The OAKTrust Digital Repository

The OAKTrust digital repository at Texas A&M is a digital service that collects, preserves, and distributes the scholarly output of the University. The repository facilitates open access scholarly communication while preserving the scholarly legacy of the Texas A&M community.

 

Communities in OAKTrust

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Recent Submissions

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Economic Indicators of the College Station - Bryan MSA, December 2024
(Private Enterprise Research Center, Texas A&M University, 2024-12-12) Bullock, Ashley; Jansen, Dennis W.; Sinha, Somali Ghosh
The Business-Cycle Index increased 0.4% from September 2024 to October 2024. The local unemployment rate remained steady at 3.2% in October 2024 compared to September 2024. Local nonfarm employment increased by 0.2% from September 2024 to October 2024. Inflation-adjusted taxable sales increased by 3.1% from September 2024 to October 2024. Among comparable college towns, the percentage of 20-24 aged residents was highest in the College Station-Bryan MSA at 17%. The College Station-Bryan MSA had the highest percentage of population growth at 1.3% among the selected college towns.
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Texas A&M University Impact on the Local Economy: Events of June 2024
(Private Enterprise Research Center, Texas A&M University, 2024-12-09) Bullock, Ashley; Jansen, Dennis W.; Sinha, Somali Ghosh
June 2024 was a landmark month for College Station and Bryan, marked by several high-profile events that drew significant crowds and boosted the local economy, including a Brazil vs. Mexico soccer friendly and a concert held by country music artist George Strait. This report evaluates the economic impact of these events on the College Station-Bryan economy by focusing on taxable sales, hotel room revenues and mixed beverage sales for the month of June 2024. Together, these two cities make over 90% of taxable sales in Brazos County. Gross ticket sales and net revenue for the Brazil vs. Mexico game and George Strait concert are also shared.
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Zenji: Heuristic Algorithms to Identify and Correct Common Japanese Kanji Handwriting Mitakes
(Texas A&M University. Undergraduate Research. Department of Computer Science and Engineering., 2024-12) Broberg, Cole; Taele, Paul
The kanji writing system—tens of thousands of logographic Japanese characters originating from China—is by far the most complex of the three Japanese scripts. Kanji present a unique challenge for English-speaking Japanese learners, as they lack an equivalent in western tongues. Whether studying in a classroom or independently, Japanese language learners are often exposed to mnemonics or other techniques to aid in the memorization of these symbols. However, the classroom setting presently provides a unique opportunity for learners to hand-write the characters and receive feedback on their writing. The difficulty and lack of feedback on handwriting for independent learners discourages the practice of hand-writing kanji, which can stunt the learning process. This paper introduces Zenji, a system of heuristic algorithms to analyze student handwriting of kanji. Zenji provides a lightweight solution that may easily be run on students’ personal computing devices and naturally integrated into existing mobile spaced-repetition solutions for kanji learning. The Zenji system provides users overall and per-stroke numeric, visual, and written feedback on various metrics, focusing on common mistakes. In validation testing, Zenji’s feedback proved to be highly accurate across the categories that it assesses, highlighting user errors and combining a classroom-like learning experience with the flexibility of independent study.