Author: Dr. G.Hannah Grace
Publisher: SK Research Group of Companies
ISBN: 8119980514
Category : Computers
Languages : en
Pages : 182
Book Description
Dr. G.Hannah Grace, Assistant Professor Senior Grade, Division of Mathematics, School of Advanced Sciences, VIT Chennai Campus, Tamil Nadu, India. Dr.Nivetha Martin, Assistant Professor, Department of Mathematics, Arul Anandar College (Autonomous), Karumathur, Madurai, Tamil Nadu, India. Dr.N.Ramila Gandhi, Associate Professor, Department of Mathematics, PSNA College of Engineering and Technology (Autonomous), Dindigul, Tamil Nadu, India. Dr.P.Pandiammal, Assistant Professor, Department of Mathematics, G.T.N Arts College (Autonomous), Dindigul, Tamil Nadu, India.
Machine Learning in Livestock Disease Management
Author: Dr. G.Hannah Grace
Publisher: SK Research Group of Companies
ISBN: 8119980514
Category : Computers
Languages : en
Pages : 182
Book Description
Dr. G.Hannah Grace, Assistant Professor Senior Grade, Division of Mathematics, School of Advanced Sciences, VIT Chennai Campus, Tamil Nadu, India. Dr.Nivetha Martin, Assistant Professor, Department of Mathematics, Arul Anandar College (Autonomous), Karumathur, Madurai, Tamil Nadu, India. Dr.N.Ramila Gandhi, Associate Professor, Department of Mathematics, PSNA College of Engineering and Technology (Autonomous), Dindigul, Tamil Nadu, India. Dr.P.Pandiammal, Assistant Professor, Department of Mathematics, G.T.N Arts College (Autonomous), Dindigul, Tamil Nadu, India.
Publisher: SK Research Group of Companies
ISBN: 8119980514
Category : Computers
Languages : en
Pages : 182
Book Description
Dr. G.Hannah Grace, Assistant Professor Senior Grade, Division of Mathematics, School of Advanced Sciences, VIT Chennai Campus, Tamil Nadu, India. Dr.Nivetha Martin, Assistant Professor, Department of Mathematics, Arul Anandar College (Autonomous), Karumathur, Madurai, Tamil Nadu, India. Dr.N.Ramila Gandhi, Associate Professor, Department of Mathematics, PSNA College of Engineering and Technology (Autonomous), Dindigul, Tamil Nadu, India. Dr.P.Pandiammal, Assistant Professor, Department of Mathematics, G.T.N Arts College (Autonomous), Dindigul, Tamil Nadu, India.
Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Application of Machine Learning in Agriculture
Author: Mohammad Ayoub Khan
Publisher: Academic Press
ISBN: 0323906680
Category : Business & Economics
Languages : en
Pages : 332
Book Description
Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics. - Addresses the technology of smart agriculture from a technical perspective - Reveals opportunities for technology to improve and enhance not only yield and quality, but the economic value of a food crop - Discusses physical instruments, simulations, sensors, and markets for machine learning in agriculture
Publisher: Academic Press
ISBN: 0323906680
Category : Business & Economics
Languages : en
Pages : 332
Book Description
Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics. - Addresses the technology of smart agriculture from a technical perspective - Reveals opportunities for technology to improve and enhance not only yield and quality, but the economic value of a food crop - Discusses physical instruments, simulations, sensors, and markets for machine learning in agriculture
Coping with Risk in Agriculture, 3rd Edition
Author: J Brian Hardaker
Publisher: CABI
ISBN: 1780645740
Category : Business & Economics
Languages : en
Pages : 290
Book Description
Risk and uncertainty are inescapable factors in agriculture which require careful management. Farmers face production risks from the weather, crop and livestock performance, and pests and diseases, as well as institutional, personal and business risks. This revised third edition of the popular textbook includes updated chapters on theory and methods and contains a new chapter discussing the state-contingent approach to the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making, probability and risk preference, this book is an indispensable guide for students and researchers of agriculture and agribusiness management.
Publisher: CABI
ISBN: 1780645740
Category : Business & Economics
Languages : en
Pages : 290
Book Description
Risk and uncertainty are inescapable factors in agriculture which require careful management. Farmers face production risks from the weather, crop and livestock performance, and pests and diseases, as well as institutional, personal and business risks. This revised third edition of the popular textbook includes updated chapters on theory and methods and contains a new chapter discussing the state-contingent approach to the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making, probability and risk preference, this book is an indispensable guide for students and researchers of agriculture and agribusiness management.
Deep Learning Applications and Intelligent Decision Making in Engineering
Author: Senthilnathan, Karthikrajan
Publisher: IGI Global
ISBN: 1799821102
Category : Technology & Engineering
Languages : en
Pages : 332
Book Description
Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
Publisher: IGI Global
ISBN: 1799821102
Category : Technology & Engineering
Languages : en
Pages : 332
Book Description
Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
Current Trends in Knowledge Acquisition
Author: Bob Wielinga
Publisher: IOS Press
ISBN: 9789051990362
Category : Computers
Languages : en
Pages : 390
Book Description
Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.
Publisher: IOS Press
ISBN: 9789051990362
Category : Computers
Languages : en
Pages : 390
Book Description
Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.
Advancement in Sensing Technology
Author: Subhas Chandra Mukhopadhyay
Publisher: Springer Science & Business Media
ISBN: 3642321801
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
The book presents the recent advancements in the area of sensors and sensing technology, specifically in environmental monitoring, structural health monitoring, dielectric, magnetic, electrochemical, ultrasonic, microfluidic, flow, surface acoustic wave, gas, cloud computing and bio-medical. This book will be useful to a variety of readers, namely, Master and PhD degree students, researchers, practitioners, working on sensors and sensing technology. The book will provide an opportunity of a dedicated and a deep approach in order to improve their knowledge in this specific field.
Publisher: Springer Science & Business Media
ISBN: 3642321801
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
The book presents the recent advancements in the area of sensors and sensing technology, specifically in environmental monitoring, structural health monitoring, dielectric, magnetic, electrochemical, ultrasonic, microfluidic, flow, surface acoustic wave, gas, cloud computing and bio-medical. This book will be useful to a variety of readers, namely, Master and PhD degree students, researchers, practitioners, working on sensors and sensing technology. The book will provide an opportunity of a dedicated and a deep approach in order to improve their knowledge in this specific field.
Enabling Healthcare 4.0 for Pandemics
Author: Abhinav Juneja
Publisher: John Wiley & Sons
ISBN: 111976906X
Category : Computers
Languages : en
Pages : 352
Book Description
ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics. In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics. In this book, the reader will find: State-of-the-art technological advancements in pandemic management; AI and ML-based identification and forecasting of pandemic spread; Smart IoT-based ecosystem for pandemic scenario. Audience The book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management.
Publisher: John Wiley & Sons
ISBN: 111976906X
Category : Computers
Languages : en
Pages : 352
Book Description
ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics. In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics. In this book, the reader will find: State-of-the-art technological advancements in pandemic management; AI and ML-based identification and forecasting of pandemic spread; Smart IoT-based ecosystem for pandemic scenario. Audience The book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management.
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
Author: Abhishek Kumar
Publisher: CRC Press
ISBN: 1000539970
Category : Computers
Languages : en
Pages : 241
Book Description
In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.
Publisher: CRC Press
ISBN: 1000539970
Category : Computers
Languages : en
Pages : 241
Book Description
In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.
Machine Learning
Author: Paul Wilmott
Publisher:
ISBN: 9781916081604
Category :
Languages : en
Pages : 242
Book Description
Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics - K Nearest Neighbours; K Means Clustering; Naïve Bayes Classifier; Regression Methods; Support Vector Machines; Self-Organizing Maps; Decision Trees; Neural Networks; Reinforcement Learning
Publisher:
ISBN: 9781916081604
Category :
Languages : en
Pages : 242
Book Description
Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics - K Nearest Neighbours; K Means Clustering; Naïve Bayes Classifier; Regression Methods; Support Vector Machines; Self-Organizing Maps; Decision Trees; Neural Networks; Reinforcement Learning