Fertilized frog eggs (and cell-free extracts) undergo periodic oscillations in the activity of "M-phase promoting factor" (MPF), the crucial triggering enzyme for mitosis (nuclear division) and cell division. MPF activity is regulated by a complex network of biochemical reactions. Novak and Tyson, and their collaborators, have been studying the qualitative and quantitative properties of a large system of nonlinear ordinary differential equations that describe the molecular details of this system as currently known. Important clues to the behavior of the model are provided by bifurcation theory, especially characterization of the codimension-1 and -2 bifurcation sets of the differential equations. To illustrate this method, I have been studying a system of 9 ordinary differential equations that describe the frog egg cell cycle with some fidelity. I will describe the bifurcation diagram of this system in a parameter space spanned by the rate constants for cyclin synthesis and cycling degradation. My results suggest either that the cell cycle control system should show dynamical behavior considerably more complex than the limit cycles and steady states reported so far, or that the biochemical rate constants of the system are constrained to avoid regions of parameter space where complex bifurcation points unfold. / Ph. D.

Os principais resultados originais relatados ao longo desse texto provêm de observações em experimentos numéricos, entretanto, na maioria dos casos, os resultados são fundamentados com instrumentos teóricos ou com modelos heurísticos. Inicialmente, introduzimos, nas equações que descrevem osciladores caóticos, uma pequena perturbação periódica a fim de observar no espaço de parâmetros a porção de parâmetros cujo comportamento caótico é extinto. Assim, constatamos que o conjunto de parâmetros correspondentes às orbitas caóticas extintas correspondem à replicas de janelas periódicas complexas previamente existentes no sistema não-perturbado. Posteriormente, utilizando as propriedades de torsão do espaço de estados dos osciladores caóticos, visualizamos transições existentes no interior das janelas periódicas complexas. Quando consideramos sequências dessas janelas sob a ótica da torsão do espaço de estados, observamos a existência de regras que relacionam janelas consecutivas ao longo dessa sequência. Adicionalmente, no espaço de parâmetros de osciladores caóticos e sistemas dinâmicos adicionais, fizemos uma estimativa da dimensão da fronteira entre o conjunto de parâmetros que leva às soluções periódicas e o conjunto que leva aos atratores caóticos. Para os sistemas investigados, os valores obtidos para essa dimensão estão no mesmo intervalo de confiança, indicando que essa dimensão é universal. / The main results reported along this text come from observations in numerical experiments, however, in most cases, results are explained by theoretical instruments or heuristic models. Initially we introduced in the equations that describe chaotic oscillators, a small periodic perturbation to observe, in the parameter space, the portion of parameters whose chaotic behavior is extinguished. Thus, we find that the set of parameters corresponding to the extinct chaotic orbits correspond to replicas of previously complex periodic windows existing in the unperturbed system. Subsequently, using the torsion properties of state spaces of chaotic oscillators, we visualize transitions within the complex periodic windows. When we consider sequences of these windows from the perspective of torsion properties of the state space, we observe the existence of rules that relate consecutive windows along these sequences. Additionally, in the parameter space of chaotic oscillators and additional dynamical systems, we estimate the dimension of the boundary between the set of parameters that leads to periodic solutions and the set that leads to chaotic attractors. For the systems considered here, the values for this dimension are in the same confidence interval, indicating that this dimension is universal.

This report describes a program which automatically characterizes the behavior of any driven, nonlinear, electrical circuit. To do this, the program autonomously selects interesting input parameters, drives the circuit, measures its response, performs a set of numeric computations on the measured data, interprets the results, and decomposes the circuit's parameter space into regions of qualitatively distinct behavior. The output is a two-dimensional portrait summarizing the high-level, qualitative behavior of the circuit for every point in the graph, an accompanying textual explanation describing any interesting patterns observed in the diagram, and a symbolic description of the circuit's behavior which can be passed on to other programs for further analysis.

Os principais resultados originais relatados ao longo desse texto provêm de observações em experimentos numéricos, entretanto, na maioria dos casos, os resultados são fundamentados com instrumentos teóricos ou com modelos heurísticos. Inicialmente, introduzimos, nas equações que descrevem osciladores caóticos, uma pequena perturbação periódica a fim de observar no espaço de parâmetros a porção de parâmetros cujo comportamento caótico é extinto. Assim, constatamos que o conjunto de parâmetros correspondentes às orbitas caóticas extintas correspondem à replicas de janelas periódicas complexas previamente existentes no sistema não-perturbado. Posteriormente, utilizando as propriedades de torsão do espaço de estados dos osciladores caóticos, visualizamos transições existentes no interior das janelas periódicas complexas. Quando consideramos sequências dessas janelas sob a ótica da torsão do espaço de estados, observamos a existência de regras que relacionam janelas consecutivas ao longo dessa sequência. Adicionalmente, no espaço de parâmetros de osciladores caóticos e sistemas dinâmicos adicionais, fizemos uma estimativa da dimensão da fronteira entre o conjunto de parâmetros que leva às soluções periódicas e o conjunto que leva aos atratores caóticos. Para os sistemas investigados, os valores obtidos para essa dimensão estão no mesmo intervalo de confiança, indicando que essa dimensão é universal. / The main results reported along this text come from observations in numerical experiments, however, in most cases, results are explained by theoretical instruments or heuristic models. Initially we introduced in the equations that describe chaotic oscillators, a small periodic perturbation to observe, in the parameter space, the portion of parameters whose chaotic behavior is extinguished. Thus, we find that the set of parameters corresponding to the extinct chaotic orbits correspond to replicas of previously complex periodic windows existing in the unperturbed system. Subsequently, using the torsion properties of state spaces of chaotic oscillators, we visualize transitions within the complex periodic windows. When we consider sequences of these windows from the perspective of torsion properties of the state space, we observe the existence of rules that relate consecutive windows along these sequences. Additionally, in the parameter space of chaotic oscillators and additional dynamical systems, we estimate the dimension of the boundary between the set of parameters that leads to periodic solutions and the set that leads to chaotic attractors. For the systems considered here, the values for this dimension are in the same confidence interval, indicating that this dimension is universal.

When modeling a neuron, modelers often focus on the values of parameters that produce a desired output. However, if these parameters are not unique, there could be a number of parameter sets that produce the same output. Thus, even though the values of the various maximum conductances, half activation voltages and so on differ, as a set they can produce the same spike height, firing rates, and so forth. To examine whether or not parameter sets are unique, a 3-compartment motoneuron model was created that has 15 target outputs and 59 parameters. Using parameter searches, over one hundred parameter sets were created for this model that produced the same output (within tolerances). Parameter values vary between parameter sets and indicate that the parameter values are not unique. In addition, some parameters are more tightly constrained than others. Principal component analysis is used to examine the dimensionality of the input and output spaces. However, neurons are more than static output generators. For example, a variety of neuromodulatory influences are known to shift parameter values to alter neuronal output. Thus the question arises as to whether this non-uniqueness extends from model outputs to the models sensitivities to its parameters. In this work, the non-unique parameter sets are further analyzed using sensitivity analyses and output correlations to show that these values vary significantly between these parameter sets. Therefore, each of these models will react to parameter variation differently. This work concludes that parameter sets are non-unique but have varying sensitivity analyses and output correlations. The ramifications of this are discussed for both modelers and neuroscientists.

Made available in DSpace on 2016-12-12T20:15:48Z (GMT). No. of bitstreams: 1 capa_ate_sumario.pdf: 940719 bytes, checksum: 34845651ded8147831931a5314e46c27 (MD5) Previous issue date: 2012-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this work, we numerically studied a four-dimensional Chua circuit model through bifurcation diagrams and parameter spaces. Our main objective here is to ex-tend the studies already realized in this system, showing a wider range of its behavior. For this purpose, we constructed the parameter spaces using the Lyapunov exponents spectrum through color scales, varying simultaneously two parameters of the system. With this procedure it was possible to discover where are the chaotic regions, the pe-riodic ones and the fixed points for the set of parameters. / Este trabalho tem como foco principal estudar, por métodos numéricos, um circuito eletrônico de Chua composto de quatro equações diferenciais através de diagramas de bifurcação e espaços de parâmetros. Nossa proposta aqui é ampliar os estudos numéricos já realizados neste sistema, revelando uma gama maior do seu comportamento. Para isso, realizamos construções dos espaços de parâmetros nos quais apresentam os valores dos expoentes de Lyapunov através de escalas coloridas, mediante a variação de dois parâmetros que compõem o circuito eletrônico. Com este procedimento é possível descobrir onde existem regiões caóticas, periódicas e pontos fixos para o conjunto de parâmetros do sistema.

Made available in DSpace on 2016-12-12T20:15:48Z (GMT). No. of bitstreams: 1 Introducao.pdf: 113158 bytes, checksum: b51f1d71911c67cb5ee9a76e2f64e8be (MD5) Previous issue date: 2012-03-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this work we studied the dynamical behavior of driven oscillators on the parameter spaces. To characterize the behavior on parameter spaces, we use two numerical methods: one to calculate the most positive Lyapunov exponent and one to calculate the spectrum of the exponents. The dynamical systems studied in this work are: three complex driven oscillators and a four-dimensional Chua circuit. With the help of the parameter spaces, it was possible to observe various dynamical behaviors of the systems. We also use others techniques, as bifurcation diagrams and trajectories on phase space (attractors) to characterize the systems dynamics. However, between the two numerical methods used, the best one was that calculate the Lyapunov exponent spectrum, because it is possible to construct the parameter spaces for the .rst and the second largest Lyapunov exponent. / Nesta dissertação estudamos a dinâmica dos osciladores forçados, via estudo do espaço (plano) de parâmetros. Para caracterizar o comportamento no espaço de parâmetros, usamos dois métodos: um que calcula somente o maior expoente de Lyapunov e o outro que calcula o espectro de Lyapunov. Os sistemas estudados nessa dissertação são: três osciladores complexos forçados e um circuito de Chua forçado no espaço quadridimensional. Com a construção dos espaços de parâmetros, foi possível observar diversos comportamentos dinâmicos. Usamos também, outras técnicas conhecidas, como a construção de diagramas de bifurcação e trajetórias no espaço de fase, para caracterizar a dinâmica dos sistemas. Porém, o método que apresentou mais recursos para caracterizar a dinâmica de um sistema, foi o que calcula o espectro de Lyapunov, pois, a partir daí, é possível construir os espaços de parâmetros para o primeiro e para o segundo maiores expoentes de Lyapunov.

Context An influence map and potential fields are used for finding path in domain of Robotics and Gaming in AI. Various distance measures can be used to find influence maps and potential fields. However, these distance measures have not been compared yet. ObjectivesIn this paper, we have proposed a new algorithm suitable to find an optimal point in parameters space from random parameter spaces. Finally, comparisons are made among three popular distance measures to find the most efficient. Methodology For our RQ1 and RQ2, we have implemented a mix of qualitative and quantitative approach and for RQ3, we have used quantitative approach. Results A* distance measure in influence maps is more efficient compared to Euclidean and Manhattan in potential fields. Conclusions Our proposed algorithm is suitable to find optimal point and explores huge parameter space. A* distance in influence maps is highly efficient compared to Euclidean and Manhattan distance in potentials fields. Euclidean and Manhattan distance performed relatively similar whereas A* distance performed better than them in terms of score in Ms. Pac-Man (See Appendix A).

Objective: Particular testing by functional decomposition of the automated driving function can potentially contribute to reducing the effort of validating highly automated driving functions. In this study, the required size of test suites for scenario-based testing and the potential to reduce it by functional decomposition are quantified for the first time. Methods: The required size of test suites for scenario-based approval of a so-called Autobahn-Chauffeur (SAE Level 3) is analyzed for an exemplary set of scenarios. Based on studies of data from failure analyses in other domains, the possible range for the required test coverage is narrowed down and suitable discretization steps, as well as ranges for the influence parameters, are assumed. Based on those assumptions, the size of the test suites for testing the complete system is quantified. The effects that lead to a reduction in the parameter space for particular testing of the decomposed driving function are analyzed and the potential to reduce the validation effort is estimated by comparing the resulting test suite sizes for both methods. Results: The combination of all effects leads to a reduction in the test suites’ size by a factor between 20 and 130, depending on the required test coverage. This means that the size of the required test suite can be reduced by 95–99% by particular testing compared to scenario-based testing of the complete system. Conclusions: The reduction potential is a valuable contribution to overcome the parameter space explosion during the validation of highly automated driving. However, this study is based on assumptions and only a small set of exemplary scenarios. Thus, the findings have to be validated in further studies.

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