Open Access. Powered by Scholars. Published by Universities.®
Electrical and Computer Engineering
Electrical and Computer Engineering Faculty Publications and Presentations
Articles 1 - 7 of 7
Full-Text Articles in Engineering
Covariance Searches For Ncrna Gene Finding, Jennifer A. Smith
Covariance Searches For Ncrna Gene Finding, Jennifer A. Smith
Electrical and Computer Engineering Faculty Publications and Presentations
The use of covariance models for non-coding RNA gene finding is extremely powerful and also extremely computationally demanding. A major reason for the high computational burden of this algorithm is that the search proceeds through every possible start position in the database and every possible sequence length between zero and a user-defined maximum length at every one of these start positions. Furthermore, for every start position and sequence length, all possible combinations of insertions and deletions leading to the given sequence length are searched. It has been previously shown that a large portion of this search space is nowhere near …
A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith
A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith
Electrical and Computer Engineering Faculty Publications and Presentations
A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …
Accelerated Non-Coding Rna Searches With Covariance Model Approximations, Jennifer A. Smith
Accelerated Non-Coding Rna Searches With Covariance Model Approximations, Jennifer A. Smith
Electrical and Computer Engineering Faculty Publications and Presentations
Covariance models (CMs) are a very sensitive tool for finding non-coding RNA (ncRNA) genes in DNA sequence data. However, CMs are extremely slow. One reason why CMs are so slow is that they allow all possible combinations of insertions and deletions relative to the consensus model even though the vast majority of these are never seen in practice. In this paper we examine reduction in the number of states in covariance models. A simplified CM with reduced states which can be scored much faster is introduced. A comparison of the results of a full CM versus a reduced-state model found …
Dial 2004 Working Group Report On Acquisition Quality Control, Elisa H. Barney Smith, Henry Baird, William Barrett, Frank Le Bourgeois, Xiaofan Lin, George Nagy, Steve Simske
Dial 2004 Working Group Report On Acquisition Quality Control, Elisa H. Barney Smith, Henry Baird, William Barrett, Frank Le Bourgeois, Xiaofan Lin, George Nagy, Steve Simske
Electrical and Computer Engineering Faculty Publications and Presentations
This report summarizes the discussions of the Working Group on Acquisition Quality at the International Workshop on Document Image Analysis for Libraries, Palo Alto, CA, 23-24 January 2004. Acquisition of the image is one of the most time intensive components of forming a digital library, and the quality of the acquisition will affect all later stages of the digital library project. The current state of the art in acquisition is analyzed. Problems and suggested improvements for image acquisition and storage formats and the special problems associated with acquisition from microfilm follows. A list of general suggestions was developed which was …
Psf Estimation By Gradient Descent Fit To The Esf, Elisa H. Barney Smith
Psf Estimation By Gradient Descent Fit To The Esf, Elisa H. Barney Smith
Electrical and Computer Engineering Faculty Publications and Presentations
Calibration of scanners and cameras usually involves measuring the point spread function (PSF). When edge data is used to measure the PSF, the differentiation step amplifies the noise. A parametric fit of the functional form of the edge spread function (ESF) directly to the measured edge data is proposed to eliminate this. Experiments used to test this method show that the Cauchy functional form fits better than the Gaussian or other forms tried. The effect of using a functional form of the PSF that differs from the true PSF is explored by considering bilevel images formed by thresholding. The amount …
Partitioning Of The Degradation Space For Ocr Training, Elisa H. Barney Smith, Tim Andersen
Partitioning Of The Degradation Space For Ocr Training, Elisa H. Barney Smith, Tim Andersen
Electrical and Computer Engineering Faculty Publications and Presentations
Generally speaking optical character recognition algorithms tend to perform better when presented with homogeneous data. This paper studies a method that is designed to increase the homogeneity of training data, based on an understanding of the types of degradations that occur during the printing and scanning process, and how these degradations affect the homogeneity of the data. While it has been shown that dividing the degradation space by edge spread improves recognition accuracy over dividing the degradation space by threshold or point spread function width alone, the challenge is in deciding how many partitions and at what value of edge …
An Unsupervised Fluoroscopic Analysis Of Knee Joint Kinematics, Charles Scott, Elisa H. Barney Smith
An Unsupervised Fluoroscopic Analysis Of Knee Joint Kinematics, Charles Scott, Elisa H. Barney Smith
Electrical and Computer Engineering Faculty Publications and Presentations
Knowledge of the three dimensional positions of bones at a joint as a function of time is required to accurately model joint kinematics. 3-D bone geometry data from a static computer tomography (CT) images can be combined with time sequence information from 2-D video fluoroscopy images to produce 3-D position data over time. The process involves creating virtual X-rays from the CT image through digitally reconstructed radiograph (DRR) projections. Historically, the process of matching the 3-D and 2-D data has required human interaction. We have eliminated the need for manual initialization using a Monte Carlo technique with a variable search …