3 resultados para scientific programming

em DigitalCommons@University of Nebraska - Lincoln


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Normile reports on Japan's expanded scientific whaling program and notes that "Canada, the United States, the Soviet Union, South Africa, and Japan were among several countries that [conducted scientific whaling] before 1982 [the year the IWC passed the worldwide commercial moratorium on whaling], but in recent years Japan has stood alone." Although true, this statement omits three equally important points.

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The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa, area. Since 1992, the U.S. Geological Survey, in cooperation with the City of Cedar Rapids, has investigated the hydrogeology and water quality of the Cedar River alluvial aquifer. This report describes a detailed analysis of the ground-water flow system in the alluvial aquifer, particularly near well field areas. The ground-water flow system in the Cedar Rapids area consists of two main components, the unconsolidated Quaternary deposits and the underlying carbonate bedrock that has a variable fracture density. Quaternary deposits consist of eolian sand, loess, alluvium, and glacial till. Devonian and Silurian bedrock aquifers overlie the Maquoketa Shale (Formation) of Ordovician age, a regional confining unit. Ground-water and surface-water data were collected during the study to better define the hydrogeology of the Cedar River alluvial aquifer and Devonian and Silurian aquifers. Stream stage and discharge, ground-water levels, and estimates of aquifer hydraulic properties were used to develop a conceptual ground-water flow model and to construct and calibrate a model of the flow system. This model was used to quantify the movement of water between the various components of the alluvial aquifer flow system and provide an improved understanding of the hydrology of the alluvial aquifer.

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Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.