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Active Tile Self-assembly and Simulations of Computational SystemsKarpenko, Daria 01 April 2015 (has links)
Algorithmic self-assembly has been an active area of research at the intersection of computer science, chemistry, and mathematics for almost two decades now, motivated by the natural self-assembly mechanism found in DNA and driven by the desire for precise control of nanoscale material manufacture and for the development of nanocomputing and nanorobotics. At the theoretical core of this research is the Abstract Tile Assembly Model (aTAM), the original abstract model of DNA tile self-assembly. Recent advancements in DNA nanotechnology have been made in developing strand displacement mechanisms that could allow DNA tiles to modify themselves during the assembly process by opening or closing certain binding sites, introducing new dynamics into tile self-assembly.
We focus on one way of incorporating such signaling mechanisms for binding site activation and deactivation into the theoretical model of tile self-assembly by extending the aTAM to create the Active aTAM. We give appropriate definitions first for incorporating activation signals and then for incorporating deactivation signals and tile detachment into the aTAM. We then give a comparison of Active aTAM to related models, such as the STAM, and take a look at some theoretical results.
The goal of the work presented here is to define and demonstrate the power of the Active aTAM with and without deactivation. To this end, we provide four constructions of temperature 1 (also known as "non-cooperative") active tile assembly systems that can simulate other computational systems. The first construction concerns the simulation of an arbitrary temperature 2 (also known as "cooperative") standard aTAM system in the sense of producing equivalent structures with a scaling factor of 2 in each dimension; the second construction generates the time history of a given 1D cellular automaton. The third and fourth constructions make use of tile detachment in order to dynamically simulate arbitrary 1D and 2D cellular automata with assemblies that record only the current state updates and not the entire computational history of the specified automaton.
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Computational Explorations of Creativity and Innovation in DesignSosa Medina, Ricardo January 2005 (has links)
This thesis addresses creativity in design as a property of systems rather than an attribute of isolated individuals. It focuses on the dynamics between generative and evaluative or ascriptive processes. This is in distinction to conventional approaches to the study of creativity which tend to concentrate on the isolated characteristics of person, process and product. Whilst previous research has advanced insights on potentially creative behaviour and on the general dynamics of innovation in groups, little is known about their interaction. A systems view of creativity in design is adopted in our work to broaden the focus of inquiry to incorporate the link between individual and collective change. The work presented in this thesis investigates the relation between creativity and innovation in computational models of design as a social construct. The aim is to define and implement in computer simulations the different actors and components of a system and the rules that may determine their behaviour and interaction. This allows the systematic study of their likely characteristics and effects when the system is run over simulated time. By manipulating the experimental variables of the system at initial time the experimenter is able to extract patterns from the observed results over time and build an understanding of the different types of determinants of creative design. The experiments and findings presented in this thesis relate to artificial societies composed by software agents and the social structures that emerge from their interaction. Inasmuch as these systems aim to capture some aspects of design activity, understanding them is likely to contribute to the understanding of the target system. The first part of this thesis formulates a series of initial computational explorations on cellular automata of social influence and change agency. This simple modelling framework illustrates a number of factors that facilitate change. The potential for a designer to trigger cycles of collective change is demonstrated to depend on the combination of individual and external or situational characteristics. A more comprehensive simulation framework is then introduced to explore the link between designers and their societies based on a systems model of creativity that includes social and epistemological components. In this framework a number of independent variables are set for experimentation including characteristics of individuals, fields, and domains. The effects of these individual and situational parameters are observed in experimental settings. Aspects of relevance in the definition of creativity included in these studies comprise the role of opinion leaders as gatekeepers of the domain, the effects of social organisation, the consequences of public and private access to domain knowledge by designers, and the relation between imitative behaviour and innovation. A number of factors in a social system are identified that contribute to the emergence of phenomena that are normally associated to creativity and innovation in design. At the individual level the role of differences of abilities, persistence, opportunities, imitative behaviour, peer influence, and design strategies are discussed. At the field level determinants under inspection include group structure, social mobility and organisation, emergence of opinion leaders, established rules and norms, and distribution of adoption and quality assessments. Lastly, domain aspects that influence the interaction between designers and their social groups include the generation and access to knowledge, activities of gatekeeping, domain size and distribution, and artefact structure and representation. These insights are discussed in view of current findings and relevant modelling approaches in the literature. Whilst a number of assumptions and results are validated, others contribute to ongoing debates and suggest specific mechanisms and parameters for future experimentation. The thesis concludes by characterising this approach to the study of creativity in design as an alternative �in silico� method of inquiry that enables simulation with phenomena not amenable to direct manipulation. Lines of development for future work are advanced which promise to contribute to the experimental study of the social dimensions of design.
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Ergodicity of PCA : equivalence between spatial and temporal mixing conditionsLouis, Pierre-Yves January 2004 (has links)
For a general attractive Probabilistic Cellular Automata on S-Zd, we prove that the (time-) convergence towards equilibrium of this Markovian parallel dynamics, exponentially fast in the uniform norm, is equivalent to a condition (A). This condition means the exponential decay of the influence from the boundary for the invariant measures of the system restricted to finite boxes. For a class of reversible PCA dynamics on {1,+1}(Zd), wit a naturally associated Gibbsian potential rho, we prove that a (spatial-) weak mixing condition (WM) for rho implies the validity of the assumption (A); thus exponential (time-) ergodicity of these dynamics towards the unique Gibbs measure associated to rho hods. On some particular examples we state that exponential ergodicity holds as soon as there is no phase transition.
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EVOLUTIONARY SKETCHESCho, Youngmi January 2011 (has links)
<p>EVOLUTIONARY SKETCHES is a three-movement sextet composition for flute, clarinet in Bb, percussion, piano, viola, and cello. The idea of the piece is based on the study of applying scientific evolutionary theories to compositional techniques. The first movement reflects my attempt to realize the generic process of development from one generation to the next by natural selection, crossover, or mutation. In the second movement, I conceive an image of evolution in which changes take place through battles among different evolutionary factors over progress. The structure of the third movement explores the extensive use of cellular automata.</p> / Dissertation
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Analysis And Predictions Of DNA Sequence Transformations On GridsJoshi, Yadnyesh R 08 1900 (has links)
Phylogenetics is the study of evolution of organisms. Evolution occurs due to mutations of DNA sequences. The reasons behind these seemingly random mutations are largely unknown. There are many algorithms that build phylogenetic trees from DNA sequences. However, there are certain uncertainties associated with these phylogenetic trees. Fine level analysis of these phylogenetic trees is both important and interesting for evolutionary biologists. In this thesis, we try to model evolutions of DNA sequences using Cellular Automata and resolve the uncertainties associated with the phylogenetic trees. In particular, we determine the effect of neighboring DNA base-pairs on the mutation of a base-pair. Cellular Automata can be viewed as an array of cells which modifies itself in discrete time-steps according to a governing rule. The state of the cell at the next time-step depends on its current state and state of its neighbors. We have used cellular automata rules for analysis and predictions of DNA sequence transformations on Computational grids.
In the first part of the thesis, DNA sequence evolution is modeled as a cellular automaton with each cell having one of the four possible states, corresponding to four bases. Phylogenetic trees are explored in order to find out the cellular automata rules that may have guided the evolutions. Master-client paradigm is used to exploit the parallelism in the sequence transformation analysis. Load balancing and fault-tolerance techniques are developed to enable the execution of the explorations on grid resources. The analysis of the sequence transformations is used to resolve uncertainties associated with the phylogenetic trees namely, intermediate sequences in the phylogenetic tree and the exact number of time-steps required for the evolution of a branch. The model is further used to find out various statistics such as most popular rules at a particular time-step in the evolution history of a branch in a phylogenetic tree. We have observed some interesting statistics regarding the unknown base pairs in the intermediate sequences of the phylogenetic tree and the most popular rules used for sequence transformations.
Next part of the thesis deals with predictions of future sequences using the previous sequences. First, we try to find out the preserved sequences so that cellular automata rules can be applied selectively. Then, random strategies are developed as base benchmarks. Roulette Wheel strategy is used for predicting future DNA sequences. Though the prediction strategies are able to better the random benchmarks in most of the cases, average performance improvement over the random strategies is not significant. The possible reasons are discussed.
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Artificial intelligence solutions for models of dynamic land use changeWu, Ning January 2012 (has links)
No description available.
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Nanolithography on H:Si(100)-(2 x 1) using combined Scanning Tunneling Microscopy and Field Ion Microscopy techniquesVesa, Cristian Unknown Date
No description available.
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Numerical Simulation and Experimental Study of Transient Liquid Phase Bonding of Single Crystal SuperalloysGhoneim, Adam 07 October 2011 (has links)
The primary goals of the research in this dissertation are to perform a systematic study to identify and understand the fundamental cause of prolonged processing time during transient liquid phase bonding of difficult-to-bond single crystal Ni-base materials, and use the acquired knowledge to develop an effective way to reduce the isothermal solidification time without sacrificing the single crystalline nature of the base materials. To achieve these objectives, a multi-scale numerical modeling approach, that involves the use of a 2-D fully implicit moving-mesh Finite Element method and a Cellular Automata method, was developed to theoretically investigate the cause of long isothermal solidification times and determine a viable way to minimize the problem. Subsequently, the predictions of the theoretical models are experimentally validated.
Contrary to previous suggestions, numerical calculations and experimental verifications have shown that enhanced intergranular diffusivity has a negligible effect on solidification time in cast superalloys and that another important factor must be responsible. In addition, it was found that the concept of competition between solute diffusivity and solubility as predicted by standard analytical TLP bonding models and reported in the literature as a possible cause of long solidification times is not suitable to explain salient experimental observations. In contrast, however, this study shows that the problem of long solidification times, which anomalously increase with temperature is fundamentally caused by departure from diffusion controlled parabolic migration of the liquid-solid interface with holding time during bonding due to a significant reduction in the solute concentration gradient in the base material.
Theoretical analyses showed it is possible to minimize the solidification time and prevent formation of stray-grains in joints between single crystal substrates by using a composite powder mixture of brazing alloy and base alloy as the interlayer material, which prior to the present work has been reported to be unsuitable. This was experimentally verified and the use of the composite powder mixture as interlayer material to reduce the solidification time and avoid stray-grain formation during TLP bonding of single crystal superalloys has been reported for the first time in this research.
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Numerical Simulation and Experimental Study of Transient Liquid Phase Bonding of Single Crystal SuperalloysGhoneim, Adam 07 October 2011 (has links)
The primary goals of the research in this dissertation are to perform a systematic study to identify and understand the fundamental cause of prolonged processing time during transient liquid phase bonding of difficult-to-bond single crystal Ni-base materials, and use the acquired knowledge to develop an effective way to reduce the isothermal solidification time without sacrificing the single crystalline nature of the base materials. To achieve these objectives, a multi-scale numerical modeling approach, that involves the use of a 2-D fully implicit moving-mesh Finite Element method and a Cellular Automata method, was developed to theoretically investigate the cause of long isothermal solidification times and determine a viable way to minimize the problem. Subsequently, the predictions of the theoretical models are experimentally validated.
Contrary to previous suggestions, numerical calculations and experimental verifications have shown that enhanced intergranular diffusivity has a negligible effect on solidification time in cast superalloys and that another important factor must be responsible. In addition, it was found that the concept of competition between solute diffusivity and solubility as predicted by standard analytical TLP bonding models and reported in the literature as a possible cause of long solidification times is not suitable to explain salient experimental observations. In contrast, however, this study shows that the problem of long solidification times, which anomalously increase with temperature is fundamentally caused by departure from diffusion controlled parabolic migration of the liquid-solid interface with holding time during bonding due to a significant reduction in the solute concentration gradient in the base material.
Theoretical analyses showed it is possible to minimize the solidification time and prevent formation of stray-grains in joints between single crystal substrates by using a composite powder mixture of brazing alloy and base alloy as the interlayer material, which prior to the present work has been reported to be unsuitable. This was experimentally verified and the use of the composite powder mixture as interlayer material to reduce the solidification time and avoid stray-grain formation during TLP bonding of single crystal superalloys has been reported for the first time in this research.
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Lattice Boltzmann Automaton Model To Simulate Fluid Flow In Synthetic FracturesEker, Erdinc 01 January 2005 (has links) (PDF)
Modeling of flow in porous and fractured media is a very important problem in reservoir engineering. As for numerical simulations conventional Navier-Stokes codes are applied to flow in both porous and fractured media. But they have long computation times, poor convergence and problems of numerical instabilities. Therefore, it is desired to develop another computational method that is more efficient and use simple rules to represent the flow in fractured media rather than partial differential equations. In this thesis Lattice Boltzmann Automaton Model will be used to represent the single phase fluid flow in two dimensional synthetic fractures and the simulation results obtained from this model are used to train Artificial Neural Networks. It has been found that as the mean aperture-fractal dimension ratio increases permeability increases. Moreover as the anisotropy factor increases permeability decreases with a second order polynomial relationship.
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