the Mathscript code generated by J-DSP for the design shown in Figure 5.The processing uses the Peak Picking block in J-DSP, which selects the highest components orfirst few components from the DFT coefficients based on the choice made. The reconstructedframes after peak picking can then be handled in LabVIEW to create output files with playbackfeatures. The model created in LabVIEW is illustrated in Figure 6. An assessment quiz was administered before (pre-quiz) and after (post-quiz) the hands-onlaboratory exercise. Some of the questions posed are itemized below:1. S is the frequency domain vector representation of the speech signal vector s. If S consists ofN components, which one of the following approaches, would result in better
designs 2 K factorial design Two-level fractional factorial design Three level full and fractional factorial designs Statistical analysis of fixed effects modelModule-3: Taguchi MethodsQuality Loss Function Introduction Quality loss function for various quality characteristics Specification tolerance Tolerance designSignal to Noise Ratio Introduction S/N ratio for continuous variables S/N ratio for classified variablesIntroduction to robust engineering System design Parameter design Tolerance design Taguchi’s approach to design of experimentConclusionsWhile there is a growing need for quality engineering professionals in the current globalmanufacturing
Shop influenced your perception of Electrical Engineering?Table 3 summarizes the main questions in the exit survey given to the students who participatedin the Hobby Shop as an integral component the introductory electrical engineering course,EENG 1201-Electrical Engineering I. Page 12.930.5 12 10 8 S co re 6 4 2 0 R-1 R-2 R-3 R-4 R-5 R-6 R-7 R-8 R-9 R-10 R-11 R-12 R-13 R-14 Avg
fingerprint and other devices so that we will try to assure that a studentis alone.AcknowledgementsThe authors would like to acknowledge to the Spanish Science and Education Ministry and theSpanish National Plan I+D+I 2004-2007 the support for this paper as the project TSI2005-08225-C07-03 "mosaicLearning: Aprendizaje electrónico móvil, de código abierto, basado enestándares, seguro, contextual, personalizado y colaborativo".Bibliography 1. Martín, S., Castro, M., Peire, J. et al. Experiencias e introducción de dispositivos móviles en la Enseñanza a Distancia. Ubiquitous Computing & Ambient Intelligence, Granada Spain, 2005. 2. Rivilla, I., Castro, M. et al. Development and implementation of a collaborative environment for
these projects, as well as Dr. Caren Sax for her assistance in designing the survey,A.J. de Ruyter for his efforts to help advise some of the student teams, and Michael Rondelli forhis guidance through the technology transfer process.Bibliography1. Marin, J. A., Armstrong Jr., J. E., and Kays, J. L., "Elements of an optimal capstone designexperience," Journal of Engineering Education, vol. 88, no. 1, pp. 19-22, 1999.2. Todd, R. H., Magleby, S. P., Sorensen, C. D., Swan, B. R., and Anthony, D. K., "A survey ofcapstone engineering courses in North America," Journal of Engineering Education, vol. 84, no. Page 12.1269.54, pp. 165-174, 1995.3
returned a later Transactions article withthe same title and author (the miscellaneous paper appears to be an earlier manuscript for theTransactions article)10, and two returned no matching results whatsoever.11-12 The miscellaneouspapers without bibliographic records in Compendex came from the 1930’s, 1950’s and 1970’s,suggesting that the problem of incompleteness in ASME paper indexing is not limited to aparticular time period. The most important conclusion from this exercise is that not all ASME miscellaneoustechnical papers are indexed within Compendex. In fact, no current electronic database can claimcomplete coverage of these papers. The sampled miscellaneous papers that could not beidentified in Compendex did not appear in the print
120 14 12 100 V a lue of S e ns or R e ading 10 80 8 Range (in) 60 6 4 40 2
, 2003, v 23, n 17, pp 6748-53. 3. Kelly, S. W., Burton, A. M., Kato T., Akamatsu S., “Incidental Learning of Real-World Regularities,” Psychological Science, 2001, v 12, n 1, pp 86-89. 4. Kundrat, M. E. “Measurement and Methods Improvement for the Grand Valley State University STEPS Camp,” submitted to the STEPS Director, GVSU. 5. Greif, Michel. The Visual Factory. Productivity Press, Portland, OR: 1991.. 6. Weiss, W. H. “Human Engineering Goals, Minimum Injuries, Maximum Productivity,” Production Engineering. 1982. 7. Barnes, R. Motion and Time Study.. New York: Wiley, 1980. 8. Konz, S. Work Design.. Columbus, OH: Grid, 1979. [1990] 9. “Ergonomics:: The Scientific Approach to Making Work Human,” International
Technology BRIAN S. MATHEWS Brian S. Mathews is a public services librarian and liaison to the Woodruff School of Mechanical Engineering and the College of Computing at the Georgia Institute of Technology. He is the Library’s Distance Learning Services Coordinator. Mathews received his Master’s in Library and Information Science from the University of South Florida in 2001. Page 12.989.1© American Society for Engineering Education, 2007 Is it Real or is it Memorex?: A Distance Learning ExperienceAbstractDistance learning in engineering education is
Conference, 2004.[3] Komerath, N. M. and Smith, M. J., “Mentoring Students to Technology Careers”, Proceedings of the 2004 ASEE Annual Conference, 2004.[4] Kukulka, D. J., Barker, D. S., Favata, J. and Sanders, R., “Implementation of the Computer Science, Engineering Technology, and Mathematics Scholarship (CSEMS) Program at Buffalo State College”, Proceedings of the 2004 ASEE Annual Conference, 2004.[5] Moskal, B. M., Lasich, D. and Middleton, N., “Science Related Degrees: Improving the Retention of Women and Minorities through Research Experience, Mentoring and Financial Assistance”, Proceedings of the 2001 ASEE Annual Conference, 2001.[6] Bayles, T. M., Spence, A. M. and Morrell, C., “Improving the Freshman Engineering Experience
2006-1740: A MODEL FOR BUILDING AND SUSTAINING COMMUNITIES OFENGINEERING EDUCATION RESEARCH SCHOLARSRobin Adams, Purdue University Robin S. Adams is an Assistant Professor in the Department of Engineering Education at Purdue University. She is also leads the Institute for Scholarship on Engineering Education (ISEE) as part of the Center for the Advancement of Engineering Education (CAEE). Dr. Adams received her PhD in Education, Leadership and Policy Studies from the University of Washington, an MS in Materials Science and Engineering from the University of Washington, and a BS in Mechanical Engineering from California Polytechnic State University, San Luis Obispo. Dr. Adams' research is
-based demonstrations previously mentioned. This new board interconnects aTexas Instrument (TI) C6711 or C6713 DSP starter kit (DSK) to an Analog Devices (AD)quadrature modulator (AD9857). This modulator is capable of operating at up to 200 millionsamples per second (MS/s), with a resulting carrier or intermediate frequency of up to 80 MHz(i.e., 40% of the system’s sample frequency). An onboard 32-bit direct digital synthesizer (DDS)is used to generate the carrier waveform values. Baseband 14-bit in-phase and quadrature (I/Q)data are presented to the modulator, which can be programmed to interpolate the data at rates of4x to 252x. The AD9857 is interfaced to the DSK using an Altera Cyclone FPGA. The FPGAprovides queuing of the I/Q data, and the
, byte count, load address and record type. The recordformat also has a 2-character suffix containing a checksum7.There are six types of records for the Intel 32-bit Hexadecimal Object file. The recordtypes are 00 Data Record, 01 End Record, 02 Extended Segment Address Record, 03Start Segment Address Record, 04 Extended Linear Address Record, and 05 Start LinearAddress Record. 1. Data Record The data record which is record type 00 is the record that holds all of the data of the file. This record begins with a colon “:” followed by the count of the byte, the first byte of the address and the type of record “00”. After the data record type “00”, the data bytes follow. The checksum follows the data bytes and is 2’s
output data. Figure 2: Virtual wind tunnel laboratory with airfoilThe students are enabled to select the input parameters (angle of attack, area of airfoil), select thesystem of units and request the corresponding results by clicking the “Plot” button as shown inFigure 3. If the students want to get the outputs for a specific velocity, they can input it in theDefault Inputs block and then click the “Output the Results” button. For example, if the angle ofattack is 8°, the area of the airfoil is 5 m2 and the specified velocity is 222 m/s, the studentsobtain the outputs shown in Figure 4. Page 11.141.5
by the dean in thelate 1990’s to help stem the fairly high attrition rate of the engineering programs. At the time,each of the engineering technology programs (civil, electrical, and mechanical) had their ownfreshman course of two credits and didn’t really want to change. This change would add anadditional two credits to the curriculum which, under university guidelines, would mean that twocredits would have to be dropped elsewhere in the curriculum. Additionally, while the Page 11.835.2undergraduate engineering programs were four-year programs, with ninety percent of theirstudents starting as new freshman, the four year engineering technology
can be accessible to students, without any increase in complexity, leading to a veryeffective method to teach the programming fundamentals.Whereas the approach described above has been used on numerous occasions and inmany institutions, we believe that it has rarely been done in Matlab. Our experience with Page 11.1203.7using this method the past three years is very encouraging.References1. Brockman, J., Fuja, T. Batill, S., “A Multidisciplinary Course Sequence for First-Year EngineeringStudents,” 2002 ASEE Annual Conference and Exposition, Montreal, Quebec, Canada, June 2002.2. McWilliams, L., Silliman, S., Pieronek, C. “Modifications to a Freshman
place to study, and AT308 is no exception to the rule. Upon completion of thiscourse, students have a much better grounding in the theoretical knowledge, which they first hearand see during lectures. They understand heat treatment and different tempers of aviation gradealuminum. They also realize the importance of following heat treatment processes to getconsistent properties of the materials. The well-equipped laboratory provides a place to apply thetheory and develop their skills. It becomes more than just paper knowledge - it is something theycan touch, make, assemble, and test. Experience is the best teacher. This is what studentsexperience during their "employment" in AT308, Inc.References1. Collicott, S. H., Increasing freshmen
Engineering Circuit Analysis, s-plane, 1 complex frequency Optics Snell's Law and Critical angle of reflection 1 Applications of radian measure Radian-degree conversions, Arc Length, Area 1 and degree equivalencies of a sector of a circle, Angular velocity and linear velocity, word problems. Logarithms and Natural Logs and Sound & Decibels, Time Constants, R-L and 1 Properties R-C electric circuits in the time domain. Statistics Data Interpretation, Statistical process control 1 Space Shuttle & NASA NASA Application
discrete plurality of cycles within a given greater cyclic increment. Angle means a fraction of once cycle. Angle is therefore sub-cyclic- unity, while frequency plural unity. Angle is less than finite cyclic unity. Frequency is greater than finite cyclic unity.” 2Webster’s Greek term monad, stems Greek Ionian System: Alphabetical Enumerationfrom roots μένειν (menein), “to be μ ο ν ά ςstable”, from μονάς (monas), "unit" [m] [o] [n] [a] [s]from μόνος (monos), "alone".6 Mu Omicron Nu Alpha Sigma 40 70 50 1 200 ∑361Schneider (1994) writes: “In the
Paper ID #9711A Longitudinal Study of the Impact of a First-Year Honors Engineering Pro-gramDr. Kathleen A Harper, The Ohio State University Kathleen A. Harper is a faculty lecturer in the Engineering Education Innovation Center at The Ohio State University. She received her M. S. in physics and B. S. in electrical engineering and applied physics from Case Western Reserve University, and her Ph. D. in physics from The Ohio State University. She has been on the staff of Ohio State’s University Center for the Advancement of Teaching, in addition to teaching in both the physics department and college of engineering. Her
courses andquality of courses, have slightly less persistence as measured by a grit test, and are notparticipating as much in class. The goal of identifying the characteristics of students who do notdo homework is to enable appropriate intervention techniques to be developed. AcknowledgementThis material is based upon work supported by the National Science Foundation underEngineering Education Research Initiation Grant No. 1137013.References1. Bennett, R.M., Schleter, W.R., Olsen, T., and Guffey, S. (2011). “Effects of an early homework completion bonus.” Proceedings, ASEE Annual Convention, Paper AC 2012- 3724.2. Duckworth, A.L. and Quinn, P.D. (2009). “Development and validation of the Short Grit Scale (Grit-S),” Journal of
/Microsoft_Speech_API[6] S.W. Arms, C.P.Townsend, D.L. Churchill, J.H.Galbreath,S.W. Mundell. “Power Management forEnergy Harvesting Wireless Sensors,” SPIE Int’l Symposium on Smart Structures & Smart Materials, SanDiego, CA, March 2005, pp.1-9.[7] D. Rakhmatov and S. Vrudhula, Energy Management for Battery-Powered Embedded Systems, ACMTransactions on Embedded Computing systems, 2, August 2003[8] Philip Levis, David Gay, TinyOS Programming, Cambridge University Press, 2009.[9] Chris Merlin, “A Tutorial for Programming in TinyOS,” 2009, accessed on Dec. 20, 2012 viahttp://www.ece.rochester.edu/projects/wcng/code/Tutorial/TinyOs_Tutorial.pdf .[10] TinyOS community: http://www.tinyos.net
: 1. Preparing a BIM in Autodesk MEP 2. Energy Modeling in Green Building Studio 3. Data analysis in classification, association, clustering, and regression 4. Identifying a noble pattern through data analysis Process Software/output Preparing a BIM for energy Autodesk MEP simulation Energy Simulation Green Building Studio Data Analysis Identifying pattern(s) • Classification Decision Tree • Clustering Factor Selection
developed in the 1930’s and 1940’s3, 4, basic concepts of thermally coupledcolumns are not typically taught in undergraduate separations courses. Although they are taughtin some design courses, they are not included in the design courses at Mississippi StateUniversity. Due to the renewed interest in process intensification, a module on thermallycoupled columns is being added to an undergraduate separations course. Page 23.177.3ImplementationThe class is a junior level separations course that focuses on equilibrium staged operations,particularly distillation columns. This one semester course includes flash distillation, short-cutand rigorous
concern, because the method oftransmission was over the phone line via an FTP connection. Once the audio files were recorded,the authors individually evaluated them before placing the files into a dedicated directory structureand transmitting them to ODU for post-processing. This batch processing methodology createdsignificant delays in the module review process and continuity was difficult to maintain due to thesequence of editing events. For example, audio files submitted during “week one” may not bereturned to the author for review until three to five weeks later. This delay caused problems inmaintaining course continuity and quality control, because it was difficult for the author(s) toremember the flow and thought processes used to create
Copyright 2003, American Society of Engineering Education” Session # 2549References1. Cullen, A. (1999, March). Practising t heory. Adult Learning 10(7). 18-21. Retrieved August 27, 2001 fromhttp://data.inspire.net2. Holmes, G. & Abington-Cooper, M. (2000). Pedagogy vs. andragogy: A false dichotomy?. The Journal ofTechnology Studies 26(2). A refereed publication of Epsilon Pi Tau.3. http://www.agc.org.4. http://www.andragogy.net5. http://www.ed.gov6. Imel, S. (1994). Guidelines for working with adult learners. (ERIC Document Reproduction Service No. ED377313) Retrieved on August 27, 2001 from https://ovid.lib.purdue.edu.7
, did not give us anypositive feedback on group cohesion and performance when compared with randomly formedgroups. The extensive use of psychological type in work setting, education and career counseling [2]gave us the idea of applying personality profiles while forming our problem laboratory groups.Jung’s comprehensive theory that relates to psychological type is the belief that everyone usesfour basic processes or functions which are called sensing(S), intuition (N), thinking (T) andfeeling (F). These four processes are used with the attitudes of introversion (I) and extraversion(E) and the orientations to the outside world as judgment (J) and perception (P).Isabel Myers developed the following work expectations for the eight preferences [2
not necessarily reflect the views of the National Science Foundation.Bibliography1. Allen, I. E.; Seaman J., “Class Difference: Online Education in the United States, 2010”, Sloan Consortium of Individual, Institution and Organizations Committed to Quality Online Education, http://www.sloan- c.org/publications/survey/staying_course, 20102. Bell, J. T.; Fogler, H. S., “Virtual Reality Laboratory Accidents”, Proceedings of the American Society for Engineering Education (ASEE) Annual Conference and Exposition, Albuquerque, New Mexico, June 20013. Valera, A.; Diez, J. L.; Valles, M.; Albertos, P., “Virtual and Remote Control Laboratory Development”, IEEE Control Systems Magazine, pp. 35- 39, February 2005.4. Chen, X.; Song, G.; and
engineering disciplines. Currently thereis not enough research data available to substantially validate this claim. In addition there is a‘myth’ that PhDs are not hired at the institutions where they received their PhD. This paperattempts to quantify the hiring pattern in the field of Mechanical Engineering at the top 10Mechanical Engineering research programs in the United States.This is important as people who have trained at great length and expense to be researchersconfront a swindling number of academic jobs4. In 1974, fewer than 30% of all science andengineering (S&E) Ph.D.s were working in industry, and more than 45% were in tenure-trackfaculty positions. By 1999, the trend had reversed with nearly 38% S&E Ph.D.s who had received their
AC 2012-5131: IMPORTANCE OF UNDERGRADUATE RESEARCH INENGINEERING TECHNOLOGY PROGRAMSDr. Sidi Berri, New York City College of Technology Sidi Berri is a professor and the Chairman of the Mechanical Engineering Technology Department of New York City College of Technology.Dr. Andy Zhang, New York City College of Technology Andy S. Zhang earned his master’s in mechanical engineering from the City College of New York in 1987 and his Ph.D. in mechanical engineering from the Graduate Center of the City University of New York in 1995. Zhang’s research areas include materials testing, composite materials, CAD/CAE, engineering animation, and mechatronics design.Dr. Gaffar Barakat Gailani, New York City College of Technology