Matching Items (61)
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Description
Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings, which are passive abilities that grant ships additional capabilities. Two of these Briefings, known as Retaliator and Get My Good Side, have strong synergy when used together, which has led to the Dreadnought community’s claiming that the Briefings are too powerful and should be rebalanced to be more in line with the power levels of other Briefings. This study collected gameplay data with and without the use of these specific Officer Briefings to determine the precise impact on gameplay. Linear correlation matrices and inference on two means were used to determine performance impact. It was found that, although these Officer Briefings do improve an individual player’s performance in a game, they do not have a consistent impact on the player’s team performance, and that these Officer Briefings are therefore not in need of rebalancing.
ContributorsJacobs, Max I. (Author) / Schneider, Laurence (Thesis director) / Tran, Samantha (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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 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
Description
The OMFIT (One Modeling Framework for Integrated Tasks) modeling environment and the BRAINFUSE module have been deployed on the PPPL (Princeton Plasma Physics Laboratory) computing cluster with modifications that have rendered the application of artificial neural networks (NNs) to the TRANSP databases for the JET (Joint European Torus), TFTR (Tokamak Fusion Test Reactor), and NSTX (National Spherical Torus Experiment) devices possible through their use. This development has facilitated the investigation of NNs for predicting heat transport profiles in JET, TFTR, and NSTX, and has promoted additional investigations to discover how else NNs may be of use to scientists at PPPL. In applying NNs to the aforementioned devices for predicting heat transport, the primary goal of this endeavor is to reproduce the success shown in Meneghini et al. in using NNs for heat transport prediction in DIII-D. Being able to reproduce the results from is important because this in turn would provide scientists at PPPL with a quick and efficient toolset for reliably predicting heat transport profiles much faster than any existing computational methods allow; the progress towards this goal is outlined in this report, and potential additional applications of the NN framework are presented.
ContributorsLuna, Christopher Joseph (Author) / Tang, Wenbo (Thesis director) / Treacy, Michael (Committee member) / Orso, Meneghini (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
DescriptionIn this project, we aim to examine the methods used to obtain U.S. mortality rates, as well as the changes in the mortality rate between subgroups of interest within our population due to various diseases.
ContributorsClermont, Nicholas Charles (Author) / Boggess, May (Thesis director) / Kamarianakis, Ioannis (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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, 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
Description
Science fiction has a unique ability to express, analyze, and critique concepts in a subtle way that emphasizes a point but is still entertaining to the audience. Because of science fiction's ability to do this it has long been a powerful way to ask questions that would normally not be addressed. As such, this paper provides an overview of the effects of biomedical technology in science fiction films. The discussions in this paper will analyze the different portrayals of the technology in the viewed cinematic pieces and the effects they have on the characters in the film. The discussion will begin with the films that have technology based in Genetic Engineering. This will then be followed by a discussion of the biomedical technology based in the fields of Endocrinology; Reanimation; Preservation; Prosthetics; Physical Metamorphosis; Super-Drugs and Super-Viruses; and Diagnostic, Surgical, and Monitoring Equipment. At the end of this paper movie summaries are provided to assist in clarifying plot details.
ContributorsGrzybowski, Amanda Ann (Author) / Foy, Joseph (Thesis director) / Facinelli, Diane (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Rupture of intracranial aneurysms causes a subarachnoid hemorrhage, which is often lethal health event. A minimally invasive method of solving this problem may involve a material, which can be administered as a liquid and then becomes a strong solid within minutes preventing flow of blood in the aneurysm. Here we report on the development of temperature responsive copolymers, which are deliverable through a microcatheter at body temperature and then rapidly cure to form a highly elastic hydrogel. To our knowledge, this is the first physical-and chemical-crosslinked hydrogel capable of rapid crosslinking at temperatures above the gel transition temperature. The polymer system, poly(N-isopropylacrylamide-co-cysteamine-co-Jeffamine® M-1000 acrylamide) and poly(ethylene glycol) diacrylate, was evaluated in wide-neck aneurysm flow models to evaluate the stability of the hydrogels. Investigation of this polymer system indicates that the Jeffamine® M-1000 causes the gels to retain water, resulting in gels that are initially weak and viscous, but become stronger and more elastic after chemical crosslinking.
ContributorsLee, Elizabeth Jean (Author) / Vernon, Brent (Thesis director) / Brennecka, Celeste (Committee member) / Overstreet, Derek (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
Description
The role of retention and forgetting of context dependent sensorimotor memory of dexterous manipulation was explored. Human subjects manipulated a U-shaped object by switching the handle to be grasped (context) three times, and then came back two weeks later to lift the same object in the opposite context relative to that experience on the last block. On each context switch, an interference of the previous block of trials was found resulting in manipulation errors (object tilt). However, no significant re-learning was found two weeks later for the first block of trials (p = 0.826), indicating that the previously observed interference among contexts lasted a very short time. Interestingly, upon switching to the other context, sensorimotor memories again interfered with visually-based planning. This means that the memory of lifting in the first context somehow blocked the memory of lifting in the second context. In addition, the performance in the first trial two weeks later and the previous trial of the same context were not significantly different (p = 0.159). This means that subjects are able to retain long-term sensorimotor memories. Lastly, the last four trials in which subjects switched contexts were not significantly different from each other (p = 0.334). This means that the interference from sensorimotor memories of lifting in opposite contexts was weaker, thus eventually leading to the attainment of steady performance.
ContributorsGaw, Nathan Benjamin (Author) / Santello, Marco (Thesis director) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05