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检索条件"任意字段=International Conference on Computer Engineering and Technology"

共 440832 条记录，以下是441-450 订阅

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Research on the Application of Intelligent Analysis System in the Promotion of Evaluation Indicators for the Development of New Rural Cultural Industries - Analysis of the Promotion Path and Key Elements Integrating TPB, TAM and DOI 24

Research on the Application of Intelligent Analysis System i...

引用

8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Li, Jiayao Hu, Yubo Ji, Haokang Zhang, Yuchen College of Art and Communication China Jiliang University Zhejiang Hangzhou China Hubei University of Science and Technology Hubei Xianning China FutureFront Interdisciplinary Research Institute Huazhong University of Science and Technology Hubei Wuhan China

ISBN: (纸本)9798400710094

This article examines the application of intelligent analysis systems in the promotion of evaluation indicators for the development of the cultural industry in new rural areas. As China places emphasis on rural revitalization and the integration of cultural industries, the lack of scientific and quantitative evaluation standards has become a challenge to the development of the cultural industry in new rural areas. This study employs the Analytic Hierarchy Process (AHP) to establish a set of evaluation indicators and constructs a hybrid model combining the Theory of Planned Behavior (TPB), technology Acceptance Model (TAM), and Diffusion of Innovations (DOI) to analyze the acceptance, adaptability, and effectiveness of these indicators in the promotion process. Through a pilot study in Wenzhou City, Zhejiang Province, this research utilizes an intelligent analysis system to collect and analyze data, aiming to provide strategic recommendations to enhance the acceptance and usage rate of evaluation indicators for the development of the cultural industry in new rural areas. © 2024 Copyright held by the owner/author(s).

关键词： Evaluation Indicators

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Analysis of Metaheuristic Optimization Algorithms for Solving Vehicle Routing Problem with Time Windows 1

Analysis of Metaheuristic Optimization Algorithms for Solvin...

引用

1st international conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Arora, Sandhya Pimprale, Varsha Deshmukh, Nutan MKSSS's Cummins College of Engineering for Women Department of Computer Engineering Pune India

ISBN: (纸本)9798350355611

The Vehicle Routing Problem with Time Windows (VRPTW) is a key optimization challenge in operations research and logistics. It extends the traditional Vehicle Routing Problem (VRP) by incorporating specific time windows within which customers must be served. The objective is to determine the most efficient routes for a fleet of vehicles, minimizing costs while meeting constraints, including time restrictions. This paper investigates the application of metaheuristic algorithms, such as Tabu Search, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Iterated Local Search (ILS), to solve the VRPTW. It covers the problem formulation, the implementation of various metaheuristic techniques, and a comparative analysis of their performance. Through this analysis, the research highlights the strengths and weaknesses of each algorithm, providing valuable insights for practical applications in logistics and transportation. © 2025 IEEE.

关键词： Genetic algorithms

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Research on muscle fatigue classification based on principal component analysis-random forest algorithm 24

Research on muscle fatigue classification based on principal...

引用

8th international conference on Electronic Information technology and computer engineering, EITCE 2024

作者： Pang, Peng Tang, Leilei College of Electrical and Information Engineering Heilongjiang University of Technology Heilongjiang Jixi China

ISBN: (纸本)9798400710094

In order to solve the problem of low accuracy of muscle fatigue classification using surface electromyography (sEMG), a fatigue classification model based on principal component analysis of surface electromyography and random forest algorithm was proposed. Firstly, the surface EMG signal is pre-processed by de-noising, and then the time domain, frequency domain and time-frequency domain features are extracted. Principal component analysis in feature extraction was used for feature dimensionality reduction, three effective principal components were extracted, and features with high contribution to the model were screened combined with the variable importance ranking results of random forest algorithm. The screened joint feature parameters were input into the classifier, and 8 subjects were tested to verify the rationality of the proposed method. The experimental results showed that: By optimizing the parameters, the classification accuracy of the random forest algorithm based on principal component analysis is increased by 5% to 93.3% compared with the simple random forest algorithm, which proves that the proposed method has excellent effect in the classification of muscle fatigue. © 2024 Copyright held by the owner/author(s).

关键词： Dimensionality reduction

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A Transparent Diagnosis Model for Diabetic Retinopathy Using Explainable AI

A Transparent Diagnosis Model for Diabetic Retinopathy Using...

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2025 IEEE international conference on Computational, Communication and Information technology, ICCCIT 2025

作者： Deo, Arpit Gupta, Priyasha Rajput, Ajeet Singh Sil, Devyani Chandorikar, Chirag Pawar, Mirth Medi-Caps University Department of Computer Science and Engineering Madhya Pradesh Indore453331 India Institute of Engineering & Technology Devi Ahilya Vishwavidyalaya Department of Computer Engineering Madhya Pradesh Indore452017 India

ISBN: (纸本)9798331512965

Diabetic retinopathy is the leading cause of vision problems and partial blindness, and its signs are complicated and variable, making detection difficult. Standard diagnosis is mainly reliant on expert interpretation of retinal images, which can lead to bias and mistake, highlighting the need for improved diagnostic approaches. Despite the fact that conventional AI technologies considerably improve diagnostic skills, their black box aspect limits healthcare practitioners' confidence and optimizes their usage in practice. Grad-CAM++ is a new technique that addresses the black box problem by improving model knowledge, allowing users to grasp the reasoning behind specific decisions. Using XAI approaches, this work creates a diagnostic model for diagnosing diabetic retinopathy, hence improving transparency. The proposed model's convergent plots validate the learning process, which results in 94.4% better diagnostic precision than previous approaches. © 2025 IEEE.

关键词： artificial intelligence convolutional neural network diabetic retinopathy Gradient-Weighted Class Activation Mapping (Grad-CAM++)

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Permissioned Blockchain Security Pqfabric from Quantum and Classical Attacks 1

Permissioned Blockchain Security Pqfabric from Quantum and C...

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

作者： Tamilarasi, C. Bhavadrarani, K. Kittappa, Thiagarajan Subashini, N. Anitha, V. Vimalraj, E. B.S.Abdur Rahman Crescent Institute of Science & Technology Department of Computer Science and Engineering Chennai India V.S.B. Engineering College Department of Computer Science and Engineering Karur India Rajalakshmi Institute of Technology Department of Mathematics Chennai600124 India Sathyabama Institute of Science and Technology Department of Mathematics Chennai600119 India Panimalar Engineering College Department of CSE Poonamallee Chennai600123 India School of Computing Mohan Babu University Andhra Pradesh Tirupati India

ISBN: (纸本)9798331518578

Old style cryptographic techniques are genuinely compromised by the development of quantum computing, which requires the formation of safety ideal models that are impervious to quantum mistakes. A new permissioned blockchain security system called PqFabric is intended to oppose both traditional and quantum attacks. PqFabric ensures the validness, mystery, and respectability of exchanges in a quantum-empowered future by including post-quantum cryptographic techniques like hash-based and grid based marks. As opposed to ordinary blockchains, PqFabric utilizes a half breed agreement process that gets information trades and members characters by melding Byzantine Fault Tolerance (BFT) with quantum-safe encryption. The system gives protection against calculation based attacks by Shor and Grover, tending to huge imperfections in existing blockchain structures. Besides, when quantum-safe guidelines advance, its secluded plan empowers smooth enhancements. With this procedure, PqFabric is situated as a ground breaking answer for organizations and areas wishing to safeguard their blockchain networks from new cryptographic risks. © 2025 IEEE.

关键词： Quantum computers

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Enhancing 3D Modeling Quality Through Orthorectified Image Accumulation

Enhancing 3D Modeling Quality Through Orthorectified Image A...

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

作者： Kwag, Cheolsu Kim, Euntaek Lee, Yongsuk Jung, Seungmin Hwang, Sung Soo Ryu, Hwangryol Moon, Youngmin Handong Global University Dept. of Computer Science and Electrical Engineering Pohang Korea Republic of School of Computer Science and Electrical Engineering Handong Global University Pohang Korea Republic of Research Institute of Industrial Science and Technology Smart Engineering Research Laboratory Pohang Korea Republic of

ISBN: (纸本)9798331510756

This study introduces a novel methodology designed to facilitate the capture of comprehensive image datasets, crucial for accurate 3D modeling of expansive indoor spaces. Leveraging orthophotos generated from panoramic camera data and visualizing image coverage density through heatmaps, our approach effectively identifies under-captured and unvisited areas. This enables targeted image acquisition, minimizes redundant reshoots, and enhances the overall quality and fidelity of 3D models. © 2025 IEEE.

关键词： Digital elevation model

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Comparative Analysis of Contextual AI for Political Tweets 1

Comparative Analysis of Contextual AI for Political Tweets

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1st international conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Khatavkar, Vaibhav Petkar, Sneha Vaidya, Archana Institute of Management Computer Engineering Department MH Pune India Computer Engineering GES Sapat COE MH Nashik India

ISBN: (纸本)9798350355611

This paper provides a comprehensive survey of Contextual AI applications for analyzing political discourse on Twitter, focusing on the latest advancements in Natural Language Processing (NLP) and machine learning models. Analyzing Twitter data, with its informal language and rapid content generation, presents challenges like sarcasm, slang, and polarization. Contextual AI models, such as BERT and GPT-based architectures, offer significant improvements in political sentiment detection, emotion analysis, and bias identification. Key studies surveyed in this paper report high performance: the PoliBERT model achieved an F1 score of 0.95 and a precision of 0.96, while the sentiment analysis of political opinions showed balanced metrics with an F1 score of 0.89 and an accuracy of 0.88. A study on detecting political leanings achieved a 99% confidence level with an accuracy of 0.96 and ROC AUC of 0.95. These results demonstrate the potential of Contextual AI for accurately classifying political biases, real-time sentiment analysis, and handling complex language nuances. Future research should focus on real-time multilingual analysis, ethical considerations, and bias mitigation. This survey highlights the importance of Contextual AI in providing more precise, nuanced, and inclusive insights into political discourse on social media. © 2025 IEEE.

关键词： Tweets

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ElderEase AR: Enhancing Elderly Daily Living with the Multimodal Large Language Model and Augmented Reality 24

ElderEase AR: Enhancing Elderly Daily Living with the Multim...

引用

2024 international conference on Virtual Reality technology, ICVRT 2024

作者： Song, Tianyu Liu, Zhengyi Zhao, Ruibin Fu, Jie Department of Computer Science and Technology School of Computer Science and Technology Intelligent Perception Group Anhui University Anhui Hefei China Chuzhou University Anhui Chuzhou China Department of Computer Science and Technology School of Computer Science and Technology Artificial Intelligence Group Anhui University Anhui Hefei China Department of Computer Science and Technology School of Information Engineering Intelligent Perception Group Chuzhou University Anhui Chuzhou China

ISBN: (纸本)9798400710186

Elderly individuals often face challenges in independent living due to age-related cognitive and physical decline. To address these issues, we propose an innovative Augmented Reality (AR) system, "ElderEase AR", designed to assist elderly users in their daily lives by leveraging a Multimodal Large Language Model (MLLM). This system enables elderly users to capture images of their surroundings and ask related questions, providing context-aware feedback. We evaluated the system’s perceived ease-of-use and feasibility through a pilot study involving 30 elderly users, aiming to enhance their independence and quality of life. Our system integrates advanced AR technology with an intelligent agent trained on multimodal datasets. Through prompt engineering, the agent is tailored to respond in a manner that aligns with the speaking style of elderly users. Experimental results demonstrate high accuracy in object recognition and question answering, with positive feedback from user trials. Specifically, the system accurately identified objects in various environments and provided relevant answers to user queries. This study highlights the powerful potential of AR and AI technologies in creating support tools for the elderly. It suggests directions for future improvements and applications, such as enhancing the system’s adaptability to different user needs and expanding its functionality to cover more aspects of daily living. © 2024 Copyright held by the owner/author(s).

关键词： Augmented reality

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Analysis of Brain Health Using Machine Learning and Artificial Intelligence technology: Modern Drug Discovery Perspective 1

Analysis of Brain Health Using Machine Learning and Artifici...

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

作者： Thirunagalingam, Arunkumar Usha, M.S. Geetha, S. Dhanamathi, A. Dhivya, S. Thendral, M.Tamil Business Intelligence and Reporting B. S. Abdur Rahman Crescent Institute of Science and Technology Department of CSE Chennai600048 India VS.B. ENGINEERING COLLEGE Department of Computer Science and Engineering Karur India Roever Engineering College Department of CSE Perambalur621220 India Sri Venkateswara College of Engineering Department of Computer Science and Engineering Sriperumbudur India Bannari Amman Institute of Technology Department of Information Technology Sathyamangalam India

ISBN: (纸本)9798331518578

The creation and discovery of pharmaceuticals may be considered the most important translational science activity that improves human invulnerability and happiness. In the pharmaceutical sector, strategies to reduce costs and speed up the development of new drugs have sparked a rigorous and fascinating brainstorming session. The use of classified big data in conjunction with remarkably improved computer power and cloud storage has enabled the application of artificial intelligence (AI), particularly the deep-learning (DL) component, in all domains. In healthy individuals, ML evaluation of neuroimaging data may accurately predict ordered age;illness and mental impairment have been linked to departures from normal brain maturation. Convolutional neural networks (CNN), a DL-based predictive display technique, were applied to both pre-handled and raw T1-weighted X-ray data in order to further evaluate the eligibility of 'brain-predicted age' as a biomarker of individual contrasts in the brain ageing process. Brain-predicted age is a very accurate, remarkably stable, and genetically valid trait that exhibits assurance as a biomarker of brain maturation. Additionally, age may be accurately predicted from raw T1-MRI data, which greatly reduces the amount of time needed to compute fresh data and accelerates the process of delivering immediate data on brain health in clinical settings. © 2025 IEEE.

关键词： Electronic health record

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Mitigating Transformer Inrush Currents Using Passive Magnetic Fault Current Limiter

Mitigating Transformer Inrush Currents Using Passive Magneti...

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2025 international conference on computer, Electrical and Communication engineering, ICCECE 2025

作者： Mondal, Asit Kumar Santra, Tapan Daphadar, Tirtha Sankar Haldia Institute of Technology Department of Electrical Engineering WB Haldia India Kalyani Government Engineering Department of Electrical Engineering Kalyani WB Nadia India College of Engineering & Management Department of Electrical Engineering WB Kolaghat India

ISBN: (纸本)9798331513894

Transformer inrush current, a transient phenomenon characterized by high peaks and harmonic content that happens during energization, can have a big effect on how the power system works. It can result in core saturation, protective relay malfunctioning issues, and excessive stresses on transformer windings. Because transformer inrush current has a major effect on protection systems, it has been the focus of much research. To minimize this problem, a novel Passive Magnetic Fault Current Limiters, or PMFCLs, offer a viable remedy. To reduce transient currents, the PMFCL adds dynamic impedance in series with the transformer using the magnetic saturation principle. This paper examines the effects of passive MFCLs on power system performance and examines how well they restrict transformer inrush current, thereby improving the performance and reliability of transformer protection systems. First the PMFCL's construction and operation are examined and the ANSYS Maxwell software and finite-element analysis(FEA) was used for the PMFCL design. Then MATLAB/Simulink is used to do comprehensive simulations for the transformer's inrush current mitigation with and without proposed PMFCL unit. © 2025 IEEE.

关键词： MATLAB

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