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This book contains the selected and peer-reviewed manuscripts that were presented in the Conferences 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. The aim of COMET 2019 was to present current and on-going research being carried out in the field of mechanical, manufacturing, electrical and electronics and general studies for engineering and technology. Besides, this book also contains the manuscripts from the System Engineering and Energy Laboratory…mehr
This book contains the selected and peer-reviewed manuscripts that were presented in the Conferences 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. The aim of COMET 2019 was to present current and on-going research being carried out in the field of mechanical, manufacturing, electrical and electronics and general studies for engineering and technology. Besides, 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, metal air batteries, advanced battery materials and energy material modelling fields. This volume is the third edition of the progress in engineering technology, Advanced Structured Materials which provides in-depth ongoing research activities among academia of UniKL MSI. Lastly, it is hoped to foster cooperation among organisations and research in the covered fields.
Andreas Öchsner is a Full Professor of Lightweight Design and Structural Simulation at Esslingen University of Applied Sciences, Germany. Having obtained a Dipl.-Ing. degree in Aeronautical Engineering at the University of Stuttgart (1997), Germany, he served as a research and teaching assistant at the University of Erlangen-Nuremberg from 1997 to 2003, while working to complete 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 (2007–2013) 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 Disciplineand Program Director).
Muhamad Husaini Abu Bakar is Director for System engineering and Energy Laboratory and Head of Research and Innovation Section at the Universiti Kuala Lumpur – Malaysian Spanish Institute,Malaysia. Having obtained a Bachelor Degree in Manufacturing Engineering with Management at the Universiti Sains Malaysia (2007), Malaysia, he spent the time from 2007–2012 at the Underwater Robotic Research Group, Universiti Sains Malaysia as a research engineer and awarded Master of Science in advance manufacturing from Universiti Sains Malaysia in 2011. Since 2012 he work as lecturer at Universiti Kuala Lumpur – Malaysian Spanish Institute and obtain his Doctor of Philosophy in Advanced Manufacturing from Universiti Sains Malaysia in 2017. His research interests are related to smart manufacturing, energy, and atomistic modelling. 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.
Faizatul Azwa Zamri completed his Bachelor’s degree in mechanical engineering at Universiti Sains Malaysia, Pulau Pinang, in 2010. In the same year, he worked as a process engineer (vision inspection system and molding) Then, he worked as tutor (part-time) at Universiti Putra Malaysia, Sarawak, Malaysia. He received a Master’s degree in Science (Material science) at Universiti Putra Malaysia, Selangor, Malaysia in 2017. His research interests in mechanical engineering are in the areas of natural fiber composite, quantum modelling and aluminium-ion battery. Currently, he is a doctoral student at Universiti Kuala Lumpur and explores the capabilities of the carbon-based materials especially in the context of alternative energy.
Inhaltsangabe
1. Micro-Power Energy Harvester Using Piezoelectric for Acoustic Soundwave Energy Harvesting.- 2. Damage Diagnosis of a Structural Steel Plate using Wavelet Packet Transform.- 3. A Study on the Influence of Temperature on Steel Corrosion over Time.- 4. Design of a Child Restraint System for Motorcycles.- 5. Drowsiness detection using electroencephalogram anomaly based on spectral entropy features and linear classifier.
1. Micro-Power Energy Harvester Using Piezoelectric for Acoustic Soundwave Energy Harvesting.- 2. Damage Diagnosis of a Structural Steel Plate using Wavelet Packet Transform.- 3. A Study on the Influence of Temperature on Steel Corrosion over Time.- 4. Design of a Child Restraint System for Motorcycles.- 5. Drowsiness detection using electroencephalogram anomaly based on spectral entropy features and linear classifier.
1. Micro-Power Energy Harvester Using Piezoelectric for Acoustic Soundwave Energy Harvesting.- 2. Damage Diagnosis of a Structural Steel Plate using Wavelet Packet Transform.- 3. A Study on the Influence of Temperature on Steel Corrosion over Time.- 4. Design of a Child Restraint System for Motorcycles.- 5. Drowsiness detection using electroencephalogram anomaly based on spectral entropy features and linear classifier.
1. Micro-Power Energy Harvester Using Piezoelectric for Acoustic Soundwave Energy Harvesting.- 2. Damage Diagnosis of a Structural Steel Plate using Wavelet Packet Transform.- 3. A Study on the Influence of Temperature on Steel Corrosion over Time.- 4. Design of a Child Restraint System for Motorcycles.- 5. Drowsiness detection using electroencephalogram anomaly based on spectral entropy features and linear classifier.
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