The presented book comprised the selected peer-reviewed full-text papers from the 11th Asia Conference on Mechanical and Materials Engineering (ACMME 2023, Sapporo, Japan, during June 8-11, 2023). The issue is dedicated to recent problems and engineering solutions in the area of mechanical engineering and engineering management and will be helpful to many specialists in the mentioned branches of engineering sciences. Aerodynamic Analysis, Design, Simulation, Wing Profile, Linear Motor, Underwater Shock Loading, Fiber-Reinforced Composite, Mechanical Properties, Engineering Management, Supply Disruption, Inventory Management, Techno-Economic Feasibility Materials Science, General Engineering, Mechanical Engineering.

Selected peer-reviewed full text papers from the 11th Asia Conference on Mechanical and Materials Engineering (ACMME 2023) Selected peer-reviewed full text papers from the 11th Asia Conference on Mechanical and Materials Engineering (ACMME 2023), June 8-11, 2023, Sapporo, Japan

Selected peer-reviewed extended articles based on abstracts presented at the 11th Asia Conference on Mechanical and Materials Engineering (ACMME 2023) Aggregated Book

Selected peer-reviewed full text papers from the 8th Asia Conference on Mechanical and Materials Engineering Selected, peer-reviewed papers from the 8th Asia Conference on Mechanical and Materials Engineering (ACMME 2020), June 11-14, 2020, Singapore, Singapore

5th ACMME 2017 Selected, peer reviewed papers from the 5th Asia Conference on Mechanical and Materials Engineering (ACMME 2017), June 9-11, 2017, Tokyo, Japan

6th ACMME 2018 Selected, peer reviewed papers from the 6th Asia Conference on Mechanical and Materials Engineering (ACMME 2018), June 15-18, 2018, Seoul, South Korea

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.