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Titlebook: 17th WCEAM Proceedings; Sustainable Manageme Georges Abdul-Nour,Minh Ngoc Dinh,Joseph Mathew Conference proceedings 2024 International Soci

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发表于 2025-3-21 16:35:05 | 显示全部楼层 |阅读模式
期刊全称17th WCEAM Proceedings
期刊简称Sustainable Manageme
影响因子2023Georges Abdul-Nour,Minh Ngoc Dinh,Joseph Mathew
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发行地址Includes the leading global conference on this subject.Provides scientific and academic record of intellectual discussions at the WCEAM.Covers a range of topics related to sustainable management of en
学科分类Lecture Notes in Mechanical Engineering
图书封面Titlebook: 17th WCEAM Proceedings; Sustainable Manageme Georges Abdul-Nour,Minh Ngoc Dinh,Joseph Mathew Conference proceedings 2024 International Soci
影响因子.17th WCEAM Proceedings provides a record of some of the intellectual discussions (including keynote addresses, research paper presentations, panel debates and practical workshops) that took place among the attendees and participants of the 17th World Congress on Engineering Asset Management (WCEAM), held from 18 - 20 October 2023 at the Sheraton Saigon Hotel and Towers, Ho Chi Minh City, Vietnam. The events were organized by the International Society for Engineering Asset Management (ISEAM) and hosted by RMIT University Vietnam LLC (RMIT VN), Ho Chi Ming City. The content of the book includes topics listed below under a general theme of Sustainable Management of Engineered Assets in a Post-Covid World: Industry 4.0, Digital Transformation, Society 5.0 and beyond.. .Sustainable asset investment, acquisition, operations, maintenance, and retirement strategies. .Production-service transformation and product-service systems. .Sustainable asset acquisition, operations, maintenance, and retirement processes. .Modeling and simulation of acquisition, operations, maintenance, and retirement processes. .Reliability and resilience engineering. .Applications of the Fourth Industrial Revolutio
Pindex Conference proceedings 2024
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Yiyuan Zheng,Yanyu Lu,Yuwen Jie,Shan Fucription of a DT designed for intelligent maintenance and, in addition, lists a series of characteristics that must be fulfilled when developing these tools, according to the relevant scientific literature. This paper is an excerpt from different contributions of the authors on this topic.
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David Kritchevsky PhD,Jon A. Story PhDapproach is to train deep learning algorithms to detect stagnant water using the YOLOv5 Instance Segmentation model. For the moment, about two-thirds of the water areas in the validation dataset are correctly predicted, implying that a well-trained deep learning model can effectively yield a more satisfactory result.
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Kaveh Sheikhrezaei,Craig Harveyte the effectiveness of our approach, we conducted experiments using practical data and compared it against alternative graph construction methods. Our findings not only confirm the feasibility and efficacy of our approach but also open up avenues for future research in this domain.
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2195-4356 rs a range of topics related to sustainable management of en.17th WCEAM Proceedings provides a record of some of the intellectual discussions (including keynote addresses, research paper presentations, panel debates and practical workshops) that took place among the attendees and participants of the
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