Computer Sciences Commons^™

L-Arginine Uptake And Metabolism Following In Vivo Silica Exposure In Rat Lungs, Leif D. Nelin, Gary S. Krenz, Louis G. Chicoine, Christopher A. Dawson, Ralph M. Schapira

Mathematics, Statistics and Computer Science Faculty Research and Publications

Pulmonary inflammation increases nitric oxide (NO) production via inducible nitric oxide synthase (iNOS). This study was performed to determine some of the factors that affect the availability of the NOS substrate, L-arginine (L-arg), in the intact lung subjected to silica-induced inflammation. Nitrate production, as an index of NO production, was significantly greater in silica-exposed lungs (53.5 ± 12.1 nmol/90 min) compared with controls (22.5 ±5.1 nmol/90 min, P < 0.05). This was accompanied by greater (P< 0.0001) 90-min [³H]L-arg uptake (62 ± 3% control, 82 ± 1% silica), a significantly (P < 0.005) increased permeability-surface area product for L-arg(0.28 ± 0.05 ml/min control, 0.63 ± 0.07 ml/min silica), and asignificantly (P < 0.001) increased urea production (1.16 ± 0.08µmol/90 min control, 1.77 ± 0.06 µmol/90 min silica). There was no difference in eNOS protein between groups and eNOS mRNA was not detectable in either group, whereas silica exposure resulted in the appearance of both iNOS protein and mRNA. Silica exposure increased CAT-1 and CAT-2 mRNA ~ 8-fold compared with controls. We conclude that the increase in NO production in silica-exposed lungs was associated with increased L-arg uptake from the vasculature, presumably resulting from increased CAT-1 and CAT-2, and by increased L-arg metabolism via arginase.

Comparative Molecular Field Analysis (Comfa) Of Protonated Methylphenidate Phenyl-Substituted Analogs, Kathleen Mary Gilbert

Theses

Protonated methylphenidate (pMP) and several phenyl-substituted pMP analogs were analyzed using Comparative Molecular Field Analysis (CoMFA) to develop a pharmacophore for dopamine transporter (DAT) binding. This research is a part of an interdisciplinary study on using methylphenidate (MP) analogs to block the binding of cocaine to the DAT as a treatment for addiction.

A random search conformational analysis using key pMP torsional angles was performed to create conformer families representing possible bioactive conformations. The lowest energy pMP conformer of each family was used as a template to create phenyl-substituted pMP analogs.

Partial least squares analysis was used to determine the …

Evaluating Java Applets For Teaching On The Internet, Michael R. Healy '04, Dale E. Berger, Victoria L. Romero '07, Christopher L. Aberson '99, Amanda Saw '11

CGU Faculty Publications and Research

The Web Interface for Statistics Education (http://wise.cgu.edu) is a website built around interactive tutorials designed to teach introductory and advanced statistical concepts. The tutorials use Java applets that dynamically illustrate the statistical concepts being taught. By using Java applets, we teach statistics in a manner not possible in a traditional classroom environment. In this paper, we provide examples of the applets, illustrate how students use them, and we report the outcome of a study that examined tutorial effectiveness as a learning tool.

Studying The Functional Genomics Of Stress Responses In Loblolly Pine With The Expresso Microarray Experiment Management System, Lenwood S. Heath, Naren Ramakrishnan, Ronald R. Sederoff, Ross W. Whetten, Boris I. Chevone, Craig Struble, Vincent Y. Jouenne, Dawei Chen, Leonel Van Zyl, Ruth Grene

Mathematics, Statistics and Computer Science Faculty Research and Publications

Conception, design, and implementation of cDNA microarray experiments present a variety of bioinformatics challenges for biologists and computational scientists. The multiple stages of data acquisition and analysis have motivated the design of Expresso, a system for microarray experiment management. Salient aspects of Expresso include support for clone replication and randomized placement; automatic gridding, extraction of expression data from each spot, and quality monitoring; flexible methods of combining data from individual spots into information about clones and functional categories; and the use of inductive logic programming for higher-level data analysis and mining. The development of Expresso is occurring in parallel with …

Branching Exponent Heterogeneity And Wall Shear Stress Distribution In Vascular Trees, Kelly Lynn Karau, Gary S. Krenz, Christopher A. Dawson

Mathematics, Statistics and Computer Science Faculty Research and Publications

A bifurcating arterial system with Poiseuille flow can function at minimum cost and with uniform wall shear stress if the branching exponent (z) = 3 [where z is defined by (D ₁)^z = (D ₂)^z + (D ₃)^z; D ₁ is the parent vessel diameter and D ₂ and D ₃ are the two daughter vessel diameters at a bifurcation]. Because wall shear stress is a physiologically transducible force, shear stress-dependent control over vessel diameter would appear to provide a means for preserving this optimal structure through maintenance …

Online Survey System (Oss), Hui Min Tan

Student Works (2000-2009)

Online survey system (OSS) is an electronic survey system and productivity tool. The system enables the user to conduct a survey at case which was previously paper-based and which can be tedious and time-consuming. It can be used or administered from anywhere an internet browser is available. The users can create and design their own interactive online survey. OSS provides a fast distribution of survey from to a large geographical area through email. The respondents just need to click on the URL attach with the invitation email to direct them to the survey. After that OSS will generates analysis report …

Some Applications Of The Ultrapower Theorem To The Theory Of Compacta, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

The ultrapower theorem of Keisler and Shelah allows such model-theoretic notions as elementary equivalence, elementary embedding and existential embedding to be couched in the language of categories (limits, morphism diagrams). This in turn allows analogs of these (and related) notions to be transported into unusual settings, chiefly those of Banach spaces and of compacta. Our interest here is the enrichment of the theory of compacta, especially the theory of continua, brought about by the importation of model-theoretic ideas and techniques.

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …

Census 2000 Demographic And Housing Profile Reports, Mark Salling, Ellen Cyran, Sharon Bliss

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

A Hierarchy Of Maps Between Compacta, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

Let CH be the class of compacta (i.e., compact Hausdorff spaces), with BS the subclass of Boolean spaces. For each ordinal α and pair $\langle K,L\rangle$ of subclasses of CH, we define Lev_≥α K,L), the class of maps of level at least α from spaces in K to spaces in L, in such a way that, for finite α, Lev_≥α (BS,BS) consists of the Stone duals of Boolean lattice embeddings that preserve all prenex first-order formulas of quantifier rank α. Maps of level ≥ 0 are just the continuous surjections, and the maps of level ≥ 1 are …

Evaluating Maximum Likelihood Estimation Methods To Determine The Hurst Coefficient, Christina Marie Kendziorski, J. B. Bassingthwaighte, Peter J. Tonellato

Mathematics, Statistics and Computer Science Faculty Research and Publications

A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficient (H) is evaluated. The Hurst coefficient, with 0.5<HS-MLE was developed to estimate H for fractionally differenced (fd) processes. However, in practice it is difficult to distinguish between fd processes and fractional Gaussian noise (fGn) processes. Thus, the method is evaluated for estimating H for both fd and fGn processes. S-MLE gave biased results of H for fGn processes of any length and for fd processes of lengths less than 2¹⁰. A modified method is proposed to correct for …

Structure-Function Relationships In The Pulmonary Arterial Tree, Christopher A. Dawson, Gary S. Krenz, Kelly Lynn Karau, Steven Thomas Haworth, Christopher C. Hanger, John H. Linehan

Mathematics, Statistics and Computer Science Faculty Research and Publications

Knowledge of the relationship between structure and function of the normal pulmonary arterial tree is necessary for understanding normal pulmonary hemodynamics and the functional consequences of the vascular remodeling that accompanies pulmonary vascular diseases. In an effort to provide a means for relating the measurable vascular geometry and vessel mechanics data to the mean pressure-flow relationship and longitudinal pressure profile, we present a mathematical model of the pulmonary arterial tree. The model is based on the observation that the normal pulmonary arterial tree is a bifurcating tree in which the parent-to-daughter diameter ratios at a bifurcation and vessel distensibility are …

Single Row Routing: Theoretical And Experimental Performance Evaluation, And New Heuristic Development, David A. Hysom

Computer Science Theses & Dissertations

The Single Row Routing Problem (SRRP) is an abstraction arising from real-world multilayer routing concerns. While NP-Complete, development of efficient SRRP routing heuristics are of vital concern to VLSI design. Previously, researchers have introduced various heuristics for SRRP; however, a comprehensive examination of SRRP behavior has been lacking.

We are particularly concerned with the street-congestion minimization constraint, which is agreed to be the constraint of greatest interest to industry. Several theorems stating lower bounds on street congestion are known. We show that these bounds are not tight in general, and argue they may be in error by at least 50% …

The Ohio Gis Network: Stage 2 1996 Investment Fund Grant First Year Progress Report To The Ohio Board Of Regents (Ohio Gis Network), Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

The Ohio Geographic Information Systems Network (Ohio GIS-Net) is an innovative consortium of Ohio’s urban and rural universities. The consortium is building a center of excellence where state-of-the-art geographic information systems (GIS) technology is applied to a research agenda that is critical to Ohio's economic development and central to research issues in policy sciences, civil engineering, public administration, economics and the environmental, urban and regional sciences. This cutting edge technology is an essential component of the basic research infrastructure of universities. It is also a critical resource in state and local economic development efforts, building and maintaining public infrastructure, and …

The Ohio Gis Network: Stage 1 1993 Investment Fund Development Grant Progress Report To The Ohio Board Of Regents (Ohio Gis Network), Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

The Ohio Geographic Information Systems Network (Ohio GIS-Net) is an innovative consortium of Ohio’s urban and rural universities. The consortium is building a center of excellence where state-of-the-art geographic information systems (GIS) technology is applied to a research agenda that is critical to Ohio's economic development and central to research issues in policy sciences, civil engineering, public administration, economics and the environmental, urban and regional sciences. This cutting edge technology is an essential component of the basic research infrastructure of universities. It is also a critical resource in state and local economic development efforts, building and maintaining public infrastructure, and …

Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

No abstract provided.

A New Soft Tissue Analysis : To Establish Facial Esthetic Norms In Young Adult Females, Anne Béress

Loma Linda University Electronic Theses, Dissertations & Projects

Two hundred and fifty-five articles, books, and masters theses were reviewed for the most frequently applied soft tissue measurements in the literature in order to develop a new soft tissue analysis computer program that includes established soft tissue measurements and the newly developed globe analysis. A meta analysis of 20 normal occlusion studies, was performed to obtain mean values and standard deviations to form a large sample size. Inclusion criteria for articles in the meta analysis were normal occlusion, no orthodontic treatment, pleasing faces, statement on age, race, and lip position of the population. For the lateral view, angular and …

Application Of Neural Networks To The Non-Destructive Testing Of Aluminum Cans, B. Balasubramaniam, Daniel .. Clair

Computer Science Technical Reports

Neural Networks are used to c lassify aluminum beverage containers as acceptable or non acceptable, depending upon their wall thicknesses. For each can, the thickness of the wall of the can at different points is measured using a non-destructive, ultra-sound technique. These measureI\}ents are then applied as inputs to the networks and the classification is provided as the output Three architectures, one unsupervised and two supervised, are tested. Their performances are analyzed and compared and the paradigm best suited to the problem is selected.

Computer Assisted Control Of Robotic Rock Drilling Equipment Using Rock Face Image Mapping, William Robert Macneil, Peter (C. Y.)(Chung You) Ho

Computer Science Technical Reports

Use of a totally unmanned mining robot is an ideal solution in removing humans from the dangerous underground mining environment. However, a complete autonomous system is a long way from reality. In the meantime, steps towards that goal can be made and integrated into current mining technology to take away some of the risk and stress from the miner making him more alert and the environment safer for those that do have to be undergroμnd. For our purposes here, the machine will be an automated robotic platform with the intelligence necessary for accurate placement of the drill tip on an …

Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su

Electrical & Computer Engineering Theses & Dissertations

An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.

In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.

The semi-continuous HMM is a class of models …

Control Uniqueness In Reconstructability Analysis, Martin Zwick

Complex Systems Faculty Publications and Presentations

When the reconstructability analysis of a directed system yields a structure in which a generated variable appears in more than one subsystem, information from all of the subsystems can be used in modeling the relationship between generating and generated variables. The conceptualization and procedure proposed here is discussed in relation to Klir's concept of control uniqueness.

Discovery Of Integrity Relationships In Relational Databases, D. Harrier, D. C. St. Clair

Computer Science Technical Reports

The use of database management system integrity constraints has been a powerful tool in raising the quality of data within an application subject database. Unfortunately, the successful use of integrity constraints requires that the database administrator has implemented the constraint before data are inserted into the database.

The results of this research provide a methodology for discovering previously unknown integrity relationships in a relational database. The methodology uses the principles of knowledge discovery from the artificial intelligence community, and Quinlan's ID3 machine learning algorithm as the discovery tool. Experimental results are provided that demonstrate how the methodology can be applied.

Ensuring The Satisfaction Of A Temporal Specification At Run-Time, Grace Tsai, Matt Insall, Bruce M. Mcmillin

Mathematics and Statistics Faculty Research & Creative Works

A responsive computing system is a hybrid of real-time, distributed and fault-tolerant systems. In such a system, severe consequences can occur if the run-time behavior does not conform to the expected behavior or specifications. In this paper, we present a formal approach to ensure satisfaction of the specifications in the operational environment as follows. First we specify behavior of the systems using Interval Temporal Logic (ITL). Next we give algorithms for trace checking of programs in such systems. Finally, we present a fully distributed run-time evaluation system which causally orders the events of the system during its execution and checks …

Set-Theoretic Reconstructability Of Elementary Cellular Automata, Martin Zwick, Hui Shu

Complex Systems Faculty Publications and Presentations

Set-theoretic reconstructability analysis is used to characterize the structures of the mappings of elementary cellular automata. The minimum complexity structure for each ECA mapping, indexed by parameter σ, is more effective than the λ parameter of Langton as a predictor of chaotic dynamics.

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …

Computing Χ² Values, John F. Dooley, Daniel C. St Clair, William E. Bond

Mathematics and Statistics Faculty Research & Creative Works

Textbooks and courses on numerical algorithms contain numerous examples which lead students to believe that the algorithm of choice for computing the zeros of a function f1994 is Newton's algorithm. In many of these courses little or no time is spent in providing students with "real world" experiences where Newton's method fails. The work presented in this paper describes a slow convergence problem encountered while trying to use Newton to estimate values for the 2 distributions. The problem occurred while the authors were trying to implement a well-known machine learning algorithm from the field of artificial intelligence. The function being …

A New Approach To Automatic Target Recognition Using Wavelet Transforms, Anitha Panapakkam, S. N. Balakrishnan, Daniel St. Clair

Computer Science Technical Reports

Automatic Target Recognition (ATR) systems have significant impact in defense applications. There is a continuing need to develop new and robust techniques to handle the increasingly complex ATR problem. The objectives of this thesis are two-fold. First a new technique to be used for ATR is developed and secondly an integrated ATR system to investigate and combine all subsystems is developed. In this thesis, we have developed a new technique for the feature extraction stage of ATR problem using wavelet transforms. Wavelet transforms have been one of the widely investigated areas of research in the past few years. The promising …

Topologies Invariant Under A Group Action, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

We study links between faithful group actions on a set and topologies on that set. In one direction, a group action has its invariant topologies (so we may regard members of the action to be homeomorphisms relative to those topologies); in the other direction, a topology has its preserving group actions (i.e., the subgroups of the homeomorphism group of the topology). This two-way passage allows us to discuss topological features of group actions as well as symmetry features of topologies.

Classification Characteristics Of Som And Art2, J. Aleshunas, D. St. Clair, W. Bond

Computer Science Technical Reports

Artificial neural network algorithms were originally designed to model human neural activities. They attempt to recreate the processes involved in such activities as learning, short term memory, and long term memory. Two widely used artificial neural network algorithms are the Self-Organizing Map (SOM) and the Adaptive Resonance Theory (ART2). Each was designed to simulate a particular biological neural activity. Both can be used as unsupervised data classifiers.

This paper compares performance characteristics of two unsupervised artificial neural network architectures; the SOM and the ART2 networks. The primary factors analyzed were classification accuracy, sensitivity to data noise, and sensitivity to the …

Classification Characteristics Of Som And Art2, J. J. Aleshunas, Daniel C. St. Clair, William E. Bond

Mathematics and Statistics Faculty Research & Creative Works

Artificial neural network algorithms were originally designed to model human neural activities. They attempt to recreate the processes involved in such activities as learning, short term memory, and long-term memory. Two widely used unsupervised artificial neural network algorithms are the Self-Organizing Map (SOM) and Adaptive Resonance Theory (ART2). Each was designed to simulate a particular biological neural activity. Both can be used as unsupervised data classifiers. This paper compares performance characteristics of two unsupervised artificial neural network architectures; the SOM and the ART2 networks. The primary factors analyzed were classification accuracy, sensitivity to data noise, and sensitivity of the algorithm …