Machine Learning in Livestock Disease Management PDF Download
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Author: Dr. G.Hannah Grace
Publisher: SK Research Group of Companies
ISBN: 8119980514
Category : Computers
Languages : en
Pages : 182
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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.
Author: Dr. G.Hannah Grace
Publisher: SK Research Group of Companies
ISBN: 8119980514
Category : Computers
Languages : en
Pages : 182
Get Book Here
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.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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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
Author: Mohammad Ayoub Khan
Publisher: Academic Press
ISBN: 0323906680
Category : Business & Economics
Languages : en
Pages : 332
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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
Author: J Brian Hardaker
Publisher: CABI
ISBN: 1780645740
Category : Business & Economics
Languages : en
Pages : 290
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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.
Author: Subhas Chandra Mukhopadhyay
Publisher: Springer Science & Business Media
ISBN: 3642321801
Category : Technology & Engineering
Languages : en
Pages : 329
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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.
Author: Bob Wielinga
Publisher: IOS Press
ISBN: 9789051990362
Category : Computers
Languages : en
Pages : 390
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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.
Author: Abhinav Juneja
Publisher: John Wiley & Sons
ISBN: 111976906X
Category : Computers
Languages : en
Pages : 352
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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.
Author: Abhishek Kumar
Publisher: CRC Press
ISBN: 1000539970
Category : Computers
Languages : en
Pages : 241
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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.
Author: Ramesh Chandra Poonia
Publisher: Academic Press
ISBN: 0323903622
Category : Computers
Languages : en
Pages : 408
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Book Description
The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. - Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture - Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture - Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge - Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain
Author: Bo Guang Zhao
Publisher: Springer Science & Business Media
ISBN: 4431756558
Category : Technology & Engineering
Languages : en
Pages : 486
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Book Description
Pine forests face a global threat of pine wilt disease, which is being spread by vector beetles carrying pathogenic nematodes from dead trees to healthy ones. Among the host pines there are varying degrees of susceptibility, and nematode strains also contain a variety of virulences, both of which factors help to determine whether infected host trees will die or survive. As well, biotic and abiotic environmental factors influence the fate of infected trees. This book describes the history of the disease, pathogenic nematodes, vector beetles, the etiology and ecology of the disease, microorganisms involved, and control methods that utilize host resistance and biological control agents. Concrete, comprehensive, and the most up-to-date knowledge about this worldwide forest epidemic is presented for readers, enabling them to understand the nature and epidemic threat of pine wilt disease.
