Physical Sciences and Mathematics Commons^™

Stochastic Orthogonalization And Its Application To Machine Learning, Yu Hong

Electrical Engineering Theses and Dissertations

Orthogonal transformations have driven many great achievements in signal processing. They simplify computation and stabilize convergence during parameter training. Researchers have introduced orthogonality to machine learning recently and have obtained some encouraging results. In this thesis, three new orthogonal constraint algorithms based on a stochastic version of an SVD-based cost are proposed, which are suited to training large-scale matrices in convolutional neural networks. We have observed better performance in comparison with other orthogonal algorithms for convolutional neural networks.

Automating Software Changes Via Recommendation Systems, Xiaoyu Liu

Computer Science and Engineering Theses and Dissertations

As the complexity of software systems is growing tremendously, it came with increasingly sophisticated data provided during development. The systematic and large-scale accumulation of software engineering data opened up new opportunities that infer information appropriately can be helpful to software development in a given context. This type of intelligent software development tools came to be known as recommendation systems.

Recommendation Systems in Software Change (RSSCs) share commonalities with conventional recommendation systems: mainly in their usage model, the usual reliance on data mining, and in the predictive nature of their functionality. So a major challenge for designing RSSCs is to automatically …

A Study On The Mental Health Of Women In The Csse Department Of California Polytechnic State University, Sophia Lao, Gabriella Garcia Nobili

Computer Science and Software Engineering

The goal of this paper is to explore the perceived effect that the Computer Science Curriculum has on the mental health of female students. To discover these effects we conducted 50 interviews over a period of several months with the female students of the Computer Science and Software Engineering (CSSE) department at California Polytechnic State University in San Luis Obispo. The total amount of Computer Science (CSC) majors at this institution is approximately 680, with 150 of them being female, so we were able to gather responses from 33.3% of the female CSC students from our interviews. It is worth …

Arkansas' Coding For All - Is It Really Reaching All Students?, Kaitlin Mckenzie

Computer Science and Computer Engineering Undergraduate Honors Theses

The Arkansas Computer Science Initiative required every high school to offer at least one computer science course by the 2015-16 academic year. Schools that did not have a qualified teacher were given access to online courses. It is important to point out that students do not need a computer science course to graduate, but credit in a computer science course could replace a 3rd science credit requirement or a 4th math credit requirement (ADE / ARCareerED Computer Science Fact Sheet). Some initial success has already been demonstrated. In 2014- 15 there were sixty computer science classes offered in all of …

Take Note: An Investigation Of The Impact Of Human Computer Interaction On The Line Note Taking Process In Theatre, Rene Borr

Computer Science

Most technology used in the theatre was not originally designed for use in a theatrical setting. A majority of technology that we see on the state has been adapted from another field -- be it music, lighting, or construction -- to fit the production's specifics needs. The very nature of the theatre is that every performance is unique, which established one of the main challenges when creating technology to be used in the theatrical setting. This paper discusses the design, creation, and testing of a program to help stage managers take line notes during rehearsal for a theatrical production. We …

Analyzing Public View Towards Vaccination Using Twitter, Mahajan Rutuja

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Educating people about vaccination tends to target vaccine acceptance and reduction of hesitancy. Social media provides a promising platform for studying public perception regarding vaccination. In this study, we harvested tweets over a year related to vaccines from February 2018 to January 2019. We present a two-stage classifier to: (1) classify the tweets as relevant or non-relevant and (2) categorize them in terms of pro-vaccination, anti-vaccination, or neutral outlook. We found that the classifier was able to distinguish clearly between anti-vaccination and pro-vaccination tweets, but also misclassified many of these as neutral. Using Latent Dirichlet Allocation, we found that two …

Opioid Misuse Detection In Hospitalized Patients Using Convolutional Neural Networks, Brihat Sharma

Master's Theses

Opioid misuse is a major public health problem in the world. In 2016, 11.3 million people were reported to misuse opioids in the US only. Opioid-related inpatient and emergency department visits have increased by 64 percent and the rate of opioid-related visits has nearly doubled between 2009 and 2014. It is thus critical for healthcare systems to detect opioid misuse cases. Patients hospitalized for consequences of their opioid misuse present an opportunity for intervention but better screening and surveillance methods are needed to guide providers. The current screening methods with self-report questionnaire data are time-consuming and difficult to perform in …

Usability Engineering Of A Privacy-Aware Compliance Tracking System, Parameswara Reddy Annapureddy

ETD Archive

Software is useful when it is able to provide useful information to the end user with minimum effort. This thesis is about usability improvements to a privacy-aware human motion tracking system for healthcare professionals. The original system has a number of usability issues: (1) Users need to wear a smartwatch, which will be used to connect to the system; (2) Data are stored in XML, comma-separated-value format which is very difficult to analyze; (3) Data are available only at the local computer and there is no easy way to access them remotely via a Web or mobile interface; (4) Analysis …

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …

A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay

Electronic Theses and Dissertations

The proliferation of mobile devices in the BRIC countries has prompted them to develop policies to manage the security of these devices. In China, mobile devices are a primary tool for payments. As a result, China instituted in 2017 a cyber security policy that applies to mobile devices giving China broad authority to manage cyber threats. The United States has a similar need for a cyber policy. Mobile devices are likely to become a primary payment tool in the United States soon. DHS has also identified a need for more effective security policy in mobile devices for government operations. This …

Probabilistic Record Linkage With Elliptic Curve Operations, Shreya Dhiren Patel

Electronic Theses and Dissertations

Federated query processing for an electronic health record infrastructure enables large epidemiology studies using data integrated from geographically dispersed medical institutions. However, government imposed privacy regulations prohibit disclosure of patient's health record outside the context of clinical care, thereby making it difficult to determine which records correspond to the same entity in the process of query aggregation.

Privacy-preserving record linkage is an actively pursued research area to facilitate the linkage of database records under the constraints of regulations that do not allow the linkage agents to learn sensitive identities of record owners. In earlier works, scalability has been shown to …

Evaluating Software Testing Techniques: A Systematic Mapping Study, Mitchell Mayeda

Electronic Theses and Dissertations

Software testing techniques are crucial for detecting faults in software and reducing the risk of using it. As such, it is important that we have a good understanding of how to evaluate these techniques for their efficiency, scalability, applicability, and effectiveness at finding faults. This thesis enhances our understanding of testing technique evaluations by providing an overview of the state of the art in research. To accomplish this we utilize a systematic mapping study; structuring the field and identifying research gaps and publication trends. We then present a small case study demonstrating how our mapping study can be used to …

Applied Machine Learning For Classification Of Musculoskeletal Inference Using Neural Networks And Component Analysis, Shaswat Sharma

Electronic Theses and Dissertations

Artificial Intelligence (AI) is acquiring more recognition than ever by researchers and machine learning practitioners. AI has found significance in many applications like biomedical research for cancer diagnosis using image analysis, pharmaceutical research, and, diagnosis and prognosis of diseases based on knowledge about patients' previous conditions. Due to the increased computational power of modern computers implementing AI, there has been an increase in the feasibility of performing more complex research.

Within the field of orthopedic biomechanics, this research considers complex time-series dataset of the "sit-to-stand" motion of 48 Total Hip Arthroplasty (THA) patients that was collected by the Human Dynamics …

Application Of Retrograde Analysis To Fighting Games, Kristen Yu

Electronic Theses and Dissertations

With the advent of the fighting game AI competition, there has been recent interest in two-player fighting games. Monte-Carlo Tree-Search approaches currently dominate the competition, but it is unclear if this is the best approach for all fighting games. In this thesis we study the design of two-player fighting games and the consequences of the game design on the types of AI that should be used for playing the game, as well as formally define the state space that fighting games are based on. Additionally, we also characterize how AI can solve the game given a simultaneous action game model, …

The D&D Sorting Hat: Predicting Dungeons And Dragons Characters From Textual Backstories, Joseph C. Macinnes

Senior Independent Study Theses

Dungeons and Dragons is a tabletop roleplaying game which focuses heavily on character interaction and creating narratives. The current state of the game's character creation process often bogs down new players in decisions related to game mechanics, not a character's identity and personality. This independent study investigates the use of machine learning and natural language processing to make these decisions for a player based on their character's backstory - the textual biography or description of a character. The study presents a collection of existing characters and uses these examples to create a family of models capable of predicting a character's …

A Hott Approach To Computational Effects, Phillip A. Wells

Senior Independent Study Theses

A computational effect is any mutation of real-world state that occurs as the result of a computation. We develop a model for describing computational effects within homotopy type theory, a branch of mathematics separate from other foundations such as set theory. Such a model allows us to describe programs as total functions over values while preserving information about the effects those programs induce.

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

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The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches …

Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat

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Information Extraction (IE) techniques are developed to extract entities, relationships, and other detailed information from unstructured text. The majority of the methods in the literature focus on designing supervised machine learning techniques, which are not very practical due to the high cost of obtaining annotations and the difficulty in creating high quality (in terms of reliability and coverage) gold standard. Therefore, semi-supervised and distantly-supervised techniques are getting more traction lately to overcome some of the challenges, such as bootstrapping the learning quickly. This dissertation focuses on information extraction, and in particular entities, i.e., Named Entity Recognition (NER), from multiple domains, …

Leveraging Blockchain To Mitigate The Risk Of Counterfeit Microelectronics In Its Supply Chain, Aman Ali Pogaku

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System on Chip (SoC) is the backbone component of the electronics industry nowadays. ASIC and FPGA-based SoCs are the two most popular methods of manufacturing SoCs. However, both ASIC and FPGA industries are plagued with risks of counterfeits due to the limitations in Security, Accountability, Complexity, and Governance of their supply chain management. As a result, the current practices of these microelectronics supply chain suffer from performance and efficiency bottlenecks. In this research, we are incorporating blockchain technology into the FPGA and ASIC microelectronic supply chain to help mitigate the risk of counterfeit microelectronics through a secure and decentralized solution …

Design And Development Of An Immersive Simulation For Social Determinants Of Health Training, Lahari Surapaneni

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This thesis research project focuses on design and development of an immersion simulation-based training tool that help raise the social determinants of health (SDOH) awareness among the health care providers. Compared to existing classroom lecture and/or role-play based SDOH education approach, our immersion-simulation based approach provides an easy access and highly realistic experience to such training curriculum at anytime and anywhere with an Internet connection. Such an interactive and immersive exposure is critical to raise SDOH awareness and maintain long-lasting empathy towards actual patients in practice, and thus help providers to be better prepared when encountering with those patients. Particularly, …

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

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The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar

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Navigating in a Virtual Environment with traditional input devices such as mouse, joysticks and keyboards provide limited maneuverability and is also time consuming. While working in a virtual environment, changing parameters to obtain the desired visualization requires time to achieve by manually entering parameter values in an algorithm to test outcomes. The following thesis presents an alternate user interface to reduce user efforts, while navigating within the Virtual Environment. The user interface is an Android application which is designed to accommodate spoken commands. This Speech Enabled User Interface termed as the Speech Navigation Application (SNA), provides the user with an …

Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma

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With massive data collections and needs for building powerful predictive models, data owners may choose to outsource storage and expensive machine learning computations to public cloud providers (Cloud). Data owners may choose cloud outsourcing due to the lack of in-house storage and computation resources or the expertise of building models. Similarly, users, who subscribe to specialized services such as movie streaming and social networking, voluntarily upload their data to the service providers' site for storage, analytics, and better services. The service provider, in turn, may also choose to benefit from ubiquitous cloud computing. However, outsourcing to a public cloud provider …

Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu

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According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online harassment detection is vital for securing and sustaining the popularity and viability of online social networks. Machine learning techniques play a crucial role in automatic harassment detection. One of the challenges of using supervised approaches is training data imbalance. Existing text generation techniques can help augment the training data, but they are still inadequate and ineffective. This research explores the role of domain-specific knowledge to complement the limited training data available for training a text …

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

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Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to design …

Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter

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In recent years embedded devices have become more ubiquitous than ever before and are expected to continue this trend. Embedded devices typically have a singular or more focused purpose, a smaller footprint, and often interact with the physical world. Some examples include routers, wearable heart rate monitors, and thermometers. These devices are excellent at providing real time data or completing a specific task quickly, but they lack many features that make security issues more obvious. Generally, Embedded devices are not easily secured. Malware or rootkits in the firmware of an embedded system are difficult to detect because embedded devices do …

Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella

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Over the years, the semantic web has emerged as a new generation of the world wide web featuring advanced technologies and research contributions. It has revolutionized the usage of information by allowing users to capture and publish machine-understandable data and expedite methods such as ontologies to perform the same. These ontologies help in the formal representation of a specified domain and foster comprehensive machine understanding. Although, the engineering of ontologies and usage of logic have been an integral part of the web semantics, new areas of research such as the semantic web search, linking and usage of open data on …

Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander

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Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards …

Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines

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This thesis describes the tools for studying different design prototypes. The goal was to develop effective tools to study these designs using a data-driven approach. “Proof of concept” experiments were conducted, in which participants were allowed to interact with a virtual environment depicting different designs as data pertaining to their virtual location and orientation was recorded for later analysis. The designs included “flat” store racks, as opposed to racks with more varied shapes, as well as “curved” racks. Focus of the design studies was to assist in identifying optimal locations for different product types. The automated data collection mechanisms required …

Llvm-Ir Based Decompilation, Ilsoo Jeon

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Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The …