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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

共 15534 条记录，以下是4461-4470 订阅

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Enhanced Fault Detection in Industrial Process via a Hellinger Distance-Based Data-Driven Scheme

Enhanced Fault Detection in Industrial Process via a Helling...

引用

Modeling, Simulation & Intelligent computing (MoSICom), international conference on

作者： Mohammed Affan K. Ramakrishna Kini Muddu Madakyaru Fouzi Harrou Mukund Kumar Menon Ying Sun Department of Chemical Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

Accurate fault detection in modern chemical processes ensures safety and efficiency. However, detecting faults in noisy environments remains a significant challenge. This paper introduces an effective fault detection (FD) strategy that combines a supervised learning approach using partial least squares (PLS) with fault detection charts based on Hellinger distance (HD) and exponentially weighted moving average (EWMA). The PLS-HD-EWMA strategy utilizes PLS to generate residuals, while HD is employed to compute the divergence between actual residuals and fault-free residuals. EWMA is then applied to evaluate the HD, providing sensitivity to small changes for effective fault detection. The proposed strategy’s efficacy is demonstrated through simulations on a benchmark continuous stirred tank reactor process, evaluating three common fault scenarios. The monitoring performance indicates that the PLS-HD-EWMA approach outperforms all the other conventional methods, offering superior fault detection capabilities.

关键词： Training Sensitivity Fault detection Computational modeling Supervised learning Noise Safety Noise measurement Continuous-stirred tank reactor Monitoring

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Deep learning based Identification of Solid Waste Management in Smart Cities through Garbage Separation and Monitoring

Deep learning based Identification of Solid Waste Management...

引用

international conference on Inventive Research in computing Applications (ICIRCA)

作者： Abin George Sham H. Mankar N V S Suryanarayana Manish Gupta R Sathish A Priya Knowledge and technology management Division Council of Scientific & Industrial Research National Aerospace Laboratories Bangaluru Karnataka India Department of Mechanical Engineering Pimpri Chinchwad College of Engineering and Research Pune Maharashtra India Administrative Officer Central Tribal University of Andhra Pradesh Vizianagaram Andhra Pradesh India Division of Research and Development Lovely Professional University Phagwara Punjab India Department of Computer Science Shri Nehru Maha Vidayala College of Arts and Science Coimbatore Tamil Nadu India School of Architecture Koneru Lakshmaiah Educational Foundation Gundur Andhra Pradesh India

The solid waste management is the process of proper decomposition of waste materials within a period of time. This includes the collection of garbage's and then proceeded through certain measures for decomposition. There are various methods adopted in the garbage separation process. This includes the artificial intelligence techniques for the estimation and determination of the solid waste through automatic detection and separation of the garbage waste using control and sensing units. They are integrated with the internet of things to enable the two way communication system. This helps to visualize the functioning of the system adopting the digital platform. The proposed system is implemented through the smart dust bin held in every household that automatically senses the non-biodegradable and biodegradable waste materials. The classification of the waste materials are identified through the image processing techniques.

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STM32-based intelligent following trolley

STM32-based intelligent following trolley

引用

2024 international conference on Green Energy and Mechatronics engineering, ICGEME 2024

作者： Chen, Hong Fu Yan, Shu Bin Gao, Yuan Yuan Xu, Ai Wei College of Mechanical and Electrical Engineering China Jiliang University Hangzhou310018 China School of Electrical Engineering Zhejiang University of Water Resources and Electric Power Hangzhou310018 China Joint Laboratory of Intelligent Equipment and System for Water Conservancy Hydropower Safety Monitoring of Zhejiang Province and Belarus Hangzhou310018 China

In this paper, we design a kind of cart that uses ultrasonic module to realize automatic target following, which can realize high-precision target following. Existing following methods have distance and hardware limitations, this paper uses a single transceiver ultrasonic module to form a triangle with the target to follow the target by comparing the length of the distance between the two sides, the hardware cost is low and less interference can be stabilized following. We also designed a host computer to facilitate the control of the cart. Finally, we tested the following ability of the trolley, and the results show that the trolley's steering reaction speed can meet the requirements, and the following is accurate and fast. © Published under licence by IOP Publishing Ltd.

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A Novel Approach for Analyzing Passengers’ Train Choice Behavior in Urban Rail Transit System 5th

A Novel Approach for Analyzing Passengers’ Train Choice Beh...

引用

5th international conference on electrical engineering and Information Technologies for Rail Transportation, EITRT 2021

作者： Sun, Xuan Liu, Yuan Li, Chunya Qin, Yong Guo, Jianyuan Zhang, Zhuo State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China China Railway Investment Company Beijing China School of Mathematics Physics and Statistics Shanghai University of Engineering Science Shanghai China School of Traffic and Transportation Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811699085

In recent years, with the improvement of information management, a large number of passenger travel data and train operation data are collected automatically in urban rail transit (URT) system. A large amount of archived data about when and where passengers travel is obtained through smart cards, which may be used to research passenger behavior and traffic demand management. Combined with automatic fare collection (AFC) and automatic Vehicle Location (AVL) data, it can assist the management department to make planning, scheduling, performance evaluation and so on. This study proposes a data-driven approach to understand passenger’s train choice behavior in congested subway system. First, the model gives a simple and reasonable assumption, that is, "get off-leave now" (GO-LN). The advantage of this assumption is that it does not rely on manual investigation. Second, an adaptive model by using AFC and AVL data is developed to estimate the probability of passenger’s train choice behavior, and the expectation maximization (EM) algorithm is used to solve the problem. Finally, a case study carried out on the Ba Tong Line of Beijing Metro is discussed to illustrate the effectiveness and robustness of the proposed model. The method proposed in this study is helpful to fully understand passenger travel behavior from incomplete data sets, infer the distribution of network passenger flow, formulate traffic regulations and provide suggestions for subway operators to implement corresponding measures. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information management

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Game-model prediction hybrid path planning algorithm for multiple mobile robots in pursuit evasion game

Game-model prediction hybrid path planning algorithm for mul...

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2021 IEEE international conference on Unmanned Systems, ICUS 2021

作者： Cui, Jianfeng Li, Dongchang Liu, Peng Qin, Jia Ma, Yuedong Lu, Zhigang North Automatic Control Technology Institute School of Electrical and Control Engineering North University of China Taiyuan China School of Electrical and Control Engineering North University of China Taiyuan China North Automatic Control Technology Institute

ISBN: (纸本)9780738146577

In this paper, a novel hybrid path planning algorithm is proposed based on the game theory and model predictive control method. Firstly, we use the feasible predicted positions, which are calculated by inputting discrete steering angles to the evader model, as the game decision set of the evader. Then, the pursuer's game decision set is obtained based on the model predictive control method, which takes each predicted position as a virtual target and solves the suboptimal problem with input constraints. Finally, we design the payment function, and acquire the collaborative strategy by solved the pursuit-evasion problem based on the zero-sum game decision method. Numerical simulations show that the proposed method can capture the evader with different maneuvers effectively. From further simulation analysis, it can also be seen that, through the proper allocation between the item of capture distance and the item of team distribution in the payment function, the evader can be captured faster while maintaining the team capture situation. © 2021 IEEE.

关键词： Motion planning

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Invention of Line-ChatBot: An Innovative Application of ChatGPT API and LINE Bot for Enhanced Student Learning

Invention of Line-ChatBot: An Innovative Application of Chat...

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IEEE international conference on Knowledge Innovation and Invention (ICKII)

作者： Bing-Hong Chen Chih-Cheng Chen Electrical and Communications Engineering Feng Chia University Taiwan Department of Automatic Control Engineering Feng Chia University Taiwan

The intelligent teaching assistant system, Line-ChatBot based on the ChatGPT API and LINE Bot is used to for homework recommendations and learning guidance. The system uses a generative language model as an accessible and cost-effective learning support tool. It has been designed to effectively comprehend and decipher difficulties in doing homework and provides tailored suggestions and guidance. Overall, Line-ChatBot is a tool for aiding students in their learning by offering an efficient, flexible, and natural learning support system. We proposed the application of this system in educational contexts for the innovation and advancement of education.

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Image Recognition Technology for Abnormal Capsule Detection

Image Recognition Technology for Abnormal Capsule Detection

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Big Data, Cloud computing, Data science & engineering (BCD)

作者： Chuin-Mu Wang Shao-Wei Chu Yen-Ching Wu Jia-Xian Jian Ming-Yu Tsai Meng-Fen Huang Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan Department of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

Capsules are widely used in the pharmaceutical and health food industries. Traditionally, the inspection of capsule appearance relies on manual visual inspection, which is both time-consuming and prone to errors. Therefore, this paper proposes the replacement of manual inspection with deep learning image technology to improve the speed and consistency of capsule appearance defect *** this study, we focus on defect types in capsule appearance that are difficult to identify and compare the performance of two deep learning network architectures: YOLOv7 [1] and YOLOv8 [2]. The training, validation, and test sets were created using manually captured images, distributed in a 7:2:1 *** experimental results demonstrate that YOLOv8 outperforms YOLOv7 in capsule appearance defect detection. YOLOv8 achieves a recall of approximately 0.916 and an average accuracy of about 96.2%. Furthermore, YOLOv8 excels in terms of detection speed and recognition accuracy. These research findings highlight the potential of deep learning for capsule appearance inspection, offering the industry opportunities to enhance production efficiency and quality control.

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A Smart Home Design with Intelligent Patient Monitoring Features by Using Internet of Things (IoT) Enabled Communication Technology

A Smart Home Design with Intelligent Patient Monitoring Feat...

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Innovative computing, Intelligent Communication and Smart electrical Systems (ICSES), international conference on

作者： P. Prince C. Rajabhushanam Department of Computer Science and Engineering Bharath Institute of Higher Education and Research (BIHER) Chennai Tamil Nadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

The integration of Internet of Things (IoT) technology into smart home systems has revolutionized patient monitoring by providing real-time health insights and automated environmental adjustments. This study focuses on designing and evaluating a smart home system with intelligent patient monitoring features, aimed at enhancing patient safety, comfort, and healthcare delivery. The system employs a network of IoT-enabled devices, including wearable health sensors, environmental monitors, and smart cameras, to track vital signs such as ECG, SPO2, and body temperature, along with environmental parameters like air quality, humidity, and temperature. The system achieved a high accuracy rate, with vital sign sensors demonstrating over 98% reliability across various metrics. A communication framework using Wi-Fi and MQTT protocols ensures seamless data transfer and real-time responsiveness. Edge computing enables low-latency data processing, while cloud analytics provide predictive insights for early health issue detection. Key findings demonstrate the system's efficiency in emergency response, with an average detection-to-alert time of 1.4 seconds, and its ability to adapt the environment based on health conditions with over 95% precision. Automated features such as temperature control, fall detection, and personalized lighting enhance patient care and well-being. This work underscores the transformative potential of smart home technologies in healthcare, paving the way for future advancements in personalized health monitoring systems.

关键词： Temperature sensors Patient monitoring Smart homes Medical services Real-time systems Sensor systems Internet of Things Wearable sensors Intelligent sensors Edge computing

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Application of a Fuzzy Logic controller in a D-STATCOM in an electrical Network with Distributed Generation

Application of a Fuzzy Logic Controller in a D-STATCOM in an...

引用

international Russian Smart Industry conference (SmartIndustryCon)

作者： Ahmad Feras Akkad Natalya Erdili Elena Sosnina Institute of Electric Power Engineering Nizhny Novgorod State Technical University n.a. R.E. Alekseev N. Novgorod Russia

ISBN: (数字)9781665464291

ISBN: (纸本)9781665464307

The article is devoted to the problem of increasing the response speed of the D-STATCOM connected to an electrical network with distributed generation (DG). Distributed generation based on renewable energy sources (RES) has a negative impact on the quality of electricity in distribution networks. The use of the D-STATCOM allows to reduce non-sinusoidal voltage and it fluctuations in the network. The traditional control methods based on the PI controller cause a slow response of the D-STATCOM, which is unacceptable, especially in transient conditions with rapid changes in RES generation. It is proposed to use a fuzzy logic controller to increase the response speed and efficiency of the D-STATCOM and to ensure the better power quality of the DG system.

关键词： Fuzzy logic PI control Heuristic algorithms Computational modeling Power system dynamics Power quality automatic voltage control

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Latency-Robust control of High-Speed Signal-Free Intersections

Latency-Robust Control of High-Speed Signal-Free Intersectio...

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2021 American control conference, ACC 2021

作者： Liu, Yang Nicolai-Scanio, Zev Jiang, Zhong-Ping Jin, Li School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Hong Kong University of Science and Technology Department of Civil and Environmental Engineering China John A. Paulson School of Engineering and Applied Sciences Harvard University United States Tandon School of Engineering New York University United States UM-SJTU Joint Institute School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781665441971

High-speed signal-free intersections are a novel urban traffic operation enabled by connected and autonomous vehicles. However, the impact of communication latency on intersection performance has not been well understood. In this paper, we consider vehicle coordination at signal-free intersections with latency. We focus on two questions: (i) how to ensure latency-resiliency of the coordination algorithm, and (ii) how latency affects the intersection's capacity. We consider a trajectory-based model with bounded speed uncertainties. Latency leads to uncertain state observation. We propose a piecewise-linear control law that ensures safety (avoidance of interference) as long as the initial condition is safe. We also analytically quantify the throughput that the proposed control can attain in the face of latency. © 2021 American automatic control Council.

关键词： Autonomous vehicles

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