over the chip. The camera plugs into the USB portof a PC and produces videos (30 frames/s) of fluid flow. The magnification ranges from 10X to500X. Other camera types and set-ups are of course workable as well, including higher-endconsumer CCD cameras. The quantification of flow rate can be made adding a graduated scale inthe image, such as with a thin plastic ruler placed along the flow channel which shows theposition of the flow front in each frame along with the time for that frame. From this analysis,the flow velocity can be accurately determined as a function of time. A common analysisobjective is to determine the pressure drop ∆𝑃 between two points as a function of flow rate Q orfluid velocity v. ∆𝑃 = 𝑓
hydrogel was removed from the microscope slides. 10. The hydrogel was placed in DI water for 24 hours to rinse off any possible residual monomer solution that did not polymerize.Tensile TestingMaterials • Synthesized hydrogels • Phosphate buffered saline (PBS) solution, pH 2.2, 6.8. • 2N Shimpo Force Guage, Model:FGV-0.5XY • 1000N Shimpo Force Guage, Model: FGV-200 HX • Shimpo Tensometer • Vaseline ® • Q-tips • 3M Fine grain sand paper with fabric base • Clamp Base • Tensile Clamps • PC with Estand ® Software Page 23.167.5 • Superglue gel Procedure 1. Hydrogels with various formulations
account it will only be accurate when there is no load applied to the system, however,after this step the PID controller is used for fine-tuning the speed.BatteryFor programming purposes the state of charge (SOC) of the battery is calculated as: ܳ ܱܵ= ܥ + ܱܵܥ (9) ܥ௧where Q is the amount of charge that has entered the battery, ܥ௧ is the capacity of the battery(1.4Ah) and SOC0 is the previous state of charge. The amount of charge that has entered thebattery is: ܳ = න ݅௧ ݀ݐ (10)where ݅௧ is
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3 O ENGD Female White 3 1 P Middle Eastern ENGD Genderqueer or North African 5 3 Q ENGD Female White 0 1The survey also included an open-ended prompt “In one word, please define what sense ofbelonging means to you.” The answers to this question are summarized in Table 3: What doessense of belonging mean to you? Examining the answers to this question helped the researchersunderstand student perceptions of sense of belonging. Results indicate that, by and large,students relate belonging to feelings of inclusion (feeling
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datacollected from this NRT.AcknowledgementThis material is based upon work supported by the National Science Foundation ResearchTraineeship Program under Grant No. 1922694.References[1] E. Santillan-Jimenez, Q. Duan, J. Dariotis, and M. Crocker, "Enhancing graduate education by fully integrating research and professional skill development within a diverse, inclusive and supportive academy," in 2020 ASEE Virtual Annual Conference, 2020, DOI: 10.18260/1-2--34569. [Online]. Available: https://peer.asee.org/34569[2] E. Santillan-Jimenez, J. E. Parker, K. Mabisi, C. B. Schutzman, and M. Crocker, "Description, Assessment, and Outcomes of Three Initial Interventions Within a National Science Foundation Research Traineeship (NRT
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, "Burnout: The cost of maskingneurodiversity in graduate STEM programs," in 2023 ASEE Annual Conference & Exposition,2023, .[17] J. Asbell-Clarke, Reaching and Teaching Neurodivergent Learners in STEM: Strategies forEmbracing Uniquely Talented Problem Solvers. Taylor & Francis, 2023.[18] (). Neurodiversity, Neurodivergent. Available:https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=neurodiversity,neurodivergent&hl=en.[19] S. L. Chellappa, "Language matters for neuroinclusivity," vol. 1, (3), pp. 146, 2023.[20] M. Legault, J. Bourdon and P. Poirier, "From neurodiversity to neurodivergence: the role ofepistemic and cognitive marginalization," vol. 199, (5-6), pp. 12843-12868, 2021.[21] J. Singer, "Odd people in
and graduate students through interactions withresearchers from CAEFF researchers (a graduated NSF Engineering Research Center) workingcollaboratively with industrial researchers from Hoowaki LLC, a small-business involved ininnovative research. AcknowledgmentsThis work was primarily supported by National Science Foundation under Award EEC‐1128481and made use of ERC Shared Facilities supported by the National Science Foundation underAward Number EEC-9731680. References1. Zhang, Z-Z.; Xue, Q-J.; Liu, W-M.; Shen, W-C; Friction and Wear Behaviors of Several Polymers Under Oil-Lubricated Conditions. J. Appl. Polym. Sci., 1998, 68, 2175–2182.2. Samyn, P
equationsof the form P(D)y(t) = Q(D)x(t), for derivative operations P(D) and Q(D) and functions x(t) andy(t) by looking at the equation in a different light. The transform reframes the equation as analgebraic equation in a new variable s by which the solution is easily obtained; in fact, for acompletely relaxed system (no initial conditions), the transform almost appears to amount to aninnocent change of variables. The new world of frequency is not trivial; in fact, the concept of "frequency response" is a difficulty when teaching circuits and controls. Two prominent methods of visualizing the frequency response exist, Bode Plots and Nyquist
. 800–817, Sep. 2013, doi: 10.1080/02615479.2012.695343.[8] Q. Zhang, “Assessing the Effects of Instructor Enthusiasm on Classroom Engagement, Learning Goal Orientation, and Academic Self-Efficacy,” Communication Teacher, vol. 28, no. 1, pp. 44–56, Jan. 2014, doi: 10.1080/17404622.2013.839047.[9] K. Giridharan and R. Raju, “Impact of Teaching Strategies: Demonstration and Lecture Strategies and Impact of Teacher Effect on Academic Achievement in Engineering Education,” International Journal of Educational Sciences, vol. 14, no. 3, pp. 174–186, Aug. 2016, doi: 10.1080/09751122.2016.11890491.[10] T.-T. Wu and Y.-T. Wu, “Applying project-based learning and SCAMPER teaching strategies in engineering education to explore the
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participating ininternational experiences and suggested the latter to be better advertised. Finally, the traineesexpressed their appreciation for the support they received from the PI and the UK NRT.AcknowledgementThis material is based upon work supported by the National Science Foundation ResearchTraineeship Program under Grant No. 1922694.References[1]E. Santillan-Jimenez, Q. Duan, J. Dariotis, and M. Crocker, "Enhancing graduate education by fully integrating research and professional skill development within a diverse, inclusive and supportive academy," in 2020 ASEE Virtual Annual Conference, 2020, doi: 10.18260/1-2- -34569. [Online]. Available: https://peer.asee.org/34569[2]E. Santillan-Jimenez, J. E. Parker, K. Mabisi, C. B. Schutzman, and
out of STEM fields. Statistical Analysis Report. ," National Center for Education Statistics, NCES 2014-001, 2013. [Online]. Available: https://nces.ed.gov/pubs2014/2014001rev.pdf[7] A. J. Kezar, M. Walpole, and L. W. Perna, "Engaging Low-Income Students," in Student Engagement in Higher Education: Theoretical Perspectives and Practical Approaches for Diverse Populations, J. Q. Quaye and S. R. Harper Eds., 2nd ed. New York, NY: Routledge, 2015.[8] C. Horn and D. de la Rosa-Pohl, "Finding a place to belong: Understanding the role of place in developing learner identity among students returning to in-person learning " in ASEE Annual Conference, Minneapolis, MN, 2022.[9] D. de la Rosa
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Future, 2008 Annual Report,National Academy of Engineering, [Online]. Available: https://www.nae.edu/File.aspx?id=43355.[Accessed Apr. 11, 2019].[10] Rest, J., Narvaez, D., Bebeau, M., & Thoma, S. (1999). A neo-Kohlbergian approach: TheDIT and schema theory. Educational Psychology Review, 11(4), 291-324.[11] Zhu, Q., & Zoltowski, C. B., & Feister, M. K., & Buzzanell, P. M., & Oakes, W. C., & Mead,A. D. (2014, June), The Development of an Instrument for Assessing Individual Ethical DecisionMaking in Project-based Design Teams: Integrating Quantitative and Qualitative Methods. Paperpresented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2—23130[12] D. Burkey, R. Cimino, M. Young, K. Dahm
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both in and out of the classroom. In 2020, this activitywas conducted as a virtual webinar and student questions were asked in the Q&A feature whichwas monitored by the meeting host.After listening to the dean’s interview, students are asked to write a one-page reflection paper inwhich they are asked to describe what they learned from the interview: (1) what is needed to besuccessful in the engineering profession; (2) the expectations of, or norms for, engineeringstudents; and (3) the lessons learned from the examples provided regarding the differencebetween successful and unsuccessful engineering teams. These reflections play an important rolein helping students understand the importance of valuing diversity in engineering teams
online classroom setting,” to be presented at American Society of Engineering Education Annual Conference, Long Beach, California, July 26-29, 2021.[27] M. Q. Patton, Qualitative research and evaluation methods. Thousand Oaks, CA: Sage, 2002.[28] A. Khan, O. Egbue, B. Palkie, and J. Madden, “Active learning: Engaging students to maximize learning in an online course,” Electronic Journal of e-Learning, vol. 15, no. 2, pp. 107-115, May, 2017.
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many seconds) does it become possible to determine if a student will struggle. Asimple neural network is proposed which is used to jointly classify body language and predicttask performance. By modeling the input as both instances and sequences, a peak F Score of0.459 was obtained, after observing a student for just two seconds. Finally, an unsupervisedmethod yielded a model which could determine if a student would struggle after just 1 secondwith 59.9% accuracy.1 IntroductionIn this work, the role of machine learning for planning student intervention is investigated.Specifically, t his w ork a sks t wo q uestions: ( i) C an a s tudent’s s truggles b e p redicted basedon body language? (ii) How soon can these struggles be predicted
: Revised and Expanded Edition. New York, NY: Basic Books.[27] Bouwma-Gearhart, J., Sitomer, A., Fisher, K. Q., Smith, C., & Koretsky, M. (2016, June). Studying Organizational Change: Rigorous Attention to Complex Systems Via a Multitheoretical Research Model. In Proceedings of the 2016 ASEE Annual Conference & Exposition.[28] Scherr, R. E., & Hammer, D. (2009). Student behavior and epistemological framing: Examples from collaborative active-learning activities in physics. Cognition and Instruction, 27(2), 147-174.[29] Lattuca, L. R., & Litzinger, T. A. (2016). Studying teaching and learning in undergraduate engineering programs. In A. Johri & B. M. Olds (Eds.), Cambridge Handbook of Engineering Education
assessments. The project was received well by the class as evidenced byassessments and interviews. Additional functions and exercises are being developed anddeployed in our DSP class. Details on assessments of the new functions deployed this spring inour DSP class will be reported at the conference.Acknowledgement: This research is funded in part by the NSF IUSE program.References Material Type Works CitedJournal article [1] X. Wu, X. Zhu, G. Q. Wu, and W. Ding, “Data mining with big data,” IEEE Transactions on Knowledge and Data Engineering, vol. 26, pp. 97–107, Jan 2014Conference paper
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