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

共 47494 条记录，以下是81-90 订阅

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A Robust Multi-view Fuzzy Clustering Method Combining Local Spatial Information

A Robust Multi-view Fuzzy Clustering Method Combining Local ...

引用

2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Sun, Siyuan Qi, Yunsong Xu, Jie School of Computer Science and Technology Jiangsu University of Science and Technology China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

In view of the fact that the existing multi-view clustering algorithm does not dig deep into the local spatial information structure, resulting in inaccurate clustering results, this paper intends to make full use of the correlation and diversity between data to improve the clustering accuracy, and use the local similarity measure to mine the potential in the data. The structure is clustered and analyzed, and the atomic information is merged in a fuzzy manner to maintain the robustness of the algorithm. It is not sensitive to noise and will retain more view structure information. The algorithm (MvNIFC) in this paper verifies the effectiveness of the algorithm through experiments on various data sets, and compares several existing multi-view blur algorithms experimentally. The results show that the clustering accuracy and noise data processing are both improved. © 2025 SPIE.

关键词： Data accuracy

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Comparative advances in Financial Sentiment Analysis:A Review of BERT,FinBert, and Large Language Models 3

Comparative Advances in Financial Sentiment Analysis:A Revie...

引用

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

作者： Mahendran, Manish Barath Gokul, Aswin Kumar Lakshmi, Poornima Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu Chennai600069 India

ISBN: (纸本)9798331527549

Capturing market sentiments and supporting well-informed financial decision-making depend on the developing field of Financial Sentiment Analysis (FSA). Natural language processing (NLP) has made significant strides in comprehending and categorizing sentiment in intricate financial texts, especially with the use of Large Language Models (LLMs). The application of various LLMs, such as Bidirectional Encoder Representations form Transformers(BERT) and Financial BERT (FinBERT), as well as distilled models, such as DistilBERT and DistilRoBERTa, on a variety of financial datasets, including Financial Phrase Bank and LexisNexis news articles, was the main focus of this review article. highlighting different approaches such as model fine-tuning, zero-shot and few-shot learning, and prompt engineering. The study focuses on practical model predictions through a case study of sentimental analysis of cryptocurrencies. While FinBERT, a financial variant of BERT, exhibits high accuracy and robustness, other LLMs exhibit varying degrees of success based on the dataset and domain requirements. The analysis concentrates on the difficulties, compromises, and potential paths for improving LLMs for financial sentiment analysis. © 2025 IEEE.

关键词： Zero-shot learning

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Application and Practice of Web Data Mining in Ecommerce Based on BP Neural Network Algorithm 1

Application and Practice of Web Data Mining in Ecommerce Bas...

引用

1st international conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yu, Cuiyuan Zhang, Xiuling Zhu, Yuye Duan, Xuexia Zhang, Guanzhu Su, Shan College of Computer Science Binzhou Vocational College Binzhou China

ISBN: (纸本)9781643685779

With the development of computer network technology and database technology, the ecommerce industry has also experienced rapid growth, generating massive amounts of transaction data every day. Web data mining technology based on BP neural network algorithm can achieve targeted collection, organization, and analysis of this data, mining novel information with potential application value for merchants from a large amount of random and noisy data, which can serve as a powerful reference for business decisionmaking, improve customer satisfaction, reduce customer churn, and explore potential customer resources. © 2025 The Authors.

关键词： Marketplaces

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A Real-Time Object Detection System with Audio Feedback for Visually Impaired Persons

A Real-Time Object Detection System with Audio Feedback for ...

引用

2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Yadav, Neha Kumawat, Saloni Mishra, Sushil Kumar Jaseja, Mahek Khare, Shanu Chandigarh University Department of Computer Science & Engineering Chandigarh India Chandigarh University Department of Computer Science & Engineering Unnao India

ISBN: (纸本)9798331527495

Object detection technologies offer attractive pos-sibilities to visually impaired people, enabling them to avoid full-on collision with obstacles and recognize objects. This paper represents a modern real-time object detection system with integrated audio feedback is presented in this study in an effort to improve accessibility and situational awareness. The YOLO (You Only Look Once) algorithm is used by the system to efficiently recognize objects in images, videos, and real-time object detection (WebCam), and the IDE we used is Jupyter Notebook. It is implemented with OpenCV. Our method combines visual and audio output using text-to-speech technology to announce the presence of detected items, while also showing bounding boxes and labels on them. The method exhibits great precision in distinguishing numerous objects in intricate settings, maintaining a 0.5 confidence threshold to guarantee dependable identifications. Important features include threaded audio announcements to eliminate interface lag, dynamic label positioning for clear visual feedback, and nonmaximum suppression to reduce overlapping detections. This multimodal method creates opportunities for applications in autonomous systems, augmented reality, and assistive technologies, in addition to improving the interpretability of detection data. Our study advances computer vision by providing an integrated system that combines real- time auditory feedback with visual detection. This technology could help visually impaired users and improve human-computer interaction in a range of applications. © 2025 IEEE.

关键词： Object detection

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Chatbot and its Impact on the Retail Industry 3

Chatbot and its Impact on the Retail Industry

引用

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

作者： Tatikonda, Reshmi Kempanna, M. Thatikonda, Ramya Bhuvanesh, A. Thota, Ragupathi Keerthanadevi, R. Department of Computer Information Systems University of the Central Missouri Warrensburg United States Department of AI and ML Bangalore Institute of Technology Bengaluru India Department of Information Technology University of the Cumberlands Williamsburg United States Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli India Department of Information Technology Jawaharlal Technological University Hyderbad India Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli India

ISBN: (纸本)9798331527549

This study explores the transformative potential of chatbots in the retail industry, highlighting their role in enhancing customer engagement, optimizing business processes, and revolutionizing the nature of retail interactions. Through a comprehensive review of existing literature and case studies, the paper delves into the cognitive processes underlying human-chatbot interactions and examines their impact on customer experience, satisfaction, and loyalty. Chatbots serve a wide array of operational functions, including inventory management, automated order processing, data-driven analytics, and employee training. These functionalities streamline workflows, improve efficiency, and maximize resource utilization. The paper further explores the innovative applications of chatbots, including AI-driven personalization, conversational commerce, and seamless integration with emerging technologies. By analyzing both the current applications and challenges of chatbot technology in retail, the study uncovers the exciting opportunities they present for shaping the future of retail by fostering more personalized, efficient, and interactive customer experiences. © 2025 IEEE.

关键词： Inventory control

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Research on Novel intelligent Patient Call System Based on Surface Electromyography Recognition 24

Research on Novel Intelligent Patient Call System Based on S...

引用

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

作者： Xiao, Dongya Zhou, Zhenang Mei, Chudong Shu, Xinyan School of Electrical Engineering and Information Technology Changchun Institute of Technology Jilin Changchun China

ISBN: (纸本)9798400710094

A novel intelligent patient call system based on surface electromyography recognition is proposed to improve the performance of existing call systems which have the issues of fixed location, inconvenient calling and lack of real-time monitoring. The system uses the STM32 as the main control chip. Firstly, the overall scheme of the call system is designed. Secondly, the hardware of the call system is designed, consisting of the surface electromyography recognition module, basic vital signs detection module, and ZigBee wireless information transmission module. Then, the software process of the call system is designed. Finally, the experiment tests of the call system are carried out. The experiment results show that when using the point-to-point working mode, the data transmission success rate reaches 100% from the slave to the host, and when using the broadcast communication mode, the data transmission success rate is 95%, both of which meet the design specification requirements. The novel intelligent call system designed in this paper features straightforward calling operations. It can monitor the physical condition of the patients in real-time, and can transmit data to the control center wirelessly for analysis and processing, which can facilitate medical staff to grasp the condition of the patients in real-time. © 2024 Copyright held by the owner/author(s).

关键词： Zigbee

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Causal fMRI-Mamba: Causal State Space Model for Neural Decoding and Brain Task States Recognition

Causal fMRI-Mamba: Causal State Space Model for Neural Decod...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Deng, Weihao Han, Fei Ling, Qinghua Liu, Qing Han, Henry School of Computer Science and Communication Engineering JiangSu University China Jiangsu Engineering Research Center of Big Data Ubiquitous Perception and Intelligent Agriculture Applications China School of Computer Jiangsu University of Science and Technology China School of Electronic and Information Engineering West Anhui University China School of Engineering and Computer Science Baylor University United States

ISBN: (纸本)9798350368741

Deep learning advances neural decoding in functional magnetic resonance imaging (fMRI) tasks with convolution and attention-based methods. However, these methods struggle with capturing global spatiotemporal information due to high dimensionality, noise and inter-individual difference of fMRI, which also increase computational complexity and prior bias. To this end, a novel causal state space model, Causal fMRI-Mamba, is proposed for neural decoding and task state mapping. It effectively captures global spatiotemporal information via eliminating local redundancies and capturing long-distance dependencies. Meanwhile, a causal representation framework is designed to extract invariant high-order features and disentangle related causal features, enhancing model performance. Furthermore, a dense connection module is expanded to prevent significant causal information loss in hidden states of inter layers. On the HCP brain task state classification task, Causal fMRI-Mamba achieves better performance and generalization than comparison methods. © 2025 IEEE.

关键词： causal representation learning Neuro-decoding state space model task-based fMRI

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Fuzzy-PI Based Energy Management System for a Fuel Cell-Battery Operated DC Motor Drive 1

Fuzzy-PI Based Energy Management System for a Fuel Cell-Batt...

引用

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

作者： Dash, Biswa Mohan Biswal, Ananya Pritilagna Roy, Krishna NIT Rourkela Department of Electrical Engineering Rourkela India

ISBN: (纸本)9798331518578

The primary aim of this study is to design and analyze an Energy Management System (EMS) for a DC motor drive. The system under consideration features a primary energy source, a Fuel Cell (FC) supplemented by a battery storage system. Battery supplements power requirements during starting and energy recovery through regenerative braking. The system has two DC-DC converters: one unidirectional boost converter connected to FC and another bidirectional converter connected to the battery for both charging and discharging, with the motor being connected to the common DC bus. The control technique is implemented by a cascaded fuzzy and PI control which when implemented in this study effectively stabilizes voltage, improves power distribution and enhances adaptability of this EMS. The hTLBO-PS algorithm helps in optimizing the coefficients of the PI controller. This work is a step towards a broader call for enhancing the performance of Hybrid Electric Vehicles (HEVs) by implementing advanced EMS techniques and addressing key global energy challenges. © 2025 IEEE.

关键词： DC motors

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Integrated Hydroponics Automation System Utilizing IoT for Enhanced Plant Growth 3

Integrated Hydroponics Automation System Utilizing IoT for E...

引用

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

作者： Nilahni, N. Sivasakthi, P. Kavitha, P. Madhumathi, S.M. Sakthi Lakshmi Priya, C. Saranyavaishalini, V.G. Department of Computer Science and Engineering PSR Engineering College Sivakasi India

ISBN: (纸本)9798331527549

Growing plants in nutrition solution with any growing medium or roots dipped in distilled water is Hydroponics. Hydroponics, the practice of growing plants in a nutrient-rich solution without soil, offers significant advantages such as higher yield, reduced water usage, and efficient resource management compared to traditional farming. However, existing hydroponic systems often require separate monitoring and control platforms for different setups, such as Wick and Drip systems, increasing complexity and cost. This paper proposes a Combined Hydroponics Automation System utilizing IoT, integrating both Wick and Drip systems into a single, unified platform. The system employs Nodemcu ESP8266 to monitor key parameters such as pH, humidity, moisture, and water levels, with data transmitted to a cloud platform for real-time access and control. The unified approach reduces development and operational costs while simplifying the monitoring process. The outcome demonstrates improved efficiency in plant management, with streamlined data visualization, remote control, and optimized resource allocation, making it a cost-effective solution for urban and resource-limited farming environments. © 2025 IEEE.

关键词： Hydroponics

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The Application of intelligent Speech Analysis in College English Oral Learning System

The Application of Intelligent Speech Analysis in College En...

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2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Luo, Huan Hunan University of Medicine Hunan China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

computer assisted language learning has developed rapidly and has received widespread attention from more and more scholars. This discipline mainly promotes simple foreign language teaching activities through the assistance of computers and information technology. This article designs and implements an English speaking learning system based on speech recognition technology, which provides users with more time and space convenience advantages as well as diverse interactive characteristics when learning English speaking. The focus of this paper is on the computer-aided evaluation method of pronunciation quality in English speaking follow-up reading. Participants in the oral test can randomly select speech samples from the speech training database and follow them according to their standard pronunciation. During the operation of the system, the feature information of the two is extracted for comparison, and the pronunciation quality is evaluated by calculating the Euclidean distance between the feature parameters of the standard template and the training template. Finally, through experiments and testing, it was confirmed that the system can effectively improve the system's scoring performance by introducing average pronunciation level, and has a certain effect on improving users' oral pronunciation level. © 2025 SPIE.

关键词： Contrastive Learning

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