Physical Sciences and Mathematics Commons^™

Tools For Managing The Past Web, Michele C. Weigle, Michael L. Nelson, Yasmin Alnoamany, Ahmed Alsum, Justin Brunelle, Mat Kelly, Hany Salaheldeen

Computer Science Presentations

PDF of a powerpoint presentation from the Archive-It Partners Meeting in Montgomery, Alabama, November 18, 2014. Also available on Slideshare.

Strategies For Sensor Data Aggregation In Support Of Emergency Response, X. Wang, A. Walden, M. Weigle, S. Olariu

Computer Science Presentations

PDF of a powerpoint presentation from the Military Communications Conference (MILCOM), Baltimore, Maryland, October 7, 2014. Also available on Slideshare.

Discretized Agent-Based Model Of Infectious Disease Spread That Uses Contact Probability, Tyrell L. Gardner

Computational Modeling & Simulation Engineering Theses & Dissertations

This study uses contact probability in an agent-based model to simulate the spread of an infectious disease. In order to perform the study, the agent-based model must first be discretized into events. Each agent in the model is given its own infectious disease state machine taken from the Susceptible-Exposed-Infected-Recovered (SEIR) model. The agents move between squares in a grid environment where each square represents a group. Groups have a contact probability as an attribute that is used to predict whether an agent comes in close contact with another agent. The transitions between the states in the SEIR model are easily …

"Archive What I See Now" Bringing Institutional Web Archiving Tools To The Individual Researcher, Michele C. Weigle, Michael L. Nelson, Liza Potts

Computer Science Presentations

PDF of a powerpoint presentation from the 2014 National Endowment for the Humanities (NEH) Office of Digital Humanities (ODH) Project Directors' Meeting in Washington D. C., September 15, 2014. Also available form Slideshare.

Meshless Mechanics And Point-Based Visualization Methods For Surgical Simulations, Rifat Aras

Computational Modeling & Simulation Engineering Theses & Dissertations

Computer-based modeling and simulation practices have become an integral part of the medical education field. For surgical simulation applications, realistic constitutive modeling of soft tissue is considered to be one of the most challenging aspects of the problem, because biomechanical soft-tissue models need to reflect the correct elastic response, have to be efficient in order to run at interactive simulation rates, and be able to support operations such as cuts and sutures.

Mesh-based solutions, where the connections between the individual degrees of freedom (DoF) are defined explicitly, have been the traditional choice to approach these problems. However, when the problem …

Scalable Reasoning For Knowledge Bases Subject To Changes, Hui Shi

Computer Science Theses & Dissertations

ScienceWeb is a semantic web system that collects information about a research community and allows users to ask qualitative and quantitative questions related to that information using a reasoning engine. The more complete the knowledge base is, the more helpful answers the system will provide. As the size of knowledge base increases, scalability becomes a challenge for the reasoning system. As users make changes to the knowledge base and/or new information is collected, providing fast enough response time (ranging from seconds to a few minutes) is one of the core challenges for the reasoning system.

There are two basic inference …

High Dimensional Data Set Analysis Using A Large-Scale Manifold Learning Approach, Loc Tran

Electrical & Computer Engineering Theses & Dissertations

Because of technological advances, a trend occurs for data sets increasing in size and dimensionality. Processing these large scale data sets is challenging for conventional computers due to computational limitations. A framework for nonlinear dimensionality reduction on large databases is presented that alleviates the issue of large data sets through sampling, graph construction, manifold learning, and embedding. Neighborhood selection is a key step in this framework and a potential area of improvement. The standard approach to neighborhood selection is setting a fixed neighborhood. This could be a fixed number of neighbors or a fixed neighborhood size. Each of these has …

Idpal – A Partially-Adiabatic Energy-Efficient Logic Family: Theory And Applications To Secure Computing, Mihail T. Cutitaru

Electrical & Computer Engineering Theses & Dissertations

Low-power circuits and issues associated with them have gained a significant amount of attention in recent years due to the boom in portable electronic devices. Historically, low-power operation relied heavily on technology scaling and reduced operating voltage, however this trend has been slowing down recently due to the increased power density on chips. This dissertation introduces a new very-low power partially-adiabatic logic family called Input-Decoupled Partially-Adiabatic Logic (IDPAL) with applications in low-power circuits. Experimental results show that IDPAL reduces energy usage by 79% compared to equivalent CMOS implementations and by 25% when compared to the best adiabatic implementation. Experiments ranging …

Improving Structural Features Prediction In Protein Structure Modeling, Ashraf Yaseen

Computer Science Theses & Dissertations

Proteins play a vital role in the biological activities of all living species. In nature, a protein folds into a specific and energetically favorable three-dimensional structure which is critical to its biological function. Hence, there has been a great effort by researchers in both experimentally determining and computationally predicting the structures of proteins.

The current experimental methods of protein structure determination are complicated, time-consuming, and expensive. On the other hand, the sequencing of proteins is fast, simple, and relatively less expensive. Thus, the gap between the number of known sequences and the determined structures is growing, and is expected to …

A Framework For Web Object Self-Preservation, Charles L. Cartledge

Computer Science Theses & Dissertations

We propose and develop a framework based on emergent behavior principles for the long-term preservation of digital data using the web infrastructure. We present the development of the framework called unsupervised small-world (USW) which is at the nexus of emergent behavior, graph theory, and digital preservation. The USW algorithm creates graph based structures on the Web used for preservation of web objects (WOs). Emergent behavior activities, based on Craig Reynolds’ “boids” concept, are used to preserve WOs without the need for a central archiving authority. Graph theory is extended by developing an algorithm that incrementally creates small-world graphs. Graph theory …

Resource Allocation In Vehicular Cloud Computing, Puya Ghazizadeh

Computer Science Theses & Dissertations

Recently, we have witnessed the emergence of Cloud Computing, a paradigm shift adopted by information technology (IT) companies with a large installed infrastructure base that often goes under-utilized. The unmistakable appeal of cloud computing is that it provides scalable access to computing resources and to a multitude of IT services. Cloud computing and cloud IT services have seen and continue to see a phenomenal adoption rate around the world.

Recently, Professor Olariu and his coworkers through series of research introduced a new concept, Vehicular Cloud Computing. A Vehicular Cloud (VC) is a network of vehicles in a parking lot …

Assessing The Fit Between Child Welfare Information Systems And Frontline Workers: Development Of A Task-Technology Fit Instrument, Kurt William Heisler

Health Services Research Dissertations

States and the federal government continue to invest heavily in child welfare information systems (CWIS) to improve caseworkers' performance, but the extent to which these systems meet caseworkers' needs is unclear. In the field of child welfare there are no reliable user-evaluation measures states can use to assess the degree to which a CWIS meets caseworkers' needs, and identify which specific features of the CWIS most need improvement. The study developed such a measure based on the task-technology fit (TTF) framework, which posits that users will evaluate the usefulness of a technology based on how well it meets their tasks …

Bits Of Research, Michele C. Weigle

Computer Science Presentations

PDF of a powerpoint presentation that provides an overview of digital preservation, web archiving, and information visualization research; dated June 26, 2014. Also available on Slideshare.

Computational Analysis Of Gene Expression And Connectivity Patterns In The Convoluted Structures Of Mouse Cerebellum, Tao Zeng

Computer Science Theses & Dissertations

One significant difference between evolved mammalian brains and other species is that mammalian brains exhibit increasingly convoluted structures in the cerebral cortex. Groove and ridge shaped structures named gyri and sulci expand surface area of cerebral cortex, making more functions possible. Prior studies using neuroimaging techniques such as dMRI and DTI have revealed that neural fibers are heavily connected to gyri comparing to those connected to sulci, such macro-scale experiments indicates that gyri are involved in large scale information processing while sulci process information locally. However, molecular and cellar level evidences, namely, gene expression pattern and its resulting neuronal connectivity …

Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala

Computer Science Theses & Dissertations

Combinatorics is the science of "possibilities." This definition, while not formal is a fair statement because all too often, in order to gain insight into the solution of many counting problems, we explore the possibilities. In some cases we seek to know how many options, while in other cases we seek to enumerate or list the options. Irrespective of the scenario, combinatorics plays a vital role today. In many instances such as exploring the options for choosing a new password for a combination lock, we employ combinatorics. In considering the possible license plate permutations for a state, or to see …

Section Abstracts: Computer Science

Virginia Journal of Science

Abstracts of the Computer Science Section for the 92nd Annual Meeting of the Virginia Academy of Science, May 13-15, 2014, Virginia Commonwealth University, Richmond, Virginia

Document Classification In Support Of Automated Metadata Extraction Form Heterogeneous Collections, Paul K. Flynn

Computer Science Theses & Dissertations

A number of federal agencies, universities, laboratories, and companies are placing their documents online and making them searchable via metadata fields such as author, title, and publishing organization. To enable this, every document in the collection must be catalogued using the metadata fields. Though time consuming, the task of identifying metadata fields by inspecting the document is easy for a human. The visual cues in the formatting of the document along with accumulated knowledge and intelligence make it easy for a human to identify various metadata fields. Even with the best possible automated procedures, numerous sources of error exist, including …

Simulation Modeling And Analysis Of Customs-Regulated Container Terminal Operations With Multimodal Transportation, Mariam A. Kotachi

Engineering Management & Systems Engineering Theses & Dissertations

World trade has been increasing dramatically in the past two decades and, as a result, container exchange has grown significantly. Consequently and to meet this increase, several container terminals are expanding and many new ones are being established. A port with one or more container terminals is considered a complex system in which many entities interact to accomplish seamless handling of containers inbound and outbound. The level of complexity is drastically heightened for container terminals containing multimodal transportation systems as they typically involve ships, rail, and trucks arriving to one or more terminals delivering containers of different sizes to several …

Markov Chain Monte Carlo Bayesian Predictive Framework For Artificial Neural Network Committee Modeling And Simulation, Michael S. Goodrich

Computational Modeling & Simulation Engineering Theses & Dissertations

A logical inference method of properly weighting the outputs of an Artificial Neural Network Committee for predictive purposes using Markov Chain Monte Carlo simulation and Bayesian probability is proposed and demonstrated on machine learning data for non-linear regression, binary classification, and 1-of-k classification. Both deterministic and stochastic models are constructed to model the properties of the data. Prediction strategies are compared based on formal Bayesian predictive distribution modeling of the network committee output data and a stochastic estimation method based on the subtraction of determinism from the given data to achieve a stochastic residual using cross validation. Performance for Bayesian …

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 …

Web Archive Services Framework For Tighter Integration Between The Past And Present Web, Ahmed Alsum

Computer Science Theses & Dissertations

Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users' needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build …

Transparent Spectrum Co-Access In Cognitive Radio Networks, Jonathan Daniel Backens

Electrical & Computer Engineering Theses & Dissertations

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary …

Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar

Engineering Management & Systems Engineering Theses & Dissertations

The delivery of health care services has been impacted by advances in Knowledge Management Information Systems (KMIS) and Information Technology (IT). The literature reveals that Electronic Health Records Systems (EHRs) are a comprehensive KMIS. There is a wide recognition in the body of knowledge that demonstrates the potential of EHRs to transform all aspects of health care services and, in consequence, the performance of Health Care Delivery Organizations (HCDO). Authors of published research also agree that there is a need for more empirical contributions that demonstrate the impact of EHRs upon HCDO. It is argued that in most cases, studies …

A Scalable Backward Chaining-Based Reasoner For A Semantic Web, Hui Shi, Kurt Maly, Steven Zeil

Computer Science Faculty Publications

In this paper we consider knowledge bases that organize information using ontologies. Specifically, we investigate reasoning over a semantic web where the underlying knowledge base covers linked data about science research that are being harvested from the Web and are supplemented and edited by community members. In the semantic web over which we want to reason, frequent changes occur in the underlying knowledge base, and less frequent changes occur in the underlying ontology or the rule set that governs the reasoning. Interposing a backward chaining reasoner between a knowledge base and a query manager yields an architecture that can support …

An Itk Implementation Of A Physics-Based Non-Rigid Registration Method For Brain Deformation In Image Guided Neurosurgery, Yixun Liu, Andriy Kot, Fotis Drakopoulos, Chengjun Yao, Andriy Fedorov, Andinet Enquobahrie, Oliver Clatz, Nikos P. Chrisochoides

Electrical & Computer Engineering Faculty Publications

As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block …

Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan

Physics Faculty Publications

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.

Do Groups Matter? An Agent-Based Modeling Approach To Pedestrian Egress, Andrew Collins, Terra Elzie, Erika Frydenlund, R. Michael Robinson

VMASC Publications

Festivals in city parks attended by individuals and families are a universal feature of urban life. These venues often have the common attributes of vendors and other obstacles that restrict pedestrian movement through certain areas, as well as fixed number of exits. In this study, the authors build an agent-based model (ABM) that incorporates group cohesion forces into this type of pedestrian egress scenario. The scenario considered was an evacuation of 500 people through a single exit. This allowed an investigation into the use of two different simulated pedestrian's heading updating rules.

Sensor Selection And Integration To Improve Video Segmentation In Complex Environments, Adam R. Reckley, Wei-Wen Hsu, Chung-Hao Chen, Gangfeng Ma, E-Wen Huang

Electrical & Computer Engineering Faculty Publications

Background subtraction is often considered to be a required stage of any video surveillance system being used to detect objects in a single frame and/or track objects across multiple frames in a video sequence. Most current state-of-the-art techniques for object detection and tracking utilize some form of background subtraction that involves developing a model of the background at a pixel, region, or frame level and designating any elements that deviate from the background model as foreground. However, most existing approaches are capable of segmenting a number of distinct components but unable to distinguish between the desired object of interest and …

Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm …

A Distributed Consensus Algorithm For Decision Making In Service-Oriented Internet Of Things, Shancang Li, George Oikonomou, Theo Tryfonas, Thomas M. Chen, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

In a service-oriented Internet of things (IoT) deployment, it is difficult to make consensus decisions for services at different IoT edge nodes where available information might be insufficient or overloaded. Existing statistical methods attempt to resolve the inconsistency, which requires adequate information to make decisions. Distributed consensus decision making (CDM) methods can provide an efficient and reliable means of synthesizing information by using a wider range of information than existing statistical methods. In this paper, we first discuss service composition for the IoT by minimizing the multi-parameter dependent matching value. Subsequently, a cluster-based distributed algorithm is proposed, whereby consensuses are …