The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: * statistics, * time-frequency analysis, and * low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be used in combination to give critical insight into the fundamental workings of various problems. Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences. An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. Renown complexity thinkers and practitioners as well as those who are new to the area of complexity will find interest in this book.

Complex Systems occur in an infinite variety of problems, not only in the realm of physical sciences and engineering, but encompassing fields as diverse as economy, the environment, humanities, social and political sciences. The high level of dynamics of such systems, which is usually expressed through the frequent occurrence of unpredictable disruptive events, makes conventional optimizers, batch schedulers and resource planning systems unworkable. Composed of selected research papers, this book brings together new developments and processes for managing complexity. The included works originate from renowned complexity thinkers, well established practitioners and new researchers in the field and detail issues of common interest. This title will particularly appeal to researchers, developers and users of complex systems from a variety of disciplines, alongside specialists in modelling complex issues.

School-university partnerships have the potential to greatly benefit teaching and learning in PK-12 environments, as well as educator preparation programs. This collaboration is advantageous to teachers, counselors, and administrators. Professional Development Schools and Transformative Partnerships provides a comprehensive look at the design, implementation, and impact of educational initiatives between schools and universities. Including cases and research on existing collaborations, this publication addresses barriers and trends in order to provide direction for successful partnerships in the future. This book is an essential reference source for educational leaders in colleges, schools, and departments of education, as well as leaders of PK-12 schools.

The concept of "chaos", and chaos theory, though it is a field of study specifically in the field of mathematics with applications in physics, engineering, economics, management, and education, has also recently taken root in the social sciences. As a method of analyzing the way in which the digital age has connected society more than ever, chaos and complexity theory serves as a tactic to tie world events and cope with the information overload that is associated with heightened social connectivity. The Handbook of Research on Chaos and Complexity Theory in the Social Sciences explores the theories of chaos and complexity as applied to a variety of disciplines including political science, organizational and management science, economics, and education. Presenting diverse research-based perspectives on mathematical patterns in the world system, this publication is an essential reference source for scholars, researchers, mathematicians, social theorists, and graduate-level students in a variety of disciplines.

Complex analysis is found in many areas of applied mathematics, from fluid mechanics, thermodynamics, signal processing, control theory, mechanical and electrical engineering to quantum mechanics, among others. And of course, it is a fundamental branch of pure mathematics. The coverage in this text includes advanced topics that are not always considered in more elementary texts. These topics include, a detailed treatment of univalent functions, harmonic functions, subharmonic and superharmonic functions, Nevanlinna theory, normal families, hyperbolic geometry, iteration of rational functions, and analytic number theory. As well, the text includes in depth discussions of the Dirichlet Problem, Green's function, Riemann Hypothesis, and the Laplace transform. Some beautiful color illustrations supplement the text of this most elegant subject.

In order to ensure the criteria for monitoring and managing the various problems and design for decision control, a mathematical description of exact human knowledge is required for the management of adaptive and complex systems. Decision Control, Management, and Support in Adaptive and Complex Systems: Quantitative Models presents an application and demonstration of a new mathematical technique for descriptions of complex systems. This comprehensive collection contains scientific results in the field of contemporary approaches to adaptive decision making that is essential for researchers, scholars, and students alike.

This volume includes contributions originating from a conference held at Chapman University during November 14-19, 2017. It presents original research by experts in signal processing, linear systems, operator theory, complex and hypercomplex analysis and related topics.