Many modern applications of automatic document classification require learning accurately with little training data. Addressing the need to reduce the manual labeling process, the semi-supervised classification technique ...

DNA local sequence alignments provide biological insights that can help scientists identify genetic diseases, map newly obtained sequences to known genomes, or identify common genomic patterns on same species. Even when ...

Wireless Sensor Network (WSN) is a wireless networking technology that can facilitate many important applications in our real life, from environmental monitoring to smart grid, and thus is a key component in the emerging ...

This dissertation proposes a spatially adaptive constrained Nonnegative Matrix Factorization (sacNMF) for unmixing of hyperspectral imagery. The image is decomposed into spectrally homogeneous regions using quadtree region ...

Finite field arithmetic plays an important role in a wide range of applications. This research is originally motivated by an application of computational biology where genetic networks are modeled by means of finite fields. ...

This dissertation presents a novel approach to the problem of _nding the characteristics of the data sources and query processing sites in a distributed database system. We model the network as a graph with nodes representing ...

The development of technologies such as microarrays has generated a large amount of data. The main characteristic of this kind of data it is the large number of predictors (genes) and few observations (experiments). Thus, ...

Storage systems contain redundant copies of data such as identical files or within sub-file regions. Using deduplication technology, we can take advantage of this re-dundancy and reduce the space needed to store files in ...

In this dissertation the mathematical modeling of Cosserat elastic plates and their Finite Element computation are presented. The mathematical model for bending of Cosserat elastic plates, which assumes physically and ...

This work introduces a framework for a fast and algorithmically scalable multiscale representation and segmentation of hyperspectral imagery. The framework is based on the scale-space representation generated by geometric ...