Tracing the history of the Mekong River, this book shows how its conceptualization and utilization have been transformed in modern times, and particularly during the Vietnam war when the Mekong River and Mekong Project became political pawns. Nguyen concludes by examining the continuation of some of the Project's schemes by the independent Southeast Asian countries and regional powers. The Mekong River links together the mainland countries of Southeast Asia in a vital geographic, but also economic and political, unit. Its historical trajectory coursed through kingdoms and colonies, and its physical presence and symbolism became more acute as it came closer to modern times. Tracing the history of the Mekong River, this book shows how its conceptualizations have been transformed in modern times, and particularly during the Vietnam War when the Mekong River and Mekong Project became political pawns. In the 1950s, the decision was made to develop the river's resources to foster economic development for the four countries of the lower Mekong basin. The Mekong Project, as it came to be known, proposed the construction of a set of major dams on the mainstream and of numerous smaller ones on the tributaries to bring hydropower, flood control, irrigation, and other benefits to the riparian countries. The Project, however, was subverted to the needs of the Vietnam War. With the return of peace, the Mekong countries can re-examine the future of the river and its potential impact on the region. Nguyen concludes by examining the continuation of some of the Project's schemes by the independent Southeast Asian countries and regional powers. Scholars and researchers interested in Southeast Asian history and economic development, environmental history, and rural sociology will find this an important study.

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

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making. The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction. Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

Distributed Artificial Intelligence (DAI) came to existence as an approach for solving complex learning, planning, and decision-making problems. When we talk about decision making, there may be some meta-heuristic methods where the problem solving may resemble like operation research. But exactly, it is not related completely to management research. The text examines representing and using organizational knowledge in DAI systems, dynamics of computational ecosystems, and communication-free interactions among rational agents. This publication takes a look at conflict-resolution strategies for nonhierarchical distributed agents, constraint-directed negotiation of resource allocations, and plans for multiple agents. Topics included plan verification, generation, and execution, negotiation operators, representation, network management problem, and conflict-resolution paradigms. The manuscript elaborates on negotiating task decomposition and allocation using partial global planning and mechanisms for assessing nonlocal impact of local decisions in distributed planning. The book will attract researchers and practitioners who are working in management and computer science, and industry persons in need of a beginner to advanced understanding of the basic and advanced concepts.

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.

Vietnam is increasingly opening up to the West, and society is in flux between tradition and modernity, and capitalism and socialism. Americans have distanced themselves from the Vietnam War now, and "Culture and Customs of Vietnam" fills a need to learn about the country, which has also evolved. Readers will find that this is the only general book on Vietnamese culture in English written by specialists. McLeod and Nguyen, historians specializing in Vietnam engagingly show the various forces of Vietnamese culture in narrative chapters on the land, people, and language; history and institutions; thought and religion; literature; art and architecture; cuisine; family, marriage, gender, and youth culture; festivals and leisure activities, and performing arts.

"Culture and Customs of Vietnam" is a comprehensive, one-stop source, providing the most useful and intriguing information for students and general readers. Some of the highlights include the discussion of the Chinese influence in writing, thought, and religion; eating habits; the changing family; and water puppetry. A chronology, glossary, and numerous photos complement the text.