Prof. Gangyi Ding Profile

Prof. Gangyi Ding

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Proceedings Article | 19 July 2024 Paper

Valve maintenance system based on mixed reality and target recognition technology

Yu An, Zheng Guan, Gangyi Ding

Proceedings Volume 13181, 131816Q (2024) https://doi.org/10.1117/12.3031254

KEYWORDS: Virtual reality, Augmented reality, Target recognition, Education and training, Autoregressive models, Image processing, Data modeling, Target detection, Clouds, Mixed reality

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In view of the current problems in the valve maintenance training process, such as high technical difficulty, reliance on manual experience, error-prone and safety risks, this system comprehensively uses metaverse-related target recognition, technology. Provide new auxiliary tools and training platforms for maintenance personnel. The system uses YOLOv8's improved target recognition model to realize real-time identification and positioning of valve equipment, allowing maintenance personnel to accurately and quickly identify equipment parts. The system uses AR technology to superimpose virtual information on actual equipment, providing maintenance personnel with intuitive guidance and operating steps, effectively reducing the technical threshold for maintenance. In addition, the system also combines virtual reality technology to provide virtual maintenance training scenarios. Maintenance personnel can simulate real maintenance scenarios in a virtual environment for real-time operations and training, thereby improving their skills and abilities in handling actual maintenance. During the system design and implementation process, a series of experimental evaluations were conducted. mAP@0.5 achieves an average accuracy improvement of 3.8% compared to the original model. In addition, the amount of parameters is reduced by 33.78%, and the amount of calculation is reduced by 12.85%. The results show that the real-time enhanced virtual maintenance system reduces maintenance difficulty, reduces human errors, and improves maintenance efficiency. At the same time, in terms of training, the system can effectively assist maintenance personnel in skill development and training in a simulated environment. In summary, the real-time enhanced virtual maintenance system designed and implemented in this study has significant application potential and practical value in the metaverse field to solve many current valve maintenance and training problems.

Proceedings Article | 7 December 2023 Paper

Survey of intelligent program synthesis techniques

Baishun Zhou, Gangyi Ding

Proceedings Volume 12941, 129414G (2023) https://doi.org/10.1117/12.3011627

KEYWORDS: Computer programming, Deep learning, Machine learning, Neural networks, Computer programming languages, Artificial intelligence, Software engineering

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Program synthesis refers to the task of solving a specific problem by automatically generating a computer program. It has received considerable attention from artificial intelligence and programming language communities. Over time, software codes and group wisdom have been accumulated on the internet. Simultaneously, artificial intelligence, such as deep learning, has obtained promising achievements in numerous fields, which has motivated researchers to address the problem of automatic program generation by considering both software engineering and intelligent technology. The key challenges in the field of program synthesis mainly consist of the huge search space of the programs and the ambiguity of user intent. In this study, we analyze program synthesis techniques according to their user intent description, focus on the impact of new technologies on program synthesis, such as data-driven and artificial intelligence, and summarize the pruning methods of program space and search technologies. Further, we discuss the existing challenges in program synthesis technology and present suggestions for further studies in this field.

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