Matching Items (10)
Filtering by
- Creators: Computer Science and Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
The area of real-time baseball statistics presents several challenges that can be addressed using mobile devices. In order to accurately record real-time statistics, it is necessary to present the user with a concise interface that can be used to quickly record the necessary data during in-game events. In this project, we use a mobile application to address this by separating out the required input into pre-game and in-game inputs. We also explore the use of a mobile application to leverage crowd sourcing techniques, which address the challenge of accuracy and precision in subjective real-time statistics.
ContributorsVan Egmond, Eric David (Author) / Tadayon-Navabi, Farideh (Thesis director) / Wilkerson, Kelly (Committee member) / Gorla, Mark (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory research of Fewell and Armbruster's "Basketball teams as strategic networks" (2012), which modeled basketball teams as networks and used metrics to characterize team strategy in the NBA's 2010 playoffs. Individual players and outcomes were nodes and passes and actions were the links. This paper used data that was recorded from playoff games of the two 2012 NBA finalists: the Miami Heat and the Oklahoma City Thunder. The same metrics that Fewell and Armbruster used were explained, then calculated using this data. The offensive networks of these two teams during the playoffs were analyzed and interpreted by using other data and qualitative characterization of the teams' strategies; the paper found that the calculated metrics largely matched with our qualitative characterizations of the teams. The validity of the metrics in this paper and Fewell and Armbruster's paper was then discussed, and modeling basketball teams as multiple-order Markov chains rather than as networks was explored.
ContributorsMohanraj, Hariharan (Co-author) / Choi, David (Co-author) / Armbruster, Dieter (Thesis director) / Fewell, Jennifer (Committee member) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
Description
As technologies advance, so does the curiosity and exploration of humankind. There are many domains across this planet that are unexplored \u2014 the depths of Earth's ocean being one of the most predominant. While the ocean covers seventy percent of Earth's surface, a vast ninety-five percent of this realm remains untouched and unseen by the human eye. The biggest causality of this can be identified in the limitations of current technologies and the large expense associated with delving into these dangerous and uncharted areas. Underwater communication between unmanned devices is the solution to this problem. With the oceanic deployment of wirelessly connected unmanned underwater vehicles (UUVs), researchers can limit risk to human safely and retrieve invaluable oceanographic data from unimaginable depths. However, before this system can be physically deployed, the network topology and environmental interactions must be simulated. More specific to the application, how does attenuation of optical propagation degrade between transmissions? A widely used open source network simulator is the ns series: ns-1, ns-2, and ns-3. Ns-3 is the most recent version, and is a valuable tool for modeling network interactions. However, underwater simulation proposes a limitation \u2014 a three-dimensional consideration for pressure. To properly model this interaction, it is vital that an extension to ns-3 be provided in order to account for the affects pressure has on the propagation of a signal at varying depths.
ContributorsSowa, Ryan John (Author) / Richa, Andrea (Thesis director) / Saripalli, Srikanth (Committee member) / Zhou, Chenyang (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
The process of cooking a turkey is a yearly task that families undertake in order to deliver a delicious centerpiece to a Thanksgiving meal. While other dishes accompany and comprise the traditional Thanksgiving supper, focusing on creating a turkey that satisfies the tastes of all guests is difficult, as preferences vary. Over the years, many cooking methods and preparation variations have come to light. This thesis studies these cooking methods and preparation variations, as well as the effects on the crispiness of the skin, the juiciness of the meat, the tenderness of the meat, and the overall taste, to simplify the choices that home cooks have to prepare a turkey that best fits their tastes. Testing and evaluation reveal that among deep-frying, grilling, and oven roasting turkey, a number of preparation variations show statistically significant changes relative to a lack of these preparation variations. For crispiness, fried turkeys are statistically superior, scoring about 1.5 points higher than other cooking methods on a 5 point scale. For juiciness, the best preparation variation was using an oven bag, with the oven roasted turkey scoring about 4.5 points on a 5 point scale. For tenderness, multiple methods are excellent, with the best three preparation variations in order being spatchcocking, brining, and using an oven bag, each of these preparation variations are just under a 4 out of 5. Finally, testing reaffirms that judges tend to have different subjective tastes, with some having different perceptions and opinions on some criteria, while statistically agreeing on others: there was 67% agreement among judges on crispiness and tenderness, while there was only 17% agreement on juiciness. Evaluation of these cooking methods, as well as their respective preparation variations, addresses the question of which methods are worthwhile endeavors for cooks.
ContributorsVance, Jarod (Co-author) / Lacsa, Jeremy (Co-author) / Green, Matthew (Thesis director) / Taylor, David (Committee member) / Chemical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Ad hoc wireless networks present several interesting problems, one of which is Medium Access Control (MAC). Medium Access Control is a fundamental problem deciding who get to transmit next. MAC protocols for ad hoc wireless networks must also be distributed, because the network is multi-hop. The 802.11 Wi-Fi protocol is often used in ad hoc networking. An alternative protocol, REACT, uses the metaphor of an auction to compute airtime allocations for each node, then realizes those allocations by tuning the contention window parameter using a tuning protocol called SALT. 802.11 is inherently unfair due to how it returns the contention window to its minimum size after successfully transmitting, while REACT’s distributed auction nature allows nodes to negotiate an allocation where all nodes get a fair portion of the airtime. A common application in the network is audio streaming. Audio streams are dependent on having good Quality of Service (QoS) metrics, such as delay or jitter, due to their real-time nature.
Experiments were conducted to determine the performance of REACT/SALT compared to 802.11 in a streaming audio application on a physical wireless testbed, w-iLab.t. Four experiments were designed, using four different wireless node topologies, and QoS metrics were collected using Qosium. REACT performs better in these these topologies, when the mean value is calculated across each run. For the butterfly and star topology, the variance was higher for REACT even though the mean was lower. In the hidden terminal and exposed node topology, the performance of REACT was much better than 802.11 and converged more tightly, but had drops in quality occasionally.
Experiments were conducted to determine the performance of REACT/SALT compared to 802.11 in a streaming audio application on a physical wireless testbed, w-iLab.t. Four experiments were designed, using four different wireless node topologies, and QoS metrics were collected using Qosium. REACT performs better in these these topologies, when the mean value is calculated across each run. For the butterfly and star topology, the variance was higher for REACT even though the mean was lower. In the hidden terminal and exposed node topology, the performance of REACT was much better than 802.11 and converged more tightly, but had drops in quality occasionally.
ContributorsKulenkamp, Daniel (Author) / Syrotiuk, Violet R. (Thesis director) / Colbourn, Charles J. (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
Cryptocurrencies have become one of the most fascinating forms of currency and economics due to their fluctuating values and lack of centralization. This project attempts to use machine learning methods to effectively model in-sample data for Bitcoin and Ethereum using rule induction methods. The dataset is cleaned by removing entries with missing data. The new column is created to measure price difference to create a more accurate analysis on the change in price. Eight relevant variables are selected using cross validation: the total number of bitcoins, the total size of the blockchains, the hash rate, mining difficulty, revenue from mining, transaction fees, the cost of transactions and the estimated transaction volume. The in-sample data is modeled using a simple tree fit, first with one variable and then with eight. Using all eight variables, the in-sample model and data have a correlation of 0.6822657. The in-sample model is improved by first applying bootstrap aggregation (also known as bagging) to fit 400 decision trees to the in-sample data using one variable. Then the random forests technique is applied to the data using all eight variables. This results in a correlation between the model and data of 9.9443413. The random forests technique is then applied to an Ethereum dataset, resulting in a correlation of 9.6904798. Finally, an out-of-sample model is created for Bitcoin and Ethereum using random forests, with a benchmark correlation of 0.03 for financial data. The correlation between the training model and the testing data for Bitcoin was 0.06957639, while for Ethereum the correlation was -0.171125. In conclusion, it is confirmed that cryptocurrencies can have accurate in-sample models by applying the random forests method to a dataset. However, out-of-sample modeling is more difficult, but in some cases better than typical forms of financial data. It should also be noted that cryptocurrency data has similar properties to other related financial datasets, realizing future potential for system modeling for cryptocurrency within the financial world.
ContributorsBrowning, Jacob Christian (Author) / Meuth, Ryan (Thesis director) / Jones, Donald (Committee member) / McCulloch, Robert (Committee member) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
IoT Media broadcast devices, such as the Roku stick, Amazon Fire, and Chromecast have been emerging onto the market recently as a portable and inexpensive alternative to cable and disk players, allowing easy integration between home and business Wi-Fi networks and television systems capable of supporting HDMI inputs without the additional overhead of setting up a heavy or complicated player or computer. The rapid expansion of these products as a mechanism to provide for TV Everywhere services for entertainment as well as cheap office appliances brings yet another node in the rapidly expanding network of IoT that surrounds us today. However, the security implications of these devices are nearly unexplored, despite their prevalence. In this thesis, I will go over the structure and mechanisms of Chromecast, and explore some of the potential exploits and consequences of the device. The thesis contains an overview of the inner workings of Chromecast, goes over the segregation and limited control and fundamental design choices of the Android based OS. It then identifies the objectives of security, four different potential methods of exploit to compromise those objectives on a Chromecast and/or its attached network, including rogue applications, traffic sniffing, evil access points and the most effective one: deauthentication attack. Tests or relevant analysis were carried out for each of these methods, and conclusions were drawn on their effectiveness. There is then a conclusion revolving around the consequences, mitigation and the future implications of security issues on Chromecast and the larger IoT landscape.
ContributorsHuang, Kaiyi (Author) / Zhao, Ziming (Thesis director) / Ahn, Gail-Joon (Committee member) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The software element of home and small business networking solutions has failed to keep pace with annual development of newer and faster hardware. The software running on these devices is an afterthought, oftentimes equipped with minimal features, an obtuse user interface, or both. At the same time, this past year has seen the rise of smart home assistants that represent the next step in human-computer interaction with their advanced use of natural language processing. This project seeks to quell the issues with the former by exploring a possible fusion of a powerful, feature-rich software-defined networking stack and the incredible natural language processing tools of smart home assistants. To accomplish these ends, a piece of software was developed to leverage the powerful natural language processing capabilities of one such smart home assistant, the Amazon Echo. On one end, this software interacts with Amazon Web Services to retrieve information about a user's speech patterns and key information contained in their speech. On the other end, the software joins that information with its previous session state to intelligently translate speech into a series of commands for the separate components of a networking stack. The software developed for this project empowers a user to quickly make changes to several facets of their networking gear or acquire information about it with just their language \u2014 no terminals, java applets, or web configuration interfaces needed, thus circumventing clunky UI's or jumping from shell to shell. It is the author's hope that showing how networking equipment can be configured in this innovative way will draw more attention to the current failings of networking equipment and inspire a new series of intuitive user interfaces.
ContributorsHermens, Ryan Joseph (Author) / Meuth, Ryan (Thesis director) / Burger, Kevin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This review explores popular gambling strategies often believed to guarantee wins, such as card counting and taking advantage of arbitrage. We present a mathematical overview of these systems to evaluate their theoretical effectiveness in ideal conditions by presenting prior research and mathematical proofs. This paper then generates results from these models using Monte Carlo simulations and compares them to data from real-world scenarios. Additionally, we examine reasons that might explain the discrepancies between theoretical and real-world results, such as the potential for dealers to detect and counteract card counting. Ultimately, although these strategies may fare well in theoretical scenarios, they struggle to create long-term winning solutions in casino or online gambling settings.
ContributorsBoyilla, Harsha (Author) / Clough, Michael (Thesis director) / Eikenberry, Steffen (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
This project tackles a real-world example of a classroom with college students to discover what factors affect a student’s outcome in the class as well as investigate when and why a student who started well in the semester may end poorly later on. First, this project performs a statistical analysis to ensure that the total score of a student is truly based on the factors given in the dataset instead of due to random chance. Next, factors that are the most significant in affecting the outcome of scores in zyBook assignments are discovered. Thirdly, visualization of how students perform over time is displayed for the student body as a whole and students who started well at the beginning of the semester but trailed off towards the end. Lastly, the project also gives insight into the failure metrics for good starter students who unfortunately did not perform as well later in the course.
ContributorsChung, Michael (Author) / Meuth, Ryan (Thesis director) / Samara, Marko (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05