Conference Session

Computing and Information Technology Division Technical Session 8

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Afsaneh Minaie, Utah Valley University; Reza Sanati-Mehrizy, Utah Valley University; Janis P. Raje

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Computing and Information Technology

Paper ID #29618Final Report on LEAP at UVU: An NSF S-STEM ProjectDr. Afsaneh Minaie, Utah Valley University Afsaneh Minaie is a Professor of Electrical and Computer Engineering and Chair of Engineering De- partment at Utah Valley University. She received her B.S., M.S., and Ph.D. all in Electrical Engineering from University of Oklahoma. Her research interests include gender issues in the academic sciences and engineering fields, Embedded Systems Design, Mobile Computing, Wireless Sensor Networks, Nanotech- nology, Data Mining and Databases.Dr. Reza Sanati-Mehrizy, Utah Valley University Reza Sanati-Mehrizy is a

Conference Session

Computing and Information Technology Division Technical Session 7

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2020 ASEE Virtual Annual Conference Content Access

Authors

Elsa Q. Villa, University of Texas at El Paso; Ann C. Gates, University of Texas at El Paso; Sanga Kim, University of Texas at El Paso ; David S. Knight, University of Washington

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and Policy Analysis, Educational Policy, Journal of Student Affairs Research and Practice, and Teachers College Record.Prof. David S. Knight, University of Washington David S. Knight is an assistant professor at the University of Washington. His research examines educator labor markets, school finance, and cost-effectiveness analysis. He received his PhD in urban education policy and MA in economics from the University of Southern California and bachelor’s degrees in eco- nomics and anthropology from the University of Kansas. American c Society for Engineering Education, 2020 The CAHSI INCLUDES Alliance: Realizing Collective ImpactAbstractTo

Conference Session

Computing and Information Technology Division Technical Session 1

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2020 ASEE Virtual Annual Conference Content Access

Authors

Leila Zahedi, Florida International University; Stephanie J. Lunn, Florida International University; Samira Pouyanfar, Microsoft; Monique S. Ross, Florida International University; Matthew W. Ohland, Purdue University, West Lafayette

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Computing and Information Technology

learning, and big data. She has published over 30 research papers in international journals and conference proceedings. She is currently working as a data scientist at Microsoft Corporation in Seattle, Washington.Dr. Monique S Ross, Florida International University Monique Ross earned a doctoral degree in Engineering Education from Purdue University. She has a Bachelor’s degree in Computer Engineering from Elizabethtown College, a Master’s degree in Computer Science and Software Engineering from Auburn University, eleven years of experience in industry as a software engineer, and three years as a full-time faculty in the departments of computer science and engineering. Her interests focus on broadening participation in

Conference Session

Computing and Information Technology Division Technical Session 6

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2020 ASEE Virtual Annual Conference Content Access

Authors

Peng Li, East Carolina University

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Computing and Information Technology

complicated virtual environments. It is uncertain that the grant program will continue to offerfree credits in the future. Third, students create their own accounts and therefore usermanagement is a problem.In the future, we plan to develop more labs on commercial, public cloud systems and use VirtualPrivate Network (VPN) to connect students’ virtual machines with a central server to providebetter support and monitoring when needed. We are also considering integrating automaticassessment scripts through the central server on the public cloud to provide immediate feedback,which has been done successfully in some labs on our in-house, cloud-based systems.REFERENCES[1] D. Puthal, B. P. S. Sahoo, S. Mishra and S. Swain, "Cloud Computing Features, Issues

Conference Session

Computing and Information Technology Division Technical Session 1

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2020 ASEE Virtual Annual Conference Content Access

Authors

Franz J. Kurfess, California Polytechnic State University, San Luis Obispo; Maria Pantoja, California Polytechnic State University, San Luis Obispo; Irene Humer, California Polytechnic State University, San Luis Obispo

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Polytechnic State University San Luis Obispo Ph. D. Electrical Engineering and Information Technology, Vienna University of Technology M. S. Physics, University of Vienna M. S. Education Physics and Mathematics, University of Vienna Research Interests: Computer Science Education, Physics Simulation, Applied Computing c American Society for Engineering Education, 2020 Deep Learning and Artificial Intelligence: Project Collaboration across ClassesAbstract. Working in collaborative environments is an essential skill for computingprofessionals. In our program, students have significant team experience from previous classes;almost all of our classes in Cal Poly’s

Conference Session

Computing and Information Technology Division Technical Session 5

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Bin Cong, California State University at Fullerton; Christopher Ryu, California State University at Fullerton; Raman Menon Unnikrishnan, California State University at Fullerton

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Maturity Model (CMM) intosoftware engineering was developed by the Software Engineering Institute of CarnegieMellon University in 1987. The integrated version (CMMI) evolved from this early work.ABET’s Criteria 2000 was inexorably linked to the quality assurance fervor of the 1990’s[2-7]. However, the work involved in preparing for accreditation is enormous, and facultymembers do not always find the direct benefit of such work. As a result, some nontechnicalfaculty members have even resorted to excoriating the entire outcomes-based approach ofthe accreditation process publicly [8].The classroom instructors of many undergraduate courses are burdened with severalchallenges such as large class sizes, dwindling instructional support and the need to

Conference Session

Computing and Information Technology Division Technical Session 8

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Weidong Kuang, University of Texas Rio Grande Valley; Abhijit Baul, University of Texas Rio Grande Valley

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future work. First, the currentsystem consists of three Python programs (or files), and the operation of the system requiressome command line inputs. It would be more convenient for a user (e.g. instructor) to use thesystem if the system could be integrated into a single application file with a Graphic UserInterface (GUI). Second, we will update the system for a more robust face recognition if acorresponding algorithm is available. Third, based on the survey, some students have a privacyconcern on face recognition. It is important to address this concern.References[1] B.K. Mohamed and C. Raghu, “Fingerprint attendance system for classroom needs,” IndiaConference (INDICON), Annual IEEE, 2012, pp. 433-438.[2] S. N. Shah and A. Abuzneid, “IoT based

Conference Session

Computing and Information Technology Division Technical Session 5

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Shinelle Hutchinson, Purdue University, West Lafayette; Yung Han Yoon, Purdue University, West Lafayette; Neesha Shantaram; Umit Karabiyik, Purdue University, West Lafayette

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will go unreported. At this point, bad actors would be able tophysically traverse the home without fear of being recorded.Although the features offered by the Google Nest Hub Max are highly utilitarian, some featurescould pose serious threats once compromised. In regard to the broadcast function of the GoogleHome app, an intruder can trigger the devices in the house and gain control over them remotely.Consider another scenario where using the Google Home app to record reminders, could bedetrimental. In this case, the intruders can gain access to personal information, such as routineschedules of the person(s) in the house, without much difficulty. A similar scenario is thecapability of the Google Home application to set-up the hub for all the

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jeong Yang, Texas A&M University-San Antonio; Brandon Earwood, Texas A&M University-San Antonio; Young Rae Kim, Texas A&M University-San Antonio; Akhtar Lodgher, Texas A&M University - San Antonio

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Computing and Information Technology

Structures throughObjects, 7th Edition.Table 1. Cyber Security Modules with Lessons and Chapters to Cover Modules. Chapter to Module#. Implementation Approach Cover Module Lesson(s) Ch. 2. Java 4.1 Secure Variable Understanding how to write secure variable declarations is Fundamentals Declarations critical to producing overall secure code. Ch. 2. Java 1 Integer Errors Introduced with arithmetic operations. Students must be made Fundamentals familiar with how integer/floating-point division is handled. Ch. 3. Decision 5.1 Secure Division Similar to type conversion, while dividing by zero is primarily Structures a topic to be addressed

Conference Session

Computing and Information Technology Division Technical Session 5

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2020 ASEE Virtual Annual Conference Content Access

Authors

Hassan Rajaei, Bowling Green State University

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Computing and Information Technology

which random distribution suits best for their decision making, and how thedeparture of one node will become the arrival of the tandem nodes. Wa S AD Wa S D A Figure 3: A Tandem Queue model used for training students3.3. Input and Output Data ModelData models are vital to any simulation study. There are two significant parts of data that must beworked, understood, and documented: the inputs data and the outputs (or result). Each part needsto be studied, analyzed, and determined. The results need to be documented for the implementationof the model. Data models of the Healthcare Clinic of Figure 1 include:Input Data: • Arrival rate of the patients

Conference Session

Computing and Information Technology Division Technical Session 8

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Jorge Crichigno, University of South Carolina; Elias Bou-Harb, University of Texas at San Antonio; Elie Kfoury, University of South Carolina; Jose Gomez, University of South Carolina; Antonio Mangino, University of Texas at San Antonio

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overlooked by practitioners and researchers. Additionally, the platform has supportedworkshops organized across the country. Workshops are co-organized with organizations thatoperate large backbone networks connecting research centers and national laboratories, andcolleges and universities conducting teaching and research activities.1. IntroductionGeneral-purpose enterprise networks are capable of transporting basic data, e.g., emails,multimedia, and web content. However, these networks face many challenges when movingpetabytes (PBs) of scientific data, e.g., genomic, climate, imaging, and high-energy physics, [1].As a response, network architects have developed the concept of a Science Demilitarized Zone(Science DMZ or S-DMZ) [2] as parts of a

Conference Session

Computing and Information Technology Division Technical Session 2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Tamer Omar, California State Polytechnic University, Pomona; Abdelfattah Amamra, California State Polytechnic University, Pomona; Kristina Rigden, California State Polytechnic University, Pomona; Thomas Ketseoglou, California State Polytechnic University, Pomona

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Computing and Information Technology

trips. If networkintrusion attacks succeed to compromise IoV systems, intruders will control the autonomous vehiclescommunicating with the infrastructure, and this may lead to serious fatal consequences. Therefore,using an IDS to protect the IoV system is very crucial. In this project, students will use traditional IDSto protect the IoV system.REFERENCES[1] Cisco, "Cisco Visual Networking Index: Forecast and Trends, 2017–2022 White Paper," 2019.[2] IBM, "The demand for cybersecurity professionals is outstripping the supply of skilled workers," 2019.[3] T. Omar, S. Venkatesan and A. Amamra, "Development of Undergraduate Interdisciplinary Cybersecurity Program: A Literature Survey," in ASEE Annual Conference & Exposition, Salt

Conference Session

Computing and Information Technology Division Technical Session 1

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2020 ASEE Virtual Annual Conference Content Access

Authors

Mia Minnes, University of California, San Diego; Sheena Ghanbari Serslev, University of California, San Diego ; Madison Edwards

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Computing and Information Technology

-surveys. TABLE II T O WHOM DO STUDENTS TURN FOR HELP WHILE STUDYING ? A S REPORTED BY STUDENTS BEFORE AND AFTER THEIR INTERNSHIPS . Resource Number (percent) of students report- Number (percent) of students report- ing typically consulting this resource ing typically consulting this resource (pre-survey) (post-survey) The class discussion board 47 (78%) 47 (78%) Your friends 49 (82%) 52 (87%) The instructor, TAs, and/or tutors 47 (78

Conference Session

Computing and Information Technology Division Technical Session 4

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2020 ASEE Virtual Annual Conference Content Access

Authors

Awatif Amin, Johnson C. Smith University

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to evaluatethe impact of retention factors on larger private and public institutions. Machine Learning and datamining can be very rewarding as researchers can apply many different methods to institutions of all sizesand types as needed. The suggestion of establishing a centralized center supporting different kinds ofresearch to solve retention problems could impact the university’s marketing and recruitment activities aswell. Improved management of new, innovative, and existing resources could improve retention andallow for greater financial stability at Jonson C. Smith University.References[1] L. A. Spakman, W. S. Maulding and j. G. Roberts, "Non-cognitive predictors of student success in college.," College Student Journa, p. 46, Fall

Conference Session

Computing and Information Technology Division Technical Session 3

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2020 ASEE Virtual Annual Conference Content Access

Authors

Daqing Hou, Clarkson University; Yu Liu, Clarkson University

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. I. I NTRODUCTIONHigh Performance Computing (HPC) stands at the forefront of engineering innovation [1, 2].With affordable and advanced HPC resources more readily accessible than ever before,computational simulation of complex physical phenomena is an increasingly attractive strategyto predict the physical behavior of diverse engineered systems [2], such as systems in nuclearsafety [3], outcome of cancer treatment [4], or multidimensional flight stresses on aircraft. Tomaintain the U.S.’s leadership position in HPC production and application [2], and to meet theneeds of the rapidly growing HPC market [5], American institutions of higher education mustproduce a sufficient supply of highly-trained HPC professionals. Sadly, at current rates

Conference Session

Computing and Information Technology Division Technical Session 7

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Hassan Rajaei, Bowling Green State University

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Computing and Information Technology

Characteristics of World-Wide- Web Client Proxy Caches. USENIX Symposium on IT and Systems. Vol. 997. 1997.4. Murlimanohar N, Balasubramonium R, Jouppi N.P. CACTI 6.0: A Tool to Model Large Caches. HP Laboratories, 20095. Todd Austin, SimpleScalar LLC, www.simplescalar.com6. S. Przybylski, M. Horowitz, J. Hennessey. Characteristics of performance-optimal multi-level cache hierarchies. ACM SIGARCH Computer Architecture news, June, 19897. Conte T.M., Hirsch M.A., Hwu W. Combining Trace Sampling with Single Pass Methods for Efficient Cache Simulation. In: IEEE Transactions on Computers, 19988. Sugumar R, Abraham S. Set Associative Cache Simulation Using Generalized Binomial Trees. In: ACM Transaction on Computer Systems, 2005.9

Conference Session

Computing and Information Technology Division Technical Session 5

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2020 ASEE Virtual Annual Conference Content Access

Authors

Alireza Kavianpour, DeVry University, Pomona

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data for the REETsenior project was analyzed. Several recommendations for improving student’s outcomes aresuggested.References1. Alternative Energy Systems and Applications, by B. K. Hodge, 2010, John Wily & Sons, Inc.2. Electric Machinery Fundamentals, 5th, S. Chapman, 2011 McGraw-Hill3. Power Electronics: Principles & Applications, Jacob, J. Michael, 20024. Renewable Energy - Sustainable Energy Concepts for the Future, engenmayr, Roland andBührke, Thomas, Eds., 2008.0 Verlag GmbH and Co. KGaA., Weinheim, Germany5. Alternative Energy Systems in Building Design Gevorkian, P. (2010), New York: McGraw-Hill.6. Techniques for a Wind Energy System Integration with an Islanded Microgrid Goyal, M., Fan,Y., Ghosh, A., & Shahnia, F. (2016

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Abul K. M. Azad, Northern Illinois University

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Computing and Information Technology

.[3] A. Miguel, J. F. PradaJuan, A. Serafín, G. Sergio and Manuel, D. “Challenges and solutions in remote laboratories. Application to a remote laboratory of an electro- pneumatic classification cell,” Computers & Education, vol. 85, pp. 180-190, July 2015.[4] D. Lowe, P. Newcombe and B. Stumpers, B. “Evaluation of the Use of Remote Laboratories for Secondary School Science Education,” Research in Science Education, vol. 43, pp. 1197-1219, 2013.[5] E. Mitsea and A. Drigas, “A Journey into the Metacognitive Learning Strategies,” International Journal of Online and Biomedical Engineering, vol. 14, no. 14, pp. 4- 20, 2019.[6] S. Appanna, “A Review of Benefits and Limitations of Online

Conference Session

Computing and Information Technology Division Technical Session 4

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2020 ASEE Virtual Annual Conference Content Access

Authors

Lina Battestilli, North Carolina State University; Sarah Korkes, North Carolina State University

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examine these changes on student performance as well, and a morein-depth analysis with an automated tool needs to be conducted on how student code quality isimpacted. Also, future studies could look at developing methods to better enforce code qualityand good style practices in short exercises. In addition, future studies should confirm the Bloom’sTaxonomy level of CS exercises before their use, and perhaps they should even aim to work withother instructors to create a bank of CS exercises and come to a consensus on how to map CStopics to BT.References [1] S. Zweben and B. Bizot. The taulbee survey. Computing Research Association, 2018. URL https://cra.org/resources/taulbee-survey/. [2] Vincenzo Del Fatto, Gabriella Dodero, Rosella Gennari

Conference Session

Computing and Information Technology Division Technical Session 8

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Simeon Ntafos, University of Texas at Dallas

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Computing and Information Technology

. Fountain, L., and D. Llewellyn, Major Hopping: A Cohort Analysis, Proc. 1997 ASEE AnnualConference, 1997.3. Matusovich, M., Streveler, R. and R.L. Miller, Why Do Students Choose Engineering? AQualitative, Longitudinal Investigation of Students' Motivational Values, Journal of EngineeringEducation, Vol. 99, No. 4, p. 289-303.4. Meyer, M. and S. Marx, Engineering Dropouts: A Qualitative Examination of WhyUndergraduates Leave Engineering, Journal of Engineering Education, Vol. 103, No. 4, p. 525-548, 2014.5. Meyers, K., and C. Brozina, Supporting an Informed Selection of an Engineering Major, Proc.2017 ASEE Annual Conference, 2017.6. Ntafos, S. and M. Hasenhuttl, Internships, Other Employment, and Academics, 2015 ASEEAnnual Conference &

Conference Session

Computing and Information Technology Division Technical Session 6

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2020 ASEE Virtual Annual Conference Content Access

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Natasha Smith P.E., University of Virginia

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Computing and Information Technology

web-based environment for administering computer assignments. The platform is effectiveand easy to use as long as some attention is given in crafting the problem statement and estab-lishing grading rubrics. Two additional tools that were instrumental for the course included thecombination of video recording (Panopto) with live notes using PDFAnnotator on a smart screen.In addition, the video-conferencing app, Zoom, enabled live participation in the class from onlinestudents and online office hours. Finally, the LMS provided an adequate environment to collectcourse resources, communicate information, and exchange assignments.References 1 B. S. Bloom; J. T. Hastings: and G. Madaus. Handbook on formative and summative evaluation of student

Conference Session

Computing and Information Technology Division Technical Session 7

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2020 ASEE Virtual Annual Conference Content Access

Authors

Radana Dvorak, University of Portland; Heather Dillon, University of Portland; Nicole Ralston, University of Portland; Jeffrey Matthew Welch, University of Portland

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Computing and Information Technology

serve as a reference for enhancing student thinking about ethics of hacking.AcknowledgementsThanks to the W.M. Keck Foundation for funding this study. Thanks to the many undergraduatestudents who made this project and paper possible.References1. KEEN. KEEN - The Framework [Internet]. [cited 2020 Jan 16]. Available from: https://engineeringunleashed.com/mindset-matters/framework.aspx2. Gentile MC. Giving Voice to Values: How to Speak Your Mind When You Know What?s Right [Internet]. Yale University Press; 2010 [cited 2015 Mar 30]. 256 p. Available from: http://books.google.com/books/about/Giving_Voice_to_Values.html?id=Y7yrKBVflgkC &pgis=13. Logan PY, Clarkson A. Teaching students to hack: curriculum issues in

Conference Session

Computing and Information Technology Division Technical Session 2

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2020 ASEE Virtual Annual Conference Content Access

Authors

Alyssa Mendlein, Temple University; Thuy-Trinh Nguyen, Temple University ; Aunshul Rege, Temple University

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board for guiding us to ensure that this project wouldbe safe, ethical and fun for all those involved. This material is supported by the National ScienceFoundation Award No. 1453040.8. References[1] R. D. Steele, “The importance of open source intelligence to the military,” International Journal of Intelligence and Counter Intelligence, vol. 8, no. 4, pp. 457-470, 1995.[2] S. Mercado, “Sailing the sea of OSINT in the information age,” Studies in Intelligence, vol. 43, no. 3, pp. 45-55, 2009.[3] D. R. Hayes and F. Cappa, “Open-source intelligence for risk assessment,” Business Horizons, vol. 61, no. 5, pp. 689-697, 2018.[4] A. K. Sood and R. J. Enbody, “Targeted cyberattacks: a superset of advanced persistent threats,” IEEE

Conference Session

Computing and Information Technology Division Technical Session 6

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Ciprian Popoviciu, East Carolina University; Philip J. Lunsford II, East Carolina University; John Pickard, East Carolina University; Colby Lee Sawyer, East Carolina University; Jarvis Woodburn; Zachary Ryan Zynda, East Carolina University; Dale Drummond, East Carolina University

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Conference4. Cisco WebEx Board, https://www.cisco.com/c/en/us/products/collaboration-endpoints/webex-board/index.html5. Cisco WebEx conferencing service, https://www.webex.com6. C. Popoviciu, P. Lunsford, J. Pickard, C. Sawyer, S. Wear, S. Lee, D. Drummond, " Deploying EdgeComputing to Augment Endpoint Functionality", Submitted to 2020 ASEE Annual Conference7. G. Aceto, A. Botta, W. de Donato, A. Pescape, "Cloud Monitoring: A Survey", Elsevier, vol 57, issue 9,p. 2093-2115 (2013)8. J. Edwards, "Data Silos: Now and Forever?" https://www.informationweek.com/strategic-cio/it-strategy/data-silos-now-and-forever/a/d-id/13332469. L.Skorin-Karpov, M. Varela, T. Hoßfeld, K. Chen, "A Survey of Emerging Concepts and Challenges forQoE Management of Multimedia

Conference Session

Computing and Information Technology Division Technical Session 3

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2020 ASEE Virtual Annual Conference Content Access

Authors

Vukica M. Jovanovic, Old Dominion University; Murat Kuzlu, Old Dominion University; Otilia Popescu, Old Dominion University; Abdul Rahman Badawi, Old Dominion University; Deborah Kay Marshall, Norfolk Public Schools; Salih Sarp, Old Dominion University; Spyridoula Tsouganatou, Old Dominion University; Petros J. Katsioloudis, Old Dominion University; Linda Vahala, Old Dominion University; Hongyi Michael Wu, Old Dominion University

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Education Virginia Department of Education, Richmond, Virginia, 2016, [Online]. Available: http://www.doe.virginia.gov/instruction/career_technical/cybersecurity/cybersecurity- white-paper.pdf, [Accessed Jan. 16, 2020].[2] Virginia Department of Education. “Computer Science Standards of Learning (SOL)”, Computer Science, Virginia Department of Education, 2017, [Online]. Available: http://www.doe.virginia.gov/testing/sol/standards_docs/computer-science/index.shtml, [Accessed Jan. 16, 2020].[3] S. B., Fee, A. M. Holland-Minkley. “Teaching computer science through problems, not solutions”. Computer Science Education, 2010. vol. 20. no. 2. pp. 129-144.[4] Code.org. Hadi Partovi, Code.org, 2019, [Online

Conference Session

Computing and Information Technology Division Technical Session 1

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2020 ASEE Virtual Annual Conference Content Access

Authors

James K. Nelson Jr. P.E., Texas A&M University; Brent L. Donham, Texas A&M University-Commerce

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Computing and Information Technology

. [Online]. Available: https://universaltechnews.com/it-ot-cybersecurity-convergence-arc- viewpoints-blog/.[5] J. Manyika and et. al., "Unlocking the Potential of the Internet of Things," McKinsey Global Institute, McKinsey and Company, June 2015.[6] THECB, "Lower-Division Academic Course Guide Manual," Texas Higher Education Coordinating Board, Austin, TX, 2019.[7] Center for Academic Cyber Defense, "2019 Knowedge Units," [Online]. Available: http://www.iad.gov/NIETP/documents/Requirements/CAE- CD_2019_Knowledge_Units.pdf. [Accessed 2020].[8] ABET, "Criteria for Accrediting Computing Programs, Effective for Reviews During the 2020-2021 Accreditation Cycle," ABET, Inc., Baltimore, 2019.[9] J. K. Nelson, D. Davis, S. Smith and M

Conference Session

Computing and Information Technology Division Technical Session 9

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2020 ASEE Virtual Annual Conference Content Access

Authors

Yuzhong Shen, Old Dominion University; Anthony W. Dean, Old Dominion University; Rafael Landaeta, Old Dominion University

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Computing and Information Technology

designed in the early 1980’s to reduceemissions by monitoring the performance of major engine component. The major component ofthe OBD is the Electronic Control Unit (ECU, Figure 3(a)), which receives inputs from varioussensors and control the actuators. OBDs provide digital trouble codes (DTCs) that can beaccessed via the Digital Link Connector (DLC, Figure 3(b)). (a) Components of OBD (b) OBD-II Port Figure 2. On-board Diagnostics (OBD)The latest version of OBD is OBD-II, which is available on all cars and light trucks built since1996. The OBD-II standard specifies the type of diagnostic connector and its pinout, theelectrical signaling protocols available, and the messaging

Conference Session

Computing and Information Technology Division Technical Session 4

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2020 ASEE Virtual Annual Conference Content Access

Authors

Stephany Coffman-Wolph, Ohio Northern University; Kimberlyn Gray, West Virginia University Institute of Technology

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. This first year will serve as a pilot to gain insight and feedback into the survey andassignment.Below is the table containing KEEN framework category [3], KEEN related course outcomes[4], and the artifact(s) that will be used to assess each outcome. Appendix B provides theInstructor/Peer Video Rubric and Self-Reflection Rubric and appendix C contains the surveysgiven to the students. Category of KEEN KEEN Related Course Assessment Plan Related Course Outcome [4] Outcome [3] Related to Curiosity Take ownership of, and express Grade on Video interest in topic/expertise/project. Communication Present technical information Grade from rubric on these portions

Conference Session

Computing and Information Technology Division Technical Session 4

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2020 ASEE Virtual Annual Conference Content Access

Authors

Afsaneh Minaie, Utah Valley University; Reza Sanati-Mehrizy, Utah Valley University; Benjamin Chambers

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and lidar sensor. In 2015, Teslaintroduced its autonomous car. Google and Tesla take different approach in their design. Googleuses LIDAR (Light Detection and Ranging) and Tesla uses an array of cameras for computervision. The autonomous cars can be fully autonomous without a need for a driver or can bedriver-managed autopilot-enabled. Google SDC is an example of an autonomous car without adriver and Tesla Model S is an example of the second type.The area of autonomous vehicle design has been gaining a tremendous growth in recent years. Amajor aspect of this growth has been advanced technology, a rich set of sensors and cameras,advances in computational intelligence and machine vision. The autonomous vehicle hasattracted the researchers, the

Conference Session

Computing and Information Technology Division Technical Session 9

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2020 ASEE Virtual Annual Conference Content Access

Authors

Mohammad Rafiq Muqri, DeVry University, Pomona

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Computing and Information Technology

, M., Shakib, J., A Taste of Java-Discrete and Fast Fourier Transforms, American Society for Engineering Education, AC 2011-451.2. Shakib, J., Muqri, M., Leveraging the Power of Java in the Enterprise, American Society for Engineering Education, AC 2010-1701.3. Mallat, S., Zhang, Z., Matching pursuit with time-frequency dictionaries, IEEE Trans. Signal Process., 41, 1993, 3397-3415.4. Rangayyan, R., Biomedical Signals analysis. A case-study approach, IEEE Press on Biomedical Signals. Calgary, Alberta, Canada, 20025. Feichtinger, H., Strohmer, T., Gabor Analysis and algorithms: Theory and applications, Editors. Birkhauser, Boston, 1998.6. Blinowska, K., Durka, P., The application of wavelet transform and matching pursuit to