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Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean 2020 Chapman University

Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean

Computational and Data Sciences (PhD) Dissertations

"Social communication is the use of language in social contexts. It encompasses social interaction, social cognition, pragmatics, and language processing” [3]. One presumed prerequisite of social communication is visual attention–the focus of this work. “Visual attention is a process that directs a tiny fraction of the information arriving at primary visual cortex to high-level centers involved in visual working memory and pattern recognition” [7]. This process involves the integration of two streams: the global and local streams; the global stream rapidly processes the scene, and the local stream processes details. This integration is important to social communication in that ...


Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim 2020 Washington University in St. Louis

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

Engineering and Applied Science Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is ...


Comparative Analysis Of Metabolic Pathways Of Bacteria Used In Fermented Food, Keanu Hoang, Kiran Bastola 2020 University of Nebraska at Omaha

Comparative Analysis Of Metabolic Pathways Of Bacteria Used In Fermented Food, Keanu Hoang, Kiran Bastola

Theses/Capstones/Creative Projects

This study presents a novel methodology for analyzing metabolic pathways. Utilizing KEGG REST API through a Biopython package and file parser, data about whether or not a bacteria has an enzyme or not was extracted. The results found that differences in metabolic pathway enrichment values follow along the lines of genera and pathway type. In particular, bacteria found in food spoilage and commercial nitrogen fixing products had high values of enrichment.


Gait Characterization Using Computer Vision Video Analysis, Martha T. Gizaw 2020 College of William and Mary

Gait Characterization Using Computer Vision Video Analysis, Martha T. Gizaw

Undergraduate Honors Theses

The World Health Organization reports that falls are the second-leading cause of accidental death among senior adults around the world. Currently, a research team at William & Mary’s Department of Kinesiology & Health Sciences attempts to recognize and correct aging-related factors that can result in falling. To meet this goal, the members of that team videotape walking tests to examine individual gait parameters of older subjects. However, they undergo a slow, laborious process of analyzing video frame by video frame to obtain such parameters. This project uses computer vision software to reconstruct walking models from residents of an independent living retirement ...


Tidytouch: An Interactive Visualization Tool For Data Science Education, Jonah E. DeVaney 2020 East Tennessee State University

Tidytouch: An Interactive Visualization Tool For Data Science Education, Jonah E. Devaney

Undergraduate Honors Theses

Accessibility and usability of software define the programs used for both professional and academic activities. While many proprietary tools are easy to grasp, some challenges exist in using more technical resources, such as the statistical programming language R. The creative project tidyTouch is a web application designed to help educate any user in basic R data visualization and transformation using the popular ggplot2 and dplyr packages. Providing point-and-click interactivity to explore potential modifications of graphics for data presentation, the application uses an intuitive interface to make R more accessible to those without programming experience. This project is in a state ...


Predicting The Impact Of Weather On Rural Travel Times Using Now-Cast Weather Forecast Data, Manish Meshram 2020 Utah State University

Predicting The Impact Of Weather On Rural Travel Times Using Now-Cast Weather Forecast Data, Manish Meshram

All Graduate Theses and Dissertations

In the states which record extreme weather conditions and high snow in winters, the travel time to drive between cities can get highly affected due to these bad weather conditions. The present solutions to tackle this problem are largely flow or time related and do not take weather conditions into account while making the predictions about travel time. Also these solutions can mostly be used for real time travel and not the future travel. In addition to that, the studies that have been done in this space are mostly for urban travel times but most parts of the interstate highways ...


Using Imagery To Improve Program Quality In Computer Programming, Joseph S. Ditton 2020 Utah State University

Using Imagery To Improve Program Quality In Computer Programming, Joseph S. Ditton

All Graduate Theses and Dissertations

A common practice in sports is to review film footage of a game. This is done in the hope that individuals on the team or the a team as a whole might learning something about technique, form, process, or strategy that they either did well on or need to improve on. We believe that the benefits of doing this could extend to computer science, and more specifically, the process of writing a computer program. This has never been done in the past, as such this research is exploratory in nature. A new tool called Phanon can record someone writing a ...


On The Explanation And Implementation Of Three Open-Source Fully Homomorphic Encryption Libraries, Alycia Carey 2020 University of Arkansas, Fayetteville

On The Explanation And Implementation Of Three Open-Source Fully Homomorphic Encryption Libraries, Alycia Carey

Computer Science and Computer Engineering Undergraduate Honors Theses

While fully homomorphic encryption (FHE) is a fairly new realm of cryptography, it has shown to be a promising mode of information protection as it allows arbitrary computations on encrypted data. The development of a practical FHE scheme would enable the development of secure cloud computation over sensitive data, which is a much-needed technology in today's trend of outsourced computation and storage. The first FHE scheme was proposed by Craig Gentry in 2009, and although it was not a practical implementation, his scheme laid the groundwork for many schemes that exist today. One main focus in FHE research is ...


Integrated Machine Learning And Bioinformatics Approaches For Prediction Of Cancer-Driving Gene Mutations, Oluyemi Odeyemi 2020 Chapman University

Integrated Machine Learning And Bioinformatics Approaches For Prediction Of Cancer-Driving Gene Mutations, Oluyemi Odeyemi

Computational and Data Sciences (PhD) Dissertations

Cancer arises from the accumulation of somatic mutations and genetic alterations in cell division checkpoints and apoptosis, this often leads to abnormal tumor proliferation. Proper classification of cancer-linked driver mutations will considerably help our understanding of the molecular dynamics of cancer. In this study, we compared several cancer-specific predictive models for prediction of driver mutations in cancer-linked genes that were validated on canonical data sets of functionally validated mutations and applied to a raw cancer genomics data. By analyzing pathogenicity prediction and conservation scores, we have shown that evolutionary conservation scores play a pivotal role in the classification of cancer ...


Cyber Security’S Influence On Modern Society, Nicholas Vallarelli 2020 Pace University

Cyber Security’S Influence On Modern Society, Nicholas Vallarelli

Honors College Theses

The world of cyber security is evolving every day, and cyber-criminals are trying to take advantage of it to gain as much money and power as possible. As the Internet continues to grow, more people around the world join the Internet. The purpose of this is to see how much of an importance cyber security has and how cyber-criminals are able to utilize the cyberworld for their own personal gain. Research has been done on how the cyberworld got where it is today. Additionally, individual research has been done in an effort to learn how to hack. A hack lab ...


A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz 2020 University of Arkansas, Fayetteville

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.


Early Warning Solar Storm Prediction, Ian D. Lumsden, Marvin Joshi, Matthew Smalley, Aiden Rutter, Ben Klein 2020 University of Tennessee, Knoxville

Early Warning Solar Storm Prediction, Ian D. Lumsden, Marvin Joshi, Matthew Smalley, Aiden Rutter, Ben Klein

Chancellor’s Honors Program Projects

No abstract provided.


Applying Imitation And Reinforcement Learning To Sparse Reward Environments, Haven Brown 2020 University of Arkansas, Fayetteville

Applying Imitation And Reinforcement Learning To Sparse Reward Environments, Haven Brown

Computer Science and Computer Engineering Undergraduate Honors Theses

The focus of this project was to shorten the time it takes to train reinforcement learning agents to perform better than humans in a sparse reward environment. Finding a general purpose solution to this problem is essential to creating agents in the future capable of managing large systems or performing a series of tasks before receiving feedback. The goal of this project was to create a transition function between an imitation learning algorithm (also referred to as a behavioral cloning algorithm) and a reinforcement learning algorithm. The goal of this approach was to allow an agent to first learn to ...


Dependency Mapping Software For Jira, Project Management Tool, Bentley Lager 2020 University of Arkansas, Fayetteville

Dependency Mapping Software For Jira, Project Management Tool, Bentley Lager

Computer Science and Computer Engineering Undergraduate Honors Theses

Efficiently managing a software development project is extremely important in industry and is often overlooked by the software developers on a project. Pieces of development work are identified by developers and are then handed off to project managers, who are left to organize this information. Project managers must organize this to set expectations for the client, and ensure the project stays on track and on budget. The main block in this process are dependency chains between tasks. Dependency chains can cause a project to take much longer than anticipated or result in the under utilization of developers on a project ...


Speech Processing In Computer Vision Applications, Nicholas Waterworth 2020 University of Arkansas, Fayetteville

Speech Processing In Computer Vision Applications, Nicholas Waterworth

Computer Science and Computer Engineering Undergraduate Honors Theses

Deep learning has been recently proven to be a viable asset in determining features in the field of Speech Analysis. Deep learning methods like Convolutional Neural Networks facilitate the expansion of specific feature information in waveforms, allowing networks to create more feature dense representations of data. Our work attempts to address the problem of re-creating a face given a speaker's voice and speaker identification using deep learning methods. In this work, we first review the fundamental background in speech processing and its related applications. Then we introduce novel deep learning-based methods to speech feature analysis. Finally, we will present ...


Identifying Privacy Policy In Service Terms Using Natural Language Processing, Ange-Thierry Ishimwe 2020 University of Arkansas, Fayetteville

Identifying Privacy Policy In Service Terms Using Natural Language Processing, Ange-Thierry Ishimwe

Computer Science and Computer Engineering Undergraduate Honors Theses

Ever since technology (tech) companies realized that people's usage data from their activities on mobile applications to the internet could be sold to advertisers for a profit, it began the Big Data era where tech companies collect as much data as possible from users. One of the benefits of this new era is the creation of new types of jobs such as data scientists, Big Data engineers, etc. However, this new era has also raised one of the hottest topics, which is data privacy. A myriad number of complaints have been raised on data privacy, such as how much ...


Investigating Machine Learning Techniques For Gesture Recognition With Low-Cost Capacitive Sensing Arrays, Michael Fahr Jr. 2020 University of Arkansas, Fayetteville

Investigating Machine Learning Techniques For Gesture Recognition With Low-Cost Capacitive Sensing Arrays, Michael Fahr Jr.

Computer Science and Computer Engineering Undergraduate Honors Theses

Machine learning has proven to be an effective tool for forming models to make predictions based on sample data. Supervised learning, a subset of machine learning, can be used to map input data to output labels based on pre-existing paired data. Datasets for machine learning can be created from many different sources and vary in complexity, with popular datasets including the MNIST handwritten dataset and CIFAR10 image dataset. The focus of this thesis is to test and validate multiple machine learning models for accurately classifying gestures performed on a low-cost capacitive sensing array. Multiple neural networks are trained using gesture ...


An Exploration Of Methods For Classifying Air-Written Letters From The Spanish Alphabet, Manuel Serna-Aguilera 2020 University of Arkansas, Fayetteville

An Exploration Of Methods For Classifying Air-Written Letters From The Spanish Alphabet, Manuel Serna-Aguilera

Computer Science and Computer Engineering Undergraduate Honors Theses

The ability to recognize human activity, especially air-writing, is an interesting challenge as one could identify any letter from many languages. I intend to investigate this problem of air-writing, but with the added twist of including the following letters from the Spanish alphabet: Á, É, Í, Ó, Ú, Ü, and Ñ. With this new alphabet, I set out to see what kinds of classifiers work best and on what kinds of data, since letters can be represented in multiple ways.

My tracking system will consist of a regular camera and a subject who will draw with a brightly colored marker ...


Learning & Planning For Self-Driving Ride-Hailing Fleets, Jack Morris 2020 William & Mary

Learning & Planning For Self-Driving Ride-Hailing Fleets, Jack Morris

Undergraduate Honors Theses

Through simulation, we demonstrate that incorporation of self-driving vehicles into ride-hailing fleets can greatly improve urban mobility. After modeling existing driver-rider matching algorithms including Uber’s Batched Matching and Didi Chuxing’s Learning and Planning approach, we develop a novel algorithm adapting the latter to a fleet of Autos – self-driving ride-hailing vehicles – and Garages – specialized hubs for storage and refueling. By compiling driver-rider matching, idling, storage, refueling, and redistribution decisions in one unifying framework, we enable a system-wide optimization approach for self-driving ride-hailing previously unseen in the literature. In contrast with existing literature that labeled driverless taxis as economically infeasible ...


Modeling Movement: A Machine-Learning Approach To Track Migration Routes After Displacement, Ethan Harrison 2020 William & Mary

Modeling Movement: A Machine-Learning Approach To Track Migration Routes After Displacement, Ethan Harrison

Undergraduate Honors Theses

Over the past decade, the number of individuals internally displaced by conflict (IDPs) has reached unprecedented levels. Humanitarian actors and first-responders face persistent information gaps in meeting the needs of these populations. Specifically, they face challenges in understanding where and how IDPs move after they are displaced, which is necessary to locate them in conflict-affected situations and provide them with life-saving assistance. In this paper, I propose a framework, using established machine-learning methods, to forecast the migration routes of these displaced populations (Chapter 1). In a case study of displacement in Yemen, my models predict 80% of IDPs' migration routes ...


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