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4th international conference on Electronic information engineering and computer science, EIECS 2024

作者： Sun, Zhenkai Meng, Xiangrui Han, Tailin Ju, Mingchi Changchun University of Science and Technology Jilin Changchun China

ISBN: (纸本)9798331531409

This study is dedicated to constructing a surrogate model of the shock wave field using physics-informed neural networks, aiming to achieve accurate reconstruction of the shock wave field with a low amount of data. The key to this method lies in the integration of the physical laws of shock wave propagation, which aims to overcome the insufficient reconstruction accuracy caused by sparse measurement points in traditional testing. This effectively reduces the safety risk of non-combat casualties. Through experimental validation, the method proposed in this paper achieves an average absolute error of less than 0.5541 kPa when dealing with small datasets;using 56 training data points for testing, the improved PINN's relative L2 Norm error is reduced by 25.876% compared to the BP neural network, and the average absolute error decreases by 9.5%. © 2024 IEEE.

关键词： Shock waves

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Tracing the transition of Insulating Oil application in Transformers

Tracing the transition of Insulating Oil application in Tran...

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2024 IEEE international Students' conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Raj, Raymon Antony Venkatachary, Sampath Kumar Sheik Sidthik, A. Sarathkumar, D. Baptist Andrews, Leo John Annamalai, A. Sivadasan, J. Rajeshkanna, R. Kongu Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638 060 India Grant Thornton Botswana Plot 50370 Acument Park Fair Grounds Gaborone Botswana Vsb College of Engineering & Technical Campus Department of Eee Tamil Nadu Coimbatore642109 India Botho University Faculty of Engineering and Technology Department of Information Technology Gaborone Botswana Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Psr Engineering College Department of Ece Tamil Nadu Sivakasi626140 India Thamirabarani Engineering College Department of Eee Tamil Nadu Tirunelveli627358 India

ISBN: (纸本)9798350348460

This study undertakes a comprehensive investigation to explore strategies for replacing current dielectric liquid understanding in transformers. Understanding existing literature fosters creativity and effective research responses. The review process incorporates data and text analysis. Statistical data from 1978 to 2022 is used to understand prevailing techniques, drawn from an analysis of 80+ research publications. Contributions include Ageing 34 %, blending 20 %, additive addition 17 %, modification 8 %, gas analysis 5 %, critical dielectric testing 5 %, case studies 2 %, and others 8 %. The discussion includes 16 exclusive review papers, highlighting contributions to mixed dielectrics, nanofluids, testing manuals, modifications, and alternative fluids. This advanced study integrates materials, techniques, and standards to explore dielectric liquids, supported by accessible research journal data. The paper provides crucial data for future research. © 2024 IEEE.

关键词： CIGRE Dielectric test Ester fluids Liquid Insulation Transformers

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Comparison of entropy coders for lossless grayscale image compression

Comparison of entropy coders for lossless grayscale image co...

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2023 international conference on Data, information and Computing science, CDICS 2023

作者： Jeromel, Aljaž Žalik, Borut University of Maribor Faculty for Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9798350382778

In this paper, a comparison between three lossless entropy coders, interpolative coding combined with FELICS, arithmetic coding, and ANS coding, in terms of grayscale image compression is presented. The encoders were compared on sequences of values, produced by applying the JPEG-LS prediction to the image, and calculating the differences between the actual values and predicted values. These values were then transformed to obtain positive numbers, which can be entropy coded by the three encoders. Experimental results show that the ANS coding is the most efficient of the three, closely followed by arithmetic coding, and interpolative coding combined with FELICS. The first two entropy coders, the ANS coder and arithmetic coder, also outperformed the PNG algorithm by a small margin. © 2023 IEEE.

关键词： Image coding

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Network Traffic Prediction Mechanism Based on Variational Mode Decomposition and GA-ELM 24

Network Traffic Prediction Mechanism Based on Variational Mo...

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8th international conference on Electronic information Technology and computer engineering, EITCE 2024

作者： Zhou, Jinghe Shi, Jinmei Chen, Xue Chen, Mengyao College of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China Hainan Province Wisdom Internet of Things Engineering and Technology Research Center Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

Accurate prediction of network traffic is crucial to network resource management, whether it’s network resource provisioning or malicious attack detection, reliable network traffic prediction mechanisms are needed for advance warning existing network traffic prediction methods still have some obvious limitations, existing network traffic prediction methods still have some obvious limitations, such as high computational complexity, VMD decomposition parameter optimization problem, premature convergence into local optimum solutions, and integrated prediction model prediction accuracy is not high many problems. In response to the above, this paper presents a model that combines Variation Mode Decomposition (VMD) and Extreme Learning Machine (ELM) for predicting network traffic based on Genetic Algorithm (GA). © 2024 Copyright held by the owner/author(s).

关键词： Variational mode decomposition

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A Mathematical Model for the Selection of Software Requirements Elicitation Techniques 14

A Mathematical Model for the Selection of Software Requireme...

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14th international conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Saxena, Virat Raj Yadav, Rajeev Parveen, Azra Sadiq, Mohd. Mangalayatan University Department of Computer Science and Engineering Uttar Pradesh Aligarh202001 India Indraprastha Institute of Information Sciences Private Limited Indraprastha Research Laboratory New Delhi110025 India Upfet Jamia Millia Islamia A Central University Software Engineering Laboratory Computer Engineering Section New Delhi110025 India

ISBN: (纸本)9798350344837

Various techniques have been developed for the identification of different types of requirements like interview, questionnaire, group elicitation techniques, attributed goal-oriented requirements analysis, fuzzy based goal-oriented requirements analysis method, non-functional requirements framework, etc. Based on the critical analysis of requirements elicitation methods, we found that single elicitation technique is not suitable to understand the need of the stakeholders. In real life applications, multiple elicitation techniques are required to elicit and select the requirements of an information system because each technique has its strength and limitations. Therefore, to address this issue, this paper presents a mathematical model for the selection of requirements elicitation techniques so that complete set of requirements along with its priority can be identified before the development of an information system. The institute examination system is considered to show the applicability of the proposed mathematical model. © 2024 IEEE.

关键词： information systems

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Deep Convolutional Neural Networks for Early-Stage Detection and Prognostication of Lung and Colon Cancer 2

Deep Convolutional Neural Networks for Early-Stage Detection...

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2nd IEEE international conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Laxmikant, Kumar Arthi, A. Vinodhini, V. Natarajan, B. Bhuvaneswari, R. Selvam, Prabu Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India Karpagam College of Engineering Computer Science and Technology Coimbatore India University College of Engineering Department of Electronics and Communication Engineering Ariyalur India VIT University School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350317558

Lung and colon cancers are significant health issues across the world, prompting the need for inventive methods of diagnosis. This study takes the lead in introducing advanced Deep ConvNets (CNNs) to enhance the accuracy of early detection. The model is trained on extensive datasets, resulting in impressive outcomes. During training, it achieves an accuracy of 92.54% and a loss value of 0.0161. These results are mirrored in testing, where the accuracy reaches 96.59% and the loss value is 0.0441. Beyond just numerical achievements, this research revolutionizes cancer diagnostics by providing a sophisticated tool for personalized and early detection. This study surpasses the mere influence on individuals and extends its reach to bring hope for society and the economy by tackling the pervasive weight of cancer. It distinguishes itself in the realm of advanced medical investigation, affirming the efficacy of the model and inspiring additional inquiry, encompassing the utilization of more extensive sets of data and implementation in diverse medical domains. © 2024 IEEE.

关键词： Colon Cancer Convolutional Neural Network Lung Cancer

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Implementing Robust Color and Multispectral Image Recognition with Deep Learning

Implementing Robust Color and Multispectral Image Recognitio...

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2024 international conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Pawar, Rahul Kumar, Prafull Anand, Kul Bhushan Department of Computer Science and Information Technology Bangalore India College of Engineering Teetthanker Mahaveer University Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

this technical abstract describes the implementation of strong shade and multispectral image popularity using a deep knowledge of techniques. Via know-how, the standards, and strategies of deep getting to know, the method affords solutions to the problems of function extraction and multiclass type for green evaluation of imagery information. Particularly, the paper introduces an approach of deep studying for image recognition that combines shade and multispectral imaging. It additionally discusses the advantages of this method, which include advanced type accuracy and robustness in opposition to noise in comparison to standard procedures. The paper then outlines the architecture of the proposed model, which incorporates convolutional neural networks (CNNs), and analyzes the overall performance of the model at the Indian Pines photo database. In the end, the paper concludes with a dialogue on the implications of the proposed model and gives directions for future research. © 2024 IEEE.

关键词： Accuracy Implementation Incorporates Multispectral research Shade Technical

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Black-Litterman Portfolio Optimization with Asset Universe Given by Large Language Models

IAENG International Journal of Computer Science

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IAENG international Journal of computer science 2024年第8期51卷 976-984页

作者： Kong, Xiangxi Min, Liangyu Lin, Dijia Li, Zhen College of Business Administration Ningbo University of Finance & Economics Zhejiang Ningbo315175 China Faculty of Business Information Shanghai Business School Shanghai 201400 China School of Information Management & Engineering Shanghai University of Finance & Economics Shanghai 200433 China School of Business Putian University Fujian Putian351100 China

Generally, the Black-Litterman portfolio model relies heavily on the expert investment opinions, where highquality investment opinions would improve model performance whereas low-quality investment opinions would result in poor model performance. Essentially, expert investment opinions are highly subjective, sourcing from these financial experts’ information and knowledge. ChatGPT, as an advanced generative AI model, could extract and analyze information from huge multi-modal data, which is beneficial to build AI investment opinions for Black-Litterman portfolio model. In this study, we construct and analyze the large language model-based Black-Litterman portfolios, ChatGPTBL and BARD-BL, where the goals of minimum variance and mean-variance trade-off are taken into account. Computational results show that the ChatGPT-based portfolios tend to be conservative, which is suitable for risk-averse investors, while the BARD-based portfolios are aggressive, which is appropriate for risk-seeking investors. Also, the superiority of Black-Litterman model using investor views generating from gradient boosting regression and GJR-GARCH algorithm is illustrated by the efficient frontiers. © (2024), (international Association of Engineers). All Rights Reserved.

关键词： Investments

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Evaluation of Machine Tool Operating State Estimation using Channel State information 22

Evaluation of Machine Tool Operating State Estimation using ...

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22nd IEEE/ACIS international conference on Software engineering research, Management and Applications, SERA 2024

作者： Matsuzaki, Takanori Kato, Shinjo Asano, Yoshihiro Sako, Yuga Horiuchi, Kozo Shiratsuchi, Hiroshi Graduate School of Humanity-Oriented Science and Engineering Kindai University Fukuoka Japan Kindai University Faculty of Humanity-Oriented Science and Engineering Fukuoka Japan Gururi Co. Ltd. Fukuoka Japan

ISBN: (纸本)9798350391343

This research aims to determine whether Wi- Fi sensing, through Channel State information (CSI), can identify the operational states of an NC milling machine without the need for contact sensors. The purpose is to evaluate whether CSI can detect machine tool vibration when developing a predictive system to detect machine tool failures using Wi-Fi sensing. The prediction system detects machine tool vibration based on changes in Wi-Fi radio waves caused by machine tool vibration. If a machine tool vibrates differently than usual, the system predicts failure based on past vibration information. To ensure the experiment's reproducibility, the NC machine tool was used to test whether CSI can be used to determine the operating state of the machine tool and the object being machined. The results showed that CSI can be used to estimate a milling machine's operating and machining state. © 2024 IEEE.

关键词： Milling machines

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Interference-Protected Radio Communication System Using a Repeater 17

Interference-Protected Radio Communication System Using a Re...

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17th IEEE international conference on advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Bobalo, Yuriy Horbatyi, Ivan Lviv Polytechnic National University Department of Theoretical Radio Engineering and Radio Measurement Lviv Ukraine

ISBN: (纸本)9798331520564

Methods of ensuring interference immunity in radio relay systems, radio communication systems between ground stations and unmanned ground vehicles or unmanned aerial vehicles are considered. On the basis of the conducted analysis, it is proposed to use special signals in the system characterized by increased interference immunity, as well as to include a repeater in the system. Mathematical modeling of the radio channel between two ground stations or vehicle and a ground station has been carried out for various types of vehicles and ground stations in the absence or presence of a repeater in the system. The technical characteristics of the variants of the proposed system are calculated. Based on the results of the research, a structural diagram of an interference-protected radio communication system using a repeater is proposed. © 2024 IEEE.

关键词： Antennas

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