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Structural Health Monitoring and Engineering Structures: Select Proceedings of Shm&es 2020

為了解決Ntust@ Moodle的問題，作者 這樣論述：

Dr. Tinh Q. Bui is currently an Associate Professor at the Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Japan. He holds other academic positions including Visiting Professor (Dalian University of Technology, China) and Visiting Associate Professor (NTUST, Taiwan)

. Prof. Bui received his PhD in Mechanical Engineering, Vienna University of Technology, Austria, 2009. He serves Editor for Applied Mathematical Modelling, Thin-Walled Structures; Engineering Analysis with Boundary Elements; Scientific Reports, SN Applied Sciences. He was awarded ＂The 2018 JACM Awa

rd for Young Investigators in Computational Mechanics＂ from Japan Association for Computational Mechanics. He is authored and co-authored of over 150 ISI peer-reviewed articles. Prof. Bui’s research interests are computational mechanics, fracture mechanics, composites, computational inelasticity, an

d numerical methods＂.Dr. Thanh Cuong-Le is lecturer at the Faculty of Civil Engineering, Ho Chi Minh City Open University, Vietnam. He received his PhD from Ghent University of Belgium in 2019. His research focuses on computational science and engineering, structural stability, dynamic analysis, pla

tes and shell, optimization and structural health monitoring. He has published papers in Computer Methods in Applied Mechanics and Engineering, Composite structures, and Thin-Walled Structures. Dr. Samir Khatir is currently a Doctor assistant at Ghent university Belgium and adjunct Doctor assistant

at Ho Chi Minh Open university Vietnam. He received PhD in Civil engineering at Ghent university and another PhD in Mechanical engineering from UMBB Algeria. Dr Samir Khatir improved and created many techniques for damage identification. He is authored and co-authored of over 40 ISI peer-reviewed ar

ticles. His primary research interest is in the areas of Civil and Mechanical engineering such as FEM, XFEM, Iso-Geometric Analysis (IGA), Extended Iso-Geometric analysis (XIGA), Dynamic, Static, Damage identification, Fracture mechanics, Optimization, Inverse problem, Wear, Friction, Laminated comp

osites, Delamination, Transmissibility, Fatigue, Bridge, Civil engineering structures, Machine Learning, Model Reduction, Deep Learning, and experimental modal analysis. He is also on the editorial board in many scientific journals.

Nac 2019: Proceedings of the 2nd International Conference ​on Nanomaterials and ​advanced Composites

為了解決Ntust@ Moodle的問題，作者 這樣論述：

Ri-ichi Murakami is a Professor Emeritus of Tokushima University, Japan, and a Professor at the Department of Materials Science and Engineering at the National Taiwan University of Science and Technology (NTUST). He received his Ph.D. from the Tokyo Institute of Technology, Japan. He is an elected f

ellow of Japan Society of Mechanical Engineers. He is Vice Editor-in-Chief of Frontiers in Materials, one of the founders of the International Conference on Advanced Materials Development and Performance and also a committee member of the International Conference on Nanomaterials and Advanced Compos

ites. His research interests include fatigue of surface modified materials and advanced composites, ceramic thin-film coatings and green composites.Pankaj Koinkar received his Ph.D. in Physics (Materials Science) from North Maharashtra University, India, in 2005. He joined the Center for Internation

al Cooperation in Engineering Education (CICEE), Tokushima University, Japan, as an Assistant Professor in March 2007. Currently, he is an Associate Professor at the Department of Optical Science and Technology at Tokushima University. His research areas include 2D nanostructures, field emission mic

roscopy, sensors and engineering education.Tomoyuki Fujii is an Associate Professor at the Department of Mechanical Engineering at Shizuoka University. He received his Ph.D. in Mechanical Engineering from Nagoya University in 2007. Prior to joining Shizuoka University in 2009, he was a researcher at

Nisshin Steel Co., Ltd. His research interests encompass the mechanical and corrosion behavior of advanced materials.Tae-Gyu Kim is a Professor at the Department of Nanomechatronics Engineering at Pusan National University, Korea. His research interests focus primarily on nanotechnology for synthes

is and characterization of CVD boron-doped diamond (BDD), diamond-like carbon (DLC) films, electrospinning nanofabrication, and smart window research. His research relates to the application of diamond electrical devices in the post-silicon era. Recently, he has pioneered single-crystalline and poly

crystalline CVD diamond growth technology on iridium, GaN, and single-crystal diamond substrates using microwave chemical vapor deposition, with a focus on the synthesis of heat sink materials for power devices. The development of optimal BDD electrodes has led to his current research on wastewater

treatment and extreme environmental devices.Hairus Abdullah received his doctoral degree in Material Science and Engineering from NTUST in May 2016. He was also a Senior Lecturer/Assistant Professor at the Department of Industrial Engineering, Universitas Prima Indonesia, Medan, Indonesia. Currently

, he is an assistant professor at the Department of Materials Science and Engineering, NTUST, Taipei, Taiwan. His research fields are photocatalysis (including hydrogen evolution reaction, pollutant degradation, and chemical conversion), electrocatalysis, photocatalytic antibacterial system, and nan

omaterial preparation.

透過趨勢和差異分析、目標市場和價值主張定義、風險管理、原型設計和驗證以及以資料為中心的人工智慧方法；以有效的端到端程序，在產品和服務開發中實施人工智慧。 案例研究：無人機產業。

為了解決Ntust@ Moodle的問題，作者Valentin Jules DE BALTHASAR DE GACHEO 這樣論述：

Creating or enhancing products and services are one of the highest objectives and benefits of AI implementation in businesses, but this topic has not yet received much attention in the literature. This study presents a procedure to guide entrepreneurial, business, and research projects develop comp

etitive solutions integrating AI, more specifically deep supervised learning algorithms using unstructured data. The drone industry is selected as a case study. A transversal method that builds on the main trends and gaps identified in the adoption of AI in businesses is presented and implemented. T

he contribution of this study is threefold: First, the results indicate that the method maximized the chance of commercial success by identifying viable use cases, prevented wasting time and funds, decreased the risks of project’s failure, designed functionalities based on needs and competition, opt

imized data storage, increased model transparency and performance, and guide data collection. The author suggests that the procedure could be applied to other industries. Second, an overview of the drone industry cumulating market, literature and regulation reviews is provided and can guide future p

rojects. Third, the specifications of a drone design are provided and could help focus on the development of AI applications for drones.