Paper ID #35741Finite Element Analysis and Design as a Degree Requirement inUndergraduate Mechanical Engineering CurriculumDr. Shield B Lin, Prairie View A&M University Shield Lin received his Ph.D. degree in Mechanical Engineering from Texas A&M University in 1986. He has worked as an engineer in a tire manufacturer and served as a consultant for an automobile company and a projector manufacturer. As a professor in mechanical engineering at Prairie View A&M University, he teaches courses in Dynamic Systems and Controls, and Finite Element Analysis and Design. In addition to teaching, he conducts research in
) (b) Figure 1. A QuadrilateralI consider this the most elementary example of metacognition. The ability of a student to thinkbeyond what is explicitly given and seek a viable answer.Example 2: The following sequence of four-letter words has a hidden message, in fact a famoussaying. What is this famous saying?zain yain xain wain vain uain tain sain rain qain oain nain main lain kain jain iain hain fain eaindain cain bain aainAnswer: No pain, no gain. In a backwards sequence, every alphabetical letter comes with thesuffix "ain" except "p" and "g" and hence "no p-ain", "no g-ain".Example 3: Consider the following problem posed in a Korean second grade class. The objectiveis to find which of the following
Paper ID #35791Transition back to in-person class for an embedded system course inEngineering Technology during the COVID-19 pandemicDr. Byul Hur, Texas A&M University Dr. B. Hur received his B.S. degree in Electronics Engineering from Yonsei University, in Seoul, Korea, in 2000, and his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida, Gainesville, FL, USA, in 2007 and 2011, respectively. In 2016, he joined the faculty of Texas A&M University, College Station, TX. USA, where he is currently an Assistant Professor. He worked as a postdoctoral associate from 2011 to 2016 at
Paper ID #35976Using Neural Networks to Distinguish Children’s Age with Visual Featuresof SketchesMr. Aniket Patel, Texas A&M University Aniket Patel is a junior in Computer Science at Texas A&M University. He is working as an undergraduate researcher pursuing how children’s drawing ability links to other developmental features associated with learning and how machine learning can be applied to this space. He previously worked as a researcher studying material science and analyzed material diffraction patterns.Mr. Seth Polsley, Texas A&M University Seth Polsley is a PhD student at Texas A&M University in the
) (b) Figure 1: (a) One assembled lab kit, (b) Assembled pieces of each lab kit Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright 2022, American Society for Engineering Education 3For each lab, the instructor developed a video tutorial on how to complete the lab assignment athome. In addition, for a majority of the labs, a second video was developed to help with the dataanalysis. These video were uploaded to YouTube and posted on the course Canvas site. Improving Student LearningThis particular course has
to the limitation on available class time, the entry level modules are only designed for3 hours lecture time. Upon completion of the module, it is expected that students will be able to:(a) understand the importance of standards in the supply chain, and(b) recall some of the basic standardized terms widely used internationally in the logistics arena.The interdisciplinary undergraduate minor program on SCM and logistics standards requires a totalof 18 credit hours courses. It requires students to complete three of the following courses with C orbetter: IEEN 4313 Standards in Supply Chain; IEEN 4332 Principles of Engr. Management; MKTG4345 Contracts and Documentation; and MGMT 4358 Lean Operations. Students also needcomplete three of the
to cover the size of the defect area. The model of both the steel pipe anddefected steel pipe with repaired composite wrapper can be seen in Figure 2.Figure 2 – ABAQUS model of (a) steel pipe without defect (b) pipe with defect andcomposite wrapper 4Additional properties and their values that were input into ABAQUS to model the steel pipe,putty and composite wrapper can be seen below in Table 2 and Table 3. The steel pipe and theputty were modelled in separate layers and the end caps of the pipe were simulated by restrictingthe end nodes of the pipe. The putty was composed of Bisphenol A diglycidyl ether, aliphaticamine hardener, and 0.5 wt% carbon nanotubes (CNTs). The composite wrapper itself
the lownumber of runs when the simulation results are scattered. This generates an exponentially distributedtwo-state Markov chain model between these two investigated cases considering the number of runsand the probability of events. The MCS results show the reliability of the battery sizing autonomy. (a) (b) (c) Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright © 2022, American Society for Engineering Education 7
Binomial theorem? To see how the Pascal’s triangle is related to binomial expansion, we write the coefficients of the expansions in a triangular array as follows: In this array, called Pascal’s triangle after Blaise Pascal (1623 – 1662), each entry other than the 1’s is the sum of the closest pair of numbers in the line above it. The pattern continues forever. (a + b)6 = a6 + 6a5b + 15a4b2 + 20a3b3 + 15a2b4 + 6x1y5 + y6 6 6 6 6 6 = a6 + ( ) 𝑎5b1 + ( )a4b2 + ( )a3b3 + ( )a2b4 + ( )a1b5 + b6 1 2 3 4 5 Binomial Theorem
., Phang, F.A., and A.A. Aziz, (2019). The introduction to engineering course: a case study from Universiti Teknologi Malaysia. Educ. Chem. Eng., 28: 45-53. 9. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. (1st ed.). Englewood Cliffs: Prentice Hall. 10. Ahmadi, M., Dileepan, P., and M.M. Helms, (2020, Spring). Long-Term Benefits of Student- Centered Experiential Learning in an MBA Quantitative Decision Analysis Course. SAM Advanced Management Journal, 85(2): 43+. 11. Specht, L. B., and P.K. Sandlin, (1991). The differential effects of experiential learning activities and traditional lecture classes in accounting. Simulation & Gaming, 22(2): 196-210. 12
by Remote Online Learning During COVID-19,” Proceedings of the American Society for Engineering Education Annual Conference (online), 26-29 July 2021.7. El-Sayed, M., El-Sayed, J., “Achieving Capstone Design Objectives During Necessitated COVID-19 Online Teaching,” Proceedings of the American Society for Engineering Education Annual Conference (online), 26-29 July 2021.8. Fleaher, C., Suwanakeree, D., Collins, S., Kirk, G., La Torre, A., Pisacane, P., Arnett, K., McCoy, B., Hill, A., Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright 2022, American Society for Engineering
. International Conference on Communication and Signal Processing, ICCSP 2016, 513-516. doi:10.1109/ICCSP.2016.7754190 6. Kernan, J. (2002). Asymmetrical digital subscriber line ( ADSL ) an in-depth study Asymmetrical Digital Subscriber Line ( ADSL ) An In-Depth Study By John Kernan Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Information Technology Rochester Institute of Technology B . Thomas Golisano College of Computing and Information Sciences. 7. Khan, A., Baig, S., & Nawaz, T. (2015). DWMT transceiver equalization using overlap FDE for downlink ADSL. Turkish Journal of Electrical Engineering and Computer Sciences, 23, 681-697. doi:10.3906/elk
Copyright © 2022, American Society for Engineering Education 10 References 1. J. F. Groen, B. Quigley, and Y. Herry, "Examining the Use of Lecture Capture Technology: Implications for Teaching and Learning," Canadian Journal for the Scholarship of Teaching and Learning, vol. 7, no. 1, p. 8, 2016. 2. M. R. Edwards and M. E. Clinton, "A study exploring the impact of lecture capture availability and lecture capture usage on student attendance and attainment," Higher Education, vol. 77, no. 3, pp. 403-421, 2019. 3. V. I. Prodanov, "In-class lecture recording: what lecture capture has to offer to
View, TX Copyright © 2022, American Society for Engineering Education 4The strength of the protective layers for commercial face masks and PCL nanofiber was measuredusing the Shimadzu Compact Tabletop Testing Machine EZTest (EZ-X Series) with a maximum500 N load capacity and a crosshead speed range of 0.001 to 1000 mm/min. The tests were carriedout at a 4 mm/min stretch rate. Figure 3. Stress-Strain diagram for a) PCL, NSM and KN95 filtration layers and b) tensile testing of PCL nanofiberThe gauge length of the samples was 1 inch. The maximum tensile strength of the layers wascalculated from the stress-strain
]. Figure 1: Security responsibilities in Infrastructure as a Service Model (IaaS)[b] Platform as a Service Model (PaaS)PaaS is the delivery of a computing platform and solution stack as a service. When using PaaS,the customer is only responsible for the application software and application data as shown inFigure 2. The customer is not required to run the operating system or any middleware that isrunning to support the application. Figure 2: Security responsibilities in Platform as a Service Model (PaaS) Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright © 2022, American Society for Engineering
University, Prairie View, TX Copyright © 2022, American Society for Engineering Education 4 a. Compression Load vs. Length b. Compression Stress vs. Slenderness Figure 3. Compression Capacity of the Bamboo Sticks LOAD LOAD Buckling failure of bracinga. RFEM Model of the Tower b. Tower Constructed and Loaded with 31-lbs at Each Arm ®Figure 4. RFEM Model, Construction, and Test of a Tower Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference
magnitude and direction. Example : A = 5 e(120)C2. Unknown vector with unknown magnitude and direction. R = R e(θR)C3. Line vector with unknown magnitude and known direction. B = B e(70)C4. Arc vector with known magnitude and unknown direction. C = 4 e(θC)A. For a System or Free Body Diagram with two unknowns:Vector Loop Equation (VLE) has only an unknown or arc vector on its left hand side (LHS).Vector System Equation (VSE) has either a line or an arc vector followed by a line vector onthe LHS and all known vectors on the right hand side.SIM1: Eliminates the LHS direction by squaring and adding the XY Component Equations of the VLE leading to an equation with a single unknown, a magnitude or
assessment of theentire microgreen supply chain. References 1. Abbaoui, B., Riedl, K. M., Ralston, R. A., Thomas-Ahner, J. M., Schwartz, S. J., Clinton, S. K, & Mortazavi, A. (2012). Inhibition of bladder cancer by broccoli isothiocyanates sulforaphane and erucic: characterization, metabolism, and interconversion. Molecular Nutrition & Food Research, 56(11), 1675–87. 2. Enssle, N. (2020). (rep.). Microgreens: Market Analysis, Growing Methods and Models. San Marcos, CA: California State University. 3. Funk, Cary and Brian Kennedy. “The New Food Fights: U.S. Public Divides Over Food Science.” Pew Research Center, Dec. 2016. Pew Research (https
Arlington AbstractThe Mechanical and Aerospace Engineering (MAE) Department at the University of Texas atArlington (UTA) launched a committee to address the rising attrition rates of students infundamental classes, such as Statics, Dynamics, Fluid Mechanics, and Solid mechanics. Thecommittee compared performance between high achieving and low achieving student populations toevaluate the ever-widening gap in student outcomes. From the initial discussions, the primarycontributing factors identified were (a) the impact of COVID-19 on pre-university preparation, (b)poor grasp of fundamental trigonometry, analytic geometry in 3D, vectors, and vector algebra, and(c) lack of problem-solving skills when faced
, self-directed research work; b. periodicopportunities for supervising work of undergraduate students in instances such as teachingassistant duties that may involve the engineering lab environment. Specifically, in the PhDseminar and research integrity course CHEN 6303, the students are led through a series of researchassignments related to literature search and writing on their dissertation proposal. Independentresearch work, viewed as self-leadership, is extensively discussed and encouraged throughout thisseries of tasks using a mentoring approach by this instructor. In a recent offering of this PhDcourse, a cohort of 19 students earned scores represented by averages ranging from 86 to 94 overfive separate but related sequential assignments
these applications, where object detection is an imperative task in this field that is to recognizecategories of objects and label their locations. This paper presents a senior design project that implemented object detection on Raspberry Pi byrunning deep learning models, where the edge devices include Raspberry Pi 3 and 4, Model B+ (Plus)Complete Starter Kit1 and a web camera. It consists of three steps: 1) hardware configuration: it is toconfigure the Raspberry Pi and mount the web-camera on the Raspberry Pi; 2) software installation:it is to install necessary software such as TensorFlow and OpenCV; 3) deploying mobile deep learningmodels on Raspberry Pi to run object detection. Experimental results demonstrate the effectiveness ofthis
), 17pp. CODEN: USXXCO US2006233695 A1 20061019.(6) Dada, Emmanuel A. ; Lau, Willie; Merritt, Richard F.; Paik, Yi H.; Swift, Graham ”Process forpreparing low molecular weight polymers”, US Patent 5,328,972 assigned to Rohm and HaasSELECTED TECHNICAL PAPERS: (1) Matthew N. O. Sadiku, Emmanuel Dada, Kazeem Olanrewaju,and Sarhan M. Musa, ”Big Data in Healthcare”, International Journal for Research in Applied Scienceand Engineering Technology, IJRASET, Volume 6, Issue VI, June 2018 (2) Kazeem B. Olanrewaju, LiemThai, and Emmanuel Dada, ”Application of Computational Fluid Dynamics (CFD) in Biotransportationof Complex Fluid in the Human System”, International Journal of Scientific and Engineering Research,IJSER, Volume 9, Issue 6, June 2018(3) Mathew
Paper ID #35790Capstone project progress on the floating buoy IoT device developmentfor mosquito researchDr. Byul Hur, Texas A&M University Dr. B. Hur received his B.S. degree in Electronics Engineering from Yonsei University, in Seoul, Korea, in 2000, and his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida, Gainesville, FL, USA, in 2007 and 2011, respectively. In 2016, he joined the faculty of Texas A&M University, College Station, TX. USA, where he is currently an Assistant Professor. He worked as a postdoctoral associate from 2011 to 2016 at the University Florida
, Florida A&M University - Florida State University Dr. Erik M. Hines is an associate professor in the Department of Educational Psychology and Learning Systems at the Florida State University as well as the coordinator of the Counselor Education Program and School Counseling Track. Dr. Hines prepares graduate students to be professional school counselors. Dr. Hines’s research agenda centers around: (a) college and career readiness for Black males; (b) parental involvement and its impact on academic achievement for students of color; and (c) improving and increas- ing postsecondary opportunities for first generation, low-income, and students of color (particularly Black males). Additionally, his research interests
., Yao, J., Mollura, D and Summers, R., “Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning,” IEEE Transactions on Medical Imaging, vol. 35, no. 5, pp. 1285–1298, 2016. https://doi.org/10.1109/TMI.2016.25281625. ElHalawany, B., Abdel-Kader, H., TagEldeen, A., Elsayed, A., and Nossair, Z., "Modified A* algorithm for safer mobile robot navigation," 2013 5th International Conference on Modelling, Identification and Control (ICMIC), 2013, pp. 74-78.6. Slack, Slack Platform Developer Tools, Available Online: https://slack.dev (last accessed on Jan 24, 2022)TIMOTHY HAWKINSTim graduated with a major in Electronic Systems Engineering Technology (ESET
Paper ID #35839Using a pilot course to evaluate curriculum redesign for a first yearengineering program.Dr. Janie M Moore, Texas A&M University Dr. Janie McClurkin Moore is an Assistant Professor in the Biological and Agricultural Engineering De- partment at Texas A&M University in College Station. A native of Columbus, Ohio, she attended North Carolina A&T State University where she received a B.S. in Bio Environmental Engineering in 2006. She then began pursuing her graduate education at Purdue University in the Agricultural and Biological Engineering Department, completing her Ph.D. in 2015. Her primary
Paper ID #35842Performance of an Omnidirectional Wind Energy Harvesting System for LowWind-SpeedsMr. Olatunde A, Adeoye, Prairie View A&M University Olatunde A. Adeoye received his BSC from the University of Lagos, Nigeria in 2005 after which he worked as a pupil engineer with the Electric Gas Turbine of the Nigeria Electric Power Authority (NEPA) and Ogun State Water Board as an Electrical Engineer till 2010. He became a member of the Nigerian So- ciety of Engineers (NSE) in 2009 and the Council for the Regulations of Engineering Services (COREN) in 2010. He received his MSEE from the University of Texas at El Paso
Paper ID #35973Policy implementation for microgrid implementation in TexasOlivia M Mills, Texas A&M UniversityJacqueline Estefane Torralba Jacqueline Estefane Torralba is a senior electrical engineering student at Prairie View A&M University. She is currently working on learning more about the policies surrounding microgrids in Texas due to the recent 2021 Winter Storm that affected Texas. She is part of a program called Innovation X which is a joint partnership with Prairie View A&M University and Texas A&M University to help make more sustainable creations for the future.Huei Hsin Lo, Texas A&M
Paper ID #35793eSMART: A collaborative, competitive challenge to foster engineeringeducationDr. Jay R Porter, Texas A&M University Jay R. Porter joined the Department of Engineering Technology and Industrial Distribution at Texas A&M University in 1998 and is currently the Associate Dean for Engineering at Texas A&M University - Galve- ston. He received the BS degree in electrical engineering (1987), the MS degree in physics (1989), and the Ph.D. in electrical engineering (1993) from Texas A&M University. His areas of interest in research and education include product development, analog/RF electronics
Paper ID #35772The Power of the Pre-Course Survey for Course Launch, AddressingConcerns, and Developing CommunityDr. Shawna Thomas, Texas A&M University Dr. Thomas is an Instructional Assistant Professor in the Department of Computer Science and Engineer- ing at Texas A&M University. She is a member of the Engineering Education Faculty in the Institute for Engineering Education & Innovation at Texas A&M. She enjoys project-based learning and incorporat- ing active learning techniques in all her courses. She received her Ph.D. from Texas A&M University in 2010, focusing on developing robotic motion