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Parallel computing has recently appeared has an alternative approach to increase computing performance. In the world of engineering and scientific computing the efficient use of parallel computers is dependent on the availability of methodologies capable of exploiting the new computing environment. The research presented here focused on a modeling approach, known as cellular automata (CA), which is characterized by a high degree of parallelism and is thus well suited to implementation on parallel processors. The inherent degree of parallelism also exhibited by the random-walk particle method provided a suitable basis for the development of a CA water quality model. The random-walk particle method was successfully represented using an approach based on CA. The CA approach requires the definition of transition rules, with each rule representing a water quality process. The basic water quality processes of interest in this research were advection, dispersion, and first-order decay. Due to the discrete nature of CA, the rule for advection introduces considerable numerical dispersion. However, the magnitude of this numerical dispersion can be minimized by proper selection of model parameters, namely the size of the cells and the time step. Similarly, the rule for dispersion is also affected by numerical dispersion. But, contrary to advection, a procedure was developed that eliminates significant numerical dispersion associated with the dispersion rule. For first-order decay a rule was derived which describes the decay process without the limitations of a similar approach previously reported in the literature. The rules developed for advection, dispersion, and decay, due to their independence, are well suited to implementation using a time-splitting approach. Through validation of the CA methodology as an integrated water quality model, the methodology was shown to adequately simulate one and two-dimensional, single and multiple constituent, steady state and transient, and spatially invariant and variant systems. The CA results show a good agreement with corresponding results for differential equation based models. The CA model was found to be simpler to understand and implement than the traditional numerical models. The CA model was easily implemented on a MIMD distributed memory parallel computer (Intel Paragon). However, poor performance was obtained. / Ph. D.

This thesis seeks two objectives. One objective is to develop a means to estimate time invariant real contact areas and surface temperatures through thermal measurements in 1D/2D systems. This allows computationally easier models, resulting in faster simulations within acceptable convergence. The second objective is to provide experimental design guidance. The methods used are a modified cellular automata technique for the direct model and a Levenberg-Marquardt parameter estimation technique to stabilize inverse solutions. The modified cellular automata technique enables each piece of physics to be solved independently over a short time step, thus frequently allowing analytical solutions to those pieces. Overall, the method was successful. The major results indicate that appropriately selected measurement locations can determine the contact distribution accurately, and that the preferred measurement location of the sensor is not very sensitive to the contact distribution specifics. This is useful because it allows selection of measurement locations regardless of the specifics of the generally unknown contact distribution. Further results show the combined effects of the normalized length and the Stanton number have a significant impact on the estimation quality, and can change the acceptable sensor domain, if the loss is high. The effect of placing the sensor in the static body can, for low loss, provide a coarse image of the contact distribution. This is useful because the static body is easier to instrument than a moving body. Finally, the estimation method worked well for the most complex model utilized, even in a sub-optimal measurement location. / Master of Science

This thesis presents a computationally efficient cryptosystem based on chaotic continuous-interval cellular automata (CCA). This cryptosystem increases data protection as demonstrated by its flexibility to encrypt/decrypt information from distinct sources (e.g., text, sound, and images). This cryptosystem has the following enhancements over the previous chaos-based cryptosystems: (i) a mathematical model based on a new chaotic CCA strange attractor, (ii) integration of modules containing dynamical systems to generate complex sequences, (iii) generation of an unlimited number of keys due to the features of chaotic phenomena obtained through CCA, which is an improvement over previous symmetric cryptosystems, and (iv) a high-quality concealment of the cryptosystem strange attractor. Instead of using differential equations, a process of mixing chaotic sequences obtained from CCA is also introduced. As compared to other recent approaches, this mixing process provides a basis to achieve higher security by using a higher degree of complexity for the encryption/decryption processes. This cryptosystem is tested through the following three methods: (i) a stationarity test based on the invariance of the first ten statistical moments, (ii) a polyscale test based on the variance fractal dimension trajectory (VFDT) and the spectral fractal dimension (SFD), and (iii) a surrogate data test. This cryptosystem secures data from distinct sources, while leaving no patterns in the ciphertexts. This cryptosystem is robust in terms of resisting attacks that: (i) identify a chaotic system in the time domain, (ii) reconstruct the chaotic attractor by monitoring the system state variables, (iii) search the system synchronization parameters, (iv) statistical cryptanalysis, and (v) polyscale cryptanalysis.

This thesis presents a computationally efficient cryptosystem based on chaotic continuous-interval cellular automata (CCA). This cryptosystem increases data protection as demonstrated by its flexibility to encrypt/decrypt information from distinct sources (e.g., text, sound, and images). This cryptosystem has the following enhancements over the previous chaos-based cryptosystems: (i) a mathematical model based on a new chaotic CCA strange attractor, (ii) integration of modules containing dynamical systems to generate complex sequences, (iii) generation of an unlimited number of keys due to the features of chaotic phenomena obtained through CCA, which is an improvement over previous symmetric cryptosystems, and (iv) a high-quality concealment of the cryptosystem strange attractor. Instead of using differential equations, a process of mixing chaotic sequences obtained from CCA is also introduced. As compared to other recent approaches, this mixing process provides a basis to achieve higher security by using a higher degree of complexity for the encryption/decryption processes. This cryptosystem is tested through the following three methods: (i) a stationarity test based on the invariance of the first ten statistical moments, (ii) a polyscale test based on the variance fractal dimension trajectory (VFDT) and the spectral fractal dimension (SFD), and (iii) a surrogate data test. This cryptosystem secures data from distinct sources, while leaving no patterns in the ciphertexts. This cryptosystem is robust in terms of resisting attacks that: (i) identify a chaotic system in the time domain, (ii) reconstruct the chaotic attractor by monitoring the system state variables, (iii) search the system synchronization parameters, (iv) statistical cryptanalysis, and (v) polyscale cryptanalysis.

Made available in DSpace on 2016-03-15T19:37:42Z (GMT). No. of bitstreams: 1 Eurico Luiz Prospero Ruivo.pdf: 15234351 bytes, checksum: 5a581041d50f5cbd30ccc684b8112487 (MD5) Previous issue date: 2012-12-11 / Universidade Presbiteriana Mackenzie / The Fourier spectra of cellular automata rules give a characterisation of the limit configurations generated by them at the end of their time evolution. In the present work, the Fourier spectra of each rule of the elementary cellular automata rule space are computed, under periodic and non-periodic boundary conditions, and the space is then partitioned according to the similarity among these computed spectra, what gives the notion of spectral classes in such space. For the partition obtained under periodic boundary condition, each spectral class is analysed in terms of the behaviour of each of its rules and how this behaviour affects the correspondent spectrum. Finally, the spectral classes are related in terms of the similarity among them, for both boundary conditions, what results in graphs depicting the proximity among the spectral classes. / Os espectros de Fourier de regras de autômatos celulares fornecem uma caracterização da configuração limite gerada por elas ao fim de suas evoluções temporais. Neste trabalho, são calculados os espectros de Fourier de todas as regras do espaço dos autômatos celulares elementares, sob condições de contorno periódica e não-periódicas, e o espaço é então particionado de acordo com a similaridade entre os espectros calculados, dando origem à noção de classes espectrais no espaço em questão. Para a participação gerada sob condição de contorno periódica, cada classe espectral é analisada de acordo com o comportamento de cada regra e a implicação deste no espectro obtido. A seguir é analisada a relação de similaridade entre as classes espectrais geradas em cada tipo de condição de contorno, o que d´a origem a grafos representando a proximidade entre as classes espectrais.