Inicialmente, analisamos três sistemas mecânicos idéias com impactos: um oscilador com impactos, um sistema com par de impactos e uma caixa de engrenagens. Entre os impactos, o movimento é descrito por uma equação diferencial linear. Por ocasião dos impactos, introduzimos na solução analítica novas condições iniciais, de acordo com a lei de Newton para impactos. Devidos aos impactos, as trajetórias no espaço de fase são descontínuas e descritas por um mapa transcendental. Os expoentes de Lyapunov, importantes para caracterizar a natureza dos atratores obtidos, são calculados através desses mapas. Nas simulações numéricas, observamos fenômenos não-lineares como crises, intermitências, transientes caóticos e coexistências de atratores e obtemos as bacias de atração dos atratores coexistentes. Ademais, mostramos como controlar comportamentos caóticos, a partir de um forçamento de amplitude pequena, e pelo método OGY (Ott, Grebogi e Yorke) de controle de caos. Finalmente, investigamos a dinâmica de um sistema não-ideal com impactos, que é composto pelo sistema de par de impactos sobreposto ao um sistema não ideal (para qual a ação da fonte de energia depende da oscilação do sistema). A partir de simulações numéricas, identificamos fenômenos não-lineares como crise interior, intermitência e coexistência de atratores. Associado à crise interior observamos um tipo de intermitência que leva o sistema a oscilar entre três atratores caóticos. Além dessa intermitência, observamos uma outra, que envolve dois atratores periódicos e um caótico. Além disso, mostramos as bacias de atração de dois atratores periódicos coexistentes. Essas bacias possuem uma característica de bacia crivada. / Initially, we analyze three ideal mechanical systems with impacts: an impact oscilator, an impact-pair, and a gear-box (gear-rattling). Between impacts, the motion is described by a linear differential equation. After each impact, we use the Newton law of impact to determine new initial conditions of an analytical solution. Due to impacts, the trajectories in phase space are discontinuous and described by a transcendental map. The Lyapunov exponents, important to characterize the attractors, are calculated from the transcendental map. In the numerical simulations, we observe nonlinear phenomena as crises, intermittency, chaotic behavior, and coexisting attractors. Moreover, we present the basins of attraction of the coexisting attractors. Furthermore, we show how to control the chaotic behavior, with a small perturbation and by the OGY (Ott, Grebogi, and Yorke) method. Finally, we investigate the dynamics of a non-ideal system with impacts, that is composed by an impact-pair system on a non-ideal system (in this system, the energy source actions depend on the system oscillations). From the numerical simulations, we identify nonlinear phenomena as interior crises, intermittency, for which the system oscillates among three chaotic attractors. Besides this intermittency, we observe another one. Associated to a chaotic and two periodic attractors. In addition, we show the riddle basins of attraction of the two coexisting periodic attractors.

Main reason of this study is to set forth the internal paradox of the basic approach of the artificial intelligence in the medical field to by discussing on the theoretical and application levels and to suggest solutions in theory and practice against that. In order to rule out the internal paradox in the medical decision support systematic, a new medical model is suggested and based on this, concepts such as disease, health, etiology, diagnosis and treatment are questioned. Meanwhile, with the current scientific data, a simple application sample based on how a decision making system which was set up by fuzzy logic and which is based on the perception of human as a complex adaptive system has been explained. Finally, results of the research about accuracy and validity of this application, current improvements based on the current model and the location on the artificial intelligence theory is discussed.

abstract: Today's world is seeing a rapid technological advancement in various fields, having access to faster computers and better sensing devices. With such advancements, the task of recognizing human activities has been acknowledged as an important problem, with a wide range of applications such as surveillance, health monitoring and animation. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. An alternative idea I propose is the use of descriptors of the shape of the dynamical attractor as a feature representation for quantification of nature of dynamics. The framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. Approximately 1\% of the total world population are stroke survivors, making it the most common neurological disorder. This increasing demand for rehabilitation facilities has been seen as a significant healthcare problem worldwide. The laborious and expensive process of visual monitoring by physical therapists has motivated my research to invent novel strategies to supplement therapy received in hospital in a home-setting. In this direction, I propose a general framework for tuning component-level kinematic features using therapists’ overall impressions of movement quality, in the context of a Home-based Adaptive Mixed Reality Rehabilitation (HAMRR) system. The rapid technological advancements in computing and sensing has resulted in large amounts of data which requires powerful tools to analyze. In the recent past, topological data analysis methods have been investigated in various communities, and the work by Carlsson establishes that persistent homology can be used as a powerful topological data analysis approach for effectively analyzing large datasets. I have explored suitable topological data analysis methods and propose a framework for human activity analysis utilizing the same for applications such as action recognition. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

Inicialmente, analisamos três sistemas mecânicos idéias com impactos: um oscilador com impactos, um sistema com par de impactos e uma caixa de engrenagens. Entre os impactos, o movimento é descrito por uma equação diferencial linear. Por ocasião dos impactos, introduzimos na solução analítica novas condições iniciais, de acordo com a lei de Newton para impactos. Devidos aos impactos, as trajetórias no espaço de fase são descontínuas e descritas por um mapa transcendental. Os expoentes de Lyapunov, importantes para caracterizar a natureza dos atratores obtidos, são calculados através desses mapas. Nas simulações numéricas, observamos fenômenos não-lineares como crises, intermitências, transientes caóticos e coexistências de atratores e obtemos as bacias de atração dos atratores coexistentes. Ademais, mostramos como controlar comportamentos caóticos, a partir de um forçamento de amplitude pequena, e pelo método OGY (Ott, Grebogi e Yorke) de controle de caos. Finalmente, investigamos a dinâmica de um sistema não-ideal com impactos, que é composto pelo sistema de par de impactos sobreposto ao um sistema não ideal (para qual a ação da fonte de energia depende da oscilação do sistema). A partir de simulações numéricas, identificamos fenômenos não-lineares como crise interior, intermitência e coexistência de atratores. Associado à crise interior observamos um tipo de intermitência que leva o sistema a oscilar entre três atratores caóticos. Além dessa intermitência, observamos uma outra, que envolve dois atratores periódicos e um caótico. Além disso, mostramos as bacias de atração de dois atratores periódicos coexistentes. Essas bacias possuem uma característica de bacia crivada. / Initially, we analyze three ideal mechanical systems with impacts: an impact oscilator, an impact-pair, and a gear-box (gear-rattling). Between impacts, the motion is described by a linear differential equation. After each impact, we use the Newton law of impact to determine new initial conditions of an analytical solution. Due to impacts, the trajectories in phase space are discontinuous and described by a transcendental map. The Lyapunov exponents, important to characterize the attractors, are calculated from the transcendental map. In the numerical simulations, we observe nonlinear phenomena as crises, intermittency, chaotic behavior, and coexisting attractors. Moreover, we present the basins of attraction of the coexisting attractors. Furthermore, we show how to control the chaotic behavior, with a small perturbation and by the OGY (Ott, Grebogi, and Yorke) method. Finally, we investigate the dynamics of a non-ideal system with impacts, that is composed by an impact-pair system on a non-ideal system (in this system, the energy source actions depend on the system oscillations). From the numerical simulations, we identify nonlinear phenomena as interior crises, intermittency, for which the system oscillates among three chaotic attractors. Besides this intermittency, we observe another one. Associated to a chaotic and two periodic attractors. In addition, we show the riddle basins of attraction of the two coexisting periodic attractors.

(i) The thesis sets out to address the problematic phenomenon of Systems of Congestion via Basic Queueing Theory. The theory, and its application in practice, appears to be a field of study which is the common domain of “theorists” and “practitioners”. (ii) This professional dichotomy has come about due to diverging interests in that one group is mainly interested in the purity of mathematical modelling, and the other group is motivated to use modelling, which conveniently employs applications oriented solutions. (iii) The schism between the groups has been accentuated by the “practitioners” who in addition to having an interest in steady state system behaviour make use of methods of modelling of the transient operation of complex Systems of Congestion. (iv) At the outset the thesis demonstrates how closed form solutions are obtained for steady state and transient state operation of a selection of Systems of Congestion. The attendant mathematical derivations are elegant and intricate. (v) Having revealed the limited utility of closed-form solutions the thesis proceeds to investigate the feasibility of using dynamical systems theory to study the transient behaviour of complex Systems of Congestion. (vi) The creation of Chaos Theory in recent decades suggests that it may be employed as a useful tool in analysing Systems of Congestion. Iterative Chaos Theory methods of orbit generation for complete Systems of Congestion are therefore examined. The use of such orbit generation methods is found to be satisfactory for simple Systems of Congestion. More than a perfunctory knowledge of chaos mapping is however required. The simplicity of modelling is emphasized. (vii) Based on the results of benchmarking the creation of dynamic system orbits against an existing simulation method, the research advances to modelling of the transient operation of complex systems. Once again the iterative method of orbit generation displays the ease of modelling while simultaneously unfolding system dynamics graphically. (viii) One may hopefully contend that a tool of eminent utility has been developed to aid practitioners in studying and optimizing Systems of Congestion. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006. / Industrial and Systems Engineering / Unrestricted

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In 2016, over 47,000 youths in the state of Florida were served by the Department of Juvenile Justice (DJJ) probation services. While on probation, these youths were exposed to 2 different, and potentially conflicting disciplinary management systems. Youth are under the authority of juvenile probation officers (JPOs), who are bound to a consequence-based management approach. This approach is guided by negative reinforcement. The youths are simultaneously engaged with staff from diversion programs, many of which are strengths-based and guided by positive reinforcement. According to the ecosystemic complexity theory of conflict, exposure to incongruent systems can have negative effects such as confusion and ineffectiveness. By applying a hermeneutic phenomenological approach, I explored the responses to this convergence point from the perspective of 9 strengths-based school counseling staff members who supervise the youth that navigate between these 2 different behavior modification systems. This sample of 9 staff members also work directly with JPOs. Data were collected using iterative versions of semistructured interviews and analyzed using content analysis. Findings revealed that conflict did exist at the convergence point, and that cohesion, on varying levels, also existed, and that solutions to the philosophical incompatibility have emerged. This research contributes to social change by illuminating the possible conflict inherent in implementing incongruent approaches to behavior management, which may inform policymakers regarding program management for juvenile justice.

The dissertation deals with prediction of crude oil price and is tailor-made for such companies which are heavily crude oil related. The main dissertation target is to make sure that such companies can get ready for price changes and safeguard themselves against negative consequences. Crude oil prices are the main factor which affects prices of such final products as petrol. It is a well known fact that quantitative predictions are not reliable and all those who are forced to real on such vague data set for their decision-making are reluctant to use them. That’s how we would like to have at least the correct trend information. The dissertation introduces some concepts originally developed within artificial intelligence theory for the crude oil predictions. Specifically common sense algorithms and qualitative interpretation of some aspects of theory of chaos are the main contribution towards expanding of available prediction tools described by the dissertation. A systematic analysis of a sequence of qualitative solutions is the key part of the dissertation.

This thesis examines the utility of mathematical complexity measures for the analysis of stratospheric dynamics. Through theoretical considerations and tests with artificial data sets, e.g., the iteration of the logistic map, suitable parameters are determined for the application of the statistical entropy measures sample entropy (SE) and Rényi entropy (RE) to methane (a long-lived stratospheric tracer) data from simulations of the SOCOL chemistry-climate model. The SE is shown to be useful for quantifying the variability of recurring patterns in a time series and is able to identify tropical patterns similar to those reported by previous studies of the ``tropical pipe'' region. However, the SE is found to be unsuitable for use in polar regions, due to the non-stationarity of the methane data at extra-tropical latitudes. It is concluded that the SE cannot be used to analyse climate complexity on a global scale. The focus is turned to the RE, which is a complexity measure of probability distribution functions (PDFs). Using the second order RE and a normalisation factor, zonal PDFs of ten consecutive days of methane data are created with a Bayesian optimal binning technique. From these, the RE is calculated for every day (moving 10-day window). The results indicate that the RE is a promising tool for identifying stratospheric mixing barriers. In Southern Hemisphere winter and early spring, RE produces patterns similar to those found in other studies of stratospheric mixing. High values of RE are found to be indicative of the strong fluctuations in tracer distributions associated with relatively unmixed air in general, and with gradients in the vicinity of mixing barriers, in particular. Lower values suggest more thoroughly mixed air masses. The analysis is extended to eleven years of model data. Realistic inter-annual variability of some of the RE structures is observed, particularly in the Southern Hemisphere. By calculating a climatological mean of the RE for this period, additional mixing patterns are identified in the Northern Hemisphere. The validity of the RE analysis and its interpretation is underlined by showing that qualitatively similar patterns can be seen when using observational satellite data of a different tracer. Compared to previous techniques, the RE has the advantage that it requires significantly less computational effort, as it can be used to derive dynamical information from model or measurement tracer data without relying on any additional input such as wind fields. The results presented in this thesis strongly suggest that the RE is a useful new metric for analysing stratospheric mixing and its variability from climate model data. Furthermore, it is shown that the RE measure is very robust with respect to data gaps, which makes it ideal for application to observations. Hence, using the RE for comparing observations of tracer distributions with those from model simulations potentially presents a novel approach for analysing mixing in the stratosphere.