Data Science and Emerging Technologies

Proceedings of DaSET 2023
2024
ISBN: 978-981-97-0292-3
Verlag: Springer Nature Singapore

Buch, Englisch, Band 191, 579 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1005 g

Reihe: Lecture Notes on Data Engineering and Communications Technologies

The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2023), held online at UNITAR International University, Malaysia during December 4–5, 2023. This book presents current research and applications of data science and emerging technologies. The topics covered are artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning.

Zielgruppe

Research

Autoren/Hrsg.

Bee Wah, Yap

Berry, Michael W.

Al-Jumeily OBE, Dhiya

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data

Über Autor(innen)

Professor Yap Bee Wah is the director of the Research and Consultancy Center at UNITAR International University Malaysia. She is the founding and general chair for DaSET2022: International Conference on Data Science and Emerging Technologies and the editor of the proceedings published in Lecture Notes on Data Engineering and Communications Technologies published by Springer. She was the conference chair of the International Conference on Soft Computing in Data Science (2015–2019 and 2021) and an editor of the SCDS conference proceedings published in the Springer CCIS series. She is also one of the editors of the book titled ‘Supervised and Unsupervised Learning for Data Science’ published by Springer Nature Switzerland AG 2020. She actively published papers in ISI and Scopus journals such as Expert Systems with Applications Journal of Statistical Computation and Simulation, Communications in Statistics-Computation and Simulation, Journal of Clinical and Translational Endocrinology,and Computers, Materials and Continua.

Professor Dhiya Al-Jumeily OBE is a professor of Artificial Intelligence and the president of eSystems Engineering Society. His research focus is on developing AI analytics for improving healthcare and the environment fulfilling the United Nations SDGs. His research has been well-recognized and featured in 300+ peer-reviewed articles, 40+ books/book chapters, and attracted over £7.5M. He has successfully supervised 25+ Ph.D. students to completion and has been an external examiner in UK and global universities. He is actively involved as a member of the editorial board/review committee for numerous international journals. He is the founder/general series chair of the IEEE International Conference on Developments in eSystems Engineering since 2007 and DASET since 2022. He was promoted and appointed by The Queen to the Most Excellent Order of the British Empire, “OBE-Ordinary Officers of the Civil Division of the said Most Excellent Order forthe “Services to Scientific Research”.

Professor Michael W. Berry is the co-author and an editor of sixteen books covering topics in scientific computing, information retrieval, text/data mining, and data science. He is the co-editor of the Soft Computing in Data Science volumes from 2015 to 2021 and Data Science and Emerging Technologies 2022 proceedings by Springer. He is also the co-author of popular books published by Society for Industrial and Applied Mathematics: Understanding Search Engines: Mathematical Modeling and Text Retrieval, Second Edition, and Computational Information Retrieval. He has published over 115 refereed journals and conference publications. He is a member of SIAM, ACM, MAA, ASEE, and the IEEE Computer Society and is on the editorial board of Foundations of Data Science (AIMS) and the SIAM Journal on Matrix Analysis and Applications (SIAM). He is also a certified program evaluator for the Computing Accreditation Commission (CAC) of the Accreditation Board for Engineering and Technology, Inc. (ABET).