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Decentralization of Identities Using Blockchain 10

Decentralization of Identities Using Blockchain

引用

10th IEEE Uttar Pradesh Section International conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Srivastava, Shreshth Grover, Veena Nallakaruppan, M.K. Krishwanth, B. Saravanan, K. Customer Engineering Qualcomm Hyderabad India School of Management Studies Noida Institute of Engineering and Technology Delhi NCR Noida India School of Computer Science Engineering and Information Systems Vit University Vellore India Cyber Security Engineer Datafoundry Private Limited India Kpr Institute of Engineering and Technology Department of Mechatronics Engineering Coimbatore India

ISBN: (纸本)9798350382471

Digital Identity Management has become an essential component of federal business units today. It involves the gathering and storing of an individual's personal information entrusted to identity providers. With an increase in the number of data breaches occurring every passing year, vulnerabilities posed by technology conglomerates and social identity providers' access to personal data represent a severe cause of alarm. Blockchain Technology, with its inherent ability to prevent manipulation and unauthorized alteration of recorded information, represents an excellent solution to identity ownership concerns. This paper seeks to provide an in-depth exploration of digital identities and the use of Blockchain Technology to create a completely decentralized system of managing identities. © 2023 IEEE.

关键词： - Digital Identity Blockchain Decentralization Identity Providers Social Identity

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Leveraging Hybrid Modeling for Enhanced Runtime Prediction in Big Data Jobs

Leveraging Hybrid Modeling for Enhanced Runtime Prediction i...

引用

2024 IEEE International conference on Computing, Semiconductor, mechatronics, Intelligent Systems and Communications, COSMIC 2024

作者： Singh, Rahul Zadokar, Vivek Narayan Kumar, Sunil Doddamani, Sachin Shivaji Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory Department of Computer Science and Engineering Mangalore575025 India

ISBN: (纸本)9798331517892

In an era of rapid data expansion, big data has significantly transformed various industries, redefining the processes of data processing, analysis, and utilization. The widespread adoption of digital technologies has driven this surge in big data, leading to an unprecedented accumulation of information from sources such as social media, sensors, and transactions. As big data evolves, it presents significant challenges and unique opportunities, necessitating innovative solutions to leverage its potential fully. One critical challenge in big data environments is accurately predicting job runtimes, essential for optimizing resource utilization and enhancing overall system performance. Current approaches, including analytical models and machine learning algorithms, often need help to manage the complexities of unstructured data and maintain interpretability effectively. This paper proposes a novel hybrid modeling approach that integrates the strengths of both techniques to improve job runtime predictions. The hybrid architecture combines an analytical model, which captures the intricate characteristics of jobs and execution environments, with a machine learning model trained to detect patterns and relationships in historical data. As demonstrated on real-world big datasets, the hybrid model achieves greater accuracy by merging these capabilities. Utilizing the flexible capabilities of PySpark and incorporating advanced feature engineering techniques, the model dynamically adapts to various dataset sizes and complexities, ensuring robust performance across different scenarios. © 2024 IEEE.

关键词： Prediction models

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A Novel Method of Obstacle Detection Using Stereo Vision for Unmanned Systems 11

A Novel Method of Obstacle Detection Using Stereo Vision for...

引用

11th International scientific conference on computer science, COMSCI 2023

作者： Ortatas, Fatma Nur Sahin, Muhammet Emin Ulutas, Hasan Yakut, Ugur Koc, Yunus Yozgat Bozok University Faculty of Engineering and Architecture Department of Computer Engineering Erdoǧan Akdaǧ Campus Atatürk Road 7th Km Yozgat Turkey

ISBN: (纸本)9798350325256

Obstacle detection is an important problem in unmanned system technologies, which have been rapidly developing in recent years. In this study, a new approach to obstacle detection is presented. For use in unmanned systems, stereo vision is utilized to detect real-time obstacles on the moving path. In this method, reference points are determined by creating lines parallel to the road. By comparing the reference points with the pixel values of the searched region, the obstacle detection and distance are measured accurately. © 2023 IEEE.

关键词： Stereo vision

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Remote Sensing Classification of River Using Machine Learning Methods 12

Remote Sensing Classification of River Using Machine Learnin...

引用

12th Academic conference of Geology Resource Management and Sustainable Development, GRMSD 2024

作者： Cui, Hanwen Li, Cheng Tian, Xiaolin School of Computer Science Zhuhai College of Science and Technology Guangdong Zhuhai519041 China Academy of Interdisciplinary Studies Hong Kong University of Science and Technology 999077 Hong Kong School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology 999078 China

ISBN: (纸本)9798331314545

In the realm of global sustainable development, effective management of water resources and the protection of ecological environments have increasingly emerged as focal points for both governmental and international organizations. Rivers, as critical conduits of water resources, fulfill various essential functions, including transportation, irrigation, aquaculture, tourism, and climate regulation, in addition to their provision of water for human consumption and agricultural purposes. This study predominantly explores the application of remote sensing technology and machine learning methodologies to classify rivers. The research is situated in Zhuhai City, characterized by a vertically distributed river network. It employs eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), both based on gradient boosting decision trees (GBDT). The data source for this investigation consists of high spatial resolution imagery from Gaofen-2 (GF-2) remote sensing satellites. The results indicate that both models achieve an overall accuracy (OA) exceeding 96.50%, with Kappa coefficients surpassing 0.92. Notably, the LightGBM model demonstrates superior performance over XGBoost in terms of both classification accuracy and operational efficiency. The utilization of remote sensing images in conjunction with machine learning techniques for the classification and monitoring of rivers offers a robust scientific framework for enhancing water resource management. Furthermore, these methodologies can assist in the formulation of effective strategies for the sustainable utilization and protection of water resources. © 2024 Proceedings of the 12th Academic conference of Geology Resource Management and Sustainable Development, GRMSD 2024. All rights reserved.

关键词： Rivers

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Evaluation of Global Sizes and Cylindricity Errors Based on fminimax Optimization Function 2

Evaluation of Global Sizes and Cylindricity Errors Based on ...

引用

2nd International conference on Automation, Robotics and computer engineering, ICARCE 2023

作者： Zhao, Xinyu Zhao, Zexiang Ren, Dongxu School of Computer Science Zhongyuan University of Technology Zhengzhou China School of Mechatronics Engineering Zhongyuan University of Technology Zhengzhou China Technology for Mechanical Industry Key Laboratory of Optical Sensing and Testing Zhengzhou China

ISBN: (纸本)9798350308341

Based on the evaluation definitions of minimum circumscribed, maximum inscribed and minimum zone methods for global sizes and cylindricity errors of cylinder, the optimization objective function of the axis parameters of the reference cylindrical surfaces and the evaluation models of global sizes and cylindricity errors were built. The subprograms for the optimization objective functions of the axis parameters of the reference cylindrical surfaces and the evaluation of global sizes and cylindricity errors were written by using Matlab language. The roundness profiles of four cylindrical samples were extracted, and their global sizes and cylindricity errors were evaluated based on least square, minimum circumscribed, maximum inscribed and minimum zone methods. The evaluation results of the optimization characteristic values of fminimax optimization function were compared with those evaluated by using other optimization methods, and it turned out that the accuracy of the optimization objective characteristic values of fminimax optimization function are higher or equal to those evaluated by other optimization methods, which is suitable to the application in the evaluation of global sizes and cylindricity errors. © 2023 IEEE.

关键词： Least squares approximations

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Brown Marmorated Stink Bug Detection Using Multiple Neural Networks

Brown Marmorated Stink Bug Detection Using Multiple Neural N...

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

作者： Vicol, Andrei Ichim, Loretta Popescu, Dan University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9798350322972

The identification and management of pest infestations in a timely manner have been an ever-pressing issue, more so than ever now, when new pests have arrived from around the world and governments are encouraging farmers to use fewer and fewer pesticides. The use of drones and artificial intelligence in the monitoring of orchards has taken a strong rise in recent years due to the advantages offered by efficiency, coverage, and price. A particularly dangerous insect in fruit production is the brown marmorated stink bug (BMSB). The paper seeks to look at a performance comparison in BMSB detection between three states of the art models of image detection and classification: MobileNetV2, Xception, and EfficientNet. Each network model was slightly modified being thus adapted for this application and the results obtained had high accuracy, between 97% and 99%. © 2023 IEEE.

关键词： Orchards

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How Large Language Models are Transforming Teachers' Assessment of Student Competency: A Case Study on LLM-Based Report Writing

How Large Language Models are Transforming Teachers' Assessm...

引用

2025 International conference on Electronics, Information, and Communication, ICEIC 2025

作者： Lee, Dongyub Kim, Daejung Loeser, Martin Seo, Kyoungwon Seoul National University of Science and Technology Department of Applied Artificial Intelligence Seoul Korea Republic of Seoul National University of Science and Technology Department of Environmental Engineering Seoul Korea Republic of Electrical Engineering and Mechatronics ZHAW Zurich University of Applied Sciences Department of Computer Science Winterthur Switzerland

ISBN: (纸本)9798331510756

Evaluating student competencies is critical to fostering academic success, but the traditional process of assessment and report generation is time-consuming and labor-intensive for teachers. The emergence of Large Language Models (LLMs) presents an opportunity to automate this process, potentially reducing the workload for educators. However, concerns such as hallucinations in LLM outputs and the lack of usability studies involving teachers raise questions about their reliability and practical application. In response, we developed an LLM-based report writing system specifically designed for real-time competency evaluation. To assess its effectiveness, we conducted a case study involving five educational experts, each with over 15 years of experience. These experts used the system to generate student competency reports and found them to be both sensible and specific. While they expressed concerns about issues like insufficient detail, they recognized the system's significant time-saving benefits. Our findings demonstrate that LLMs can positively impact teachers' competency assessments by streamlining the reporting process, offering valuable support for educators. © 2025 IEEE.

关键词： Students

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Line-Start Permanent Magnet Machines for Low-Power Applications

Line-Start Permanent Magnet Machines for Low-Power Applicati...

引用

2024 International conference on Electrical Machines, ICEM 2024

作者： Barta, Jan Toman, Marek Losak, Petr Aarniovuori, Lassi Vitek, Ondrej Brno University of Technology Department of Power Electrical and Electronic Engineering Brno Czech Republic Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic Electrical Engineering LUT University Lahti Finland

ISBN: (纸本)9798350370607

The improvement of efficiency is one of the main areas of research in electrical machines today. Three-phase induction machines are widely used in industry, motivating researchers to explore methods to increase their efficiency or replace them with more efficient alternatives. A line-start synchronous machine is a promising machine design for achieving high-efficiency classes even for low-power applications. The main contribution of this paper is to show the achievable performance of the LSPMSM by simply replacing the rotor of an induction machine. In this work, two different geometries suitable for low-power machines are optimized and studied in terms of electromagnetic parameters. Finally, the results of the start-up simulations for both machine designs are presented. The presented method shows that by replacing the induction machine rotor with a line-start permanent magnet rotor, it is possible to significantly enhance machine efficiency, even for low-power applications. © 2024 IEEE.

关键词： Permanent magnets

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Control device of pepper picker based on truss manipulator 24

Control device of pepper picker based on truss manipulator

引用

8th International conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Ji, Xiang Gao, Rucheng Zheng, Bing Shi, Jinmei Li, Qi Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

A picker control device based on a truss manipulator integrates the information of various sensors such as force sense, temperature sense, vision and distance, and timely feedback information to realize the flexible picking of pepper fruit ears by the executive parts. The hardware device consists of a computer vision control system, an industrial control system, a robotic arm and an end actuator. Coordinate various parts of the image, identification module, LiDAR, induction switch, temperature and humidity module, wireless communication module, truss structure and end grabbers, etc., to realize the identification and positioning of the detected object, the acquisition and reporting of the working environment and operating state of the equipment, the accurate control of the structure, and the multi-axis linkage control functions. Automated pepper picking to help agricultural production. © 2024 Copyright held by the owner/author(s).

关键词： Robotic arms

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Development of science Virtual Reality Lab Simulation (SVLS): Enhancing Immersive Experiences 9

Development of Science Virtual Reality Lab Simulation (SVLS)...

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Joint 9th International conference on Digital Arts, Media and Technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Litchaweerat, Supanat Khenda, Prasopsuk Intayoad, Wacharawan Tongpaeng, Yootthapong Putjorn, Pruet Mae Fah Luang University Software Engineering Chiang Rai Thailand Mae Fah Luang University Center of Excellence in Ai and Emerging Technologies School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9798350318241

In order to improve student learning in primary science laboratories, this pilot study explores the development and application of a Virtual Reality (VR) simulation system called science Virtual Lab Simulation (SVLS). Unlike traditional teaching approaches, SVLS is designed to provide an engaging and interactive environment that helps young learners better understand scientific concepts. Three crucial components of virtual reality (VR) in education are highlighted by the study's methodology: the system's overall usability, the interaction between users and VR technology, and the learning experience itself. The results showed students' desire and enthusiasm to learn were increased by the VR environment, which made scientific concepts easier to understand. The study suggested that the active use of VR technology may contribute to enhancing science education by potentially making learning more engaging and enjoyable. The user-friendliness and intuitiveness of the VR system appeared to play a role in its effective integration into learning environments. Additionally, the research highlighted the importance of designing VR systems with interfaces and instructions that are considerate of the cognitive and physical abilities of young students, though further studies are recommended to fully understand these impacts. To summarize, the SVLS prototype showcases how VR may revolutionize the teaching of primary science. It highlights how well built VR systems can greatly enhance various elements of education, including learning engagement, technological interaction, and overall academic outcomes. © 2024 IEEE.

关键词： Virtual reality

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