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Low Voltage Power Line Physical Topology Recognition Method Based on data Drive 3

Low Voltage Power Line Physical Topology Recognition Method ...

引用

2023 3rd international conference on Power Grid Systems and Green Energy, PGSGE 2023

作者： Huang, Fu Lin, Junhong Zhang, Daolu Wu, Dan Digital Grid Research Institute CSG Guangdong Guangzhou510000 China

The current traditional low-voltage power line physical topology identification method mainly detects the line pulse signal to identify the line topology, leading to poor identification effects due to the lack of correlation analysis of node voltage. A data-driven low-voltage power line physical topology identification method is proposed in this regard. The correlation between the node timing voltages is analyzed by exploring the voltage law to determine the connection between low-voltage power lines. The node resistance values are also calculated to convert the physical topology identification problem into a linear equation problem. In the experiments, the proposed method is verified for identification accuracy. The analysis of the experimental results shows that the proposed method has a low root-mean-square error and better recognition accuracy when recognizing the physical topology of low-voltage power lines. © Published under licence by IOP Publishing Ltd.

关键词： Mean square error

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Online education based on distributed multi-layer data processing technology 3

Online education based on distributed multi-layer data proce...

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3rd international conference on Machine Learning and Big data Analytics for IoT Security and Privacy, SPIoT2023

作者： Cui, Shunji Jilin Agricultural Science and Technology University Jilin China

In order to promote the intelligent development of online education and optimize the status quo of online education, an online education method based on distributed multi-layer data processing technology is proposed. The method integrates the database information and builds the BTREE index by calculating the distributed database resource information, the initial information sequence, the main information set and the trade-off coefficient of information attributes. The bidirectional index method is used to extract the core data segment of integrated data and establish the time series table. The schedule is used to constrain the data twice, and the coincidence degree of the initial data transmission path is compared with the actual path parameters after evaluation, so as to realize the automatic matching of the data transmission path. The experimental results show that compared with the traditional transmission path matching method, the designed automatic matching method improves the matching accuracy of the complete data transmission path by 24% and the broken data transmission path by 19%, which has practical advantages. It is proved that this method can promote the precise personality teaching of online education, so as to achieve the effect of optimizing online education. It can also provide reference for the intelligent development of other online education. © 2023 Elsevier B.V.. All rights reserved.

关键词： Economic and social effects

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Research and Design of a Deep Learning-Based Free Trade Zone data Analysis System

Research and Design of a Deep Learning-Based Free Trade Zone...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), international

作者： Jinyi Wei Ting Lu Shuli Wang School of Economics Wuhan University of Technology Wuhan China

This study aims to design and implement a deep learning-based data analysis system for free trade zones. In the context of accelerated globalization and economic integration, data analysis of free trade zones is crucial for optimizing trade processes and enhancing economic efficiency. Traditional data analysis methods are somewhat inadequate in handling the high dimensionality, large scale, and complexity of free trade zone data. This research utilizes deep learning technology, particularly Long Short-Term Memory (LSTM) networks, to process and analyze vast quantities of data from free trade zones, providing more profound insights. The study begins by reviewing the fundamentals of deep learning, followed by an analysis of its applicability and advantages in processing data from free trade zones. Through practical application cases, the study demonstrates the system's effectiveness in data preprocessing, model training, and result analysis. This system not only improves the efficiency of data processing but also provides more scientific bases for decision-making for policymakers and businesses, thereby promoting high-quality economic development.

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Unveiling the Potential of BaLa2ZnO5: Er3+ LEDs for Overcoming NLOS Challenges in VLC Systems 3

Unveiling the Potential of BaLa2ZnO5: Er3+ LEDs for Overcomi...

引用

3rd international conference on Advanced Electrical Engineering, ICAEE 2024

作者： Chahed, Halima Fassi, Benattou Driz, Samia University of Djillali Liabes Telecommunications and Digital Signal Processing Laboratory Faculty of Electrical Engineering Sidi Bel Abbes22000 Algeria

ISBN: (纸本)9798350349351

Visible Light Communication (VLC) is a promising wireless data transfer paradigm that uses light waves to provide high-speed communication in indoor environments. In Non-Line-of-Sight (NLOS) scenarios, where the direct line-of-sight (LOS) between transmitter and receiver is obstructed, VLC offers unique advantages over traditional radio frequency (RF) communication, including increased security and reduced interference. In this paper, we investigate the influence of quantum efficiency (QE) of LEDs on the performance of VLC systems, particularly in NLOS situations. Using OptiSystem software Version 19, we conduct thorough modeling and analysis of the VLC NLOS model for both conventional LEDs and Barium Lanthanum Zinc Oxide doped with Erbium (Er3+) ions (BaLa2ZnO5: Er3+) LEDs. Our comparative study highlights the superior performance of the proposed BaLa2ZnO5: Er3+ LED, achieving a Q-Factor of 6.63 and a lower Bit Error Rate (BER) of 8.17× 10-12. These results elucidate the impact of QE on key performance metrics such as BER, Q-Factor, and signal distortion, emphasizing the crucial role of QE in improving the reliability and efficiency of VLC systems. Opening the path for future advances in wireless communication technology. © 2024 IEEE.

关键词： Quantum efficiency

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Security risk propagation and control strategies for complex tasks based on improved multi-signal flow graph 3

Security risk propagation and control strategies for complex...

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2023 3rd international conference on Big data, Artificial Intelligence and Risk Management, ICBAR 2023

作者： Tan, Xiaodong Officers College of Pap Chengdu610213 China

ISBN: (纸本)9798400716478

Security risk management is the key to ensure the smooth implementation of major and complex tasks. Due to various risk factors spread, interweave and influence each other, there are some difficulties and challenges to trace the source of security risks. A security management strategy based on improved multi-signal flow graph is proposed in this paper. Firstly, considering on the characteristic and law of tasks, and making an in-depth analysis of the elements of security risk of tasks, Security Risk Effects and Criticality Analysis(SRECA) is developed. Secondly, fuzzy deduction graph is used to describe the quantitive relationships of security risk propagation, thus a Security Risk Propagation Model(SRPM) is built based on improved multi-signal flow graph. Thirdly, the characteristic of risk propagation by SRPM, After analyzing and evaluating the risk factors whose probability of occurrence is the highest, and severity is the maximum, thus security accidents of a task can be reduced by putting forward some idiographic precaution measures. Finally, taking the example of security risk management for the boat training, The experimental results show that the personnel risk is the main risk affecting navigation safety, and it is important to develop personal safety education training, work abilities and vocational level, physical and psychological quality, ideological state and security awareness in order to minimize the probability of loss due to navigational accidents. © 2023 ACM.

关键词： Graphic methods

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Active Control Technology of Supply Chain Intelligent Work Robot Based on Speech Enhancement Technology 3rd

Active Control Technology of Supply Chain Intelligent Work R...

引用

3rd international conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2023

作者： Tang, Zhanbiao Gu, Sanlin Zhang, Lixing He, Jiao Tian, Lin State Grid Gansu Electric Power Company Materials Company Gansu Lanzhou730050 China Cloud Data Technology Co. LTD Gansu Lanzhou730050 China

ISBN: (纸本)9789819721993

In order to improve the efficiency and quality of supply chain management, achieve intelligent management of the supply chain, reduce management costs, and provide competitive advantages for enterprises and meet market demands. Propose an active control method for supply chain intelligent operation robots based on speech enhancement technology. By preprocessing the voice signal of the supply chain intelligent operation robot and utilizing the Teager energy operator, the characteristics of the supply chain intelligent operation robot's voice signal are extracted. On this basis, based on speech enhancement technology, the least squares support vector machine is used to output control results and achieve active control of supply chain intelligent operation robots. The experimental results show that the supply chain intelligent operation robot proposed in this paper has high active control accuracy and short time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Speech enhancement

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An Enhanced Research Productivity Monitoring System for Higher Education Institutions (HEI's) with Natural Language processing (NLP) 3

An Enhanced Research Productivity Monitoring System for High...

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3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Regla, Alfio I. Ballera, Melvin A. College of Computer Studies Technological Institute of the Philippines 1338 Arlegue St. Quiapo Manila1001 Philippines

The HEI in the Philippines is entrusted with three mandates by the Commission on Higher Education (CHED): teaching, research, and extension service. Among these mandates, research productivity plays a crucial role in fostering knowledge generation, production, and transfer within the community. However, monitoring research productivity has been a persistent challenge due to the diverse evaluation criteria set by local and international accrediting organizations, which directly impact an HEI's educational quality. This study has selected an academic institution and aims to 1) Design a system model as research data collection;2) employ Natural Language processing (NLP)-based techniques to facilitate the monitoring and retrieval of information on research productivity and 3) generate visualizations and analytics based on research data. The extensive review of relevant literature, visualization and analysis of the institution's research data were carried out in this study. NLP techniques was employed to enable mapping of the institution's research output to the government and organizations research agenda, facilitating the identification of emerging topics through clustering techniques and modeling. Systems evaluation through Technology Acceptance Model (TAM) was gained 4.56 mean results from the respondent corresponding to "Strongly Agree" which indicates that system is able to assist in monitoring the institution's research productivity. © 2023 Elsevier B.V.. All rights reserved.

关键词： data visualization

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Web Scraping using Natural Language processing: Exploiting Unstructured Text for data Extraction and Analysis 3

Web Scraping using Natural Language Processing: Exploiting U...

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3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Pichiyan, Vijayaragavan Muthulingam, S. Sathar, G. Nalajala, Sunanda Ch, Akhil Das, Manmath Nath Department of CSE-DS Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology Telangana Hyderabad India Department of CSE Alliance University Karnataka Bangalore562106 India

In recent years, combining web scraping techniques with Natural Language processing (NLP) has emerged as a powerful approach to unlock deeper insights from unstructured textual data. This research study presents a detailed exploration of web scraping using NaturalLanguage processing (NLP) techniques, demonstrating how these methodologies can be synergistically integrated to extract and analyze unstructured text from diverse web sources. This research study analyzes the challenges posed by unstructured data on the web and how NLP can play a pivotal role in converting this text into structured and actionable information. The first part of the paper covers an overviewof web scraping methods, including rule-based parsing, XPath queries, and the use of web scraping libraries such as BeautifulSoupand Scrapy. The second part of this research work focuses on applying NLP techniques to process and analyze the extracted textual data. Further, the preprocessing steps such as tokenization, stemming, and stop word removal, are analyzed followed by more advanced techniques like Named Entity Recognition. © 2023 Elsevier B.V.. All rights reserved.

关键词： Websites

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Optimization Research on Radar signal processing Technology Based on MTI-MTD

Optimization Research on Radar Signal Processing Technology ...

引用

data Science and Computer Application (ICDSCA), IEEE international conference on

作者： Mingzheng Mao Xinrui Han School of Information and Electronics Beijing Institute of Technology Beijing China

Due to the continuous development of radar signal processing technology, the MTI-MTD (moving target detection) technology is deeply studied in this paper. This article introduces the principles and properties of MTI and MTD filter banks and analyzes their advantages in clutter suppression, signal-to-noise ratio improvement, and target velocity measurement. Therefore, a radar signal processing system based on MTI-MTD technology, including an acquisition, preprocessing, and target recognition module, is designed. First, the acquisition module receives the radar echo signal and performs analog-to-digital conversion. Second, the preprocessing module is responsible for some operations on the echo signal, such as MTI filtering and Keystone distance migration correction. Third, the target recognition module is responsible for MTD filtering of the preprocessed signal and uses the neural network model to classify and locate the target. Through the verification of three sets of experimental data, the effectiveness and feasibility of this method are high. In addition, we compare it with the traditional method. The experiment results show that the radar signal processing method based on MTI-MTD technology can detect moving targets at various distances, speeds, and signal-to-noise ratios. It improves the ability of radar signal processing technology to detect moving targets in clutter.

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Classifying static muscle fatigue: an surface electromyography signal analysis approach 3

Classifying static muscle fatigue: an surface electromyograp...

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3rd international conference on Biomedical and Intelligent Systems, IC-BIS 2024

作者： Huang, Yanyan Wang, Chenyang Sun, Yifeng Jin, Zhikun School of Mechanical Engineering Shanghai Dianji University Shanghai201306 China

ISBN: (纸本)9781510681279

This study aims to propose and validate an innovative method for detecting and classifying muscle fatigue, based on surface electromyography (sEMG) signals, with a focus on accurately identifying and classifying static muscle fatigue. By recruiting seven healthy young volunteers (comprising two males and five females), this research conducted a series of fatigue tests, during which the participants' surface electromyographic signals and their subjective fatigue scores were meticulously recorded. The study extracted 18 features from the surface electromyographic signals, including time domain, frequency domain, and time-frequency domain characteristics. These features were then labeled as "normal"or "fatigued"based on the participants' Borg CR-10 subjective fatigue scale. In the data processing phase, 80% of the statistical features were selected as the training dataset for machine learning models (CNN-SVM, KNN, SVM, RF), with the remaining 20% serving as the test dataset to evaluate the performance of the four algorithms in terms of accuracy in muscle fatigue classification. The experimental results indicate that in the evaluation mode utilizing all features, the CNN-SVM model achieved the highest accuracy and F1-score, at 86.13% and 84.58% respectively. In the mode that only utilized the four principal sEMG signal features, the KNN model exhibited the best performance with an accuracy rate of 75.87%.The muscle fatigue recognition model proposed in this study is of paramount significance for monitoring muscle fatigue in static sitting and standing postures. © 2024 SPIE.

关键词： Statistical tests

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