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检索条件"任意字段=International Conference on Advances in Intelligent Control and Computer Engineering"

共 47502 条记录，以下是111-120 订阅

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Invariant Set Analysis and control Synthesis of Multi-Equilibrium Switched Systems under control Constraints 13

Invariant Set Analysis and Control Synthesis of Multi-Equili...

引用

13th international conference on intelligent control and Information Processing, ICICIP 2025

作者： Han, Yuejiang Zhang, Lixian Ding, Yihang Dong, Yifei Liang, Ye School of Astronautics Harbin Institute of Technology Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798331516147

This paper investigates the problems of invariant set analysis and control synthesis for multi-equilibrium switched systems under control constraints. A control strategy based on the invariant set method is proposed, accompanied by criteria formulated as linear matrix inequalities, ensuring that the state remains within the mode-dependent invariant sets. Furthermore, considering the control constraints in practical scenarios, a multi-equilibrium switched controller with control constraints (MESCC controller) is designed. Compared to existing works, the proposed method incorporates mode-dependent dwell time conditions and mode-dependent invariant sets, thereby offering enhanced design flexibility. An example of an aero-engine control system is presented to demonstrate the effectiveness and potential of the theoretical results. © 2025 IEEE.

关键词： control system synthesis

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AI Principles in Practice with a Learning engineering Framework 17

AI Principles in Practice with a Learning Engineering Framew...

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17th international conference on computer Supported Education, CSEDU 2025

作者： Van Campenhout, Rachel Brown, Nick Johnson, Benny VitalSource 227 Fayetteville Street RaleighNC United States

ISBN: (纸本)9789897587467

With the explosion of generative AI, rapid innovation in educational technology can lead to extraordinary advances for teaching and learning-as well AI tools that are ineffective or even harmful to learning. AI should be used responsibly, yet defining responsible AI principles in an educational technology context and how to put those principles into practice is an evolving challenge. Broad AI principles such as transparency, accountability, and human oversight should be paired with education-specific values. In this paper, we discuss the development of AI principles and how to put those principles in practice using learning engineering as a framework, providing examples of the application of responsible AI principles in the context of developing AI-generated questions and feedback. Frameworks to support the rapid development of innovative technology-and the responsible use of AI-are necessary to ground learning tools' efficacy and ensure their benefit for learners. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Educational robots

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A comprehensive review of recent advances and challenges in artificial intelligence and machine learning 4th

A comprehensive review of recent advances and challenges in ...

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4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Singla, Ishdeep Hans, Aarti Smiksha Diya Swami, Harsh Kumar Ranjan, Rahul Computer Science and Engineering Chandigarh University Mohali Gharuan India

ISBN: (纸本)9781032911571

Modern advances in Artificial Intelligence (AI) and Machine Learning (ML) have transformed many businesses and elements of everyday life. Machine learning and deep learning support disease diagnosis, drug development, and patient risk assessment. This study examines how healthcare organizations evaluate enormous data sets using machine learning. This paper examines pros and downsides of current methods and research obstacles. Our goal is to educate healthcare professionals and government organizations on machine learning-based big data analytics in intelligent healthcare. AIML-powered chatbots enable governments educate and serve residents. They assist people get permits, answer questions, and use government services. Assistants help students make appointments, answer inquiries, and offer course material. Lead generation, product recommendations, and marketing efforts using AIML chatbots may boost revenue. AIML helps companies make data-driven decisions, find patterns, and recognize trends using data analysis and predictive analytics. Machine Learning studies how computers learn and improve without programming. Machine learning (ML) is a very captivating technology that has garnered significant interest over the course of technological advancements. As indicated by its nomenclature, this attribute endows the computer with a capacity that enhances its resemblance to human behaviour: the ability to acquire knowledge. © 2025 the Author(s).

关键词： Adversarial machine learning

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Blockchain based File Storage and File Sharing System with Time-Restricted Access using InterPlanetary File System 3

Blockchain based File Storage and File Sharing System with T...

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3rd international conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Venkat Prashanth, M. Hemesh Verma, K. Chauhan, Jaykishor Prasad Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (纸本)9798331527549

This paper presents a file storage and sharing system implemented using IPFS Pinata, *** and Hardhat which offer decentralized, effective, and secure access to digital assets. This system also enables the ability to upload files to the IPFS network for distributed storage and the ability to share them with peers . It also implements a time based access control system using smart contracts to easily control access to the files uploaded. This innovation improves security and facilitates timely exchange of information while also eradicating the necessity of having to manage access. This is due to the versatility of blockchain’s unalterable nature together with IPFS distributed file-sharing system which provides a secure file-sharing method while keeping costs low and helps maintain adaptability. © 2025 IEEE.

关键词： Blockchain decentralized IPFS secure access Time Based Access Conrol

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computer-Assisted Knowledge Points and Question Difficulty Classification Based on BERT

Computer-Assisted Knowledge Points and Question Difficulty C...

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2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Zhu, Jia Jun Yang, Zichuan Hong, Binjie Song, Jiacheng Wang, Jiwei Chen, Tianhao Yang, Shuilan Lan, Zixun Ma, Fei Department of Information and Computing Science Xi'an Jiaotong-Liverpool University Suzhou China School of Engineering Suzhou Centennial College Suzhou China Department of Applied Mathematics Xi'an Jiaotong-Liverpool University Suzhou China GROW Inc. Suzhou China EasyStack Inc. Nanjing China TAL Education Group Beijing China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

In recent years, with the increasing use of educational technology and online learning platforms, there has been a growing interest in developing intelligent systems that can automatically predict the knowledge points associated with educational questions. This paper presents a novel approach for knowledge point prediction in middle school mathematics questions. The dataset used in this study consists of a large collection of 591,379 middle school mathematics questions. To leverage the power of natural language processing techniques, the questions are preprocessed using a tokenizer and encoded into word embeddings using BERT (Bidirectional Encoder Representations from Transformers). Matrix dot production is then employed to calculate the similarity between each test question and the training set, and the top-n most similar vectors are selected for each test question. A voting mechanism is introduced to eliminate duplicate knowledge points and rank them based on their total scores in descending order, resulting in k candidate solutions. The performance of the proposed approach is evaluated using top-k accuracy as the evaluation metric and a lowest common ancestor (LCA) algorithm is used to calculate accuracy at different levels of the knowledge point tree. The results demonstrate the effectiveness of the proposed approach in predicting knowledge points for middle school mathematics questions and its potential for application in intelligent tutoring systems and educational assessment tools. © 2025 SPIE.

关键词： Natural language processing systems

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Assessment and Management of Security Risks in Accounting Information Systems from a Lifecycle Perspective

Assessment and Management of Security Risks in Accounting In...

引用

2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Gong, Lijiahui Business School Wuhan Huaxia Institute of Technology Wuhan430223 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

As the carrier of information assets, the importance of accounting information systems is increasing with the development of informatization. Meanwhile, information systems are facing more security threats. How to effectively ensure the security of information systems and prevent information assets from being stolen or damaged has become an inevitable challenge. Therefore, conducting research on the security issues of information systems is of great significance. In response to the data security risks in accounting information systems, this article first establishes a risk indicator system and proposes an information system risk assessment model based on adaptive fuzzy neural networks, which scores the risk indicator attributes during the assessment process. In addition, we propose a fine-grained weight adaptive adjustment algorithm in the model, which provides a quantitative method for the risk indicators of accounting information systems. The feasibility and applicability of the model have been verified through simulation testing. © 2025 SPIE.

关键词： Information security Risk assessment Network security computer security Computing systems Fuzzy logic Situational awareness sensors Neural networks Systems modeling Prototyping

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IoT-Based Transfer Learning and Genetic Algorithm Approaches for Smart Environmental Pollution Detection and Management 5

IoT-Based Transfer Learning and Genetic Algorithm Approaches...

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5th IEEE international conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Alauddin, Shafqat Sree Vidhya, S. Pragadeeswaran, S. Sowjanya, P. Bhokare, Rajashree Khan, Maaz Allah Shibli National College Department of Chemistry Uttar Pradesh Azamgarh India Erode Sengunthar Engineering College Department of Computer Science and Engineering Tamilnadu Thudupathi India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai India Department of Ece Telangana Dhulapally India Dr. D. Y. Patil Institute of Technology Department of Electrical Engineering Pimpri Maharashtra Pune India Department of Engineering & Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9798350356236

The identification of environmental pollution remains to be a significant issue, as conventional technologies lack scalability and flexibility to dynamic, real-time situations. This study presents an IoT-enabled hybrid model that combines transfer learning and genetic algorithms to overcome these restrictions. IoT networks enable real-time, extensive data acquisition, whereas transfer learning uses pre-trained models for effective feature extraction and domain adaption. Genetic algorithms enhance hyperparameters and sensor configurations, guaranteeing energy economy and optimal model performance. The suggested CNN-LSTM architecture utilising multi-scale attention attains a training accuracy of 95.6% and an F1 score of 0.96, exceeding the performance of conventional Random Forest and CNN models in accuracy, recall, and precision. The comparative study confirms the model's strength and flexibility, illustrating its capacity for scaled, practical applications. This framework creates a dependable and effective system for intelligent environmental pollution control, providing substantial improvements in detection accuracy and operational efficacy compared to current methods. © 2025 IEEE.

关键词： Environmental management

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Blockchain-Enabled Supply Chain Management with Role-Based Access control and AES Encryption

Blockchain-Enabled Supply Chain Management with Role-Based A...

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2025 international conference on Computing for Sustainability and intelligent Future, COMP-SIF 2025

作者： Dharshan, J.Y. Amarnath, Arjun R. Reddy, Pothamsetti Sai Srujan Rajagopal, Shinu M. Prashanth, Mrudula Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Mechanical Engineering Bengaluru India

ISBN: (纸本)9798331538538

Blockchain-Enabled Supply Chain Management with Role-Based Access control and AES Encryption will use blockchain technology in order to enable safe, transparent, and decentralized supply chain management. Using smart contracts deployed on Polygon Amoy Testnet, the system ensures data integrity, confidentiality, and traceability while implementing role- based access control (RBAC) in order not to give unauthorized access to data. AES encryption is set forth for secretive treatment of information, thus affording a double-layered security measure for protection against on-chain as well as off-chain transactions. The solution is intended for deployment and testing in both localhost environments for rapid prototyping and the Polygon Amoy Testnet for scalable and distributed implementation. The Polygon Amoy Testnet provides an inexpensive development environment: developers can acquire test tokens (0.807 POL) via the Polygon Faucet for complete testing purposes. Deployment and interactions of smart contracts can be checked via the Polygon Testnet Explorer. The project combines blockchain's immutability with cryptographic security to address traditional supply chain inefficiencies, enhancing trust, scalability, and data accuracy. © 2025 IEEE.

关键词： Authentication

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Development of Real-Time Oxygen and Temperature Monitoring System with CI/CD Pipeline Integration and HMI 1

Development of Real-Time Oxygen and Temperature Monitoring S...

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1st international conference on advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kolte, Gaurav Amar Gunnal, Aditya Kolhare, Nilima R. COEP Technological University Dept. of Electronics and Telecommunication Engineering Pune411005 India COEP Technological University Dept. of Instrumentation and Control Engineering Pune411005 India

ISBN: (纸本)9798331518578

The steel manufacturing industry stands as the backbone of global infrastructure development, providing the raw materials essential for constructing everything from skyscrapers to automobiles. Central to this industry's efficiency is the performance of its furnaces, where the transformation of raw materials into high-quality steel occurs. Steel furnace environments require precise monitoring of parameters like temperature and oxygen levels to ensure efficiency, safety, and compliance with environmental standards. This paper presents a novel monitoring device designed to address these needs while incorporating modern software development practices. The device offers real-time monitoring and graph visualization of temperature and oxygen levels, surpassing conventional methods. It introduces the integration of Git, Continuous Integration/Continuous Deployment (CI/CD) pipelines, Real-Time Operating Systems (RTOS) and diagnostic tools, enhancing reliability and facilitating seamless updates. This amalgamation of hardware and software engineering replaces outdated monitoring systems. Through its multifaceted capabilities, this research contributes significantly to the evolution of smart, interconnected industrial systems, promising improved performance and safety in steel furnace operations. The NXP LPC 55s69 micro-controller unit is used for the computation of oxygen and temperature from a zirconia-based oxygen sensor and thermocouple using nernst-einstein equation. For integration of the device with a PLC control we have used RS232 and RS485 communication protocols. © 2025 IEEE.

关键词： Thermocouples

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Next-Gen Energy Management: IoT Gateway for Smart Monitoring and Appliance control 6

Next-Gen Energy Management: IoT Gateway for Smart Monitoring...

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6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Kabra, Sohum Nadagouda, Prithvi Nikam, Yash Kavedia, Manoj S. Thadomal Shahani Engineering College Mumbai India Thadomal Shahani Engineering College Mumbai India

ISBN: (纸本)9798331522667

This research study proposes an IoT-based solution for intelligent energy management, designed to monitor and optimize power consumption in both residential and industrial environments. The system will integrate an AI meter for real-time tracking of voltage, current, and power usage, alongside environmental sensors that measure parameters like temperature, humidity, light intensity, and motion. These data inputs are processed by an IoT gateway based on an ESP32 microcontroller and Raspberry pi, which will handle the data locally or transmits it to a cloud-based or edge machine learning model. The machine learning model analyzes real-time sensor data combined with historical consumption patterns to predict and implement optimal appliance control strategies. The system aims to reduce power consumption by up to 20-25%, contributing to energy efficiency without compromising operational performance and delays. Appliances are controlled remotely using IR Blasters and relays, allowing for dynamic, real-time adjustments based on environmental factors. The solution is scalable, making it applicable for both household energy management and large-scale warehouse automation. By utilizing predictive analytics and intelligent control, the system optimizes energy usage, offering a sustainable, automated solution for modern smart homes and industries. This integration of IoT and machine learning provides a significant step toward more efficient and sustainable energy management practices. © 2025 IEEE.

关键词： Gateways (computer networks)

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