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Full-Text Articles in Physical Sciences and Mathematics

Design And Implementation Of Interactive Tutorials For Data Structures, Ross Gore, Lewis Barnett Iii Nov 2002

Design And Implementation Of Interactive Tutorials For Data Structures, Ross Gore, Lewis Barnett Iii

Department of Math & Statistics Technical Report Series

The Tutorial Generation Toolkit (TGT) is a set of Java classes that supports authoring of interactive tutorial applications. This paper describes extensions to the capabilities of the TGT and several new tutorials aimed at the Data Structures course which were built using the toolkit.


A Comparison Of The Low Mode And Monte Carlo Conformational Search Methods, Carol A. Parish, Rosina Lombardi, Kent Sinclair, Emelyn Smith, Alla Goldberg, Melissa Rappleye, Myrianne Dure Oct 2002

A Comparison Of The Low Mode And Monte Carlo Conformational Search Methods, Carol A. Parish, Rosina Lombardi, Kent Sinclair, Emelyn Smith, Alla Goldberg, Melissa Rappleye, Myrianne Dure

Chemistry Faculty Publications

The Low Mode (LM) and Monte Carlo (MC) conformational search methods were compared on three diverse molecular systems; (4R, 5S, 6S, 7R)-hexahydro-5,6-dihydroxy-1,3,4,7-tetrakis(phenylmethyl)-2H-1,3-diazapin-2-one (1), 2-methoxy-2-phenyl-2-triflouromethyl-N-α-methyl benzyl propanamide (2) and a trimeric 39-membered polyazamacrolide (3). We find that either method, or a combination of the methods, is equally efficient at searching the conformational space of the smaller molecular systems while a 50:50 hybrid of Low Mode and Monte Carlo is most efficient at searching the space of the larger molecular system.


Advanced Portfolio Theory: Why Understanding The Math Matters, Tom Arnold Oct 2002

Advanced Portfolio Theory: Why Understanding The Math Matters, Tom Arnold

Finance Faculty Publications

The goal of this paper is to motivate the use of efficient set mathematics for portfolio analysis [as seen in Roll, 1977] in the classroom. Many treatments stop at the two asset portfolio case (avoiding the use of matrix algebra) and an alarming number of treatments rely on illustration and templates to provide a heuristic sense of the material without really teaching how efficient portfolios are generated. This is problematic considering that the benefits of understanding efficient set mathematics go beyond portfolio analysis and into such topics as regression analysis (as demonstrated here).


Electron Hopping Conductivity And Vapor Sensing Properties Of Flexible Network Polymer Films Of Metal Nanoparticles, Francis P. Zamborini, Michael C. Leopold, Jocelyn F. Hicks, Pawel J. Kulesza, Marcin A. Malik, Royce W. Murray Jun 2002

Electron Hopping Conductivity And Vapor Sensing Properties Of Flexible Network Polymer Films Of Metal Nanoparticles, Francis P. Zamborini, Michael C. Leopold, Jocelyn F. Hicks, Pawel J. Kulesza, Marcin A. Malik, Royce W. Murray

Chemistry Faculty Publications

Films of monolayer protected Au clusters (MPCs) with mixed alkanethiolate and ω-carboxylate alkanethiolate monolayers, linked together in a network polymer by carboxylate-Cu2+-carboxylate bridges, exhibit electronic conductivities (σEL) that vary with both the numbers of methylene segments in the ligands and the bathing medium (N2, liquid or vapor). A chainlength-dependent swelling/contraction of the film's internal structure is shown to account for changes in σEL. The linker chains appear to have sufficient flexibility to collapse and fold with varied degrees of film swelling or dryness. Conductivity is most influenced (exponentially dependent) by the chainlength of the nonlinker (alkanethiolate) ligands, a result consistent …


Self-Similarity In Network Traffic, Francisco Chinchilla Apr 2002

Self-Similarity In Network Traffic, Francisco Chinchilla

Honors Theses

It is critical to properly understand the nature of network traffic in order to effectively design models describing network behavior. These models are usually used to simulate network traffic, which in turn are used to construct congestion control techniques, perform capacity planning studies, and/or evaluate the behavior of new protocols. Using the wrong models could lead to potentially serious problems such as delayed packet transmissions or an increase in packet drop rates.

Traditionally, packet arrivals were assumed to follow a Poisson arrival process. Although Poisson processes have several properties that make them easy to work with, they do not accurately …


Discrete Predictive Analysis In Probabilistic Safety Assessment, Paul Kvam, J. Glenn Miller Jan 2002

Discrete Predictive Analysis In Probabilistic Safety Assessment, Paul Kvam, J. Glenn Miller

Department of Math & Statistics Faculty Publications

This paper presents methods for predicting future numbers of component failures for probabilistic safety assessments (PSAs). The research is motivated and illustrated by discrete failure data from the nuclear industry, including failure counts for emergency diesel generators, pumps, and motor operated valves. Failure counts are modeled with Poisson and binomial distributions. Multiple-failure environments create extra problems for predictive inference, and are a primary focus of this paper. Common cause failures (CCFs), in particular, refer to the simultaneous failure of system components due to an external event. CCF prediction is investigated, and approximate inference methods are derived for various CCF models.


Nonparametric Estimation Of A Distribution Subject To A Stochastic Precedence Constraint, Miguel A. Arcones, Paul H. Kvam, Francisco J. Samaniego Jan 2002

Nonparametric Estimation Of A Distribution Subject To A Stochastic Precedence Constraint, Miguel A. Arcones, Paul H. Kvam, Francisco J. Samaniego

Department of Math & Statistics Faculty Publications

For any two random variables X and Y with distributions F and G defined on [0,∞), X is said to stochastically precede Y if P(XY) ≥ 1/2. For independent X and Y, stochastic precedence (denoted by XspY) is equivalent to E[G(X–)] ≤ 1/2. The applicability of stochastic precedence in various statistical contexts, including reliability modeling, tests for distributional equality versus various alternatives, and the relative performance of comparable tolerance bounds, is discussed. The problem of estimating the underlying distribution(s) of experimental data under the assumption that they obey a …


Common Cause Failure Prediction Using Data Mapping, Paul H. Kvam, J. Glenn Miller Jan 2002

Common Cause Failure Prediction Using Data Mapping, Paul H. Kvam, J. Glenn Miller

Department of Math & Statistics Faculty Publications

To estimate power plant reliability, a probabilistic safety assessment might combine failure data from various sites. Because dependent failures are a critical concern in the nuclear industry, combining failure data from component groups of different sizes is a challenging problem. One procedure, called data mapping, translates failure data across component group sizes. This includes common cause failures, which are simultaneous failure events of two or more components in a group. In this paper, we present methods for predicting future plant reliability using mapped common cause failure data. The prediction technique is motivated by discrete failure data from emergency diesel generators …


[Introduction To] Generalized Analytic Continuation, William T. Ross, Harold S. Shapiro Jan 2002

[Introduction To] Generalized Analytic Continuation, William T. Ross, Harold S. Shapiro

Bookshelf

The theory of generalized analytic continuation studies continuations of meromorphic functions in situations where traditional theory says there is a natural boundary. This broader theory touches on a remarkable array of topics in classical analysis, as described in the book. This book addresses the following questions: (1) When can we say, in some reasonable way, that component functions of a meromorphic function on a disconnected domain, are "continuations" of each other? (2) What role do such "continuations" play in certain aspects of approximation theory and operator theory? The authors use the strong analogy with the summability of divergent series …


[Introduction To] Data Structures With Java: A Laboratory Approach, Joe Kent, Lewis Barnett Iii Jan 2002

[Introduction To] Data Structures With Java: A Laboratory Approach, Joe Kent, Lewis Barnett Iii

Bookshelf

This book is designed to present the key topics in the second course for computer science students using the Java programming language. For convenience, we cover exceptions and file operations in Java, although this may have been covered in the first course. We also cover material on the binary representation of data and Java's bitwise operations, with applications.These are topics needed for computer organization an operating systems courses.