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

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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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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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Memristor-Fet Hybrid Circuits for Real-Time Electronic Applications

Memristor-Fet Hybrid Circuits for Real-Time Electronic Appli...

引用

2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Raj, P Michael Preetam Vittapu, Sravan K Chinnasamy, P. Gupta, Manu Priyanka, B.G. Gajbhiye, Pranjali Mlr Institute of Technology Department of Cse Hyderabad India Nalla Narasimha Reddy Education Society's Group of Institutions Department of Ece Hyderabad India Kalasalingam Academy of Research and Education Department of Cse Tamil Nadu India Sreenidhi Institute of Science and Technology Department of Electronics and Computer Engineering Hyderabad India Pes Institute of Technology and Management Department of Ece Shivamogga India Woxsen University Department of Ai Research Centre Hyderabad India

ISBN: (纸本)9798331529833

Circuits comprising of memristor paired with Field effective transistor (FET) were determined to be exceedingly significant as the output current modulated by the FET heightened memristive executions. In this paper, the memristor-FET pair is studied in terms of its electronic features. The duo exhibited the characteristics of negative resistance. Interestingly, the duo was capable of generating ramp and pulse signals with improved circuit complexity of ~93% when compared to conventional signal generators. Importantly, the linearity was improved by ~20.5%. © 2025 IEEE.

关键词： Memristors

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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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Vision-Based Hand Gesture Recognition System for Assistive Communication Using Neural Networks and GSM Integration 2

Vision-Based Hand Gesture Recognition System for Assistive C...

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2nd international conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Singhal, Pooja Verma, Sonia Gupta, Ritu Kumar, Rishi Arya, Rajneesh Kumar Department of Computer Science ABES Engineering College Uttar Pradesh Ghaziabad India Department of Computer Science Bhagwan Parshuram of Institute and Technology GGSIPU Delhi India Dehradun India

ISBN: (纸本)9798331530389

This paper explores the application of vision-based hand gesture recognition in addressing communication challenges faced by deaf and dumb individuals within the realm of human-computer interaction (HCI). Highlighting the barriers posed by conventional communication methods and sign language interpretation, the paper introduces the Dumb Aid Phone system as an innovative solution. This system, functioning as an interface, enables seamless interaction for non-speaking individuals with their surroundings. Utilizing image processing and neural networking, the system captures and interprets hand gestures, matching them with a database to generate corresponding speech sounds. Enhanced by a web camera and a GSM module, the Dumb Aid Phone system not only facilitates effective communication but also holds the potential to revolutionize accessibility, contributing to a more inclusive society for the deaf and dumb community. © 2025 IEEE.

关键词： Gesture recognition

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Boot process of RISC-V multi-core heterogeneous SoC integrated with eFPGA 24

Boot process of RISC-V multi-core heterogeneous SoC integrat...

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

作者： Gao, Po Zhang, Yanxin Tan, Lang Yang, Lixin Niu, Bin Yan, Shengli Li, Dejian Wang, Zhihua Beijing Smartchip Microelectronics Technology Co. Ltd. Beijing China School of Integrated Circuits Tsinghua University Beijing China

ISBN: (纸本)9798400710094

The RISC-V multi-core heterogeneous SOC has five harts that divided into three clusters, and integrates an eFPGA. Inter-cluster is asymmetric-multiprocessor and intra-cluster is symmetric-multiprocessor. The SoC not only has the powerful computing ability of general CPU, but also has the scalability and parallel processing ability of FPGA. But it also makes the process of loading and launching the firmware extremely complicated. According to the hardware architecture of SoC and possible use scenarios, four basic bare-metal and operating system combination boot schemes and three methods to load eFPGA executable files are designed. The actual test shows that the boot process can work as expected. These boot schemes cover almost all the usage scenario of SoC, expand the application range of SoC, and are more conducive to the popularization and use of SoC. © 2024 Copyright held by the owner/author(s).

关键词： Firmware

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Smart Classroom Power Automation: An Adaptive And Predictive Approach

Smart Classroom Power Automation: An Adaptive And Predictive...

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2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Madhurima, Gangireddy Reddy, Panduga Venkata Jaya Srikanth Srinivasa Perumal, R. Vellore Institute of Technology School of Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331529833

The growing demand for energy efficiency in educational institutions has led to the exploration of smart technologies for managing power consumption. This project introduces a "Power Automation for Classrooms"system that leverages long-range RFID (Radio Frequency Identification) technology to automate the activation of classroom lights and fans based on student attendance. The system operates by detecting student entries through RFID tags without the need for manual scanning, thus ensuring a seamless and instant process. The project aims to reduce energy wastage by activating the power in stages depending on the number of students present, with specific power allocation thresholds set according to the class strength. The data on students entered, as well as the power consumption for each classroom, is stored in the cloud, allowing for real-time monitoring, analysis and supports data-driven decision-making for future energy planning. © 2025 IEEE.

关键词： Decision making

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Cloud Based Automated Control System Workshops and Rooms for Controlling Parameters 1

Cloud Based Automated Control System Workshops and Rooms for...

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

作者： Kumar, Dinesh Kuntal, Ravinder Singh Deep, Pragya Chamoli, Anup Shekhar Singh, Pinki Mandal, Rishabh SRM Institute of Science & Technology Department of Computer Science and Engineering UP Ghaziabad India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India IIMT College of Engineering Department of AI & DS Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun248001 India Accurate College of Engineering & Management Department of Computer Science and Engineering Greator Noida India Tula's Institute Department of Computer Science and Engineering UK Dehradun India

ISBN: (纸本)9798331518578

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing. © 2025 IEEE.

关键词： Smart manufacturing

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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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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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