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Multiobjective Heuristic Search
Solutions to most real-world optimization problems involve a trade-off between multiple conflicting and non-commensurate objectives. Some of the most challenging ones are area-delay trade-off in VLSI synthesis and design space exploration, time-space trade-off in computation, and multi-strategy games. Conventional search techniques are not equipped to handle the partial order state spaces of multiobjective problems since they inherently assume a single scalar objective function. Multiobjective heuristic search techniques have been developed to specifically address multicriteria combinatorial optimization problems. This text describes the multiobjective search model and develops the theoretic...
Biologically Inspired Design
From simple cases such as hook and latch attachments found in Velcro to articulated-wing flying vehicles, biology often has been used to inspire many creative design ideas. The scientific challenge now is to transform the paradigm into a repeatable and scalable methodology. Biologically Inspired Design explores computational techniques and tools that can help integrate the method into design practice. With an inspiring foreword from Janine Benyus, Biologically Inspired Design contains a dozen chapters written by some of the leading scholars in the transdisciplinary field of bioinspired design, such as Frank Fish, Julian Vincent and Jeannette Yen from biology, and Amaresk Chakrabarti, Satyand...
Predicting Natural Disasters With AI and Machine Learning
In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges of disasters and charts a path toward proactive solutions by applying artificial intelligence (AI) and machine learning (ML). This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four ‘R...
Intelligent Techniques in Engineering Management
This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.
Astronomy in India, 1784-1876
Indian scientific achievements in the early twentieth century are well known, with a number of heralded individuals making globally recognized strides in the field of astrophysics. Covering the period from the foundation of the Asiatick Society in 1784 to the establishment of the Indian Association for the Cultivation of Science in 1876, Sen explores the relationship between Indian astronomers and the colonial British. He shows that from the mid-nineteenth century, Indians were not passive receivers of European knowledge, but active participants in modern scientific observational astronomy.
Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods
Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.
The Skyrme Model
The December 1988 issue of the International Journal of Modern Physics A is dedicated to the memory of Tony Hilton Royle Skyrme. It contains an informative account of his life by Dalitz and Aitchison's reconstruction of a talk by Skyrme on the origin of the Skyrme model. From these pages, we learn that Tony Skyrme was born in England in December 1922. He grew up in that country during a period of increasing economic and political turbulence in Europe and elsewhere. In 1943, after Cambridge, he joined the British war effort in making the atomic bomb. He was associated with military projects throughout the war years and began his career as an academic theoretical physicist only in 1946. During...
Nonnegative Matrix Factorization
Nonnegative matrix factorization (NMF) in its modern form has become a standard tool in the analysis of high-dimensional data sets. This book provides a comprehensive and up-to-date account of the most important aspects of the NMF problem and is the first to detail its theoretical aspects, including geometric interpretation, nonnegative rank, complexity, and uniqueness. It explains why understanding these theoretical insights is key to using this computational tool effectively and meaningfully. Nonnegative Matrix Factorization is accessible to a wide audience and is ideal for anyone interested in the workings of NMF. It discusses some new results on the nonnegative rank and the identifiability of NMF and makes available MATLAB codes for readers to run the numerical examples presented in the book. Graduate students starting to work on NMF and researchers interested in better understanding the NMF problem and how they can use it will find this book useful. It can be used in advanced undergraduate and graduate-level courses on numerical linear algebra and on advanced topics in numerical linear algebra and requires only a basic knowledge of linear algebra and optimization.
Accounts in Drug Discovery
Accounts in Drug Discovery describes recent case studies in medicinal chemistry with a particular emphasis on how the inevitable problems that arise during any project can be surmounted or overcome. The Editors cover a wide range of therapeutic areas and medicinal chemistry strategies, including lead optimization starting from high-throughput screening "hits" as well as rational, structure-based design. The chapters include "follow-ons" and "next generation" compounds that aim to improve upon first-generation agents. This volume surveys the range of challenges commonly faced by medicinal chemistry researchers, including the optimization of metabolism and pharmacokinetics, toxicology, pharmac...
