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Debunking popular reform efforts, this book argues that education reformers are fighting a fruitless uphill battle. Neither top-down regulation nor locally based reforms will transform schooling. The insurmountable problem is juxtaposing a continuous change theme with a continuous, conservative system that defies change. In partnership with all community agencies, educators must initiate the creation of learning societies as part of a larger social agenda. Following an introductory chapter, chapter 2 discusses the essential partnership of moral purpose with change agentry. Chapter 3 treats the complexity of the change process, identifying eight basic lessons of a new change paradigm: (1) you can't mandate or force change; (2) change is a journey, not a blueprint; (3) problems are our friends; (4) vision and strategic planning come later; (5) individualism and collectivism must have equal power; (6) neither centralization nor decentralization works by itself; (7) connections with the wider environment is critical for success; and (8) every person is a change agent. Chapters 4 and 5 discuss the school as a learning organization and the two-way relationship between a learning organization and its environment. Chapter 6 argues that continuous teacher education is essential to produce moral change agents. The final chapter treats the productive individual's role in shaping and checking schooling and other social institutions. Contains 168 references and a subject index. (MLH)

This anthology considers some ways that chaos theory might be not only a descriptive metaphor for the conditions of leadership, planning, and policy in higher education, but also a prescriptive metaphor that might be used to improve these functions and others. The essays are: (1) "Introduction: Metaphor, Chaos Theory, and This Book" (Marc Cutright); (2) "Managing Universities in a Supercomplex Age" (Ronald Barnett); (3) "Strategic Planning and Chaos Theory: Are They Compatible?" (Jean (Prinvale) Swenk); (4) "A Chaos Theory Metaphor for Strategic Planning" (Marc Cutright); (5) "Chaos Theory Applied to College Planning: A Case Study in Defense of Ten Propositions" (James R. Perkins, Jeffrey B. Lanigan, John A. Downey, and Bernard H. Levin); (6) "Chaos Theory and the Evolution of a State System of Higher Education" (Jeffery P. Aper); (7) "Performance Indicators and Chaos Theory" (Bob Barnetson); (8) "The Impact of Technology and Student Choice on Postsecondary Education: 'Plus Ca Change?'" (Adrian Kershaw and Susan Safford); (9) "Reshaping Higher Education in a Post-Fordist World: Chaos and Collingwood" (Bryant Griffith and Lynn Speer Lemisko); (10) "Chaotic Systems: Confounding or Confirming the Leadership Role in Higher Education?" (John T. Dever); and (11) "Leadership's Natural Ally: Applying Chaos and Complexity Theories to Academe" (Barbara Mossberg). (Each chapter contains references.) (SLD)

This book relates the radically new sciences of the 20th century--quantum mechanics, chaos theory, and complexity theory--to organizational problems and challenges facing corporate leaders. The book draws on the science of the human brain, with its three different kinds of neural structures--mental, emotional, and spiritual--to illustrate how to exercise the full creative capacities of the "corporate brain." It proposes a new model for structure, leadership, and learning within organizations that allows them to thrive on uncertainty, deal creatively with rapid change, and realize the full potential of workers and leaders. Part 1, "Using the New Science to Rewire Corporate Thinking," contains chapter 1, "Three Levels of Real Transformation"; chapter 2, "Three Kinds of Thinking: How the Brain Rewires Itself"; chapter 3, "Eight Principles of the Old and New Science Applied to Leadership"; and chapter 4, "At the Edge." Part 2, "Structure and Leadership of the Rewired Corporation," contains chapter 5, "The Western Model: The Newtonian Self and the Newtonian Organization"; chapter 6, "The Eastern Model: The Networked Self and the Networked Organization"; chapter 7, "The Quantum Model: Bridging East and West"; chapter 8, "Dialogue: A Chance to Grow New Neural Connections"; and chapter 9, "Servant Leaders: What Do They Really Serve?" Ten figures, three tables, and an index are included. (Contains 31 references.) (LMI)

This book provides an introduction to the field of curriculum and instruction development as it relates to emerging postmodern education paradigms. The book discusses such terms as "curriculum development,""postmodernism,""hermeneutics,""paradigm,""chaos theory,""poststructuralism," and "critical theory" in the context of the educational milieu of the 1990s in the United States. Readers are challenged to examine their own definitions of and the reality of the classroom connections. The book is divided into three parts with 13 chapters. Part 1, "Postmodern Curriculum Development as a Field of Study," includes: (1) "Introduction to Curriculum Development and Postmodernity"; (2) "Historical Perspectives on Curriculum as a Field of Study"; (3) "The Reconceptualization of Curriculum and Instruction"; and (4) "Postmodern Schooling, Curriculum, and the Theological Text." Part 2, "Contemporary Curriculum Development Paradigms," contains: (5) "The Hermeneutic Circle and Postmodern Community"; (6) "Race, Gender, and Ethnicity in a Multicultural Milieu"; (7) "Postmodern Philosophies in Curriculum Studies"; (8) "Curriculum for Interdependence and Ecological Sustainability"; (9) "Utopian Visions, Democracy, and the Egalitarian Ideal"; (10) "Qualitative Inquiry, Fine Arts, and the Synthetical Moment"; and (11) "Time Management and Chaos in the Finite Cosmos." Part 3, "Curriculum Development in the Postmodern Era," includes: (12) "Postmodern Education: Kaleidoscopic Sensibilities"; and (13) "A Postmodern Postscript: Proleptic Prolegomena." (EH)

This book suggests the adoption of a critical pragmatic approach to the problems of educational change. It offers a set of criticisms by which theories and reform proposals may be judged and tested, and proposes the reconstruction of schools in place of school restructuring. A primary question to be asked is, "How shall social institutions be organized, and to what end?" Chapter 1 outlines the essential tension in theorizing about schools. It illustrates how the current school-reform dilemma came about, how the frameworks approach to the study of institutions is faulty, and how a nonfoundational notion of organizational inquiry improves on the faults of traditional social science methodological assumptions. Chapter 2 criticizes chaos theory, in particular, attempts to apply chaos theory to the practice of teaching and learning in educational institutions. Chapter 3 discusses the appropriateness of democratic models for school organizations in developed and developing nations. The fourth chapter examines three efforts to restructure schools in Kentucky, Chicago (Illinois), and West Feliciana (Louisiana). These proposals are tested first against a modernist model of interrogation and then against a postmodern, critical paradigmatic model for educational reform. Chapter 5 explores the pluralistic nature of democracies and raises the question of individual autonomy relative to contemporary fractured democratic states. Three kinds of democratically based pluralistic recommendations are examined. Chapter 6 argues that schools are buoys in a moral sea, that schools in a democratic society must rest on aesthetic and moral-ethical processes, and that the failure of restructuring has resulted from reformers overlooking the polyvalue basis of all patterned social life. The concluding chapter offers possible guides for the reconstruction of school organizations for the 21st century. (Contains 253 references.) (LMI)

Reviews four books: (1) "A Dynamic Systems Approach to Development: Applications" (Linda B. Smith and Esther Thelen, Eds.); (2) "The Psychology of Gender" (Anne E. Beall and Robert J. Sternberg, Eds.); (3) "Children's Understanding: The Development of Mental Models" (Graeme S. Halford); and (4) "Adolescent Storm and Stress: An Evaluation of the Mead-Freeman Controversy" (James E. Cote). (AA)

This book applies "new science"--the discoveries and hypotheses in biology, chemistry, and physics that challenge fundamental world views--to organizational change. The focus is on new ways about thinking about organizations. The introduction and chapter 1 introduce three branches of science and their contributions to understanding--quantum physics, self-organizing systems, and chaos theory. Chapters 2 through 4 explore the implications of quantum physics for organizational designs and practices for large, complex systems. Chapters 5 and 6 deal with the theory of self-organizing or dissipative structures. They introduce new ways of understanding disequilibrium and change, as well as the uses of disorder in creating new possibilities for evolutionary growth. Chaos theory is the subject of chapter 7, which proposes a hypothesis to explain forces in organizations that create durable structure. The eighth chapter and the epilogue draw together various principles from the new science to offer a "new" scientific approach to management. Four figures, 10 photographs, an index, and a list of suggested readings are included. (Contains 78 references.) (LMI)

We live within a time of intense flux and unpredictable change. It is doubtful whether our techniques of management deal with such times very well, as they tend to look for eternal truths and forms of action and control. This paper asks whether our situation might be improved by looking to pre-Platonic philosophical sources for guidance; in this case the writings of Lao Tzu, Heraclitus and Gorgias. After exploring this background the paper considers the ways that people manage software installations, as these are exemplars of chaotic systems with unintended and often disruptive effects. The conclusion is that these ancient philosophers have something to say to us about the way our attempts to create order actually create disorder. Order and disorder are not opposites which negate each other, but are intertwined in an `order/disorder' complex. [ABSTRACT FROM AUTHOR]

This paper proposed a kind of gray image digital watermarking algorithm of combining discrete wavelet transform and discrete cosine transform with singular value decomposition based on chaos and scrambling for the purpose of raising security, invisibility and robustness of watermark. It hided the digital watermarking in the discrete cosine transform domain. The image that contained the watermark was restored and the watermark was extracted by the singular value decomposition. The experimental results demonstrate that the watermark not only has good invisibility by use of this algorithm but also has good robustness against geometric distortion, noise attack and so on. [ABSTRACT FROM AUTHOR]

A chaotic orbit generated by a nonlinear system is irregular, aperiodic, unpredictable and has sensitive dependence on initial conditions. However, the chaotic trajectory is still not well enough to be a crypto system in digital secure communication. Therefore, we propose a Modified Logistic Map (MLM) and give a theoretical proof to show that the MLM is a chaotic map according to Devaney's definition. Based on the MLMs, we establish a Modified Logistic Hyper-Chaotic System (MLHCS) and apply MLHCS to develop a symmetric cryptography algorithm, Asymptotic Synchronization of Modified Logistic Hyper-Chaotic System (ASMLHCS). [ABSTRACT FROM AUTHOR]

Performance results for finding the best genetic algorithm for the complex real problem of optimal machinery equipment operation and predictive maintenance are presented. A genetic algorithm is a stochastic computational model that seeks the optimal solution to an objective function. A methodology calculation is based on the idea of measuring the increase of fitness and fitness quality evaluation with chaos theory principles applying within genetic algorithm environment. Fuzzy neural networks principles are effectively applied in solved manufacturing problems mostly where multisensor integration, real - timeness, robustness and learning abilities are needed. A modified Mamdani neuro-fuzzy system improves the interpretability of used domain knowledge. [ABSTRACT FROM AUTHOR]

There are numerous algorithms available for training artificial neural networks. Besides classical algorithms for supervised learning such as backpropagation, associative memory and radial basis function, this training task can be employed by evolutionary computation since most of the gradient descent related algorithms can be view as an application of optimization theory and stochastic search. In this paper, the logistic model of population growth from ecology is integrated into initialization, selection and crossover operators of genetic algorithms for neural network training. These chaotic operators are very efficient in maintaining the population diversity during the evolution process of genetic algorithms. A comparison is done on the basis of a benchmark comprising several data classification problems for neural networks. Three variants of training – Backpropagation (BP), Genetic Algorithms (GA) and Genetic Algorithms with Chaotic Operators (GACO) – are described and compared. The experimental results confirm the dynamic mobility of chaotic algorithms in GACO network training, which can overcome saturation and improve the convergence rate. [ABSTRACT FROM AUTHOR]

The aim of this paper is to show how efficient mathematical models can be in simulating situations that are apparently distant from one another. The works of M. C. Escher and Buckminster Fuller are used as starting points for the exploration of the first applications of non-Euclidean geometry to architecture. The investigation goes on to fractals and chaos, nurbs, blob architecture and deconstructivism. [ABSTRACT FROM AUTHOR]

The present paper introduces the development, valuable part and application of neural network. It also analyzes systematically the existing problems and the combination of neural network with wavelet analysis, fuzzy set, chaos, rough sets and other theories, together with its applications and the hot spots of the research on neural network. The analysis proves that the prospects of neural network will be primising with the combination method, and that subject integration will be the chief interest for the neural network research. [ABSTRACT FROM AUTHOR]

This paper proposes a robust and simple controller design for the Duffing-Holmes chaotic system. The control system is robust against parametric uncertainties and external disturbances. The control input consists of a continuous nominal control part and a discontinuous switching control input. Illustrative example is given. Simulation results show the promise of the proposed method. Input chattering is remarkably eliminated. Trajectory tracking is effectively achieved. [ABSTRACT FROM AUTHOR]

Feature selection is a useful technique for increasing classification accuracy. The primary objective is to remove irrelevant features in the feature space and identify relevant features. Binary particle swarm optimization (BPSO) has been applied successfully in solving feature selection problem. In this paper, chaotic binary particle swarm optimization (CBPSO) with logistic map for determining the inertia weight is used. The K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) serves as a classifier for evaluating classification accuracies. Experimental results indicate that the proposed method not only reduces the number of features, but also achieves higher classification accuracy than other methods. [ABSTRACT FROM AUTHOR]

We present a novel analysis of multimedia data that is useful in human computer interfacing. By analyzing the video content of humans walking towards a camera, we establish the nonlinear nature of fronto-normal human gait which motivates the use of nonlinear dynamical analysis used in chaos theory to analyze human gait. In doing so, we obtain features that may be used as a biometric which can be used for automatic identification of humans using computers. We apply this in a multi-biometric experiment to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Modern content-based image retrieval systems use different features to represent properties (e.g., color, shape, texture) of the visual content of an image. Retrieval is performed by example where a query image is given as input and an appropriate metric is used to find the best matches in the corresponding feature space. Both selecting the features and the distance metric continue to be active areas of research. In this paper, we propose a new approach, based on the recently proposed Multidimensional Dynamic Time Warping (MD-DTW) distance [1], for assessing the texture similarity of images with structured textures. The MD-DTW allows the detection and comparison of arbitrarily shifted patterns between multi-dimensional series, such as those found in structured textures. Chaos theory tools are used as a preprocessing step to uncover and characterize regularities in structured textures. The main advantage of the proposed approach is that explicit selection and extraction of texture features is not required (i.e., similarity comparisons are performed directly on the raw pixel data alone). The method proposed in this preliminary investigation is shown to be valid by proving that it creates a statistically significant image texture similarity measure. [ABSTRACT FROM AUTHOR]

This paper is concerned with the identical synchronization problem for a class of chaotic systems. Under certain conditions, a dynamic compensator is proposed to achieve the synchronization only using the accessible output variables. A numerical example is included to demonstrate the proposed scheme. [ABSTRACT FROM AUTHOR]

Compared with low-dimensional chaos system, Hyperchaos system has excellent security in communication because Hyperchaos sequence has better complexity and randomicity. The thought is proposed that Hyperchaos sequence is applied to Design the pseudorandom sequence after decreasing its dimension, then the novel algorithm is proposed, and the thorough analysis and research are carried on to verify Hyperchaos sequence's capability. Study shows that the novel chaos pseudorandom sequence has good complexity and well-proportioned stochastic diffusion. A novel stochastic sequence design method is achieved. [ABSTRACT FROM AUTHOR]

This paper proposes a proportional-integral-derivative (PID)-learning-type adaptive fuzzy controller (AFC) for chaotic Duffing dynamic systems. The proposed PID-learning-type AFC is comprised of a fuzzy controller and a robust controller. The fuzzy controller is designed to mimic an ideal controller and the robust controller is designed to dispel the effect of the approximation error between the fuzzy controller and the ideal controller. All the control parameters are on-line tuned in the sense of Lyapunov theorem, thus the stability of the system can be guaranteed. Finally, a comparison between a conventional AFC and the proposed PID-learning-type AFC is presented. Simulation results verify that the proposed PID-learning-type AFC can achieve better tracking performance and faster tracking error convergence than the conventional AFC for chaotic Duffing dynamic systems. [ABSTRACT FROM AUTHOR]

An actual physical simulation model was constructed, and it was used simulate the course of water displacing oil. Under certain physical property parameter conditions, we simulated the water injection well and the oil withdrawal well on the physical simulation model, and continuous measured online the oil and water content of different area of physical simulation model in three-dimensional space using the 512 routes resistivity measuring circuit, then we can obtain large numbers of simulation samples. Considering the issues that the relationship between the remaining oil and every parameters of water displacing oil is a complicated and nonlinear, the chaos genetic angorithm neural network was used to establish the water displacing remaining oil model, in order to obtain the distributing situation of remaining oil in various complicated condition. The experimental results show that this method is feasible and effective. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive intelligent tracking control (AITC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This AITC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. The all adaptation laws of the AITC system are derived based on the Lyapunov stability analysis, so that the stability of the system can be guaranteed. Finally, the proposed AITC system is applied to control a Van der Pol oscillator and a Genesio chaotic system. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most common brain disorders. At least 40 million people or about 1% of the population worldwide currently suffer from epilepsy Despite advances in neurology and neuroscience, approximately 25–30% of epileptic patients remain unresponsive to anti-epileptic drug treatment, which is the standard therapy for epilepsy There is a growing body of evidence and interest in predicting epileptic seizures using intracranial electroencephalogram (EEG), which is a tool for evaluating the physiological state of the brain. Although recent studies in the EEG dynamics have been used to demonstrate seizure predictability, the question of whether the brain΄s normal and pre-seizure epileptic activities are distinctive or differentiable remains unanswered. In this study, we apply data mining techniques to EEG data in order to verify the classifiability of the brain dynamics. We herein propose a quantitative analysis derived from the chaos theory to investigate the brain dynamics. We employ measures of chaoticity and complexity of EEG signals, including Short-Term Maximum Lyapunov Exponents, Angular Frequency, and Entropy, which were previously shown capable of contemplating dynamical mechanisms of the brain network. Each of these measures can be used to display the state transition toward seizures, in which different states of patients can be classified (normal, pre-seizure, and post-seizure states). In addition, optimization and data mining techniques are herein proposed for the extraction of classifiable features of the brain΄s normal and pre-seizure epileptic states from spontaneous EEG. We use these features in study of classification of the brain΄s normal and epileptic activities. A statistical cross validation is implemented to estimate the accuracy of the brain state classification. The results of this study indicate that it may be possible to design and develop efficient seizure warning algorithms for diagnostic and therapeutic purposes. [ABSTRACT FROM AUTHOR]

There is a lot of literature announcing the advent of Information Society; in the meantime, though, we are living in a transitional period that has been labeled as Risk Society (RS). One of the specific traits of RS is the spreading of this perception of risk and the growing wish for higher security. However, this paper argues that risk is poorly treated nowadays and that a new approach is in demand. Futures Studies (FS) can provide this perspective, but only as long as it is able to integrate the inputs of other disciplines such as Chaos Theory, Evolutionary Theory and Kondratieff Waves (KW). KW can have a key role in this endeavor as they can offer ways to surpass one of FS shortcomings, their difficulty to incorporate in a solid way human variables in systemic methods. On the other hand, FS can help KW in several aspects: to improve their capacity to work with inputs from diverse sources, to assimilate with greater ease the normative aspects inherent to risk researches and, finally, a way to get around the not-so-appealing determinism implicit in KW. [ABSTRACT FROM AUTHOR]

Chapter III of the book "In Search of the Lost Feminine: Decoding the Myths That Radically Reshaped Civilization" is presented. It focuses on the chaos that followed the Trojan War in the year 1200 BCE. It was during the Dark Age after the Trojan War that women came to be considered as subordinates. Women became the target of widespread vilification by 800 BCE.

An interview with Robert May, president of the Royal Society in Great Britain, is presented. He states that most of the things which are discussed in education are focused on linear systems. May explains that chaos theory implies the end of the Newtonian dream. He also admits that life sciences are more complicated because of its nature as very high-dimensional systems.

Chapter 6 of the book "Chaos, Complexity, Curriculum and Culture: A Conversation," edited by William E. Doll, Jr., M. Jayne Fleener, Donna Trueit, and John St. Julien is presented. It investigates the two main theories of nonlinearity which are the notions of chaos theory in mathematics and complexity theory in science. It also discusses the three aspects of chaos including the fractal patterns, bounded infinity, and unpredictability.

Introduction Over the past fifty years or so we have seen a veritable fragmentation of economic theory. Research has ramified in different directions and its very foundations – methods and techniques of analysis, crucial concepts and simplifying assumptions, central problems – have undergone broad diversification. This has led to a division of labour among substantially autonomous groups of economists who often ignore, or in any case do not take into account in their own research, what happens in other areas of research. This trend has been reinforced by the high level of technicality that, together with diversification in the techniques of analysis, makes the studies required for any given field of research increasingly specific and time-consuming. For instance, the new evolutionary theories of the firm have no relation to research on the microeconomic foundations of macroeconomics; it would be quite difficult to find some common ground between research on the institutional evolution of financial markets and the so-called ‘new growth theory’ which seeks to make technical progress endogenous to the theory itself. Economists become ever more specialised and increasingly limit their readings and their professional contacts to researchers active in the same field and pursuing a similar research orientation; increasing numbers of specialised journals and professional societies are created; the very processes of academic selection favour the fragmentation of economists into separate corporations. It is thus quite difficult, in this situation, to provide a reasonably balanced and complete illustration of the different streams of economic research. [ABSTRACT FROM AUTHOR]

The article focuses on the chaotic system in communications. The deterministic but unpredictable behaviors of certain classes of nonlinear dynamical systems have been called chaos. If a chaotic system can he decomposed into two subsystems, a drive system and a conditionally stable response system, then the identical chaotic system at the receiver can he synchronized when driven with a common signal. The authors note that on the basis of the self-synchronization properties of chaotic systems, various chaotic communication systems using chaos as carrier have been proposed.

ABSTRACT Great variations in fertility constitute one of the major findings of this project to our knowledge of the demography of the past. In the Ancient Americas (that is, more than 1,500 years ago), fertility seems to have been surprisingly low (gross reproduction ratio, GRR, = 2.3), and the brake on explosive population growth was fertility rather than mortality (life expectancy at birth, e0, = 34 years). Consequently, the ancient demographic regime was a relatively low-pressure system. A high-pressure system of high fertility and high mortality dates from the middle period, 1500 bp–500 bp (before the present). Characteristic of only simple horticulturists in ancient times, a high-pressure demographic regime seems to have become more general during the middle period, intrinsic to both complex agrarian systems as well as foragers and fishers (GRR = 3.0 and 2.8, respectively). Agriculture was not the engine of demographic transformation in prehistoric America because nonhorticulturists also experienced a substantial rise in fertility. A second great demographic transformation began 500 years ago with the intrusion of Old World populations and technologies. While these changes were sweeping, indeed many peoples were thrust to the verge of extinction, the fundamental demography of the survivors did not change greatly. The old demographic regime persisted into the nineteenth century, if the picture developed here from the osteological evidence is trustworthy. Likewise, African–American demographic systems seem to have been under high pressure: very high fertility and high mortality, with the highest pressures characteristic of the free. European–American demographic systems, as measured here, were decidedly low pressure, with relatively moderate mortality and moderately higher fertility. [ABSTRACT FROM AUTHOR]

In this chapter the authors explore the interaction between fuzzy control systems and chaos. First, they show that fuzzy modeling techniques can be used to model chaotic dynamical systems, which also implies that fuzzy systems can be chaotic. On the subject of controlling chaos, this chapter presents a unified approach, using the LMI-based fuzzy control system design. The authors develop a unified approach to address such problems stabilization, synchronization, and chaotic model following control (CMFC) as for chaotic systems. [ABSTRACT FROM PUBLISHER]

The article presents the experiences of the David Byrne, author of the book "Complexity Theory & the Social Sciences," that inspired him to write the book. The pattern of contingent events that led to the writing of this book began when the Byrne picked Mitchell Waldrop's book "Complexity," off the popular science shelves in a large Newcastle bookshop. Waldrop was dealing with in his account of the work of the members of the Santa Fe Institute and others who had gone beyond chaos theory, but it was the subtitle of the book which caught his imagination complexity was defined as the domain between linearly determined order and indeterminate chaos. That rang so many bells and seemed to offer a solution to so many problems. After all it is a commonplace to say that the social world has been tricky territory for scientific investigation, precisely because it is complex, whereas the methods and forms of understanding generally employed in science are absolutely dependent on things being sorted out in simple terms.

In this chapter the author focuses on the new and changing methodologies in science and social science. The recognition of indeterminate nature of much of the natural world is important to social science for three reasons. First, if it is the case that complex systems in the social world behave similarly to ones in the natural world, then it is possible that the same kinds of organizing principles underlie these systems. Second, the techniques for studying complex systems are most likely to have similarities. Lastly the study of complex systems implies the study of the relationships between one system and another and so an interdisciplinary approach to the study of, for example, the interrelationship of social and biological systems is much more likely to yield results. Advances in chaos theory required more sophisticated computing and what is the final twist is that the development of this computing itself led to new insights about the nature of complexity, especially as the result of emergent properties in the computing environments themselves.

We have given an overview of the different methods which allow the transmission of information with chaotic carriers. We have highlighted that chaotic carriers could be of great interest in communication applications in which one needs to spread the information and/or desires sonic level of secrecy. The demodulation of the information can be achieved in different ways. Synchronization can be one of these ways if one wants to develop coherent receivers. Until now. synchronization of chaos seems to be a solution which is not suitable for imperfect communication channels since it is difficult to maintain synchronization when noise is added in the channel. These aspects have been addressed in the sections entitled "Synchronization of Chaotic Systems" and "Exploiting Chaos Synchronization for Transmission of Information." The statistical properties of the chaotic signals can he exploited in different manners, by replacing the conventional PN sequences of standard spread-spectrum systems by a chaotic oscillator (see section entitled "Example 1: Chaotic Direct-Sequence Spread-Spectrum Systems" or by using differential coding techniques (see section entitled `Example 2: Differential Chaos Shift Keying"1) if one wants to develop noncoherent receivers. The statistical aspects as well as the deterministic aspect of chaos can be exploited together to improve the statistical approach. This view which has been developed in the section entitled "Improving Chaos Transmission by Exploiting the Deterministic Feature of Chaos" offers new avenues in communicating with chaos and will be certainly exploited in a next generation of spread-spectrum systems. [ABSTRACT FROM AUTHOR]

This article presents selected methods developed for controlling chaos in various aspects. These start from the most primitive concepts like parameter variation, through classical controller applications, to quite sophisticated ones like stabilization of unstable periodic orbits embedded within a chaotic attractor. The most common goal of control for a chaotic system is suppression of oscillations of the "bad" kind and influencing the system in such a way that it will produce a prescribed, desired motion. The goals vary depending on a particular application. The most common goal is to convert chaotic motion into a stable periodic or constant one. Many chaotic systems display what is called multiple basins of attracton and fractal basin boundaries. This means that, depending on the initial conditions, trajectories can converge to different steady states.

The article describes a number of simple deterministic electronic circuits that exhibit chaos. The earliest experimental observations of chaos in electronic circuits were in forced nonautonomous nonlinear oscillators. Technically a chaotic circuit is one whose steady-state behavior is characterized by one or more positive Lyapunov exponents. Lyapunov exponents characterize the average exponential rate of separation of trajectories of a dynamical system on the attractor. Chaos may be defined as bounded steady-state behavior in a deterministic dynamical system that is not an equilibrium point, not periodic, and not quasi-periodic.

The article discusses the basic concept underlying chaotic systems which is that seemingly simple equations can produce extremely complex behavior when followed over time. Many nonlinear differential equations also result in chaos. The chaotic nature of these equations poses a major problem in modeling many physical processes, as these models rely on nonlinear models. Applications that result in nonlinear dynamic models include fluid dynamics, meteorology, and hemodynamics. A major area of work that utilizes chaos theory is the modeling of nonlinear dynamical systems. Chaos theory is attractive for these models because traditional mathematical models cannot be solved analytically.

The article states that the traditional linear, psychodynamic models of therapy are not as effective as multi-level systemic family therapy for treating the urban poor or those families who live in a world of disorganization and chaos. A systemic approach is presented which may end the need for the continual tying and untying in the mental health field. The Chaos Theory is described. Social workers must advocate for a national family policy. They need to reassess their own thinking about health and illness, especially with regard to the multicultural imperatives of the late Twentieth Century.

The article reports on chaos theory related to sociology. Chaotic system refers to systems or behavior that are completely random. A system can be both chaotic and stable depending on when one observes it. Chaos theory seems on the surface to some postmodernists as proving that empirical science is an illusion rooted in self-deception. However, there are two dire difficulties with such a claim. For one thing, there is the double-reflexivity problem. Reflexity is the postmodern term for the idea that no truth claim can be understood as other than grounded in the power relations experienced by those making the claim. The emergence of chaos, complexity criticality and self-organization however possess many drawbacks. As with all great breakthroughs in science, the incorporation into science of the ideas of chaos, complexity, emergence, and complex adaptive systems brings with it increased power to understand and manipulate the world. As with all other major scientific breakthroughs, both good news and bad news are inherent in such a new conceptual advances.

The article reports on some of the specific ways in which algorithmic pattern manifests itself in complex system dynamics, especially chaotic complex system dynamics. In both engineering systems theory and mathematical dynamical systems theory, one studies systems in terms of temporal changes in numerical variables. This is a powerful paradigm for modeling and data analysis, with a great deal of history behind it, and a large amount of theory backing it up. The article discusses the algorithmic information theory in order to study the theory of universal turing machines. It also describes a computational algorithm for extracting patterns from systems, which is called the chaos language algorithm (CLA). The concept at the heart of the CLA is the use of formal languages to represent patterns in the trajectories of a dynamical system. The end result of this algorithmic process is a formal language that captures some of the statistical and algorithmic structure of the attractor of the dynamical system.

The article reports on chaos theory in relation to social reality. Chaos is a mathematical theory. Two complementary myths have developed around chaos as an explanatory model. The first myth is that chaos represents complete uncertainty or even complete indeterminacy. The second myth is that chaos has been reliably identified in very many social and psychological systems. Three conditions must be realized for a chaotic system--there must be a non-linear operation, it must be iteratively carried out, that is, the operation is repeated with the output of one iterative cycle becoming the input of the next; and there must be sensitivity to initial conditions. Only if all three conditions are present, then the system is chaotic. The article also discusses a study aimed at determining whether the social act of holding doors open for other people is a behavior that is passed on. The experiment was based on the observation that while at one time people simply passed through a swinging door letting it go behind them, a polite, door-holding pattern had replaced this and become established quite quickly.