Matching Items (36)
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The Performance Based Studies Research Group (PBSRG) has developed industry-tested leadership and management techniques that have been proven to increase organizational performance. The Leadership Society of Arizona (LSA) has worked closely with PBSRG to develop an educational framework that introduces these leadership concepts to college students. LSA is now endeavoring

The Performance Based Studies Research Group (PBSRG) has developed industry-tested leadership and management techniques that have been proven to increase organizational performance. The Leadership Society of Arizona (LSA) has worked closely with PBSRG to develop an educational framework that introduces these leadership concepts to college students. LSA is now endeavoring to make this curriculum more accessible for K-12 students and educators. As part of a thesis creative project, the author has developed a strategy to connect with and enable local high schools, teachers, and students to engage with the professional industry and higher education. This strategy will allow LSA to connect with up to 150 high school students over the summer of 2016. By making this education easily accessible, the author has accomplished a milestone in the larger effort encompassed by LSA. The course chosen to present to high school students is an abridged variation of the Barrett Honors College course "Deductive Logic: Leadership and Management Techniques". The class framework is designed to instantiate a self-sustaining program for future summer school courses. The summer school course will allow high school students to learn, understand, and apply college level concepts into their education, work, and personal lives. The development of the framework for the program encompasses networking/partnering efforts, marketing package creation, and the delivery of the summer school course over the months of June and July in 2016.
ContributorsDunn, Melissa Anne (Author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Social media is used by people every day to discuss the nuances of their lives. Major League Baseball (MLB) is a popular sport in the United States, and as such has generated a great deal of activity on Twitter. As fantasy baseball continues to grow in popularity, so does the

Social media is used by people every day to discuss the nuances of their lives. Major League Baseball (MLB) is a popular sport in the United States, and as such has generated a great deal of activity on Twitter. As fantasy baseball continues to grow in popularity, so does the research into better algorithms for picking players. Most of the research done in this area focuses on improving the prediction of a player's individual performance. However, the crowd-sourcing power afforded by social media may enable more informed predictions about players' performances. Players are chosen by popularity and personal preferences by most amateur gamblers. While some of these trends (particularly the long-term ones) are captured by ranking systems, this research was focused on predicting the daily spikes in popularity (and therefore price or draft order) by comparing the number of mentions that the player received on Twitter compared to their previous mentions. In doing so, it was demonstrated that improved fantasy baseball predictions can be made through leveraging social media data.
ContributorsRuskin, Lewis John (Author) / Liu, Huan (Thesis director) / Montgomery, Douglas (Committee member) / Morstatter, Fred (Committee member) / Industrial, Systems (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Billions of people around the world deal with the struggles of poverty every day. Consequently, a number of others have committed themselves to help alleviate poverty. Many various methods are used, and a current consensus on the best method to alleviate poverty is lacking. Generally the methods used or researched

Billions of people around the world deal with the struggles of poverty every day. Consequently, a number of others have committed themselves to help alleviate poverty. Many various methods are used, and a current consensus on the best method to alleviate poverty is lacking. Generally the methods used or researched exist somewhere on the spectrum between top-down and bottom-up approaches to fighting poverty. This paper analyzes a specific method proposed by C.K. Prahalad known as the Bottom of the Pyramid solution. The premise of the method is that large multinational corporations should utilize the large conglomerate of money that exists amongst poor people \u2014 created due to the sheer number of poor people \u2014 for business ventures. Concurrently, the poor people can benefit from the company's entrance. This method has received acclaim theoretically, but still needs empirical evidence to prove its practicality. This paper compares this approach with other approaches, considers international development data trends, and analyzes case studies of actual attempts that provide insight into the approach's potential for success. The market of poor people at the bottom of the pyramid is extremely segmented which makes it very difficult for large companies to financially prosper. It is even harder to establish mutual benefit between the large corporation and the poor. It has been found that although aspects of the bottom of the pyramid method hold merit, higher potential for alleviating poverty exists when small companies venture into this space rather than large multinational corporations. Small companies can conform to a single community and niche economy to prosper \u2014 a flexibility that large companies lack. Moving forward, analyzing the actual attempts provides the best and only empirical insights; hence, it will be important to consider more approaches into developing economies as they materialize.
ContributorsSanchez, Derek Javier (Author) / Henderson, Mark (Thesis director) / Shunk, Dan (Committee member) / Industrial, Systems (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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The U.S. Navy and other amphibious military organizations utilize a derivation of the traditional side stroke called the Combat Side Stroke, or CSS, and tout it as the most efficient technique available. Citing its low aerobic requirements and slow yet powerful movements as superior to the traditionally-best front crawl (freestyle),

The U.S. Navy and other amphibious military organizations utilize a derivation of the traditional side stroke called the Combat Side Stroke, or CSS, and tout it as the most efficient technique available. Citing its low aerobic requirements and slow yet powerful movements as superior to the traditionally-best front crawl (freestyle), the CSS is the go-to stroke for any operation in the water. The purpose of this thesis is to apply principles of Industrial Engineering to a real-world situation not typically approached from a perspective of optimization. I will analyze pre-existing data about various swim strokes in order to compare them in terms of efficiency for different variables. These variables include calories burned, speed, and strokes per unit distance, as well as their interactions. Calories will be measured by heart rate monitors, converting BPM to calories burned. Speed will be measured by stopwatch and observer. Strokes per unit distance will be measured by observer. The strokes to be analyzed include the breast stroke, crawl stroke, butterfly, and combat side stroke. The goal is to informally test the U.S. Navy's claim that the combat side stroke is the optimum stroke to conserve energy while covering distance. Because of limitations in the scope of the project, analysis will be done using data collected from literary sources rather than through experimentation. This thesis will include a design of experiment to test the findings here in practical study. The main method of analysis will be linear programming, followed by hypothesis testing, culminating in a design of experiment for future progress on this topic.

ContributorsGoodsell, Kevin Lewis (Author) / McCarville, Daniel R. (Thesis director) / Kashiwagi, Jacob (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2014-12
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The Arizona Department of Environmental Quality (ADEQ) experienced a problem with the quality of their services. The agency was expending a large amount of resources, both time and money to control contractors' work with unexpected poor quality work. ADEQ partnered with Dr. Dean Kashiwagi and the Performance Based Studies Research

The Arizona Department of Environmental Quality (ADEQ) experienced a problem with the quality of their services. The agency was expending a large amount of resources, both time and money to control contractors' work with unexpected poor quality work. ADEQ partnered with Dr. Dean Kashiwagi and the Performance Based Studies Research Group (PBSRG) early in 2014 to find a solution to the procurement problems. PBSRG introduced the Performance Information Procurement System (PIPS) and began implementation on four test projects. Three of the projects have moved into the execution phase delivering almost $100K savings in the procurement process alone. The three main causes of the issues were: lack of a system identifying the quality of vendors, management, direction, and control (MDC), and lack of a system to track vendor performance. Best value PIPS is a paradigm shift from the traditional price-based model and has succeeded in mitigating these challenges for the industry, while also validating the PBSRG model.
ContributorsFink, Fabian Josef (Author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2014-12
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The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and

The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and FAA. With the magnitude of operation of the prominent players in the airline industry today, the crew staffing problem proves very large and has become heavily reliant on operations research solution methodologies. An area of opportunity that has not yet been extensively researched lies in the planning of crew vacation. This paper develops a model driven by the idea of system risk that constructs an optimal vacation grid for the time period of one year. The model generates a daily allocation that maximizes vacation offering while ensuring a given level of system reliability. The model is then implemented using data from US Airways and model improvements are provided for practical application in the airline industry based on the output.
ContributorsFisher, Tignes Noel (Author) / Gel, Esma (Thesis director) / Jacobs, Tim (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
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The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques

The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
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This research covers the relationship between popular electronic dance music (EDM) and the seasons and climate. The precedence and relevance of the research is outlined through prior research initiatives by Karen Aplin and Paul Williams on the effect of weather on classical music. The hypothesis is that the climate will

This research covers the relationship between popular electronic dance music (EDM) and the seasons and climate. The precedence and relevance of the research is outlined through prior research initiatives by Karen Aplin and Paul Williams on the effect of weather on classical music. The hypothesis is that the climate will affect how music by artists residing within the climate and the seasons will affect the popularity of certain genres. Warmer climates will produce songs that are more upbeat and energetic while colder climates will result in songs that are more complex and heavy. The analysis of this hypothesis will be performed in two parts. The first will be a data driven analysis from Beatport.com's Top 100 EDM charts to observe the season's impact on genre popularity. The second will be a case study analysis of a number of artists from around the world to observe climate impact on EDM. From the analysis, we are able to draw the connection that climate does in fact have an impact on the types of music produced. Likewise, we are able to conclude that there is a distinct variation in deep house, techno/tech house, and house as a result of the seasons shifting. Techno/tech house is more popular in the warmer spring and summer months and house and deep house have a higher standing in the colder fall and winter months.
ContributorsMuzzy, Bryce Richard (Author) / Feisst, Sabine (Thesis director) / Tobias, Evan (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / School of Music (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
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The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation

The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation study. This research seeks to determine the acquisition processes that contribute significantly to total simulated program time in the acquisition system for all programs reaching Milestone C. Specifically, this research examines the effect of increased scope management, technology maturity, and decreased variation and mean process times in post-Design Readiness Review contractor activities by performing additional simulation analyses. Potential policies are formulated from the results to further improve program acquisition completion time.
ContributorsWorger, Danielle Marie (Author) / Wu, Teresa (Thesis director) / Shunk, Dan (Committee member) / Wirthlin, J. Robert (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
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The efficient refurbishment of rotable parts on an aircraft proves to be a main concern for airline carriers today. Airlines must be able to seamlessly rotate parts into and out of the system for maintenance in accordance with FAA requirements while leaving daily operations uninterrupted. In this paper, we develo

The efficient refurbishment of rotable parts on an aircraft proves to be a main concern for airline carriers today. Airlines must be able to seamlessly rotate parts into and out of the system for maintenance in accordance with FAA requirements while leaving daily operations uninterrupted. In this paper, we develop an airline maintenance scheduling model that constructs an optimal schedule for part maintenance over a given time horizon using deterministic forecasting techniques. The model generates a schedule that minimizes the total cost of a maintenance schedule solution while maximizing the utility of all parts in the system. The model is then tested against actual network data of three part types crucial to airline operations and used to investigate the current data collection processes of US Airways maintenance lead time metrics. Manual sensitivity analysis is performed to generate the marginal value of each parameter and potential model extensions are highlighted as a result of these conclusions.
ContributorsDunham, Nicole Elizabeth (Author) / Gel, Esma (Thesis director) / Jacobs, Timothy (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-12