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Diseases of Forest Trees and their Management

Diseases of Forest Trees and their Management

The book is intended to provide comprehensive introduction to the important aspects of the field of forest pathology and tree diseases. The book is arranged in two major parts. The fundamental chapters present forest diseases pathogens epidemics and management that is applicable to all forest trees. The applied chapters on the individual crops that are grouped alphabetically present information on the symptoms pathogen and integrated management of major diseases of forest trees. It was designed to give a broad overview of the field of forest pathology but with sufficient detail that they will be able to assess their specific role as practicing forestry professionals. Note: T& F does not sell or distribute the Hardback in India Pakistan Nepal Bhutan Bangladesh and Sri Lanka. | Diseases of Forest Trees and their Management

GBP 99.99
1

The bioeconomy and non-timber forest products

The bioeconomy and non-timber forest products

This book provides the first in-depth investigation of how non-timber forest products are an integral part of local national and global bioeconomies. While the plants and fungi that produce non-timber forest products are essential to the sustainability of forest ecosystems peoples' food and livelihood security and sovereignty and thus the bioeconomy are often absent from bioeconomic strategies. Presenting a selection of empirical cases from around the world that engage with the bioeconomy and non-timber forest products this volume reveals how essential these products are to creating a greener and more sustainable future how to to better integrate them into efforts to transition to and expand the bioeconomy and how such efforts can be supported and developed. Chapters analyse how and to what degree non-timber forest products promote sustainable resource use generate employment and contribute to food and livelihood security and poverty alleviation. The volume develops approaches and identifies interventions and policies to support the integration of non-timber forest products into bioeconomy strategies including in national reporting schemes to provide recommendations for future research and practical implementation. This book will be of great interest to students and scholars of forest and natural resource management bioeconomics circular economy and ecological economics more widely. It will also be of interest to professionals working in sustainable development and the forestry sector.

GBP 120.00
1

Deep Learning in Visual Computing and Signal Processing

Deep Learning in Visual Computing and Signal Processing

An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing. The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing such as in biorobotics for automated brain tumor segmentation in MRI images in neural networks for use in seizure classification for digital forensic investigation based on deep learning and more. | Deep Learning in Visual Computing and Signal Processing

GBP 131.00
1

Deep Learning for Biomedical Applications

Deep Learning for Biomedical Applications

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i. e. raw data signal-time series medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis image processing perspectives and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists researchers practitioners professionals and educations who are working in the context of the topics. | Deep Learning for Biomedical Applications

GBP 130.00
1

Deep Neural Network Applications

Deep Neural Network Applications

The world is on the verge of fully ushering in the fourth industrial revolution of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars trucks and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet which led to the emergence of the information age AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives and from it innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception speech recognition decision-making and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches problem solving knowledge representation planning learning natural language processing perception motion and manipulation social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications. | Deep Neural Network Applications

GBP 145.00
1

Object Detection with Deep Learning Models Principles and Applications

Object Detection with Deep Learning Models Principles and Applications

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision illustrating them using key topics including object detection face analysis 3D object recognition and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students researchers and practitioners interested in deep learning computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection | Object Detection with Deep Learning Models Principles and Applications

GBP 110.00
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Deep Learning in Time Series Analysis

Deep Learning in Time Series Analysis

Deep learning is an important element of artificial intelligence especially in applications such as image classification in which various architectures of neural network e. g. convolutional neural networks have yielded reliable results. This book introduces deep learning for time series analysis particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. An important factor in classifying stochastic time series is the structural risk associated with the architecture of classification methods. The book addresses and formulates structural risk and the learning capacity defined for a classification method. These formulations and the mathematical derivations will help the researchers in understanding the methods and even express their methodologies in an objective mathematical way. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of machine learning including students engineers researchers and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the deep learning methods for time series analysis. | Deep Learning in Time Series Analysis

GBP 115.00
1

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas including chest X-ray breast computer-aided detection lung and chest microscopy and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering artificial intelligence and machine learning and biomedical imaging.

GBP 110.00
1

Deep Learning A Comprehensive Guide

Deep Learning A Comprehensive Guide

Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks and continuing through the architecture of various types of CNNs RNNs LSTM and more till the end of the book each and every topic is given the utmost care and shaped professionally and comprehensively. Key Features Includes the smooth transition from ML concepts to DL concepts Line-by-line explanations have been provided for all the coding-based examples Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away Even a person with a non-computer-science background can benefit from this book by following the theory examples case studies and code snippets Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding Includes references to the related YouTube videos that provide additional guidance AI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful. | Deep Learning A Comprehensive Guide

GBP 130.00
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Deep Learning and IoT in Healthcare Systems Paradigms and Applications

Deep Learning and IoT in Healthcare Systems Paradigms and Applications

This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It describes deep learning techniques in conjunction with IoT used by practitioners and researchers worldwide. The authors explore the convergence of IoT and deep learning to enable things to communicate share information and coordinate decisions. The book includes deep feedforward networks regularization optimization algorithms convolutional networks sequence modeling and practical methodology. Chapters look at assistive devices in healthcare alerting and detection devices energy efficiency in using IoT data mining for gathering health information for individuals with autism IoT for mobile applications and more. The text also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies. | Deep Learning and IoT in Healthcare Systems Paradigms and Applications

GBP 147.00
1

C++ Template Metaprogramming in Practice A Deep Learning Framework

C++ Template Metaprogramming in Practice A Deep Learning Framework

Using the implementation of a deep learning framework as an example C++ Template Metaprogramming in Practice: A Deep Learning Framework explains the application of metaprogramming in a relatively large project and emphasizes ways to optimize systems performance. The book is suitable for developers with a basic knowledge of C++. Developers familiar with mainstream deep learning frameworks can also refer to this book to compare the differences between the deep learning framework implemented with metaprogramming and compile-time computing with deep learning frameworks using object-oriented methods. Consisting of eight chapters the book starts with two chapters discussing basic techniques of metaprogramming and compile-time computing. The rest of the book’s chapters focus on the practical application of metaprogramming in a deep learning framework. It examines rich types and systems expression templates and writing complex meta-functions as well as such topics as: Heterogeneous dictionaries and policy templates An introduction to deep learning Type system and basic data types Operations and expression templates Basic layers Composite and recurrent layers Evaluation and its optimization Metaprogramming can construct flexible and efficient code. For C++ developers who are familiar with object-oriented programming the main difficulty in learning and mastering C++ metaprogramming is establishing the thinking mode of functional programming. The meta-programming approach involved at compile time is functional which means that the intermediate results of the construction cannot be changed and the impact may be greater than expected. This book enables C++ programmers to develop a functional mindset and metaprogramming skills. The book also discusses the development cost and use cost of metaprogramming and provides workarounds for minimizing these costs. | C++ Template Metaprogramming in Practice A Deep Learning Framework

GBP 99.99
1

Swarm Intelligence and Deep Evolution Evolutionary Approach to Artificial Intelligence

Swarm Intelligence and Deep Evolution Evolutionary Approach to Artificial Intelligence

The book provides theoretical and practical knowledge about swarm intelligence and evolutionary computation. It describes the emerging trends in deep learning that involve the integration of swarm intelligence and evolutionary computation with deep learning i. e. deep neuroevolution and deep swarms. The study reviews the research on network structures and hyperparameters in deep learning and attracting attention as a new trend in AI. A part of the coverage of the book is based on the results of practical examples as well as various real-world applications. The future of AI based on the ideas of swarm intelligence and evolution is also covered. The book is an introductory work for researchers. Approaches to the realization of AI and the emergence of intelligence are explained with emphasis on evolution and learning. It is designed for beginners who do not have any knowledge of algorithms or biology and explains the basics of neural networks and deep learning in an easy-to-understand manner. As a practical exercise in neuroevolution the book shows how to learn to drive a racing car and a helicopter using MindRender. MindRender is an AI educational software that allows the readers to create and play with VR programs and provides a variety of examples so that the readers will be able to create and understand AI. | Swarm Intelligence and Deep Evolution Evolutionary Approach to Artificial Intelligence

GBP 160.00
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Visual Object Tracking using Deep Learning

Visual Object Tracking using Deep Learning

This book covers the description of both conventional methods and advanced methods. In conventional methods visual tracking techniques such as stochastic deterministic generative and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates graduate students and academic researchers in the fields of electrical engineering electronics and communication engineering computer engineering and information technology. | Visual Object Tracking using Deep Learning

GBP 89.99
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Generative Adversarial Networks and Deep Learning Theory and Applications

Generative Adversarial Networks and Deep Learning Theory and Applications

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks which includes creating new tools and methods for processing text images and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology including computer vision security multimedia and advertisements image generation image translation text-to-images synthesis video synthesis generating high-resolution images drug discovery etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering undergraduate and postgraduate students researchers and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries accreditation agencies government agencies and especially the academic institution of higher education intending to launch or reform their engineering curriculum | Generative Adversarial Networks and Deep Learning Theory and Applications

GBP 140.00
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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence (AI) when incorporated with machine learning and deep learning algorithms has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images covers the automation of a system through machine learning and deep learning approaches presents data analytics and mining for decision-support applications and includes case-based reasoning natural language processing computer vision and AI approaches in real-time applications. Academic scientists researchers and students in the various domains of computer science engineering electronics and communication engineering and information technology as well as industrial engineers biomedical engineers and management will find this book useful. By the end of this book you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning | Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

GBP 145.00
1

Minority Churches as Media Settlers Negotiating Deep Mediatization

Minority Churches as Media Settlers Negotiating Deep Mediatization

How do minority Christian churches adapt to and negotiate with the changes brought about by deep mediatization? How do they use their media to present themselves to their followers and the general public? This book aims to answer these questions by investigating how minority organizations of two different Christian traditions in the UK and Poland – the Seventh-day Adventist Church and the Orthodox Churches – use their own media to position themselves in their social religious and political environments. Based on the analyses of media practices media content and interview material the study develops the new concept of media settlers which pertains to religious organizations that use their media to fulfill their own aims: expand assert their authority and maintain their communities. They do so through five key media practices which can be defined as strategies: acknowledgment authorization omission replication of content and mass-mediatization of digital media. This book is of particular interest to scholars of religion and mediatization mainly sociologists graduate students and qualitative researchers working with discourse analysis. It is an insightful read for anyone interested in the Seventh-day Adventist and Orthodox Churches nowadays. | Minority Churches as Media Settlers Negotiating Deep Mediatization

GBP 120.00
1

The Climate–Energy–Land Nexus in Indonesia Biofuel REDD+ and biochar

The Climate–Energy–Land Nexus in Indonesia Biofuel REDD+ and biochar

This book extends the framework of the climate-energy-land nexus to elucidate political economic social and institutional factors and causal mechanisms that stringent climate targets bring about rather than mitigate a disproportional heavy burden on the forest sector in Indonesia. Assessing climate energy agricultural forest and transmigration policies and REDD+ and biochar solutions through a multidisciplinary approach ranging from biological agricultural technological economic and institutional lenses the book identifies the political-economic and socio-technical regimes that cause the crosssectoral transfer of responsibility for greenhouse gas emissions to palm-oil-based biofuel imposing an excess burden on the forest sector and accelerating indirect land-use change. It also proposes possible countermeasures for agricultural and forest sectors reconfirming that technical applications and integrated policymaking should trigger the socioeconomic changes that will make transformative change happen in Indonesia. As an analysis of the success or otherwise of stringent climate targets policies and technological and non-technological measures on the reduction of greenhouse gases this book will be of great interest to students and scholars in the fields of environment & sustainability Asian studies energy environment and agriculture forestry and agriculture & environmental sciences. It will also appeal to practitioners and policymakers tackling net-zero emissions and land and forest governance. | The Climate–Energy–Land Nexus in Indonesia Biofuel REDD+ and biochar

GBP 130.00
1

Deep Learning Machine Learning and IoT in Biomedical and Health Informatics Techniques and Applications

Deep Learning Machine Learning and IoT in Biomedical and Health Informatics Techniques and Applications

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable there is lack of formal models or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision uncertainties and approximations to get a rapid solution. However recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable low-cost and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics time series biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval brain image segmentation among others. • Discusses deep learning IoT machine learning and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy robustness and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems | Deep Learning Machine Learning and IoT in Biomedical and Health Informatics Techniques and Applications

GBP 140.00
1

Roots of Sustainability in the Iberian Empires Shipbuilding and Forestry 14th - 19th Centuries

Roots of Sustainability in the Iberian Empires Shipbuilding and Forestry 14th - 19th Centuries

This book sheds light on the roots of sustainability in the Iberian Peninsula that lie in the interrelations between shipbuilding and forestry from the 14th to the 19th centuries combining various geographical scales (local regional and national) and different timespans (short-term and long-term studies). Three main themes are discussed in depth here: firstly the roots of current conservationism in the Iberian Peninsula; the evolution of the forest policies set in motion at local regional and national levels to meet the demand for wood and timber; and the long-standing impact of naval empirical forestry on the conservation and transformation of the forest landscape. Therefore the book attempts on the one hand to unravel the forest policies and empirical forestry implemented in the Iberian Peninsula as the roots or origins of what we refer to nowadays as sustainability and to assess the contribution of imperial forestry to landscape planning and the conservation of forest resources on the other and finally to break away from the prevailing theological narrative that shipbuilding was the main agent of forest destruction in the early modern Iberian Peninsula for which both quantitative and qualitative analyses will be conducted. This book will be of key interest to environmental and social historians and researchers and to anyone devoted to conducting research on the emergence and evolution of the concept of sustainability with respect to the governance and the historical transformation of woodlands around the world. | Roots of Sustainability in the Iberian Empires Shipbuilding and Forestry 14th - 19th Centuries

GBP 130.00
1

AI Machine Learning and Deep Learning A Security Perspective

AI Machine Learning and Deep Learning A Security Perspective

Today Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i. e. securing the intelligent systems themselves) AI/ML/DL models and algorithms can actually also be used for cyber security (i. e. the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field many researchers and industry professionals cannot yet obtain a detailed comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both securing the AI system itself and using AI to achieve security It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered | AI Machine Learning and Deep Learning A Security Perspective

GBP 99.99
1

Long-Term Monitoring and Research in Asian University Forests Understanding Environmental Changes and Ecosystem Responses

Long-Term Monitoring and Research in Asian University Forests Understanding Environmental Changes and Ecosystem Responses

This book disseminates various long-term data and research results from university forests in Asia towards realizing adaptive forest management and conservation based on a comprehensive understanding of environmental changes and ecological responses. University forests - which refer to large forested areas owned or controlled by universities and devoted primarily to research and teaching programs in forest-related sciences - have collected managed and analyzed long-term meteorological hydrological biological and geographic data under an organizationally stable observation system. With the influence of global warming becoming apparent and extreme weather events occurring more frequently in the region it is an important and urgent challenge to understand long-term environmental and ecosystem changes in forests and provide robust scientific knowledge on how ecosystems respond to those changes. This book is a step towards addressing the challenge. The chapters in this book were originally published as a special issue of the Journal of Forest Research. | Long-Term Monitoring and Research in Asian University Forests Understanding Environmental Changes and Ecosystem Responses

GBP 130.00
1

Basics of Wildlife Health Care and Management

Basics of Wildlife Health Care and Management

The book provides basic understanding of the various topics of wildlife which will be useful for biologist zoologist veterinarians working in forest zoos or at field level where they use to get wild animals for post mortem or for treatment. It also provides helpful information to the forest officers zoo managers and protected area managers for critical care management and for doing needful things before approaching a veterinarian to save the life of animal or to collect biological material useful for diagnosis. Note: T&F does not sell or distribute the Hardback in India Pakistan Nepal Bhutan Bangladesh and Sri Lanka. | Basics of Wildlife Health Care and Management

GBP 99.99
1

Cognitive Dependability Engineering Managing Risks in Cyber-Physical-Social Systems under Deep Uncertainty

Cognitive Dependability Engineering Managing Risks in Cyber-Physical-Social Systems under Deep Uncertainty

The work is a context-oriented analysis and synthesis of complex engineered systems to ensure continuous and safe operations under conditions of uncertainty. The book is divided in four parts the first one comprises an overview of the development of systems engineering: starting with basics of Systems Science and Single Systems Engineering through System of Systems Engineering to Cognitive Systems Engineering. The Cognitive Systems Engineering model was based on the concept of imperfect knowledge acquisition and management. The second part shows the evolutionary character of the dependability concept over the last fifty years. Beginning from simple models based on the classical probability theory through the concepts of tolerating faults as well as resilience engineering we come to the assumptions of Cognitive Dependability Engineering (CDE) based on the concept of continuous smart operation both under normal and abnormal conditions. The subject of the next part is analysis and synthesis of Cyber-Physical-Social (CPS) Systems. The methodology consists of the following steps: modeling CPS systems' structure simulating their behavior in changing conditions and in situations of disruptions and finally assessing the dependability of the entire system based on CDE. The last part of the work answers the question of how to deal with risks in CPS systems in situations of high level of uncertainty. The concept of a Cognitive Digital Twin was introduced to support the process of solving complex problems by experts and on this basis a framework for cognitive dependability based problemsolving in CPS Systems operating under deep uncertainty was developed. The possibilities and purposefulness of using this framework have been demonstrated with three practical examples of disasters that have happened in the past and have been thoroughly analyzed. | Cognitive Dependability Engineering Managing Risks in Cyber-Physical-Social Systems under Deep Uncertainty

GBP 145.00
1

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower enhance and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector this book demonstrates the depth breadth complexity and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics drug discovery and development medical imaging automation robotic surgery electronic smart records creation outbreak prediction medical image analysis and radiation treatments. This book aims to endow different communities with the innovative advances in theory analytical results case studies numerical simulation modeling and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers scientists healthcare professionals programmers and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science Ravenshaw University Cuttack Odisha India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology Sharda University Greater Noida India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University Turkey.

GBP 115.00
1

(De)constructing Societal Threats During Times of Deep Mediatization

(De)constructing Societal Threats During Times of Deep Mediatization

This book explores how both elite and non-elite actors frame societal threats such as the refugee crisis and COVID-19 using both digital and traditional media. It also explores ways in which the framing of these issues as threatening can be challenged using these platforms. People typically experience societal threats such as war and terrorism through the media they consume both on and offline. Much of the research in this area to date focuses on either how political and media elites present these issues to citizens or audience responses to these frames. This book takes a different approach by focusing on how issues such as the refugee crisis and the COVID-19 pandemic are both constructed and deconstructed in an era of hybrid media. It draws on a range of traditional and innovative research methodologies to explore how these issues are framed as ‘threats’ within deeply mediatized societies ranging from content analysis of newspaper coverage of the Macedonian name dispute in Greece to investigating conspiratorial communities on YouTube using Systemic Functional Linguistics. In doing so this book enriches our understanding of not only how civil and uncivil actors frame these issues but also their impact on societal resilience towards future crises. (De)constructing Societal Threats During Times of Deep Mediatization will be a key resource for academics researchers and advanced students of Communication Studies Media Studies Journalism Cultural Studies Research Methods Sociology and Politics. The chapters included in this book were originally published as a special issue of The Communication Review.

GBP 130.00
1