Digital Commons Network^™

Behavioral Operations Management In Federal Governance, Frederick Leonard Mobley

Walden Dissertations and Doctoral Studies

The environmental uncertainty of federal politics and acquisition outsourcing in competitive markets requires an adaptive decision-analysis structure. Practitioners oriented toward exclusively static methods face severe challenges in understanding qualitative aspects of organizational governance. The purpose of this grounded theory study was to examine and understand behavioral relationship attributes within intuitive, choice, judgment, or preference decision-making processes. The problem addressed in this study was the detrimental effects of organizational citizenship behavior (OCB), compulsory citizenship behavior (CCB), and social exchange theory (SET) on the acquisition management relationship The OCB, CCB, SET dictates that sound business development, relationship acumen, emotional intelligence and perceptiveness …

The Transmuted Exponentiated Generalized-G Family Of Distributions, Haitham M. Yousof, Ahmed Z. Afify, Morad Alizadeh, Nadeem Shafique Butt, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce a new class of continuous distributions called the transmuted exponentiated generalized-G family which extends the exponentiated generalized-G class introduced by Cordeiro et al. (2013). We provide some special models for the new family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Rényi and Shannon entropies, order statistics and probability weighted moments are derived. The estimation of the model parameters is performed by maximum likelihood. The flexibility of the proposed family is illustrated by means of an applications to real dataset.

Modeling Stem Cell Population Dynamics, Samiur Arif

Computer Science Theses & Dissertations

Because of the stochastic nature of biological systems, mathematical and computational modeling approaches have become more acceptable to experimentalists and clinicians in recent years as contributing to new understandings of complicated cell mechanisms and tissue physiology. Indeed, even single cell or small tissue samples are complex dynamic systems that adapt to environmental challenges in space and time which is poorly understood. Mathematical models and computer simulations can explain and uncover unknown aspects of cell behavior and tissue functions. Models based on key biological mechanisms can give interesting insights and formulate predictions that cannot be derived from physical experiments or statistical …

Towards Detection And Control Of Civilian Unmanned Aerial Vehicles, Matthew Peacock, Michael N. Johnstone

Australian Information Warfare and Security Conference

Considering the significant number of non‐military unmanned aerial vehicles (UAVs) that can be purchased to operate in unregulated air space and the range of such devices, the potential for security and privacy problems to arise is significant. This can lead to consequent harm for critical infrastructure in the event of these UAVs being used for criminal or terrorist purposes. Further, if these devices are not being detected, there is a privacy problem to be addressed as well. In this paper we test a specific UAV, the Parrot AR Drone version 2, and present a forensic analysis of tests used to …

The Log-Beta Generalized Half-Normal Regression Model, Rodrigo R. Pescim, Edwin M. M. Ortega, Gauss M. Cordeiro, Clarice G. B. Demtrio, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce a log-linear regression model based on the beta generalized half-normal distribution (Pescim et al., 2010). We formulate and develop a log-linear model using a new distribution so-called the log-beta generalized half normal distribution. We derive expansions for the cumulative distribution and density functions which do not depend on complicated functions. We obtain formal expressions for the moments and moment generating function. We characterize the proposed distribution using a simple relationship between two truncated moments. An advantage of the new distribution is that it includes as special sub-models classical distributions reported in the lifetime literature. We also show that …

Scitech Book News Reviews, Susan Fingerman

Sci-Tech News

No abstract provided.

Brovine: Mammary Gland Gene Database, Therin C. Irwin

Computer Science and Software Engineering

Brovine is used by the Animal Science department at Cal Poly to catalog and analyze genetic information. Brovine, or the Mammary Gland Gene Database, is a system used to store and categorize genetic information which is gathered through experimentation and through TESS, a web application that lets users search through catalogs of similar genetic information. This document describes the purpose, use, and maintenance of Brovine.

Computational Approaches For Structure Based Drug Design And Protein Structure-Function Prediction, Sai Lakshmana Kumar Vankayala

USF Tampa Graduate Theses and Dissertations

This dissertation thesis consists of a series of chapters that are interwoven by solving interesting biological problems, employing various computational methodologies. These techniques provide meaningful physical insights to promote the scientific fields of interest. Focus of chapter 1 concerns, the importance of computational tools like docking studies in advancing structure based drug design processes. This chapter also addresses the prime concerns like scoring functions, sampling algorithms and flexible docking studies that hamper the docking successes. Information about the different kinds of flexible dockings in terms of accuracy, time limitations and success studies are presented. Later the importance of Induced fit …

Scale Invariant Object Recognition Using Cortical Computational Models And A Robotic Platform, Danny Voils

Dissertations and Theses

This paper proposes an end-to-end, scale invariant, visual object recognition system, composed of computational components that mimic the cortex in the brain. The system uses a two stage process. The first stage is a filter that extracts scale invariant features from the visual field. The second stage uses inference based spacio-temporal analysis of these features to identify objects in the visual field. The proposed model combines Numenta's Hierarchical Temporal Memory (HTM), with HMAX developed by MIT's Brain and Cognitive Science Department. While these two biologically inspired paradigms are based on what is known about the visual cortex, HTM and HMAX …

The Utility Of Transient Sensitivity For Wildlife Management And Conservation: Bison As A Case Study, Michael Buhnerkempe, Nathanial Burch, Sarah J. Hamilton, Kerry M. Byrne, Eddie Childers, Kirstin A. Holfelder, Lindsay Mcmanus, Matthew I. Pyne, Greg Schroeder, Paul F. Doherty

Mathematics, Statistics and Computer Science Faculty Research and Publications

Developing effective management strategies is essential to conservation biology. Population models and sensitivity analyses on model parameters have provided a means to quantitatively compare different management strategies, allowing managers to objectively assess the resulting impacts. Inference from traditional sensitivity analyses (i.e., eigenvalue sensitivity methods) is only valid for a population at its stable age distribution, while more recent methods have relaxed this assumption and instead focused on transient population dynamics. However, very few case studies, especially in long-lived vertebrates where transient dynamics are potentially most relevant, have applied these transient sensitivity methods and compared them to eigenvalue sensitivity methods. We …

Gene Network Inference And Expression Prediction Using Recurrent Neural Networks And Evolutionary Algorithms, Heather Y. Chan

Theses and Dissertations

We demonstrate the success of recurrent neural networks in gene network inference and expression prediction using a hybrid of particle swarm optimization and differential evolution to overcome the classic obstacle of local minima in training recurrent neural networks. We also provide an improved validation framework for the evaluation of genetic network modeling systems that will result in better generalization and long-term prediction capability. Success in the modeling of gene regulation and prediction of gene expression will lead to more rapid discovery and development of therapeutic medicine, earlier diagnosis and treatment of adverse conditions, and vast advancements in life science research.

Drug Off-Target Effects Predicted Using Structural Analysis In The Context Of A Metabolic Network Model, Roger L. Chang, Lei Xie, Philip E. Bourne, Bernhard O. Palsson

Publications and Research

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been …

Automated Isolation Of Translational Efficiency Bias That Resists The Confounding Effect Of Gc(At)-Content, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Detection of this bias is an important tool …

Automated Interpretation Of The Tandem Mass Spectra Of Peptides Using Artificial Neural Networks, Timothy Patrick Manning

Theses

The manual interpretation of mass spectra is a complex and time consuming task. The problem of manually interpreting this data is further exacerbated by the large numbers of mass spectra which can potentially be produced in a single proteoniics experiment. This shows the need for high throughput approaches to the interpretation of mass spectra. Existing automated approaches are however error prone due to the complexity of the task. Accordingly, this thesis discusses and evaluates the application of neural networks to improving the sensitivity, specificity and robustness of current approaches to the automated interpretation of such mass spectral data.

Several neural …

Enhancing Ais To Improve Whale-Ship Collision Avoidance And Maritime Security, Philip A. Mcgillivary, Kurt Schwehr, Kevin Fall

Center for Coastal and Ocean Mapping

Whale-ship strikes are of growing worldwide concern due to the steady growth of commercial shipping. Improving the current situation involves the creation of a communication capability allowing whale position information to be estimated and exchanged among vessels and other observation assets. An early example of such a system has been implemented for the shipping lane approaches to the harbor of Boston, Massachusetts where ship traffic transits areas of the Stellwagen Bank National Marine Sanctuary frequently used by whales. It uses the Automated Identification Systems (AIS) technology, currently required for larger vessels but becoming more common in all classes of vessels. …

A Locus-Based Paradigm For Generating Systems Biological Inferences From Large Scale Functional Genomics Datasets, Ajish Dominic George

Legacy Theses & Dissertations (2009 - 2024)

Genomics data is growing at a exponential rate. The ability to integrate new results with existing knowledge about genomic biology is rapidly becoming the limiting factor as there no universal language with which to describe genomic functional elements. To integrate and compare new and existing genomic data, we define our basic functional unit of a genome to be a locus -- a set of positional coordinates along any genome with an arbitrary amount of functional annotations attached. The locus concept enables addressing genomic elements and annotations at any level of granularity from entire swaths of chromosomes to single base-positions. We …

Dna Sequence Representation By Use Of Statistical Finite Automata, Asmi Shah

Master's Projects

This project defines and intends to solve the problem of representing information carried by DNA sequences in terms of amino acids, through application of the theory of finite automata. Sequences can be compared against each other to find existing patterns, if any, which may include important genetic information. Comparison can state whether the DNA sequences belong to the same, related or entirely different species in the ‘Tree of Life’ (phylogeny). This is achieved by using extended and statistical finite automata. In order to solve this problem, the concepts of automata and their extension, i.e. Alergia algorithm have been used. In …

Investigation And Quantification Of Codon Usage Bias Trends In Prokaryotes, Amanda L. Hanes

Browse all Theses and Dissertations

Organisms construct proteins out of individual amino acids using instructions encoded in the nucleotide sequence of a DNA molecule. The genetic code associates combinations of three nucleotides, called codons, with every amino acid. Most amino acids are associated with multiple synonymous codons, but although they result in the same amino acid and thus have no effect on the final protein, synonymous codons are not present in equal amounts in the genomes of most organisms. This phenomenon is known as codon usage bias, and the literature has shown that all organisms display a unique pattern of codon usage. Research also suggests …

Alayzing The Effects Of Modularity On Search Spaces, Ozlem Garibay

Electronic Theses and Dissertations

We are continuously challenged by ever increasing problem complexity and the need to develop algorithms that can solve complex problems and solve them within a reasonable amount of time. Modularity is thought to reduce problem complexity by decomposing large problems into smaller and less complex subproblems. In practice, introducing modularity into evolutionary algorithm representations appears to improve search performance; however, how and why modularity improves performance is not well understood. In this thesis, we seek to better understand the effects of modularity on search. In particular, what are the effects of module creation on the search space structure and how …

Algorithmic Techniques Employed In The Isolation Of Codon Usage Biases In Prokaryotic Genomes, Douglas W. Raiford Iii

Browse all Theses and Dissertations

While genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Isolation of translational efficiency bias can have important …

Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert

Faculty Publications

Due to the immensity of phylogenetic tree space for large data sets, researches must rely on heuristic searches to infer reasonable phylogenies. By designing meta-searches which appropriately combine a variety of heuristics and parameter settings, researchers can significantly improve the performance of heuristic searches. Advanced language constructs in the open-source PSODA project—including variables, mathematical and logical expressions, conditional statements, and user-defined commands—give researchers a better framework for the exploration and exploitation of phylogenetic meta-search algorithms. PSODA’s approach to scripting meta-search algorithms is unique among open-source packages and addresses several limitations of other phylogenetic applications.

Protein Design By Mining And Sampling An Undirected Graphical Model Of Evolutionary Constraints, John Thomas, Naren Ramakrishnan, Chris Bailey-Kellogg

Computer Science Technical Reports

Evolutionary pressures on proteins to maintain structure and function have constrained their sequences over time and across species. The sequence record thus contains valuable information regarding the acceptable variation and covariation of amino acids in members of a protein family. When designing new members of a protein family, with an eye toward modified or improved stability or functionality, it is incumbent upon a protein engineer to uncover such constraints and design conforming sequences. This paper develops such an approach for protein design: we first mine an undirected probabilistic graphical model of a given protein family, and then use the model …

Classifying Rna Secondary Structures Using Support Vector Machines, Prathy Usha Sunkara

Theses

In contrast to DNA, RNA prevails as a single strand. As a consequence of small self-complementary regions, RNA commonly exhibits an intricate secondary structure, consisting of relatively short, double helical segments alternated with single stranded regions. The amount of sequence data available is rising rapidly day by day. One of the problems encountered on a specific molecule is finding the relevant data between the massive number of other sequences to be done by reading lists with a short description of all new entries in large databases already existing. One of the main objectives of this work is to take the …

Discovering Weak Community Structures In Large Biological Networks , Jianhua Ruan, Weixiong Zhang

All Computer Science and Engineering Research

Identifying intrinsic structures in large networks is a fundamental problem in many fields, such as biology, engineering and social sciences. Motivated by biology applications, in this paper we are concerned with identifying community structures, which are densely connected sub-graphs, in large biological networks. We address several critical issues for finding community structures. First, biological networks directly constructed from experimental data often contain spurious edges and may also miss genuine connections. As a result, community structures in biological networks are often weak. We introduce simple operations to capture local neighborhood structures for identifying weak communities. Second, we consider the issue of …

The Multiple Roles Of Anticipation In Developmental Robotics, Doug Blank, Joshua M. Lewis, James B. Marshall

Computer Science Faculty Research and Scholarship

Anticipatory systems have been shown to be useful in discrete, symbolic systems. However, non­symbolic anticipatory systems are less well understood. In this paper, we explore the use of anticipation within the framework of connectionist networks to bootstrap from an innate behavior; to drive a reinforcement signal; and to provide feedback on the learnability of a task.

A Probability-Based Similarity Measure For Saupe Alignment Tensors With Applications To Residual Dipolar Couplings In Nmr Structural Biology, Anthony K. Yan, Christopher J. Langmead, Bruce Randall Donald

Computer Science Technical Reports

High-throughput NMR structural biology and NMR structural genomics pose a fascinating set of geometric challenges. A key bottleneck in NMR structural biology is the resonance assignment problem. We seek to accelerate protein NMR resonance assignment and structure determination by exploiting a priori structural information. In particular, a method known as Nuclear Vector Replacement (NVR) has been proposed as a method for solving the assignment problem given a priori structural information [24,25]. Among several different kinds of input data, NVR uses a particular type of NMR data known as residual dipolar couplings (RDCs). The basic physics of residual dipolar couplings tells …

An Improved Nuclear Vector Replacement Algorithm For Nuclear Magnetic Resonance Assignment, Christopher James Langmead, Bruce Randall Donald

Computer Science Technical Reports

We report an improvement to the Nuclear Vector Replacement (NVR) algorithm for high-throughput Nuclear Magnetic Resonance (NMR) resonance assignment. The new algorithm improves upon our earlier result in terms of accuracy and computational complexity. In particular, the new NVR algorithm assigns backbone resonances without error (100% accuracy) on the same test suite examined in [Langmead and Donald J. Biomol. NMR 2004], and runs in $O(n^{5/2} \log {(cn)})$ time where $n$ is the number of amino acids in the primary sequence of the protein, and $c$ is the maximum edge weight in an integer-weighted bipartite graph.

Functional Annotation And Dendrogram Representation Of Gene Expression Clustering Results, Antoneta Petkova Vladimirova

Theses

The advances in genomic sciences have created vast amounts of gene expression data. To make sense of the expression information, various techniques have been applied. Clustering is among the unsupervised methods used to group the results according to gene expression level. Dendrogram visualization allows graphical representation of the clustering. The aim of this thesis is to enhance these techniques by adding another layer of functionality, namely, annotating the dendrogram with gene functional information. Presented is an application which visualizes yeast clustering results as a dendrogram along with color-coded gene keyword annotations. Gene keyword information was extracted from a major biological …

Parallel 3d Reconstruction Of Assymmetric Virus Structure From Electron From Electron Micrographs: Algorithms And Experiments, Robert E. Lynch, Dan C. Marinescu, Yongchang Ji, Hong Lin

Department of Computer Science Technical Reports

No abstract provided.

Development Of A Networked Interactive Information Environment Within A National Park, John Clifton

Theses

For the most part, the Killarney National Park (KNP) currently disseminates information to visitors in paper format and by word of mouth in a non-coherent fashion. Society as a whole is moving towards an Information Age delivered through an electronic medium. This project aims to facilitate the KNP in delivering a new electronically presented information experience to its global visitors.

Electronic media facilitate the delivery of in-depth multimedia as well as multilingual information. This information will be made available on demand to visitors and delivered through a variety of media including information points and handheld devices to facilitate the various …