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“Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.
Real Analysis is a discipline of intensive study in many institutions of higher education, because it contains useful concepts and fundamental results in the study of mathematics and physics, of the technical disciplines and geometry. This book is the first one of its kind that solves mathematical analysis problems with all four related main software Matlab, Mathcad, Mathematica and Maple. Besides the fundamental theoretical notions, the book contains many exercises, solved both mathematically and by computer, using: Matlab 7.9, Mathcad 14, Mathematica 8 or Maple 15 programming languages. The book is divided into nine chapters, which illustrate the application of the mathematical concepts using the computer. Each chapter presents the fundamental concepts and the elements required to solve the problems contained in that chapter and finishes with some problems left to be solved by the readers. The calculations can be verified by using a specific software such as Matlab, Mathcad, Mathematica or Maple.
User Modeling and Adaptation for Daily Routines is motivated by the need to bring attention to how people with special needs can benefit from adaptive methods and techniques in their everyday lives. Assistive technologies, adaptive systems and context-aware applications are three well-established research fields. There is, in fact, a vast amount of literature that covers HCI-related issues in each area separately. However, the contributions in the intersection of these areas have been less visible, despite the fact that such synergies may have a great impact on improving daily living. Presenting a comprehensive review of state-of-the-art practices on user modeling and adaptation for people with special needs, as well as some reflections on the challenges that need to be addressed in this direction, topics covered within this volume include the analysis, design, implementation and evaluation of adaptive systems to assist users with special needs to take decisions and fulfil daily routine activities. Particular emphasis is paid to major trends in user modeling, ubiquitous adaptive support, diagnostic and accessibility, recommender systems, social interaction, designing and building adaptive assistants for daily routines, field studies and automated evaluation. Nine leading contributors write on key current research in the domain of adaptive applications for people with special needs, integrating and summarizing findings from the best known international research groups in these areas. User Modeling and Adaptation for Daily Routines highlights how adaptation technologies can ease daily living for all, and support sustainable high-quality healthcare, demographic ageing and social/economic inclusion. highlights how adaptation technologies can ease daily living for all, and support sustainable high-quality healthcare, demographic ageing and social/economic inclusion.
Knowledge is power: In today’s era of knowledge-based economies, constantly changing business environments, severe competition, and globalization, gaining the knowledge edge will greatly empower an organization to stay on the cutting edge. Intelligence Methods and Systems Advancements for Knowledge-Based Business examines state-of-the-art research in decision sciences and business intelligence, and the applications of knowledge-based business with information systems. This comprehensive volume will provide researchers, academics, and business professionals with the research and inspiration they need to strengthen and empower their businesses in today’s world.
Genetic Programming IV: Routine Human-Competitive Machine Intelligence presents the application of GP to a wide variety of problems involving automated synthesis of controllers, circuits, antennas, genetic networks, and metabolic pathways. The book describes fifteen instances where GP has created an entity that either infringes or duplicates the functionality of a previously patented 20th-century invention, six instances where it has done the same with respect to post-2000 patented inventions, two instances where GP has created a patentable new invention, and thirteen other human-competitive results. The book additionally establishes: GP now delivers routine human-competitive machine intelligence GP is an automated invention machine GP can create general solutions to problems in the form of parameterized topologies GP has delivered qualitatively more substantial results in synchrony with the relentless iteration of Moore's Law
V.1. Design representation and models of routine design. v.2. Models of innovat ive design, reasoning about physical systems, and reasoning about geometry. v.3 . Knowledge acquisition, commercial systems, and integrated environments.
This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader’s area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.