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Complex Systems Science in Biomedicine
Complex Systems Science in Biomedicine covers the emerging field of systems science involving the application of physics, mathematics, engineering and computational methods and techniques to the study of biomedicine including nonlinear dynamics at the molecular, cellular, multi-cellular tissue, and organismic level. With all chapters helmed by leading scientists in the field, Complex Systems Science in Biomedicine's goal is to offer its audience a timely compendium of the ongoing research directed to the understanding of biological processes as whole systems instead of as isolated component parts.
Complex Systems in Biomedicine
Features contributions from several Italian research groups that are working on the field of biomedicine. Each chapter in this book deals with a specific subfield, with the aim of providing an overview of the subject and an account of the research results.
A Legacy for Living Systems : Gregory Bateson as Precursor to Biosemiotics
This book represents a major attempt to revise this deficiency. Scholars from ecology, biochemistry, evolutionary biology, cognitive science, anthropology and philosophy discuss how Bateson's thinking might lead to a fruitful reframing of central problems in modern science. Most important perhaps, Bateson's bioanthropology is shown to play a key role in developing the set of ideas explored in the new field of biosemiotics. The idea that organismic life is indeed basically semiotic or communicative lies at the heart of the biosemiotic approach to the study of life.The only book of its kind, this volume provides a key resource for the quickly-growing substratum of scholars in the biosciences, philosophy and medicine who are seeking an elegant new approach to exploring highly complex systems.
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Issues in Multi-Agent Systems : The AgentCities.ES Experience
The purpose of this book is to present current status of this technology by looking at its application in different domains, such as electronic markets, e-tourism, ambience intelligence, and complex system analysis.It starts by discussing software engineering issues for the development of multi-agent systems, how much it costs to build a multi-agent system, and which methods and tools are currently available. Next chapters present some of the most relevant aspects that are considered for the development of multi-agent systems.
Categories for software engineering
This book provides a gentle, software engineering oriented introduction to category theory. Assuming only a minimum of mathematical preparation, this book explores the use of categorical constructions from the point of view of the methods and techniques that have been proposed for the engineering of complex software systems: object-oriented development, software architectures, logical and algebraic specification techniques, models of concurrency, inter alia. After two parts in which basic and more advanced categorical concepts and techniques are introduced, the book illustrates their application to the semantics of CommUnity – a language for the architectural design of interactive systems. "For computer scientists, this unique book presents Category Theory in a manner tailored to their interests and with examples to which they can relate." Ira Forman, IBM "This book applies little-known yet quite powerful formal tools from category theory to software structures: designs, architectures, patterns, and styles. Rather than focus on issues at the level of computational models and semantics, it instead applies these tools to some of the problems facing the sophisticated software architect.
Big Data : Conceptual Analysis and Applications
The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used.
Autonomy oriented computing : From problem solving to complex systems modeling
Autonomy Oriented Computing explores the important theoretical and practical issues in AOC, by analyzing methodologies and presenting experimental case studies. The book serves as a comprehensive reference source for researchers, scientists, engineers, and professionals in all fields concerned with this promising new development in computer science. It can also be used as a main or supplementary text in graduate and undergraduate programs across a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing and Computer Vision, Programming Paradigms, Computational Biology, and many others. The first part of the book, Fundamentals, describes the basic concepts and characteristics of an AOC system, and then it enumerates the critical design and engineering issues faced in AOC system development. The second part of the book, AOC in Depth, provides a detailed analysis of methodologies and case studies to evaluate the use of AOC in problem solving and complex system modeling. The final chapter reviews the essential features of the AOC paradigm and outlines a number of possibilities for future research and development.
Artificial life models in software
Artificial Life Models in Software presents software tools, environments and realities dealing with creation, imitation and analysis of artefactual, virtual and living forms, written by those who personally design and produce software, hardware and art installations in artificial life, simulated complex systems and virtual worlds. This timely volume offers a nearly exhaustive overview and original analysis of major non-profit artificial life software packages. The carefully selected topics include: · simulation of real and imaginary life forms and their evolution · self-organization · emergent behaviours · swarm intelligence · evolutionary robotics · agent-based simulations · adaptive, complex and biologically inspired ecosystems · creative computer art There has long been a need within the academic and research community for an informal introduction and guidance to modern software tools for modelling and simulation of life-like phenomena – Artificial Life Models in Software fills this gap and provides invaluable information to both professional and amateur readers, offering detailed reviews of contemporary software for artificial life.
Artificial general intelligence
This book focused on engineering general intelligence – autonomous, self-reflective, self-improving, commonsensical intelligence.Each author explains a specific aspect of AGI in detail in each chapter, while also investigating the common themes in the work of diverse groups, and posing the big, open questions in this vital area.
Architecture of advanced numerical analysis systems: designing a scientific computing system using ocaml
Applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language.
Analysis and Design of Information Systems : Third ed.
This third edition of the successful Analysis and Design of Information Systems provides a comprehensive introduction and user-friendly survey to all aspects of business transformation and analysis, and aims to provide the complex set of tools covering all types of systems, including legacy, transactional, database, and web/e-commerce topics.
A Platform-Centric Approach to System-on-Chip (SOC) Design
The book proposes a new methodology for realizing platform-centric design of complex systems, and presents a detailed plan for its implementation. The proposed plan allows component vendors, system integrators and product developers to collaborate effectively and efficiently to create complex products within budget and schedule constraints.
Complex systems approach to economic dynamics
This monograph introduces new concepts of unstable periodic orbits and chaotic saddles which are unstable structures embedded in a chaotic attractor, responsible for economic intermittency.
Artificial markets modeling : Methods and applications
Agent-based computational modeling with its intrinsic multidisciplinary approach is gaining increasing recognition in the social sciences, particularly in economics, business and finance. This volume is devoted to recent contributions to the field from both the social sciences and computer sciences.
Analysis, Control and Optimization of Complex Dynamic Systems
Analysis, Control and Optimization of Complex Dynamic Systems gathers in a single volume a spectrum of complex dynamic systems related papers written by experts in their fields, and strongly representative of current research trends. Complex systems present important challenges, in great part due to their sheer size which makes it difficult to grasp their dynamic behavior, optimize their operations, or study their reliability. Yet, we live in a world where, due to increasing inter-dependencies and networking of systems, complexity has become the norm. With this in mind, the volume comprises two parts. The first part is dedicated to a spectrum of complex problems of decision and control encountered in the area of production and inventory systems. The second part is dedicated to large scale or multi-agent system problems occurring in other areas of engineering such as telecommunication and electric power networks, as well as more generic context.
Mathematical Methods in Time Series Analysis and Digital Image Processing
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed.
Managing Complexity : Insights, Concepts, Applications
Each chapter in Managing Complexity focuses on analyzing real-world complex systems and transferring knowledge from the complex-systems sciences to applications in business, industry and society. The interdisciplinary contributions range from markets and production through logistics, traffic control, and critical infrastructures, up to network design, information systems, social conflicts and building consensus. They serve to raise readers' awareness concerning the often counter-intuitive behavior of complex systems and to help them integrate insights gained in complexity research into everyday planning, decision making, strategic optimization, and policy.
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Linearization Methods for Stochastic Dynamic Systems
The aim of this book is to give a systematic introduction to and overview of the relatively simple and popular linearization methods available. The scope is limited to models with continous external and parametric excitations, yet these cover the majority of known approaches. The book contains an application chapter with emphasis on vibration analysis of stochastic mechanical structures as well as a chapter devoted to the assessment of the accuracy of the theoretical methods presented, both with respect to numerical and to experimental studies.
