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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Mamatha, G.N. More, Priyanka Amudha, A. Singh, Jagtej Niranjani, B. Aggarwal, Diksha Karnataka Bangalore India Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore641021 India Centre for Interdisciplinary Research for Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Business Administration Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Quantum University Research Center Quantum University India

ISBN: (纸本)9798350370249

This paper provides an electricity and postpone optimization of routing protocols for Vehicular advert-hoc Networks. It specializes in the improvement of power performance to overcome the scalability demanding situations inherent in implementing VANETs. The authors examine four existing routing protocols, namely AODV, DSR, OLSR and ZRP, and suggest a dual-level optimization method for stepped forward power performance. The proposed technique considers both the electricity consumption of routing protocols and their response time in opposition to packet shipping delay. On one stage, a power consumption threshold is employed to become aware of the most desirable routing nodes and discard ineffectual information packets. On any other degree, the paper proposes a collaborative based technique for lightweight packet forwarding via most effective forwarding the nearby data packets of the same vacation spot. The simulation consequences display that the proposed approach effects in superior power efficiency and reduced response time for packet shipping compared to present protocols, making the proposed approach green and effective in VANETs. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Discharge image reconstruction and frequency domain analysis based on event data

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High Voltage 2024年第6期9卷 1195-1201页

作者： Quan Yuan Lei Deng Hao Guo Qishen Lyu Xin Zhang Jibin Wu Yu Deng Hongyang Zhou Xilin Wang Zhidong Jia Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenGuangdongChina Department of Precision Instrument Center for Brain Inspired Computing ResearchTsinghua UniversityBeijingChina College of Information and Computer Taiyuan University of TechnologyTaiyuanChina Shenzhen Power Supply Corporation China Southern Power Grid CorporationShenzhenChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina China Electric Power Research Institute BeijingChina School of Electrical Engineering and Automation Xiamen University of TechnologyXiamenChina

Optical image method has been the earliest and most used direct method for observing gas ***,research on gas discharge monitoring based on visible light mainly relies on high-speed cameras,but the large size,significant data storage requirements,and susceptibility to interference from complex backgrounds and lighting conditions limit their further *** vision sensing(DVS)technology is a neuromorphic sensing technology that asynchronously measures the luminance changes at each *** offers advantages such as a large dynamic range(>120 dB),high temporal resolution(up to 1µs),and small data volume(MB level).In this study,dynamic vision sensing technology was employed to monitor both 30 mm short-gaps and 1080 mm long-gaps discharge processes *** study developed the CountImage encoding method for event data and conducted image reconstruction,time-domain analysis,and frequency-domain charac-teristic analysis based on the event *** results show that the event-reconstructed images are highly consistent with the high-speed camera images,and the arc develop-ment process and its path can also be clearly ***,this study discovered a correlation between the electrical characteristics and event information during the discharge *** the time domain,the duration of the maximum DVS event count closely matches the duration during which the voltage drops to zero during *** the frequency domain,the Pearson correlation coefficient between the event stream spectrum and the voltage signal spectrum is greater than *** the maximum number of brightening events(ONmax)and the maximum number of darkening events(OFFmax)are positively correlated with the voltage applied between the *** study demonstrates that,compared to the GB/s data rate of high-speed cameras,this approach can record the discharge process and accurately reconstruct the discharge process,arc morphology,and discharge path at M

关键词： image analysis holds

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Detection of Military Vehicles based on Edge Devices from Unmanned Aerial Vehicle 2

Detection of Military Vehicles based on Edge Devices from Un...

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2nd International Conference on Distributed computing and Optimization Techniques, ICDCOT 2024

作者： Umasankar, L. Anitha, D. Trisheela, S. Al-Jawahry, Hassan M. Borra, Subba Reddy S.A.Engineering College Electrical and Electronics Engineering Tiruvallur Poonamallee India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Tamilnadu Kattankulathur India Nitte Meenakshi Institute of Technology Dept of Cse Bengaluru India The Islamic University Najaf Iraq Computer Science and Engineering Maisammaguda Hyderabad India

ISBN: (纸本)9798350382952

The recent technology in surveillance for military vehicle parts forms the basis of intelligence warfare through information realized through monitoring and tracking operations in complex situations. Therefore, the process of identifying and classifying vehicles by an aerial vehicle installed with a resource-limited device and an intelligent object detection algorithm significantly assists security agencies. It is possible to make use of this vehicle either manually or autonomously. To overcome these issues, edge device based military vehicle detection from Unmanned Aerial Vehicle (UAV) is proposed. At present, no publicly available dataset exists that includes different military classes. Therefore, the proposed approach use a dataset consisting of 6772 images labeled as Tanks, Military Trucks, Helicopters, Aircraft, Civilian Cars and Civilian Aircraft. This data set is used to train deep learning models such as Quantized SSD Mobilenetv2 and Tiny Yolo v5 that are then compared with resource limited edge devices. The results reveal that Tiny Yolo v5 outperforms other models, showing high efficiency and suitability for edge-based devices due to its lightweight design. © 2024 IEEE.

关键词： Military vehicles

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Multiuser Resource Allocation for Semantic-Relay-Aided Text Transmissions

Multiuser Resource Allocation for Semantic-Relay-Aided Text ...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Hu, Zeyang Liu, Tianyu You, Changsheng Yang, Zhaohui Chen, Mingzhe Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China College of Information Science and Electronic Engineering ZheJiang University Hangzhou China Institute for Data Science and Computing University of Miami Department of Electrical and Computer Engineering Coral GablesFL33146 United States

ISBN: (纸本)9798350370218

Semantic communication (SemCom) is an emerging technology that extracts useful meaning from data and sends only relevant semantic information. Thus, it has the great potential to improve the spectrum efficiency of conventional wireless systems with bit transmissions, especially in low signal-to-noise ratio (SNR) and small bandwidth regions. However, the existing works have mostly overlooked the constraints of mobile devices, which may not have sufficient capabilities to implement resource-demanding semantic encoder/decoder based on deep learning. To address this issue, we propose in this paper a new semantic relay (SemRelay), which is equipped with a semantic receiver to assist multiuser text transmissions. Specifically, the SemRelay decodes semantic information from a base station and forwards it to the users using conventional bit transmission, hence effectively improving text transmission efficiency. To study the multiuser resource allocation, we formulate an optimization problem to maximize the multiuser weighted sum-rate by jointly designing the SemRelay transmit power allocation and system bandwidth allocation. Although this problem is non-convex and hence challenging to solve, we propose an efficient algorithm to obtain its high-quality suboptimal solution by using the block coordinate descent method. Last, numerical results show the effectiveness of the proposed algorithm as well as superior performance of the proposed SemRelay over the conventional decode-and-forward (DF) relay, especially in small bandwidth region. © 2023 IEEE.

关键词： joint power and bandwidth allocation Semantic communication semantic relay

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An Explainable Deep Learning Approach for EEG- Induced Motor Imagery Classification 20

An Explainable Deep Learning Approach for EEG- Induced Motor...

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20th IEEE India Council International Conference, INDICON 2023

作者： Ganguly, Biswarup Ghosh, Ahona Dey, Sharmistha Sarkar, Indranil Saha, Sriparna Meghnad Saha Institute of Technology Electrical Engineering Department Kolkata India Maulana Abul Kalam Azad University of Technology Department of Computer Science & Engineering West Bengal India University Institute of Computing Chandigarh University Punjab Gharuan India Guru Nanak Institute of Technology Department of Computer Application Kolkata India

ISBN: (纸本)9798350305593

Movement interpretation from the motor imagery (MI) signal of electroencephalogram (EEG) is an emerging field that can potentially upgrade the quality of life of individuals with motor impairments. In this manuscript, an explainable deep learning (x-DL) approach has been proposed to identify four class MI form EEG signals. The acquired EEG signals are preprocessed and then converted to time-frequency (TF) spectra for extracting the frequency content of the MI signals. The obtained TF images are then fed to a deep learning (DL) framework employing residual convolutional neural network for proper classification. The classification score, obtained from the network, has been propagated through the layers of the DL framework up to the input layer for obtaining layer wise relevance maps. These relevance maps signify the explainability of the proposed network, in terms of visual results. Comparative analysis reveals the effectiveness of the proposed x-DL module using a benchmark dataset. The obtained results and the utilization of signals from only two EEG channels demonstrate the possibility of employing the suggested strategy for developing a cost-effective brain-computer interfacing architecture applicable in real-time healthcare applications. © 2023 IEEE.

关键词： Convolutional neural network electroencephalogram explainable deep learning motor imagery wavelet transform

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The effects of point defect type, location, and density on the Schottky barrier height of Au/MoS2 heterojunction: a first-principles study (vol 12, 18001, 2022)

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SCIENTIFIC REPORTS 2022年第1期12卷 1-15页

作者： Sorkin, Viacheslav Zhou, Hangbo Yu, Zhi Gen Ang, Kah-Wee Zhang, Yong-Wei Institute of High-Performance Computing A*STAR 1 Fusionopolis Way Singapore 138632 Singapore Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Institute of Materials Research and Engineering A*STAR 2 Fusionopolis Way Singapore 138634 Singapore

Using DFT calculations, we investigate the effects of the type, location, and density of point defects in monolayer MoS2on electronic structures and Schottky barrier heights (SBH) of Au/MoS2heterojunction. Three types of point defects in monolayer MoS2, that is, S monovacancy, S divacancy and MoS(Mo substitution at S site) antisite defects, are considered. The following findings are revealed: (1) The SBH for the monolayer MoS2with these defects is universally higher than that for its defect-free counterpart. (2) S divacancy and MoSantisite defects increase the SBH to a larger extent than S monovacancy. (3) A defect located in the inner sublayer of MoS2, which is adjacent to Au substrate, increases the SBH to a larger extent than that in the outer sublayer of MoS2. (4) An increase in defect density increases the SBH. These findings indicate a large variation of SBH with the defect type, location, and concentration. We also compare our results with previously experimentally measured SBH for Au/MoS2contact and postulate possible reasons for the large differences among existing experimental measurements and between experimental measurements and theoretical predictions. The findings and insights revealed here may provide practical guidelines for modulation and optimization of SBH in Au/MoS2and similar heterojunctions via defect engineering.

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Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge computing Networks

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IEEE Transactions on Mobile computing 2025年第7期24卷 5681-5698页

作者： Tang, Jian Li, Xiuhua Li, Hui Li, Penghua Wang, Xiaofei Leung, Victor C. M. Chongqing University School of Big Data & Software Engineering Chongqing400000 China Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Tianjin University College of Intelligence and Computing Tianjin300072 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

Federated Learning (FL) has significant potential to protect data privacy and mitigate network burden in mobile edge computing (MEC) networks. However, due to the system and data heterogeneity of mobile clients (MCs), client selection and bandwidth allocation is key for achieving cost-efficient FL in MEC networks with limited bandwidth. To address these challenges, we investigate the issue of joint client selection and bandwidth allocation for reducing the cost (i.e., latency and energy consumption) of FL training. We formulate the problem and decompose it into a holistic subproblem to reduce the number of rounds and a partial subproblem to reduce the costs of FL each round. We propose a joint class-balanced client selection and bandwidth allocation (CBCSBA) framework to address the whole problem. Specifically, for the holistic subproblem, CBCSBA combines MCs into groups, each having data distribution as close as possible to class-balanced distribution;For the partial subproblem, CBCSBA reduces costs by exploratively selecting a group and sequentially optimizing the latency and energy consumption of MCs within the group. Experimental results show that CBCSBA outperforms the baseline frameworks in reducing latency by 28.2% and energy consumption by 25.3% on average in the considered four datasets. © 2002-2012 IEEE.

关键词： Federated learning

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Automatic Detection and Measurement Method for Road Block on UGVs 23

Automatic Detection and Measurement Method for Road Block on...

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2023 Research in Adaptive and Convergent Systems, RACS 2023

作者： Shin, Jiwoo Kim, Seoyeon Kim, Taesik Jung, Jinman Department of Electrical and Computer Engineering Inha University Incheon Korea Republic of Institute of Human Centered Computing Inha University Incheon Korea Republic of Department of Civil and Environmental Engineering Hongik University Seoul Korea Republic of Department of Computer Engineering Inha University Incheon Korea Republic of

ISBN: (纸本)9798400702280

Deep excavation in urban areas has the potential to cause significant economic and human losses by damaging adjacent structures. Prior to such damage, deformation may occur in the sidewalk or road nearest to the construction site. Accurate measurement of deformation levels is crucial for assessing stability in such scenarios, but existing techniques face challenges in achieving precise measurements. In this paper, we propose a novel approach for detecting and measuring block joints using laser sensor data. Our method consists of two key steps: detection and measurement based on laser sensor data. In the detection stage, the proposed method constructs dynamic frames from line data from laser sensor that contain depth information and utilizes these frames to detect block objects. Furthermore, in the measurement stage, it employs a clustering based measurement, called CPLF (Clustered Piecewise Linear Fitting). We built its prototype implementation on an Unmanned Ground Vehicle (UGV) equipped with a laser sensor and performed measurements to quantify its run-time performance. The implementation results show that our proposed approach yields more accurate results within a 1 mm of error.1 © 2023 Owner/Author.

关键词： Object detection

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Agricultural Water Conservation through AI-Enhanced Solar IoT Networks 3

Agricultural Water Conservation through AI-Enhanced Solar Io...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Maniraj, S.P. Monisha, J. Amutha, R. Kavitha, R. Shriidhar, P.J. Srinivasan, C. Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Kattankulathur Tamilnadu Chennai India Tamil Nadu Chennai India Ultra College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vinayaka Missions Kirupananda Variyar Engineering College Department of Computer Science and Engineering Tamil Nadu Salem India Saveetha Universityi Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509675

With the increasing water shortage and climatic uncertainty, creative strategies for effective water management in agriculture are necessary. This research investigates the integration of Artificial Intelligence (AI), particularly Artificial Neural Networks (ANN), with solar-powered Internet of Things (IoT) networks to enhance water utilization in agricultural activities. The proposed system facilitates accurate irrigation scheduling using real-time data from soil moisture sensors, meteorological stations, and crop health monitoring devices. The ANN model analyses this data to predict ideal irrigation schedules and volumes, minimizing water waste while improving crop yields. The solar-powered IoT framework provides sustainability and reduces dependence on traditional energy sources. Field trials indicate that the AI-enhanced system may promote water saving by as much as 30% relative to traditional irrigation techniques. Moreover, using AI enables adaptive learning, enabling the system to enhance its irrigation tactics using historical and real-time data. This novel method conserves water resources and fosters sustainable agriculture practices, coinciding with global initiatives to address water shortages and assure food security. The findings underscore the potential of technology-based solutions to revolutionize agricultural water management for a sustainable future. © 2025 IEEE.

关键词： Smart agriculture

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Independent control of Spatial Wavefront of Beam Scanning Antenna with Transmissive Phase Gradient Metasurface

Independent control of Spatial Wavefront of Beam Scanning An...

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International Symposium on Antennas and Propagation (ISAP)

作者： Ravi Anand Amine Mezghani Anirban Sarkar School of Computing and Electrical Engineering Indian Institute of Technology Mandi Mandi India Department of Electrical and Computer Engineering University of Manitoba Winnipeg Canada

ISBN: (数字)9798350364774

ISBN: (纸本)9798350364781

To control and shape the spatial wavefront of reconfigurable leaky-wave antenna (LWA) by integrating a single layered transmissive phase gradient metasurface (TPGMS) is demonstrated. The amplitude and phase of transmission is controlled with single layer sub-wavelength design of TPGMS, where phase modulation is achieved through the geometrical manipulation of the unitcell structure. The proposed unique design of metasurface has advantage of transmission phase tunability and stability for polarization insensitive waves at different angle of incidence. The numerical simulation of the proposed integrated model shows the full control of the scanning beam from 22° to 48° at 5GHz for sub-6GHz applications.

关键词： Wireless communication Shape Phase modulation Transmitting antennas Metasurfaces Leaky wave antennas Stability analysis Numerical models Numerical stability Periodic structures

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