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Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web.
The study of chaotic systems has become a major scientific pursuit in recent years, shedding light on the apparently random behaviour observed in fields as diverse as climatology and mechanics. InThe Essence of Chaos Edward Lorenz, one of the founding fathers of Chaos and the originator of its seminal concept of the Butterfly Effect, presents his own landscape of our current understanding of the field. Lorenz presents everyday examples of chaotic behaviour, such as the toss of a coin, the pinball's path, the fall of a leaf, and explains in elementary mathematical strms how their essentially chaotic nature can be understood. His principal example involved the construction of a model of a board sliding down a ski slope. Through this model Lorenz illustrates chaotic phenomena and the related concepts of bifurcation and strange attractors. He also provides the context in which chaos can be related to the similarly emergent fields of nonlinearity, complexity and fractals. As an early pioneer of chaos, Lorenz also provides his own story of the human endeavour in developing this new field. He describes his initial encounters with chaos through his study of climate and introduces many of the personalities who contributed early breakthroughs. His seminal paper, "Does the Flap of a Butterfly's Wing in Brazil Set Off a Tornado in Texas?" is published for the first time.
Finalist for the Helen Bernstein Book Award for Excellence in Journalism From a New York Times investigative reporter, this “authoritative and devastating account of the impacts of social media” (New York Times Book Review) tracks the high-stakes inside story of how Big Tech’s breakneck race to drive engagement—and profits—at all costs fractured the world. The Chaos Machine is “an essential book for our times” (Ezra Klein). We all have a vague sense that social media is bad for our minds, for our children, and for our democracies. But the truth is that its reach and impact run far deeper than we have understood. Building on years of international reporting, Max Fisher tells the gripping and galling inside story of how Facebook, Twitter, YouTube, and other social network preyed on psychological frailties to create the algorithms that drive everyday users to extreme opinions and, increasingly, extreme actions. As Fisher demonstrates, the companies’ founding tenets, combined with a blinkered focus on maximizing engagement, have led to a destabilized world for everyone. Traversing the planet, Fisher tracks the ubiquity of hate speech and its spillover into violence, ills that first festered in far-off locales, to their dark culmination in America during the pandemic, the 2020 election, and the Capitol Insurrection. Through it all, the social-media giants refused to intervene in any meaningful way, claiming to champion free speech when in fact what they most prized were limitless profits. The result, as Fisher shows, is a cultural shift toward a world in which people are polarized not by beliefs based on facts, but by misinformation, outrage, and fear. His narrative is about more than the villains, however. Fisher also weaves together the stories of the heroic outsiders and Silicon Valley defectors who raised the alarm and revealed what was happening behind the closed doors of Big Tech. Both panoramic and intimate, The Chaos Machine is the definitive account of the meteoric rise and troubled legacy of the tech titans, as well as a rousing and hopeful call to arrest the havoc wreaked on our minds and our world before it’s too late.
Chaos in Ecology is a convincing demonstration of chaos in a biological population. The book synthesizes an ecologically focused interdisciplinary blend of non-linear dynamics theory, statistics, and experimentation yielding results of uncommon clarity and rigor. Topics include fundamental issues that are of general and widespread importance to population biology and ecology. Detailed descriptions are included of the mathematical, statistical, and experimental steps they used to explore nonlinear dynamics in ecology. Beginning with a brief overview of chaos theory and its implications for ecology. The book continues by deriving and rigorously testing a mathematical model that is closely wedded to biological mechanisms of their research organism. Therefrom were generated a variety of predictions that are fundamental to chaos theory and experiments were designed and analyzed to test those predictions. Discussion of patterns in chaos and how they can be investigated using real data follows and book ends with a discussion of the salient lessons learned from this research program Book jacket.
Chaos and complexity explained, with illuminating examples ranging from unpredictable pendulums to London's wobbly Millennium Bridge. The math we are taught in school is precise and only deals with simple situations. Reality is far more complex. Trying to understand a system with multiple interacting components—the weather, for example, or the human body, or the stock market—means dealing with two factors: chaos and complexity. If we don't understand these two essential subjects, we can't understand the real world. In Everyday Chaos, Brian Clegg explains chaos and complexity for the general reader, with an accessible, engaging text and striking full-color illustrations. By chaos, Clegg means a system where complex interactions make predicting long-term outcomes nearly impossible; complexity means complex interacting systems that have new emergent properties that make them more than the sum of their parts. Clegg illustrates these phenomena with discussions of predictable randomness, the power of probability, and the behavior of pendulums. He describes what Newton got wrong about gravity; how feedback kept steam engines from exploding; and why weather produces chaos. He considers the stock market, politics, bestseller lists, big data, and London's wobbling Millennium Bridge as examples of chaotic systems, and he explains how a better understanding of chaos helps scientists predict more accurately the risk of catastrophic Earth-asteroid collisions. We learn that our brains are complex, self-organizing systems; that the structure of snowflakes exemplifies emergence; and that life itself has been shown to be an emergent property of a complex system.
Make. More. Future. Artificial intelligence, big data, modern science, and the internet are all revealing a fundamental truth: The world is vastly more complex and unpredictable than we've allowed ourselves to see. Now that technology is enabling us to take advantage of all the chaos it's revealing, our understanding of how things happen is changing--and with it our deepest strategies for predicting, preparing for, and managing our world. This affects everything, from how we approach our everyday lives to how we make moral decisions and how we run our businesses. Take machine learning, which makes better predictions about weather, medical diagnoses, and product performance than we do--but often does so at the expense of our understanding of how it arrived at those predictions. While this can be dangerous, accepting it is also liberating, for it enables us to harness the complexity of an immense amount of data around us. We are also turning to strategies that avoid anticipating the future altogether, such as A/B testing, Minimum Viable Products, open platforms, and user-modifiable video games. We even take for granted that a simple hashtag can organize unplanned, leaderless movements such as #MeToo. Through stories from history, business, and technology, philosopher and technologist David Weinberger finds the unifying truths lying below the surface of the tools we take for granted--and a future in which our best strategy often requires holding back from anticipating and instead creating as many possibilities as we can. The book’s imperative for business and beyond is simple: Make. More. Future. The result is a world no longer focused on limitations but optimized for possibilities.
It is now generally recognised that very simple dynamical systems can produce apparently random behaviour. In the last couple of years, attention has turned to focus on the flip side of this coin: random-looking time series (or random-looking patterns in space) may indeed be the result of very complicated processes or “real noise”, but they may equally well be produced by some very simple mechanism (a low-dimensional attractor). In either case, a long-term prediction will be possible only in probabilistic terms. However, in the very short term, random systems will still be unpredictable but low-dimensional chaotic ones may be predictable (appearances to the contrary). The Royal Society held a two-day discussion meeting on topics covering diverse fields, including biology, economics, geophysics, meteorology, statistics, epidemiology, earthquake science and many others. Each topic was covered by a leading expert in the field. The meeting dealt with different basic approaches to the problem of chaos and forecasting, and covered applications to nonlinear forecasting of both artificially-generated time series and real data from context in the above-mentioned diverse fields. This book marks a rather special and rare occasion on which prominent scientists from different areas converge on the same theme. It forms an informative introduction to the science of chaos, with special reference to real data.
A desription of the new mathematical ideas in nonlinear dynamics in such a way that engineers can apply them to real physical systems.
Chaos theory has been hailed as a revolution of thoughts and attracting ever increasing attention of many scientists from diverse disciplines. Chaotic systems are nonlinear deterministic dynamic systems which can behave like an apparently erratic and irregular motion. Keep in mind that if we could characterise a chaotic system in some sense it would allow us to evidence that a deterministic generating system exists behind that chaotic system in spite of showing an apparently random behaviour. This fact would provide us to take advantage of this deterministic character to be able to make predictions and control over the variables of these (chaotic) deterministic dynamic systems. Methods and techniques related to test the hypothesis of chaos try to estimate the so-called Lyapunov exponents as a way of characterising achaotic system. Nowadays quantifying chaos from time-series data through this kind of quantitative measure in a rigorous fashion is far from being a trivial exercise and poses a number of theoretical and practical challenges...
In this volume, leading experts present current achievements in the forefront of research in the challenging field of chaos in circuits and systems, with emphasis on engineering perspectives, methodologies, circuitry design techniques, and potential applications of chaos and bifurcation. A combination of overview, tutorial and technical articles, the book describes state-of-the-art research on significant problems in this field. It is suitable for readers ranging from graduate students, university professors, laboratory researchers and industrial practitioners to applied mathematicians and physicists in electrical, electronic, mechanical, physical, chemical and biomedical engineering and science.