Digital Commons Network^™

Remote Sensing Of Icebergs In Greenland's Fjords And Coastal Waters, Jessica Scheick

Electronic Theses and Dissertations

Increases in ocean water temperature are implicated in driving recent accelerated rates of mass loss from the Greenland Ice Sheet. Icebergs provide a key tool for gaining insight into ice-ocean interactions and until recently have been relatively understudied. Here we develop several methods that exploit icebergs visible in optical satellite imagery to provide insight on the ice--ocean environment and explore how iceberg datasets can be used to examine the physics of iceberg decay and parent glacier properties. First, a semi-automated algorithm, which includes a machine learning-based cloud mask, is applied to six years (2000-2002 and 2013-2015) of the Landsat archive …

Three-Dimensional Bedrock Channel Evolution With Smoothed Particle Hydrodynamics, Nick Richmond

Electronic Theses and Dissertations

Bedrock channels are responsible for balancing and communicating tectonic and climatic signals across landscapes, but it is difficult and dangerous to observe and measure the flows responsible for removing weakly-attached blocks of bedrock from the channel boundary. Consequently, quantitative descriptions of the dynamics of bedrock removal are scarce. Detailed numerical simulation of violent flows in three dimensions has been historically challenging due to technological limitations, but advances in computational fluid dynamics aided by high-performance computing have made it practical to generate approximate solutions to the governing equations of fluid dynamics. From these numerical solutions we gain detailed knowledge of the …

A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab

Electronic Theses and Dissertations

The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order …

An Evaluation Of Geotagged Twitter Data During Hurricane Irma Using Sentiment Analysis And Topic Modeling For Disaster Resilience, Ike Robert Vayansky

Electronic Theses and Dissertations

Disasters require quick response times, thought-out preparations, overall community, and government support. These efforts will ensure prevention of loss of life and reduce possible damages. The United States has been battered by multiple major hurricanes in the recent years and multiple avenues of disaster response efforts were being tested. Hurricane Irma can be recognized as the most popular hurricane in terms of social media attention. Irma made landfall in Florida as a Category 4 storm and preparation measures taken were intensive thus providing a good measure to evaluate in terms of efficacy. The effectiveness of the response methods utilized are …

Towards An Efficient, Scalable Stream Query Operator Framework For Representing And Analyzing Continuous Fields, John Whittier

Electronic Theses and Dissertations

Advancements in sensor technology have made it less expensive to deploy massive numbers of sensors to observe continuous geographic phenomena at high sample rates and stream live sensor observations. This fact has raised new challenges since sensor streams have pushed the limits of traditional geo-sensor data management technology. Data Stream Engines (DSEs) provide facilities for near real-time processing of streams, however, algorithms supporting representing and analyzing Spatio-Temporal (ST) phenomena are limited.

This dissertation investigates near real-time representation and analysis of continuous ST phenomena, observed by large numbers of mobile, asynchronously sampling sensors, using a DSE and proposes two novel stream …

Principles And Guidelines For Advancement Of Touchscreen-Based Non-Visual Access To 2d Spatial Information, Hari Prasath Palani

Electronic Theses and Dissertations

Graphical materials such as graphs and maps are often inaccessible to millions of blind and visually-impaired (BVI) people, which negatively impacts their educational prospects, ability to travel, and vocational opportunities. To address this longstanding issue, a three-phase research program was conducted that builds on and extends previous work establishing touchscreen-based haptic cuing as a viable alternative for conveying digital graphics to BVI users. Although promising, this approach poses unique challenges that can only be addressed by schematizing the underlying graphical information based on perceptual and spatio-cognitive characteristics pertinent to touchscreen-based haptic access. Towards this end, this dissertation empirically identified a …

Rediscovering The Interpersonal: Models Of Networked Communication In New Media Performance, Alicia Champlin

Electronic Theses and Dissertations

This paper examines the themes of human perception and participation within the contemporary paradigm and relates the hallmarks of the major paradigm shift which occurred in the mid-20th century from a structural view of the world to a systems view. In this context, the author’s creative practice is described, outlining a methodology for working with the communication networks and interpersonal feedback loops that help to define our relationships to each other and to media since that paradigm shift. This research is framed within a larger field of inquiry into the impact of contemporary New Media Art as we experience it. …

D-Fens: Dns Filtering & Extraction Network System For Malicious Domain Names, Jeffrey Spaulding

Electronic Theses and Dissertations

While the DNS (Domain Name System) has become a cornerstone for the operation of the Internet, it has also fostered creative cases of maliciousness, including phishing, typosquatting, and botnet communication among others. To address this problem, this dissertation focuses on identifying and mitigating such malicious domain names through prior knowledge and machine learning. In the first part of this dissertation, we explore a method of registering domain names with deliberate typographical mistakes (i.e., typosquatting) to masquerade as popular and well-established domain names. To understand the effectiveness of typosquatting, we conducted a user study which helped shed light on which techniques …

Improving The Accuracy Of Mobile Touchscreen Qwerty Keyboards, Amanda Kirk

Electronic Theses and Dissertations

In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can …

A Bi-Encoder Lstm Model For Learning Unstructured Dialogs, Diwanshu Shekhar

Electronic Theses and Dissertations

Creating a data-driven model that is trained on a large dataset of unstructured dialogs is a crucial step in developing a Retrieval-based Chatbot systems. This thesis presents a Long Short Term Memory (LSTM) based Recurrent Neural Network architecture that learns unstructured multi-turn dialogs and provides implementation results on the task of selecting the best response from a collection of given responses. Ubuntu Dialog Corpus Version 2 (UDCv2) was used as the corpus for training. Ryan et al. (2015) explored learning models such as TF-IDF (Term Frequency-Inverse Document Frequency), Recurrent Neural Network (RNN) and a Dual Encoder (DE) based on Long …

Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor

Electronic Theses and Dissertations

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …

Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller

Electronic Theses and Dissertations

The inherent heterogeneity of tumor tissue presents a major challenge to nanoparticle-medicated drug delivery. This heterogeneity spans from the molecular to the cellular (cell types) and to the tissue (vasculature, extra-cellular matrix) scales. Here we employ computational modeling to evaluate therapeutic response as a function of vascular-induced tumor tissue heterogeneity. Using data with three-layered gold nanoparticles loaded with cisplatin, nanotherapy is simulated with different levels of tissue heterogeneity, and the treatment response is measured in terms of tumor regression. The results show that tumor vascular density non-trivially influences the nanoparticle uptake and washout, and the associated tissue response. The drug …

New Approaches To Mapping Forest Conditions And Landscape Change From Moderate Resolution Remote Sensing Data Across The Species-Rich And Structurally Diverse Atlantic Northern Forest Of Northeastern North America, Kasey R. Legaard

Electronic Theses and Dissertations

The sustainable management of forest landscapes requires an understanding of the functional relationships between management practices, changes in landscape conditions, and ecological response. This presents a substantial need of spatial information in support of both applied research and adaptive management. Satellite remote sensing has the potential to address much of this need, but forest conditions and patterns of change remain difficult to synthesize over large areas and long time periods. Compounding this problem is error in forest attribute maps and consequent uncertainty in subsequent analyses. The research described in this document is directed at these long-standing problems.

Chapter 1 demonstrates …

Self-Organized Structures: Modeling Polistes Dominula Nest Construction With Simple Rules, Matthew Harrison

Electronic Theses and Dissertations

The self-organized nest construction behaviors of European paper wasps (Polistes dominula) show potential for adoption in artificial intelligence and robotic systems where centralized control proves challenging. However, P. dominula nest construction mechanisms are not fully understood. This research investigated how nest structures stimulate P. dominula worker action at different stages of nest construction. A novel stochastic site selection model, weighted by simple rules for cell age, height, and wall count, was implemented in a three-dimensional, step-by-step nest construction simulation. The simulation was built on top of a hexagonal coordinate system to improve precision and performance. Real and idealized …

Designing Interactive Virtual Environments With Feedback In Health Applications., Yi Li

Electronic Theses and Dissertations

One of the most important factors to influence user experience in human-computer interaction is the user emotional reaction. Interactive environments including serious games that are responsive to user emotions improve their effectiveness and user satisfactions. Testing and training for user emotional competence is meaningful in healthcare field, which has motivated us to analyze immersive affective games using emotional feedbacks. In this dissertation, a systematic model of designing interactive environment is presented, which consists of three essential modules: affect modeling, affect recognition, and affect control. In order to collect data for analysis and construct these modules, a series of experiments were …

Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar

Electronic Theses and Dissertations

Network Science is one of the important and emerging fields in computer science and engineering that focuses on the study and analysis of different types of networks. The goal of this dissertation is to design and develop network science algorithms that can be used to study and analyze mobile networks. This can provide essential information and knowledge that can help mobile networks service providers to enhance the quality of the mobile services. We focus in this dissertation on the design and analysis of different network science techniques that can be used to analyze the dynamics of mobile networks. These techniques …

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

Electronic Theses and Dissertations

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work …

Region Based Gene Expression Via Reanalysis Of Publicly Available Microarray Data Sets., Ernur Saka

Electronic Theses and Dissertations

A DNA microarray is a high-throughput technology used to identify relative gene expression. One of the most widely used platforms is the Affymetrix® GeneChip® technology which detects gene expression levels based on probe sets composed of a set of twenty-five nucleotide probes designed to hybridize with specific gene targets. Given a particular Affymetrix® GeneChip® platform, the design of the probes is fixed. However, the method of analysis is dynamic in nature due to the ability to annotate and group probes into uniquely defined groupings. This is particularly important since publicly available repositories of microarray datasets, such as ArrayExpress and NCBI’s …

Fm Radio Signal Propagation Evaluation And Creating Statistical Models For Signal Strength Prediction In Differing Topographic Environments, Timothy Land

Electronic Theses and Dissertations

Radio wave signal strength and associated propagation models are rarely analyzed across individual geographic provinces. This study evaluates the effectiveness of the Radio Mobile model to predict radio wave signal strength in the Blue Ridge and Valley and Ridge physiographic provinces. A spectrum analyzer was used on 19 FM transmitters to determine model accuracy. Statistical analysis determined the significance between different terrain factors and signal strength. Field signal strength was found to be related to test site elevation, transmitter azimuth, elevation angle, transmitter elevation, path loss, and distance. Using 76 signal strength receiver sites, Ordinary Least Square regression models predicted …

An Analysis Of International Agreements Over Cybersecurity, Lucas Ashbaugh

Electronic Theses and Dissertations

Research into the international agreements that increase cooperation over cybersecurity challenges is severely lacking. This is a necessary next step for bridging diplomatic challenges over cybersecurity. This work aspires to be push the bounds of research into these agreements and offer a tool that future researchers can rely on. For this research I created, and made publicly available, the International Cybersecurity Cooperation Dataset (ICCD), which contains over 350 international cybersecurity agreements and pertinent metadata. Each agreement is marked per which subtopics within cybersecurity related agreements it covers. These typologies are:

• Discussion and Dialogue

• Research

• Confidence Building Measures

• Incident Response

• Crime …

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Learning Algorithms For Fat Quantification And Tumor Characterization, Sarfaraz Hussein

Electronic Theses and Dissertations

Obesity is one of the most prevalent health conditions. About 30% of the world's and over 70% of the United States' adult populations are either overweight or obese, causing an increased risk for cardiovascular diseases, diabetes, and certain types of cancer. Among all cancers, lung cancer is the leading cause of death, whereas pancreatic cancer has the poorest prognosis among all major cancers. Early diagnosis of these cancers can save lives. This dissertation contributes towards the development of computer-aided diagnosis tools in order to aid clinicians in establishing the quantitative relationship between obesity and cancers. With respect to obesity and …

Machine Learning Methods For Flow Cytometry Analysis And Visualization, Emily Sassano

Electronic Theses and Dissertations

Flow cytometry is a popular analytical cell-biology instrument that uses specific wavelengths of light to profile heterogeneous populations of cells at the individual level. Current cytometers have the capability of analyzing up to 20 parameters on over a million cells, but despite the complexity of these datasets, a typical workflow relies on subjective labor-intensive manual sequential analysis. The research presented in this dissertation provides two machine learning methods to increase the objectivity, efficiency, and discovery in flow cytometry data analysis. The first, a supervised learning method, utilizes previously analyzed data to evaluate new flow cytometry files containing similar parameters. The …

Exploring Natural User Abstractions For Shared Perceptual Manipulator Task Modeling & Recovery, Senglee Koh

Electronic Theses and Dissertations

State-of-the-art domestic robot assistants are essentially autonomous mobile manipulators capable of exerting human-scale precision grasps. To maximize utility and economy, non-technical end-users would need to be nearly as efficient as trained roboticists in control and collaboration of manipulation task behaviors. However, it remains a significant challenge given that many WIMP-style tools require superficial proficiency in robotics, 3D graphics, and computer science for rapid task modeling and recovery. But research on robot-centric collaboration has garnered momentum in recent years; robots are now planning in partially observable environments that maintain geometries and semantic maps, presenting opportunities for non-experts to cooperatively control task …

Compiler Design Of A Policy Specification Language For Conditional Gradual Release, Manasa Kashyap Harinath

Electronic Theses and Dissertations

Securing the confidentiality and integrity of information manipulated by computer software is an old yet increasingly important problem. Current software permission systems present on Android or iOS provide inadequate support for developing applications with secure information flow policies. To be useful, information flow control policies need to specify declassifications and the conditions under which declassification must occur. Having these declassifications scattered all over the program makes policies hard to find, which makes auditing difficult. To overcome these challenges, a policy specification language, 'Evidently' is discussed that allows one to specify information flow control policies separately from the program and which …

In-Memory Computing Using Formal Methods And Paths-Based Logic, Alvaro Velasquez

Electronic Theses and Dissertations

The continued scaling of the CMOS device has been largely responsible for the increase in computational power and consequent technological progress over the last few decades. However, the end of Dennard scaling has interrupted this era of sustained exponential growth in computing performance. Indeed, we are quickly reaching an impasse in the form of limitations in the lithographic processes used to fabricate CMOS processes and, even more dire, we are beginning to face fundamental physical phenomena, such as quantum tunneling, that are pervasive at the nanometer scale. Such phenomena manifests itself in prohibitively high leakage currents and process variations, leading …

Assessment Of Information Security Culture In Higher Education, Henry Glaspie

Electronic Theses and Dissertations

Information security programs are instituted by organizations to provide guidance to their users who handle their data and systems. The main goal of these programs is to protect the organization's information assets through the creation and cultivation of a positive information security culture within the organization. As the collection and use of data expands in all economic sectors, the threat of data breach due to human error increases. Employee's behavior towards information security is influenced by the organizations information security programs and the overall information security culture. This study examines the human factors of an information security program and their …

Analysis Of Large-Scale Population Genetic Data Using Efficient Algorithms And Data Structures, Ardalan Naseri

Electronic Theses and Dissertations

With the availability of genotyping data of very large samples, there is an increasing need for tools that can efficiently identify genetic relationships among all individuals in the sample. Modern biobanks cover genotypes up to 0.1%-1% of an entire large population. At this scale, genetic relatedness among samples is ubiquitous. However, current methods are not efficient for uncovering genetic relatedness at such a scale. We developed a new method, Random Projection for IBD Detection (RaPID), for detecting Identical-by-Descent (IBD) segments, a fundamental concept in genetics in large panels. RaPID detects all IBD segments over a certain length in time linear …

Relating First-Person And Third-Person Vision, Shervin Ardeshir Behrostaghi

Electronic Theses and Dissertations

Thanks to the availability and increasing popularity of wearable devices such as GoPro cameras, smart phones and glasses, we have access to a plethora of videos captured from the first person (egocentric) perspective. Capturing the world from the perspective of one's self, egocentric videos bear characteristics distinct from the more traditional third-person (exocentric) videos. In many computer vision tasks (e.g. identification, action recognition, face recognition, pose estimation, etc.), the human actors are the main focus. Hence, detecting, localizing, and recognizing the human actor is often incorporated as a vital component. In an egocentric video however, the person behind the camera …

Examining Users' Application Permissions On Android Mobile Devices, Muhammad Safi

Electronic Theses and Dissertations

Mobile devices have become one of the most important computing platforms. The platform's portability and highly customized nature raises several privacy concerns. Therefore, understanding and predicting user privacy behavior has become very important if one is to design software which respects the privacy concerns of users. Various studies have been carried out to quantify user perceptions and concerns [23,36] and user characteristics which may predict privacy behavior [21,22,25]. Even though significant research exists regarding factors which affect user privacy behavior, there is gap in the literature when it comes to correlating these factors to objectively collected data from user devices. …

Personalized Digital Body: Enhancing Body Ownership And Spatial Presence In Virtual Reality, Sungchul Jung

Electronic Theses and Dissertations

person's sense of acceptance of a virtual body as his or her own is generally called virtual body ownership (VBOI). Having such a mental model of one's own body transferred to a virtual human surrogate is known to play a critical role in one's sense of presence in a virtual environment. Our focus in this dissertation is on top-down processing based on visual perception in both the visuomotor and the visuotactile domains, using visually personalized body cues. The visual cues we study here range from ones that we refer to as direct and others that we classify as indirect. Direct …