Esta obra introduce al lector en un campo de la investigacion que se halla en continua expansion. La existencia del caos determinista, la aparicion de objetos fractales en la naturaleza o nuestra incapacidad de predecir el futuro, pese a disponer de modelos deterministas, se exponen de forma coherente y a un alto nivel. Asimismo, se analizan con profundidad, mediante diversas aproximaciones teoricas, la aparicion de la complejidad y su cuantificacion, asi como sus implicaciones en campos tan dispares como la evolucion y las extinciones, la dinamica de selvas o de virus emergentes
Applied Biomechatronics Using Mathematical Models provides an appropriate methodology to detect and measure diseases and injuries relating to human kinematics and kinetics. It features mathematical models that, when applied to engineering principles and techniques in the medical field, can be used in assistive devices that work with bodily signals. The use of data in the kinematics and kinetics analysis of the human body, including musculoskeletal kinetics and joints and their relationship to the central nervous system (CNS) is covered, helping users understand how the complex network of symbiotic systems in the skeletal and muscular system work together to allow movement controlled by the CNS. With the use of appropriate electronic sensors at specific areas connected to bio-instruments, we can obtain enough information to create a mathematical model for assistive devices by analyzing the kinematics and kinetics of the human body. The mathematical models developed in this book can provide more effective devices for use in aiding and improving the function of the body in relation to a variety of injuries and diseases. - Focuses on the mathematical modeling of human kinematics and kinetics - Teaches users how to obtain faster results with these mathematical models - Includes a companion website with additional content that presents MATLAB examples
Chaos: from simple models to complex systems aims to guide science and engineering students through chaos and nonlinear dynamics from classical examples to the most recent fields of research. The first part, intended for undergraduate and graduate students, is a gentle and self-contained introduction to the concepts and main tools for the characterization of deterministic chaotic systems, with emphasis to statistical approaches. The second part can be used as a reference by researchers as it focuses on more advanced topics including the characterization of chaos with tools of information theory and applications encompassing fluid and celestial mechanics, chemistry and biology. The book is novel in devoting attention to a few topics often overlooked in introductory textbooks and which are usually found only in advanced surveys such as: information and algorithmic complexity theory applied to chaos and generalization of Lyapunov exponents to account for spatiotemporal and non-infinitesimal perturbations. The selection of topics, numerous illustrations, exercises and proposals for computer experiments make the book ideal for both introductory and advanced courses. Sample Chapter(s). Introduction (164 KB). Chapter 1: First Encounter with Chaos (1,323 KB). Contents: First Encounter with Chaos; The Language of Dynamical Systems; Examples of Chaotic Behaviors; Probabilistic Approach to Chaos; Characterization of Chaotic Dynamical Systems; From Order to Chaos in Dissipative Systems; Chaos in Hamiltonian Systems; Chaos and Information Theory; Coarse-Grained Information and Large Scale Predictability; Chaos in Numerical and Laboratory Experiments; Chaos in Low Dimensional Systems; Spatiotemporal Chaos; Turbulence as a Dynamical System Problem; Chaos and Statistical Mechanics: Fermi-Pasta-Ulam a Case Study. Readership: Students and researchers in science (physics, chemistry, mathematics, biology) and engineering.
This collection of five essays by Germanys most prominent and influential social thinker both links Luhmanns social theory to the question What is modern about modernity? and shows the origins and context of his theory. In the introductory essay, Modernity in Contemporary Society, Luhmann develops the thesis that the modern epistemological situation can be seen as the consequence of a radical change in social macrostructures that he calls social differentiation, thereby designating the juxtaposition of and interaction between a growing number of social subsystems without any hierarchical structure. European Rationality defines rationality as the capacity to see the difference between systems and their environment as a unity. Luhmann argues that, in a world characterized by contingency, rationality tends to become coextensive with imagination, a view that challenges their classical binary opposition and opens up the possibility of seeing modern rationality as a paradox. In the third essay, Contingency as Modern Societys Defining Attribute, Luhmann develops a further and probably even more important paradox: that the generalization of contingency or cognitive uncertainty is precisely what provides stability within modern societies. In the process, he argues that medieval and early modern theology can be seen as a preadaptive advance through which Western thinking prepared itself for the modern epistemological situation. In Describing the Future, Luhmann claims that neither the traditional hope of learning from history nor the complementary hope of cognitively anticipating the future can be maintained, and that the classical concept of the future should be replaced by the notion of risk, defined as juxtaposing the expectation of realizing certain projects and the awareness that such projects might fail. The book concludes with The Ecology of Ignorance, in which Luhmann outlines prospective research areas for sponsors who have yet to be identified.
This book constitutes the revised selected papers of the 9th International Conference on Cloud Computing, Big Data & Emerging Topics, JCC-BD&ET 2021, held in La Plata, Argentina*, in June 2021. The 12 full papers and 2 short papers presented were carefully reviewed and selected from a total of 37 submissions. The papers are organized in topical sections on parallel and distributed computing; machine and deep learning; big data; web and mobile computing; visualization.. *The conference was held virtually due to the COVID-19 pandemic.
A classic and influential work that laid the theoretical foundations for information theory and a timely text for contemporary informations theorists and practitioners. With the influential book Cybernetics, first published in 1948, Norbert Wiener laid the theoretical foundations for the multidisciplinary field of cybernetics, the study of controlling the flow of information in systems with feedback loops, be they biological, mechanical, cognitive, or social. At the core of Wiener's theory is the message (information), sent and responded to (feedback); the functionality of a machine, organism, or society depends on the quality of messages. Information corrupted by noise prevents homeostasis, or equilibrium. And yet Cybernetics is as philosophical as it is technical, with the first chapter devoted to Newtonian and Bergsonian time and the philosophical mixed with the technical throughout. This book brings the 1961 second edition back into print, with new forewords by Doug Hill and Sanjoy Mitter. Contemporary readers of Cybernetics will marvel at Wiener's prescience—his warnings against “noise,” his disdain for “hucksters” and “gadget worshipers,” and his view of the mass media as the single greatest anti-homeostatic force in society. This edition of Cybernetics gives a new generation access to a classic text.
