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arXiv 2024年

作者： Chen, Yixuan Chen, Mingzhe Xu, Hao Yang, Zhaohui Wong, Kai-Kit Zhang, Zhaoyang Hangzhou310027 China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Yonsei Frontier Laboratory Yonsei University Seoul03722 Korea Republic of

In this letter, we study the energy efficiency maximization problem for a fluid antenna system (FAS) in near field communications. Specifically, we consider a point-to-point near-field system where the base station (BS) transmitter has multiple fixed-position antennas and the user receives the signals with multiple fluid antennas. Our objective is to jointly optimize the transmit beamforming of the BS and the fluid antenna positions at the user for maximizing the energy efficiency. Our scheme is based on an alternating optimization algorithm that iteratively solves the beamforming and antenna position subproblems. Our simulation results validate the performance improvement of the proposed algorithm and confirm the effectiveness of FAS. Copyright © 2024, The Authors. All rights reserved.

关键词： Beam forming networks

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Performance Optimization for Multicast Mm Wave MIMO Networks with Mobile Users

Performance Optimization for Multicast Mm Wave MIMO Networks...

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IEEE International Conference on Communications Workshops, ICC

作者： Songling Zhang Mingzhe Chen Wenjing Zhang Zhaohui Yang Danpu Liu Zhilong Zhang Kai-Kit Wong Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA Zhejiang Lab Hangzhou China Zhejiang University Hangzhou China Department of Electronic and Electrical Engineering University College London London UK

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

In this paper, the problem of maximizing the sum rate of mobile users in a multi-base station (BS) cooperative millimeter-wave (mmWave) multicast communication system is studied. In the considered model, due to the real-time mobility of users, the users being served by a given BS and beamforming of BSs and users are dynamic. Multiple BSs must cooperate to serve dynamic requests of multiple mobile users. This problem is posed as an optimization framework whose goal is to maximize the sum rate of all mobile users by jointly optimizing the number of users served by all BSs and beamforming matrices of both BSs and users. To solve this non-convex optimization problem, we first introduce a value decomposition based reinforcement learning (VD- RL) algorithm to determine the users to be served by each BS. Then, we use the block diagonalization method to obtain the fully digital transmit beamforming matrices of all BSs as well as the receive beamforming matrices of the users. Finally, a fast optimization algorithm is used to optimize the hybrid beamforming matrices of both BSs and users. Simulation results show that, the proposed algorithm can achieve up to 51 % gain in terms of the sum rate of all mobile users compared to baseline multi-agent algorithms.

关键词： Multicast algorithms Array signal processing Heuristic algorithms Simulation Conferences Multicast communication Real-time systems

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Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI

Quantifying White Matter Hyperintensity and Brain Volumes in...

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IEEE International Symposium on Biomedical Imaging

作者： Pablo Laso Stefano Cerri Annabel Sorby-Adams Jennifer Guo Farrah Mateen Philipp Goebl Jiaming Wu Peirong Liu Hongwei Bran Li Sean I. Young Benjamin Billot Oula Puonti Gordon Sze Sam Payabavash Adam DeHavenon Kevin N. Sheth Matthew S. Rosen John Kirsch Nicola Strisciuglio Jelmer M. Wolterink Arman Eshaghi Frederik Barkhof W. Taylor Kimberly Juan Eugenio Iglesias Massachusetts General Hospital Harvard Medical School USA Electrical Engineering Mathematics and Computer Science University of Twente The Netherlands Pioneer Centre for AI University of Copenhagen Denmark Centre for Medical Image Computing University College London UK Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology USA Danish Research Centre for Magnetic Resonance Denmark Yale School of Medicine USA

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH (ρ=.85) and hippocampal volumes (ρ=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://***/fswiki/WMH-SynthSeg.

关键词： Atrophy Neuroimaging Image segmentation Multiple sclerosis Image resolution Magnetic resonance imaging White matter

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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UAV Swarm-enabled Collaborative Post-disaster Communications in Low Altitude Economy via a Two-stage Optimization Approach

arXiv

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arXiv 2025年

作者： Zheng, Xiaoya Sun, Geng Li, Jiahui Wang, Jiacheng Wu, Qingqing Niyato, Dusit Jamalipour, Abbas College of Computer Science d Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University 639798 Singapore College of Computing and ta Science Nanyang Technological University 639798 Singapore Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electrical and Computer Engiering The University of Sydney SydneyNSW2006 Australia

The low-altitude economy (LAE), as a new economic paradigm, plays an indispensable role in cargo transportation, healthcare, infrastructure inspection, and especially post-disaster communication. Specifically, unmanned aerial vehicles (UAVs), as one of the core technologies of the LAE, can be deployed to provide communication coverage, facilitate data collection, and relay data for trapped users, thereby significantly enhancing the efficiency of post-disaster response efforts. However, conventional UAV self-organizing networks exhibit low reliability in long-range cases due to their limited onboard energy and transmit ability. Therefore, in this paper, we design an efficient and robust UAV-swarm enabled collaborative self-organizing network to facilitate post-disaster communications. Specifically, a ground device transmits data to UAV swarms, which then use collaborative beamforming (CB) technique to form virtual antenna arrays and relay the data to a remote access point (AP) efficiently. Then, we formulate a rescue-oriented post-disaster transmission rate maximization optimization problem (RPTRMOP), aimed at maximizing the transmission rate of the whole network. Given the challenges of solving the formulated RPTRMOP by using traditional algorithms, we propose a two-stage optimization approach to address it. In the first stage, the optimal traffic routing and the theoretical upper bound on the transmission rate of the network are derived. In the second stage, we transform the formulated RPTRMOP into a variant named V-RPTRMOP based on the obtained optimal traffic routing, aimed at rendering the actual transmission rate closely approaches its theoretical upper bound by optimizing the excitation current weight and the placement of each participating UAV via a diffusion model-enabled particle swarm optimization (DM-PSO) algorithm. Simulation results show the effectiveness of the proposed two-stage optimization approach in improving the transmission rate of the construct

关键词： Unmanned aerial vehicles (UAV)

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Statistical 3D Device Simulation of Full Fluctuations of Gate-All-Around Silicon Nanosheet MOSFETs at Sub-3-nm Technology Nodes

Statistical 3D Device Simulation of Full Fluctuations of Gat...

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2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

作者： Kola, Sekhar Reddy Li, Yiming Chen, Chieh-Yang Chuang, Min-Hui National Yang-Ming Chiao Tung University Electrical Engineering and Computer Science International Graduate Program Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Department of Electrical Engineering and Computer Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Parallel and Scientific Computing Laboratory Hsinchu300 Taiwan

ISBN: (纸本)9781665409230

We for the first time study characteristic fluctuation of gate-all-around silicon nanosheet MOSFETs induced by random dopants fluctuation (RDF), interface trap fluctuation (ITF), and work function fluctuation (WKF), and their combinations. The explored devices affected by the WKF and its combination result in sizeable variability. Because of enigmatical interactions among the aforementioned random factors, overestimated variabilities occur if we only consider one random source each time, compared with the statistical 3D device simulation for full RDF, ITF and WKF at the same time. Notably, 10.78% and 103% overestimations are found for the threshold voltage and off-state current fluctuations. © 2022 IEEE.

关键词： Nanosheets

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IoT-Based Car Safety System With Airbag Notification for Emergency Assistance

IoT-Based Car Safety System With Airbag Notification for Eme...

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International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： L. Ramalingam Umamagewaran Jambulingam S. Muthumarilakshmi N. Malathi M. Venkatesh School of Computer Science and Engineering Sriram Engineering CollegePerumalpattu Chennai Tamil Nadu India Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Computer Science and Engineering S.A. Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Madanapalle Institute of Technology & Science Madanapalle Andhra Pradesh India

The development of Internet of Things (IoT) technology has provided the potential for creative uses in many fields, including car safety systems. This research presents an IoT-based automotive safety system that intends to improve the safety of passengers during accidents by providing quick airbag deployment notification and assistance in an emergency. The system uses a network of in-car communication modules, actuators, and sensors. These sensors continually monitor several parameters, including impact intensity, deceleration, and acceleration. The technology senses the force of a collision and activates the airbags, significantly lowering the potential for serious injury. Additionally, the IoT-based system instantly notifies emergency response agencies of the collision, including the vehicle's position, the collision's severity, and if it is occupants. This makes it possible for first responders to respond swiftly and provide the occupants with quick assistance. The technology uses Wi-Fi communication protocols to send data between the car and emergency response services, ensuring a reliable and real-time connection. The collected data is securely transmitted and stored on a cloud-based platform, enabling effective analysis and historical accident tracking. Reduced response times, increased occupant safety, and better accident data collecting for further research and preventive measures are just several advantages of the proposed IoT-based automobile safety system with airbag notification for emergency help. IoT technology in automobile safety systems brings new benefits for enhancing general road safety and emergency response capabilities.

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Detection and Classification of Faults in a Power System with Inverter Penetration Based on a Real-Time Machine Learning Application

Detection and Classification of Faults in a Power System wit...

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Smart Technologies, Communication and Robotics (STCR)

作者： R. Geetha P. Thilagavathi Jose Anand A. Anitha Govindaram Jerril Gilda S. D. Parameswari Department of Computing Technologies SRM Institute of Science and Technology Chennai Tamilnadu Department of Computer Science and Engineering Aarupadai Veedu Institute of Technology Chennai Tamil Nadu India Department of ECE KCG College of Technology Karapakkam Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Sri Muthukumaran Institute of Technology Tamil Nadu India Department of Artificial Intelligence and Machine Learning Jerusalem College of Engineering Pallikaranai Chennai Tamil Nadu India

ISBN: (数字)9798350357530

ISBN: (纸本)9798350357547

This study investigates the implementation of a machine learning (ML) algorithm for the classification and localization of faults in a power system with inverter penetration. The approach utilizes the Clarke transform and cosine distance prediction method to detect fault types and insertion distances. However, the results indicate that the general objective was not met, as the algorithm exhibited significant errors in fault classification, frequently predicting multiple fault types per observation, leading to indecisive fault identification. Additionally, the fault insertion distance detection showed poor performance, achieving only 36% accuracy with a tuned window of =1250. The study concludes that the decision criterion using L2 normal for characteristic eigenvalues and cosine distance for eigenvectors holds potential, but improvements in the regression model are necessary for reliable fault classification and localization in inverter-penetrated power systems.

关键词： Location awareness Fault diagnosis Machine learning algorithms Transforms Machine learning Prediction algorithms Inverters Real-time systems Data models Power system reliability

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Automated Fire Hydrant Monitoring and Maintenance using IoT Data Analytics and Naive Bayes Classifier

Automated Fire Hydrant Monitoring and Maintenance using IoT ...

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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： R. Sarasu V. Nandagopal N V Shibu Suresh Lakshminarayanan T Saju Raj M. Rajmohan Department of Spatial Informatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Electrical and Electronics Engineering School of Engineering Mohan Babu University Tirupathi India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Engineering & Electronics University of Technology and Applied Sciences South Al Batina Oman Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Chennai India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

This paper introduces a new method for managing fire hydrants that uses a monitoring system based on the Internet of Things (IoT) and a Naive Bayes Classifier (NBC) for predictive maintenance. Water pressure, flow rate, and the physical state of fire hydrants are among the essential factors for the proposed system continually collecting data using an IoT sensor network. The system analyzes real-time data using NBC. These predictive capabilities reduce the potential of hydrant breakdowns during emergencies through preventive maintenance potential. It introduces a reliable IoT infrastructure for fire hydrant monitoring, improving the acquired data's granularity and timeliness. NBC provides a powerful instrument for early problem detection, significantly improving maintenance effectiveness. Since the technology is compatible with existing fire department procedures, it can easily integrate into current operational processes. Better public safety, more efficient use of resources, and more dependable fire hydrants are potential outcomes of responsive and proactive data-driven maintenance techniques. The findings improve overall fire safety and operational efficiency, with a 25% decrease in maintenance expenditures and a 40% increase in issue detection accuracy.

关键词： Accuracy Scalability Urban areas Real-time systems Maintenance Naive Bayes methods Internet of Things Stakeholders Predictive maintenance Risk mitigation

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An Authenticated Method for a Secure Changing Password

An Authenticated Method for a Secure Changing Password

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Electronic engineering, Information Technology & Education (EEITE), International Conference in

作者： Mostefa Kara Konstantinos Karampidis Laid Kenioua Manolis Karampidis Muath AlShaikh Giorgos Papadourakis Abdelkader Laouid Scientific and Technology Hub of Sidi Abdellah National Higher School of Mathematics Algiers Algeria Department of Electrical and Computer Engineering Hellenic Mediterranean University Crete Greece LIAP Laboratory El Oued University El Oued Algeria Computer Science Department College of Computing and Informatics Saudi Electronic University Riyadh Kingdom of Saudi Arabia

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

Despite their age, passwords are still widely used more than ever. In many cases, it is the solution that best fits the usage scenario. Researchers are proposing innovative designs and methods to support these scenarios. Many systems, especially sensitive ones, need to change the password. Classic systems rely on changing passwords in two stages, the first i s authentication, which usually consists of two or three rounds, and the second is creating a new password (PW), which also consists of two or three rounds. In this paper, a hidden transmission of a new random PW using the previous one is presented, we talk about an authenticated changing of PW. The verifier g enerates half of the new password and sends it to the prover, the prover authenticates the sent message using the old PW and then returns the authentication proof. After checking it, the verifier creates the second half of the PW. The proposed method combines the authentication and change PW processes into one process consisting of 3 rounds. Therefore, the proposal facilitates the process of automatic periodic change of PW between two entities (user, app, system, etc). Analysis and experiments show that our technique is robust, lightweight, and reduces many potential risks in the field.

关键词： Design methodology Education Authentication Passwords Proposals

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