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Analysis on the Application of Artificial Intelligence technology in College Teaching 3rd

Analysis on the Application of Artificial Intelligence Techn...

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3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Ren, Yuankun Wenxin, Jiang Lu, Hailan Liaoning Shenyang110036 China Nanning University Guangxi Nanning530200 China

ISBN: (纸本)9783031631351

The application of artificial intelligence technology in university teaching presents broad potential and prospects. Through personalized teaching, artificial intelligence can provide customized teaching materials and guidance based on students’ learning styles and levels;Through big data analysis, artificial intelligence provides teachers with detailed information on students’ learning situations, which helps to better guide and coach students;At the same time, artificial intelligence can also utilize virtual laboratories and simulated environments to develop safer and more practical learning experiences. In addition, artificial intelligence technology can also provide automated evaluation and feedback, reducing the workload of teachers. In summary, the application of artificial intelligence technology in university teaching can improve students’ learning outcomes and teachers’ teaching quality, bringing new opportunities for innovation and progress in the field of education. With the further development of technology and the continuous promotion of applications, artificial intelligence will continue to play a more important role, laying a solid foundation for cultivating more outstanding talents in higher education. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Artificial intelligence

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A Simulation Framework for Vision-Based Target Tracking Control of UAVs 3rd

A Simulation Framework for Vision-Based Target Tracking Con...

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3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Zhu, Ridong Sun, Meng The 9th Academy Unmanned System Center China Aerospace Science and Technology Corporation Beijing China Aerospace Times Feihong Technology Company Limited Beijing China

ISBN: (纸本)9789819711062

This work focuses on visual-based target tracking of drone via visual simulation system. A simulation platform is particularly designed to simulate the environments in real-world applications. The platform follows a modular design. In this platform, Unreal Engine is chosen as the rendering platform, Airsim is employed to construct sensor models and acquire the kinematic state of drone body and environmental information. The drone is controlled by PX4 autopilot, and trajectory is planned by EGO-Planner. The target recognition and tracking is achieved by a siamese-based tracking algorithm. Four flight simulation experiments are conducted to verify the use of the developed framework for vision-based tracking, which demonstrate the usefulness and applying method of the simulation system for UAVs in disturbance scenarios. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Drones

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Encoding method for computer-Generated Hologram based on curve descriptions 3

Encoding method for Computer-Generated Hologram based on cur...

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3rd international conference on Optics and Image Processing, ICOIP 2023

作者： Li, Chunqi Huang, Qitai Ren, Jianfeng School of Optoelectronic Science and Engineering Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou215006 China Key Lab of Advanced Optical Manufacturing Technologies of Jiangsu Province Key Lab of Modern Optical Technologies of Education Ministry of China Soochow University Suzhou215006 China

ISBN: (纸本)9781510667426

computer-Generated Hologram (CGH) can be used to detect aspheric surface with high accuracy. In order to improve the encoding efficiency of CGH, this paper proposes an encoding method to describe the engraved fringes in segments using the arc as the primitive. Firstly, the phase contour boundary is obtained, and then the boundary is discretized by Newton iteration method. Finally, the discrete points are encoded with the circular arc as the primitive based on the minimum rms criterion of residual error, and the engraved fringes are obtained. In this paper, the CGH is designed, encoded and fabricated for an aspheric surface. The encoding file is only 7M under the premise of encoding accuracy better than λ / 100 rms, which proves that this method can greatly improve the encoding efficiency compared with linear encoding. Finally, all errors of CGH are analyzed and summarized, and the root-mean-square error of all errors was 0.00283 λ ,which proves the feasibility of the encoding method in this paper. © 2023 SPIE. All rights reserved.

关键词： Errors

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Surface defect detection of the power machinery based on deep learning 3

Surface defect detection of the power machinery based on dee...

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3rd international conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Chen, Tao Zhao, Yutong Li, Bo Ding, Tianhong Cui, Mengmeng Shui, Chongyuan Sichuan Institute of Product Quality Supervision Inspection and Testing Chengdu610000 China The Key Laboratory of Power Machinery and Engineering of Education Ministry Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781510668522

With the rapid development of machine learning methods, deep learning models based on big data and computer arithmetic are widely used in various scenarios, including target detection and image recognition. In order to detect surface defects of the power machinery more rapidly and accurately, this paper investigates the performance of various convolutional neural network models in the task of detecting surface defects, identifies relatively excellent detection models based on the confusion matrix, and summarizes the more appropriate detection scenarios for different models. The results indicate that EfficientNet has good comprehensive performance in detection tasks. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Surface defects

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A Belief Propagation Cooperative Localization Algorithm in GNSS-Loss Environments 3

A Belief Propagation Cooperative Localization Algorithm in G...

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3rd international conference on Digital Signal and computer Communications, DSCC 2023

作者： Ma, Fei Tan, Guoping Zhou, Siyuan Hu, Hexuan College of Computer and Information Hohai University Jiangsu Intelligent Transportation and Intelligent Driving Research Institute Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University College of Computer and Information Hohai University Nanjing China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

When vehicles are in driving environments such as urban roads and tunnels, the global navigation satellite system (GNSS) signal can fail to achieve positioning due to occlusion. Cooperative positioning can effectively improve the accuracy and coverage of vehicle positioning. In this paper, we address the vehicle localization issue in GNSS-Loss driving environments and with random packet loss due to wireless communications. We propose an improved cooperative localization algorithm based on belief propagation, which first linearizes the measurement model of distance by statistical linear regression method, then performs belief propagation based on the linearized model, and solves the packet loss problem by expanding the dimension of the vehicle state. From the simulation results, the algorithm can effectively reduce the impact of packet loss and improve the vehicle localization accuracy. © 2023 SPIE.

关键词： Belief propagation

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A three-dimensional DV-Hop algorithm based on the improved grey wolf algorithm for wireless sensor networks 3

A three-dimensional DV-Hop algorithm based on the improved g...

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3rd international conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Ye, Shuai Yu, Xiuwu Liu, Yong School of Electrical Engineering University of South China Hengyang China

ISBN: (纸本)9781510668522

Location technology has become one of the core technologies of the Internet of Things, especially for wireless sensor networks. The DV-Hop algorithm is used in various situations as one of the representative algorithms. Aiming at the large positioning error of the DV-Hop algorithm, this paper proposes a three-dimensional DV-Hop algorithm based on the improved Grey Wolf algorithm (TDIGW). First of all, the algorithm refines the number of hops through a multicommunication radius strategy, which reduces errors caused by the number of node hops. Then, mean square error is introduced to optimize the average hop distance of the beacon nodes. Finally, the grey wolf algorithm with dynamic weight factor optimization is used instead of least squares to calculate the coordinate positions of the unknown nodes. The simulation results show that compared with the traditional 3D-DVHop algorithm and other *** average localization error of this algorithm is reduced by 20.13%, 12.62% and 8.98% respectively. The algorithm proposed in this paper reduces the localization error effectively © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Sensor nodes

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Research and application based on simulation of ESM model 3

Research and application based on simulation of ESM model

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3rd international conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Wang, Jingyi Fu, Yucheng Zhang, Yang Computer Science Shanghai University Shanghai China Mathematics Shanghai University Shanghai China

ISBN: (纸本)9781510668522

In this paper, simulation is based on the ESM model, which is traditionally characterized by high nonlinearity and high uncertainty. The complexity of the system poses a great challenge for its overall characterization. Modern simulation technology can perform detailed numerical modeling and simulation calculations to realize the analysis and prediction of the system operation state, providing an effective research tool and decision support for the construction of the ESM model optimization system. In this paper, the simulation application of ESM model is based on matrix equation and dynamical system, and the sensitivity analysis is attempted, which proves that the simulation effect of ESM model is good and has good research value and application significance, in order to provide some reference significance for the research in other fields. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Sensitivity analysis

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Maximum Entropy Inverse Reinforcement Learning based Trajectory Planning for Autonomous Driving 3

Maximum Entropy Inverse Reinforcement Learning based Traject...

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3rd international conference on High Performance Computing and Communication engineering, HPCCE 2023

作者： Zhang, Puhao Xie, Shumin Lu, Xiaoya Zhong, Zuodong Li, Qing School of Automation and Electrical Engineering Beijing University of Science and Technology 30 Xueyuan Road Haidian District Beijing100083 China School of Mechanics and Civil Engineering and Architecture Northwestern Polytechnical University 127 Youyi West Road Xi'an710072 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education 30 Xueyuan Road Haidian District Beijing100083 China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

With the rapid advancement of autonomous driving technology, effective trajectory planning has become crucial for ensuring road safety and driving efficiency. Traditional trajectory planning methods often rely on preset rules and models, making them ill-suited for the complex and dynamic traffic environment. To address this, a Maximum Entropy Inverse Reinforcement Learning (MaxEnt IRL) based trajectory planning method is proposed in this paper, aiming at learning from expert driving behaviors to infer an efficient reward function, which in turn guides decision-making and path planning for autonomous vehicles. This study begins by analyzing expert driving data to extract key state and action features. Then, the MaxEnt IRL algorithm is applied to learn the reward function underlying these features, reflecting the decision-making logic of expert drivers. The learned reward function is subsequently used to guide the trajectory planning of the autonomous driving system, generating safe and efficient driving paths. A series of experiments conducted in a simulated environment demonstrate that the MaxEnt IRL-based method proposed in this paper exhibits higher adaptability and efficiency in handling complex traffic scenarios compared to traditional trajectory planning methods. © 2024 SPIE.

关键词： Decision making

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Comparison of Non-Overlap and Overlap Savonius Wind Turbines in the Physics Aspect Using Computational Fluid Dynamics Method 3

Comparison of Non-Overlap and Overlap Savonius Wind Turbines...

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3rd international Symposium on Physics and Applications 2023, ISPA 2023

作者： Nensy Irawan, Elysa Yamashita, Ken-Ichiro Fujita, Goro Functional Control Systems Shibaura Institute of Technology Tokyo Japan Department of Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Department of Electrical Engineering Salesian Polytechnic Tokyo Japan Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan

Wind energy has good potential as a renewable energy source. Savonius-type wind turbines can provide power generation at a low cost with minimal environmental impact. Due to its low efficiency, researchers were focused on increasing it through many methods, such as applying twisted-bladed, optimizing the blade shape, and applying overlap. Most researchers have studied the effects of overlap on Savonius blades only in terms of performance improvements. This study evaluates the effect of overlap on the Savonius blade from a physics perspective using the Computational Fluid Dynamics method to get a new approach based on the improvement. The models are 2-bladed Savonius with non-overlap and 0.2 overlap. The main software used is Ansys Student 2023 R2. The turbulent model chosen is a realizable k-ïσ enhanced wall treatment. Then, pressure and velocity coupling were done using SIMPLE: 2nd order upwind, 1st order implicit. As a result, the overlap model has a higher reverse flow but lower pressure for all Tip Speed Ratio. Another finding shows that turbulent kinetic energy decreases with overlap. For the non-overlap model, the amount of turbulence is greater downstream, which causes vortices to form and lowers turbine performance. So, the effects of the overlap blade result in higher average Torque Coefficient than non-overlap. © Published under licence by IOP Publishing Ltd.

关键词： Wind turbines

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IoT-Based Secure Healthcare Framework Using Blockchain technology with Nature-Inspired Optimization Algorithms 3rd

IoT-Based Secure Healthcare Framework Using Blockchain Techn...

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3rd international conference on Emerging Electronics and Automation, E2A 2023

作者： Tripathy, Ramamani Satyanarayana Murty, P.T. Maram, Balajee Garg, Ankit Daniya, T. Santhosh Kumar, B. Computer Science and Engineering Chitkara University Himachal Pradesh India Shri Vishnu Engineering College for Women Bhimavaram India AIT-Department of Computer Science and Engineering Chandigarh University Mohali GharuanPunjab140055 India GMR Institute of Technology Rajam532127 India Telangana Ibrahimpatnam501506 India

ISBN: (纸本)9789819730896

This study introduces a novel method for resolving security and privacy issues in IoT-based healthcare systems by combining blockchain technology with optimization algorithms that are inspired by natural processes. Concerns concerning the danger of private patient data have been raised by the healthcare industry's explosive growth of IoT applications. We provide a comprehensive framework that makes use of the security capabilities built into blockchain to guarantee data integrity, authentication, and access control in order to reduce these risks. In order to improve system performance and resource allocation, we also develop optimization algorithms that are inspired by nature. The architecture of the framework includes smart contracts, communication protocols, and secure data flow to automate business processes within the healthcare ecosystem. Our method improves security while maximizing resource utilization by fusing blockchain's tamper-proof record with the adaptability of nature-inspired algorithms. The effectiveness of the suggested framework is assessed using simulations or real-world testing and benchmarked against current techniques. In the end, this research helps build a robust and effective healthcare framework that protects patient information, respects privacy, and improves the overall effectiveness of IoT-enabled healthcare systems. Additionally, the system's effectiveness and scalability can be improved by including optimization techniques that draw inspiration from nature. In order to create a safe and effective healthcare environment, this research paper offers a comprehensive framework that blends IoT, blockchain, and nature-inspired optimization algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data integrity

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