Multimodal and Tensor Data Analytics for Industrial Systems Improvement / Springer Optimization and Its Applications Bd.211 (PDF)
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Advancements in sensing technologies and the shift toward the Internet of Things (IoT) has transformed and will continue to transform data analytics by producing new requirements and more complex forms of data. The abundance of data creates an unprecedented opportunity to design more efficient systems and make near-optimal operational decisions. On the other hand, the structural complexity and heterogeneity of the generated data pose a significant challenge to extracting useful features and patterns for making use of the data and facilitating decision-making. Therefore, continual research is needed to develop new statistical and analytical methodologies that overcome these data challenges and turn them into opportunities.
Nathan Gaw is an Assistant Professor of Data Science in the Department of Operational Sciences at Air Force Institute of Technology, Wright-Patterson AFB, Ohio, USA. His research develops new statistical machine learning algorithms to optimally fuse high-dimensional, multi-modal data sources to support decision making in military, healthcare and remote sensing. He received his B.S.E. and M.S. in biomedical engineering and a Ph.D. in industrial engineering from Arizona State University (ASU), Tempe, AZ, USA, in 2013, 2014, and 2019, respectively. Dr. Gaw was a Postdoctoral Research Fellow at the ASU-Mayo Clinic Center for Innovative Imaging (AMCII), Tempe, AZ, USA, from 2019-2020, and a Postdoctoral Research Fellow in the School of Industrial and Systems Engineering (ISyE) at Georgia Institute of Technology, Atlanta, GA, USA, from 2020-2021. He has also served as chair of the INFORMS Data Mining Society, and a member of IISE and IEEE.Panos M. Pardalos is Distinguished Professor Emeritus of Industrial and Systems Engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor in Industrial & Systems Engineering. He is also an affiliated faculty member of the Computer and Information Science Department, the Hellenic Studies Center, and the Biomedical Engineering Program. He is also the Director of the Center for Applied Optimization. Dr. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing. He has co-authored and co-edited more than 30 books, as well as publishing more than 600 journal articles and conference proceedings. Prof. Pardalos is a Fellow of AAAS (American Association for the Advancement of Science), Fellow of American Institute for Medical and Biological Engineering (AIMBE), andEUROPT. He is a Distinguished
Mostafa Reisi Gahrooei is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Florida. His research interests focus on data-driven modelling and monitoring complex and distributed systems by developing efficient methodologies and algorithms for modelling high-dimensional and multimodal data. The applications of his work are in precision agriculture, manufacturing, healthcare, and transportation systems. He is a co-director of the Data Informatics for Systems Improvement and Design (DISIDE) lab. Dr. Reisi is a member of the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial and Systems Engineers (IISE).
- 2024, 2024, 394 Seiten, Englisch
- Herausgegeben: Nathan Gaw, Panos M. Pardalos, Mostafa Reisi Gahrooei
- Verlag: Springer Nature Switzerland
- ISBN-10: 3031530926
- ISBN-13: 9783031530920
- Erscheinungsdatum: 16.05.2024
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 13 MB
- Ohne Kopierschutz
- Vorlesefunktion
Schreiben Sie einen Kommentar zu "Multimodal and Tensor Data Analytics for Industrial Systems Improvement / Springer Optimization and Its Applications Bd.211".
Kommentar verfassen