A common research interest in medical, biological, and engineering research is determining whether certain independent variables are correlated with the survival or failure times. Standard statistical techniques cannot usually be applied for...
The classification of self-dual codes has been an extremely active area in
coding theory since 1972 [33]. A particularly interesting class of self-dual codes
is those of Type II which have high minimum distance (called extremal or...
Given a metric space (K, d), the hyperspace of K is defined by H(K) = {F c K: F is compact, F ≠ 0}. H(K) is itself a metric space under the Hausdorff metric dH. Hyperspaces have been extensively studied by topologists since the 1970's, but the...
The purpose of this research study is to examine the use of time series forecasting and text mining to investigate the prescription of antibiotics. The specific objective is to examine the relationship between the total payments, private insurance...
Computer scientists studying formal languages have made use of a variety of representations to both reason, and communicate their ideas to others. Symbolic representations have proved useful for rigorously defining the theoretical objects of the...
Phase II clinical trial are generally single arm trial where a homogeneity assumption is placed on the response. In practice, this assumption may be violated resulting in a heterogeneous response. This heterogeneous or overdispersed response can be...
Swarm Intelligence (SI) techniques were inspired by bee swarms, ant colonies, and most
recently, bird flocks. Flock-based Swarm Intelligence (FSI) has several unique features, namely
decentralized control, collaborative learning, high exploration...
Recently our lab has shown that with broadband stimuli (either visual noise or natural scenes), performance for detecting oriented content is worst at horizontal, best at the obliques, and intermediate at vertical orientations--an anisotropy...
Data Classification is a task that could be found in many life activities. In general, the term could be used for any activity that derives some decision or forecast based on the currently available information. Using a more accurate definition, a...
Many important applications require the discovery of items which have occurred frequently. Knowledge of these items is commonly used in anomaly detection and network monitoring tasks. Effective solutions for this problem focus mainly on reducing...
The topic of this dissertation is the automation of the process of extracting understandable patterns and rules from data. An unprecedented amount of data is available to anyone with a computer connected to the Internet. The disciplines of Data...
Ligaments--Wounds and injuries; Knee--Wounds and injuries; Women athletes--Wounds and injuries
Anterior Cruciate Ligament (ACL) injuries are among the most common injuries incurred by both recreational and professional athletes. ACL injuries often occur during popular contact sports like basketball, football, volleyball and baseball, and...
Intimate partner violence--Psychological aspects; Victims of family violence--Rehabilitation; Victims of violent crimes--Mental health; Creative writing--Therapeutic use; Post-traumatic stress disorder--Treatment
Described as important long-term consequences of trauma exposure, disruptions in emotional processes are regarded as central features of posttraumatic stress disorder (PTSD); however, the nature of these posttraumatic emotional disruptions remains...
Recent advances in high throughput methodologies offer researchers the ability to understand complex systems via high dimensional and multi-relational data. One example is the realm of molecular biology where disparate data (such as gene sequence,...
Regression analysis is a statistical method used to relate a variable of interest, typically y (the dependent variable), to a set of independent variables, usually, X1, X2,...,Xn . The goal is to build a model that assists statisticians in...
For complex classification systems, data is usually gathered from multiple sources of information that have varying degree of reliability. In fact, assuming that the different sources have the same relevance in describing all the data might lead to...
Corpus callosum; Diagnostic imaging; Autism--Diagnosis
Early detection of human disease in today’s society can have an enormous impact
on the severity of the disease that is manifested. Disease such as Autism and Dyslexia,
which have no current cure or proven mechanism as to how they develop, can...
Representing the complex data in a concise and accurate way is a special stage in data mining methodology. Redundant and noisy data affects generalization power of any classification algorithm, undermines the results of any clustering algorithm and...
Item response theory; Goodness-of-fit tests; Monte Carlo method
Item response theory (IRT) is expanding to diverse research settings, without accompanying access to easily implemented model fit methods. One simple model fit approach involves x2/df ratios. However, its utility is not known across several...
Estimating and analysis of deformation, either rigid or non-rigid, is an active area of research in various medical imaging and computer vision applications. Its importance stems from the inherent inter- and intra-variability in biological and...
