This book contains the selected, peer-reviewed manuscripts presented at the Conference on Multidisciplinary Engineering and Technology (COMET 2019), held at the University Kuala Lumpur Malaysian Spanish Institute (UniKL MSI), Kedah, Malaysia, from September 18 to 19, 2019. This event presented research being carried out in the field of mechanical, manufacturing, electrical and electronics for engineering and technology. This book also contains the manuscripts from the System Engineering and Energy Laboratory (SEELAB) research cluster, UniKL, which is actively doing research mainly focused on artificial intelligence, Internet of things, metal air batteries, advanced battery materials and energy material modelling fields. This book is the fourth edition of the progress in engineering technology, Advanced Structured Materials which provides in-depth ongoing research activities among academia of UniKL MSI.

Autorentext

Muhamad Husaini Abu Bakar is a Director for System engineering and Energy Laboratory and at the Universiti Kuala Lumpur Malaysian Spanish Institute, Malaysia. From 2017 till now, he also holds the position as Head of Research and Innovation Section at the same university. He has published over 50 scientific publications in Deep Learning, computational atomistic and metal-air battery. His research activities were recognized by the innovation award of PECIPTA, IIDEX, ICOMPEX, I-ENVEX and MARA due to his innovative invention in smart material and smart monitoring system.

Mohd Nurhidayat Zahelem is a doctoral student at Universiti Kuala Lumpur. From 2016 to 2018, he was a senior lecturer at the Universiti Kuala Lumpur Malaysian Spanish Institute, Malaysia and held the position as Head of Mechanical Section. From 2014 to 2015, he has been appointed as Programme Coordinator for Bachelor of Engineering Technology (Hons.) in Mechanical (Automotive). Andreas Öchsner is a Full Professor of Lightweight Design and Structural Simulation at Esslingen University of Applied Sciences, Germany. After completing his Dipl.-Ing. degree in Aeronautical Engineering at the University of Stuttgart (1997), he served as a research and teaching assistant at the University of Erlangen-Nuremberg from 1997 to 2003 while pursuing his Doctor of Engineering Sciences (Dr.-Ing.) degree. From 2003 to 2006, he was an Assistant Professor at the Department of Mechanical Engineering and Head of the Cellular Metals Group affiliated with the University of Aveiro, Portugal. He spent seven years (20072013) as a Full Professor at the Department of Applied Mechanics, Technical University of Malaysia, where he was also Head of the Advanced Materials and Structure Lab. From 2014 to 2017 he was a Full Professor at the School of Engineering, Griffith University, Australia and Leader of the Mechanical Engineering Program (Head of Discipline and Program Director).

Klappentext
This book contains the selected, peer-reviewed manuscripts presented at the Conference on Multidisciplinary Engineering and Technology (COMET 2019), held at the University Kuala Lumpur Malaysian Spanish Institute (UniKL MSI), Kedah, Malaysia, from September 18 to 19, 2019. This event presented research being carried out in the field of mechanical, manufacturing, electrical and electronics for engineering and technology. This book also contains the manuscripts from the System Engineering and Energy Laboratory (SEELAB) research cluster, UniKL, which is actively doing research mainly focused on artificial intelligence, Internet of things, metal air batteries, advanced battery materials and energy material modelling fields. This book is the fourth edition of the progress in engineering technology, Advanced Structured Materials which provides in-depth ongoing research activities among academia of UniKL MSI.

Inhalt
1. Vibration Response of Magnetorheological Elastomer Sandwich Plate.- 2. Nonlinear Control of Magnetorheological Fluid Electrohydraulic Positioning System.- 3. Development of Magnetorheological Fluid (MRF) Powertrain for Electric Vehicle Application.- 4. GPU Accelerated Vehicle Detection for Roads.- 5. Anomaly Vehicle Detection using Deep Neural Network.