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检索条件"任意字段=International Conference on Advanced Computer Control"

共 19904 条记录，以下是161-170 订阅

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Design And Stability Analysis of control Loops In Field Oriented control of Traction PMSM Drives For EV Application

Design And Stability Analysis of Control Loops In Field Orie...

引用

2024 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2024

作者： Kumar, Mayank Deosarkar, Pankaj Advanced Engineering Tata Motors Limited Erc Pune India

ISBN: (纸本)9798350348460

This paper focuses on the design and stability analysis of control loops within the framework of field-oriented control (FOC) applied to traction permanent magnet synchronous motor (PMSM) drives for electric driven vehicle (EVs). The proposed field-oriented control (FOC) technique is for controlling the traction motor which aims to improve dynamic and steady state performance of drive system. The key concept of this motor control technique is to obtain the linearized dynamics of PMSM similar to the dynamics of DC machine. The linear model of motor controller consists of three loops i.e., speed loop and two inner current loops. And the main objective of paper is to design the control scheme to achieve fast response and increase the overall efficiency of the system. The drive system is subjected to operate in three driving modes i.e., acceleration, cruising (constant speed) and deceleration mode along with variable loading condition to test the robust behaviour of system. The simulation results of model are verified in MATLAB-Simulink environment. © 2024 IEEE.

关键词： controller EVs FOC MATLAB PMSM SiC-inverter VSI

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Survey on advanced Techniques for Cardiac Arrest Prediction Using Machine Learning 4

Survey on Advanced Techniques for Cardiac Arrest Prediction ...

引用

4th international conference on Power, Energy, control and Transmission Systems, ICPECTS 2024

作者： Periasamy, J.K. Raagavi, K. Tarun Ashwanth, P. Sri Sai Ram Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

Cardiac arrest has been a leading cause of mortality worldwide, with limited opportunities for intervention. This project introduces a novel machine-learning approach to predict and process cardiac arrest risk in high-risk patients. Our system integrates 1. advanced signal processing techniques for ECG analysis 2. Deep learning algorithms for pattern recognition 3. Real-time monitoring and alert system. By analyzing ECG data, medical history, and vital signs, our system provides personalized risk scores, enabling early intervention and improving patient outcomes. Our approach has the potential to revolutionize cardiac arrest prediction, saving lives and reducing healthcare costs. © 2024 IEEE.

关键词： Electrocardiography

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Policy-based Role and Access Modeling 12

Policy-based Role and Access Modeling

引用

12th IEEE international conference on Intelligent Data Acquisition and advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Ayman, Noha Kiryakos, Mariam Sabty, Caroline El Bolock, Alia Abdennadher, Slim German International University Informatics and Computer Science Cairo Egypt Swansea University Swansea United Kingdom

ISBN: (纸本)9798350358056

In this paper, we present an approach based on Attribute Based Access control (ABAC) and Risk Adaptive Access control (RAdAC) to improve the reliability of the risk assessment and authorization process. The model has been designed to adapt to the complex and ever-changing nature of modern campus networks by incorporating location information. This added layer of risk assessment enhances the ABAC model by adding a level of authorization to it. © 2023 IEEE.

关键词： Attribute Based Access control (ABAC) policy Risk Adaptive Access control (RAdAC)

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Research on Transmission control Technology in computer Wireless Network Communication

Research on Transmission Control Technology in Computer Wire...

引用

2023 international conference on Mechatronics and Intelligent control, ICMIC 2023

作者： Yuan, Chunyang Li, Bing Shandong Yellow River Administration Shandong Yellow River Information Center Shandong Jinan China

ISBN: (纸本)9781510668393

computer wireless network communication is an indispensable part of modern Internet infrastructure, which can providestable, efficient and secure data transmission services for different application scenarios and usage habits. Transmissioncontrol technology is also crucial. As one of the core technologies of network information transmission, computer communication technology has good anti-interference performance and can play an extremely important role inthetransmission and control of various network data. Based on the actual situation, this paper discusses the transmissioncontrol, communication network and transmission control technology of computer communication, and puts forward counter measures. © 2023 SPIE.

关键词： Wireless networks

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Tennis Ball Recognition in Complex Scenes Based on Improved YOLOv5 7

Tennis Ball Recognition in Complex Scenes Based on Improved ...

引用

7th international conference on advanced Algorithms and control Engineering, ICAACE 2024

作者： Li, Qizheng Zhao, Yuan Chongqing University Of Technology Department Of Computer Science And Engineering Chongqing China

ISBN: (纸本)9798350361445

In order to solve the problems of low accuracy of tennis recognition, oversized model and low detection frame rate in complex environment, this paper proposes a method based on improving YOLOv5s network. The method improves tennis recognition in complex scenes by improving the loss function, adding a convolutional attention mechanism, and designing a new feature extraction network to extract features. The experimental results show that the mean average precision (mAP) of the improved tennis ball detection model reaches 87.73% under the same experimental conditions, which is 9.28% better than the original model of YOLOv5s. And the detection speed of the model can reach 69 frames/s, and the size of the model is only 12.1MB, which can meet the requirements of real-time and light weight for tennis ball recognition while greatly improving the accuracy. © 2024 IEEE.

关键词： Object detection

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A New Offloading Method in Cloud Platforms: Reducing Latency Based on Data Compression 7

A New Offloading Method in Cloud Platforms: Reducing Latency...

引用

7th international conference on advanced Algorithms and control Engineering, ICAACE 2024

作者： Yang, Zhiqin Zhou, Zhennan Dong, Han Feng, Xiaoning Southampton Ocean Engineering Joint Institute Harbin Engineering University Harbin China College Of Computer Science And Technology Harbin Engineering University Harbin China

ISBN: (纸本)9798350361445

This paper introduces a novel approach to reduce computational latencies in cloud platforms by integrating data compression with Non-Orthogonal Multiple Access (NOMA) technologies. We propose a computational task offloading scheme that optimizes resource allocation to minimize maximum user task completion latency by utilizing an adaptive step size Artificial Fish Swarm Algorithm. Experiments conducted using Python simulation demonstrate that our approach significantly lowers task completion latencies compared to existing methods that rely solely on either data compression or NOMA technologies. © 2024 IEEE.

关键词： Data compression

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Evaluating Models for Deepfake Detection: A Comparative Study 5

Evaluating Models for Deepfake Detection: A Comparative Stud...

引用

5th international conference on IoT Based control Networks and Intelligent Systems, ICICNIS 2024

作者： Krishna, Vamsi Neha, Perla Sree Vyshnavi, P. Vidyasekaran, Harine Amrita Vishwa Vidyapeetham Computer Science and Engineering Chennai India

ISBN: (纸本)9798331518097

Deepfake detection poses a significant challenge in digital forensics due to increasingly advanced AI-generated videos. This study evaluates three models using the FaceForensics++ and DeeperForensics-1.0 datasets. The preprocessing involved video encoding, renaming, trimming, frame extraction, face detection, and data loading. The first model, a Convolutional Neural Network (CNN), achieved 84% accuracy. The second model, Xception, an efficient CNN with depth-wise separable convolutions and residual connections, attained 89% accuracy. The third model, combining CNN with a Recurrent Neural Network (RNN) and LSTM layers, significantly improved detection accuracy to 97%. This hybrid model highlights the importance of capturing spatial and temporal features in deepfake detection, demonstrating the efficacy of advanced deep learning techniques in addressing the deepfake threat. © 2024 IEEE.

关键词： Convolutional neural networks

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Brain-machine Cooperative control for Multi-robot Formation

Brain-machine Cooperative Control for Multi-robot Formation

引用

2024 IEEE international conference on Unmanned Systems, ICUS 2024

作者： Yang, Zhenge Bi, Luzheng Fei, Weijie Zhang, Peiyu School of Mechanical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350384185

With the aging of society and the growing number of patients experiencing motor dysfunction, enhancing their quality of life and autonomy has become increasingly *** paper proposes a brain-computer synergistic multi-robot formation control technique aimed at efficiently managing multi-robot formations through brain-computer interface (BCI) *** system framework includes a Leader controller, Follower controller, Formation Decision Module, and Autonomous Navigation *** validation demonstrates the system's performance in tasks such as formation transformation and autonomous *** confirm that the auxiliary controller effectively tracks user formation control intentions and accomplishes multi-robot formation tasks ***, the autonomous navigation module significantly enhances system autonomy, reduces user control demands, and alleviates user control *** research contributes to improving the quality of life for motor disorder patients by leveraging advanced BCI and robotics technologies to facilitate independent living and social participation through enhanced task assistance and reduced dependency on direct user control. © 2024 IEEE.

关键词： Multipurpose robots

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Enhancing Power Efficiency by Integrating Processor Performance Metrics with Power Supply Phase control 13

Enhancing Power Efficiency by Integrating Processor Performa...

引用

13th international conference on Renewable Energy Research and Applications

作者： Kawaguchi, Shinichi Kanagawa Inst Technol Dept Clin Engn Atsugi Kanagawa Japan

ISBN: (纸本)9798350375596;9798350375589

The processor is the most power-consuming device in a computer, yet it often operates under light load conditions for extended periods. During these times, the processor's power supply also experiences a light load, which significantly decreases its efficiency. Therefore, maintaining high efficiency across a wide range of conditions, including light load, is crucial. Previously, an adaptive power efficiency control method was proposed that links real-time power control to the processor's logical data processing workload, optimizing the configuration to achieve the highest possible power efficiency. While this method has shown the potential to improve CPU power efficiency in some programs, processor power fluctuations vary depending on the computing system, and the characteristics of power load differ according to the program being executed. In this study, the processor power supply efficiency improvement under more fluctuating power loads was experimentally verified by applying the proposed method during the execution of various types of programs. The results confirmed that the proposed method can enhance power efficiency and reduce power loss.

关键词： processor power supply efficiency performance monitor

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Real-Time Gesture Recognition for Volume control Using Python and ML Techniques 5

Real-Time Gesture Recognition for Volume Control Using Pytho...

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5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Musthafa, Syed Murugan, Lavanya Mutharasu, M. Vadivel, T. Fathima, H. Leelavathi, M. M.Kumarasamy College of Engineering Department of Information Technology Tamil Nadu Karur639 113 India American International University Computer Science Kuwait Andhra Pradesh Madanapalle517325 India KSR College of Arts and Science Department of Computer Applications Tamil Nadu Tiruchengode637 215 India Sree Saraswathi Thyagaraja College Department of AI & ML Tamil Nadu Pollachi642205 India

ISBN: (纸本)9798331530013

This research study proposes a gesture-based volume control system that combines computer vision and machine learning to improve user interaction with audio devices. By applying the OpenCV library for real-time video processing and MediaPipe's hand-tracking module, the system interprets hand gestures to control the volume. This system measures the distance between the index finger and thumb. Using this distance, the system adjusts the system's audio volume by using the Pycaw library. The purpose is to have a touchless interface wherein the user can control audio levels by simple hand movements to enhance accessibility and usability across various environments. This is an promising alternative to traditional input methods as the demand for more natural human-computer interaction grows, this gesture-based approach represents a leveraging computer vision and machine learning technique, which accurately detects gestures in volume control. The goal of this project is to design a touchless volume control system that relies on gesture input, computer vision, and machine learning techniques in order to bring an intuitive user experience. The proposed system integrates OpenCV for real-time video processing and makes use of Media Pipe's advanced hand-tracking abilities to identify gestures, which are the distance between the thumb and index finger, to control the volume of audio. Pycaw is used to interact with the audio output of the system to dynamically control the volume. This gesture-based interface is designed to improve accessibility, usability, and user experience by providing a modern, intuitive alternative to traditional volume control methods. © 2024 IEEE.

关键词： Gesture recognition

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