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Research on the Transient Potential Rise Characteristics of High - speed Railway Rail Lightning Strike and Its Impact on Trackside Signal Equipment 37

Research on the Transient Potential Rise Characteristics of ...

引用

37th international conference on Lightning Protection, ICLP 2024

作者： Wang, Shulai Xiang, Nianwen Wang, Chaoqun Lyu, Zengwei Chen, Zhiwei School of Electrical Engineering and Automation Hefei University of Technology Hefei China Institute of Energy Hefei Comprehensive National Science Center Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9783800764174

Lightning strikes on the catenary will cause a sharp rise in rail potential, which directly threatens the safety of the signal equipment connected to the rail along the trackside. It is urgent to carry out research on the propagation law of transient overvoltage on rails caused by lightning strikes on the catenary. A rail lightning electromagnetic transient calculation model considering the influence of integrated grounding system and catenary is established, and the influence law of different lightning strike point positions, different pier heights, and different lightning current waveforms on the distribution of rail potential rise is calculated. The specific conclusions are as follows: when lightning strikes different positions within a catenary span, the rail potential within 700m near the lightning strike point will exceed the lightning strike tolerance level of the trackside signal equipment, causing equipment damage. The potential rise increases by about 9 kV;for every 5 m increase in pier height, the rail potential rise increases by about 16%. Based on the law of the rail potential rise, the common-mode protection methods for the trackside signal equipment are proposed by appropriately reducing the horizontal connection distance of uplink and downlink ground wires to decrease the rail potential and installing common-mode protection devices. © 2024 IEEE, © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Signaling equipment

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DELTA-V: An Open-Source High-Level Synthesis Driven ASIP Design automation Tool for RISC-V Microprocessors 14

DELTA-V: An Open-Source High-Level Synthesis Driven ASIP Des...

引用

14th international conference on Electrical and Electronics engineering, ELECO 2023

作者： Yanik, Muhammet Enes Tökez, Murat Nisanci, Mehmet Akif Çiçek, Ihsan Gebze Technical University Δ Laboratory Dept. of Electronics Engineering Kocaeli Turkey

ISBN: (纸本)9798350360493

Application-Specific Instruction-set Processors are crucial for optimizing performance and energy efficiency in specific applications while retaining compiler-supported programmability, especially in open-standard architectures like RISC-V. To meet the increasing demand for ASIPs, rapid design and prototyping are essential. High-Level Synthesis automates the translation of high-level software descriptions into hardware, significantly reducing design time. However, it's important to note that while HLS provides designs, it doesn't directly create RISC-V cores. ASIP designers bridge this gap, but must also be proficient in hardware description languages like VHDL. In this work, we introduce DELTA-V, a project that seamlessly combines OpenASIP and AMD Vitis HLS. This integration empowers ASIP designers to customize RISC-V cores efficiently. Leveraging ASIP strengths, DELTA-V enables tailored SoC development, achieving over %60 cycle count reduction for efficient RISC-V processors with minimal effort. © 2023 IEEE.

关键词： computer hardware description languages

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Credit Card Fraud Detection using Neural Embeddings and Radial Basis Network with a novel hybrid fruitfly-fireworks algorithm 3

Credit Card Fraud Detection using Neural Embeddings and Radi...

引用

3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Singh, Indu Aditya, Nilesh Srivastava, Pranjal Mittal, Shivanshu Mittal, Taruvar Surin, Noel Vaibhav Delhi Technological University Department of Computer Science and Engineering India Netaji Subhas University of Technology Department of Manufacturing Processes and Automation Engineering India Netaji Subhas University of Technology Department of Information Technology India

ISBN: (纸本)9798350338607

Financial institutions are highly concerned about credit card fraud due to the growing frequency of deceitful activities linked with credit card transactions. To address this issue, a novel fraud detection system is proposed that combines advanced feature engineering and neural network architecture. The proposed approach. FFFW-RBN, employs a hybrid swarm intelligence model comprising the Fruitfly Optimization Algorithm and Fireworks Algorithm, (FFO-FWA) for feature selection, and the Neural Embeddings Generator in combination with a Shallow Radial Basis Network (RBF) for localized pattern classification. The proposed system achieves a 99.97% accuracy, 0.91 recall, and a precision of 0.94. The experimental results demonstrate that our methodology effectively and practically detects fraudulent credit card transactions. The paper presents a comprehensive evaluation of the system, including various performance metrics and a confusion matrix, highlighting its potential for real-world implementation. © 2023 IEEE.

关键词： Radial basis function networks

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Design and Implementation of a Common Coupling Test Bench for China Standard EMU and CRH380B EMU 3

Design and Implementation of a Common Coupling Test Bench fo...

引用

3rd international conference on Electrical engineering and Control Science, IC2ECS 2023

作者： Liu, Guangqian Wu, Huazhu School of Automation and Electrical Engineering Dalian Jiaotong University Liaoning Dalian116028 China

ISBN: (纸本)9798350382426

The debugging of EMU coupling is an important condition to ensure the safe and efficient operation of EMU trains after coupling. At present, CRH380B and CR400BF are the main models of China's high-speed railway, but the traditional coupling debugging equipment cannot meet the needs of debugging these two models at the same time. According to the actual demand of a domestic locomotive factory, a coupling test bench is designed that can complete the commissioning task of two types of vehicles. The test system is realized by software and hardware design, which can complete the signal test of the coupling electrical coupler of CR400BF and CRH380B head cars in static conditions. Through the actual test, the designed coupling debugging system can meet the requirements of the coupling debugging of two kinds of EMU, and has practical application significance. © 2023 IEEE.

关键词： China standard EMU Coupling debugging Single-chip computer System design

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Development of neural network model based on attention mechanism applied to the prediction of Ship damaged stability 3

Development of neural network model based on attention mecha...

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3rd international conference on Artificial Intelligence and computer engineering, ICAICE 2022

作者： Li, Haoqing Huang, Xiaohao Pan, Changchun Yang, Chunlei Wang, Jinbao School of Sensing Science and Engineering Shanghai Key Laboratory of Navigation and Location based Services Shanghai Jiao Tong University Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China China Institute of Ship and Ocean Engineering Design and Research Shanghai China

ISBN: (纸本)9781510663473

As a key indicator in ship design, many major incidents of ship sinking are related to the ship's damaged stability. The process of calculating the damaged stability becomes more and more complex and time-consuming on account of more and more stringent specification standards. A two-stage design step is used in this article to realize the calculation of ship's damaged stability under various watertight bulkhead fast. Firstly, a multi-layer feed-forward neural network model was designed for the predictive regression of a ship's damaged stability using the location of the watertight bulkhead as a variable. Secondly, the relationship between each watertight bulkhead variant and the damaged stability A-value is analysed. After that, with hydrostatic curve calculation based on the inlet simulation and the interaction between watertight bulkheads considered, a multilayer feed-forward neural network model based on the attention mechanism is designed, which could predict the regression of the damaged stability A-value and analyse bulkhead weights. Finally, the validity of the model was verified by the data, in which the mean value of the prediction error MAE (mean absolute error) was at 2.67×10-4 and the computation time was greatly reduced. © 2023 SPIE.

关键词： Neural network models

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Translating Natural Language Specifications into Access Control Policies by Leveraging Large Language Models 6

Translating Natural Language Specifications into Access Cont...

引用

6th IEEE international conference on Trust, Privacy and Security in Intelligent Systems, and Applications, TPS-ISA 2024

作者： Lawal, Sherifdeen Zhao, Xingmeng Rios, Anthony Krishnan, Ram Ferraiolo, David San AntonioTX United States University of Texas Department of Information Systems and Cyber Security San AntonioTX United States Department of Electrical & Computer Engineering San AntonioTX United States National Institute of Standards and Technology GaithersburgMD United States

ISBN: (纸本)9798350386745

This paper investigates the application of large language models (LLMs) for the automated translation and information extraction of access control policies from a natural language source. Prior research in this domain have predominantly relied on manual methods, traditional natural language processing (NLP), or a hybrid approach involving machine learning and artificial neural networks combined with NLP techniques. We demonstrate a significant advancement by leveraging the power of LLMs to achieve improved efficiency and accuracy in these tasks. Our study focuses on applying cutting-edge prompt engineering techniques designed to optimize LLM performance in the specific context of access control policy information extraction. The findings highlight the potential of LLMs to streamline the process of converting human-readable requirements into formal, machine-interpretable policies, ultimately contributing to the automation and security of access control systems. © 2024 IEEE.

关键词： Natural language processing systems

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Traffic Classification For Botnet Detection Using Deep Learning 3

Traffic Classification For Botnet Detection Using Deep Learn...

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3rd international conference on Smart Cities, automation and Intelligent Computing Systems, ICON-SONICS 2023

作者： Hossen, Md. Sagar Ahmad, Tohari Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781509062805

In this modern world, we are naturally dependent on technology, which is constantly evolving. At the same time, our fear of data fraud is increasing every day. The ever-increasing number of attacks on our servers indicates that people have learned to adapt to new technologies. In addition, the number of botnet attacks is not insignificant, and botnets threaten computer networks. This can impact security systems, including malware distribution, phishing, spamming, and click fraud. Due to their harmful effects, botnets must be identified as soon as possible. Due to the dynamic character of botnets, however, detection has proven difficult. In this proposed method, deep learning is used to analyze and predict botnet data, and model performance metrics such as accuracy, precision, Recall, and F1 score are compared to prior work. In the proposed procedure, patterns are also discussed by analyzing botnet data. Various scenarios and sensors separate the NCC and NCC-2 datasets. The NCC dataset is separated into 13 scenarios, while the NCC-2 dataset is separated into 3 sensors. The dataset is preprocessed using the clean method, the null value handling method, the imbalance method, and the feature selection method to extract the essential characteristics. The dataset is then trained using LSTM, GRU, and Bi-LSTM models, and 99.93% accuracy is achieved. © 2023 IEEE.

关键词： Long short-term memory

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Quantum Technology Quantum Neural Networks in Smart Grids Control: Premier Perspectives 8

Quantum Technology Quantum Neural Networks in Smart Grids Co...

引用

8th international conference on Control, Instrumentation and automation, ICCIA 2022

作者： Safari, Ashkan Ghavifekr, Amir Aminzadeh University of Tabriz IEEE Systems Sensors Councils Smart Grids Society Faculty of Electrical and Computer Engineering Tabriz Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9781665495691

This paper presents a practical field of quantum technology and its contribution to smart grids, and their future in smart sustainable cities (SSCs). Smart grids are among the important basis of an SSC, so its factors such as forecasting, optimization, turbine design have a significant role. Based on quantum technology's amazing features, it has conspicuous applications in smart grids including weather prediction, or demand response forecasting. This paper represents SSCs, smart grids, and quantum technology and its use in the ladders. Then, defines the areas of smart grids in which quantum technology can make a noticeable development. Respectively, it compares quantum technology with other regular supercomputing technologies. Ultimately, quantum technology is a kind of technology that has a noticeable contribution potentiality to other technologies to make the world to be processed in a faster, and much more accurate way, and smart grids, SSCs are, also, in this future. © 2022 IEEE.

关键词： Smart power grids

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Navigating the Future: Harnessing Artificial Intelligence Generated Content (AIGC)for Enhanced Learning Experiences in Higher Education

Navigating the Future: Harnessing Artificial Intelligence Ge...

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2024 international conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Lu, Guangyun Hussin, Norriza Binti Sarkar, Arindam SEGi University Faculty Of Information Technology Petaling Jaya Selangor Kota Damansara47810 Malaysia Ramakrishna Mission Vidyamandira Department Of Computer Science And Electronics Belur Math West Bengal Howrah711202 India

ISBN: (纸本)9798350371567

This The current study explores the impact of integrating Artificial Intelligence Generated Content (AIGC) in higher education, with a specific focus on the roles of university teachers and students' learning outcomes. The research delves into the transformation of teaching practices, the challenges encountered by teachers in the process of AIGC integration, and identifies opportunities for collaboration and innovation. Utilizing a quantitative research method, a survey questionnaire was employed to collect data, providing information for practical recommendations. The findings indicate that university teachers acknowledge the potential benefits of AIGC in education while emphasizing the necessity to address challenges for effective implementation. Participants perceive AIGC as a tool facilitating more creative and engaging teaching methods, task automation, and changes in teaching approaches. Identified challenges include difficulties in utilizing AIGC effectively and adapting to new teaching methods. AIGC also presents opportunities for innovation, collaboration, and the creation of engaging learning environments. Slight variations in perspectives based on gender and current roles were observed, with female teachers and teaching assistants/professors perceiving higher impact and opportunities for collaboration and innovation. Participants with higher AIGC expertise perceived a greater impact and fewer challenges. Those aligned with the educational purposes of AIGC noted greater impact and opportunities for collaboration while acknowledging usage difficulties. © 2024 IEEE.

关键词： Artificial intelligence

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The Role of AI and Blockchain in Supply Chain Traceability 3

The Role of AI and Blockchain in Supply Chain Traceability

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3rd international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Sherin, K. Kaur, Namita Joshi, Ankita Ravindar, B. Nayak, Pinki Srinivas, Kolachina St. Joseph's Institute of Technology Department of Computer Science and Engineering India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Sciences Telangana Warangal India Dr. Akhilesh das Gupta Institute of Technology & Management Department of Information Technology Delhi India Kl University Klef Kl Business School Andhra Pradesh Vaddeswaram522302 India

ISBN: (纸本)9798350399264

Optimizing the abilities to boost numerous goals, such as budget, service, and reliability, is at the core of industrial automation. To do this, supply chain management must adopt the product lifecycle, manufacturing systems lifecycle, and economic cycle. In a nutshell, a manufacturing company generates a massive quantity of data. A distribution network stakeholder has accessibility to its data and may utilize AI to draw new insights. Since only little information is provided to the consumer, only a limited context can be established. With blockchain, everyone can see everyone else's data. As a result, an individual's stakeholder insights will be more substantial. This will aid in establishing an intelligent supply chain © 2023 IEEE.

关键词： Blockchain

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