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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68829 条记录，以下是1041-1050 订阅

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A Neural Interface System-on-Chip for Nerve Signal Recording and Analysis of Human Gesture 8

A Neural Interface System-on-Chip for Nerve Signal Recording...

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Liu, Junhuo Li, Zhijun Gu, Jason Feng, Ying Li, Guoxin College of Artificial Intelligence Anhui University Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China University of Science and Technology of China Department of Automation Hefei230026 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSCanada Canada School of Automation Science and Engineering South China University of Technology Guangzhou510640 China

ISBN: (纸本)9798350300178

The intensity of surface electromyography (sEMG) reflects the state of muscle activity, and the monitoring of neural activity is accomplished by recording and analyzing sEMG, so as to help the elderly and patients with muscle injury live normally. However, the current products in the literature or on the market cannot support the integration of signal recording and decision making simultaneously. To solve this challenge, a novel neural interface system-on-chip (SoC) is developed, which includes a neural signal recorder, a hardware integrated classifier with signal screening capability and a series of communication interfaces for data transmission. In addition, function circuits consisting of the controller and the clock generator are designed to provide operation instructions and the necessary reference timing. The prototype of the system was developed by using Verilog on FPGA. In the experiments, five volunteer subjects with healthy upper limbs were invited to participate in the verification of model parameter training and real-time gesture recognition. The experimental results show that the average recognition accuracy reach to 98.14%. which is better than the existing model of the same classifier. © 2023 IEEE.

关键词： System-on-chip

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Research on Vibration Displacement Measurement of Sleeper Based on Machine Vision 1

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UNIfied conference of international Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, international conference on Maintenance Engineering, IncoME-V 2023, international conference on the Efficiency and Performance Engineering Network, TEPEN 2023

作者： Chi, Yuliang Gao, Yunpeng Liu, Guiyi Zhang, Chao School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014000 China Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems in Inner Mongolia Autonomous Region Baotou014000 China Baotou Railway Vocational and Technical College Baotou014000 China

ISBN: (数字)9783031494215

ISBN: (纸本)9783031494208

Machine vision technology has the characteristics of high precision, fast speed, non-contact and high degree of automation in displacement detection. It is feasible to apply machine vision technology to the detection of vibration displacement of railway sleeper. In this paper, the vibration displacement measurement technology of railway sleeper is studied, and a machine vision method based on monocular vision measurement is proposed. According to the geometric relationship between the feature points of the target and the corresponding feature points of the space target in the shot image, the pose information of the space target relative to the camera coordinate system is calculated. By monitoring the change of the attitude of the target rigidly connected to the sleeper, the vibration displacement results of the sleeper when the train passes are obtained. The experimental results show that the proposed method meets the requirements of sleeper vibration measurement in terms of measurement accuracy, sampling comment and stability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Displacement measurement

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Fault Diagnostic Opportunities for Robot Servo Motors Using the Physics of Failure Analysis 14

Fault Diagnostic Opportunities for Robot Servo Motors Using ...

引用

14th international conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Zhang, Bo Liang, Shan Wang, Kai Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Computer Science and Technology University of Chemical Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350329988

Joint robots are widely used in various industries, such as aviation, aerospace, and automotive manufacturing. The performance degradation of servo motors can significantly affect the overall performance of the robots because of the core component of joint robots, and therefore, it is critical to detect and address servo motor failures promptly. In this study, we analyze some common causes and mechanisms of performance degradation in robot servo motors using the physics of failure analysis. We also discuss strategies for detecting and diagnosing faults using these mechanisms before the servo motors fail completely. © 2023 IEEE.

关键词： Servomotors

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Research on the Problem of Pure Azimuth Passive Location in UAV Formation Flight Based on Genetic Algorithm

Research on the Problem of Pure Azimuth Passive Location in ...

引用

2023 IEEE international conference on Electrical, automation and computer Engineering, ICEACE 2023

作者： Huang, Jiankai Liang, Xin Duan, Yueqian Science and Technology College of NCHU Information Electronics Department Jiangxi Jiujiang China

ISBN: (纸本)9798350309614

Aiming at the problem of azimuth-only passive positioning of UAV formation in flight, this paper first establishes the polar coordinate equation, and uses the direction information to establish a model under the condition of constant Angle. Secondly, the maximum likelihood estimation method, filtering method and mathematical geometry algorithm are used to reduce the impact of errors, and the coordinates of the drone that's passively receiving the signal are obtained. At the same time, the dynamic programming model is established by observation method and iteration method to reduce the specific position of the UAV and realize the positioning of the UAV. Thirdly, genetic algorithm and hidden circle model are used to determine the deviated UAV radius in the optimal arc, and the specific position of nine UAVs uniformly distributed on the circumference is obtained. Finally, according to the filtering algorithm, the deviation can be removed to realize the effective and specific positioning of the UAV. It is found that in the formation flight of 9 UAVs based on genetic algorithm, using the hidden circle model and genetic algorithm, in addition to 2 UAVs with known serial numbers (1 center of circle), 1 UAVs with unknown serial numbers are needed to adjust the UAVs to return to the ideal position and achieve effective positioning. © 2023 IEEE.

关键词： Genetic Algorithm Maximum Likelihood Estimation Passive Localization Polar Coordinates

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A Case-based Channel Selection Method for EEG Emotion Recognition Using Interpretable Transformer Networks 23

A Case-based Channel Selection Method for EEG Emotion Recogn...

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2023 international conference on computer, Vision and Intelligent technology, ICCVIT 2023

作者： Du, Yang Guan, Zijing Huang, Weichen Zhang, Xichun Huang, Qiyun School of Automation Science and Engineering South China University of Technology China Center for Brain-Computer Interface Pazhou Lab China Research Center for Brain-Computer Interface Pazhou Lab China South China University of Technology China

ISBN: (纸本)9798400708701

Optimizing the selection of features and channels with satisfactory emotion classification accuracy is important for electroencephalograph (EEG)-based emotion recognition. Here, we propose a novel case-based channel selection method based on interpretable transformer networks for emotion recognition. Gradients and relevance of the prediction of the transformer model were used for backpropagation to produce the attention relevance map. Critical channels were selected by ranking the attention relevance value. We test the effectiveness of the proposed method on the multi-channel EEG emotional datasets SEED. The results demonstrated that the method can pick out the critical channels effectively with relatively high classification accuracy. The locations of selected channels converged on the frontal and temporal areas which were consistent with neuroscience findings. Thus, the proposed method has a potential to reduce computation time and assist source localization in cognitive neuroscience studies. © 2023 ACM.

关键词： Emotion Recognition

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A Fine Tuned Ensemble Approach to Classify Requirement from User Story 26

A Fine Tuned Ensemble Approach to Classify Requirement from ...

引用

26th international conference on computer and Information technology, ICCIT 2023

作者： Tasnim, Arpa Akhter, Nazneen Ali, K M Akkas Bangladesh University of Professionals Department of Information and Communication Technology Dhaka Bangladesh Bangladesh University of Professionals Department of Computer Science and Engineering Dhaka Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798350359015

The manual classification process in software requirement Specification (SRS) has several challenges, including subjectivity, time commitment, and the possibility of mistakes and discrepancies. There is a chance of inconsistencies and classification errors when requirements are manually classified because of subjectivity and anomalies. Furthermore, the corresponding manual effort grows increasingly difficult and unfeasible as the volume of requirements increases. This study explores the field of automated classification, highlighting the crucial role of automation in distinguishing between functional and non-functional requirements. Utilizing the PROMISE repository with 969 requirements, the study deploys an ensemble of machine learning classifiers - Random Forest, Multinomial Naive Bayes, Gradient Boosting, XGBoost, and AdaBoost. Based on the test dataset, the empirical results show that the suggested ensemble method achieves a 98% accuracy in binary classification of Functional Requirements (FR) and Non-Functional Requirements (NFR). Moreover, Grid search and hyperparameter optimization methods refine the ensemble's performance, highlighting its usefulness in enhancing the accuracy and consistency of software requirement analysis in the binary classification framework. © 2023 IEEE.

关键词： Ensemble FRs NFRs Software Requirement Specification

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Optimal Guidance Law Considering Coupled Orbit-Attitude for Space Target

Optimal Guidance Law Considering Coupled Orbit-Attitude for ...

引用

2023 international conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： You, Fengqin Zhang, Zhouyu Zhu, Yeqing Wu, Panlong Nanjing University of Science and Technology ZiJin College School of Computer Jiangsu Nanjing China Nanjing University of Science and Technology School of Automation Jiangsu Nanjing China

ISBN: (纸本)9798350312492

Space debris seriously threaten the safety of artificial spacecraft in orbit. To achieve the rapidity of space debris capturing and removal, an optimal guidance law considering coupled orbit-attitude for space non-cooperative target is proposed. Firstly, a relative kinematics model of the spacecraft and the target is constructed, and a coupling control strategy based on time-division multiplexing theory is designed. Then, the optimal guidance law with minimum energy consumption as the cost function is designed, and the acceleration command is adjusted through vector decomposition to reduce the impact of velocity leading angle on the deviation accuracy. Finally, the designed guidance law is simulated and verified in the case of thrust attenuation error, and compared with proportional guidance law. The results show that the proposed optimal guidance law can reduce energy consumption by 56.9% while satisfying the guidance accuracy. © 2023 IEEE.

关键词： Space debris

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Research on CNC Machine Tool Industrial Robot Based on computer Artificial Intelligence technology 6

Research on CNC Machine Tool Industrial Robot Based on Compu...

引用

6th IEEE international conference on automation, Electronics and Electrical Engineering, AUTEEE 2023

作者： Niu, Jingli Liu, Jinqian Henan College of Industry & Information Technology Department of Mechanical Engineering Jiaozuo Henan China Henan Administration of Coal Mine Safety Safety Technology Center Zhengzhou Henan China

ISBN: (纸本)9798350305623

In this paper, intelligent mobile robots suitable for economic CNC machine tools or improved CNC machine tools are studied. The system can realize the following three CNC process: feed, discharge, tool change. It saves labor and reduces production cost. The system is double four-link structure, there is no dead Angle. This paper uses Zigbee wireless communication technology, GPRS technology, 3G communication technology and other advanced technologies to build a CNC machining group network based on wireless communication technology and to design robot automatic loading and unloading mechanism, communication unit between robot and CNC lathe, plan robot loading and unloading running track. In addition, in order to achieve the exact position of unloading and tool change, visual navigation is also installed the intelligent judgment of working environment can be realized. It greatly improves the efficiency and automation of production. © 2023 IEEE.

关键词： CNC machine tool communication technology mobile robot visual system

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A contemporary review of machine learning-based heart disease prediction 2

A contemporary review of machine learning-based heart diseas...

引用

2nd IEEE international conference on IoT, Communication and automation technology, ICICAT 2024

作者： Gupta, Sukriti Tripathi, A. Srivastava, Chaynika Buddha Institute of Technology Department of Computer Science & Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Heart disease remains a leading cause of global mortality, necessitating effective predictive tools. As per the World Heart Federation, it was found that over a billion people globally continue to be affected by heart disease and 20.5 million deaths in 2021 occurred and there is no one-size-fits-all approach which can improve cardiovascular health worldwide (***, 2023). Machine learning emerges as a valuable tool for predicting heart diseases, offering improved accuracy compared to conventional approaches. The study focuses on addressing the global challenge of heart disease by leveraging machine learning for predictive analysis. It focused on increasing early detection so that treatment can be made and save the lives of individuals. The investigation unfolds the way machine learning can be applied to the early identification of cardiac conditions in the modern era. While analyzing machine learning, it appeared as a powerful as well as efficient technology that operates on testing as well as training principles. The research aims to employ classification techniques so it would able to build predictive models that will further uncover hidden patterns and increase accuracy in diagnosis. © 2024 IEEE.

关键词： Adversarial machine learning

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Research on NLOS environmental ranging method based on gradient boosting tree 8

Research on NLOS environmental ranging method based on gradi...

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8th international conference on Electrical, Mechanical and computer Engineering, ICEMCE 2024

作者： Li, Wenyu Cao, Shun Liu, Xianda Wang, Minghao Sheng, Shuan Shenyang University of Chemical Technology School of Information Engineering Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control System Liaoning Shenyang China Shenyang National Research Institute of Intelligent Robots Co. Ltd. Liaoning China

ISBN: (纸本)9798331506230

Indoor distance measurement plays a critical role in positioning services. The complexity of indoor environments, coupled with a limited and small sample size, results in suboptimal distance accuracy. This paper proposes a method for non-line-of-sight distance measurement based on a gradient boosting tree model, effectively addressing the issue of sample size dependency. The random hyperparameter settings of the gradient boosting tree model lead to prolonged fitting times. Additionally, the model utilizes a fixed learning rate, which limits the analysis of features in small samples. To tackle these concerns, we develop a grid optimization algorithm that identifies the best hyperparameter combinations through a hyperparameter grid search. We also implement a weighted value approach and a cosine annealing algorithm to precisely update the learning rate according to training conditions, thus maximizing the learning of small sample features. Our proposed model significantly enhances distance accuracy in non-line-of-sight environments under constraints of training sample size and variety. Comparative experiments demonstrate that our model improves distance accuracy by 63% relative to other machine learning models, with a mean square error of only 0.168m. © 2024 IEEE.

关键词： Distance measurement

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