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A relational database for the c.elegans nematode
Andrea Adams

ABSTRACT: Bioinformatics is a field in which computer systems are used to process experimental data from biological experiments. Working with members of the Biology department, I have constructed a relational database system to aid them in processing the data from an experiment involving the results on genes expressed in neurons and mitochondria in the nemetode c.elegans when it is raised in an environment devoid of oxygen. To accomplish this, I mined data from the existing SAGE and Mitores databases to construct two relational databases: one detailing all of the genes expressed in neurons, and the other detailing the genes expressed in mitochondria. Then, once experimental data has been loaded into the database, the biologists use a web interface to access and query the databases.

Applications of Linear Discriminant Analysis
Nick Alena

ABSTRACT: The Mona Lisa => Leonardo DaVinci, 2.0cm Wing Span => Deadly Midge, Viagra => Spam. Is it possible to use numerical characteristics of a painting to determine its creator, or measurements of an insect to distinguish its species, or titles of emails to separate spam from legitimate messages? Linear discriminant analysis (LDA) is a statistical method used to identify group membership using a linear combination of features. The techniques extend concepts from ANOVA (analysis of variance) and regression analysis. We examine methods for choosing good discriminating variables and producing a linear combination that best distinguishes between the groups.

Social Capital and Corporate Change
Jasper G Burch

ABSTRACT: Social Capital is loosely defined as resources which are embeded in a social network. There are many types of socail capital including: prestige, decision making power, knowledge and experience. In this presentation we will explore ways to measure social capital and examine how it impacts corporate change processes. We will also examine ways in which to effect the social capital available for or against a change by changing the structure of a soial network.

Beowulf Cluster for Bioinformatics
Benjamin Case and Stephen Ciesla

ABSTRACT: Scientific computing is requiring greater and greater processing power. Cluster computing provides a inexpensive means of creating powerful parralel processing computers. We construct a Beowulf Linux cluster for Bioinformatics work and discuss the research and construction of the cluster as well as the mechanics of how parralel processing systems are used to tackle large scale problems

Analysis of NFL \`Draft Pick Value Chart \`
Dustin Cidorowich

ABSTRACT: The goal of this project is to evaluate the \`Draft Pick Value Chart\`, which is used by most NFL teams as a way of allocating value to individual draft picks. I have used the games played and games started as a proxy for drafted players value, and will use regression methodology to to link the explanatory variables to the drafted players value. The variables used in the analysis include selection number, year, team, and position. The predicted values will be scaled and compared with the \`Draft Pick Value Chart\` values. Would it be in a teams best interest to trade a second and fourth round draft pick for a first round pick?

Survey of techniques of labyrinth analysis
Ellen Galo

ABSTRACT: As labyrinths have become popular for meditation and entered the mainstream, the means to analyze existing labyrinths and create new esigns has also become a topic of interest to both mathematicians and non-mathematicians alike. In this talk I will survey and summarize the available literature, and indicate where labyrinth research and design connects to already-existing areas of graph theory and combinatorics. Some labyrinth history will also be mentioned as background.

The Shortest Network Problem
Dipesh Mainali

ABSTRACT: Suppose that a finite set of n objects are scattered randomly in a plane. How can a shortest possible network of straight lines connect them? The Shortest Network Problem has plenty of practical applications and thus is one of the most studied Graph Theory problems. In this talk we will look at what Minimal Spanning Trees and Minimal Steiner Trees are, how they can be found, and how they can be used to find the shortest network.

ROC Confidence Regions Using Radial Sweep
Yordan D. Minev

ABSTRACT: A biometric authentication system matches physiological characteristics to a database of such characteristics. In biometric authentication, genuine users are generally those that the system should accept and imposters are those that the system should reject. One methodology for evaluating the matching performance of biometric authentication systems is the receiver operating characteristics (ROC) curve. The ROC curve graphically illustrates the relationship between type I and type II statistical classification errors when varying a threshold across a genuine and an imposter match score distributions. The performance of each biometric system can be estimated via a confidence region for a ROC curve of that system\`s performance. In this project ROC confidence regions will be created using radial sweep method. Radial sweep is based on converting the type I and type II errors to polar coordinates. The technique of bootstrapping will be utilized to estimate the variability of each point on an individual ROC curve. Simulations will be performed using real biometric match score data. A radial sweep method for comparing two ROC curves will be discussed.

You Know What They Say About Assuming ...
Tim Morse

ABSTRACT: Anyone who has taken an introductory statistics course is familiar with the idea of assumptions. In order to make all those wonderful statistical calculations work, your professor told you to “assume the underlying population is normally distributed.” As you progressed through your statistical education the assuming undoubtedly continued. But what really happens if we leave out all the assumptions? Better yet, what if the real world refuses to cooperate with us? This talk will explore these questions and reveal what, if anything, goes wrong when the assumptions statisticians cling to no longer hold true.

Methods for Comparing Two Survival Curves
Julie Muetterties

ABSTRACT: A survival curve shows the proportion of a population at risk which survives up to a certain time. Such curves can be described by theoretical parametric models (such as exponential, lognormal, or Weibull) as well as nonparametric methods (such as Kaplan- Meier). We investigate methods for determining if survival curves from two populations or treatments are significantly different with applications to real data.

Lifting the Fog Over Math Modeling of Air Pollution
Matt Way

ABSTRACT: We’ve all seen the tall smoke stacks releasing massive clouds of smog into the air, but were does it go? This presentation is an application of multivariable calculus and probability to predicting where the smoke will end up out of a smoke stack. We will explore the diffusion process itself, take the Gaussian Plume Model from the two-dimensional page and put it into the 3 dimensional context of a smoke stack, and even prove Laplace’s Equation using air pollution. These questions are important when installing a structure that will be emitting smoke, in relation to the type smog being emitted and what can be found in the surrounding community.