Computer Sciences Commons^™

Signal Structure For A Class Of Nonlinear Dynamic Systems, Meilan Jin

Theses and Dissertations

The signal structure is a partial structure representation for dynamic systems. It characterizes the causal relationship between manifest variables and is depicted in a weighted graph, where the weights are dynamic operators. Earlier work has defined signal structure for linear time-invariant systems through dynamical structure function. This thesis focuses on the search for the signal structure of nonlinear systems and proves that the signal structure reduces to the linear definition when the systems are linear. Specifically, this work: (1) Defines the complete computational structure for nonlinear systems. (2) Provides a process to find the complete computational structure given a state …

Blockchain: Technical Review, Evan D. Poff

Marriott Student Review

This review of blockchain technology accompanies the article "Strategic Implications of Blockchain."

Buzzwords, Evan D. Poff

Marriott Student Review

This feature will explain the following buzzwords:

• Blockchain
• Cryptocurrency
• Work-Life Integration
• Passive Equities
• Risk-Adjusted Returns

A Large-Scale Analysis Of How Openssl Is Used In Open-Source Software, Scott Jared Heidbrink

Theses and Dissertations

As vulnerabilities become more common the security of applications are coming under increased scrutiny. In regards to Internet security, recent work discovers that many vulnerabilities are caused by TLS library misuse. This misuse is attributed to large and confusing APIs and developer misunderstanding of security generally. Due to these problems there is a desire for simplified TLS libraries and security handling. However, as of yet there is no analysis of how the existing APIs are used, beyond how incorrect usage motivates the need to replace them. We provide an analysis of contemporary usage of OpenSSL across 410 popular secure applications. …

Suggesting Missing Information In Text Documents, Grant Michael Hodgson

Theses and Dissertations

A key part of contract drafting involves thinking of issues that have not been addressedand adding language that will address the missing issues. To assist attorneys with this task, we present a pipeline approach for identifying missing information within a contract section. The pipeline takes a contract section as input and includes 1) identifying sections that are similar to the input section from a corpus of contract sections; and 2) identifying and suggesting information from the similar sections that are missing from the input section. By taking advantage of sentence embedding and principal component analysis, this approach suggests sentences that …

A Coverage Metric To Aid In Testing Multi-Agent Systems, Jane Ostergar Linn

Theses and Dissertations

Models are frequently used to represent complex systems in order to test the systems before they are deployed. Some of the most complicated models are those that represent multi-agent systems (MAS), where there are multiple decision makers. Brahms is an agent-oriented language that models MAS. Three major qualities affect the behavior of these MAS models: workframes that change the state of the system, communication activities that coordinate information between agents, and the schedule of workframes. The primary method to test these models that exists is repeated simulation. Simulation is useful insofar as interesting test cases are used that enable the …

Shadow Patching: Exemplar-Based Shadow Removal, Ryan Sears Hintze

Theses and Dissertations

Shadow removal is an important problem for both artists and algorithms. Previous methods handle some shadows well but, because they rely on the shadowed data, perform poorly in cases with severe degradation. Image-completion algorithms can completely replace severely degraded shadowed regions, and perform well with smaller-scale textures, but often fail to reproduce larger-scale macrostructure that may still be visible in the shadowed region. This paper provides a general framework that leverages degraded (e.g., shadowed) data to guide the image completion process by extending the objective function commonly used in current state-of-the-art image completion energy-minimization methods. This approach achieves realistic shadow …

Recommender Systems For Family History Source Discovery, Derrick James Brinton

Theses and Dissertations

As interest in family history research increases, greater numbers of amateurs are participating in genealogy. However, finding sources that provide useful information on individuals in genealogical research is often an overwhelming task, even for experts. Many tools assist genealogists in their work, including many computer-based systems. Prior to this work, recommender systems had not yet been applied to genealogy, though their ability to navigate patterns in large amounts of data holds great promise for the genealogical domain. We create the Family History Source Recommender System to mimic human behavior in locating sources of genealogical information. The recommender system is seeded …

Usable Secure Email Through Short-Lived Keys, Tyler Jay Monson

Theses and Dissertations

Participants from recent secure email user studies have expressed a need to use secure email tools only a few times a year. At the same time, Internet users are expressing concerns over the permanence of personal information on the Internet. Support for short-lived keys has the potential to address both of these problems. However, the short-lived keys usability and security space is underdeveloped and unexplored. In this thesis, we present an exploration of the short-lived keys usability and security design space. We implement both a short-lived keys and a long-term keys secure email prototype. With these two prototypes, we conduct …

Time Reversed Smoke Simulation, Jeremy Michael Oborn

Theses and Dissertations

Physics-based fluid simulation often produces unpredictable behavior that is difficult for artists to control. We present a new method for art directing smoke animation using time reversed simulation. Given a final fluid configuration, our method steps backward in time generating a sequence that, when played forward, is visually similar to traditional forward simulations. This will give artists better control by allowing them to start from any timestep of the simulation. We address a number of challenges associated with time reversal including generating a believable final configuration and reversing entropy.

The Human Touch: How Non-Expert Users Perceive, Interpret, And Fix Topic Models, Tak Yeon Lee, Alison Smith, Kevin Seppi, Niklas Elmqvist, Jordan Boyd-Graber, Leah Findlater

Faculty Publications

Topic modeling is a common tool for understanding large bodies of text, but is typically provided as a “take it or leave it” proposition. Incorporating human knowledge in unsupervised learning is a promising approach to create high-quality topic models. Existing interactive systems and modeling algorithms support a wide range of refinement operations to express feedback. However, these systems’ interactions are primarily driven by algorithmic convenience, ignoring users who may lack expertise in topic modeling. To better understand how non-expert users understand, assess, and refine topics, we conducted two user studies—an in-person interview study and an online crowdsourced study. These studies …

The Annotation Cost Of Context Switching: How Topic Models And Active Learning [May Not] Work Together, Nozomu Okuda

Theses and Dissertations

The labeling of language resources is a time consuming task, whether aided by machine learning or not. Much of the prior work in this area has focused on accelerating human annotation in the context of machine learning, yielding a variety of active learning approaches. Most of these attempt to lead an annotator to label the items which are most likely to improve the quality of an automated, machine learning-based model. These active learning approaches seek to understand the effect of item selection on the machine learning model, but give significantly less emphasis to the effect of item selection on the …

A General-Purpose Animation System For 4d, Justin Alain Jensen

Theses and Dissertations

Computer animation has been limited almost exclusively to 2D and 3D. The tools for 3D computer animation have been largely in place for decades and are well-understood. Existing tools for visualizing 4D geometry include minimal animation features. Few tools have been designed specifically for animation of higher-dimensional objects, phenomena, or spaces. None have been designed to be familiar to 3D animators. A general-purpose 4D animation system can be expected to facilitate more widespread understanding of 4D geometry and space, can become the basis for creating unique 3D visual effects, and may offer new insight into 3D animation concepts. We have …

Improving Gamification By Leveraging Endogenous Value, Brennan Laurence Smith

Theses and Dissertations

"Gamification" is the application of game design principles to non-game contexts, such as education, personal fitness, etc. Gamification's intent is to incentivize unpalatable tasks. Current gamification efforts in the industry use some features traditionally associated with games, but fail to use game design principles as defined by the games industry. One such principle is endogenous rewards for task completion. We propose that endogenous rewards will increase the efficacy of gamification by increasing user engagement and retention. To demonstrate, we create a gamification framework where the rewards for completing real-life tasks are items with high endogenous value in the game, incentivizing …

A Novel Approach To A Big Simulation Problem: Creating Efficient Dry Granular Material Simulations With Accurate Visual Detail And Behavior, Seth Holladay

Journal of Undergraduate Research

We received a MEG grant for researching the simulation of granular materials for computer graphics and animation. Materials such as sand and snow simulation is very expensive but necessary for productions, as well as hard to control the look, so I have been mentoring undergraduate and graduate students researching how to make sand simulations both efficient and art directable.

Calculating Music Similarity With Mobile Device Playlists, Jacob O'Bryant, Dennis Ng

Journal of Undergraduate Research

Music recommendation systems, such as Pandora and Spotify, help listeners to discover new music. The similarity of different songs is an important measure used in music recommendation. We have studied manually-created playlists on mobile devices to see if they can be used to accurately calculate song similarity. We collected playlists from 41 research subjects and used a co-occurrence model to calculate similarity between songs in the collection.

Utilizing The Power Of Graphical Processing For Dna Mapping: A Comparison Of Gnumap And Barracuda, Cole Lyman, Mark Clement

Journal of Undergraduate Research

Recent advances in genome sequencing technologies have resulted in a large increase in the amount of genetic data available. Large Genome Wide Association Studies (GWAS) have the potential to identify the causes of cancer, Alzheimer’s disease, heart failure and many other diseases if the large quantities of data that are becoming available can be analyzed effectively. Next-generation read mapping software, a crucial step in analyzing genetic data, is slow while trying to achieve high mapping accuracy. One approach to speeding up next-generation read mapping focuses on using Graphical Processing Units (GPUs). This project compared the effectiveness of two genome mappers, …

The Ogcleaner: Detecting False-Positive Sequence Homology, Masaki Stanley Fujimoto

Theses and Dissertations

Within bioinformatics, phylogenetics is the study of the evolutionary relationships between different species and organisms. The genetic revolution has caused an explosion in the amount of raw genomic information that is available to scientists for study. While there has been an explosion in available data, analysis methods have lagged behind. A key task in phylogenetics is identifying homology clusters. Current methods rely on using heuristics based on pairwise sequence comparison to identify homology clusters. We propose the Orthology Group Cleaner (the OGCleaner) as a method to evaluate cluster level verification of putative homology clusters in order to create higher quality …

Using Multiview Annotation To Annotate Multiple Images Simultaneously, Timothy C. Price

Theses and Dissertations

In order for a system to learn a model for object recognition, it must have a lot of positive images to learn from. Because of this, datasets of similar objects are built to train the model. These object datasets used for learning models are best when large, diverse and have annotations. But the process of obtaining the images and creating the annotations often times take a long time, and are costly. We use a method that obtains many images of the same objects in different angles very quickly and then reconstructs those images into a 3D model. We then use …

Informing The Use Of Hyper-Parameter Optimization Through Meta-Learning, Samantha Corinne Sanders

Theses and Dissertations

One of the challenges of data mining is finding hyper-parameters for a learning algorithm that will produce the best model for a given dataset. Hyper-parameter optimization automates this process, but it can still take significant time. It has been found that hyperparameter optimization does not always result in induced models with significant improvement over default hyper-parameters, yet no systematic analysis of the role of hyper-parameter optimization in machine learning has been conducted. We propose the use of meta-learning to inform the decision to optimize hyper-parameters based on whether default hyper-parameter performance can be surpassed in a given amount of time. …

Diversity And Efficiency: An Unexpected Result, Joseph Smith Johnson

Theses and Dissertations

Empirical evidence shows that ensembles with adequate levels of pairwise diversity among a set of accurate member algorithms significantly outperform any of the individual algorithms. As a result, several diversity measures have been developed for use in optimizing ensembles. We show that diversity measures that properly combine the diversity space in an additive and multiplicative manner, not only result in ensembles whose accuracy is comparable to the naive ensemble of choosing the most accurate learners, but also results in ensembles that are significantly more efficient than such naive ensembles. In addition to diversity measures found in the literature, we submit …

Robust Object Tracking: A Path-Planning Approach, Bryant Eldon Chandler

Theses and Dissertations

When attempting to follow ground-based moving objects (hereafter referred to as ``waldos'') using an unmanned air vehicle (UAV), occlusion can become a significant problem for computer vision algorithms designed to track the object. When a waldo is occluded, the computer vision algorithm loses the track and the UAV's ability to predict movement degrades. We propose a path-planning and replanning method that moves a UAV to a location that maximizes the important waldos that can be seen while accounting for occlusion, and attempts to maximize the area it can see during travel. The proposed work moves beyond state-of-the-art algorithms designed to …

Network Reconstruction And Vulnerability Analysis Of Financial Networks, Nathan Scott Woodbury

Theses and Dissertations

Passive network reconstruction is the process of learning a structured (networked) representation of a dynamic system through the use of known information about the structure of the system as well as data collected by observing the inputs into a system along with the resultant outputs. This work demonstrates an improvement on an existing network reconstruction algorithm so that the algorithm is capable of consistently and perfectly reconstructing a network when system inputs and outputs are measured without error. This work then extends the improved network reconstruction algorithm so that it functions even in the presence of noise as well as …

A Green Form-Based Information Extraction System For Historical Documents, Tae Woo Kim

Theses and Dissertations

Many historical documents are rich in genealogical facts. Extracting these facts by hand is tedious and almost impossible considering the hundreds of thousands of genealogically rich family-history books currently scanned and online. As one approach for helping to make the extraction feasible, we propose GreenFIE—a "Green" Form-based Information-Extraction tool which is "green" in the sense that it improves with use toward the goal of minimizing the cost of human labor while maintaining high extraction accuracy. Given a page in a historical document, the user's task is to fill out given forms with all facts on a page in a document …

Right Now Is The Wrong Time: And Other Considerations When Presenting Security Warnings, Brock Johanson, Bonnie Anderson

Journal of Undergraduate Research

Neuro Information Security (NeuroIS) focuses on the use of neurological measurements to improve the security of information systems. The BYU NeuroIS lab uses neurological tools and measurements to examine factors that affect security outcomes. Previous work has focused on various factors such as dual task interference (DTI), threat assessment, as well as factors such as habituation and generalization, which have become focus streams of research. The primary point of failure in most security related incidents tends to be users themselves. As such, anything that can be used to overcome neurobiological phenomenon such as those listed above can ultimately lead in …

Mobile Hands: What Your Phone Use Says About You, Parker Williams, Jeff Jenkins

Journal of Undergraduate Research

The percentage of individuals using mobile phones to respond to online applications, forms, and surveys is predicted to rapidly increase in the future. As of June 2, 2015, there were an estimated 2.6 billion smartphones in use in the world; by 2020 there will be 6.1 billion smartphones in use. Smartphones will account for roughly 80% of all mobile driven data traffic by 2020 (Lunden, 2015). With the proliferation of smartphones, measuring the fidelity of information gathered from and about the user becomes extremely important. Smartphones are a rich source of behavioral and biometric information, gathering data about how the …

Intelligent Stitching: Transforming Offline Stroke Extraction For Online Handwriting Recognition, Curtis Wigington, William Barrett

Journal of Undergraduate Research

Images of historical documents are being collected and archived much faster than volunteers can possibly index them alone. Improvements in offline handwriting recognition could greatly accelerate the work of indexing by FamilySearch. Offline handwriting recognition has already been shown to be effective in assisting indexers and automating the transcription of historical documents into searchable texts. As documents are collected from all around the world, generalized techniques that are robust to damage and noise are needed. Effective stroke extraction and processing is an important tool in improving current recognition techniques.

Theory And Applications Of Network Structure Of Complex Dynamical Systems, Vasu Nephi Chetty

Theses and Dissertations

One of the most powerful properties of mathematical systems theory is the fact that interconnecting systems yields composites that are themselves systems. This property allows for the engineering of complex systems by aggregating simpler systems into intricate patterns. We call these interconnection patterns the "structure" of the system. Similarly, this property also enables the understanding of complex systems by decomposing them into simpler parts. We likewise call the relationship between these parts the "structure" of the system. At first glance, these may appear to represent identical views of structure of a system. However, further investigation invites the question: are these …

"I Can Physically Feel The Difference": Exploring Physicalizations Of Running Data, Zann Benjamin Anderson

Theses and Dissertations

We explore user interactions with concrete physical visualizations—physicalizations—of personal experiential data. We conducted three user studies involving physicalizations of data gathered while trail running—a sport in which participants are largely more focused on the experience than the exercise itself. In two qualitative studies, we asked trail runners to give us a GPS path from a "significant run" and then prepared a 3D physicalization featuring the path overlaid as a raised line on the corresponding real-world terrain. In the first, physicalizations had a significant impact in helping participants recall memories of their experiences, and participants shared many stories. In a follow-up …

A Semi-Automatic Grading Experience For Digital Ink Quizzes, Brooke Ellen Rhees

Theses and Dissertations

Teachers who want to assess student learning and provide quality feedback are faced with a challenge when trying to grade assignments quickly. There is currently no system which will provide both a fast-to-grade quiz and a rich testing experience. Previous attempts to speed up grading time include NLP-based text analysis to automate grading and scanning in documents for manual grading with recyclable feedback. However, automated NLP systems all focus solely on text-based problems, and manual grading is still linear in the number of students. Machine learning algorithms exist which can interactively train a computer quickly classify digital ink strokes. We …