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This paper provides evidence through an event study, portfolio simulation, and regression analysis that insider trading, when appropriately aggregated, has predictive power for abnormal risk-adjusted returns on some country and sector exchange traded funds (ETFs). I examine ETFs because of their broad scope and liquidity. ETF markets are relatively efficient

This paper provides evidence through an event study, portfolio simulation, and regression analysis that insider trading, when appropriately aggregated, has predictive power for abnormal risk-adjusted returns on some country and sector exchange traded funds (ETFs). I examine ETFs because of their broad scope and liquidity. ETF markets are relatively efficient and, thus, the effects I document are unlikely to appear in ETF markets. My evidence that aggregated insider trading predicts abnormal returns in some ETFs suggests that aggregated insider trading is likely to have predictive power for financial assets traded in less efficient markets. My analysis depends on specialized insider trading data covering 88 countries is generously provided by 2iQ.
ContributorsKerker, Mackenzie Alan (Author) / Coles, Jeffrey (Thesis director) / Mcauley, Daniel (Committee member) / Licon, Wendell (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor)
Created2014-05
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Description
The goal of the ANLGE Lab's AR assembly project is to create/save assemblies as well as to replicate assemblies later with real-time AR feedback. In this iteration of the project, the SURF algorithm was used to provide object detection for 5 featureful objects (a Lego girl piece, a Lego guy

The goal of the ANLGE Lab's AR assembly project is to create/save assemblies as well as to replicate assemblies later with real-time AR feedback. In this iteration of the project, the SURF algorithm was used to provide object detection for 5 featureful objects (a Lego girl piece, a Lego guy piece, a blue Lego car piece, a window piece, and a fence piece). Functionality was added to determine the location of these 5 featureful objects within a frame as well by using the SURF keypoints associated with detection. Finally, the feedback mechanism by which the system detects connections between objects was improved to consider the size of the blocks in determining connections rather than using static values. Additional user features such as adding a new object and using voice commands were also implemented to make the system more user friendly.
ContributorsSelvam, Nikil Panneer (Author) / Atkinson, Robert (Thesis director) / Runger, George (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory,

In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory, and by minimizing bias and variance while fully utilizing the available information about the system at hand, one can make valuable, accurate predictions about the future. Combining this knowledge with the work of quality gurus W. E. Deming, Eliyahu Goldratt, and Dean Kashiwagi, a framework for making valuable predictions for continuous improvement is made. After this information is synthesized, it is concluded that the best way to make accurate, informative predictions about the future is to "balance the present and future," seeing the future through the lens of the present and thus minimizing bias, variance, and risk.
ContributorsSynodis, Nicholas Dahn (Author) / Kashiwagi, Dean (Thesis director, Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
The influence of mix design on the structural properties of FAU-type (faujasite) zeolite was studied. Samples were synthesized in a forced convection oven using various proportions of coal fly ash, sodium hydroxide (NaOH), and sodium chloride (NaCl). Three faujasite varieties, labeled X, P and S, were prepared for each mix

The influence of mix design on the structural properties of FAU-type (faujasite) zeolite was studied. Samples were synthesized in a forced convection oven using various proportions of coal fly ash, sodium hydroxide (NaOH), and sodium chloride (NaCl). Three faujasite varieties, labeled X, P and S, were prepared for each mix design. Samples were characterized using Fourier transform infrared (FT-IR) spectroscopy and thermo-gravimetric analysis (TGA). Mercury intrusion porosimetry (MIP) was used to obtain porosity information on the samples. Mechanical strength testing was performed on solid blocks of the zeolite samples prepared in a mold. It was found that the S variety in mix design (iv) had the most desirable balance of porosity and strength for engineering applications.
Created2015-05
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Description
As an example of "big data," we consider a repository of Arctic sea ice concentration data collected from satellites over the years 1979-2005. The data is represented by a graph, where vertices correspond to measurement points, and an edge is inserted between two vertices if the Pearson correlation coefficient between

As an example of "big data," we consider a repository of Arctic sea ice concentration data collected from satellites over the years 1979-2005. The data is represented by a graph, where vertices correspond to measurement points, and an edge is inserted between two vertices if the Pearson correlation coefficient between them exceeds a threshold. We investigate new questions about the structure of the graph related to betweenness, closeness centrality, vertex degrees, and characteristic path length. We also investigate whether an offset of weeks and years in graph generation results in a cosine similarity value that differs significantly from expected values. Finally, we relate the computational results to trends in Arctic ice.
ContributorsDougherty, Ryan Edward (Author) / Syrotiuk, Violet (Thesis director) / Colbourn, Charles (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
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Description
We created an Android application, Impromp2, which allows users to search for and save events of interest to them in the Phoenix area. The backend, built on the Parse platform, gathers events daily using Web services and stores them in a database. Impromp2 was designed to improve upon similarly-purposed apps

We created an Android application, Impromp2, which allows users to search for and save events of interest to them in the Phoenix area. The backend, built on the Parse platform, gathers events daily using Web services and stores them in a database. Impromp2 was designed to improve upon similarly-purposed apps available for Android devices in several key ways, especially in user interface design and data interaction capability. This is a full-stack software project that explores databases and their performance considerations, Web services, user interface design, and the challenges of app development for a mobile platform.
ContributorsNorth, Joseph Robert (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Faucon, Philippe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
A primary goal in computer science is to develop autonomous systems. Usually, we provide computers with tasks and rules for completing those tasks, but what if we could extend this type of system to physical technology as well? In the field of programmable matter, researchers are tasked with developing synthetic

A primary goal in computer science is to develop autonomous systems. Usually, we provide computers with tasks and rules for completing those tasks, but what if we could extend this type of system to physical technology as well? In the field of programmable matter, researchers are tasked with developing synthetic materials that can change their physical properties \u2014 such as color, density, and even shape \u2014 based on predefined rules or continuous, autonomous collection of input. In this research, we are most interested in particles that can perform computations, bond with other particles, and move. In this paper, we provide a theoretical particle model that can be used to simulate the performance of such physical particle systems, as well as an algorithm to perform expansion, wherein these particles can be used to enclose spaces or even objects.
ContributorsLaff, Miles (Author) / Richa, Andrea (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team

The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team be as successful as possible by defining which positions are most important to a team's success. Data from fifteen years of NFL games was collected and information on every player in the league was analyzed. First there needed to be a benchmark which describes a team as being average and then every player in the NFL must be compared to that average. Based on properties of linear regression using ordinary least squares this project aims to define such a model that shows each position's importance. Finally, once such a model had been established then the focus turned to the NFL draft in which the goal was to find a strategy of where each position needs to be drafted so that it is most likely to give the best payoff based on the results of the regression in part one.
ContributorsBalzer, Kevin Ryan (Author) / Goegan, Brian (Thesis director) / Dassanayake, Maduranga (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
Lithium-ion batteries are the predominant source of electrical energy storage for most portable electronics applications, including hybrid/electric vehicles, laptops, and cellular phones. However, these batteries pose safety concerns due to their flammability and tendency to violently ignite upon short circuiting or failing. Solid electrolytes are a current research development aimed

Lithium-ion batteries are the predominant source of electrical energy storage for most portable electronics applications, including hybrid/electric vehicles, laptops, and cellular phones. However, these batteries pose safety concerns due to their flammability and tendency to violently ignite upon short circuiting or failing. Solid electrolytes are a current research development aimed at reducing the flammability and reactivity of lithium batteries. The compound Li7La3Zr2O12, or LLZO, exhibits satisfactory ionic conductivity in the cubic phase, which is normally synthesized via doping with Al. It has recently been discovered that synthesizing nanostructured LLZO can stabilize the cubic phase without the need for doping. Here nanostructured LLZO was formed using templating on various cellulosic fibers, including cotton fibers, printer paper, filter paper, and nanocellulose fibrils followed by calcination at 700-800 °C. The effect of templating material, calcination temperature, calcination time, and heating ramp rate on LLZO phase and morphology was thoroughly investigated. Templating was determined to be an effective method for controlling the LLZO size and morphology, and most templating experiments resulted in LLZO fibers or ligaments similar in size and morphology to the original template material. A systematic study on the various experimental parameters was performed, concluding that low calcination time and low ramp rate favored smaller ligament formation. Further, it was verified that cubic phase stabilization occurred for LLZO with ligaments of less than 1 micron on average without the use of doping. This research provides more information regarding the size dependence on cubic LLZO stabilization that has not been previously investigated in detail.
ContributorsGordon, Zachary Daniel (Author) / Chan, Candace K. (Thesis director) / Lin, Jerry (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Chemical Engineering Program (Contributor)
Created2015-05
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Description
"The Legal Adventures of Frankie and Rosie" is a creative project that explores the nontraditional format of comics to express creative nonfiction. The project is a set of 30 independent comics that focuses on two primary college-going students who are based off of the authors. The characters, Frankie and Rosie

"The Legal Adventures of Frankie and Rosie" is a creative project that explores the nontraditional format of comics to express creative nonfiction. The project is a set of 30 independent comics that focuses on two primary college-going students who are based off of the authors. The characters, Frankie and Rosie narrate their stories through dialogue. The authors use this narrative model to archive their college experience at ASU. Representing creative nonfiction through comics yields an amalgamated format that can be challenging for both the writers to produce as well as for the readers to consume. Ultimately, the project serves as an attempt to test whether or not the comic medium can stand by itself as an appropriate format to express creative nonfictional narratives without becoming a diluted combination of its purer predecessors.
Created2015-05