this paper, wedemonstrate that it is feasible to achieve high performance in physical simulations using a simple case.There are different Python parallel libraries that are available today with the main aim of ensuringPython codes run faster in parallel to break the GIL, which is essential to promote Python as ahigh-performance programming language. With the new Python parallel libraries, physical simulationscan be executed successfully on GPUs and multicores. Taichi, NumPy and Numba are Python librariesdesigned for high-performance numerical computing and machine learning. In this paper we introducethese Python libraries / frameworks and use them to implement several physical simulations. Weevaluate the performance of these libraries and
Session XXXX An Effective Way of Teaching Electrical and Computer Engineering Capstone Senior Design Courses for Underrepresented Students Vewiser Turner, Sarhan M. Musa Electrical and Computer Engineering Department Prairie View A&M University AbstractCapstone senior design courses in electrical and computer engineering must give theunderrepresented students the opportunity to learn about the real-world engineering. In electricaland computer engineering programs at Prairie View A&M University (PVAMU), senior designcourses considered as the bridge between the academia classroom and
Paper ID #35818The Fast and Practical Approach to Effectively Securing a CloudComputing System with Today’s TechnologyMr. Emmanuel Sunday Kolawole Emmanuel S Kolawole is a PHD Student at Prairie View A&M University and currently working as a Net- work Security Engineer in one of the giant Semi-Conductor/IT Industries in USA. In his current role, he is responsible for planning, design and build security architectures. Emmanuel supervise the implemen- tation of network and computer security and ensuring compliance with corporate cyber security policies and procedures.He monitors cyber security requirements for local
Paper ID #35803Return to In-person Learning and Undergraduate Student Sense ofBelonging during the Fall 2021 SemesterDr. Laura Ann Gelles, University of Texas at Dallas Laura Gelles is a postdoctoral research associate at the University of Texas at Dallas within the Erik Jonsson School of Engineering and Computer Science where she is studying retention of undergraduate engineering students. She has extensive experience using qualitative and mixed-methods research in Engineering Education. Before joining UTD in September 2020, Laura worked at the University of San Diego on their RED grant to study institutional change
interest includes manufacturing process optimization, operations research, lean production sys- tems, supply chain management and inventory control. He is a member of ASEE, IISE, IEOM, and Phi Beta Delta Honor Society.Dr. Rafiqul Islam, Northwestern State University of Louisiana Biography Dr. RAFIQUL ISLAM has been a faculty of the Northwestern State University at Natchitoches, Louisiana in the department of Engineering Technology since January, 2000. He had been the faculty of the De- Vry University, Calgary, Alberta, Canada, for five years. He also taught for four years at the West Coast University, Los Angeles, California. He has four years of working experience in the areas of communi- cations and computer
Paper ID #35947Object Detection on Raspberry PiProf. Xishuang Dong, Prairie View A&M University Xishuang Dong is Assistant Professor of Electrical and Computer Engineering Department, Roy G. Perry College of Engineering, Prairie View A&M University. His research interests include deep learning, object detection, natural language processing, computer systems biology, and Internet of Things.Xavier Alexander DukesMr. Joshua Littleton, Prairie View A&M UniversityTri’Heem NevilleChristopher RollersonArthur L Quinney American c Society for Engineering Education, 2022
their learning inother subjects in the mechanical engineering curriculum, such as Machine Design, Heat Transfer,Mechanical Vibrations, Air Dynamics, etc. In the capstone senior design class, finite element analysispackage is the most used computer tool for design analysis and refinement process. Many students Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright 2022, American Society for Engineering Education 4also include graphical finite element analysis results in their portfolios that have assisted them inexplaining what they have learned in the
studies2,3 have reported onthe sudden shift to online learning in 2020. According to literature2,4, the effect of COVID andonline learning greatly impacted the effectiveness of student comprehension throughout the country.Students were constantly presented with distractions to learning and were unable to focus solely oncoursework. As a result, students did not submit assignments or stopped attending class. One study2suggested that a major contributor to student failure was the availability and functionality ofcomputers and computer software in an online format. Table 2 shows the difference between thepercentages of students who attempted assignments from Fall 2019 – Fall 2021. In Fall 2019, anaverage of 8.75 students attempted all homework, quiz
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
the computational “how-to” processes, byassigning them open-ended questions. These open-ended questions are broad and may have multiple rightanswers. The answers to open-ended problems will open up stimulating discussion among all students. Inthis way, every student can benefit from the open discussion by sharing ideas and learning from oneanother.4. Fostering Mathematical Curiosity to Building MotivationBuilding motivation and arousing mathematical curiosity in students takes effort and experience.Unmotivated students will not learn well, no matter how well we have prepared the lectures. Asinstructors, we play a pivotal role in recognizing these students’ trouble spots and motivating them tolearn and bring back their enthusiasm.It is no
focus on Computer Science and Software Development for STEM Education.Mr. Prasanna Vasant Kothalkar, UT Dallas Prasanna Kothalkar received the B.S. degree in Computer Engineering from Mumbai University, Mumbai, India in 2010, M.S. degree in Computer Science from University of Texas at Dallas, Dallas, United States, in 2014. He has interned at technology companies for research positions in the areas of Speech Processing and Machine Learning. Currently he is pursuing his Ph.D. degree as a Research Assistant in the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas (UTD), Richardson, United States under supervision of Dr. John H. L. Hansen. His research interests focus on Child Speech
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
2four to apply the basic programming concepts to solving common engineering problems (e.g.,interpolation; pattern identification and matching; analyzing, arranging, controlling repetitiveprocesses). The implementation committees selected Python as a programming language that wouldbe easy to learn and that students could use in other courses. Students could build on python as afirst programming language to develop their computational and algorithmic thinking skills thatwould serve them in any major discipline for subsequent years. The introduction to programming ina first engineering course would provide sufficient understanding of computer logic and good,structured, modular programming habits to be a foundation and base level of preparation
the problem-solving skills of humans with theexpertise in an input area based on knowledge-based, rule-based, or production systems, typicallyheuristics model of learned and refined over times of problem-solving experience. The architectureof these systems was inspired by the stimulus-response model of cognition from psychology and thepattern-matching-and-search model of symbolic computation, which originated in Emil Post’s workin symbolic logic [3]. The production system framework was introduced during this era. Thisallowed for flexible execution, and it also facilitated the incremental addition of knowledge, withoutdistorting the overall program structure. This rule-based knowledge representation and architectureare intuitive and relatively
Compliance Specialist in Atlanta, GA. Specifically, she worked in public drinking water compliance and regulations, regularly leading audits and inspections. Alisha also previously served as a 6th and 7th grade mathematics teacher. Her current career interests include identi- fying and integrating real-world problems in STEM learning and increasing diversity and representation in the STEM field.Mr. Alain Mota, Southern Methodist University Alain Mota is the STEM Development and Implementation Coordinator at RME and a Program Manager at the Caruth Institute for Engineering Education. In this role, he works across schools supporting the research and implementation goals of several projects at the unit and the institute. As
Pins With RISC-V Instruction Set Architecture 1 Darius Gatson, 2Ryan Barnes, 3Charles Hoffmeister, 4Marian Zaki 1,2,3 Undergraduate Computer Science Students, 4Assistant Professor Computer Science College of Science and Engineering Houston Baptist University gatsondm, barnesrd, hoffmeisterc, mzaki @hbu.edu AbstractIn this paper we are demonstrating the use of RISC-V assembly code to operate a 4-bit full adder. Thisproject was implemented as a partial fulfillment of our Computer Architecture (COSC 3341) courseproject where we learned about the latest open-source
online instruction to enhance studentengagement, comprehension, and scholarship abilities. The need for such modifications is toovercome two types of challenges: 1) student’s lack of accessibility to academic resources andcampus practices, and 2) retention rates in engineering education (e.g., not the focus of this paper).According to research studies, the effectiveness of conventional practices depends on two majoraspects: 1) classroom environment, and 2) students being able to access campus resources such asstudy spaces, books, outdoor recreation programs, advising programs, computer labs, and internetservices [11], [12], [13], [19].From these conventional practices, though Problem-based learning (PBL) [17], Project-basedlearning [27], [28
” approach coupled with a computer simulation (or even better, in a virtual realityrendering) will provide a true learning experience, in addition to enhancing retention of knowledgegained. The engineering program at Ashesi University in Accra, Ghana, stipulates a two-semestercourse in the freshman year on Foundations of Design and Entrepreneurship, that provides a greatenvironment “to cultivate within students, the critical thinking skills, the concern for others, andthe courage it will take to transform the continent.”19 AssessmentThe assessment of student progress should accompany instruction. Typical summativeassessments do not serve the purpose of helping students to improve their performance during
the instructor," Proceedings of the 2012 ASEE PSW Section Conference, 2012. 4. S. Banerjee, "To capture the research landscape of lecture capture in university education," Computers & education, vol. 160, p. 104032, 2021. 5. V. Berardi and G. E. Blundell, "A learning theory conceptual foundation for using capture technology in teaching," Information Systems Education Journal, vol. 12, no. 2, p. 64, 2014. 6. URL: https://mediasite.com/ 7. E. Seidel, "Personal communication based on Mediasite statistics at the Texas A&M University College of Engineering", 2021. 8. D. G. Oblinger and B. L. Hawkins, "The myth about online course development: A faculty member can
. (2006). Computer-mediated communication as a virtual third place: building Oldenburg’s great good places on the world wide web. New Media & Society, 8(3), 421-440.6. Li, N., Verma, H., Skevi, A., Zufferey, G., Blom, J., & Dillenbourg, P. (2014). Watching MOOCs together: investigating co-located MOOC study groups. Distance Education, 35(2), 217-233.7. Bulger, M., Bright, J., & Cobo, C. (2015). The real component of virtual learning: motivations for face-to-face MOOC meetings in developing and industrialised countries. Information, Communication & Society, 18(10), 1200- 1216.8. Mahadevan, D., Kumar, A., & Bijlani, K. (2015, August). Virtual group study rooms for MOOCS. In 2015 International Conference on
). Under his direction, EVRL has acquired and conducted research, in excess of $12M, funded from the Department of Defense, Department of Energy, Army Research Laboratory, NASA and Department of Homeland Security along with other funding from Purdue University’s Visual Analytics for Command, Control, and Interoperability Environments (VACCINE), a DHS Center of Excellence. Dr. Nyarko has also worked as an independent Software Engineer with contracts involving computa- tional engineering, scientific/engineering simulation & visualization, visual analytics, complex computer algorithm development, computer network theory, machine learning, mobile software development, and avionic system software development
greatest strengths are his experience spanning across a significant spectrum of interdisciplinary science and engineering and the management of these technology programs. He has worked on multimillion-dollar contracts with the Department of Defense, Missile Defense, Department of Energy and NASA. His current work spans a broad range of problems in computational science and engineering specifically in the use of AI and machine learning to Ocean Engineering. Some of the specific applications he works on include new ocean infrastructure, Smart Energy Absorbing Structures (SEAS), ocean renewable energy powered autonomous exploration vehicles and marine cybersecurity.Dr. Rahul Subramanian, Ocean Engineering, Texas A and M
., 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
spaces byacquiring, classifying, and disseminating IAQ data to support their community in making informeddecisions on daily actions in entering indoor spaces, such as cafeteria, bookstore, or taking the shuttleon campus. This project provided the senior Engineering, Computer Information Systems andCybersecurity students an invaluable opportunity to apply their existing technical knowledge, improvetheir time management, communication skills, and work as a team on a real-world problem.Lessons Learned Proceedings of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright © 2022, American Society for Engineering Education
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
and Computer Engineering, PVAMUNPSI/Day of Science 2020NPSIThe NPSI in 2020 was an online five-day summer learning experience. To attract high schoolstudents to NPSI, our strategy involved marketing, recruiting, and ensuring we had involvementfrom parents for legal matters such as the students' indemnification forms and photo releases.Marketing had included developing a webpage [http://www.geocities.ws/npsi/index.html], aQualtrics survey to collect the submitted data, a flyer and recruitment letter, as well as a social mediablast. Recruiting had involved identifying high schools in the area and email blasts to students andparents. The schools that participated in the program are shown in Figure 2 below. Figure 2. Distribution of
reputed Center for Arrhythmia Research at the University of Michigan, Ann Arbor, MI, for his postdoctoral training followed by a research faculty position at the University of Toledo, OH. Dr. Deo’s research interests are in computational modeling of bioelectrical systems and optics-based biosensing. Dr. Deo’s research has been funded by National Science Foundation, National Institutes of Health and American Heart Association. American c Society for Engineering Education, 2022 1 Session XXXX Application-Centric Math Curriculum
issue by having a “cap” on class sizes. The authors of thispaper recommend a “cap” of about 25 students. This is based on years of instruction, trying toincrease student engagement in a class. It is not practical to engage students, especially reluctant at-risk students, when the class size is over 25. This is especially true when one recognizes thatlearning is something that the student must accomplish. The instructor only facilitates learning. Inmany cases, and especially for “at-risk” students, the best thing a teacher can do is stop talking andlisten to the student. Students do not need more eloquent lectures or more interactive computer-based tools. They often need time to formulate their questions and be heard by someone who knowsthe
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
early 1990s (unpublished), for the kinematic analysis ofmechanisms, with its extensions, the Timoshenko problem was reduced to solving six equations,each with only one unknown. Five Simplified Integrated Methods of Solution (SIMS) with aninnovative polar unit vector notation, were developed. The ten types of basic planar vectorsystems identified by the author, in 2018, are solved with the Five SIMS with least computing. The Class-book provides reading material for 60 classes at 10 per Unit, in 6 Units.IILA (Integrated Instruction, Learning and Assessment) is achieved with a Five-fold Plan. 1. Class Reviews in OpenOffice and interactive Mathcad formats 2. YouTube Class Reviews (15 minutes each) by the author 3