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A Software-Defined Radio Transmitter for Variable-Coded Modulation on a CubeSatThe large volume of satellites sharing the same spectrum and the complexities of communications in Low-Earth Orbit (LEO) pose challenges to the downlink of large volumes of data on a platform that is bandwidth, power, and time limited. LEO satellites operate in a highly variable communications environment due to variations in inter-satellite or satellite-to-ground geometries, weather, and interference. Therefore, there is motivation for implementing satellite communication techniques that manage these issues to increase the data throughput. One such technique is variable-coded modulation which shows improvement by taking advantage of the dynamic nature of a satellite link. As part of the Air Force Research Laboratory University Nanosatellite Program, and in collaboration with NASA, this project focuses on the development of an S-band software defined radio for CubeSats that utilizes variable-coded modulation defined by the Digital Video Broadcasting-Satellite-Second Generation standard. This project defense discusses the initial development and testing using GNU Radio, and the challenges for full implementation, as well as the current status of the transmitter, and future work.
Applied machine learning using twitter sentiment and time series data for stock market forecastingThis paper presents an approach to determine stock prices using Twitter sentiment. Due to the highly stochastic nature of the stock market, it is difficult to determine a model that accurately predicts prices. In Twitter Mood Predicts the Stock Market by Bollen, capturing tweets and classifying each tweet’s mood was useful in predicting the Dow Industrial Jones Average (DJIA). Accurately predicting a movement quantitatively is profitable. We present a method that captures sentiment from Twitter with mentions of specific companies to predict their price for the following day.
'I am the last frontier': idealized Alaskan themes through media and their influence on culture, tourism, and policyA large body of literature suggests that in media history there exists prominent narrative themes about the State of Alaska. These themes affect both resident and visitor perceptions and judgements about what life is and should be in Alaska and subsequently, create values that ultimately influence how the state operates. The evolution of these themes are understood in a modern capacity in the Alaska reality television phenomenon of the early 2000’s. This study concludes that the effect of these forms of media may create conflict and ultimately, may not work in the state’s best interests. The researcher believes that the state has new tools to use in its image management. She recommends that new forms of media be cultivated Alaskan residents, tourism industry leaders and special interest groups as a means of alleviating the misrepresentations, expanding communication representation and developing positive visitor experiences for younger visitors who utilize new forms of media. Communication Theory, interviews and content analysis are used to present a study on Alaskan culture, its presence in media and the influence mass media has on this unique environment.
Analysis of GNAC Volleyball using the Bradley-Terry ModelRanking is the process by which a set of objects is assigned a linear ordering based on some property that they possess. Not surprisingly, there are many different methods of ranking used in a wide array of diverse applications; ranking plays a vital role in sports analysis, preference testing, search engine optimization, psychological research, and many other areas. One of the more popular ranking models is Bradley-Terry, which is a type of aggregation ranking that has been used mostly within the realm of sports. Bradley-Terry uses the outcome of individual matchups (paired-comparisons) to create rankings using maximum-likelihood estimation. This project aims to briefly examine the motivation for modeling sporting events, review the history of ranking and aggregation-ranking, communicate the mathematical theory behind the Bradley-Terry model, and apply the model to a novel volleyball dataset.
Research methodology: community input regarding air-quality curriculum for rural AlaskaDuring the summer months in rural Alaska, poor air-quality due to wildfire smoke and gravel road dust can have negative impacts on respiratory health, disproportionately affecting Elders and youth who have weakened respiratory systems. After conducting initial research during the summer of 2019, after visiting twenty-nine communities in the Interior and Southcentral regions of Alaska, the research found that more community involvement is needed to bolster engagement in understanding the impacts of air-quality and implementing steps to mitigate those impacts. This research was in response to those findings, targeting schools and the educational system to drive community engagement and interest in air-quality. Qualitative research was conducted in five communities, employing face-to-face interviews and thematic analysis. The results illustrate the complex and unique relationships that communities, schools, and educators have in rural Alaska. The conclusion of this research finds that integrating air-quality as an important curriculum component will take long-term dedication from educators and the communities alike.