Machine Learning And Knowledge Discovery For Engineering Systems Health Management

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Ashok N. Srivastava,Jiawei Han
Machine Learning and Knowledge Discovery for Engineering Systems Health Management Book PDF

Author : Ashok N. Srivastava,Jiawei Han
Publisher : CRC Press
Page : 489 pages
File Size : 52,9 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781439841792

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management by Ashok N. Srivastava,Jiawei Han Pdf

This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Ashok Srivastava
Machine Learning and Knowledge Discovery for Engineering Systems Health Management Book PDF

Author : Ashok Srivastava
Publisher : Unknown
Page : 502 pages
File Size : 48,5 Mb
Release : 2016
Category : Electronic
ISBN : OCLC:1142100401

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management by Ashok Srivastava Pdf

This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Advances in Machine Learning and Data Mining for Astronomy

Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
Advances in Machine Learning and Data Mining for Astronomy Book PDF

Author : Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
Publisher : CRC Press
Page : 746 pages
File Size : 50,5 Mb
Release : 2012-03-29
Category : Computers
ISBN : 9781439841730

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Advances in Machine Learning and Data Mining for Astronomy by Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava Pdf

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

Corrosion Processes

George Vachtsevanos,K. A. Natarajan,Ravi Rajamani,Peter Sandborn
Corrosion Processes Book PDF

Author : George Vachtsevanos,K. A. Natarajan,Ravi Rajamani,Peter Sandborn
Publisher : Springer Nature
Page : 339 pages
File Size : 44,7 Mb
Release : 2020-01-01
Category : Technology & Engineering
ISBN : 9783030328313

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Corrosion Processes by George Vachtsevanos,K. A. Natarajan,Ravi Rajamani,Peter Sandborn Pdf

This book discusses relevant topics in field of corrosion, from sensing strategies to modeling of control processes, corrosion prevention, detection of corrosion initiation, prediction of corrosion growth and evolution, to maintenance practices and return on investment.Written by leading international experts, it combines mathematical and scientific rigor with multiple case studies, examples, colorful images, case studies and numerous references exploring the essentials of corrosion in depth. It appeals to a wide readership, including corrosion engineers, managers, students and industrial and government staff, and can serve as a reference text for courses in materials, mechanical and aerospace engineering, as well as anyone working on corrosion processes.

Spectral Feature Selection for Data Mining (Open Access)

Zheng Alan Zhao,Huan Liu
Spectral Feature Selection for Data Mining Open Access Book PDF

Author : Zheng Alan Zhao,Huan Liu
Publisher : CRC Press
Page : 224 pages
File Size : 42,9 Mb
Release : 2011-12-14
Category : Business & Economics
ISBN : 9781439862100

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Spectral Feature Selection for Data Mining (Open Access) by Zheng Alan Zhao,Huan Liu Pdf

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics Book PDF

Author : Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Publisher : Academic Press
Page : 374 pages
File Size : 50,5 Mb
Release : 2021-06-10
Category : Science
ISBN : 9780128220443

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics by Pradeep N,Sandeep Kautish,Sheng-Lung Peng Pdf

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Data-Driven Technology for Engineering Systems Health Management

Gang Niu
Data Driven Technology for Engineering Systems Health Management Book PDF

Author : Gang Niu
Publisher : Springer
Page : 357 pages
File Size : 54,9 Mb
Release : 2016-07-27
Category : Technology & Engineering
ISBN : 9789811020322

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Data-Driven Technology for Engineering Systems Health Management by Gang Niu Pdf

This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.

Machine Learning and Analytics in Healthcare Systems

Himani Bansal,Balamurugan Balusamy,T. Poongodi,Firoz Khan KP
Machine Learning and Analytics in Healthcare Systems Book PDF

Author : Himani Bansal,Balamurugan Balusamy,T. Poongodi,Firoz Khan KP
Publisher : CRC Press
Page : 275 pages
File Size : 42,5 Mb
Release : 2021-06-30
Category : Technology & Engineering
ISBN : 9781000406191

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Machine Learning and Analytics in Healthcare Systems by Himani Bansal,Balamurugan Balusamy,T. Poongodi,Firoz Khan KP Pdf

Bridges the gap between engineering and medicine in combining the design and problem solving skills of engineering with health sciences Explores real-world case studies in machine learning and healthcare analytics Presents a detailed exploration of applications of machine learning in healthcare systems Provides readers with how the industry avoids some of the consequences of old methods of data sharing strategies Offers readers multiple perspectives on a variety of disciplines

Smart Healthcare Systems

Adwitiya Sinha,Megha Rathi
Smart Healthcare Systems Book PDF

Author : Adwitiya Sinha,Megha Rathi
Publisher : CRC Press
Page : 332 pages
File Size : 55,7 Mb
Release : 2019-07-24
Category : Computers
ISBN : 9780429670282

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Smart Healthcare Systems by Adwitiya Sinha,Megha Rathi Pdf

About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.

Machine Learning for Health Informatics

Andreas Holzinger
Machine Learning for Health Informatics Book PDF

Author : Andreas Holzinger
Publisher : Springer
Page : 481 pages
File Size : 41,6 Mb
Release : 2016-12-09
Category : Computers
ISBN : 9783319504780

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Machine Learning for Health Informatics by Andreas Holzinger Pdf

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

Machine Learning, Deep Learning, Big Data, and Internet of Things for Healthcare

Govind Singh Patel,Seema Nayak,Sunil Kumar Chaudhary
Machine Learning Deep Learning Big Data and Internet of Things for Healthcare Book PDF

Author : Govind Singh Patel,Seema Nayak,Sunil Kumar Chaudhary
Publisher : CRC Press
Page : 188 pages
File Size : 40,6 Mb
Release : 2022-08-25
Category : Computers
ISBN : 9781000635935

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Machine Learning, Deep Learning, Big Data, and Internet of Things for Healthcare by Govind Singh Patel,Seema Nayak,Sunil Kumar Chaudhary Pdf

This book reviews that narrate the development of current technologies under the theme of the emerging concept of healthcare, specifically in terms of what makes healthcare more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is machine learning, deep learning, big data, and Internet of Things (IoT)—the scientific field that gives machines the ability to learn without being strictly programmed. It has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data-intensive processes in healthcare operational environments. This book offers comprehensive coverage of the most essential topics, including: • Introduction to e-monitoring for healthcare • Case studies based on big data and healthcare • Intelligent learning analytics in healthcare sectors using machine learning and IoT • Identifying diseases and diagnosis using machine learning and IoT • Deep learning architecture and framework for healthcare using IoT • Knowledge discovery from big data of healthcare-related processing • Big data and IoT in healthcare • Role of IoT in sustainable healthcare • A heterogeneous IoT-based application for remote monitoring of physiological and environmental parameters

Healthcare and Knowledge Management for Society 5.0

Vineet Kansal,Raju Ranjan,Sapna Sinha,Rajdev Tiwari,Nilmini Wickramasinghe
Healthcare and Knowledge Management for Society 5 0 Book PDF

Author : Vineet Kansal,Raju Ranjan,Sapna Sinha,Rajdev Tiwari,Nilmini Wickramasinghe
Publisher : CRC Press
Page : 255 pages
File Size : 54,7 Mb
Release : 2021-12-27
Category : Technology & Engineering
ISBN : 9781000529692

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Healthcare and Knowledge Management for Society 5.0 by Vineet Kansal,Raju Ranjan,Sapna Sinha,Rajdev Tiwari,Nilmini Wickramasinghe Pdf

Healthcare and knowledge management is the need of the era; this book investigates various challenges faced by practitioners in this area. It also covers the work to be done in the healthcare sector and the use of different computing techniques for better insight and decision-making. Healthcare and Knowledge Management for Society 5.0: Trends, Issues, and Innovations showcases the benefits of computing techniques used for knowledge management in the field of healthcare in the futuristic perspective of having a human-centric society 5.0. The book includes topics related to the use of technologies like artificial intelligence, machine learning, deep learning, Internet of Things, blockchain, and sensors for effective healthcare and management. Case studies are included for easy comprehension and the book covers the most up-to-date research in the field. The use of techniques like artificial intelligence in the field of knowledge management is also discussed. This book is intended for researchers and academicians to explore new ideas, techniques, and tools. Researchers working in interdisciplinary research can also find many interesting topics which will pave the way for a new arena in healthcare and knowledge management.

Machine Learning for Healthcare Applications

Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
Machine Learning for Healthcare Applications Book PDF

Author : Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
Publisher : John Wiley & Sons
Page : 416 pages
File Size : 43,8 Mb
Release : 2021-05-04
Category : Computers
ISBN : 9781119792598

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Machine Learning for Healthcare Applications by Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar Pdf

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Prognostics and Health Management

Douglas Goodman,James P. Hofmeister,Ferenc Szidarovszky
Prognostics and Health Management Book PDF

Author : Douglas Goodman,James P. Hofmeister,Ferenc Szidarovszky
Publisher : John Wiley & Sons
Page : 512 pages
File Size : 48,5 Mb
Release : 2019-04-01
Category : Technology & Engineering
ISBN : 9781119356707

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Prognostics and Health Management by Douglas Goodman,James P. Hofmeister,Ferenc Szidarovszky Pdf

A comprehensive guide to the application and processing of condition-based data to produce prognostic estimates of functional health and life. Prognostics and Health Management provides an authoritative guide for an understanding of the rationale and methodologies of a practical approach for improving system reliability using conditioned-based data (CBD) to the monitoring and management of health of systems. This proven approach uses electronic signatures extracted from conditioned-based electrical signals, including those representing physical components, and employs processing methods that include data fusion and transformation, domain transformation, and normalization, canonicalization and signal-level translation to support the determination of predictive diagnostics and prognostics. Written by noted experts in the field, Prognostics and Health Management clearly describes how to extract signatures from conditioned-based data using conditioning methods such as data fusion and transformation, domain transformation, data type transformation and indirect and differential comparison. This important resource: Integrates data collecting, mathematical modelling and reliability prediction in one volume Contains numerical examples and problems with solutions that help with an understanding of the algorithmic elements and processes Presents information from a panel of experts on the topic Follows prognostics based on statistical modelling, reliability modelling and usage modelling methods Written for system engineers working in critical process industries and automotive and aerospace designers, Prognostics and Health Management offers a guide to the application of condition-based data to produce signatures for input to predictive algorithms to produce prognostic estimates of functional health and life.

AI and Machine Learning Paradigms for Health Monitoring System

Hasmat Malik,Nuzhat Fatema,Jafar A. Alzubi
AI and Machine Learning Paradigms for Health Monitoring System Book PDF

Author : Hasmat Malik,Nuzhat Fatema,Jafar A. Alzubi
Publisher : Springer Nature
Page : 513 pages
File Size : 45,6 Mb
Release : 2021-02-14
Category : Technology & Engineering
ISBN : 9789813344129

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AI and Machine Learning Paradigms for Health Monitoring System by Hasmat Malik,Nuzhat Fatema,Jafar A. Alzubi Pdf

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.