Displaying all 4 results
- Conference Session
- DSA Technical Session 2
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Emma Fox, Franklin W. Olin College of Engineering; Zachary del Rosario, Olin College of Engineering
- Tagged Topics
- Data Science & Analytics Constituent Committee (DSA)
thatprecisely zero were average. The Air Force fixed this problem by designing adjustable seats toaccount for the observed pilot variation [1].While variability in human dimensions is now considered obvious and easily handled, othersources of variability are still neglected or mishandled. In aerospace engineering, enormousresources are dedicated to quantifying the variability in material strength, but other propertiessuch as elasticity are designed using average values [3]. This treatment of variability leads to avariance deficit that undermines structural safety.Statistics is considered unique as a discipline that focuses on understanding variability [4]. Forinstance, Makar and Rubin assert that mathematical convention inherently emphasizes certainty
- Conference Session
- DSA Technical Session 5
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Nicolas Leger, Florida International University; Maimuna Begum Kali, Florida International University; Stephanie Jill Lunn, Florida International University
- Tagged Topics
- Data Science & Analytics Constituent Committee (DSA)
uses data science to design more efficienttransportation systems [22]. Chemical engineering as a field is currently shifting from being adiscipline driven by “empirical and heuristic” principles to being more driven by artificialintelligence (AI) methods [23].Machine learning and data science are interconnected disciplines that play crucial roles invarious industries, including energy and aerospace. Machine learning is a subset of AI thatenables computer systems to learn and improve from experience without being explicitlyprogrammed [24]. To put it in better words, machine learning “is a branch of AI that usesalgorithms to give robots the ability to learn from data and get better over time [25, p.1].” Itinvolves the development of algorithms
- Conference Session
- DSA Technical Session 5
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Duo Li, Shenyang Institute of Technology; Elizabeth Milonas, New York City College of Technology; Qiping Zhang, Long Island University
- Tagged Topics
- Data Science & Analytics Constituent Committee (DSA)
. Zizka, "Meeting real-world demands of the global economy: an employer's perspective," Journal of Aviation/Aerospace Education & Research, vol. 27, no. 2, pp. 59-76, 2018.[12]. Milonas, Elizabeth, Duo Li, Qiping Zhang. “Content Analysis of Two-year & Four-year Data Science Programs in the United States.” In Proceedings of the 128th ASEE Annual Conference, July 26-29, 2021. [Online]. Available:file:///Users/emilonas/Downloads/content-analysis-of- two-year-and-four-year-data-science-programs-in-the-united-states.pdf.
- Conference Session
- DSA Technical Session 7
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Isil Anakok, Virginia Polytechnic Institute and State University; Kai Jun Chew, Embry-Riddle Aeronautical University, Daytona Beach; Holly M Matusovich, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University
- Tagged Topics
- Data Science & Analytics Constituent Committee (DSA)
’ responses to the question “Has the arrival of generativeAI (e.g., ChatGPT) impacted your thinking on assessment or assessment practices?” based ontheir home department Home Department No Yes Maybe I am # of % of not participants participants sure Aerospace Engineering 1 2 3 4 Biomedical Engineering 3 3 4 Chemical Engineering 2 1 3 4 Civil Engineering 3