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Articles 1 - 8 of 8
Full-Text Articles in Mathematics
Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash
Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash
Symposium of Student Scholars
Employee attrition is a relevant issue that every business employer must consider when gauging the effectiveness of their employees. Whether or not an employee chooses to leave their job can come from a multitude of factors. As a result, employers need to develop methods in which they can measure attrition by calculating the several qualities of their employees. Factors like their age, years with the company, which department they work in, their level of education, their job role, and even their marital status are all considered by employers to assist in predicting employee attrition. This project will be analyzing a …
Finding Similar Stocks By Detecting Cliques In Market Graphs, Sudhashree Sayenju
Finding Similar Stocks By Detecting Cliques In Market Graphs, Sudhashree Sayenju
Symposium of Student Scholars
The stock market provides an abundant source of data. However, when the amount of raw data becomes overwhelming it grows increasingly difficult to know how the stocks interact with each other. Stock data visualization as a market graph serves as one of the most popular way of summarizing important information. When modelling the data as a graph, vertices correspond to stocks and edges correspond to strong correlation in their pricing in a certain period of time. This project presents a technique to find stocks that behave very similarly. Such information helps investors make decisions on which stocks to purchase next. …
Quantitatively Motivated Model Development Framework: Downstream Analysis Effects Of Normalization Strategies, Jessica M. Rudd
Quantitatively Motivated Model Development Framework: Downstream Analysis Effects Of Normalization Strategies, Jessica M. Rudd
Doctor of Data Science and Analytics Dissertations
Through a review of epistemological frameworks in social sciences, history of frameworks in statistics, as well as the current state of research, we establish that there appears to be no consistent, quantitatively motivated model development framework in data science, and the downstream analysis effects of various modeling choices are not uniformly documented. Examples are provided which illustrate that analytic choices, even if justifiable and statistically valid, have a downstream analysis effect on model results. This study proposes a unified model development framework that allows researchers to make statistically motivated modeling choices within the development pipeline. Additionally, a simulation study is …
Genetic Algorithm Guidance Of A Constraint Programming Solver For The Multiple Traveling Salesman Problem, Jessica M. Rudd, Andrew M. Henshaw, Lauren Staples, Sanjoosh Akkineni, Lin Li, Joe Demaio
Genetic Algorithm Guidance Of A Constraint Programming Solver For The Multiple Traveling Salesman Problem, Jessica M. Rudd, Andrew M. Henshaw, Lauren Staples, Sanjoosh Akkineni, Lin Li, Joe Demaio
Published and Grey Literature from PhD Candidates
This project developed a metaheuristic approach to the Multiple Traveling Salesman Problem that pairs a custom genetic algorithm with a conventional combinatorial optimization solver. This combined approach was used to build an optimal route for two popular radio show hosts to visit each of the 37 Atlanta area Jersey Mike's Subs in one day. This supported a fundraising eort to send children with chronic and terminal illnesses to Disney World through an organization called Bert's Big Adventure. Atlanta-area Jersey Mike's locations donated 100% of proceeds earned on this Day of Giving to Bert's Big Adventure. With the suggested route developed …
Automatic Knowledge Extraction From Ocr Documents Using Hierarchical Document Analysis, Mohammad Masum, Sai Kosaraju, Tanju Bayramoglu, Girish Modgil, Mingon Kang
Automatic Knowledge Extraction From Ocr Documents Using Hierarchical Document Analysis, Mohammad Masum, Sai Kosaraju, Tanju Bayramoglu, Girish Modgil, Mingon Kang
Published and Grey Literature from PhD Candidates
Industries can improve their business efficiency by analyzing and extracting relevant knowledge from large numbers of documents. Knowledge extraction manually from large volume of documents is labor intensive, unscalable and challenging. Consequently, there have been a number of attempts to develop intelligent systems to automatically extract relevant knowledge from OCR documents. Moreover, the automatic system can improve the capability of search engine by providing application-specific domain knowledge. However, extracting the efficient information from OCR documents is challenging due to highly unstructured format. In this paper, we propose an efficient framework for a knowledge extraction system that takes keywords based queries …
An Optimized Route For Q100'S Bert And Kristin To Visit All Jersey Mike's Subs In Atlanta For Charity
Symposium of Student Scholars
The Bert Show is a popular morning show on Atlanta’s Q100 radio station. They host a non-profit organization that provides a “magical, all-expenses-paid, five-day journey to Walt Disney World for children with chronic and terminal illnesses and their families” called “Bert’s Big Adventure.” On March 28th, 2018, thirty-seven locations of Jersey Mike’s are participating in the their Jersey Mike’s Day of Giving to support Bert’s Big Adventure. The goal is to have two popular radio show hosts visit each of these locations for some photos and presence to draw in more customers! But how do we get two …
A Data Generating Review That Bops, Twists And Pulls At Misconceptions, Kimberly Gardner
A Data Generating Review That Bops, Twists And Pulls At Misconceptions, Kimberly Gardner
Faculty and Research Publications
Statistics is an integral part of the K-12 mathematics curriculum (age 5-18). Naturally, students construct misconceptions of what they learn. This article discusses The Bop It© Challenge, a review activity assesses student understanding and reveals their misundertandings of statistical concepts.
On The Estimation Of Averages Over Infinite Intervals With An Application To Average Persistence In Population Models, Sean F. Ellermeyer
On The Estimation Of Averages Over Infinite Intervals With An Application To Average Persistence In Population Models, Sean F. Ellermeyer
Faculty and Research Publications
We establish a general result for estimating the upper average of a continuous and bounded function over an infinite interval. As an application, we show that a previously studied model of microbial growth in a chemostat with time–varying nutrient input admits solutions (populations) that exhibit weak persistence but not weak average persistence.