The revolution in information technology and the explosion in the use of computing devices in people's everyday activities has forever changed the perspective of the data mining and machine learning fields. The enormous amounts of easily...
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...
The Combinatorial Nullstellensatz can be used to solve certain problems in combinatorics. However, one of the major complications in using the Combinatorial Nullstellensatz is ensuring that there exists a nonzero monomial. This dissertation looks...
A hyper basis function network (HyperBF) is a generalized radial basis function network (RBF) where the activation function is a radial function of a weighted distance. The local weighting of the distance accounts for the variation in local scaling...
Images, Photographic--Databases; Image processing--Digital techniques; Data mining; Cluster analysis
The performance of content-based image retrieval systems has proved to be inherently constrained by the used low level features, and cannot give satisfactory results when the user's high level concepts cannot be expressed by low level features. In...
The advent of larger storage spaces, affordable digital capturing devices, and an ever growing online community dedicated to sharing images has created a great need for efficient analysis methods. In fact, analyzing images for the purpose of...
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...
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...
Clustered longitudinal data is often collected as repeated measurements on subjects over time arising in the clusters. Examples include longitudinal community intervention studies, or family studies with repeated measures on each member. Meanwhile,...
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...
Outerplanar graphs are planar graphs that have a plane embedding in which each vertex lies on the boundary of the exterior region. An outerplanar graph is maximal outerplanar if the graph obtained by adding an edge is not outerplanar. Maximal...
The complexity of high-dimensional data creates a number of concerns when trying to analyze it. This data often consists of a response or survival time and potentially thousands of predictors. These predictors can be highly correlated, and the...
Two stage stochastic programming is an important part in the whole area of stochastic programming, and is widely spread in multiple disciplines, such as financial management, risk management, and logistics. The two stage stochastic programming is a...
Pattern recognition systems; Cluster analysis; Data mining
Despite the large number of existing clustering methods, clustering remains a challenging task especially when the structure of the data does not correspond to easily separable categories, and when clusters vary in size, density and shape. Existing...
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...
Marginal inference for waiting times in multi-stage time-to-event models is complicated by right censoring of observations as well as the prior history of events in the model. In general, complications arise due to the evolution of the censoring...
Preventive maintenance is a broad term that encompasses a set of activities aimed at improving the overall reliability and availability of a system. Preventive maintenance involves a basic trade-off between the costs of conducting...
The objective of this thesis is to develop computer programs for the dynamic analysis of structures. For a shear building two computer programs were developed: (1) Dynamic Analysis of a Shear Building within the Elastic Range and (2) the Dynamic...
Bioinformatics; Breast--Cancer--Treatment; Medical care--Data processing
Statistical models have been the first choice for comparative effectiveness in clinical research. Though effective, these models are limited when the data to be analyzed do not fit the assumed distributions; which is mostly the case when the study...
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,...
