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This book details how artificial intelligence and other informatic methods can be applied to the field of tribology. Using problems often found within tribological condition monitoring, behaviour prediction, system optimization and mechanism analysis, the book covers methods used such as Artificial Neural Networks (ANN). Including case studies throughout, the book offers an accessible introduction to tribological research, beginning with background on the theory behind tribo-informatics, and updates in the latest technology. It describes how to establish a tribo-informatics database, methods through which to express tribo-systems such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF), and its applications. It can be used in state monitoring, behaviour prediction and system optimization. Through case studies, practical examples of how tribo-informatics can be implemented are shown throughout various industries. This book will be of interest to students and researchers in the field of tribology, friction, wear and artificial intelligence.
This book presents innovative solutions utilising informatics to deal with various issues related to the COVID-19 outbreak. The book offers a collection of contemporary research and development on the management of Covid-19 using health data analytics, information exchange, knowledge sharing, the Internet of Things (IoT), and the Internet of Everything (IoE)-based solutions. The book also analyses the implementation, assessment, adoption, and management of these healthcare informatics solutions to manage the pandemic and future epidemics. The book is relevant to researchers, professors, students, and professionals in informatics and related topics.
Digital Twin Driven Smart Service draws on the latest industry practice and research to explain how to implement digital twin service in a range of scenarios. It addresses relevant theory and methodologies, including product service, prognostic health management service, energy efficient service and testing service. Other sections discuss key enabling technologies supported by cutting-edge case studies of implementation. Drawing on the work of researchers at the forefront of this technology, this book is the ideal guide for anyone interested in product services, manufacturing services and digital twin services. This book is one part of a trilogy on digital twins, the other titles being Digital Twin Driven Smart Design and Digital Twin Driven Smart Manufacturing. - Provides a wide range of applications, including tribological testing, cutting tool service and energy efficiency assessment - Explains everything needed to understand and implement digital twin models for service, including frameworks, theories and technologies - Explores future challenges for research in this area, including the ongoing standardization of digital twin technology
Steel Informatics aims to review the application of data-driven computing techniques related to the design of steel, including phase transformation, composition-process-property correlation, and different processing techniques, particularly deformation and joining. This book initiates with fundamentals of informatics followed by a description of applications of statistical analyses in defining the different attributes of steel. The proceeding chapters of this book cover recent applications of statistical, machine learning, expert systems, and optimization algorithms in the domains of iron and steel making, casting, deformation, phase transformation and heat treatment, microstructure analysis, and design of steel. Features: • Exclusive title focussing on informatics in steel design. • Covers related statistics as well as artificial intelligence and machine learning aspects. • Explains metallurgical aspects lucidly for the data scientists, steel researchers, and industries. • Discusses all aspects of steel technology. • Describes pertinent tools used for related computations. This book is useful for researchers, professionals, and graduate students in metallurgy, materials science, steel and welding, and computational materials science.
· Highlights how Artificial Intelligence and Machine Learning techniques are used in the Thermal Spray industry to predict future research directions · Sheds light on Artificial Intelligence’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques · Combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumed, and lower costs · Discusses how certain barriers are preventing the successfully implementing of Artificial Intelligence in the Thermal Spray industry Looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future · Offers a thorough analysis of the digital technologies available for modeling and achieving high-performance coatings including giving Artificial intelligence-related models like ANN and CNN more attention
The two-volume set LNCS 7066 and LNCS 7067 constitutes the proceedings of the Second International Visual Informatics Conference, IVIC 2011, held in Selangor, Malaysia, during November 9-11, 2011. The 71 revised papers presented were carefully reviewed and selected for inclusion in these proceedings. They are organized in topical sections named computer vision and simulation; virtual image processing and engineering; visual computing; and visualisation and social computing. In addition the first volume contains two keynote speeches in full paper length, and one keynote abstract.