This book, presented in three volumes, examines environmental disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.

This book, presented in three volumes, examines environmental disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.

This book, presented in three volumes, examines environmental disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.

Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.

Calculation is the main function of a computer. The central unit is responsible for executing the programs. The microprocessor is its integrated form. This component, since the announcement of its marketing in 1971, has not stopped breaking records in terms of computing power, price reduction and integration of functions (calculation of basic functions, storage with integrated controllers). It is present today in most electronic devices. Knowing its internal mechanisms and programming is essential for the electronics engineer and computer scientist to understand and master the operation of a computer and advanced concepts of programming. This first volume focuses more particularly on the first generations of microprocessors, that is to say those that handle integers in 4 and 8-bit formats. The first chapter presents the calculation function and reminds the memory function. The following is devoted to notions of calculation model and architecture. The concept of bus is then presented. Chapters 4 and 5 can then address the internal organization and operation of the microprocessor first in hardware and then software. The mechanism of the function call, conventional and interrupted, is more particularly detailed in a separate chapter. The book ends with a presentation of architectures of the first microcomputers for a historical perspective. The knowledge is presented in the most exhaustive way possible with examples drawn from current and old technologies that illustrate and make accessible the theoretical concepts. Each chapter ends if necessary with corrected exercises and a bibliography. The list of acronyms used and an index are at the end of the book.

Systems and Uses of Digital Sciences for Knowledge Organization is a large-scale scientific work that brings together researchers and R&D professionals to discuss ideas and actions in the organization of knowledge. The main objective of this book is to define collaborative strategies, use advanced technologies in multiple research fields and outline applications of knowledge organization and its cultural, education, economic and industrial potential. The organization of knowledge and advanced technologies (OCTA) asks the following questions: How can we strengthen alliances between multi-disciplinary and trans-disciplinary studies? How can we broaden our skills surrounding common objects of study? How can we innovate the solutions found and propose sustainable development to society confidently? This book is a result of intensive and collaborative work between highly respected scientific authors. The nine chapters that have been selected for this book have been peer-reviewed by the OCTA program committee, both as written submissions and when presented during the OCTA multi-conference on organization.

Blockchain is new-age technology used to track every transaction using cryptocurrency across servers linked in a peer-to-peer network, enabling transactions to be secure, transparent and reliable. Retaining an efficient, secure and patient-centric healthcare industry has never been so important, especially due to the damaging effects of the Covid-19 pandemic. The applicability of Blockchain in the healthcare domain can be seen as a remarkable opportunity for researchers and scientists to solve real-world problems. This book focuses on the fundamentals of Blockchain technology along with the methods of its integration with the healthcare industry. It also provides an enhanced understanding of Blockchain technology, AI and IoT across the various application areas of the healthcare industry. Furthermore, throughout the book, areas of relevant applications, such as patient data privacy protection, pharmaceutical supply chains and genomics are discussed.