design types. Following the initial enrollment of each subject the random sequence of photographswere taken in both the dark skin tone and light skin tone populations. Twenty-seven photographswere taken of each test subject in numerical order from the list of random numbers listed in theBox-Behnken matrix shown in Appendix A. Following each photograph, the matching scoregenerated by the VeriLook software was entered into the corresponding cell in the matrix.Results Scores from the Box-Behnken matrix were entered into the DOE PRO statistical analysissoftware. The results from the dark skin tone subjects (Mean, x = 385.65, and Standarddeviation, s = 143.18) showed an overall greater ability of the software to identify the subjectsover
(STEM) has become a majorconcern in the United States in recent years21,22. It is widely accepted that the United States’leadership position in the world relies largely on its scientific and technical expertise. In thistechnological era, as the demand for the workforce in the STEM fields continues to grow, moreinvestments must be made in STEM education to prepare enough scientists and engineers whowill create the innovations vital for the success of the U.S. economy. However, the currentoutput from the U. S. educational system is struggling to meet this exponentially increasingdemand for scientists and engineers25. The impending wave of retiring baby boomer STEMprofessionals will worsen the situation in the next few years44. The shortage in
Paper ID #34786 1D and 3D dynamic solvers for species transport, heat transfer, electrochemical reactions (adsorption and desorption), impedance, polarization and electrical potential for solid oxide fuel cells (SOFCs) and sodium sulphur batteries (Na-S). He also has developed a novel model to predict the nickel coarsening in high temperature SOFCs based on electro-migration. His current research is related to computational modeling of liquid atomization, drag coefficient of complex geometries, combustion, fire dynamics and heat transfer mechanisms of 3D direct laser metal sintering.Dr. Chip W Ferguson, Western Carolina University Chip Ferguson is the Associate Dean of the College of Engineering and Technology and
universities. Race can be included asa third independent variable or it can be considered in other studies. The research should includethe comparison of females in different SMET programs at different universities.Finally, the researcher recommends further research on the retention of females versus males inthe electronics programs at DeVry University.Bibliographic Information1. U. S. Bureau of Labor Statistics. (2001, December 3). BLS releases 2000-2010 employment projections. Retrieved December 23, 2003, from http://www.bls.gov/news.release/ecopro.nr0.htm2. Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development (2000). Land of plenty: Diversity as America’s competitive edge in science
Paper ID #28572How Extra Credit Quizzes and Test Corrections Improve Student LearningWhile Reducing StressDr. Brian Scott Rice, Rochester Institute of Technology Dr. Brian S. Rice is an assistant professor in the Manufacturing and Mechanical Engineering Technology Department at Rochester Institute of Technology since 2016. He joined the RIT faculty after spending over 25 years in applied research while working at University of Rochester Laboratory for Laser Ener- getics, Lockheed Martin Corporation, and Eastman Kodak Company. Areas of applied research include system dynamics and controls, solid mechanics, heat transfer, and
. B. (2006). Introduction to operations and supply chain management. Pearson Education, Inc.: Upper Saddle River, New Jersey.Builder Magazine http://www.builderonline.com/Burt, D. N., Dobler, D. W. & Starling, S. L. (2003). World class supply chain management: The key to supply chain management, 7th ed. McGraw-Hill Irwin: New York, NY.Bushnell, R. D. & Meyers, R. B. (1999). Getting started with bar codes: a systematic guide.Chopra, S. & Meindl, P. (2004). Supply Chain Management, 2nd ed. Prentice Hall: New Jersey.Council of Supply Chain Management Professionals (CSCMP), http://www.cscmp.orgDrickhamer, D. (2004, May). Supply Chain Superstars. Industry Week, 253(5), 59-66.Heizer, J. & Render, B. (2006). Principles of
filter after the DAC channel. O3. Compute and analyze signal spectra using DFT/FFT algorithms. O4. Analyze filter frequency response; perform digital filtering; verify the signal spectral effects. O5. Design FIR filters and implement them in real-time using the floating-point format. O6. Design IIR filters and implement them in real-time using the floating-point format. O7. Waveform generation using digital filter(s). O8. Develop comprehensive real-time DSP project and demonstrate the implementation.B. DSP Laboratories with MATLAB and TI TSM320C67C13 DSKIn order to fulfill our course learning outcomes, we have developed our labs using bothMATLAB and TMS320C6713 DSK
Global Health, 4(3), e148-e149.[2] Roundy, C. M., Azar, S. R., Rossi, S. L., Huang, J. H., Leal, G., Yun, R., ... & Vasilakis, N.(2017). Variation in Aedes aegypti mosquito competence for Zika virus transmission. Emerginginfectious diseases, 23(4), 625.[3] Kindhauser, M. K., Allen, T., Frank, V., Santhana, R. S., & Dye, C. (2016). Zika: the originand spread of a mosquito-borne virus. Bulletin of the World Health Organization, 94(9), 675.[4] Paaijmans, K. P., & Thomas, M. B. (2011). The influence of mosquito resting behaviour andassociated microclimate for malaria risk. Malaria journal, 10(1), 1-7.[5] Murdock, C. C., Evans, M. V., McClanahan, T. D., Miazgowicz, K. L., & Tesla, B. (2017).Fine-scale variation in microclimate across
education philosophy allows offering a degreeprogram with significant amount of the course work and other requirements, such as labwork, met by external courses and work experience, the above mentioned on-lineinstruction in nanotechnology will be phased in gradually.Bibliography1. Daly, S. and L. Bryan. “Models of Nanoscale (Phenomena) as Tools for Engineering Design andScience Inquiry”. Proceedings of the 2007 ASEEAnnual Conference.2. Dhillon, H. and S. Anwar. “A Framework for the Assessment of Online Engineering TechnologyCourses: A Case Study”. Proceedings of the 2007 ASEE Annual Conference.3. Anwar, S., J. A. Rolle, and A. A. Memon. “Development and Delivery of On-line Upper DivisionEngineering Technology Courses”. Proceedings of the 2005 ASEE
shows the reduction in the FLbackscattered radiated power as distance increases, which is a familiar characteristic ofRF signal propagation. Page 13.972.6 " D i s t a n c e A p a r t ( m ) 0 " d ど 0 0 . 5
/learning methodology and corresponding assessment/evaluation method is Page 13.912.11presented. It will ensure eventual realization of the reform objectives. The curriculumreform will start from Fall semester of 2008 and completed after a learning andassessment cycle of three years.References1. Connor, H; Dench, S; Bates, P., An Assessment of Skill Needs in Engineering,Institute for Employment Studies Report, SD2, Nottingham, UK, 2001.2. Choudhury, A., Ramrattan, S. and Ikonomov, P., “A web based approach for realtime process control”, International Journal of Advanced Manufacturing Systems, Vol.8(2), 2005.3. Choudhury, A., Ikonomov, P., Keil, M
student’s mindset. The use of Excel and LabVIEW in data analysisand simulation prepares students well for the paradigm shift and for keeping the transfer optionopen.VI. AcknowledgementsWe thank B. Taylor, T. Como, and A. Kisselev for their able assistance in the development oflaboratory apparatus. Some equipment and software items are purchased with NYS Perkingrants and NSF ATE grants. This project benefited from several CUNY PSC grants.VII. Appendix:An Excel program is used to calculate the force in a 4-charge configuration. Page 11.1268.8Figure A-1: The R, S, T, U charges are located on two bars. R-S and T-U are differentpolarities for the case of
-2005. She is currently Program Director for Mechanical Engineering Technology in the Department of Mechanical Engineering at the College of Engineering, Technology, and Architecture.Natalie Segal, University of Hartford Prior to her appointment as a full-time teacher of technical communications at S. I. Ward College of Technology at the University of Hartford, Assistant Professor NATALIE SEGAL worked for more than 20 years as a technical writer and taught technical writing part-time at Ward College for eight years. She holds her Bachelor's Degree in English Education from the University of Connecticut, a Master's Degree in English from Trinity College and a Master of Fine Arts in
., Warren, C., & Newcombe, N. S. (2013). The malleability of spatial skills: A meta-analysis of training studies. Psychological Bulletin, 139(2), 352-402. 4. Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies, Cambridge University Press, New York. 5. Hegarty, M., and Waller, D. (2004). “A dissociation between mental rotation and perspective-taking spatial abilities.” Intelligence, 32(2), 175–191. 6. Lohman, D. F. (1988). “Spatial abilities as traits, processes, and knowledge.” Advances in the psychology of human intelligence, R. J. Sternberg, ed., Vol. 4, Psychology Press, New York, 181–248. 7. Maeda and Yoon 2013 8. Sorby, S., Casey, B., Veurink
experiences and influence of learning style preferences on user intentions regarding MOOCs. British Journal of Educational Technology, 46(3), 528–541. https://doi.org/10.1111/bjet.12275Evans, B. J., Baker, R. B., & Dee, T. S. (2016). Persistence patterns in massive open online courses (MOOCs). Journal of Higher Education, 87(2), 206–242. https://doi.org/10.1353/jhe.2016.0006Eynon, R., & Gillani, N. (2014). Communication patterns in massively open online courses. The Internet and Higher Education. 23. 18-26. doi:https://doi.org/10.1016/j.iheduc.2014.05.004.Feng, L., Jiang, H., Wang, J., 446485189@qq.com, & Gong, Y. (2018). Design, implementation and evaluation of MOOCs and DBL‐based cross
familiar estimationof standard deviation from range values. Although the Tabular Method is simple to use, it hassome disadvantages4. First, the range estimation of standard deviation is an approximation and issometimes inefficient. Second, it is sometimes desirable to obtain confidence intervals on thesources of measurement variation5, and that is not easily accomplished with the Tabular Method.Third, a gage capability study is truly a designed experiment so the principles of goodexperimental analysis should be applied. It is noteworthy the D. Montgomery, a leading author inthe field of quality control, has removed the Tabular Method from recent editions of histextbook(s).The later Design of Experiment Method applies those good principles of
, 2016. 5. Reese, S. (2001). Excellence in engineering technology education. Techniques, 4, 26-27. 6. Kaufman, A., Warner, S., & Buechele, J., (2011). The characteristics of model technology education teacher. Technology and Engineering Teacher, 3, 25-34. 7. ASME Vision 2030 Task Force (2012). Vision 2030: Creating the Future of Mechanical Engineering Education, Phase 1 Final Report, https://community.asme.org/board_education/w/wiki/7883.asme-vision- 2030-project.aspx; retrieved February 1, 2016. 8. Grinter, I.E. chair, ASEE Committee on Evaluation of Engineering Education (1955). Summary of the Report on Evaluation of Engineering Education. Reprinted, Journal of Engineering Education, January
routeswith varying levels of difficulty also provided an opportunity for risk taking and success throughtrial and error. In other words, if a team originally chooses a route and/or sensor(s) that requireshigher levels of programming and they continue to fail, shifting to a different and possibly easiernavigational route can happen.Before students arrived, teams were randomly formed (two teams of five and three teams of sixstudents), lab facilitators and helpers assigned, and team packets prepared with event resources,such as team member role cards. PMTM 2.0 allowed each team member to choose their rolefrom the options shown in Table 1, and the mission recorder role from 2015 was removed andthe role of data engineer added. This was primarily based on
own.Manufacturing Cost and InnovationThe percentage of jobs in the manufacturing sector has slowly been decreasing since the1940’s decade. In the early 1940’s, over 30% of all US employment was within themanufacturing sector declining to 11.0% of all employment by the end of 2005.Additionally, US employment in manufacturing sharply decreased from a steady value ofapproximately 17 million to approximately 14.5 million between the years 2000 and2004.10 (Figure 1). Page 11.579.3 Figure 1. US Employment in Manufacturing:1995-2004 (Source: Bureau of Labor Statistics)It is important to note that while the percentage of jobs in the manufacturing sector wassteadily
students carefully explained the refrigeration cycle from athermodynamic point of view. They also describe the cycle using the first law ofthermodynamics. They provided T-s diagrams for the real and ideal cycles and identifiedopportunities for efficiency improvements based on the Carnot Cycle. The group alsopresented the appropriate metric, COPrefrigeration for a household refrigerator as shownbelow: Q% evaporator COPREFRIGERATION ? W% electric _ motorWhere,Q% evaporator = Evaporator load, kWW% = Electric motor load, kW electric _ motorExperimental Design: The students outlined in detail all the necessary steps to measurethe proposed metric. The outlined steps
AC 2007-348: INTEGRATING TEAMWORK ACROSS THE CURRICULUMCharlie Edmonson, University of Dayton Charlie P. Edmonson is an Associate Professor and Program Coordinator of Industrial Engineering Technology at the University of Dayton. Prior to joining the faculty at UD, he retired from the U. S. Air Force after 30 years of engineering design, industrial engineering, and experience at various levels of management.Donna Summers, University of Dayton DONNA C.S. SUMMERS, Ph.D. is a Professor of Industrial Engineering Technology at the University of Dayton. Her major areas of concentration are Quality Assurance and Human Factors. She holds a Bachelor of Science in Mechanical Engineering from the
students who had participated in undergraduate research and found that 83%intended to continue in science-related graduate education, and that the percentage was the samefor underrepresented groups in STEM fields. In another study of 36 undergraduate minoritieswho had participated in a summer research program, Morley et al.8 found 92% of the studentseither were enrolled in a graduate program or had plans to enroll within two years. Zydney et al.9 studied a group of their university‟s alumni, matching a set of undergraduate research program Page 23.711.2participants to a set of individuals who resembled the participants except for the fact that
, Stylus Publishing, LLC,2004. Page 25.1005.75. Toohey S., "Designing courses in Higher Education", Buckingham, UK: SRHE and Open University Press,1999.6. F.P. Deek, F.P., Kimmel, H., & McHugh, J., “Pedagogical changes in the delivery of the first course in computer science: Problem solving then programming”, Journal of Engineering Education, 87, 3, pp. 313-320, July 1998.7. Meier, R.L., Williams, M.R., and Humphreys, M.A., “Refocusing our efforts: assessing non-technical competency gaps”, Journal of Engineering Education, 89, 3, pp. 377-385. 2000.8. Massa N.M., Masciadrelli G.J, Mullett G.J., " Re-Engineering Technician
surveys completed, the vast majority of ratings in all thecategories have been “4”s and “5”s. Such scores correspond to “Often” and “Always or almostalways” with respect to the student interns performing the Key Actions that demonstrate eachcompetency. The average rating for the 14 competencies and completed supervisor surveys forthe seven interns was 4.59. Given the small sample size, there are limits to the conclusions thatcan be drawn from these data, but other departments using the same methodology could obtainvaluable information for continuous improvement. The ratings of the competencies for the seveninterns are displayed in Table 2. Competencies are listed in order from highest to lowestsupervisor ratings. As indicated by the Sample Size
Consultant provide consulting services to local industry. Services include: elastomeric product design and analysis, machine design, finite element analysis, solid modeling, vibration analysis and diagnostic testing. Dr. Michael holds several patents and has several patents pending primarily in the area of noise, vibration and harshness (NVH) type isolation products. He has published extensively in this area as well. He is a licensed professional engineer in the Commonwealth of Pennsylvania.Mr. Fredrick A. Nitterright, Pennsylvania State University, Erie Mr. Fred Nitterright is a lecturer in Mechanical Engineering Technology at Penn State Erie, The Behrend College. He received the A. A. S. in Mechanical Drafting and Design in
aspects; 3) Using astandardized method for quantifying defects will lead to more statistically significant data.ACKNOWLEDGMENTSThis work was supported by the National Science Foundation grant number EEC-0552860,Research Experiences for Undergraduates (REU) Industrial Applications of Sensing, Modeling,and Control. Additional thanks to Dr. Mike Baswell for his assistance in the foundry pouringmolten aluminum and to Mr. Wayne Hawkins for his assistance in preparing specimens formetallography and analysis.BIBLIOGRAPHY 1. Abdelrahman, M. and Pardue, S., “An REU Experience on the Industrial Applications of Sensing, Modeling And Control,” Conference Proceedings of ASEE-SE Regional Conference, April 2008, Memphis, TN. 2. Abdelrahman, M
. 4, SD = 0.86 3.a. Explain the PIC16FXX embedded system circuit design. M = 4.13, Med. = 4, SD = 0.76 3.b. Use I/O pin configuration and control functions with an internal CONFIG register. M = 4.27, Med. = 4, SD = 0.65 4.a. Explain the use of a flowchart for PIC programming. M = 3.93, Med. = 4, SD = 1.01 4.b. Calculate and write a time delay loop(s
objectives. A detailed questionnaire has beendeveloped and used in several courses to gather information on the opinions and reflections ofstudents on the learning opportunities offered them. In this unique survey, presented to thestudent not as a course evaluation but as survey of the student‟s opinions of his/her own learning,students are asked to evaluate their own ability to understand and apply the course knowledgeand skills objectives. Students are asked also to rate the course various learning opportunities –lectures, text, laboratories, etc. – insofar as each opportunity aided their learning in each courseobjective.The survey has provided valuable new information to the instructor to measure and meet notonly continuous improvements in
Program 6* 7 8 S/NS** Outcomes1 Inspecting size tolerances b, c, g 1 3 NS2 Flatness “ 1 2 S3 Straightness “ 1 2 S4 Circularity “ 1 3 NS5 Parallelism “ 1 1 S6 Perpendicularity and Angularity
and present a group-basedinterim report. The report was required to consist of • Problem statement o Describe the issue(s) o Report the project sponsors’ requirements for addressing the issue(s) • Scope & schedule of the project o Itemize the work the project is going to do o Balance the responsibilities of the team members o Schedule the project (daily work schedule, and workload of each team member) • Benefits of the project o Estimate the benefits of the solution to address the issue(s) in the project (note: quantification will be needed in final report)The interim report was the first milestone of the project and the guideline for the remainingwork. After