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检索条件"任意字段=2023 3rd International Conference on Electrical Engineering and Computer Technology, ICEECT 2023"

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Advanced AODV Technique to Improve Communications in a 4G Telecommunication Network and Related Issues 3

Advanced AODV Technique to Improve Communications in a 4G Te...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Saravanan, M.S. Pavan Kumar, P. Saveetha School of Engineering Department of Computer Science and Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamilnadu Chennai India Saveetha School of Engineering Kallam Haranadha Reddy Institute of Technology Tamilnadu Chennai India

ISBN: (纸本)9798350317022

The major purpose of this research study is to improve network performance in 4G groups and people (bandwidth or throughput - the amount of data or bytes that need to transmit in a given length of time), as well as signal strength in hubs (nodes), and to address concerns about handoff and connection loss. The Advanced Ad-hoc On-demand Distance Vector (Adv-AODV) technique is used to improve bandwidth performance and signal loss (dBm) by comparing with the TCP (Transfer Control Protocol). The TCP compared with Adv-AODV based MANET and VANET. Information is transferred and different nodes are established. The algorithm's precision was determined. The sample size for this research study N = 20 with and two group such of TCP and MANET and VANET. The Adv-AODV method achieves higher bandwidth performance and signal strength. The degree of significance in the t-Test analysis is significant with [P = 0.0452], with a significance value of 0.05 and confidence interval of 95% with G-power of 80%. The Adv-AODV routing protocol, as well as MANET and VANET, where nodes (hubs) regularly shift their location inside the network. Unique moving endpoints (hubs) and other interconnected nodes (hubs) engage with one another and exchange important information over a different transmission medium. © 2023 IEEE.

关键词： Adv-AODV algorithm Bandwidth Hubs Mobile Ad-Hoc Network Signal Strength Telecommunication Vehicular Ad-Hoc Network

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Simulation of Message Injection Attacks on Control Area Networks 3

Simulation of Message Injection Attacks on Control Area Netw...

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3rd IEEE Mysore Sub Section international conference, MysuruCon 2023

作者： Vanajakshi, J. Renuka, A. Adesh, N.D. Manipal Institute of Technology Manipal Academy of Higher Education Department of Computer Science and Engineering Karnataka Manipal India Manipal Institute of Technology Manipal Academy of Higher Education Department of Information and Communication Technology Karnataka Manipal India

ISBN: (纸本)9798350340358

The automobile industry is gradually incorporating new technologies into vehicles, making them increasingly connected, autonomous, and data-driven. It makes use of Control Area Network (CAN), a vital communication protocol for networking multiple Electronic Control Units (ECUs) within automobiles. Given its critical role in facilitating communication, CAN is vulnerable to a variety of cyber security threats. The objective of this work is to analyze the security elements of the CAN protocol while simulating attacks on CAN communication data to identify attack vectors targeting the CAN communication protocol and to preserve vehicle security. The proposed method involves analyzing and decoding CAN bus communication messages, which will aid in diagnostics, debugging, and security assessments by revealing insights into vehicle communication and behavior. This technique enables the vehicle to be secured with the required security measures, by investigating attack surfaces and attack vectors. As an effect, existing Python and CAN tools are being utilized to simulate message injection attacks and decode CAN messages in order to identify vulnerabilities, assess risks, and implement appropriate security solutions. The findings show that message injection simulation is carried out using Python and CAN tools, and CAN bus communication messages are captured. This results in disruption of the normal functioning of the vehicle. The captured data is inspected to decode and identify the components of the vehicle. Finally, an overview of best practices for countering cyber-Attacks is provided for the security of in-vehicle network communication. © 2023 IEEE.

关键词： Cybersecurity

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An Empirical Evaluation of Deep Convolutional Neural Networks for Flood Detection in Real-Time 3rd

An Empirical Evaluation of Deep Convolutional Neural Network...

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3rd international conference on Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Kishore, Falguni Nacoulma, Delwende Pierre Wilfried Rai, Nikita Singla, Kanika Department of Computer Science and Engineering Sharda University Greater Noida India

ISBN: (纸本)9789819725076

Satellite imagery has improved rescue and damage assessment in natural disasters, particularly floods. However, previous water detection methods using satellite images have been inefficient. This study examined flood events in Kerala and Maharashtra in 2018 using Synthetic Aperture Radar (SAR) and three deep learning models: LinkNet, SegNet, and U-Net with MobileNetV2 as backbone. Results showed that LinkNet had the highest accuracy at 92.90%, followed by MobileNetV2 at 92.40%, and SegNet at 86.28%. These findings validate the prospective of SAR and deep learning models in accurate flood identification. Further research could advance flood detection and response strategies, supporting disaster management efforts. The study suggests that LinkNet is the most accurate model among those tested. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Satellite imagery

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Research and implementation of abnormal outage behavior prediction and analysis system based on digital twinning technology 3

Research and implementation of abnormal outage behavior pred...

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3rd international conference on Electronics, electrical and Information engineering, ICEEIE 2023

作者： Qiao, Junfeng Peng, Lin Zhou, Aihua Ou, Zhujian Xu, Xiaoyi Zhu, Fuyun State Grid Laboratory of Power cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co.LTD. Jiangsu Nanjing210003 China Nantong Power Supply Company State Grid Jiangsu Electric Power Co. LTD Jiangsu Nanjing210014 China

ISBN: (纸本)9781510671423

Electric power failure is the most common problem in power supply, and it is also one of the biggest problems for customers. From the perspective of power management, blackouts can be divided into fault blackouts and planned blackouts. There are three types of reasons for failure and power failure. One is overload of public transformer and special transformer, iron core grounding and lightning breakdown. The other is drop fuse failure and lack of equivalence for special transformer users. The last is power failure for residential users, line disconnection after meter, short circuit, leakage switch failure, etc. For planned outage, it is mainly caused by planned maintenance and repair according to the operation cycle of power line equipment. Among them, planned power outages are controllable, and the power management unit notifies the power customers in advance. However, the failure of power outages usually causes certain damage to the power customers, so it has certain harmfulness. In view of the above problems, this paper uses digital twinning technology to analyze the causes of failure and outage, and uses digital technology to carry out failure and outage prediction to reduce the losses caused by failure and outage. © 2023 SPIE.

关键词： Forecasting

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Combining Autoencoder and Category-Based Low-Rank Domain Adaptation Method for Multi-Site ASD Identification 3

Combining Autoencoder and Category-Based Low-Rank Domain Ada...

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3rd international conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Yu, Lei Wang, Li Cheng, Ming Xue, Minhao Wang, Lei School of Electrical Engineering and Control Science Nanjing Tech University Jiangsu Nanjing211816 China

ISBN: (纸本)9781510667563

With the development of deep learning in diagnosing autism spectrum disorder (ASD), multi-site resting-state functional magnetic resonance imaging (rs-fMRI) images have made excellent progress. However, there is a heterogeneous problem between the multi-site data caused by inconsistent data distribution. To address this problem, we propose a combining autoencoder and category-based low-rank domain adaptation (AECLR) method for multi-site ASD identification. The main idea is to extract non-linear features and alignment the distribution of these features. In the first stage, the unsupervised autoencoder is used to obtain the non-linear representation. In the second stage, the common structure between all domains was mined by the category-based low-rank constraints, which transform all source domain data and the target domain data into the common latent space and then the source domain data could be linearly represented by the target domain data. As a result, the ablation experiments of the AECLR method achieve independent performance and the AECLR method also obtain a satisfactory classification when compared with the state-of-the-art method. © 2023 SPIE.

关键词： Magnetic resonance imaging

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Beyond Reality: A Synthesis Analysis of Metaverse-Based Immersive Learning Experience 3

Beyond Reality: A Synthesis Analysis of Metaverse-Based Imme...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Alhafis Bin Hashim, Mohd Ekram Mustafa, Wan Azani Nasir, Suraya Md Albakry, Nur Safinas Binti Kamaruddin, Nor Hazlen Puadi, Mohd Farizal Habelalmateen, Mohammed I. Almoussawi, Zainab Abed Sustainability and Creative Industry Sultan Idris Educational University Faculty of Art Multimedia Creative Department Malaysia UniCITI Alam Campus Centre of Excellence Universiti Malaysia Perlis Faculty of Electrical Engineering Technology Sungai Chuchuh Perlis Padang Besar Malaysia The Islamic University Faculty of Engineering Najaf Iraq College of Islamic Science Ahl Al Bayt University Karbala Iraq

ISBN: (纸本)9798350317022

The incorporation of metaverse-based immersive learning experiences marks a paradigm leap beyond traditional pedagogical bounds in the ever-changing environment of education technology. This synthesis review digs into the world of metaverse and education, delving into the multiple elements and consequences of immersive learning in the metaverse. The review conducts a systematic analysis of a large body of literature on the design, implementation, and effects of metaverse-based educational initiatives. The synthesis illustrates the various applications of immersive technologies in promoting enhanced learning settings, transcending physical classroom boundaries. This review exposes the potential of metaverse-based immersive learning experiences to engage learners, promote creativity, and facilitate collaborative knowledge production by combining findings from numerous studies. Furthermore, the synthesis explores critically the obstacles and considerations involved in the adoption of these technologies, addressing themes such as accessibility, ethics, and pedagogical efficacy. This review presents a sophisticated perspective of the metaverse's role in determining the future of education as we venture beyond the confines of reality. It provides guidance for educators, academics, and policymakers interested in harnessing the transformative power of immersive learning experiences in the metaverse. The synthesis not only consolidates existing information, but it also prepares the path for future research projects aimed at maximizing the educational potential of this developing technological frontier. © 2023 IEEE.

关键词： Immersive Learning experience Metaverse New Media

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Research on axial stress monitoring of cables based on BOTDA 3

Research on axial stress monitoring of cables based on BOTDA

引用

3rd international conference on Mechanical, Electronics, and electrical and Automation Control, METMS 2023

作者： Xue, Naichuan Yao, Wei Liu, Yunhong Sun, Changhai School of Electrical Engineering Dalian University of Technology Liaoning Dalian116081 China State Grid Shanxi Electric Power Co Ltd. Taiyuan Power Supply Company Shanxi Taiyuan030000 China

ISBN: (纸本)9781510666689

This paper introduces the basic principle of measuring the axial stress of optical fiber based on Brillouin time domain analysis technology (BOTDA), and applies distributed optical fiber sensing to the axial stress monitoring of power cables. We build a cable axial stress monitoring system based on BOTDA, and in view of the problem that the built-in optical fiber structure of the existing optoelectronic hybrid cable could not be effectively used for stress monitoring, we propose a new type of intelligent sensing cable. The built-in optical fiber adopts a nylon tight-packed structure, so that the force on the optical fiber can effectively represent the axial stress of the cable. We build the Brillouin frequency shift test platform to study the influence of different bending radii on the Brillouin scattering frequency shift of optical fibers when the cable was bent. The test results show that the built-in optical fiber of the cable adopts a nylon tight-packed structure, and combined with BOTDA technology, the stress distribution of each position of the cable can be effectively monitored by analyzing the Brillouin scattering frequency shift, which can reflect the axial stress of different bending radii of the cable. It provides strong support for establishing a cable stress database and building a comprehensive perception platform for power cables. © 2023 SPIE. All rights reserved.

关键词： Time domain analysis

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Research on Motion Control Algorithms for Asymmetric Robot Structures 3rd

Research on Motion Control Algorithms for Asymmetric Robot S...

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3rd international conference on Information Control, electrical engineering, and Rail Transit, ICEERT 2023

作者： Yang, Qi Liang, Xunyang Wang, Yilu Wang, Shida Huang, Xingzhuo School of Mechanical Engineering Shenyang Ligong University Shenyang110159 China

ISBN: (纸本)9789819746194

In order to meet the diversified storage requirements and improve the work safety and warehouse management level, a design of warehouse robot based on STM32 single chip computer is proposed. According to the functional requirements of the experimental environment, the corresponding mechanical structure is designed and the control hardware is selected. The sinusoidal speed regulation is used to control the speed of the robot in the process of starting and braking and to prevent the robot from producing too large shock due to the speed change too fast. At the same time, in order to solve the speed instability and deviation caused by unbalanced center of gravity and uneven distribution of ground friction coefficient, the CASADE PID algorithm of Angle ring and speed ring in series is used to control the motion. The experiment shows that the traveling speed of the robot can be flexibly set according to the actual demand, and the steady-state error between the actual speed and the preset speed is no more than 3%, and the real-time attitude adjustment can be carried out when the speed is stable, and the automatic correction can be made back to the preset trajectory when the deviation occurs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Three term control systems

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Gait recognition based on GaitPart and multimodal feature fusion 3

Gait recognition based on GaitPart and multimodal feature fu...

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3rd international conference on Control and Intelligent Robotics, ICCIR 2023

作者： Chen, Pengpeng Hu, Chuanping School of Electrical Information Zhengzhou University Zhengzhou 450001 China School of Cyber Science and Engineering Zhengzhou University Zhengzhou 450002 China

ISBN: (纸本)9781510671867

A new multimodal feature fusion representation method is proposed to address the problem of low accuracy in gait recognition under single-modal conditions. The contour features and skeletal features are obtained using background subtraction and human pose estimator, respectively. The two types of features are fused in an embedded manner to generate contour-skeleton feature images. The resulting skeleton-contour sequences are horizontally segmented and processed individually. Finally, the extracted feature vectors are mapped to a metric space using fully connected layers. Furthermore, in the existing GaitPart algorithm, the triplet loss function is employed for distance metric learning during network training. However, it suffers from slow convergence and unstable performance. To enhance the discriminative ability of the network, we propose a joint loss function that combines the triplet loss and softmax loss during the training process. Finally, extensive experiments are conducted on the CASIA-B dataset to evaluate the effectiveness of our proposed approach. © 2023 SPIE.

关键词： Gait analysis

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Dynamic Object Tracking Based on Triplet Relationship Guided Sampling Consensus Algorithm 3

Dynamic Object Tracking Based on Triplet Relationship Guided...

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2023 3rd international conference on computer, Remote Sensing and Aerospace, CRSA 2023

作者： Zhou, Jiaxing Yao, Youxin Chen, Xiang Guo, Hanlin Huang, Qixuan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361000 China Shanghai Satellite Engineering Institute Shanghai201109 China

Compared with the traditional methods based on the prediction of moving object trajectory, the method based on image registration has the advantage of not relying on the object motion equation to track the object. However, in the case of a large number of outliers, the image matching method has the defects of inadequate filtering of outliers or erroneous filtering of incomers due to the limitations of spatial constraints of feature matching pairs, which will make the tracking of flying objects inaccurate or impossible. During the flight, the object may be in a similar background and the image shooting angle is different, which makes the object imaging angle change, resulting in a large number of outlier interference. Because of the above situation, this paper adopted an improved TRESAC algorithm based on RANSAC, which used a feature matching method based on a triplet relationship to effectively filter outliers and then adopted an initial data subset selection strategy to increase its robustness. Experimental results show that the TRESAC algorithm can filter outliers quickly and accurately, and the object is still tracked effectively under the condition of similar background and pose change. © Published under licence by IOP Publishing Ltd.

关键词： Statistics

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