crucial. To improve question selection for code search, we propose probabilistic version spaces (ProbVS), in which the user-intended program’s probability is high and others are low. ProbVS combines traditional version spaces for compactly representing extensive programs and large language models (on the user-provided natural language description) for adjusting programs’ probabilities to align with users’ intents. Extensive experiments on a benchmark of 44 tasks demonstrated the effectiveness of Excalibur and ProbVS and demystified how ProbVS affects probability distributions and how the configurable parameters affect ProbVS. © 1976-2012 IEEE.

关键词： Normal distribution

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Drowning Recognition for Ocean Surveillance using computer Vision and Drone Control

Drowning Recognition for Ocean Surveillance using Computer V...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Rakotondraibe, Maureen Fang, Tianyang Saniie, Jafar Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

According to WHO's report from 2021, Drowning is the 3rd leading cause of unintentional death worldwide. The use of autonomous drones for drowning recognition can increase the survival rate and help lifeguards and rescuers with their life saving mission. This paper presents a real-time drowning recognition model and algorithm for ocean surveillance that can be implemented on a drone. The presented model has been trained using two different approaches and has 88% accuracy. Compared to the contemporary models of drowning recognition designed for swimming pools, the model presented is better suited for outdoor applications in the ocean. © 2023 IEEE.

关键词： Drones

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Application of Machine Learning and Image Recognition for Driver Attention Monitoring

Application of Machine Learning and Image Recognition for Dr...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Tailor, Manav Ali, Jahangir Yu, Xinrui Yi, Won-Jae Saniie, Jafar Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

This paper presents a real-time prototype system for monitoring the distraction levels of the driver. Due to the nature of high traffic conditions commonly seen nowadays, accidents are highly likely to occur as drivers cannot always recognize their exhaustion levels themselves. We utilize a single low-cost camera facing the driver connected to a single-board computer;a series of frame captures from the camera are fed to a neural network, and a pattern detection algorithm to predict the driver's distraction level is utilized. All training is conducted under personalized training sets to increase accuracy and to match an individual's driving patterns as accurately as possible. This system is designed to serve as a baseline for further system development, and many vital sub-components can be changed regarding input data type and choices of machine learning algorithms. © 2023 IEEE.

关键词： Cameras

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Optimal Design of Aperture Illuminations for Microwave Power Transmission with Annular Collection Areas

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engineering 2023年第11期30卷 63-74页

作者： Xun Li Baoyan Duan Yiqun Zhang Yongxin Guo Shaanxi Key Laboratory of Space Solar Power Station System Xidian UniversityXi’an 710071China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117576Singapore

This work presents an optimal design method of antenna aperture illumination for microwave power transmission with an annular collection *** objective is to maximize the ratio of the power radiated on the annular collection area to the total transmitted *** formulating the aperture amplitude distribution through a summation of a special set of series,the optimal design problem can be reduced to finding the maximum ratio of two real quadratic *** on the theory of matrices,the solution to the formulated optimization problem is to determine the largest characteristic value and its associated characteristic *** meet security requirements,the peak radiation levels outside the receiving area are considered to be extra constraints.A hybrid grey wolf optimizer and Nelder–Mead simplex method is developed to deal with this constrained optimization *** order to demonstrate the effectiveness of the proposed method,numerical experiments on continuous apertures are conducted;then,discrete arrays of isotropic elements are employed to validate the correctness of the optimized ***,patch arrays are adopted to further verify the validity of the proposed method.

关键词： Microwave power transmission Beam collection efficiency Ring-shaped beam Annular collection area Grey wolf optimizer Nelder-Mead simplex method

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