Computer Sciences Commons^™

A Robust Deep Model For Improved Classification Of Ad/Mci Patients, Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li

Electrical & Computer Engineering Faculty Publications

Accurate classification of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many research tasks, it is of a particular interest to identify noninvasive imaging biomarkers for AD diagnosis. In this paper, we present a robust deep learning system to identify different progression stages of AD patients based on MRI and PET scans. We utilized the dropout technique to improve classical deep learning by preventing its weight coadaptation, which is a typical cause of overfitting in deep learning. …

Reminiscing About 15 Years Of Interoperability Efforts, Herbert Van De Sompel, Michael L. Nelson

Computer Science Faculty Publications

Over the past fifteen years, our perspective on tackling information interoperability problems for web-based scholarship has evolved significantly. In this opinion piece, we look back at three efforts that we have been involved in that aptly illustrate this evolution: OAI-PMH, OAI-ORE, and Memento. Understanding that no interoperability specification is neutral, we attempt to characterize the perspectives and technical toolkits that provided the basis for these endeavors. With that regard, we consider repository-centric and web-centric interoperability perspectives, and the use of a Linked Data or a REST/HATEAOS technology stack, respectively. We also lament the lack of interoperability across nodes that play …

Making Sense Of Video Analytics: Lessons Learned From Clickstream Interactions, Attitudes, And Learning Outcome In A Video-Assisted Course, Michail N. Giannakos, Konstantinos Chorianopoulos, Nikos Chrisochoides

Computer Science Faculty Publications

Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an …

Deep Convolutional Neural Networks For Annotating Gene Expression Patterns In The Mouse Brain, Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, Shuiwang Ji

Computer Science Faculty Publications

Background: Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D in situ hybridization (ISH) gene expression patterns in multiple developing stages of the mouse brain. Currently, the ISH images are annotated with anatomical terms manually. In this paper, we propose a computational approach to annotate gene expression pattern images in the mouse brain at various structural levels over the course of development.

Results: We applied deep convolutional neural network that was trained on a large set …

Scalable 3d Hybrid Parallel Delaunay Image-To-Mesh Conversion Algorithm For Distributed Shared Memory Architectures, Daming Feng, Christos Tsolakis, Andrey N. Chernikov, Nikos P. Chrisochoides

Computer Science Faculty Publications

In this paper, we present a scalable three dimensional hybrid parallel Delaunay image-to-mesh conversion algorithm (PDR.PODM) for distributed shared memory architectures. PDR.PODM is able to explore parallelism early in the mesh generation process because of the aggressive speculative approach employed by the Parallel Optimistic Delaunay Mesh generation algorithm (PODM). In addition, it decreases the communication overhead and improves data locality by making use of a data partitioning scheme offered by the Parallel Delaunay Refinement algorithm (PDR). PDR.PODM utilizes an octree structure to decompose the initial mesh and to distribute the bad elements to different octree leaves (subregions). A set of …

Tetrahedral Image-To-Mesh Conversion Software For Anatomic Modeling Of Arteriovenous Malformations, Fotis Drakopoulos, Ricardo Ortiz, Andinet Enquobahrie, Deanna Sasaki-Adams, Nikos Chrisochoides

Computer Science Faculty Publications

We describe a new implementation of an adaptive multi-tissue tetrahedral mesh generator targeting anatomic modeling of Arteriovenous Malformation (AVM) for surgical simulations. Our method, initially constructs an adaptive Body-Centered Cubic (BCC) mesh of high quality elements. Then, it deforms the mesh surfaces to their corresponding physical image boundaries, hence, improving the mesh fidelity and smoothness. Our deformation scheme, which builds upon the ITK toolkit, is based on the concept of energy minimization, and relies on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of the extracted feature points needed for the registration, and thus, adjusts …

Saccharomyces Boulardii And Bismuth Subsalicylate As Low-Cost Interventions To Reduce The Duration And Severity Of Cholera, Johnathan Sheele, Jessica Cartowski, Angela Dart, Arjun Poddar, Shikha Gupta, Ajay Gupta

Computer Science Faculty Publications

We conducted a randomised single-blinded clinical trial of 100 cholera patients in Port-au-Prince, Haiti to determine if the probiotic Saccharomyces cerevisiae var. boulardii and the anti-diarrhoeal drug bismuth subsalicylate (BS) were able to reduce the duration and severity of cholera. Subjects received either: S. boulardii 250 mg, S. boulardii 250 mg capsule plus BS 524 mg tablet, BS 524 mg, or two placebo capsules every 6 hours alongside standard treatment for cholera. The length of hospitalisation plus the number and volume of emesis, stool and urine were recorded every 6 hours until the study subject was discharged (n=83), left against …

Characteristics Of Social Media Stories, Yasmin Ainoamany, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

An emerging trend in social media is for users to create and publish "stories", or curated lists of web resources with the purpose of creating a particular narrative of interest to the user. While some stories on the web are automatically generated, such as Facebook’s "Year in Review", one of the most popular storytelling services is "Storify", which provides users with curation tools to select, arrange, and annotate stories with content from social media and the web at large. We would like to use tools like Storify to present automatically created summaries of archival collections. To support automatic story creation, …

Scaffolding To Improve Writing Skills In A Computer Science Literacy Course, Wu He, Harris Wu, Li Xu, Kurt Maly

Computer Science Faculty Publications

Writing has been recognized as an important skill in the technology field. This paper reports a study that uses a scaffolding approach to improve student writing skills in a computer science literacy course. While the quantitative results do not show a significant impact of scaffolding in individual paper assignment on the subsequent group wiki assignment, the student feedback in end-of-semester evaluations strongly indicated that scaffolding indeed helped improve their writing.

Extreme-Scale Parallel Mesh Generation: Telescopic Approach, Nikos Chrisochoides, Andrey Chernikov, Daming Feng, Christos Tsolakis

Computer Science Faculty Publications

In this poster we focus and present our preliminary results pertinent to the integration of multiple parallel Delaunay mesh generation methods into a coherent hierarchical framework. The goal of this project is to study our telescopic approach and to develop Delaunay-based methods to explore concurrency at all hardware layers using abstractions at (a) medium-grain level for many cores within a single chip and (b) coarse-grain level, i.e., sub-domain level using proper error metric- and application-specific continuous decomposition methods.

Profiling Web Archives For Efficient Memento Query Routing, Sawood Alam, Michael L. Nelson, Herbert Van De Sompel, Lyudmila L. Balakireva, Harihar Shankar, David S. H. Rosenthal

Computer Science Faculty Publications

No abstract provided.

A Dynamic Programming Algorithm For Finding The Optimal Placement Of A Secondary Structure Topology In Cryo-Em Data, Abhishek Biswas, Desh Ranjan, Mohammad Zubair, Jing He

Computer Science Faculty Publications

The determination of secondary structure topology is a critical step in deriving the atomic structures from the protein density maps obtained from electron cryomicroscopy technique. This step often relies on matching the secondary structure traces detected from the protein density map to the secondary structure sequence segments predicted from the amino acid sequence. Due to inaccuracies in both sources of information, a pool of possible secondary structure positions needs to be sampled. One way to approach the problem is to first derive a small number of possible topologies using existing matching algorithms, and then find the optimal placement for each …

Multi-Surface Simplex Spine Segmentation For Spine Surgery Simulation And Planning, Rabia Haq

Computational Modeling & Simulation Engineering Theses & Dissertations

This research proposes to develop a knowledge-based multi-surface simplex deformable model for segmentation of healthy as well as pathological lumbar spine data. It aims to provide a more accurate and robust segmentation scheme for identification of intervertebral disc pathologies to assist with spine surgery planning. A robust technique that combines multi-surface and shape statistics-aware variants of the deformable simplex model is presented. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user-assistance is …

De Novo Protein Structure Modeling And Energy Function Design, Lin Chen

Computer Science Theses & Dissertations

The two major challenges in protein structure prediction problems are (1) the lack of an accurate energy function and (2) the lack of an efficient search algorithm. A protein energy function accurately describing the interaction between residues is able to supervise the optimization of a protein conformation, as well as select native or native-like structures from numerous possible conformations. An efficient search algorithm must be able to reduce a conformational space to a reasonable size without missing the native conformation. My PhD research studies focused on these two directions.

A protein energy function—the distance and orientation dependent energy function of …

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.

Numerical Studies Of The A6 Relativistic Magnetron Using Particle-In-Cell Simulations, Vineetha Jujjavarapu

Electrical & Computer Engineering Theses & Dissertations

The magnetron became a major component in radar systems around the time of the World War II. More recent radar techniques require short microwave pulses (with nanosecond pulse-widths for ultra wideband operations) and high peak power in the Giga-Watt range. In order to achieve these specifications for the military, the magnetron needs to have both a fast start and the rapid growth rate of oscillations in order to serve as a microwave source for the short-pulse applications. These two factors depend on the geometry of the cathode. Other requirements include high conversion efficiency and low leakage current (in order to …

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 …

Camera Viewpoint Invariant Vehicular Traffic Segmentation And Classification, Jeffrey B. Flora

Electrical & Computer Engineering Theses & Dissertations

The goal of this intelligent transportation systems work is to develop a computer vision method that is view angle independent for segmenting and classifying vehicular traffic on highway systems. In order to achieve this goal, this work implements an algorithm for vehicle segmentation, feature extraction, and classification using the existing Virginia Department of Transportation (VDOT) infrastructure on networked traffic cameras. The VDOT traffic video is analyzed for vehicle detection and segmentation using an adaptive Gaussian mixture model algorithm. Speed estimation is performed using a single camera calibration. Size and shape features from morphological properties and texture features from histogram of …

"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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …