How far we are from the complete knowledge: Complexity of knowledge acquisition in Dempster-Shafer approach

When a knowledge base represents the experts' uncertainty, then it is reasonable to ask how far we are from the complete knowledge, that is, how many more questions do we have to ask (to these experts, to nature by means of experimenting, etc) in order to attain the complete knowledge. Of course, since we do not know what the real world is, we cannot get the precise number of questions from the very beginning: it is quite possible, for example, that we ask the right question first and thus guess the real state of the world after the first question. So we have to estimate this number and use this estimate as a natural measure of completeness for a given knowledge base. We give such estimates for Dempster-Shafer formalism. Namely, we show that this average number of questions can be obtained by solving a simple mathematical optimization problem. In principle this characteristic is not always sufficient to express the fact that sometimes we have more knowledge. For example, it has the same value if we have an event with two possible outcomes and nothing else is known, and if there is an additional knowledge that the probability of every outcome is 0.5. We'll show that from the practical viewpoint this is not a problem, because the difference between the necessary number of questions in both cases is practically negligible

Excess Credit and the South Korean Crisis

over-borrowing, South Korea, financial crisis

Statistical and thermal properties of mesoscopic systems: application to the many-nucleon system

The dissertation investigates the statistical and thermal properties of mesoscopic systems and applies it to the multi-nucleon systems. The investigation was carried out using four approaches starting from the simplest and progressing to the more sophisticated. The first approach develops and employs the three-dimensional simple harmonic oscillator (3D-SHO) quantum statistics to obtain the thermal properties of multi-particle systems. The recently discovered method that relates the single particle oscillator properties to the multi particle oscillator is applied. The approach is successful in predicting observables at temperatures beginning slightly above the ground state domain for nuclear systems. The 3D-SHO potential function is spherically symmetric because the value of the potential depends only on distance. Because of this high degree of symmetry, the states of the three-dimension SHO are highly degenerate. Accordingly, the 3D-SHO approach has a limited capability to address the intrashell excitations, which significantly limits the utility of the predicted level density of the system, especially at low excitation energies. To account more completely for the intrashell effect, a second approach is introduced. In this approach, the single particle states of a temperature-independent mean field Hamiltonian are generated. Those states are used as an input to generate thermally populated states of the desired multi-fermion system. The thermal population procedures are similar to those used with the single particle 3D-SHO. The approach involves an un-physical condensation of the fermions at the very low temperature range. Above this un-physical condensation region, however, the approach gives a good description for the nuclear level densities. Due to computational obstacles, the range of unphysical condensation temperature is undetermined for nuclei with mass number larger than 24 and this limits the application of the mean-field approach at the present time. In attempting to improve the fundamental concepts of the quantum statistics, Tsallis\u27 description for statistical mechanics, which introduces a new parameter, is investigated in some detail. We advance this theory by introducing the generalized-thermodynamic relations and expand the applications of the theory to include many fermion systems for a certain range of the new parameter in this approach. The additional parameter introduced by Tsallis suppresses the thermal response of the system at a given temperature. Ultimately, theory must derive this parameter from the Hamiltonian dynamics in order for the theory to have true predictive power. The last investigation employs the moment method to predict the nuclear level density from the Hamiltonian. This involves extracting the central moment of a fully microscopic no-core shell model Hamiltonian and using the Gram-Charlier expansion function to represent the level density of the system. The key advantage is that one can compute these moments without having to compute the full many-body spectra. The results are encouraging and imply that the no-core shell model can be used to predict nuclear level densities for heavy nuclei in larger model spaces, i.e. for situations beyond the conventional direct diagonalization techniques. A further improvement to the moment method using configuration moments approach is also investigated

Viral Quasispecies Reconstruction Using Next Generation Sequencing Reads

The genomic diversity of viral quasispecies is a subject of great interest, especially for chronic infections. Characterization of viral diversity can be addressed by high-throughput sequencing technology (454 Life Sciences, Illumina, SOLiD, Ion Torrent, etc.). Standard assembly software was originally designed for single genome assembly and cannot be used to assemble and estimate the frequency of closely related quasispecies sequences. This work focuses on parsimonious and maximum likelihood models for assembling viral quasispecies and estimating their frequencies from 454 sequencing data. Our methods have been applied to several RNA viruses (HCV, IBV) as well as DNA viruses (HBV), genotyped using 454 Life Sciences amplicon and shotgun methods

A GPU Implementation for Two-Dimensional Shallow Water Modeling

In this paper, we present a GPU implementation of a two-dimensional shallow water model. Water simulations are useful for modeling floods, river/reservoir behavior, and dam break scenarios. Our GPU implementation shows vast performance improvements over the original Fortran implementation. By taking advantage of the GPU, researchers and engineers will be able to study water systems more efficiently and in greater detail.Comment: 9 pages, 1 figur