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2016

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Full-Text Articles in Computer Sciences

The Amplified Need For Supreme Court Guidance On Student Speech Rights In The Digital Age, William Calve Jan 2016

The Amplified Need For Supreme Court Guidance On Student Speech Rights In The Digital Age, William Calve

St. Mary's Law Journal

Abstract forthcoming.


An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao Jan 2016

An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao

Browse all Theses and Dissertations

Local image features are used in many computer vision applications. Many point detectors and descriptors have been proposed in recent years; however, creation of effective descriptors is still a topic of research. The Scale Invariant Feature Transform (SIFT) developed by David Lowe is widely used in image matching and image retrieval. SIFT detects interest points in an image based on Scale-Space analysis, which is invariant to change in image scale. A SIFT descriptor contains gradient information about an image patch centered at a point of interest. SIFT is found to provide a high matching rate, is robust to image transformations; …


Intelligent Caching To Mitigate The Impact Of Web Robots On Web Servers, Howard Nathan Rude Jan 2016

Intelligent Caching To Mitigate The Impact Of Web Robots On Web Servers, Howard Nathan Rude

Browse all Theses and Dissertations

With an ever increasing amount of data that is shared and posted on the Web, the desire and necessity to automatically glean this information has led to an increase in the sophistication and volume of software agents called web robots or crawlers. Recent measurements, including our own across the entire logs of Wright State University Web servers over the past two years, suggest that at least 60\% of all requests originate from robots rather than humans. Web robots display different statistical and behavioral patterns in their traffic compared to humans, yet present Web server optimizations presume that traffic exhibits predominantly …


Open Data Discourse: Consumer Acceptance Of Personal Cloud: Integrating Trust And Risk With The Technology Acceptance Model, Murad Moqbel, Valerie L. Bartelt Jan 2016

Open Data Discourse: Consumer Acceptance Of Personal Cloud: Integrating Trust And Risk With The Technology Acceptance Model, Murad Moqbel, Valerie L. Bartelt

Information Systems Faculty Publications

This paper provides the data used to analyze the conceptual replication of Pavlou (2003) by Moqbel and Bartelt (2015) which studied factors that impacted consumer’s behavioral intentions to make online transactions by integrating trust and perceived risk with the technology acceptance model (TAM). We provide a detailed description of the data so it meets the open data standards. In particular, we explain the structure of the data so that other researchers can easily analyze the same dataset to come to the same results and conclusions. Our dataset consists of 240 observations which includes the following constructs: perceived trust, perceived risk, …


Towards A New Gis Maturity Model: An Organizational Usage Perspective, Omer Abdulaziz Alrwais Jan 2016

Towards A New Gis Maturity Model: An Organizational Usage Perspective, Omer Abdulaziz Alrwais

CGU Theses & Dissertations

The first condition required for an Information Technology (IT) system to produce value is that it be used by its designated target group of users. Despite the prevalence of “system use” in IS literature, it has been often limited to the individual level. The organizational perspective is rarely considered. This dissertation focuses on system usage in the GIS domain through an organizational lens. GIS is a technology with the potential to transform government by enhancing business processes and providing a platform to manage spatial and non-spatial data, which is expected to result in better decision-making. However, little is known about …


Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari Jan 2016

Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari

Computer Science Faculty Publications and Presentations

The assessment of students’ metacognitive knowledge and skills about reading is critical in determining their ability to read academic texts and do so with comprehension. In this paper, we used induction trees to extract metacognitive knowledge about reading from a reading strategies dataset obtained from a group of 1636 undergraduate college students. Using a C4.5 algorithm, we constructed decision trees, which helped us classify participants into three groups based on their metacognitive strategy awareness levels consisting of global, problem-solving and support reading strategies. We extracted rules from these decision trees, and in order to evaluate accuracy of the extracted rules, …


Un Indicator De Incluziune Cu Aplicaţii În Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru Jan 2016

Un Indicator De Incluziune Cu Aplicaţii În Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru

Branch Mathematics and Statistics Faculty and Staff Publications

În aceasta lucrare vom prezenta un procedeu de algoritmizare a operatiilor necesare deplasarii automate a unui obiect predefinit dintr-o imagine video data intr-o regiune tinta a acelei imagini, menit a facilita realizarea de aplicatii software specializate in rezolvarea acestui gen de probleme.


An Indicator Of Inclusion With Applications To Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru Jan 2016

An Indicator Of Inclusion With Applications To Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.


Mining Human Activity Using Dimensionality Reduction And Pattern Recognition, Ismail El Moudden, Mounir Ouzir, Badreddine Benyacoub, Souad El Bernoussi Jan 2016

Mining Human Activity Using Dimensionality Reduction And Pattern Recognition, Ismail El Moudden, Mounir Ouzir, Badreddine Benyacoub, Souad El Bernoussi

Research and Infrastructure Service Enterprise (RISE) Faculty Publications

Human activity recognition (HAR) is an emerging research topic in pattern recognition, especially in computer vision. The main objective of human activity recognition is to automatically detect and analyze human activities from the information acquired from different sensors. Human activity prediction using big data remains a challengingly open problem. Several approaches have recently been developed in order to find practical ways to solve high dimensionality of data problems. The aim of this study is to attempt, using data mining techniques, to deal with HAR modeling involving a significant number of variables in order to identify relevant parameters from data and …


Selective Mutation Accumulation: A Computational Model Of The Paternal Age Effect, Eoin C. Whelan, Alexander C. Nwala, Christopher Osgood, Stephan Olariu Jan 2016

Selective Mutation Accumulation: A Computational Model Of The Paternal Age Effect, Eoin C. Whelan, Alexander C. Nwala, Christopher Osgood, Stephan Olariu

Biological Sciences Faculty Publications

Motivation: As the mean age of parenthood grows, the effect of parental age on genetic disease and child health becomes ever more important. A number of autosomal dominant disorders show a dramatic paternal age effect due to selfish mutations: substitutions that grant spermatogonial stem cells (SSCs) a selective advantage in the testes of the father, but have a deleterious effect in offspring. In this paper we present a computational technique to model the SSC niche in order to examine the phenomenon and draw conclusions across different genes and disorders.

Results: We used a Markov chain to model the probabilities of …


Computational Approaches For Binning Metagenomic Reads, Ying Wang Jan 2016

Computational Approaches For Binning Metagenomic Reads, Ying Wang

Electronic Theses and Dissertations

Metagenomics uses sequencing technologies to study genetic sequences from whole microbial communities. Binning metagenomic reads is the most fundamental step in metagenomic studies, which is essential for the understanding of microbial functions, compositions, and interactions in environmental samples. Various taxonomy-dependent and taxonomy-independent approaches have been developed based on information such as sequence similarity, sequence composition, or k-mer frequency. However, there is still room for improvement, and it is still challenging to bin reads from species with similar or low abundance or to bin reads from unknown species. In this dissertation, we introduce one taxonomy-independent and three taxonomy-dependent approaches to improve …


Spatiotemporal Graphs For Object Segmentation And Human Pose Estimation In Videos, Dong Zhang Jan 2016

Spatiotemporal Graphs For Object Segmentation And Human Pose Estimation In Videos, Dong Zhang

Electronic Theses and Dissertations

Images and videos can be naturally represented by graphs, with spatial graphs for images and spatiotemporal graphs for videos. However, for different applications, there are usually different formulations of the graphs, and algorithms for each formulation have different complexities. Therefore, wisely formulating the problem to ensure an accurate and efficient solution is one of the core issues in Computer Vision research. We explore three problems in this domain to demonstrate how to formulate all of these problems in terms of spatiotemporal graphs and obtain good and efficient solutions. The first problem we explore is video object segmentation. The goal is …


Design Of A Jmldoclet For Jmldoc In Openjml, Arjun Mitra Reddy Donthala Jan 2016

Design Of A Jmldoclet For Jmldoc In Openjml, Arjun Mitra Reddy Donthala

Electronic Theses and Dissertations

The Java Modeling Language (JML) is a behavioral interface specification language designed for specifying Java classes and interfaces. OpenJML is a tool for processing JML specifications of Java programs. To facilitate viewing of these specifications in a user-friendly manner, a tool JMLdoc was created. The JMLdoc tool adds JML specifications to the usual Javadoc documentation. JMLdoc is an enhancement of Javadoc that adds to the Javadoc documentation the JML specifications that are present in the source code. The JMLdoc tool is a drop-in replacement for Javadoc, with additional functionality and additional options. The current design of JMLdoc uses the standard …


Collective Estimation Of Multiple Bivariate Density Functions With Application To Angular-Sampling-Based Protein Loop Modeling, Mehdi Maadooliat, Lan Zhou, Seyed Morteza Najibi, Xin Gao, Jianhua Z. Huang Jan 2016

Collective Estimation Of Multiple Bivariate Density Functions With Application To Angular-Sampling-Based Protein Loop Modeling, Mehdi Maadooliat, Lan Zhou, Seyed Morteza Najibi, Xin Gao, Jianhua Z. Huang

Mathematics, Statistics and Computer Science Faculty Research and Publications

This article develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed …


Almost Perfect Restriction Semigroups, Peter R. Jones Jan 2016

Almost Perfect Restriction Semigroups, Peter R. Jones

Mathematics, Statistics and Computer Science Faculty Research and Publications

We call a restriction semigroup almost perfect if it is proper and the least congruence that identifies all its projections is perfect. We show that any such semigroup is isomorphic to a ‘W -product’ W(T,Y)W(T,Y), where T is a monoid, Y is a semilattice and there is a homomorphism from T into the inverse semigroup TIYTIY of isomorphisms between ideals of Y. Conversely, all such W-products are almost perfect. Since we also show that every restriction semigroup has an easily computed cover of this type, the combination yields a ‘McAlister-type’ theorem for all restriction semigroups. …


Two Combinatorial Proofs Of Identities Involving Sums Of Powers Of Binomial Coefficients, John Engbers, Christopher Stocker Jan 2016

Two Combinatorial Proofs Of Identities Involving Sums Of Powers Of Binomial Coefficients, John Engbers, Christopher Stocker

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.


A Hybrid Segmentation And D-Bar Method For Electrical Impedance Tomography, Sarah J. Hamilton, J. M. Reyes, Samuli Siltanen, X. Zhang Jan 2016

A Hybrid Segmentation And D-Bar Method For Electrical Impedance Tomography, Sarah J. Hamilton, J. M. Reyes, Samuli Siltanen, X. Zhang

Mathematics, Statistics and Computer Science Faculty Research and Publications

The regularized D-bar method for electrical impedance tomography (EIT) provides a rigorous mathematical approach for solving the full nonlinear inverse problem directly, i.e., without iterations. It is based on a low-pass filtering in the (nonlinear) frequency domain. However, the resulting D-bar reconstructions are inherently smoothed, leading to a loss of edge distinction. In this paper, a novel method that combines a D-bar approach with the edge-preserving nature of total variation (TV) regularization is presented. The method also includes a data-driven contrast adjustment technique guided by the key functions (CGO solutions) of the D-bar method. The new TV-enhanced D-bar …


An Ensemble Model Of Qsar Tools For Regulatory Risk Assessment, Prachi Pradeep, Richard J. Povinelli, Shannon White, Stephen Merrill Jan 2016

An Ensemble Model Of Qsar Tools For Regulatory Risk Assessment, Prachi Pradeep, Richard J. Povinelli, Shannon White, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting …


Pain Level Detection From Facial Image Captured By Smartphone, Md Kamrul Hasan, Golam Mushih Tanimul Ahsan, Sheikh Iqbal Ahamed, Rechard Love, Reza Salim Jan 2016

Pain Level Detection From Facial Image Captured By Smartphone, Md Kamrul Hasan, Golam Mushih Tanimul Ahsan, Sheikh Iqbal Ahamed, Rechard Love, Reza Salim

Mathematics, Statistics and Computer Science Faculty Research and Publications

Accurate symptom of cancer patient in regular basis is highly concern to the medical service provider for clinical decision making such as adjustment of medication. Since patients have limitations to provide self-reported symptoms, we have investigated how mobile phone application can play the vital role to help the patients in this case. We have used facial images captured by smart phone to detect pain level accurately. In this pain detection process, existing algorithms and infrastructure are used for cancer patients to make cost low and user-friendly. The pain management solution is the first mobile-based study as far as we found …


Solving Set Cover With Pairs Problem Using Quantum Annealing, Yudong Cao, Shuxian Jiang, Debbie Perouli, Sabre Kais Jan 2016

Solving Set Cover With Pairs Problem Using Quantum Annealing, Yudong Cao, Shuxian Jiang, Debbie Perouli, Sabre Kais

Mathematics, Statistics and Computer Science Faculty Research and Publications

Here we consider using quantum annealing to solve Set Cover with Pairs (SCP), an NP-hard combinatorial optimization problem that plays an important role in networking, computational biology, and biochemistry. We show an explicit construction of Ising Hamiltonians whose ground states encode the solution of SCP instances. We numerically simulate the time-dependent Schrödinger equation in order to test the performance of quantum annealing for random instances and compare with that of simulated annealing. We also discuss explicit embedding strategies for realizing our Hamiltonian construction on the D-wave type restricted Ising Hamiltonian based on Chimera graphs. Our embedding on the Chimera graph …


A Generalized Gamma-Weibull Distribution: Model, Properties And Applications, R. S. Meshkat, H. Torabi, Gholamhossein G. Hamedani Jan 2016

A Generalized Gamma-Weibull Distribution: Model, Properties And Applications, R. S. Meshkat, H. Torabi, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We prepare a new method to generate family of distributions. Then, a family of univariate distributions generated by the Gamma random variable is defined. The generalized gamma-Weibull (GGW) distribution is studied as a special case of this family. Certain mathematical properties of moments are provided. To estimate the model parameters, the maximum likelihood estimators and the asymptotic distribution of the estimators are discussed. Certain characterizations of GGW distribution are presented. Finally, the usefulness of the new distribution, as well as its effectiveness in comparison with other distributions, are shown via an application of a real data set.


Learning About Modeling In Teacher Preparation Programs, Hyunyi Jung, Eryn Stehr, Jia He, Sharon L. Senk Jan 2016

Learning About Modeling In Teacher Preparation Programs, Hyunyi Jung, Eryn Stehr, Jia He, Sharon L. Senk

Mathematics, Statistics and Computer Science Faculty Research and Publications

This study explores opportunities that secondary mathematics teacher preparation programs provide to learn about modeling in algebra. Forty-eight course instructors and ten focus groups at five universities were interviewed to answer questions related to modeling. With the analysis of the interview transcripts and related course materials, we found few opportunities for PSTs to engage with the full modeling cycle. Examples of opportunities to learn about algebraic modeling and the participants’ perspectives on the opportunities can contribute to the study of modeling and algebra in teacher education.


Remarks On A Paper Of Ahmad, Ahmad And Ahmed, Gholamhossein G. Hamedani Jan 2016

Remarks On A Paper Of Ahmad, Ahmad And Ahmed, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Ahmad et al. (2015) consider a Transmuted Kumaraswamy distribution and study certain properties of their distribution. In the title of their paper they mention characterization of this distribution, but no characterization are presented in their paper. In the present short note, we establish certain characterizations of the Transmuted Kumaraswamy distribution in three directions.


The Transmuted Weibull-Pareto Distribution, Ahmed Z. Afify, Haitham M. Yousof, Nadeem Shafique Butt, Gholamhossein G. Hamedani Jan 2016

The Transmuted Weibull-Pareto Distribution, Ahmed Z. Afify, Haitham M. Yousof, Nadeem Shafique Butt, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

A new generalization of the Weibull-Pareto distribution called the transmuted Weibull-Pareto distribution is proposed and studied. Various mathematical properties of this distribution including ordinary and incomplete moments, quantile and generating functions, Bonferroni and Lorenz curves and order statistics are derived. The method of maximum likelihood is used for estimating the model parameters. The flexibility of the new lifetime model is illustrated by means of an application to a real data set.


Towards The Scalability And Hybrid Parallelization Of A Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez Jan 2016

Towards The Scalability And Hybrid Parallelization Of A Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez

Open Access Theses & Dissertations

The purpose of this research is to design a faster implementation of the spatially variant algorithm that improves its performance when it is running on a parallel computer system.

The spatially variant algorithm is used to synthesize a spatially variant lattice for a periodic electromagnetic structure. The algorithm has the ability to spatially vary the unit cell orientation and exploit its directional dependencies. The algorithm produces a lattice that is smooth, continuous and free of defects. The lattice spacing remains strikingly uniform when the unit cell orientation, lattice spacing, fill fraction and more are spatially varied. This is important for …


Design And Evaluation Of The Impact Of A Multi-Agent Control System (Framework) Applied To A Social Setting, Perez Antonio Perez Jan 2016

Design And Evaluation Of The Impact Of A Multi-Agent Control System (Framework) Applied To A Social Setting, Perez Antonio Perez

Open Access Theses & Dissertations

The objective of this research is to design and analyze the performance of a new mechanism to improve the advising of students in a nontraditional environment. This nontraditional environment includes: a minority serving, commuter campus with a high percentage of transfer students. Specifically, these demographics are unable to keep a tightly controlled cohort of students flowing through to the completion of the curriculum. Students in these circumstances usually have varied course loads and competing priorities due to family and financial needs or other societal responsibilities. Therefore, there is a need for an individualized approach to advising.

University administrations face challenges …


Ontology-Driven Integration Of Data For Freight Performance Measures, Eduardo J. Torres Jan 2016

Ontology-Driven Integration Of Data For Freight Performance Measures, Eduardo J. Torres

Open Access Theses & Dissertations

Transportation performance measures are defined as quantitative and qualitative indicators that rely on data or information to explain mobility, congestion, safety, environmental and other factors. Though performance measures have been used for freeways and other highways, not many have been specified and applied to the freight transportation system. Recently, freight performance measures have been recommended by Federal Highway Administration to quantify the operating efficiency of the freight transportation system on existing infrastructures. This research seeks to expand this concept and to develop a comprehensive freight performance measurement framework. The expanded framework recommended in this Thesis consists of four criteria: safety, …


Assessing Accuracies And Improving Efficiency For Segmentation-Based Rna Secondary Structure Prediction Methods, Gerardo A. Cardenas Jan 2016

Assessing Accuracies And Improving Efficiency For Segmentation-Based Rna Secondary Structure Prediction Methods, Gerardo A. Cardenas

Open Access Theses & Dissertations

RNA secondary structure prediction has become an important area of interest in biology and medicine because it helps in understanding the mechanisms of many biological processes such as gene regulation and viral replication, and in designing RNA-based therapies to treat various diseases such as cancers and AIDS. Different thermodynamics-based computational algorithms for RNA structure prediction exist, and have been used to help understand the disease mechanisms and design treatments. However, most of these computational tools that can predict complex pseudoknot structures have a sequence length limitation of few hundred nucleotide bases due to their high demands of computer resources. Yet, …


Scalability Improvements To Nrlmol For Dft Calculations Of Large Molecules, Carlos Manuel Diaz Jan 2016

Scalability Improvements To Nrlmol For Dft Calculations Of Large Molecules, Carlos Manuel Diaz

Open Access Theses & Dissertations

Advances in high performance computing (HPC) have provided a way to treat large, computationally demanding tasks using thousands of processors. With the development of more powerful HPC architectures, the need to create efficient and scalable code has grown more important. Electronic structure calculations are valuable in understanding experimental observations and are routinely used for new materials predictions. For the electronic structure calculations, the memory and computation time are proportional to the number of atoms. Memory requirements for these calculations scale as N2, where N is the number of atoms. While the recent advances in HPC offer platforms with large numbers …


A Unified Cyber-Enhanced Approach For Detecting Cross-Site Scripting Attacks On Web Applications, Bhanukiran Gurijala Jan 2016

A Unified Cyber-Enhanced Approach For Detecting Cross-Site Scripting Attacks On Web Applications, Bhanukiran Gurijala

Open Access Theses & Dissertations

Cyber-security is one of our nation's most critical security priorities, and its importance continues to grow with the pervasiveness of computers and Web-based applications. In particular, cross-site scripting (XSS) is one of the most common and dangerous types of injection attacks that exploit input validation vulnerabilities. XSS has intensified due to: 1) lack of extensive security domain knowledge of software engineers who are involved in building and/or maintaining Web-applications; and 2) lack of proper software development processes focused on security, resulting in fixes to security vulnerabilities late in the software development lifecycle. Indeed, the cost benefits of removing defects, in …