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Handbook of Research on Administration, Policy, and Leadership in Higher Education
The creation of a sustainable and accessible higher education systems is a pivotal goal in modern society. Adopting strategic frameworks and innovative techniques allows institutions to achieve this objective. The Handbook of Research on Administration, Policy, and Leadership in Higher Education is an authoritative reference source for the latest scholarly research on contemporary management issues in educational institutions and presents best practices to improve policies and retain effective governance. Addressing the current state of higher education at an international level, this book is ideally designed for academicians, educational administrators, researchers, and professionals.
Advances in Chemical Physics
Volume 109 in the prestigious Advances in Chemical Physics Series, edited by Nobel Prize winner Ilya Prigogine, and renowned authority Stuart A. Rice, continues to report recent advances in every area of the discipline. Significant, up-to-date chapters by internationally recognized researchers present comprehensive analyses of subjects of interest and encourage the expression of individual points of view. This approach to presenting an overview of a subject will both stimulate new research and serve as a personalized learning text for beginners in the field.
Computational Techniques in Neuroscience
The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms suc...
Smart Technologies for Energy and Environmental Sustainability
As the application of smart technologies for monitoring environmental activities becomes more widespread, there is a growing demand for solutions that can help analyze the risk factors and impacts on the environment by focusing on energy consumption, storage, and management. This book is designed to serve as a knowledge-sharing platform, focusing on the emerging models, architectures, and algorithms being developed for smart computational technologies that can lead to efficient energy conservation and environmental sustainability.
Global Trends in Intelligent Computing Research and Development
As the amount of accumulated data across a variety of fields becomes harder to maintain, it is essential for a new generation of computational theories and tools to assist humans in extracting knowledge from this rapidly growing digital data. Global Trends in Intelligent Computing Research and Development brings together recent advances and in depth knowledge in the fields of knowledge representation and computational intelligence. Highlighting the theoretical advances and their applications to real life problems, this book is an essential tool for researchers, lecturers, professors, students, and developers who have seek insight into knowledge representation and real life applications.
Optimization of EOQ Model with Limited Storage Capacity by Neutrosophic Geometric Programming
In this article, we present deterministic single objective economic order quantity model with limited storage capacity in neutrosophic environment. We consider variable limit production cost and time dependent holding cost into account. Here we minimize total average cost of proposed model by applying neutrosophic geometric programming, which is obtained by extending existing fuzzy and intuitionistic fuzzy geometric programming for solving resultant non-linear optimization model. Next we consider numerical application to show that optimal solution obtained by neutrosophic geometric programming is more desirable than that of crisp, fuzzy and intuitionistic fuzzy geometric programming. Also we perform sensitivity analysis of parameters and present key managerial insights. Finally we draw the conclusions.
Effective Big Data Management and Opportunities for Implementation
“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.
Computational Intelligence for Big Data Analysis
The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.
Imprecision and Uncertainty in Information Representation and Processing
The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets. The different chapters, written by active researchers in their respective areas, are structured to provide a coherent picture of this interdisciplinary yet still evolving field of science. They describe key tools and give practical insights into and research perspectives on the use of Atanassov's intuitionistic fuzzy sets and logic, and generalized nets for describing and dealing with uncertainty in different areas of science, technology and business, in a single, to date...
