Matching Items (37)
Description
Modern, advanced statistical tools from data mining and machine learning have become commonplace in molecular biology in large part because of the “big data” demands of various kinds of “-omics” (e.g., genomics, transcriptomics, metabolomics, etc.). However, in other fields of biology where empirical data sets are conventionally smaller, more traditional statistical methods of inference are still very effective and widely used. Nevertheless, with the decrease in cost of high-performance computing, these fields are starting to employ simulation models to generate insights into questions that have been elusive in the laboratory and field. Although these computational models allow for exquisite control over large numbers of parameters, they also generate data at a qualitatively different scale than most experts in these fields are accustomed to. Thus, more sophisticated methods from big-data statistics have an opportunity to better facilitate the often-forgotten area of bioinformatics that might be called “in-silicomics”.
As a case study, this thesis develops methods for the analysis of large amounts of data generated from a simulated ecosystem designed to understand how mammalian biomechanics interact with environmental complexity to modulate the outcomes of predator–prey interactions. These simulations investigate how other biomechanical parameters relating to the agility of animals in predator–prey pairs are better predictors of pursuit outcomes. Traditional modelling techniques such as forward, backward, and stepwise variable selection are initially used to study these data, but the number of parameters and potentially relevant interaction effects render these methods impractical. Consequently, new modelling techniques such as LASSO regularization are used and compared to the traditional techniques in terms of accuracy and computational complexity. Finally, the splitting rules and instances in the leaves of classification trees provide the basis for future simulation with an economical number of additional runs. In general, this thesis shows the increased utility of these sophisticated statistical techniques with simulated ecological data compared to the approaches traditionally used in these fields. These techniques combined with methods from industrial Design of Experiments will help ecologists extract novel insights from simulations that combine habitat complexity, population structure, and biomechanics.
As a case study, this thesis develops methods for the analysis of large amounts of data generated from a simulated ecosystem designed to understand how mammalian biomechanics interact with environmental complexity to modulate the outcomes of predator–prey interactions. These simulations investigate how other biomechanical parameters relating to the agility of animals in predator–prey pairs are better predictors of pursuit outcomes. Traditional modelling techniques such as forward, backward, and stepwise variable selection are initially used to study these data, but the number of parameters and potentially relevant interaction effects render these methods impractical. Consequently, new modelling techniques such as LASSO regularization are used and compared to the traditional techniques in terms of accuracy and computational complexity. Finally, the splitting rules and instances in the leaves of classification trees provide the basis for future simulation with an economical number of additional runs. In general, this thesis shows the increased utility of these sophisticated statistical techniques with simulated ecological data compared to the approaches traditionally used in these fields. These techniques combined with methods from industrial Design of Experiments will help ecologists extract novel insights from simulations that combine habitat complexity, population structure, and biomechanics.
ContributorsSeto, Christian (Author) / Pavlic, Theodore (Thesis advisor) / Li, Jing (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2018
Description
Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as many games as possible, however they also need to grow their program by training and retaining new players. The purpose of this project was to create a prototype statistical tool that maximizes a player line-up's probability of scoring the next point, while having as equal playing time across all experienced and novice players as possible. Game, player, and team data was collected for 25 different games played over the course of 4 tournaments during Fall 2017 and early Spring 2018 using the UltiAnalytics iPad application. "Amount of Top 1/3 Players" was the measure of equal playing time, and "Line Efficiency" and "Line Interaction" represented a line's probability of scoring. After running a logistic regression, Line Efficiency was found to be the more accurate predictor of scoring outcome than Line Interaction. An "Equal PT Measure vs. Line Efficiency" graph was then created and the plot showed what the optimal lines were depending on what the user's preferences were at that point in time. Possible next steps include testing the model and refining it as needed.
ContributorsSpence, Andrea Nicole (Author) / McCarville, Daniel R. (Thesis director) / Pavlic, Theodore (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper outlines the development of a software application that explores the plausibility and potential of interacting with three-dimensional sound sources within a virtual environment. The intention of the software application is to allow a user to become engaged with a collection of sound sources that can be perceived both graphically and audibly within a spatial, three-dimensional context. The three-dimensional sound perception is driven primarily by a binaural implementation of a higher order ambisonics framework while graphics and other data are processed by openFrameworks, an interactive media framework for C++. Within the application, sound sources have been given behavioral functions such as flocking or orbit patterns, animating their positions within the environment. The author will summarize the design process and rationale for creating such a system and the chosen approach to implement the software application. The paper will also provide background approaches to spatial audio, gesture and virtual reality embodiment, and future possibilities for the existing project.
ContributorsBurnett, Garrett (Author) / Paine, Garth (Thesis director) / Pavlic, Theodore (Committee member) / School of Humanities, Arts, and Cultural Studies (Contributor) / School of Arts, Media and Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Effective communication and engineering are not a natural pairing. The incongruence is because engineering students are focused on making, designing and analyzing. Since these are the core functions of the field there is not a direct focus on developing communication skills. This honors thesis explores the role and expectations for student engineers within the undergraduate engineering education experience to present and communicate ideas. The researchers interviewed faculty about their perspective on students' abilities with respect to their presentation skills to inform the design of a workshop series of interventions intended to make engineering students better communicators.
ContributorsAlbin, Joshua Alexander (Co-author) / Brancati, Sara (Co-author) / Lande, Micah (Thesis director) / Martin, Thomas (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Simulation games are widely used in engineering education, especially for industrial engineering and operations management. A well-made simulation game aids in achieving learning objectives for students and minimal additional teaching by an instructor. Many simulation games exist for engineering education, but newer technologies now exist that improve the overall experience of developing and using these games. Although current solutions teach concepts adequately, poorly-maintained platforms distract from the key learning objectives, detracting from the value of the activities. A backend framework was created to facilitate an educational, competitive, participatory simulation of a manufacturing system that is intended to be easy to maintain, deploy, and expand.
ContributorsChandler, Robert Keith (Author) / Clough, Michael (Thesis director) / Pavlic, Theodore (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Temnothorax ants are a model species for studying collective decision-making. When presented with multiple nest sites, they are able to collectively select the best one and move the colony there. When a scout encounters a nest site, she will spend some time exploring it. In theory she should explore the site for long enough to determine both its quality and an estimate of the number of ants there. This ensures that she selects a good nest site and that there are enough scouts who know about the new nest site to aid her in relocating the colony. It also helps to ensure that the colony reaches a consensus rather than dividing between nest sites. When a nest site reaches a certain threshold of ants, a quorum has been reached and the colony is committed to that nest site. If a scout visits a good nest site where a quorum has not been reached, she will lead a tandem run to bring another scout there so that they can learn the way and later aid in recruitment. At a site where a quorum has been reached, scouts will instead perform transports to carry ants and brood there from the old nest. One piece that is missing in all of this is the mechanism. How is a quorum sensed? One hypothesis is that the encounter rate (average number of encounters with nest mates per second) that an ant experiences at a nest site allows her to estimate the population at that site and determine whether a quorum has been reached. In this study, encounter rate and entrance time were both shown to play a role in whether an ant decided to lead a tandem run or perform a transport. Encounter rate was shown to have a significant impact on how much time an ant spent at a nest site before making her decision, and encounter rates significantly increased as migrations progressed. It was also shown to individual ants did not differ from each other in their encounter rates, visit lengths, or entrance times preceding their first transports or tandem runs, studied across four different migrations. Ants were found to spend longer on certain types of encounters, but excluding certain types of encounters from the encounter rate was not found to change the correlations that were observed. It was also found that as the colony performed more migrations, it became significantly faster at moving to the new nest.
ContributorsJohnson, Christal Marie (Author) / Pratt, Stephen (Thesis director) / Pavlic, Theodore (Committee member) / Shaffer, Zachary (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
The first step in process improvement is to scope the problem, next is measure the current process, but if data is not readily available and cannot be manually collected, then a measurement system must be implemented. General Dynamics Mission Systems (GDMS) is a lean company that is always seeking to improve. One of their current bottlenecks is the incoming inspection department. This department is responsible for finding defects on parts purchased and is critical to the high reliability product produced by GDMS. To stay competitive and hold their market share, a decision was made to optimize incoming inspection. This proved difficult because no data is being collected. Early steps in many process improvement methodologies, such as Define, Measure, Analyze, Improve and Control (DMAIC), include data collection; however, no measurement system was in place, resulting in no available data for improvement. The solution to this problem was to design and implement a Management Information System (MIS) that will track a variety of data. This will provide the company with data that will be used for analysis and improvement. The first stage of the MIS was developed in Microsoft Excel with Visual Basic for Applications because of the low cost and overall effectiveness of the software. Excel allows update to be made quickly, and allows GDMS to collect data immediately. Stage two would be moving the MIS to a more practicable software, such as Access or MySQL. This thesis is only focuses on stage one of the MIS, and GDMS will proceed with stage two.
ContributorsDiaz, Angel (Author) / McCarville, Daniel R. (Thesis director) / Pavlic, Theodore (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Revenue management (RM) attempts to understand and shape consumer behavior to maximize revenue from a perishable resource. Various algorithms can be used to control bid-prices, and subsequently, perform differently with respect to the total network revenue that they generate. There is currently a need for some method to compare RM engines; a simulation can fulfill this need.
The first module of this thesis will create a statistically accurate representation of customers arriving at ticket purchasing channels. Each customer's attributes are: arrival time, origin and destination, number of destined tickets, and willingness to pay. Each attribute can be generated using a specific distribution.
The created customers will then be used to simulate the purchase of tickets and overall revenue for a flight network. With a valid simulation, airlines will be able to compare the performance of different RM engines under various circumstances.
The first module of this thesis will create a statistically accurate representation of customers arriving at ticket purchasing channels. Each customer's attributes are: arrival time, origin and destination, number of destined tickets, and willingness to pay. Each attribute can be generated using a specific distribution.
The created customers will then be used to simulate the purchase of tickets and overall revenue for a flight network. With a valid simulation, airlines will be able to compare the performance of different RM engines under various circumstances.
ContributorsFischer, Amanda (Author) / Gel, Esma (Thesis director) / Jacobs, Tim (Thesis director) / Purnomo, Hadi (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2012-05
Description
This paper explores the ability to predict yields of soybeans based on genetics and environmental factors. Based on the biology of soybeans, it has been shown that yields are best when soybeans grow within a certain temperature range. The event a soybean is exposed to temperature outside their accepted range is labeled as an instance of stress. Currently, there are few models that use genetic information to predict how crops may respond to stress. Using data provided by an agricultural business, a model was developed that can categorically label soybean varieties by their yield response to stress using genetic data. The model clusters varieties based on their yield production in response to stress. The clustering criteria is based on variance distribution and correlation. A logistic regression is then fitted to identify significant gene markers in varieties with minimal yield variance. Such characteristics provide a probabilistic outlook of how certain varieties will perform when planted in different regions. Given changing global climate conditions, this model demonstrates the potential of using data to efficiently develop and grow crops adjusted to climate changes.
ContributorsDean, Arlen (Co-author) / Ozcan, Ozkan (Co-author) / Travis, Daniel (Co-author) / Gel, Esma (Thesis director) / Armbruster, Dieter (Committee member) / Parry, Sam (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In an effort to provide the utmost safety for the guests of a park, it is important to make the best decision when selecting the location for emergency response crews. A theme park is different from a regular residential or commercial area because the crowds and shows block certain routes, and they change throughout the day. We propose an optimization model that selects staging locations for emergency medical responders in a theme park to maximize the number of responses that can occur within a pre-specified time. The staging areas are selected from a candidate set of restricted access locations where the responders can store their equipment. Our solution approach considers all routes to access any park location, including areas that are unavailable to a regular guest. Theme parks are a highly dynamic environment. Because special events occurring in the park at certain hours (e.g., parades) might impact the responders' travel times, our model's decisions also include the time dimension in the location and re-location of the responders. Our solution provides the optimal location of the responders for each time partition, including backup responders. When an optimal solution is found, the model is also designed to consider alternate optimal solutions that provide a more balanced workload for the crews.
ContributorsLivingston, Noah Russell (Author) / Sefair, Jorge (Thesis director) / Askin, Ronald (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12