Digital Commons Network^™

Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song

Theses and Dissertations--Computer Science

Road crashes are one of the main causes of death in the United States. To reduce the number of accidents, roadway assessment programs take a proactive approach, collecting data and identifying high-risk roads before crashes occur. However, the cost of data acquisition and manual annotation has restricted the effect of these programs. In this thesis, we propose methods to automate the task of roadway safety assessment using deep learning. Specifically, we trained convolutional neural networks on publicly available roadway images to predict safety-related metrics: the star rating score and free-flow speed. Inference speeds for our methods are mere milliseconds, enabling …

Enhance Nmf-Based Recommendation Systems With Auxiliary Information Imputation, Fatemah Alghamedy

Theses and Dissertations--Computer Science

This dissertation studies the factors that negatively impact the accuracy of the collaborative filtering recommendation systems based on nonnegative matrix factorization (NMF). The keystone in the recommendation system is the rating that expresses the user's opinion about an item. One of the most significant issues in the recommendation systems is the lack of ratings. This issue is called "cold-start" issue, which appears clearly with New-Users who did not rate any item and New-Items, which did not receive any rating.

The traditional recommendation systems assume that users are independent and identically distributed and ignore the connections among users whereas the recommendation …

Confprofitt: A Configuration-Aware Performance Profiling, Testing, And Tuning Framework, Xue Han

Theses and Dissertations--Computer Science

Modern computer software systems are complicated. Developers can change the behavior of the software system through software configurations. The large number of configuration option and their interactions make the task of software tuning, testing, and debugging very challenging. Performance is one of the key aspects of non-functional qualities, where performance bugs can cause significant performance degradation and lead to poor user experience. However, performance bugs are difficult to expose, primarily because detecting them requires specific inputs, as well as specific configurations. While researchers have developed techniques to analyze, quantify, detect, and fix performance bugs, many of these techniques are not …

A Diverse Band-Aware Dynamic Spectrum Access Architecture For Connectivity In Rural Communities, Vijay K. Shah

Theses and Dissertations--Computer Science

Ubiquitous connectivity plays an important role in improving the quality of life in terms of economic development, health and well being, social justice and equity, as well as in providing new educational opportunities. However, rural communities which account for 46% of the world's population lacks access to proper connectivity to avail such societal benefits, creating a huge "digital divide" between the urban and rural areas. A primary reason is that the Information and Communication Technologies (ICT) providers have less incentives to invest in rural areas due to lack of promising revenue returns. Existing research and industrial attempts in providing connectivity …

Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang

Theses and Dissertations--Computer Science

Technological advances in next-generation sequencing and biomedical imaging have led to a rapid increase in biomedical data dimension and acquisition rate, which is challenging the conventional data analysis strategies. Modern machine learning techniques promise to leverage large data sets for finding hidden patterns within them, and for making accurate predictions. This dissertation aims to design novel machine learning-based models to transform biomedical big data into valuable biological insights. The research presented in this dissertation focuses on three bioinformatics domains: splice junction classification, gene regulatory network reconstruction, and lesion detection in mammograms.

A critical step in defining gene structures and mRNA …

Learning To Map The Visual And Auditory World, Tawfiq Salem

Theses and Dissertations--Computer Science

The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training …

Application Of Boolean Logic To Natural Language Complexity In Political Discourse, Austin Taing

Theses and Dissertations--Computer Science

Press releases serve as a major influence on public opinion of a politician, since they are a primary means of communicating with the public and directing discussion. Thus, the public’s ability to digest them is an important factor for politicians to consider. This study employs several well-studied measures of linguistic complexity and proposes a new one to examine whether politicians change their language to become more or less difficult to parse in different situations. This study uses 27,500 press releases from the US Senate between 2004–2008 and examines election cycles and natural disasters, namely hurricanes, as situations where politicians’ language …

Metadata-Based Image Collecting And Databasing For Sharing And Analysis, Xi Wu

Theses and Dissertations--Computer Science

Data collecting and preparing is generally considered a crucial process in data science projects. Especially for image data, adding semantic attributes when preparing image data provides much more insights for data scientists. In this project, we aim to implement a general-purpose central image data repository that allows image researchers to collect data with semantic properties as well as data query. One of our researchers has come up with the specific challenge of collecting images with weight data of infants in least developed countries with limited internet access. The rationale is to predict infant weights based on image data by applying …

Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal

Theses and Dissertations--Computer Science

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …

Depth Enhancement And Surface Reconstruction With Rgb/D Sequence, Xinxin Zuo

Theses and Dissertations--Computer Science

Surface reconstruction and 3D modeling is a challenging task, which has been explored for decades by the computer vision, computer graphics, and machine learning communities. It is fundamental to many applications such as robot navigation, animation and scene understanding, industrial control and medical diagnosis. In this dissertation, I take advantage of the consumer depth sensors for surface reconstruction. Considering its limited performance on capturing detailed surface geometry, a depth enhancement approach is proposed in the first place to recovery small and rich geometric details with captured depth and color sequence. In addition to enhancing its spatial resolution, I present a …

Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco

Theses and Dissertations--Computer Science

Campus networks have recently experienced a proliferation of devices ranging from personal use devices (e.g. smartphones, laptops, tablets), to special-purpose network equipment (e.g. firewalls, network address translation boxes, network caches, load balancers, virtual private network servers, and authentication servers), as well as special-purpose systems (badge readers, IP phones, cameras, location trackers, etc.). To establish directives and regulations regarding the ways in which these heterogeneous systems are allowed to interact with each other and the network infrastructure, organizations typically appoint policy writing committees (PWCs) to create acceptable use policy (AUP) documents describing the rules and behavioral guidelines that all campus network …

Ε-Superposition And Truncation Dimensions In Average And Probabilistic Settings For ∞-Variate Linear Problems, Jonathan M. Dingess

Theses and Dissertations--Computer Science

This thesis is a representation of my contribution to the paper of the same name I co-author with Dr. Wasilkowski. It deals with linear problems defined on γ-weighted normed spaces of functions with infinitely many variables. In particular, I describe methods and discuss results for ε-truncation and ε-superposition methods. I show through these results that the ε-truncation and ε-superposition dimensions are small under modest error demand ε. These positive results are derived for product weights and the so-called anchored decomposition.

Rule Mining And Sequential Pattern Based Predictive Modeling With Emr Data, Orhan Abar

Theses and Dissertations--Computer Science

Electronic medical record (EMR) data is collected on a daily basis at hospitals and other healthcare facilities to track patients’ health situations including conditions, treatments (medications, procedures), diagnostics (labs) and associated healthcare operations. Besides being useful for individual patient care and hospital operations (e.g., billing, triaging), EMRs can also be exploited for secondary data analyses to glean discriminative patterns that hold across patient cohorts for different phenotypes. These patterns in turn can yield high level insights into disease progression with interventional potential. In this dissertation, using a large scale realistic EMR dataset of over one million patients visiting University of …

Hadoop-Edf: Large-Scale Distributed Processing Of Electrophysiological Signal Data In Hadoop Mapreduce, Yuanyuan Wu

Theses and Dissertations--Computer Science

The rapidly growing volume of electrophysiological signals has been generated for clinical research in neurological disorders. European Data Format (EDF) is a standard format for storing electrophysiological signals. However, the bottleneck of existing signal analysis tools for handling large-scale datasets is the sequential way of loading large EDF files before performing an analysis. To overcome this, we develop Hadoop-EDF, a distributed signal processing tool to load EDF data in a parallel manner using Hadoop MapReduce. Hadoop-EDF uses a robust data partition algorithm making EDF data parallel processable. We evaluate Hadoop-EDF’s scalability and performance by leveraging two datasets from the National …

A Machine Learning Approach To Artificial Floorplan Generation, Genghis Goodman

Theses and Dissertations--Computer Science

The process of designing a floorplan is highly iterative and requires extensive human labor. Currently, there are a number of computer programs that aid humans in floorplan design. These programs, however, are limited in their inability to fully automate the creative process. Such automation would allow a professional to quickly generate many possible floorplan solutions, greatly expediting the process. However, automating this creative process is very difficult because of the many implicit and explicit rules a model must learn in order create viable floorplans. In this paper, we propose a method of floorplan generation using two machine learning models: a …

Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori

Theses and Dissertations--Computer Science

Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities …