Application Of Chaos Theory Research Articles

Application of Chaos Theory in Analyzing the Cardiac Rhythm in Healthy Subjects at Different Sleep Stages

The changes in the chaotic element of the cardiac rhythm (CR) were quantitated at different sleep stages by calculating the correlation dimension (D2) in 26 healthy subjects of both sexes (mean age 29.2 years), including 7 trained and 19 untrained subjects. Three untrained subjects took part in tests with autonomic nervous system blockers (atropine and propranolol). The study demonstrated a correlation between the changes in D2 at different sleep stages and the level of the autonomic regulation of CR. As the influence of the parasympathetic system on CR increased from one stage of slow wave sleep to another, D2 increased; during rapid eye movement (REM) sleep, this influence weakened and D2 decreased. The character of changes differed in the trained and untrained subjects and depended on the initial level of the autonomic regulation of CR. In the trained subjects, characterized by predominance of the parasympathetic regulation of CR, the initial and subsequent D2 values were higher than in the untrained subjects. Both during wakefulness and at all stages of sleep, D2 increased when the sympathetic regulation of CR was blocked, decreased when the parasympathetic regulation was blocked, and reached the lowest level when both of them were blocked. This showed that the chaotic element of CR, expressed numerically by D2, depends on the regulating effects of the autonomic nervous system.

EC-SVM approach for real-time hydrologic forecasting

This study demonstrates a combined application of chaos theory and support vector machine (SVM) in the analysis of chaotic time series with a very large sample data record. A large data record is often required and causes computational difficulty. The decomposition method is used in this study to circumvent this difficulty. The various parameters inherent in chaos technique and SVM are optimised, with the assistance of an evolutionary algorithm, to yield the minimal prediction error. The performance of the proposed scheme, EC-SVM, is demonstrated on two daily runoff time series: Tryggevælde catchment, Denmark and the Mississippi River at Vicksburg. The prediction accuracy of the proposed scheme is compared with that of the conventional approach and the recently introduced inverse approach. This comparison shows that EC-SVM yields a significantly lower normalised RMSE value of 0.347 for the Tryggevælde catchment runoff and 0.0385 for the Mississippi River flow compared to 0.444 and 0.2064, respectively, resulting from the conventional approach. A slight improvement in accuracy was obtained by analysing the first difference or the daily flow difference time series. It should be noted, however, that the computational speed in analysing the daily flow difference time series is significantly much faster than that of the daily flow time series.

Destructive cycles: the role of genomic instability and adaptation in carcinogenesis.

Classical theories of carcinogenesis postulate that the accumulation of several somatic mutations is responsible for oncogenesis. However, these models do not explain how non-mutagenic carcinogens cause cancer. In addition, known mutation rates appear to be insufficient to account for observed cancer rates. Moreover, the current theory doesn't easily account for the long latencies observed in human cancers. Proponents of an aneuploidy-driven theory of carcinogenesis suggest that genomic instability has a causative role in carcinogenesis. In support of this theory, pre-neoplastic cells frequently display genomic instability while normal cells do not. Data obtained from a variety of model organisms have revealed that disruption of the cell cycle controls required for homeostasis results in the acquisition of genomic instability. Subsequently, this genomic instability becomes self-propagating via 'destructive cycles' and provides a medium for cellular selection and adaptation. Genomic instability allows numerous genetic and epigenetic alterations to accumulate during carcinogenesis without markedly changing phenotype until they are qualitatively or quantitatively sufficient to be selectively advantageous in the tumor microenvironment. Observations of adaptation in tumor cell populations and application of chaos theory may help elucidate the mechanism that drives the enormous genetic heterogeneity observed in tumors and provide insights into the development of new therapeutic cancer interventions and treatments.

New modelling of complex fish migration by application of chaos theory and neural network

Rules or patterns of movement or migration were still vague even for the main commercial fishes due to different routs in scale or in different, times resulting from complex environments to complex behaviour concept. The quantitative model of fish migration has been investigated using chaos theory to mimic more realistic fish movements by time steps from environmental and biological stimuli. The model uses three steps within a model neural network such as input stimuli, central decision‐making and response output in fish movements. The stimuli in the first step include the main physical (temperature, salinity, light, flow etc.) and biotic factors (prey, predator, life cycle etc.) which could be quantified as intensity parameters which were then normalized as ratios. The decision‐making process can be generated available signals for motor neuron using Lorenz chaos equations by the relevant stimuli. The response of fish movements from the output signal representing speed and direction can be re‐regulated as object‐oriented migration depending on physiological state or life cycle by third response filtering. The simulation results seen as 2‐dimensional seasonal migration for demersal fishes in the southern sea of the Korean Peninsula represented more realistic meandering tracks than the interpolated tracks in previous reports.

Numerical modeling of chaotic behavior for small-scale movements of demersal fishes in coastal water

: The presented model involves the application of chaos theory to generate fish movements resulting from environmental stimuli. The model uses three steps within a model neural network such as input stimuli, central decision making and response output resulting in fish movements. The stimuli in the first step include the main abiotic and biotic factors, which could be quantified as an intensity parameter that was then normalized as a ratio between 0 and 1. The decision-making process can be generated using chaos dynamics with the stimuli parameters. The response of fish movements from the output signal representing movement speed and direction of fish can be re-regulated as main movement pattern depending on physiological state or life cycle by third response filtering. The simulation results seen as a movement pattern for sea bream and flounder using this neural chaotic model fitted very well to the observations of fish tracked in the sea by ultrasonic tracking methods. It was also revealed that the fish movement components generated as movement velocity and direction when in tidal flow had similar patterns to those patterns seen in field observations with similar irregular and chaotic variations with time.

Events in Indonesia: exploring the limits to formal tourism trends forecasting methods in complex crisis situations

The desire to know the future is as old as humanity. For the tourism industry the demand for accurate foretelling of the future course of events is a task that consumes considerable energy and is of great significance to investors. This paper examines the issue of forecasting by comparing forecasts of inbound tourism made prior to the political and economic crises that engulfed Indonesia from 1997 onwards with actual arrival figures. The paper finds that current methods of forecasting are not able to cope with unexpected crises and other disasters and that alternative methods need to be examined including scenarios, political risk and application of chaos theory. The paper outlines a framework for classifying shocks according to a scale of severity, probability, type of event, level of certainty and suggested forecasting tools for each scale of shock.

Practical applications of chaos theory to the modulation of human ageing: nature prefers chaos to regularity.

From time to time, novel ways of interpreting and modifying ageing mechanisms are proposed. Occasionally, these lead to a conceptual dead end, whereas at other times new and vital insights into basic ageing mechanisms are gained. This review concentrates on one such way of interpreting and manipulating ageing processes, based on chaos (dynamical systems) theory. One prediction of this theory is that a wide-ranging loss of physiological complexity from molecular to cellular, and from tissue to organismic levels accompanies ageing and age-related diseases. Although this view has been criticised, and arguments have been put forward to claim that there is also an increase of complexity during ageing and dysfunction, this review holds that the interpretation of ageing as a simplification of physiological dynamical complexity offers clear advantages. Ageing changes can be quantified and the results of treatment monitored. Clinical benefits can be predicted and intervention strategies improved. Two main practical suggestions for achieving successful ageing at the clinical level are examined. First, chaos theory challenges the traditional pharmacological regimes and implies that, for maximum benefit, medication aimed at modifying some of the signs of ageing should be given at irregular, pulsed or multiple intervals, and at constantly changing dosage strengths. Second, for preventing age-related disability, it is necessary to introduce and maintain a multiplicity of external and internal physiological stimuli, such as variable physical and mental exercise regimes.

Application of chaos theory to solving the problems of social and environmental decline in Lesotho

This paper examines the definition of chaos theory and its use in different circumstances. The paper explains that environmental crisis is complex, chaotic and unstable and will remain so unless actions are taken to reverse the trend. It further suggests that chaos theory could be used to interpret the crisis and help identify solutions. By recommending the application of chaos theory to the environmental problems in Lesotho, the paper explores some of the key issues that contribute to and perpetuate the environmental situation, for example, the current land tenure system and the problem of overgrazing. In addition, it identifies appropriate and realistic government policies that could be implemented to address the environmental degradation in the country. The paper concludes that the application of chaos theory may be unable to help solve the environmental crisis in Lesotho unless there is political will and commitment and collective effort from all stakeholders, coupled with an attitudinal change.

Uncovering nonlinear dynamics-the case study of sea clutter

Nonlinear dynamics are basic to the characterization of many physical phenomena encountered in practice. Typically, we are given a time series of some observable(s) and the requirement is to uncover the underlying dynamics responsible for generating the time series. This problem becomes particularly challenging when the process and measurement equations of the dynamics are both nonlinear and noisy. Such a problem is exemplified by the case study of sea clutter which refers to radar backscatter from an ocean surface. After setting the stage for this case study, the paper presents tutorial reviews of: (1) the classical models of sea clutter based on the compound K distribution and (2) the application of chaos theory to sea clutter. Experimental results are presented that cast doubts on chaos as a possible nonlinear dynamical mechanism for the generation of sea clutter. Most importantly, experimental results show that on timescales smaller than a few seconds, sea clutter is very well described as a complex autoregressive process of order four or five. On larger timescales, gravity or swell waves cause this process to be modulated in both amplitude and frequency. It is shown that the amount of frequency modulation is correlated with the nonlinearity of the clutter signal. The dynamical model is an important step forward from the classical statistical approaches, but it is in its early stages of development.

Chaos in discrete production systems?

In the literature, several cases are reported of models of discrete nonstochastic production systems that show irregular, apparently chaotic behavior. In this paper, a number of these cases are analyzed, and the irregular behavior is attributed to: (1) chaotic behavior in hybrid models, (2) chaotic behavior in discrete-event models that use a chaotic map, or (3) periodic behavior with a period longer than the observation window. The irregular behavior of a discrete-event model of a two-machine production system is analyzed by means of nonlinear time-series analysis and sensitivity analysis. This case reveals the possibilities and limitations of the application of chaos theory to discrete-event models of production systems. Also, a new method for determining the sensitivity of discrete-event models to truly small changes is introduced. Realistic, non-artificial discrete-event models of discrete production systems that show chaotic behavior were not found in this study.

Theoretical foundations for the evolution and testing of a chaos theory of communicating

The authors explore the heuristic implications of chaos theory for the study of the process of communicating. Chaos theory's application to the study of communication is delineated from a socio‐cultural perspective. The basic tenants of chaos theory are outlined and some of the parallels between chaos theory, as developed for the physical sciences, and the process of communicating are described. Theoretical foundations for a chaos theory of communicating are laid, and suggestions are made for future evolution and testing of these foundations.

Non-linear dynamics and duopolistic competition: a R&D model and simulation

In recent years, a number of studies have considered the application of chaos theory to economics; the primary focus, however, has been the implications for stock prices, the foreign exchange market, and the macroeconomy. This paper describes a non-linear model of duopolistic competition, which focuses on a firm's expenditure and the resulting quality or technological endowment of its product. Results from computer iteration of the model are presented which indicate that chaotic outcomes are possible for a range of competing managerial policies; the associated unpredictability is due solely to the dynamics of the interaction. The study also provides the results of some initial work on how management adaptation may act to forestall chaotic outcomes.

The Application of Chaos Theory to the Career‐Plateaued Worker

This article uses chaos theory as a way to conceptualize the career‐plateaued worker. After discussing the literature regarding both chaos theory and career plateau, it applies some of the principles of chaos theory to career‐plateaued workers on the basis of a case study. The article concludes that chaos theory provides career practitioners a useful application for working with this type of client.

The Paradox of Stability and Change in Relationships: What Does Chaos Theory Offer for the Study of Romantic Relationships?

This article explores the potential relevance of chaos theory in understanding development and change in romantic relationships. Chaos theory implies that relationship development may not be linear, that relationships may quickly and spontaneously shift to different states and relational patterns, and that predicting their future state may be problematic. Furthermore, chaos theory generates several methodological and statistical issues for relationship studies. The application of chaos theory may increase the understanding of relation- ships as it stimulates a renewed emphasis on relationships as process, a moving from concern with predictability to emerging patterns, seeing variability as normal, and the recognition of the need for multiple perspectives and methods in studying relational development.

Chaos theory and James Joyce's Everyman

This study examines how Leopold Bloom's behaviour relates to such human matters as fate, free will, chance and courage. Unravelling some of Ulysses' most challenging passages, it reveals the heroism of the novel's main character while also demonstrating the utility of chaos theory for literary analysis. In a detailed assessments of Bloom's thoughts, behaviour and character, the author examines the philosophy of life apparent in Bloom's persistence amidst the day's - and the novel's - dramatic shifts. He demonstrates specific ways in which the stream-of-consciousness technique conveys personality, how Bloom's contingent relationship with his world reveals his fears and hopes, and how he finally pursues his desires despite the sad life that fate seems to have prepared for him. More than this, the author provides one of the most thorough applications of chaos theory to literature yet rendered. He demonstrates how chaos theory expands our understanding of literature and how cross-disciplinary exchange between science and the arts can inform our judgement of the ontological value of both. In the process, he also shows how and why chaos theory offers the best model yet for understanding daily human life and a fresh, humanistic understanding of Joyce.

At the Edge of Chaos

The search for a unified conceptual framework for social work has floundered as the profession has struggled with general systems theory and, most recently, the eco-systems perspective. Social work has also ignored chaos or complex systems theory, which, as the successor to general systems theory, some believe is the third major scientific revolution of the 20th century, following relativity and quantum theories. This article reviews key concepts and applications of chaos theory in the context of general systems theory and concludes that chaos theory shows promise as a solution to many problems posed by the now dated general systems approach.

Technothrillers and English for science and technology

Discussions on pre-historic life, novel techniques for DNA reconstruction, computer algorithms for large-database processing, or applications of chaos theory are topics one would normally find in specialized publications; however, they can appear in contemporary technothriller stories where adventure and academic seminar are skillfully blended. This article focuses on a particular teaching experience where a contemporary fiction work featuring high-tech has been used as source material in EST courses, and how this approach has had a positive impact on students' motivation to learn English as well as on their overall performance in the foreign language. It is suggested that since the same field of information —in this case science—can be accessed through different genres, EST teachers can incorporate fiction literature into their language programs, and exploit these reading passages through a combination of strategies drawn from literature lessons and tasks from ESP methodology. This choice allows both to attain the goals of EST courses and to initiate students into reading literature in the foreign language.

Chaos, Group Psychotherapy, and the Future of Uncertainty and Uniqueness

This paper explores the application of chaos theory, a new non-linear dynamical theory, to the understanding of psychotherapy groups. Two features of psychotherapy groups that have been insufficiently described or explained, uncertainty and uniqueness, are considered in the light of the chaos theory notion that groups proceed through periods of order and disorder. The recommendation is made that chaos theory be explored further as the field moves into the millennium and a hundred years of its own existence.

Application of chaos theory and fractal geometry to measurement of powder flow : R.G.Iacocca. (Pennsylvania State University, USA.)

Application of chaos theory and fractal geometry to measurement of powder flow : R.G.Iacocca. (Pennsylvania State University, USA.)

Chaotic Phenomena in Power Systems: Detection and Applications

This paper presents an overview of some possible applications of chaotic dynamics in power engineering. Recent studies of chaos in electric power systems are reviewed. Ways of analyzing time series data to determine the extent to which the observations can be characterized as low dimensional chaos are discussed. Novel applications of chaos theory in power engineering are also presented.