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Coverage Enhancement technology of Wireless Sensor Networks for Power Transmission Scenes 3

Coverage Enhancement Technology of Wireless Sensor Networks ...

引用

3rd international conference on Intelligent computing, Communication and convergence, ICI3C 2023

作者： Zhou, Hongyu Lv, Jun Chen, Hongzhong Dai, Feng Wu, Qiang Chen, Xiao State Grid Corporation of China Beijing100031 China State Grid Jiangsu Electric Power Co. Ltd Nanjing210018 China

ISBN: (纸本)9798350343922

In this article, firstly, the demand of WSN (Wireless Sensor Network) for power transmission scenarios is analyzed, then the principle and classification of coverage enhancement technology are introduced, and finally the selection and design of coverage enhancement technology for power transmission scenarios are discussed in detail. Aiming at the demand of power transmission scene, this article adopts high-power and anti-interference wireless communication module to improve the transmission distance and anti-interference ability of the sensor. At the same time, a routing algorithm based on multi-hop communication is designed, and intermediate nodes are used for data forwarding to expand the coverage of the network. The node deployment optimization strategy is implemented, and the sensor deployment position is reasonably selected according to the layout and environmental characteristics of power transmission facilities to maximize the network coverage. Finally, the simulation experiment is carried out, and the results show that the network coverage has been significantly improved after adopting the node deployment optimization strategy. At the same time, this method not only improves the communication quality, but also increases the data transmission rate. This shows the effectiveness of this method in optimizing network performance. The research and application of this technology will help to improve the performance of WSN in power transmission scenarios and meet its real-time monitoring requirements for equipment status and environmental parameters. © 2023 IEEE.

关键词： Inductive power transmission

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Evaluating Teachers' Performance through Aspect-Based Sentiment Analysis 9

Evaluating Teachers' Performance through Aspect-Based Sentim...

引用

9th IEEE international conference for convergence in technology, I2CT 2024

作者： Bhowmik, Abhijit Noor, Noorhuzaimi Mohd Mazid-Ul-Haque, Md. Miah, Md Saef Ullah Karmaker, Debajyoti Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan Malaysia American International Univeristy-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798350394474

This research demonstrates a novel approach for evaluating teacher performance by conducting aspect-based sentiment analysis (ABSA) on student feedback. A large dataset of over 2 million student comments about teachers is analyzed using cutting-edge natural language processing and customized deep learning techniques. The methodology involves identifying positive, negative and neutral aspects of teaching using a BiLSTM model. Rigorous preprocessing, domain adaptation, and performance metrics ensure a robust and objective evaluation. The granular, nuanced insights obtained through this aspect-level sentiment analysis enable educational institutions to provide targeted and unbiased feedback to teachers on their strengths and areas needing improvement. Moreover, this work lays the foundation for detecting potentially fraudulent reviews in academic settings - a crucial capability for safeguarding assessment integrity. The detailed aspect-based analysis methodology presented here significantly advances subjective and holistic evaluation practices. This research has far-reaching implications for enriching teacher development while upholding the credibility of performance assessments through sentiment analysis innovations. © 2024 IEEE.

关键词： Sentiment analysis

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Research on Foreign Object Detection of Transmission Line Based on Improved YoloV5

Research on Foreign Object Detection of Transmission Line Ba...

引用

2024 international conference on Intelligent computing and Robotics, ICICR 2024

作者： Liu, Chao Yao, Chen Wen, Hongyuan College of Intelligent Manufacturing Taizhou Institute of Science and Technology Nanjing University of Science and Technology Taizhou China Yuguo Station Upward Operation Workshop China Railway Shenyang Bureau Group Co. Ltd. Shenyang China

ISBN: (纸本)9798350372274

As the transmission power network is expanding, The traditional manual fault detection approach reveals a relatively low level of efficiency and is considerably influenced by human factors. In this article, an outstanding and innovative foreign object detection approach for transmission lines based on the enhanced YOLOv5 is presented. The lightweight network unit C2F is utilized to substitute the C3 module for compressing the size of the network model. Via the introduction of the Biformer module, with the aim of attaining a substantial improvement in the feature extraction capacity of the model. Employ the Focal loss function to substitute the cross-entropy loss function adopted in the original model, thereby reducing the impact of the sample imbalance problem on the model training and simultaneously enhancing the convergence rate of the model. The improved model parameters are reduced by 25.47 %, The number of floating-point operations has decreased by 30.16%, the number of frames transmitted per second has been enhanced by 17.6%. The mAP value has got a boost of2.81%. ©2024 IEEE.

关键词： Power transmission lines

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Post TV Trend: The Proliferation Of Digital technology 9

Post TV Trend: The Proliferation Of Digital Technology

引用

9th international conference on Advanced computing and Communication Systems, ICACCS 2023

作者： Rani, Madhu Singh, Satendar Tomar, Shagun Gupta, Manisha Sharda University Sharda School of Business Studies Greater Noida India

ISBN: (纸本)9798350397376

Media convergence"refers to the interweaving of computers, IT (Information technology), media content, media companies, and communication networks. This pattern has grown with online commercial venues, networked firms, and consumer-facing services. It is also caused by digital media activities, goods, and services. This article focuses on the media and entertainment sectors and discusses the effects of digitalization on new media. Using secondary sources, this investigation examines how shifting media ecosystems have affected viewing habits and content preferences. Insight into how digital technology is influencing the media and entertainment industries may be found in the rapidly expanding over-the-top (OTT) video market. OTT means "over the internet". Recent OTT events are broken down and analyzed in connection to the new media's political and economic environment. © 2023 IEEE.

关键词： Digital storage

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Enhancing Speech Emotion Recognition Through Knowledge Distillation 15

Enhancing Speech Emotion Recognition Through Knowledge Disti...

引用

15th international conference on Information and Communication technology convergence, ICTC 2024

作者： Nguyen, Trung Minh Tran, Phuong-Nam Dang, Duc Ngoc Minh Fpt University AiTA Lab Dept. of Computing Fundamental Ho Chi Minh City Viet Nam Kyung Hee University Networking Intelligence Lab Dept. of Computer Science and Engineering Gyeonggi-do Yongin-si Korea Republic of

ISBN: (纸本)9798350364637

The importance of Speech Emotion Recognition (SER) is growing across diverse applications, which has resulted in the development of multiple methodologies and models to improve SER performance. Nevertheless, some modern SER models require significant processing resources and exhibit poor performance, making them unsuitable for real-time applications. To address this, we propose a novel approach that leverages Knowledge Distillation (KD) to create lightweight student models derived from the 3M-SER architecture. Our method focuses on compressing the text embedding component by replacing BERTBASE with smaller variants while maintaining VGGish for audio embedding. Experiments conducted on the IEMOCAP dataset demonstrate that our student model, which reduces model size by up to 44.9%, achieves performance remarkably close to that of the teacher model while improving inference time by up to 40.2% when trained with KD. These results underscore the effectiveness of KD in creating efficient and accurate SER models suitable for resource-constrained environments and real-time applications. Our work contributes to the ongoing effort to make advanced SER technology more accessible and deployable in practical settings. © 2024 IEEE.

关键词： Speech recognition

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Enhancement of Industrial Automation using Internet of Things

Enhancement of Industrial Automation using Internet of Thing...

引用

2024 international conference on Advances in Data Engineering and Intelligent computing Systems, ADICS 2024

作者： Sheeba, Adlin Subasini, C.A. Kata Purna Avinash, S. Maheswaran Vijayendran, S. St. Joseph's Institute Of Technology Tamil Nadu Chennai600 119 India

ISBN: (纸本)9798350364828

The convergence of Industrial Automation, Cloud computing, and the Industrial IoT Devices has sparked a transformative paradigm shift across diverse industries. This synergy harnesses the power of interconnected smart devices, cloud-based data processing, and automated systems to redefine operational landscapes. In this abstract, we explore the intricate integration of these technologies and their collective impact on industrial realms. IoT sensors embedded within machinery facilitate real-time data collection on performance metrics, environmental factors, and machine health. These data streams, propelled through cloud-based infrastructure, undergo robust processing and analysis, enabling predictive maintenance, process optimization, and informed decision-making. The marriage of cloud computing and IoT not only allows for remote monitoring and control but also facilitates agile responsiveness to dynamic operational needs. By leveraging machine learning algorithms, anomalies are identified, allowing preemptive actions to mitigate potential downtime and enhance productivity. Moreover, the scalability and accessibility of cloud systems offer unprecedented flexibility in adapting to evolving industry requirements. However, such integration necessitates robust security measures to safeguard sensitive industrial data transmitted and stored within cloud environments. Encryption protocols, stringent access controls, and resilient authentication mechanisms become paramount to ensure data integrity and confidentiality. This abstract encapsulates the potential of this amalgamation, illuminating its transformative capabilities in optimizing processes, reducing downtime, and fostering cost-efficient, data-driven decision-making across industrial sectors. © 2024 IEEE.

关键词： Cloud computing

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A Stochastic Games based Resource Allocation Method for Cloud based Safe computing Platform 26

A Stochastic Games based Resource Allocation Method for Clou...

引用

IEEE 26th international conference on Intelligent Transportation Systems (ITSC)

作者： Zhang, Zhilin Lv, Fei Ying, Zhipeng Wang, Xi Zhao, Hongli Tang, Tao Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China China Acad Railway Sci Signals & Commun Res Inst Beijing 100081 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China

ISBN: (纸本)9798350399462

Safe computing platform is a safe architecture for the wayside equipment of CBTC, which keeps train operation control safely and efficiently in urban rail transit system. With the expansion of the subway line and the increase of passenger flow, the cloud computing technology is introduced into transit system to cope with the increase of maintenance cost and accident risk probability caused by the increase of physical equipments of CBTC. However, the architecture of safe computing platform must be considered when transplant the physical wayside equipment to cloud servers, which is hard to allocate the resources for the wayside equipment softwares to realize a good load-balance value while meeting the safety requirements defined by the safe computing platform. As one of the standard analytical tools, game theory has been applied in various fields to analyze resource allocation and decision-making problems. And stochastic games is good at modeling multi-agent decision-making problems, which is suitable for the problem we face. In this paper, a stochastic games is utilized to formulate the resource allocation of the cloud servers among the safe computing platform softwares and a SARSA based resources allocation algorithm with safety requirements is proposed to solve it. We compare SRAS with other similar algorithms in some simulation scenarios. The simulation results show that the SRAS method can get a better convergence performance and load-balance value of the cloud servers.

关键词： Cloud computing Safe computing platform Stochastic games Resources allocation

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Perspectives of Digital Twin-Empowered Distributed Artificial Intelligence for Edge computing

Perspectives of Digital Twin-Empowered Distributed Artificia...

引用

international conference on Artificial Intelligence Innovation (ICAII)

作者： Hoa Tran-Dang Kim, Dong-Seong Kumoh Natl Inst Technol Dept IT Convergence Engn Gumi Si South Korea

ISBN: (纸本)9798350345148;9798350345155

Driven by 6G networking, Edge Intelligence (EI) makes the most of the widespread edge resources to gain Artificial Intelligence (AI) insight. Future time-critical and data-intensive applications need distributed AI (DAI) and analytics solutions on the Edge computing platforms to enable EI from small devices to whole industrial factories. To deal with critical challenges of DAI implementation such as communication reliability, resource constrains and heterogeneity of edge devices, and dynamic nature of edge computing environment, we integrate digital twin (DT) technology to form an efficient framework. With this framework, efficient DT models are developed for edge devices, edge servers, and edge networks to predict accurately the states of physical entities using probabilistic graphical models (PGMs) and machine learning (ML) algorithms. In addition, a DT-empowered edge computing architecture specifying the optimal edge server placement, DT placement, and edge clustering is developed to support the implementation and development of DAI solutions. Specially, the framework is able to support various task partitioning-based DAI models including data parallelism, model parallelism, and pipeline parallelism as well as federated learning.

关键词： edge computing digital twin distributed AI edge intelligence Industrial IoT 6G networking Probabilistic Graphical Models (PGMs)

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Stress Analysis in Online Examination using Deep Learning Approach 8

Stress Analysis in Online Examination using Deep Learning Ap...

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8th IEEE international conference for convergence in technology, I2CT 2023

作者： Prabhakar, Priyanka Palaniswamy, Suja Pati, Peeta Basa Amrita Vishwa Vidyapeetham Department of Computer Science & Engineering Amrita School of Computing Bengaluru India

ISBN: (纸本)9798350334012

Nowadays, learning has changed its mode from offline to online, i.e., e-Learning. This e-learning has become more popular during the pandemic situations. Many platforms offer online exams and proctored exams, which are used at schools and colleges. Students' stress levels will be ordinarily high during examinations, whether offline or online, and the percentage of stress levels will be based on the students' cognitive behavior, subject knowledge, and the difficulty level of the questions. This study aims to propose a system for accurate stress level detection among students during the exam, thereby analyzing the impact of stress on their exam performance and scoring. © 2023 IEEE.

关键词： Support vector machines

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Optimization of a Consensus Protocol in Blockchain-IoT convergence 5

Optimization of a Consensus Protocol in Blockchain-IoT Conve...

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5th international conference on Emerging Smart computing and Informatics, ESCI 2023

作者： Kaur, Manpreet Gupta, Shikha Chandigarh University Department of Computer Science and Engineering Ghauraun140413 India Guru Nanak Dev Engineering College Department of Computer Science and Engineering Ludhiana India

ISBN: (纸本)9781665475242

A consensus mechanism determines how partici-pants agree on a transaction or a state change in the distributed ledger technology (DLT) such as blockchain by receiving consent from majority of network participants before inclusion of a block to blockchain. The consensus mechanism is required in almost every blockchain application. Most contemporary blockchain consensus systems need massive processing capabilities, signif-icant energy consumption, and reliance on monetary stake. Because of these limitations, mainstream consensus approaches are unsuitable for low-resource applications such as IoT. As a result, this paper introduces a new consensus protocol known as 'Delegated Proof of Accessibility' (DPoAC). The DPoAC protocol minimized the computational resource needs and energy usage demands of the existing proof-based consensus mechanisms, making it appropriate to use in applications with limited resources, such the Internet of Things. In addition, the lack of a financial stake in DPoAC makes it ideal for blockchain-IoT convergence. © 2023 IEEE.

关键词： Blockchain

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