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Articles 1 - 7 of 7
Full-Text Articles in Applied Mathematics
Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove
Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove
Mathematics Summer Fellows
This study examines the change in connotative language use before and during the Covid-19 pandemic. By analyzing news articles from several major US newspapers, we found that there is a statistically significant correlation between the sentiment of the text and the publication period. Specifically, we document a large, systematic, and statistically significant decline in the overall sentiment of articles published in major news outlets. While our results do not directly gauge the sentiment of the population, our findings have important implications regarding the social responsibility of journalists and media outlets especially in times of crisis.
Decision Tree For Predicting The Party Of Legislators, Afsana Mimi
Decision Tree For Predicting The Party Of Legislators, Afsana Mimi
Publications and Research
The motivation of the project is to identify the legislators who voted frequently against their party in terms of their roll call votes using Office of Clerk U.S. House of Representatives Data Sets collected in 2018 and 2019. We construct a model to predict the parties of legislators based on their votes. The method we used is Decision Tree from Data Mining. Python was used to collect raw data from internet, SAS was used to clean data, and all other calculations and graphical presentations are performed using the R software.
A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross
A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross
Yale Day of Data
Post-market surveillance is a collection of processes and activities used by product manufacturers and regulators, such as the U.S. Food and Drug Administration (FDA) to monitor the safety and effectiveness of medical devices once they are available for use “on the market”. These activities are designed to generate information to identify poorly performing devices and other safety problems, accurately characterize real-world device performance and clinical outcomes, and facilitate the development of new devices, or new uses for existing devices. Typically, a device is monitored by comparing adverse events in the exposed population to a matched unexposed population. This research considers …
Modeling Traffic At An Intersection, Kaleigh L. Mulkey, Saniita K. Fasenntao
Modeling Traffic At An Intersection, Kaleigh L. Mulkey, Saniita K. Fasenntao
Symposium of Student Scholars
The main purpose of this project is to build a mathematical model for traffic at a busy intersection. We use elements of Queueing Theory to build our model: the vehicles driving into the intersection are the “arrival process” and the stop light in the intersection is the “server.”
We collected traffic data on the number of vehicles arriving to the intersection, the duration of green and red lights, and the number of vehicles going through the intersection during a green light. We built a SAS macro code to simulate traffic based on parameters derived from the data.
In our program …
The Overhaul Of U.S. Patent Law, Ron D. Katznelson
The Overhaul Of U.S. Patent Law, Ron D. Katznelson
Ron D. Katznelson
No abstract provided.
Patent Examination Policy And The Social Costs Of Examiner Allowance And Rejection Errors, Ron D. Katznelson
Patent Examination Policy And The Social Costs Of Examiner Allowance And Rejection Errors, Ron D. Katznelson
Ron D. Katznelson
No abstract provided.
A Fine Mapping Theorem To Refine Results From Association Genetics Studies, Steven J. Schrodi
A Fine Mapping Theorem To Refine Results From Association Genetics Studies, Steven J. Schrodi
Steven J Schrodi
No abstract provided.