Computational Approaches

Over the last fifty years, the ability to carry out analysis as a precursor to decision making in engineering design has increased dramatically. In particular, the advent of modern computing systems and the development of advanced numerical methods have made computational modelling a vital tool for producing optimized designs. This text explores how computer-aided analysis has revolutionized aerospace engineering, providing a comprehensive coverage of the latest technologies underpinning advanced computational design. Worked case studies and over 500 references to the primary research literature allow the reader to gain a full understanding of the technology, giving a valuable insight into the world’s most complex engineering systems. Key Features: Includes background information on the history of aerospace design and established optimization, geometrical and mathematical modelling techniques, setting recent engineering developments in a relevant context. Examines the latest methods such as evolutionary and response surface based optimization, adjoint and numerically differentiated sensitivity codes, uncertainty analysis, and concurrent systems integration schemes using grid-based computing. Methods are illustrated with real-world applications of structural statics, dynamics and fluid mechanics to satellite, aircraft and aero-engine design problems. Senior undergraduate and postgraduate engineering students taking courses in aerospace, vehicle and engine design will find this a valuable resource. It will also be useful for practising engineers and researchers working on computational approaches to design.

This book presents recently developed computational approaches for the study of reactive materials under extreme physical and thermodynamic conditions. It delves into cutting edge developments in simulation methods for reactive materials, including quantum calculations spanning nanometer length scales and picosecond timescales, to reactive force fields, coarse-grained approaches, and machine learning methods spanning microns and nanoseconds and beyond. These methods are discussed in the context of a broad range of fields, including prebiotic chemistry in impacting comets, studies of planetary interiors, high pressure synthesis of new compounds, and detonations of energetic materials. The book presents a pedagogical approach for these state-of-the-art approaches, compiled into a single source for the first time. Ultimately, the volume aims to make valuable research tools accessible to experimentalists and theoreticians alike for any number of scientific efforts, spanning many different types of compounds and reactive conditions.

Focusing on five main groups of interdisciplinary problems, this book covers a wide range of topics in mathematical modeling, computational science and applied mathematics. It presents a wealth of new results in the development of modeling theories and methods, advancing diverse areas of applications and promoting interdisciplinary interactions between mathematicians, scientists, engineers and representatives from other disciplines. The book offers a valuable source of methods, ideas, and tools developed for a variety of disciplines, including the natural and social sciences, medicine, engineering, and technology. Original results are presented on both the fundamental and applied level, accompanied by an ample number of real-world problems and examples emphasizing the interdisciplinary nature and universality of mathematical modeling, and providing an excellent outline of today’s challenges. Mathematical modeling, with applied and computational methods and tools, plays a fundamental role in modern science and engineering. It provides a primary and ubiquitous tool in the context making new discoveries, as well as in the development of new theories and techniques for solving key problems arising in scientific and engineering applications. The contributions, which are the product of two highly successful meetings held jointly in Waterloo, Ontario, Canada on the main campus of Wilfrid Laurier University in June 2015, i.e. the International Conference on Applied Mathematics, Modeling and Computational Science, and the Annual Meeting of the Canadian Applied and Industrial Mathematics (CAIMS), make the book a valuable resource for any reader interested in a broader overview of the methods, ideas and tools involved in mathematical and computational approaches developed for other disciplines, including the natural and social sciences, engineering and technology.

Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families. Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans. A major challenge presently is to integrate the hard-earned knowledge and expertise of traditional historical linguistics with cutting-edge methodology explored primarily in computational linguistics. The idea for the present volume came out of a concrete response to this challenge. The 1st International Workshop on Computational Approaches to Historical Language Change (LChange'19), at ACL 2019, brought together scholars from both fields. This volume offers a survey of this exciting new direction in the study of semantic change, a discussion of the many remaining challenges that we face in pursuing it, and considerably updated and extended versions of a selection of the contributions to the LChange'19 workshop, addressing both more theoretical problems — e.g., discovery of "laws of semantic change" — and practical applications, such as information retrieval in longitudinal text archives.

This volume of original chapters written by experts in the field offers a snapshot of how historical built spaces, past cultural landscapes, and archaeological distributions are currently being explored through computational social science. It focuses on the continuing importance of spatial and spatio-temporal pattern recognition in the archaeological record, considers more wholly model-based approaches that fix ideas and build theory, and addresses those applications where situated human experience and perception are a core interest. Reflecting the changes in computational technology over the past decade, the authors bring in examples from historic and prehistoric sites in Europe, Asia, and the Americas to demonstrate the variety of applications available to the contemporary researcher.

Terrorist groups throughout the world have been studied primarily through the use of social science methods. However, major advances in IT during the past decade have led to significant new ways of studying terrorist groups, making forecasts, learning models of their behaviour, and shaping policies about their behaviour. Handbook of Computational Approaches to Counterterrorism provides the first in-depth look at how advanced mathematics and modern computing technology is shaping the study of terrorist groups. This book includes contributions from world experts in the field, and presents extensive information on terrorism data sets, new ways of building such data sets in real-time using text analytics, introduces the mathematics and computational approaches to understand terror group behaviour, analyzes terror networks, forecasts terror group behaviour, and shapes policies against terrorist groups. Auxiliary information will be posted on the book’s website. This book targets defence analysts, counter terror analysts, computer scientists, mathematicians, political scientists, psychologists, and researchers from the wide variety of fields engaged in counter-terrorism research. Advanced-level students in computer science, mathematics and social sciences will also find this book useful.

The past fifteen years have seen great changes in the field of language acquisition. New experimental methods have yielded insights into the linguistic knowledge of ever younger children, and interest has grown in the phonological, syntactic, and semantic aspects of the lexicon. Computational investigations of language acquisition have also changed, reflecting, among other things, the profound shift in the field of natural language processing from hand-crafted grammars to grammars that are learned automatically from samples of naturally occurring language.Each of the four research papers in this book takes a novel formal approach to a particular problem in language acquisition. In the first paper, J. M. Siskind looks at developmentally inspired models of word learning. In the second, M. R. Brent and T. A. Cartwright look at how children could discover the sounds of words, given that word boundaries are not marked by any acoustic analog of the spaces between written words. In the third, P. Resnik measures the association between verbs and the semantic categories of their arguments that children likely use as clues to verb meanings. Finally, P. Niyogi and R. C. Berwick address the setting of syntactic parameters such as headedness--for example, whether the direct object comes before or after the verb.

Biopharmaceuticals are emerging as frontline medicines to combat several life-threatening and chronic diseases. However, such medicines are expensive to develop and produce on a commercial scale, contributing to rising healthcare costs. Developability of Biotherapeutics: Computational Approaches describes applications of computational and molecular modeling techniques that improve the overall process of discovery and development by removing empiricism. The concept of developability involves making rational choices at the pre-clinical stages of biopharmaceutical drug development that could positively impact clinical outcomes. The book also addresses a general lack of awareness of the many different contributions that computation can make to biopharmaceutical drug development. This informative and practical reference is a valuable resource for professionals engaged in industrial research and development, scientists working with regulatory agencies, and pharmacy, medicine, and life science students and educators. It focuses primarily on the developability of monoclonal antibody candidates, but the principles described can also be extended to other modalities such as recombinant proteins, fusion proteins, antibody drug conjugates and vaccines. The book is organized into two sections. The first discusses principles and applications of computational approaches toward discovering and developing biopharmaceutical drugs. The second presents best practices in developability assessments of early-stage biopharmaceutical drug candidates. In addition to raising awareness of the promise of computational research, this book also discusses solutions required to improve the success rate of translating biologic drug candidates into products available in the clinic. As such, it is a rich source of information on current principles and practices as well as a starting point for finding innovative applications of computation towards biopharmaceutical drug development.