Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Oguzhan Oruc, The Citadel; Eva Singleton, The Citadel Military College ; Andrew B. Williams, The Citadel; Kevin Skenes, The Citadel

Tagged Topics

Professional Papers

(ψ) u N  y˙ E  = RB V = s(ψ)c(θ) s(ψ)s(θ)s(ϕ) + c(ϕ)cψ c(ϕ)s(ψ)s(θ) − c(ψ)s(ϕ)    v  (6) z˙D −s(θ) c(θ)s(ϕ) c(ϕ)c(θ) win which c(x) = cos(x) and s(x) = sin(x). Thus, the first three equations of motion can beobtained from (6).The second step of the modeling is to examine the rotational kinematics of the vehicle. Let theangular velocities vector of the vehicle is ν = [p, q, r]T . Using Euler’s rotation theorem [9] andthe rotation matrices given in (2), ν can be expressed as it follows,  ˙ ϕ

Collection

2025 Northeast Section Conference

Authors

SUPARSHYA BABU SUKHAVASI; Thanu Sri Gandham; Susrutha Babu Sukhavasi; Meruva Veera Venkata Bhargav

to its three outputs. The input vector is denoted as I (A, B, C),potential to minimize power consumption and enhance while the output vector is represented as O (P, Q, R). Thecomputational efficiency. Numerous studies have examined relationship between the inputs and outputs follows specificthe role of reversible logic gates in the development of logical operations: P = A, Q = A ⊕ B (XOR operation), andenergy-efficient sequential circuits, leading to remarkable R = (A ⋅ B) ⊕ C (AND followed by XOR). Since the Peresprogress in digital circuit design. gate is reversible, it preserves information, making it highly In [1

Collection

2025 Northeast Section Conference

Authors

SUPARSHYA BABU SUKHAVASI; Susrutha Babu Sukhavasi; Mohammad Jaheerabi; Venkata Durga Sunanda Gangula

circuits, A B C P Q R P Q Rincluding the Toffoli and BJN gates, prevent such losses. 0 0 0 0 0 0 0 0 0 Quantum computing has benefited significantly from 0 0 1 0 0 1 0 0 1RLGs, where information is encoded in quantum states and 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0 1 0 1 0 0 1 0 0 1 0 1 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0

Conference Session

Track 6: Technical Session 1: Gendered Impacts of Code Critiquers on Self-Efficacy in First-Year Engineering Students.

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Mary Benjamin, Michigan Technological University; Laura Albrant, Michigan Technological University; Michelle E Jarvie-Eggart P.E., Michigan Technological University; Leo C. Ureel II, Michigan Technological University; Laura E Brown, Michigan Technological University; Jon Sticklen, Michigan Technological University; AJ Hamlin, Michigan Technological University

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2025 CoNECD Paper Submissions, Diversity

sample sizes increase, the distribution of the sample mean differencesapproaches normality, even when the underlying data is not perfectly normal (Ghasemi &Zahediasl, 2012).To ensure the data met this assumption, the Shapiro-Wilk test was employed to assess normality.The Shapiro-Wilk test is frequently used in real-world applications across various fields,including educational and psychological research, to evaluate whether data significantly deviatesfrom a normal distribution (Razali & Wah, 2011). This approach helped ensure the validity of thesubsequent t-tests, providing confidence that the assumptions of the statistical models wereadequately met.Figure 4: LAESE Factor scores - Histograms and Q-Q plotsfigure 5: CPSES Factor scores

Conference Session

Track 4: Technical Session 1: Report of a Survey of Early Career Latinx Engineers: Trends across 3 Years in Perceptions of the Workplace, Social Cognitions, Job Satisfaction, and Turnover Intentions

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Lisa Y Flores, University of Missouri - Columbia; Rachel L Navarro, University of North Dakota; Jinkoo Lee, University of Missouri - Columbia; Bo Hyun Lee, The Ohio State University; Han Na Suh, Georgia State University - Perimeter College; Sarah Lynn Orton P.E., University of Missouri - Columbia; Pat Garriott

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2025 CoNECD Paper Submissions, Diversity

Method: Measures search * high scores represent high levels of the respective variables Ø Perceived Support-Organization (6-point Likert Scale), Supervisors, Coworkers, Family (4-point Likert Scale) Ø Perceived Organizational Climate (5-point Likert Scale) Ø Workplace Incivility (5-point Likert Scale) Ø Workplace Microaggressions (6-point Likert Scale) Ø Work-family Conflict (5-point Likert Scale) q Engineering Task Self-Efficacy (6-point

Conference Session

Student Papers

Collection

2025 ASEE Southeast Conference

Authors

Megan Elizabeth Batchelor, Mercer University; Chandan Roy, Mercer University

Tagged Topics

Student Papers

experiment, and Q is the power input from the DC source to theheating element. [3]Derivation of the Thermal Resistance FormulaThis formula is derived from the basic principles of steady-state heat transfer. In steady-stateconditions, the rate of heat generated by the heating element (𝑄) is equal to the rate at which heatis dissipated through the heat sink into the surrounding environment, with no net energyaccumulation in the system. [4] Thermal resistance in this context functions similarly toelectrical resistance in circuits, where a temperature difference (𝛥𝑇) drives the heat flow just as avoltage difference drives current.The general formula for thermal resistance is defined as: 𝛥𝑇

Collection

2025 Northeast Section Conference

Authors

Shruti Brahma, University of New Haven; Siddhant Alhat Rajendra, University of New Haven; Ardiana Sula, University of New Haven

-series statistical overview of the ARIMA approach and recurrent neural net-works (RNNs), specifically long-short-term memory (LSTM) TABLE Imodels are as follows. P ROJECTED G ROWTH R ATE S CENARIOS (OVERALL USA)A. Building Our Model: ARIMA and LSTM Growth Rate Type Value To create the ARIMA model, we first specify an (p, d, q) Average Growth Rate 0.0345 (3.45%)configuration and fit it to the enrollment data.The tuple (5,1,0) Maximum Growth Rate (Optimistic) 0.1146 (11.46%)represents

Collection

2025 Northeast Section Conference

Authors

Nusrat Zahan; Sidike Paheding

transformations, respectively. A. Quantitative AnalysisB. Model Analysis In the analysis of the UFO 120 and USR 248 datasets, data augmentation is found to be effective in enhancing PSNR and This study examines how data augmentation affects under- SSIM over models.water image super-resolution (SR) on three popular models,namely SCRNN, SRDRM, and DEEP SESR. SRCNN is TABLE Ihighly effective due to its simple and lightweight architec- Q UANTITATIVE EVALUATION OF DIFFERENT DATA AUGMENTATIONture, making it an ideal choice for IoT-based devices. Its

Collection

2025 Northeast Section Conference

Authors

Srilekha Bandla; Mukesh Reddy Jonnala; Peiqiao Wu; Sarosh Patel; Xingguo Xiong

by a stepper motor, ensuring controlled drugyet to create practical implementations that integrate CNN- delivery at a calculated rate:LSTM methodology with real-time therapeutic systems forpersonal treatment, which follows standard seizure detection Q = RP M × V (2)approaches described in [23] and [24]. An integrated system delivers VNS technology with a CNN- Where: - Q is the flow rate in mL/min, - RP M is the motorLSTM model and drug delivery systems as one functional unit. speed in rotations per minute, - V is the volume displaced perSeizures are detected through ECG motion data entry with revolution.real-time detection and adjustable intervention responses that

Conference Session

Track 5: Technical Session 2: Barriers in the Workplace: An Analysis of Engineering Workplace Culture and Climate

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Susan Sajadi, Virginia Polytechnic Institute and State University; Olivia Ryan, Virginia Polytechnic Institute and State University; Katherine Drinkwater, Virginia Polytechnic Institute and State University

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2025 CoNECD Paper Submissions, Diversity

averaging the item scores within the factor, as is appropriate for an exploratory‬ ‭study‬‭[29]‬‭. Before conducting regression, assumptions‬‭were checked using VIF, Q-Q plots, and‬ ‭residual plots. For all predictors, the VIF was less than 10, Q-Q plots of residuals were linear,‬ ‭and no patterns were identified in the residuals vs. predicted plots‬‭[30]‬‭. To increase the statistical‬ ‭power of the regression model, responses to some demographic questions were grouped together;‬ ‭for example, the 14 options for a participant’s engineering field were grouped into four main‬ ‭categories (civil, electrical, mechanical, and other). This reduction resulted in 23 predictor‬ ‭variables. For each factor, a standard multiple

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Leslie Hopkinson, West Virginia University; Lynette Michaluk, West Virginia University; Lizzie Santiago, West Virginia University

by the National Science Foundation under Grant No.2406798. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] A. Godwin and A. Kirn, “Identity-based motivation: Connections between first-year students’ engineering role identities and future-time perspectives,” Journal of Engineering Education, vol. 109, no. 3, pp. 362–383, 2020, doi: 10.1002/jee.20324.[2] S. Liu, S. Xu, Q. Li, H. Xiao, and S. Zhou, “Development and validation of an instrument to assess students’ science, technology, engineering, and mathematics identity,” Phys. Rev. Phys. Educ. Res., vol. 19, no. 1, p

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Vivek Singhal, University of Wisconsin - Stout; Kenan Baltaci, University of Wisconsin - Stout

Tagged Topics

Professional Papers

30 20 20 11 20 8 9 5 0 0 10 0 0 0 Very Well Very Satisfied Very Fair Well Satisfied Fair Neutral Neutral Neutral Not Well at All Not Satisfied Not Fair Q 10

Collection

2025 ASEE -GSW Annual Conference

Authors

Mohammad A Aliedeh, New Mexico State University

T2 Q1 T3 I1 V1 V2 V3 T4 Q V4 R2 R2 I R1 R1 R4 R4

Collection

2025 ASEE -GSW Annual Conference

Authors

Shadi Balawi, Texas A&M University

or harder to bend and justifywhy. This exercise takes around 5-10 minutes with class discussion and Q&A. The Baseline andStudy groups are two sections of the same course taught by the same instructor having around 80student each. Table 1. Sample Quiz Questions for Both Study and Baseline Groups. Proceedings of the 2025 ASEE Gulf-Southwest Annual Conference The University of Texas at Arlington, Arlington, TX Copyright  2025, American Society for Engineering Education 4Point Biserial Correlation Coefficients for both groups vary across questions, but all of thesequestions had positive values indicating good

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Kimberly T. Luthi, Embry-Riddle Aeronautical University - Worldwide; David Paul Harvie, Embry-Riddle Aeronautical University - Worldwide; John K Wilson, Embry-Riddle Aeronautical University - Worldwide; Monica Surrency, Embry-Riddle Aeronautical University - Worldwide

Tagged Topics

Diversity, Professional Papers

engineering-related fields. The questions also investigated how students were supported as they developedtheir identify with in the engineering community with an increased motivation to advance.Out of the responses to Q-1 (-ways you felt most supported and any areas for improvement in thepeer-led activities) 63% were positive. Similarly, positive comments made up 65% of responsesfor Q-2 (has the interaction with peers helped support your academic and career goals?) InVivowas used to code the reflective responses by themes.Positive Experiences with Peer Led ActivitiesAttitudes and interest towards engaging with peers was well supported through the first question.To answer the question, indicators around broader statements regarding the PLTL (Peer-Led

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Erin Bosarge, University of South Alabama

Tagged Topics

Diversity, Professional Papers

Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097[9] Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Shen, M. Q. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041[10] Rizvi, S., Waite, J., & Sentance, S. (2023). Artificial intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature review. Computers and Education: Artificial Intelligence, 4, 100145. https://doi.org/10.1016/j.caeai.2023.100145[11] Almatrafi, O., Johri, A., & Lee, H. (2024). A systematic review of AI literacy conceptualization, constructs, and implementation and

Collection

2025 Northeast Section Conference

Authors

Paul Cotae; Nian Zhang; Onyinye Obioha-Val

backscatter spectroscopy for standoff detection of trace explosives, “Optical Engineering, vol.59,no. 9,p.092009,2020.doi: 10.1117/1.OE.59.9.092009.[3] Chawla, Nitshe, Bowyer K, Hall L., Kegelmeyer W. “SMOTE: Synthetic Minority Over-Sampling Technique.” Journal of Artificial Research, vol.16, 2002, pp.321-357.[4] C.J. Breshike, C. A. Kendziora, R. Furstenberg, and R. A. McGrill, “Infrared backscatter imaging spectroscopy for standoff detection of trace explosive, “Journal of Applied Physics, vol.125, no.10, p.104901, 2019. doi:10.1063/1.5079622.[5] C.Liu, J. Li, M.E. Paoletti, J.M. Haut, A. Plaza and Q. Shi, “Accessibility-Free Active Learning for Hyperspectral Image Classification

Collection

2025 Northeast Section Conference

Authors

Shashi Kiran Chandrappa, Fairfield University; Sidike Paheding, Fairfield University

! 2n+1 X n X The Indian Pines dataset is a widely studied bench- f (x) = Φq ϕq,p (xp ) , (1)mark in HSI classification, captured using the Airborne q=1 p=1Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. The where ϕq,p and Φq denote the univariate inner and outerdataset was collected in a region of agricultural fields near functions, respectively. In KANs, each of these inner functionsNorthwestern Indiana, USA, and is particularly

Collection

2025 Northeast Section Conference

Authors

Shashi Kiran Chandrappa; Sidike Paheding; Yu Cai Cai

delimiters This is awesome! - Response: Positiveand retrieving key attributes, including method, URL, headers, This is bad! - Response: Negativeand classification labels. Headers are dynamically mapped Wow that movie was good! - Response: Positiveinto a structured format, and categorical labels are assigned What a horrible show! -numerical values (Normal → 0, Anamoly → 1). A combined Model Output Output: Negative 3) Chain of thought: Detailed roadmap for your LLM’s rea-soning journey. It explicitly lays out each step the LLM shouldtake, from identifying the question to analyzing informationand drawing conclusions. Model Input Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls

Conference Session

CANCELLED: Track 6: Technical Session 2: Gender Differences in Global Identity Development: Implications for Intercultural Competence in Higher Education

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Aparajita Jaiswal, Purdue University at West Lafayette (PPI); Sakhi Aggrawal, Purdue University at West Lafayette (PPI); Vidya Reddy Madana, Purdue University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

Perspect Inst, pp. 1–35, 2014, Accessed: Jul. 23, 2024. [Online]. Available: https://www.academia.edu/download/100632196/manual.pdf[15] E. Wandschneider et al., “The Forum BEVI Project: Applications and implications for international, multicultural, and transformative learning,” Mak Sense Beliefs Values Theory Res Pr., vol. 25, pp. 150–228, 2015, Accessed: Nov. 15, 2023. [Online]. Available: https://books.google.com/books?hl=en&lr=&id=1ck8CwAAQBAJ&oi=fnd&pg=PA407&d q=Wandschneider,+E.,+Pysarchik,+D.+T.,+Sternberger,+L.+G.,+Ma,+W.,+Acheson,+K.,+ et+al.+(2015).+The+Forum+BEVI+project:+Applications+and+implications+for+internati onal,+multicultural,+and+transformative+learning.+Frontiers

Conference Session

Student Papers

Collection

2025 ASEE Southeast Conference

Authors

Hammad Afzal Quddus, Mercer University; Landon James Yarbrough, Mercer University; Megan Elizabeth Batchelor, Mercer University; Chandan Roy, Mercer University

Tagged Topics

Student Papers

impedance TH and TL are calculated using equations(1) and (2) and the Q is calculated using equation (3). The area of the sample is measured.InsulationIn the original setup, closed-foam insulation was used. This proved to be a big disadvantagesince it covered the whole setup. It was crucial for the two meter bars to be perfectly aligned asthere needs to be one-dimensional heat flow throughout the whole apparatus. With closed-foaminsulation, there was no way to ensure this condition. It was possible that once pressure wasapplied, there might have been a slight misalignment, and even a minor misalignment couldbring air gaps into the system, making the data inaccurate. Figure 3: Previous Design with Closed-Foam InsulationThe team

Collection

2025 Northeast Section Conference

Authors

Safeena Khanam

. language understanding,” NAACL-HLT, 2019. • However, both methods failed to generate relevant [13] S. Reimers and I. Gurevych, “Sentence-BERT: Sentence embeddings using Siamese BERT-networks,” EMNLP, 2019. responses for Queries 4 and 5, suggesting that [14] Q. Zhu et al., “Efficient context retrieval in dialogue systems using neural certain queries may require alternative embedding similarity,” ACL, 2021. optimization strategies or more comprehensive [15] H. Jeon et al., “Memory-efficient transformer architectures for long- training data. context NLP,” ICLR

Collection

2025 Northeast Section Conference

Authors

Joseph P. Duszak; John F. Drazan; Cynthia A. Bautista

., vol. 48, no. 2, pp. 71–75, M. K. Muehlbauer, and A. Loomis, “Breaking Apr. 2023, doi: 10.1097/NNE.0000000000001318. Boundaries: How Immersive Virtual Reality Is[39] P. García-Pazo, S. Pol-Castañeda, C. Moreno-Mulet, A. physiological outcome measures,” Front. Virtual Real., Pomar-Forteza, and A. Carrero-Planells, “Virtual reality vol. 4, Aug. 2023, doi: 10.3389/frvir.2023.1211001. and critical care education in nursing: A cross-sectional [49] R. M. Dunnington, “Presence with Scenario-Based High study,” Nurse Educ. Today, vol. 131, p. 105971, Dec. Fidelity Human Patient Simulation,” Nurs. Sci. Q., vol. 2023, doi: 10.1016/j.nedt

Conference Session

Track 5: Technical Session 3: Enhancing Diversity and Inclusion for First-Generation Students: A First Year Seminar Course Approach

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Alandra Kahl, Pennsylvania State University, Greater Allegheny

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

industry-specific career modules.• Explore partnerships for experiential learning. Q&AQUESTIONS AND DISCUSSION.Mastering Essential Skills• Icebreaker fostered community and collaboration.• Critical thinking explored via case studies and problem-solving.• Time management strategies: Prioritizing, SMART goals, and scheduling.• Effective communication emphasized clear messaging and active listening.• Reflection on takeaways and skill application.Slide 1: Title Slide • Notes: Welcome everyone to the presentation on supporting first-generation students through a specialized First Year Seminar (FYS) course at Penn State Greater Allegheny. Today, I'll be sharing insights into the challenges faced by

Conference Session

Track 5: Technical Session 6: Advancing Accessibility: Leveraging Technology to Empower Deaf and Hard of Hearing Students in STEM Higher Education

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Sunday David Ubur, Virginia Polytechnic Institute and State University; Sarah Over, Virginia Tech; Denis Gracanin, Virginia Polytechnic Institute and State University; C. Cozette Comer, Virginia Polytechnic Institute and State University

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2025 CoNECD Paper Submissions, Diversity

. K. Bharti, “Real-time sign language converter for mute and deaf people,” in 2021 International Conference on Artificial Intelligence and Machine Vision (AIMV), IEEE, 2021, pp. 1–6.[33] Q. Fu, J. Fu, S. Zhang, X. Li, J. Guo, and S. Guo, “Design of intelligent human-computer interaction system for hard of hearing and non-disabled people,” IEEE Sensors Journal, vol. 21, no. 20, pp. 23 471–23 479, 2021.[34] T. H. Soe, F. Guribye, and M. Slavkovik, “Evaluating ai assisted subtitling,” in Proceedings of the 2021 ACM International Conference on Interactive Media Experiences, 2021, pp. 96–107.[35] F. Hamid Yousuf, A. Bushnaf Alwarfalli, and I. Ighneiwa, “Arabic sign language recognition system by using surface

Collection

2025 ASEE -GSW Annual Conference

Authors

Matthew Kuester, University of Mary Hardin-Baylor

in height (zA – zB) between the two locations. The volume flowrate (Q) is calculated by applying Bernoulli’s equation along a streamline that runs along the watersurface and utilizing conservation of mass between points A and B: 1/2 2𝑔(𝑧𝐴 − 𝑧𝐵 ) 𝑄 = 𝑑𝐴 𝑤𝐴 𝑑𝐴 𝑤𝐴 2 ( ) −1 ( 𝑑𝐵 𝑤𝐵 )The students also estimated the flow speed by timing how long it took a ping-pong ball to travel aspecified distance along the creek. This provided a

Collection

2025 ASEE -GSW Annual Conference

Authors

Roy Uzoma Lan; Chinedu Okonkwo, The University of Texas at San Antonio; Ibukun Gabriel Awolusi, The University of Texas at San Antonio; Jiannan Cai

/j.fuel.2022.124842Moosavi, S., & Bush, J. (2024). Embedding Sustainability in Interdisciplinary Pedagogy for Planning and Design Studios. Journal of Planning Education and Research, 44(2), 576–589. https://doi.org/10.1177/0739456X211003639Morel, J. C., Charef, R., Hamard, E., Fabbri, A., Beckett, C., & Bui, Q. B. (2021). Earth as construction material in the circular economy context: Practitioner perspectives on barriers to overcome. In Philosophical Transactions of the Royal Society B: Biological Sciences (Vol. 376, Issue 1834). Royal Society Publishing. https://doi.org/10.1098/rstb.2020.0182Nazia Kabir, Md. Ramjan Ali, Md. Ariful Islam, Tasnia Thanim Mathin, Mritunjoy

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Shuyu Wang, The Ohio State University; Rachel Louis Kajfez, The Ohio State University

Improve the Soft Skills,” Journal of Engineering Education Transformations, vol. 33, no. 3, p. 75, Jan. 2020, doi: 10.16920/jeet/2020/v33i3/147042.[3] M. Hu, J. Ji, J. Duan, and Q. Wang, “Distributed wind power virtual simulation experiment system for cultivating the ability to solve complex engineering problems,” Comput Appl Eng Educ, vol. 29, no. 6, pp. 1441–1452, 2021, doi: 10.1002/cae.22396.[4] N. Wognum, C. Bil, F. Elgh, M. Peruzzini, and W. Verhagen, “Transdisciplinary Engineering Research Challenges,” 2018.[5] R. Stroud, “Is Transdisciplinary Education Engaging the 21st Century Engineering Student?,” tjes, vol. 11, Aug. 2020, doi: 10.22545/2020/00138.[6] R. J. Lawrence, “Deciphering

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Razvan Cristian Voicu, Robotics and Mechatronics Engineering, Kennesaw State University, Marietta, GA; Muhammad Hassan Tanveer, Kennesaw State University; Ayse Tekes, Kennesaw State University

Tagged Topics

Diversity, Professional Papers

personalized learning. Rand Corporation (2015).[6] Campbell, J. P., DeBlois, P. B. & Oblinger, D. G. Academic analytics: A new tool for a newera. EDUCAUSE review 42, 40 (2007).[7] Okubo, F., Yamashita, T., Shimada, A. & Ogata, H. A neural network approach for students’performance prediction, 598–599 (2017).[8] Pan, S. J. & Yang, Q. A survey on transfer learning. IEEE Transactions on knowledge anddata engineering 22, 1345–1359 (2009).[9] John, B. Brain, mind, experience, and school. How people learn (2000).[10] Shute, V. J. Focus on formative feedback. Review of educational research 78, 153–189(2008).[11] Devlin, J. Bert: Pre-training of deep bidirectional transformers for language understanding.arXiv preprint arXiv:1810.04805 (2018).[12

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Priscilla J Hill, Mississippi State University; Bill B Elmore, Mississippi State University

Tagged Topics

Diversity, Professional Papers

TO ENTER THE CORRECT SIGN (HEAT ADDED=positive, HEAT REMOVED=negative) • Shell/Tube exchanger water-side duty, btu/hr • Fin-Fan exchanger water-side duty, btu/hr • Jacketed exchanger water-side duty, btu/hr • Reservoir Tank water-side duty, btu/hr • Uninsulated piping/equipment water-side duty, btu/hrShell/Tube exchanger • The duty of this exchanger adheres to the standard heat transfer equation • Q = Uo * Ao * ΔTlm ; where ΔTlm is the log mean temperature difference, F The total exchanger outside tube area, Ao, is 50.25 ft2 • What is the ΔTlm, F? • What is the overall heat transfer coefficient, Uo, btu/hr-ft2-F?Figure 3b. Part 2 of questions based on given data and Figure 2.Similar to the