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Articles 1 - 7 of 7
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Design And Implementation Of Interactive Tutorials For Data Structures, Ross Gore, Lewis Barnett Iii
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.
Advanced Portfolio Theory: Why Understanding The Math Matters, Tom Arnold
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).
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
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.
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
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 …
Discrete Predictive Analysis In Probabilistic Safety Assessment, Paul Kvam, J. Glenn Miller
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.
Common Cause Failure Prediction Using Data Mapping, Paul H. Kvam, J. Glenn Miller
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 …
Nonparametric Estimation Of A Distribution Subject To A Stochastic Precedence Constraint, Miguel A. Arcones, Paul H. Kvam, Francisco J. Samaniego
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(X≤Y) ≥ 1/2. For independent X and Y, stochastic precedence (denoted by X≤spY) 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 …