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Research on distribution line arc fault detection method 5

Research on distribution line arc fault detection method

引用

5th International conference on mechatronics and computer Technology engineering, MCTE 2022

作者： Huang, Xinzhang Bao, Jieqiu Chen, Wei Dang, Yanyang Shenyang Institute of Engineering No. 18 Puchang Road Shenyang110136 China TBEA Co. Ltd No. 189 Beijing Road Changji Xinjiang831100 China

ISBN: (纸本)9781510661073

Arc faults in distribution lines are one of the main causes of electrical fires and need to be protected against them. In this paper, a series and parallel arc fault experimental platform is built regarding UL1699. The current waveforms of different arc faults are collected, and the current waveforms of some electrical equipment during normal operation are also collected. In this paper, the phase space reconstruction method is used to derive the phase space trajectory diagram of the current signals during arc fault and the normal operation of electrical equipment. The arc fault current feature quantity extraction algorithm is proposed based on fractal science, and the algorithm is implemented using Matlab software to extract the feature quantities of different arc faults and some electrical equipment's normal operation current signals. Simulation results show the effectiveness and feasibility of this method. © 2022 SPIE.

关键词： Fractals

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AI for science: Practice from Baidu PaddlePaddle

AI for Science: Practice from Baidu PaddlePaddle

引用

2024 Portland International conference on Management of engineering and Technology, PICMET 2024

作者： Chai, Xiaomeng Zhang, Min Tian, Hua Beijing University of Posts and Telecommunications School of Economics and Management Beijing China

ISBN: (纸本)9781890843458

AI4S (AI for science) is an interdisciplinary field dedicated to solving and studying complex scientific problems using AI methods. Currently, AI4S has made significant breakthroughs in life science, energy science, physics and computer science, Earth and Environmental science. Numerous fundamental software for AI4S have emerged as a result. As a global technology leader deeply engaged in the field of AI, Baidu strongly supports the deployment and application of AI4S solutions through its deep learning platform, PaddlePaddle. This paper presents a case study of PaddlePaddle, outlining its experience in accelerating innovation in the field of science. It explores the specific practices employed by PaddlePaddle to aid the development of AI4S, intending to provide constructive suggestions on how to accelerate the popularization of AI4S on the ground through deep learning platforms. The ultimate goal is to contribute to China's solution for AI-enabled scientific development in the wave of the new round of industrial revolution. © 2024 PICMET.

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Enhancing Paralympic Athlete Performance: Kinematic Analysis and computer Information Systems for Optimal Training Load Adjustment

Enhancing Paralympic Athlete Performance: Kinematic Analysis...

引用

International IoT, Electronics and mechatronics conference, IEMTRONICS 2024

作者： Shukurov, Kamoliddin Mirjamolov, Mekhriddin Kholdorov, Shokhrukhmirzo Malikova, Nodira Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi Amir Temur 108 Tashkent Uzbekistan Physical Education and Sports Scientific Research Institute Sportchilar Street 19 Chirchik Uzbekistan

ISBN: (纸本)9789819747832

This article explores the possibility of preparing athletes for Paralympic competitions based on kinematic tests grounded in computer information systems. The study examines the effectiveness of adjusting training load volumes in athletes’ physical preparation and diagnosing based on specific indicators. One of the primary objectives for domain experts is to integrate methods and tools into the training process that yield significant results in a short timeframe. The outcomes of this research reveal the potentialities of kinematic analysis concerning the volume and intensity of selected loads for each phase of para-athletes’ preparation, as well as the methodology chosen for executing these loads. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Information use

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RAMEN: A Ratio-Weighted Majority Entropy- Based Decision Tree Algorithm for Classifying Imbalanced Datasets

RAMEN: A Ratio-Weighted Majority Entropy- Based Decision Tre...

引用

2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Afolabi, Doyin Sennaike, Oladipupo Ogunseye, Shawn Adewole, Phillip University of Lagos Computer Science Department Lagos Nigeria Bentley University Computer Information Systems WalthamMA United States

ISBN: (纸本)9798350322972

Dealing with imbalanced datasets is an essential part of most analytic lifecycles. However, an inadequate classification of imbalance datasets may result in the loss of information and insights, as well as in the reduced repurposability of the data. While most well-known classification algorithms, including the decision tree algorithm, can efficiently make predictions from balanced datasets, these algorithms are inefficient when classifying imbalanced datasets. To address this concern, the present study, building on a traditional decision tree classification algorithm - namely, the ID3 algorithm -proposes a ratio-weighted majority entropy decision tree algorithm (RAMEN). RAMEN removes bias toward the majority class in imbalanced datasets. The RAMEN algorithm is then tested on two imbalanced datasets: a cancer case dataset and a banknote verification dataset. Comparing the performances of the RAMEN technique with those of the traditional ID3 decision tree algorithm and the minority entropy-based decision tree algorithm, we find that RAMEN outperforms both aforementioned algorithms for the two datasets. © 2023 IEEE.

关键词： Classification (of information)

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Research and development of blockchain consensus algorithms 7

Research and development of blockchain consensus algorithms

引用

7th International conference on mechatronics and Intelligent Robotics, ICMIR 2023

作者： Ma, Xinkun Li, Yingna Wang, Jinyu Faculty of Information Engineering and Automation Kunming University of Science and Technology 727 Jingming South Rd. Chenggong District Kunming650500 China Computer Technology Application Key Lab of the Yunnan Province 727 Jingming South Rd. Chenggong District Kunming650500 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

Blockchain technology is a paradigm of distributed systems, and its consistency problem is solved by consensus algorithms. This paper summarizes the existing consensus algorithms and divides them into three types: proof, voting, and Paxos-like. The implementation methods and advantages and disadvantages of some representative algorithms among the three types of consensus algorithms are introduced. Finally, the research hotspots and development directions of consensus algorithms in terms of performance and scalability are pointed out. © 2023 SPIE. All rights reserved.

关键词： Blockchain

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A Two State Adaptive Ant Colony Algorithm Framework for Solving Multi-objective Optimization Problems 7

A Two State Adaptive Ant Colony Algorithm Framework for Solv...

引用

7th IEEE Information Technology and mechatronics engineering conference, ITOEC 2023

作者： Li, Xu Liu, Zhengyan Fuyang Normal University School of Computer and Information Engineering Fuyang China

ISBN: (纸本)9798350334197

In order to improve the performance of ant colony algorithm in solving multi-objective optimization problems and enhance the universality of the algorithm, this paper introduces cloud model theory and proposes an adaptive ant colony algorithm framework between "development"and "exploration". In the algorithm, the concept of cloud model dominant solution is introduced, and pheromone update mechanism, pheromone status evaluation mechanism and the determination mechanism of cloud model dominant solution are constructed. At the same time, a multi-objective adaptive mechanism based on cloud model has been constructed, enabling the algorithm to maintain a balance between exploring unknown feasible solutions and developing known Pareto optimal solutions, thereby improving the search efficiency of the algorithm. In the simulation comparative experiment of solving multi-objective traveling salesman problem, the experimental results show that the framework proposed in this paper is feasible and effective. © 2023 IEEE.

关键词： Multiobjective optimization

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Research on the Integration of Artificial Intelligence and Signal Processing: A Trend Analysis Based on Bibliometrics 24

Research on the Integration of Artificial Intelligence and S...

引用

5th International conference on computer science and Management Technology, ICCSMT 2024

作者： Ma, Guoxuan School of Computer Science and Engineering Northeastern University Liaoning Shenyang China

ISBN: (纸本)9798400709999

To understand the recent advancements in the application of artificial intelligence in the field of signal processing, this paper employs VOSviewer and CiteSpace to conduct a quantitive analysis and visualization of relevant literature from 2020 to September *** analyzing the number of publications, citation patterns, and collaboration networks, this study elucidates the primary contributors, core research directions, and the global landscape of scientific collaboration in this *** research findings indicate that the integration of AI and signal processing has not only achieved theoretical breakthroughs but is also widely applied to solve practical problems, such as optimizing medical diagnoses and enhancing communication *** bibliometric visualization analysis, this paper provides a panoramic view of the current state of research in this area and offers targeted predictions and recommendations for future development trends. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Quantization (signal)

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Study on inertia based MPPT control using reinforcement learning algorithm for extra power production

Study on inertia based MPPT control using reinforcement lear...

引用

2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Jargalsaikhan, Nyam Byambaa, Sergelen Masahiro, Furukakoi Tomonobu, Senjyu University of the Ryukyus Grad. School of Engineering and Science Okinawa Japan Mongolian University of Science and Technology Department of Electrical Engineering Ulaanbaatar Mongolia Sasebo College National Institute of Technology Nagasaki Japan University of the Ryukyus Faculty of Engineering Okinawa Japan

ISBN: (纸本)9798350322972

Permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) also known as Type 4-WECS has many advantages over other types of WECS. One of the advantages is full variable speed operation for low wind speed. With the MPPT control, most wind turbines try to follow optimal rotational speed for maximum possible power capture. However, due to rotor inertia, tracking loss is inevitable, which causes decreased power production. This study investigates the use of inertia in the rotational masses of the WT for increased power production. The idea is to use the rotor inertia of the large-scale wind turbine (VSWT) to temporarily retain the rotational speed at a higher value for a short time rather than following optimal rotational speed in a variable speed region. As a result, the wind turbine can capture more power. The optimal tip speed ratio (TSR) method is used as the main MPPT control method, and additional Reinforcement Learning (RL) algorithm-based reference rotational readjustment was used for the purpose mentioned above. The simulation studies have been conducted in Matlab/Simulink® software and it showed that power production of wind turbines has increased slightly than the standard method. © 2023 IEEE.

关键词： Wind turbines

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Corpus Construction for Etiquette Entity and Relation Extraction in Ancient Chinese Texts Assisted by Large Language Models 8

Corpus Construction for Etiquette Entity and Relation Extrac...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Siriguleng Inner Mongolia MINZU University College of Computer Science and Technology Tongliao China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

To address the issue of data scarcity in entity relationship extraction tasks within the domain of ancient texts and meet the needs of researchers in digital humanities, this paper proposes an automated data annotation method based on the large language model ChatGPT and prompt engineering. By treating the large language model as a 'data annotator,' we developed an entity relationship extraction dataset tailored to ritual scenarios in ancient texts for the natural language processing field. This dataset includes five entity types and ten relationship types, characterized by precise labeling. To verify the robustness and versatility of the dataset, comprehensive experiments were conducted on three pre-trained language models. The results demonstrate that pre-trained models based on prompt learning achieve the best performance in entity relationship extraction tasks. This study shows that the data annotation method leveraging large language models provides a feasible solution for automated data annotation, and the corpus of etiquette entity relationship extraction lays an important foundation for the construction of etiquette question answering system and knowledge graph of ancient books. © 2025 IEEE.

关键词： ancient chinese texts etiquette entity and relation extraction LLMs

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University student's mental stress detection using machine learning 7

University student's mental stress detection using machine l...

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7th International conference on mechatronics and Intelligent Robotics, ICMIR 2023

作者： Firoz, Mehedi Islam, Mohammad Monirul Shidujaman, Mohammad Islam, Ashraful Habib, Tarek Department of Computer Science and Engineering Daffodil International University Bangladesh Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Bangladesh

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

University students are especially susceptible to the negative effects of mental stress in today's environment, which is a serious issue overall. A great deal of pressure is now being placed on a period of life that was traditionally considered to be the most carefree. People in today's culture are exposed to increasingly high levels of mental stress, which has been related to a broad variety of health problems, such as depression, suicide, heart attacks, and strokes. Because of this, in order to primarily extract, for the purposes of this research, the mental stress ratings of university students, we applied a total of six distinct machine learning methods. The Decision Tree Classifier, the Random Forest Classifier, the SVC, the KNN Classifier, the Multinomial NB, and the K-Nearest Neighbors Regressor are only some of the machine learning algorithms that are available. This investigation's principal objective is to determine the percentage of students who are struggling to deal with emotional pressure in their lives. The dataset was put together by hand with paper and manual information obtained from a survey. Out of the six distinct classification strategies, the Decision Tree Classifier and the Random Forest Classifier both achieved a test result of 0.99, which is the maximum score that can be achieved. © 2023 SPIE. All rights reserved.

关键词： Machine learning

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