Integrated Systems: Data Driven Engineering (eBook, PDF)

Redaktion: Alam, Mohammad-Reza; Fathi, Madjid

• Format: PDF

Produktbeschreibung

The term "integrated system" denotes the seamless collaboration of numerous (potentially unrelated) subsystems to achieve a specific goal. It involves combining various components-hardware, software, networks, and workflows-into a unified system that operates cohesively. Widely utilized across scientific and technological domains, integrated systems aim to elevate coherence, efficiency, and overall functionality quality. The Integrated System Design and Technology (ISDT) conference convenes a distinguished group of leading scientists with diverse backgrounds and notable achievements in technological innovation with the goal of fostering cross-disciplinary research and innovation. This gathering serves as an enabler for addressing major scientific and societal challenges that necessitate integrated systems, emphasizing the importance of collaboration in overcoming complex issues. The book at hand includes peer-reviewed research results that were presented and critically discussed duringthe ISDT 2023 which were held in Antalya, Turkey, in May 2023.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 357
• Erscheinungstermin: 16. September 2024
• Englisch
• ISBN-13: 9783031536526
• Artikelnr.: 71749113

Autorenporträt

Professor Mohammad-Reza Alam holds the American Bureau of Shipping Chair in Ocean Engineering and is Professor and Vice Chair of the Department of Mechanical Engineering at the University of California, Berkeley. His research interests include theoretical and experimental fluid dynamics, ocean and coastal waves phenomena, dynamical systems and nonlinear dynamics, and fluid flow controls. He received his PhD from the Massachusetts Institute of Technology in 2008 and joined the faculty of UC Berkeley in 2011. Professor Alam serves as the director of the "Ocean and Coastal Science and Engineering" program and the "Theoretical and Applied Fluid Dynamics Laboratory" at UC Berkeley.   Madjid Fathi is a professor at the Department of Electrical Engineering  and Computer Science, University of Siegen. He is the Chair and Director  of the Institute of Knowledge-Based Systems and Knowledge Management.  Before he got to Siegen he was visiting Professor at UNM, Florida State and  Georgia Tech. in USA. He established the Research Center KMIS  (Knowledge Management & Intelligent System) in 2007.  He did his sabbatical in U.C. Berkeley from 2012.-2013 at  BISC (Berkeley Initiative of Soft Computing) by Professor Zadeh, the Father of Fuzzy Logic.  His research interests are focused on AI & Knowledge Based system and knowledge management applications  in medicine and engineering, computational intelligence and nowledge discovery from text (KDT). Dr. Fathi has published 3 text and 5 edited books, with his students he published more than 250 papers receiving 4 best paper awards. His recent published book "Computer Aided Writing" by springer published in 2020. He is also the editor of the book series "Integrated Systems: Innovations and Applications" published by Springer. the last one will be published in june 2024. 

Inhaltsangabe

Automated Photonic Waveguide Loss Measurement using Out-scattering Light Method.- Interpretable Prototype Discovery in Deep Learning-based Time Series Classification.- One-Shot Defect Fingerprint Comparability Using Siamese Networks for Wafer Map Similarity in Semiconductor Manufacturing.- Opportunities of Data Driven Medicine: Collection, Transfer, and Processing of Vital Data inOutpatient Care.- Performance and Optimization of Microfluidic Channels with Acute Angles and SerpentineCurvatures.- Swimming Robots for Targeted Chaotic Mixing in Viscous Environments.- Adaptive Hierarchical Meta-scheduling for Distributed Time-triggered Systems with Diverse Internaland System Architectures.- Cognitive Controllable Local System Improving Blackstart Resilience in Smart Distribution Grids.- Real-Time Anomaly Detection in Connected Autonomous Vehicles: A Data-Driven Approach.- MASTER-XR: Mixed reAlity ecoSystem for TEaching Robotics in manufacturing.- Semantically Enriched Interfaces for ProductConfiguration.