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This book is a collection of works regarding the interactions of science, technology, and society.
The interrelations of science and technology as an object of study seem to have drawn the attention of a number of disciplines: the history of both science and technology, sociology, economics and economic history, and even the philosophy of science. The question that comes to mind is whether the phenomenon itself is new or if advances in the disciplines involved account for this novel interest, or, in fact, if both are intercon nected. When the editors set out to plan this volume, their more or less explicit conviction was that the relationship of science and technology did reveal a new configuration and that the disciplines concerned with 1tS analysis failed at least in part to deal with the change because of conceptual and methodological preconceptions. To say this does not imply a verdict on the insufficiency of one and the superiority of any other one disciplinary approach. Rather, the situation is much more complex. In economics, for example, the interest in the relationship between science and technology is deeply influenced by the theoretical problem of accounting for the factors of economic growth. The primary concern is with technology and the problem is whether the market induces technological advances or whether they induce new demands that explain the subsequent diffusion of new technologies. Science is generally considered to be an exogenous factor not directly subject to market forces and, therefore, appears to be of no interest.
This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communities of nations). Part three contains discussions of non-Gaussian laws connected to scientific productivity and presents various deterministic and stochastic models of science dynamics and research productivity. The book shows that many famous fat tail distributions as well as many deterministic and stochastic models and processes, which are well known from physics, theory of extreme events or population dynamics, occur also in the description of dynamics of scientific systems and in the description of the characteristics of research productivity. This is not a surprise as scientific systems are nonlinear, open and dissipative.
Models of Science Dynamics aims to capture the structure and evolution of science, the emerging arena in which scholars, science and the communication of science become themselves the basic objects of research. In order to capture the essence of phenomena as diverse as the structure of co-authorship networks or the evolution of citation diffusion patterns, such models can be represented by conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, or computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive study of the topic. This volume fills this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented cover stochastic and statistical models, system-dynamics approaches, agent-based simulations, population-dynamics models, and complex-network models. The book comprises an introduction and a foundational chapter that defines and operationalizes terminology used in the study of science, as well as a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of remaining challenges for future science models and their relevance for science and science policy.
This volume intends to give an insight into progress in the field of studies on modern science and technology. Researchers from Sweden, Japan and Germany began a "three country comparative study" in 1984. One of the primary aims of this study group was to better take account of the increasing importance of Japan in both analytical work and technology policy. To this end, researchers from the Research Policy Institute (RPI) at the University of Lund, the Graduate School of Policy Science at Saitama University in Urawa, and the Fraunhofer Institute for Systems and Innovation Research in Karlsruhe met almost every year with policy makers from the three countries, in order to see how well the scientific debate is reflected in the interests of practitioneers in the related policies. The cooperation with the Swedish Board for Technical Development (STU)!, the Japanese Ministry of Education, Science and Culture (Monbusho), and the German Federal Ministry for Research and Technology (BMFT) brought about numerous "grey" papers, publications and two volumes of seminar proceedings. The first book2 deals with the problems of measuring technological change and summarizes tentative research plans from our first meetings. I concluded then, in November 1986, that "quantitative results are to be checked in a qualitative discursive process with the involved people. ( . . . ) The interaction of various indicators raises the pressure of argument and credibility. Case studies in dynamic fields of technology ideally supplement quantitative approaches.
In this provocative and broad-ranging work, the authors argue that the ways in which knowledge - scientific, social and cultural - is produced are undergoing fundamental changes at the end of the twentieth century. They claim that these changes mark a distinct shift into a new mode of knowledge production which is replacing or reforming established institutions, disciplines, practices and policies. Identifying features of the new mode of knowledge production - reflexivity, transdisciplinarity, heterogeneity - the authors show how these features connect with the changing role of knowledge in social relations. While the knowledge produced by research and development in science and technology is accorded central concern, the
"Lab Dynamics is a book about the challenges to doing science and dealing with the individuals involved, including oneself. The authors, a scientist and a psychotherapist, draw on principles of group and behavioral psychology but speak to scientists in their own language about their own experiences. They offer in-depth, practical advice, real-life examples, and exercises tailored to scientific and technical workplaces on topics as diverse as conflict resolution, negotiation, dealing with supervision, working with competing peers, and making the transition from academia to industry." "This is a uniquely valuable contribution to the scientific literature, on a subject of direct importance to lab heads, postdocs, and students. It is also required reading for senior staff concerned about improving efficiency and effectiveness in academic and industrial research."--BOOK JACKET
Natural disasters bedevil our planet, and each appears to be a unique event. Leading geologist Susan W. Kieffer shows how all disasters are connected. In 2011, there were fourteen natural calamities that each destroyed over a billion dollars’ worth of property in the United States alone. In 2012, Hurricane Sandy ravaged the East Coast and major earthquakes struck in Italy, the Philippines, Iran, and Afghanistan. In the first half of 2013, the awful drumbeat continued—a monster supertornado struck Moore, Oklahoma; a powerful earthquake shook Sichuan, China; a cyclone ravaged Queensland, Australia; massive floods inundated Jakarta, Indonesia; and the largest wildfire ever engulfed a large part of Colorado. Despite these events, we still behave as if natural disasters are outliers. Why else would we continue to build new communities near active volcanoes, on tectonically active faults, on flood plains, and in areas routinely lashed by vicious storms? A famous historian once observed that “civilization exists by geologic consent, subject to change without notice.” In the pages of this unique book, leading geologist Susan W. Kieffer provides a primer on most types of natural disasters: earthquakes, tsunamis, volcanoes, landslides, hurricanes, cyclones, and tornadoes. By taking us behind the scenes of the underlying geology that causes them, she shows why natural disasters are more common than we realize, and that their impact on us will increase as our growing population crowds us into ever more vulnerable areas. Kieffer describes how natural disasters result from “changes in state” in a geologic system, much as when water turns to steam. By understanding what causes these changes of state, we can begin to understand the dynamics of natural disasters. In the book’s concluding chapter, Kieffer outlines how we might better prepare for, and in some cases prevent, future disasters. She also calls for the creation of an organization, something akin to the Centers for Disease Control and Prevention but focused on pending natural disasters.
This textbook covers handling and performance of both road and race cars. Mathematical models of vehicles are developed always paying attention to state the relevant assumptions and to provide explanations for each step. This innovative approach provides a deep, yet simple, analysis of the dynamics of vehicles. The reader will soon achieve a clear understanding of the subject, which will be of great help both in dealing with the challenges of designing and testing new vehicles and in tackling new research topics. The book deals with several relevant topics in vehicle dynamics that are not discussed elsewhere and this new edition includes thoroughly revised chapters, with new developments, and many worked exercises. Praise for the previous edition: Great book! It has changed drastically our approach on many topics. We are now using part of its theory on a daily basis to constantly improve ride and handling performances. --- Antonino Pizzuto, Head of Chassis Development Group at Hyundai Motor Europe Technical Center Astonishingly good! Everything is described in a very compelling and complete way. Some parts use a different approach than other books. --- Andrea Quintarelli, Automotive Engineer
Many historical processes are dynamic. Populations grow and decline. Empires expand and collapse. Religions spread and wither. Natural scientists have made great strides in understanding dynamical processes in the physical and biological worlds using a synthetic approach that combines mathematical modeling with statistical analyses. Taking up the problem of territorial dynamics--why some polities at certain times expand and at other times contract--this book shows that a similar research program can advance our understanding of dynamical processes in history. Peter Turchin develops hypotheses from a wide range of social, political, economic, and demographic factors: geopolitics, factors affecting collective solidarity, dynamics of ethnic assimilation/religious conversion, and the interaction between population dynamics and sociopolitical stability. He then translates these into a spectrum of mathematical models, investigates the dynamics predicted by the models, and contrasts model predictions with empirical patterns. Turchin's highly instructive empirical tests demonstrate that certain models predict empirical patterns with a very high degree of accuracy. For instance, one model accounts for the recurrent waves of state breakdown in medieval and early modern Europe. And historical data confirm that ethno-nationalist solidarity produces an aggressively expansive state under certain conditions (such as in locations where imperial frontiers coincide with religious divides). The strength of Turchin's results suggests that the synthetic approach he advocates can significantly improve our understanding of historical dynamics.