Biomedical Engineering and Bioengineering Commons^™

Scattering Correction Methods Of Infrared Spectra Using Graphics Processing Units, Asher Imtiaz

Theses and Dissertations

Fourier transform infrared (FTIR) microspectroscopy has been used for many years as a technique that provides distinctive structure-specific infrared spectra for a wide range of materials (e.g., biological (tissues, cells, bacteria, viruses), polymers, energy related, composites, minerals). The mid-infrared radiation can strongly scatter from distinct particles, with diameters ranging between 2-20 micrometer. Transmission measurements of samples (approximately 100 micrometers x 100 micrometers x 10 micrometers) with distinct particles. will be dominated by this scattering (Mie scattering). The scattering distorts the measured spectra, and the absorption spectra appear different from pure absorbance spectra. This thesis presents development and implementation of two …

Extracting The Structure And Conformations Of Biological Entities From Large Datasets, Ali Dashti

Theses and Dissertations

In biology, structure determines function, which often proceeds via changes in conformation. Efficient means for determining structure exist, but mapping conformations continue to present a serious challenge. Single-particles approaches, such as cryogenic electron microscopy (cryo-EM) and emerging "diffract & destroy" X-ray techniques are, in principle, ideally positioned to overcome these challenges. But the algorithmic ability to extract information from large heterogeneous datasets consisting of "unsorted" snapshots - each emanating from an unknown orientation of an object in an unknown conformation - remains elusive.

It is the objective of this thesis to describe and validate a powerful suite of manifold-based algorithms …

Efficient Computation Of K-Nearest Neighbor Graphs For Large High-Dimensional Data Sets On Gpu Clusters, Ali Dashti

Theses and Dissertations

The k-Nearest Neighbor Graph (k-NNG) and the related k-Nearest Neighbor (k-NN) methods have a wide variety of applications in areas such as bioinformatics, machine learning, data mining, clustering analysis, and pattern recognition. Our application of interest is manifold embedding. Due to the large dimensionality of the input data (<15k), spatial subdivision based techniques such OBBs, k-d tree, BSP etc., are not viable. The only alternative is the brute-force search, which has two distinct parts. The first finds distances between individual vectors in the corpus based on a pre-defined metric. Given the distance matrix, the second step selects k nearest neighbors for each member of the query data set.

This thesis presents the development and implementation of a distributed exact k-Nearest Neighbor Graph (k-NNG) construction method. The proposed method uses Graphics Processing Units (GPUs) and exploits multiple levels of parallelism for distributed computational systems using GPUs. It is scalable for different cluster sizes, with each compute node in the cluster …