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

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Research on Video Sample Collection and Processing Methods Based on Artificial Intelligence Platform 11th

Research on Video Sample Collection and Processing Methods B...

引用

11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Hu, An Wang, Qi Xu, Xiaoguang Zhao, Yao Ji, Qian Pei, Lei State Grid Henan Information and Telecommunication Company Henan Province Zhengzhou450052 China State Grid Henan Electric power Company Henan Province Zhengzhou450052 China Henan Jiuyu Tenglong Information Engineering Co. Ltd Henan Province Zhengzhou450052 China

This paper summarizes the video sample collection and processing methods based on artificial intelligence platform, focusing on video noise cancellation, content segmentation and classification, and feature extraction and representation techniques. The paper believes that the deep learning technology, especially the convolutional neural network, shows great potential in image recognition and video analysis, and effectively improves the level of automation and accuracy of video processing. This paper discusses the importance of building a large-scale and high-quality video sample library, and how to improve the processing efficiency and accuracy of video data through intelligent technology. © 2024 The Authors. Published by Elsevier B.V.

关键词： Convolutional neural networks

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Deep Learning Based Phonocardiogram Signals Analysis for Cardiovascular Abnormalities Detection

Deep Learning Based Phonocardiogram Signals Analysis for Car...

引用

2023 international conference on Robotics and automation in Industry, ICRAI 2023

作者： Hussain, Sayed Shahid Ashfaq, Muniba Khan, Muhammad Salman Anwar, Shahzad Department of Computer Systems Engineering Peshawar Pakistan Department of Mechatronics Systems Engineering Peshawar Pakistan

ISBN: (纸本)9781665464727

Cardiovascular diseases are among the vital causes of mortality worldwide which need early detection with the use of auscultation examination. Heart diseases could be diagnosed in a convenient way of heartbeat sound analysis. Manual auscultation is time-consuming and problematic to differentiate heart sounds related to different kinds of heart abnormalities. Also, as it requires an expert in the field, it becomes costly and quite prone to human error. Due to all these issues, there is a high demand for an automatic diagnostic system, an alternative way to human examination. This research focuses on developing Artificial Intelligence (AI) based system of the latest computational algorithms for detecting heart abnormalities from heart sounds. Heart sounds are classified as to be normal or abnormal from Phonocardiogram (PCG) signals. One of the recent techniques introduced in deep learning algorithms for audio classification is 1-Dimensional Convolutional Neural Network (1D-CNN). This research work includes a 1D-CNN as a classification algorithm. A widely used publicly available dataset of heart sounds from PhysioNet/CinC (2016) challenge is utilized. The method acquires accuracy, sensitivity, specificity, F1 score, and precision of 95.45%, 97.44%, 93.6%, 95.45%, and 95.54% respectively. The proposed approach uses a less-complicated customized 1D-CNN algorithm, outshining most of the previous competitive methods by securing high performance that makes it appropriate for diagnosing heart diseases from PCG data. © 2023 IEEE.

关键词： Heart

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Research on Multi-model Fusion Attitude Detection and Velocity-Based Power System 1

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Zhang, PengCheng Bai, JunZhe Ouyang, Peng Zhuang, YiFei Zhang, Kun School of Electrical Engineering and Automation Nantong University Nantong China Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

In the context of the close integration of artificial intelligence and sports, the precise measurement and intelligent coach-free scientific guidance remain one of the hotly debated topics. However, most current technologies are still limited to manual supervision and measurement of relevant indicators through hardware sensors. This approach is time-consuming and labor-intensive, not only prone to interfering with athletes’ actual performance but also requiring coaches’ real-time supervision to prevent irrecoverable injuries. Therefore, this paper proposes the LW-Pose model, which introduces Depth-Wise (DW) convolutions and channel attention mechanisms to optimize the backbone network. We replace the original decoupled head section with the Vision Transformer method and analyze the output vectors using Simcc technology to ultimately obtain accurate posture outputs. The proposed method achieves an AP50 of 92.6% and AP of 71.8%. Based on this technology, a velocity-based power training system has been developed with accuracy of 97%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Channel attention Depth-Wise convolutions Simcc Velocity-based power training system Vision Transformer

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Analysis of Coloboma Defected Eyes using Automated Pre-Trained CNN Models 3

Analysis of Coloboma Defected Eyes using Automated Pre-Train...

引用

3rd international conference on Computation, automation and Knowledge Management, ICCAKM 2022

作者： Nijhawan, Rahul Sule, Neomi Verma, Madhushi Sharma, Bharti Bansal, Ishan University of Petroleum and Energy Studies Computer Science Engineering Department Dehradun India Bennett University School of Computer Science Engineering and Technology Greater Noida India DIT Computer Science Engineering Department Dehradun India College of Engineering Roorkee Computer Science Engineering Department Roorkee India

ISBN: (数字)9781665453196

ISBN: (纸本)9781665453196

Coloboma is a defect of the iris of the eye. It takes place before the birth of the child. It can affect one or both eyes. If treated from the early stages, it can restore most of that person's vision. To detect it in the early stages, we need the help of machine learning techniques and pre-Trained CNN models so that the accurate and speedy results do not take the time it usually takes otherwise. VGG16, VGG19, and Inception V3 are three feature extraction models discussed in this article that provide crucial yet simple combination techniques that can lead to more accurate predictions. We compare the above extraction models with different classifiers for the highest accuracy. After examining the ROC and Confusion Matrix, we find the best suitable model and classifier pair. In this case, we get the largest area under the curve, 95.9%, with inception V3 and neural network classifier. © 2022 IEEE.

关键词： Extraction

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Local Path Planning for USVs Based on An Improved DWA Algorithm 1

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Zhao, Hao-Zhong Wang, Cheng-Cheng Wang, Yu-Long Uddin, M. Monir School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Department of Mathematics and Physics North South University Dhaka1229 Bangladesh

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

To enhance the path planning performance of an unmanned surface vehicles (USV), a modified Dynamic Window Approach (DWA) is proposed. This modification aims to overcome issues such as local best solution and poor dynamic collision avoidance performance. Firstly, to improve the safety of USV operation in real environments, an obstacle inflation model is introduced. Secondly, to enhance the USV’s ability to navigate around obstacles, a virtual target point evaluation function is added to the traditional DWA. Finally, to improve dynamic collision avoidance capability and shorten collision avoidance time, the speed sampling space is enhanced by eliminating collision trajectories. Simulation experiments demonstrate that the enhanced DWA exhibits satisfactory collision avoidance capabilities compared to the traditional method in both static and dynamic environments. The improved DWA algorithm is more effective in path planning in complex Marine environment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned surface vehicles

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Integrating OPC UA Aggregation Server Functionality Within the IEC 61499 Framework for Enhanced Industrial automation 1

引用

international conference on computer Science, Electronics and Industrial engineering, CSEI 2023

作者： Ayala, Paulina Chasiquiza, Edwin-O. Andaluz, Diego-F. Lopez, Edgar-R. Pastuña, Henry-José Garcia, Marcelo V. Universidad Tecnica de Ambato UTA Ambato180103 Ecuador Universidad de las Fuerzas Armadas ESPE campus latacunga Latacunga170146 Ecuador University of Basque Country UPV/EHU Bilbao48013 Spain

ISBN: (数字)9783031709814

ISBN: (纸本)9783031709807

This article aims to enhance industrial process automation through efficient communication among various processes, enabling better control and monitoring of operations. To achieve this, the IEC-61499 standard and OPC UA protocol were utilized to design a client/server model-based communication architecture. This architecture facilitates bidirectional communication among devices and systems comprising the industrial infrastructure, enabling real-time control and continuous process monitoring. Additionally, an OPC UA aggregation server has been implemented to centrally access data from multiple aggregated OPC UA servers and clients, thereby reducing implementation costs and complexity. The use of this aggregation server also provides a global view of all industrial processes, simplifying the identification and resolution of real-time issues or inefficiencies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Office automation

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DC Series Arc Fault Detection Method for Photovoltaic Array Based on Random Forest 2

DC Series Arc Fault Detection Method for Photovoltaic Array ...

引用

2nd IEEE international conference on Control, Electronics and computer Technology, ICCECT 2024

作者： Li, Weijun Li, Tianyou Su, Jun College of Electrical Engineering and Automation Xiamen University of Technology Xiamen China

ISBN: (纸本)9798350380958

With the continuous development of the domestic photovoltaic industry and the increasing installed capacity of photovoltaics, fires occur frequently in photovoltaic power stations. The cause of fires is often caused by DC arc faults. Therefore, a reliable DC arc fault detection method for photovoltaic arrays is of great significance for ensuring the safe and reliable operation of photovoltaic power generation systems. The photovoltaic array is greatly affected by environmental factors, the output data is unstable, and the amplitude change of the fault arc data is also uncertain, which leads to the misjudgment of the DC arc detection method. Aiming at the DC series arc fault of photovoltaic array, this paper proposes a detection method of DC series arc fault of photovoltaic array based on random forest. Based on the Simlink platform, a simulation model of photovoltaic series arc fault is built. The simulation model is used to obtain the series arc fault data, and the difference between the normal string and the series arc fault string is compared. The DC series arc fault data is analyzed by statistical method and the feature quantity is extracted as the training set. The feature quantity is used to train the random forest model to establish the photovoltaic series fault diagnosis model. The string voltage data of each group collected by the inverter before and after the series arc fault of a photovoltaic project in a new energy enterprise in Xiamen are used for diagnosis. The inverter string data of the actual series arc fault verify that the method can effectively identify the DC series arc fault, and is less affected by environmental factors. The stability of the detection method is good. © 2024 IEEE.

关键词： Feature extraction

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Discussion the Laptop computer cooling system 2

Discussion the Laptop computer cooling system

引用

2nd international conference on Mechanical, Electronics, and Electrical and automation Control, METMS 2022

作者： He, Haoqian Queen's University Belfast United Kingdom

ISBN: (数字)9781510654785

ISBN: (纸本)9781510654778

Notebook computers have become increasingly common in people's daily lives in today's society due to its portability. More and more people use laptop computer frequently in their work life and daily entertainment. It has covered almost all fields, including work, games and so *** such a high number of users, all computers will undoubtedly experience problems - laptop computer cooling ***, now the more common way of heat dissipation is the air-cooled cooling based on fan cooling and the water-cooled cooling based on cold fluid cooling. the author used contrast experiments method or calculation to conduct the research. It can be concluded that the efficiency of air-cooled heat dissipation is slightly lower than that of water-cooled heat dissipation. © 2022 SPIE

关键词： Laptop computers

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Static Code Analysis of IEC 61131-3 ST Programs via Symbolic Execution

Static Code Analysis of IEC 61131-3 ST Programs via Symbolic...

引用

2024 IEEE international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Mengyan Huang, Yanhong Shi, Jianqi Chen, Yinghao Yang, Yang East China Normal University Shanghai China National Trusted Embedded Software Engineering Technology Research Center Shanghai China Hardware/Software Co-Design Technology and Application Engineering Research Center Shanghai China

ISBN: (纸本)9781665410205

A Programmable Logic Controller (PLC) is an essentially domain-specific computer used to control physical equipment and is widely used in industrial control fields. It plays a crucial role in automating complex processes for industrial automation systems, requiring high reliability as code vulnerabilities can potentially lead to disasters. Therefore, vulnerability detection in PLC programs is of significant importance. However, the availability of tools supporting vulnerability detection in PLC programming languages is limited. This paper attempts to improve industrial security from the perspective of code security and proposes a static code analysis approach specifically designed for IEC 61131-3 Structured Text (ST) programs. This approach uses structural pattern matching and symbolic execution technology to identify program defects and improve quality by detecting problematic code structures and potential issues early in the development process, thereby reducing the debugging effort required during developments. Considering the characteristic of periodic loop execution in PLCs, we introduce the loop unwinding technique to collect constraints from subsequent execution cycles for detection purposes. Based on the aforementioned approach, we implement a static code analysis tool, ST-Checker and make a series of evaluations. The experimental results show that this method is feasible and can detect potential defects that existing PLC compilers cannot detect, improving the precision of defect detection with data dependencies. © 2024 IEEE.

关键词： Programmable logic controllers

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Electric Vehicle Control Protocol for on Board System 1

Electric Vehicle Control Protocol for on Board System

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1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Maidurkar, Hitesh M. Salodkar, Prachi Badar, Altaf.Q.H. Ramdeobaba University Nagpur Nagpur India Ramdeobaba University Nagpur Faculty of Electrical Engineering Nagpur India National Institude of Technology Faculty of Electrical Engineering Warangal India

ISBN: (纸本)9798331520540

The Control Area Network (CAN) protocol is a powerful data bus standard designed to facilitate communication between multiple microcontrollers in a vehicle. industrial automation systems without requiring a host computer. Developed by Bosch in 1983, CAN has become a standard in the automotive industry due to its reliability and efficiency in handling real-time data transmission. CAN operates on a multi-master, message-oriented architecture. It utilizes differential signaling to provide high noise immunity and error detection capabilities, ensuring reliable data communication even in harsh environments. The protocol supports various frame formats, including standard (11-bit identifier) and extended (29-bit identifier) frames, allowing for a wide range of applications. One of the key features of CAN is its arbitration process, which prioritizes messages based on their identifiers. This enables high-priority messages to access the bus first, ensuring timely and critical data transmission. Additionally, CAN FD (Flexible Data Rate) and CAN XL (extended data Length) have been introduced to enhance data throughput and accommodate larger payloads, addressing the growing data demands in modern vehicles. CAN is widely used in electric vehicles (EVs) to enable seamless communication between different electronic control units (ECUs), such as battery management systems, motor controllers, and safety systems. Its efficiency, reliability, and flexibility make it an integral part of the electronic communication architecture in EVs and various other applications, in this paper we are also used the varies type of protocol which is used in Electrical vehicle communication. © 2025 IEEE.

关键词： Automotive industry

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