Proceeding of the 3rd International Conference on Electronics, Biomedical Engineering, and Health Informatics

ICEBEHI 2022, 5¿6 October, Surabaya, Indonesia
Herausgegeben:Triwiyanto, Triwiyanto; Rizal, Achmad; Caesarendra, Wahyu

• Gebundenes Buch

Produktbeschreibung

This book presents high-quality peer-reviewed papers from the International Conference on Electronics, Biomedical Engineering, and Health Informatics (ICEBEHI) 2022 held at Surabaya, Indonesia, virtually. The contents are broadly divided into three parts: (a) Electronics, (b) Biomedical Engineering, and (c) Health Informatics. The major focus is on emerging technologies and their applications in the domain of biomedical engineering. It includes papers based on original theoretical, practical, and experimental simulations, development, applications, measurements, and testing. Featuring the latest advances in the field of biomedical engineering applications, this book serves as a definitive reference resource for researchers, professors, and practitioners interested in exploring advanced techniques in the fields of electronics, biomedical engineering, and health informatics. The applications and solutions discussed here provide excellent reference material for future product development.

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Produktdetails

• Lecture Notes in Electrical Engineering 1008
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-99-0247-7
• 2023
• Seitenzahl: 736
• Erscheinungstermin: 30. April 2023
• Englisch
• Abmessung: 241mm x 160mm x 34mm
• Gewicht: 1388g
• ISBN-13: 9789819902477
• ISBN-10: 9819902479
• Artikelnr.: 67168881

Autorenporträt

Dr. Triwiyanto received the B.S. degree in Physics from Airlangga University, Indonesia, M.S. degree in Electronic Engineering from the Institut Teknologi Sepuluh Nopember Surabaya, Indonesia, in 2004, and the Ph.D. degree in Electrical Engineering from Gadjah Mada University, Yogyakarta, Indonesia, in 2018. From 1998 to 2004, he was Senior Lecturer with the Microcontrollers Laboratory. Since 2005, he has been Assistant Professor with the Medical Electronics Technology Department, Health Polytechnic Ministry of Health Surabaya, Indonesia. In 2018, Triwiyanto received the best Doctoral Student Award from Gadjah Mada University. Additionally, he is Editor-in-Chief in several peer review journals, Chairman, and Technical Programme Committee in several international conferences. His current research interests include microcontroller, electronics, biomedical signal processing, machine learning, rehabilitation engineering, and surface electromyography (sEMG)-based physical human-robot interactions.  Dr. Achmad Rizal received bachelor of engineering in telecommunication engineering from STT Telkom (now, Telkom University), Bandung, Indonesia, in 2000. He received master degree in biomedical engineering from Institut Teknologi Bandung, Bandung, Indonesia, in October 2006. He received Ph. D degree from Universitas Gadjah Mada, Yogyakarta, Indonesia. His research interests include biomedical signal processing, biomedical image processing, biomedical instrumentation, and telemedicine. Now, he is Associate Professor in School of Electrical Engineering, Telkom University.  Dr. Wahyu Caesarendra is Assistant Professor at the Faculty of Integrated Technologies, Universiti Brunei Darussalam, since October 2018. He received Doctor of Philosophy degree from the University of Wollongong in 2015. He worked as Postdoctoral Research Fellow in Rolls-Royce@NTU Corp Lab, School of Mechanical andAerospace Engineering, Nanyang Technological University, Singapore, from February 2017 to September 2018. In 2011, Wahyu Caesarendra was awarded of University Postgraduate Award and International Postgraduate Tuition Award from the University of Wollongong. He worked in the automotive and electrical company prior to joining Diponegoro University as Lecturer in 2007. He was Visiting Assistant Professor at the National Taiwan University of Science and Technology from August 5 to 11, 2019. He has authored more than 130 research articles in journals and conference proceedings. He is also Academic and Guest Editor in peer-reviewed journals. His research interest includes vibration condition monitoring, fault diagnosis and prognosis, mechatronics and robotics, machine learning and deep learning, mechanical design and 3D printing, smart manufacturing, and IoT.

Inhaltsangabe

A Preliminary Study of Vehicle License Plate Detection and Identification.- Feature Selection using Extra Trees Classifier for Research Productivity Framework in Indonesia.- A Survey on Big Data Analytics for Load Prediction in Smart Grids.- Analysis of Three Phase Induction Motor Speed Performance with Load Torque Changes Using Inverter Space Vector Pulse Width Modulation (SVPWM) Control.- Assessing the Effect on Cognitive Workload Index, EEG Band Ratio's, Band Frequencies Using Band Power and Implementing Machine Learning Classification.- Fetal ECG Signal Processing Using One-Dimensional Convolutional Neural Network (1-D CNN) for Fetal Arrhythmias Detection.- Diabetic Retinopathy Classification based on Fundus Image using Convolutional Neural Network (CNN) With MobilenetV2.- Image Improvement and Dose Reduction on Computed Tommography Mastoid Using Interactive Reconstruction.- Classification of Pneumonia Based on X-Ray Images with ResNet-50 Architecture.- A Model Convolutional NeuralNetwork for Early Detection of Chili Plant Diseases in Small Datasets.- Early Risk Pregnancy Prediction Based on Machine Learning Built on Intelligent Application using Primary Health Care Cohort Data.

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A Preliminary Study of Vehicle License Plate Detection and Identification.- Feature Selection using Extra Trees Classifier for Research Productivity Framework in Indonesia.- A Survey on Big Data Analytics for Load Prediction in Smart Grids.- Analysis of Three Phase Induction Motor Speed Performance with Load Torque Changes Using Inverter Space Vector Pulse Width Modulation (SVPWM) Control.- Assessing the Effect on Cognitive Workload Index, EEG Band Ratio’s, Band Frequencies Using Band Power and Implementing Machine Learning Classification.- Fetal ECG Signal Processing Using One-Dimensional Convolutional Neural Network (1-D CNN) for Fetal Arrhythmias Detection.- Diabetic Retinopathy Classification based on Fundus Image using Convolutional Neural Network (CNN) With MobilenetV2.- Image Improvement and Dose Reduction on Computed Tommography Mastoid Using Interactive Reconstruction.- Classification of Pneumonia Based on X-Ray Images with ResNet-50 Architecture.- A Model Convolutional NeuralNetwork for Early Detection of Chili Plant Diseases in Small Datasets.- Early Risk Pregnancy Prediction Based on Machine Learning Built on Intelligent Application using Primary Health Care Cohort Data.