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Training System of Athletes in Track and Field with Computer Big Data technology 3

Training System of Athletes in Track and Field with Computer...

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3rd international conference on Artificial intelligence and Autonomous robot Systems, AIARS 2024

作者： Liang, Yongzhang Wuchang Shouyi University Wuhan China

ISBN: (纸本)9798350376173

In the pursuit of excellence in competitive sports, improving the performance of track and field athletes is a continuous pursuit. The rise of computer big data technology has brought new breakthroughs to sports training, making outstanding contributions in personalized training, injury prevention, competition analysis, and performance improvement. This article is based on computer big data technology, first analyzing the training needs of track and field athletes and the potential of big data technology. By collaborating with professional track and field teams, multidimensional data including physiological, biochemical, athletic skills, and psychological states of athletes are collected. Machine learning algorithms are utilized for in-depth analysis and personalized training plans are developed. This can promote the modernization of the field of track and field training towards data-driven development, laying a solid foundation for scientific training and coach decision-making in track and field sports. The final results indicate that the average training efficiency of athletes under traditional training methods is about 76%, while the average training efficiency of athletes trained through big data technology can reach about 82%. The use of computer big data technology can significantly improve the accuracy and efficiency of track and field athlete training, which helps to enhance the overall performance of athletes and reduce the risk of injury. Data analysis can also enhance communication between athletes and coaches, thereby optimizing training strategies. Despite the challenges of implementation and data processing, the application prospects of computer big data technology in track and field athlete training systems are very broad through continuous technological innovation and interdisciplinary cooperation. © 2024 IEEE.

关键词： Sports

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Deformable Feature Fusion Network for Multi-Modal 3D Object Detection 3

Deformable Feature Fusion Network for Multi-Modal 3D Object ...

引用

3rd international conference on robotics, Artificial intelligence and Intelligent Control (RAIIC)

作者： Guo, Kun Gan, Tong Ding, Zhao Ling, Qiang Univ Sci & Technol China Dept Automat Hefei Peoples R China Anhui ShineAuto Autonomous Driving Technol Co Ltd Res & Dev Dept Hefei Peoples R China Anhui JiangHuai Automobile Grp Co Ltd Inst Intelligent & Networked Automobile Hefei Peoples R China

ISBN: (纸本)9798350352634;9798350352627

LiDAR and cameras are two widely used sensors in 3D object detection. LiDAR point clouds show geometry knowledge of objects, while RGB images provide semantic information, such as color and texture. How to effectively fuse their features is the key to improving detection performance. This paper proposes a Deformable Feature Fusion Network, which performs LiDAR-camera fusion in a flexible way. We present multi-modal features in the bird's-eye view(BEV), and build a Deformable-Attention Fusion(DAF) module to conduct feature fusion. Besides fusion methods, feature alignment is also important in multi-modal detection. Data augmentation of point clouds may change the projection relationship between RGB images and LiDAR point clouds and causes feature misalignment. We introduce a Feature Alignment Transform(FAT) module and alleviate the problem without introducing any trainable parameters. We conduct experiments on the KITTI dataset to evaluate the effectiveness of proposed modules and the experiment results show that our method outperforms most existing methods.

关键词： 3D object detection multi-modal fusion feature alignment

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Efficiency Improvement of Mobile robot Path Planning using Dingo Optimization Algorithm 3

Efficiency Improvement of Mobile Robot Path Planning using D...

引用

3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Liu, Xiaoyu Zhu, Yuanjing Xu, Qianxue Yang, Jundong Ding, Hongwei Yunnan University School of Information Science and Engineering Yunnan Kunming China Yunnan University Dianchi College Department of Electronic Information Engineering Yunnan Kunming China

ISBN: (纸本)9781665490788

When solving the problem of path planning method for mobile robot obstacle avoidance, the newly proposed Dingo optimization algorithm (DOA) is used for path planning, and the efficiency of path planning is improved by using the advantage of the dingo optimization algorithm with few parameters and fast convergence. At the same time, the path obtained in the grid map is deredundantly processed, and the path length is optimized, which shortens the path length to a certain extent and improves the accuracy of path planning. In order to verify the superiority of the dingo optimization algorithm in solving the problem of mobile robot path planning, it is combined with the wolf pack algorithm (GWO) for path planning on the grid map, and the result shows that the dingo optimization algorithm is more prominent in robot path planning And better adaptability. © 2023 IEEE.

关键词： Motion planning

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Multimodal Fusion Algorithm of AIS, Radar and Fishery Safety Information for Submarine Cable Protection 3

Multimodal Fusion Algorithm of AIS, Radar and Fishery Safety...

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3rd international conference on Artificial intelligence and Autonomous robot Systems, AIARS 2024

作者： Cui, Fengjuan Tian, Tian Xu, Qian Yin, Jie Zhang, Li Li, Yarong Liu, Yang Zhao, Zhen The North China Sea Data and Information Service SOA Qingdao China Qingdao University of Science and Technology Qingdao China

ISBN: (纸本)9798350376173

The current manual approach to assessing external damage to submarine cables lacks standardized risk identification and grading standards, and falls short in providing comprehensive and continuous risk monitoring. To address these issues, this paper introduces a multimodal fusion algorithm for submarine cable protection. It combines AIS, radar, and fishery safety production data: Shore-based small target radar captures ship trajectories within its range, while the ship's AIS trajectory data is obtained using an automatic identification data system. The fishery safety production system contributes fishery ship trajectory information. These data are integrated, resulting in composite track sets. Risk levels for submarine cables are then calculated based on ship positions, trajectories, relative directions, and speeds in the composite track sets, and warnings are generated. The algorithm effectively identifies and evaluates potential risks, enhancing the precision of vessel behavior analysis and reducing the risk of submarine cable damage. © 2024 IEEE.

关键词： Risk assessment

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AI/ML applications in Spoofing Detection in 5G Networks: Challenges and Solutions 3

AI/ML Applications in Spoofing Detection in 5G Networks: Cha...

引用

3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Singh, Monika Hegde, Raveesh Jha, Mahesh Kumar Choudhary, Amar Rubini, P. Cmr Institute of Technology Bengaluru India Alliance University Alliance College of Engineering and Design Bengaluru India Cmr University School of Engineering and Technology Bengaluru India

ISBN: (纸本)9798331515911

5G networks has advanced connectivity, high data, low latency and reliability. Along with these features new challenges come with respect to security, particularly spoofing attacks. One of the necessity in 5G and future wireless communication is to prevent the spoofing attacks depending on the applications. Artificial intelligence (AI) and Machine Learning (ML) present promising solutions for detecting and mitigating spoofing threats in 5G networks. This paper explains the different types of spoofing and applications, challenges, and future prospects of AI/ML in addressing spoofing in 5G networks. AI/ML algorithms can be used in detection of the location of attackers. This paper also analyses current methodologies, highlight key challenges, and discuss potential advancements that could enhance the security of 5G networks. © 2025 IEEE.

关键词： Adversarial machine learning

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Inverse Kinematics Analysis of 5-DOF Cooperative robot Based on Long Short-Term Memory Network 3

Inverse Kinematics Analysis of 5-DOF Cooperative Robot Based...

引用

3rd IEEE international conference on Software Engineering and Artificial intelligence, SEAI 2023

作者： Wang, Songtao Zhang, Yanyan Chen, Sisi Xu, Minghan Yu, Yimeng Liu, Pingxian Nanchang Institute of Technology School of Mechanical Engineering Nanchang China

ISBN: (纸本)9798350337952

To solve the problems of lengthy computation times and slow path searches for the 5-DOF cooperative robot, an algorithm based on the long short-term memory network (LSTM) is proposed in this paper. Firstly, the forward and inverse analytical kinematics models of the 5-DOF cooperative robot are established based on the physical structure. Secondly, the forward and inverse kinematic models are verified by the Matlab robot toolbox. Then, a large amount data of the joints and the corresponding pose data are obtained by the analysis of the kinematics robot. Finally, the algorithm based on the LSTM network is established by training the data of the joints and poses. Compared with the traditional analytical method, the algorithm based on the LSTM network is more efficient and satisfies the demands of real-time computing. © 2023 IEEE.

关键词： Long short-term memory

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AI-Powered Real-Time Math Equation Editor with Multi-Modal Input for Enhanced Interaction 3

AI-Powered Real-Time Math Equation Editor with Multi-Modal I...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Saravanan, Dhanush Muthuraj, Murugesh Rangasamy, Prasanth Raja, S. Tamizharasan, D. K.S.Rangasamy College of Technology Department of Artificial Intelligence and Data Science Tiruchengode India K. S. Rangasamy College of Technology Department of Mathematics Tiruchengode India

ISBN: (纸本)9798331509675

This paper proposes a mobile application that translates vocal input into real-time, editable arithmetic equations, thus serving as a flexible input method for mathematical expressions. The application will allow users to speak, change, and export equations as images. It offers such features as real-time recognition of handwriting, creation of documents from stored files, and scanning pictures to digitize handwritten mathematical content. In future versions, it will incorporate step-by-step solutions for equations. The solution thus enhances access and efficiency in working with mathematical information by the user through offline capability, support for more than one language, and seamless integration with other applications. © 2025 IEEE.

关键词： Character recognition

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MSMEs Readiness for Adopting Artificial intelligence and Machine Learning 3

MSMEs Readiness for Adopting Artificial Intelligence and Mac...

引用

3rd international conference on Advanced Computing Technologies and applications, ICACTA 2023

作者： Patil, Kanchan Pranay Pramod, Dhanya Vijayakumar Bharathi, S. Deemed University Symbiosis Centre for Information Technology Symbiosis International Pune India

ISBN: (纸本)9798350348347

This study explored the factors influencing organizations' artificial intelligence and machine learning technology adoption in the context of MSMEs of developing countries with particular reference to the Indian context. The study shall focus on AI adoption in automotive, industrial manufacturing, consumer products, and aerospace & defence MSMEs. The survey comprised 309 samples. SEM (structural equation modelling) tested the structural model. The factors influencing Artificial intelligence and Machine learning adoption intention for MSME were modelled using an integrated theories approach which included the technology readiness index (TRI), technology Acceptance Model (TAM) and technology-Organization-Environment framework (TOE). The study analyzed the results and stated the implications for theory and practice. © 2023 IEEE.

关键词： Machine learning

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Fuzzy Sliding-Mode Control for robot Manipulators Based on Variable Universe 3

Fuzzy Sliding-Mode Control for Robot Manipulators Based on V...

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3rd IEEE international conference on Digital Twins and Parallel intelligence, DTPI 2023

作者： Zhao, Ruhua Yang, Junjie Li, Xue Mo, Hong Changsha University of Science & Technology School of Electrical & Information Engineering Changsha410001 China

ISBN: (纸本)9798350318470

The inaccuracy of modeling information and external disturbance bring great challenges to the control of robot manipulators. In the paper, an adaptive control strategy of robot manipulators with model uncertainty is presented by integrating variable universe fuzzy control (VUFC) into the sliding-mode control (SMC). The strong robustness of SMC overcomes the interference of uncertainty to the system. In order to effectively alleviate chattering which is easy to occur in traditional SMC, the VUFC technology is adopted to improve the switching control and designs a dynamic variable switching control, which suppress the chattering significantly. Then, a suitable adaptive law is given and the stability of the system is analyzed by means of Lyapunov theorem, which ensure that the system error can converge to near zero. Finally, the comparison results show that this control strategy possesses a better performance than SMC and the fuzzy SMC, which can continuously and stably achieve tracking control. © 2023 IEEE.

关键词： Sliding mode control

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Magnetometer IMU-based Trolley Mapping and Navigation Optimization on Complex Road Surfaces 3

Magnetometer IMU-based Trolley Mapping and Navigation Optimi...

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3rd international conference on Artificial intelligence and Computer Information technology, AICIT 2024

作者： He, Wei Shen, Bin Zhang, ZhiQi Liu, LongJie School of Electrical and Information Engineering Wuhan Institute of Technology WIT Wuhan China

ISBN: (纸本)9798350365443

AHRS-LeGO-LOAM: Based on the LeGO-LOAM algorithm (a lightweight ground-optimized Lidar ranging and mapping method), we have added a new measurement module IMU (AHRS Attitude and Heading Reference System) with magnetometer to detect data deviations caused by asymmetry in the body pose when the robot moves to a non-planar or sunken road section. LeGO-LOAM, a system for rapid mapping of automobiles to determine motion trajectory and pose estimation, can be used to collect point cloud data at nine degrees of freedom after adding a magnetometer. We started by using a point cloud segmentation algorithm to filter out the noise, and then use feature extraction to obtain distinct planar and edge features. We compare the performance of AHRS-LeGO-LOAM with the current LeGO-LOAM, using a data set collected from the variable terrain environment of ground trolleys, and the results show that AHRS-LeGO-LOAM has a higher accuracy rate on the same dataset. We also integrated AHRS-LeGO-LOAM into the SLAM framework to eliminate drift-induced pose estimation errors, and tested them using the KITTI data set. © 2024 IEEE.

关键词： SLAM robotics

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