995 resultados para Resolution algorithm


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An unsigned, undated draft of a resolution by Mechanics in the Kingston, Ont. area responding to the availability of cheap convict labour. The resolution proposes to shift convict labour to the Marmora, Ont. iron fields.

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The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

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14th Congress, 1st session, 1815-1816. House. Document no. 33. January 27, 1816. Read and referred to the Committee on Military Affairs.

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Full Title: 47. Message from the President of the United States, transmitting a report of the Secretary of State, in obedience to a resolution of the thirteenth inst. "requesting the President to lay before this House such documents relative to the Russian mediation as in his opinion it may not be improper to communicate." United States,13th Congress, 2d session, 1813-1814. House. Doc. no. 35. January 18, 1814. Ordered to lie on the table. One letter in French with English translation Printed by Roger C. Weightman

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This thesis introduces the Salmon Algorithm, a search meta-heuristic which can be used for a variety of combinatorial optimization problems. This algorithm is loosely based on the path finding behaviour of salmon swimming upstream to spawn. There are a number of tunable parameters in the algorithm, so experiments were conducted to find the optimum parameter settings for different search spaces. The algorithm was tested on one instance of the Traveling Salesman Problem and found to have superior performance to an Ant Colony Algorithm and a Genetic Algorithm. It was then tested on three coding theory problems - optimal edit codes, optimal Hamming distance codes, and optimal covering codes. The algorithm produced improvements on the best known values for five of six of the test cases using edit codes. It matched the best known results on four out of seven of the Hamming codes as well as three out of three of the covering codes. The results suggest the Salmon Algorithm is competitive with established guided random search techniques, and may be superior in some search spaces.