Metrics of monograph use in the Marston Science Library

As academic libraries are increasingly supported by a matrix of databases functions, the use of data mining and visualization techniques offer significant potential for future collection development and service initiatives based on quantifiable data. While data collection techniques are still not standardized and results may be skewed because of granularity problems, faulty algorithms, and a host of other factors, useful baseline data is extractable and broad trends can be identified. The purpose of the current study is to provide an initial assessment of data associated with science monograph collection at the Marston Science Library (MSL), University of Florida. These sciences fall within the major Library of Congress Classification schedules of Q, S, and T, excluding R, TN, TR, and TT. Overall strategy of this project is to look at the potential science audiences within the university community and analyze data related to purchasing and circulation patterns, e-book usage, and interlibrary loan statistics. While a longitudinal study from 2004 to the present would be ideal, this paper presents the results from the academic year July 1, 2008 to June 30, 2009 which was chosen as the pilot period because all data reservoirs identified above were available.

Extending Distance-based Ranking Models In Estimation of Distribution Algorithms

Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking models, such as Mallows and Generalized Mallows under the Kendall’s-t distance, have demonstrated their validity when solving this type of problems. Nevertheless, there are still many trends that deserve further study. In this paper, we extend the use of distance-based ranking models in the framework of EDAs by introducing new distance metrics such as Cayley and Ulam. In order to analyse the performance of the Mallows and Generalized Mallows EDAs under the Kendall, Cayley and Ulam distances, we run them on a benchmark of 120 instances from four well known permutation problems. The conducted experiments showed that there is not just one metric that performs the best in all the problems. However, the statistical test pointed out that Mallows-Ulam EDA is the most stable algorithm among the studied proposals.

Probability in Quantum Mechanics: The Everett Interpretation and the Decision-Theoretic Program

The Everett interpretation of quantum mechanics is an increasingly popular alternative to the traditional Copenhagen interpretation, but there are a few major issues that prevent the widespread adoption. One of these issues is the origin of probabilities in the Everett interpretation, which this thesis will attempt to survey. The most successful resolution of the probability problem thus far is the decision-theoretic program, which attempts to frame probabilities as outcomes of rational decision making. This marks a departure from orthodox interpretations of probabilities in the physical sciences, where probabilities are thought to be objective, stemming from symmetry considerations. This thesis will attempt to offer evaluations on the decision-theoretic program.