. “Efficient hardware data mining with the Apriori algorithm on FPGAs”. In Proceedings of the 13th IEEE Symposium on Field-Programmable Custom Computing Machines, 2005.2. B. de Ruijsscher, G. N. Gaydadjiev, J. Lichtenauer, and E. Hendriks. “FPGA accelerator for real-time skin segmentation”. In Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia, 2006.3. B. Harris, A. C. Jacob, J. M. Lancaster, J. Buhler, and R. D. Chamberlain. “A banded Smith-Waterman FPGA accelerator for Mercury BLASTP”. In Proceedings of the 2007 International Conference on Field Programmable Logic and Applications, 2007.4. Xilinx MicroBlaze: http://www.xilinx.com/tools/microblaze.htm5. Altera Nios
, Los Alamos National Laboratory; Dr. Doug Neal,LaVision, Inc.References[1] J. Hertzberg, B. Leppek, and K. Gray, “Art for the Sake of Improving Attitudes towards Engineering,” p. 30, 2012.[2] J. S. Rossmann and K. A. Skvirsky, “You don’t need a weatherman to know which way the wind blows: The Art & Science of Flow Visualization,” 2010 IEEE Front. Educ. Conf. FIE, pp. F2F-1-F2F-4, 2010.[3] B. L. Smith and D. R. Neal, “Particle Image Velocimetry,” Part. Image Velocim., p. 27, 2016.[4] R. J. Adrian, “Twenty years of particle image velocimetry,” Exp. Fluids, no. 39, pp. 159– 169, 2005.[5] W.-Y. Chang, F. Lin, W.-F. Tsai, J.-S. Lai, C.-H. Loh, and S.-C. Kang, “Development of Portable PIV Devices,” in The Proceedings of
course and performance on the designproject and final exams were compared to previous semesters. The survey questions are given inthe Appendix B.ResultsThe first section of the study involved a demonstration in class of the hotSPICE tool (equivalentthermal resistance circuits) along with a homework assignment. The tool was not advertised forthe students to use on the homework to determine if they would use it on their own without areminder or encouragement. The optional survey was distributed after the homework assignmentswere collected (see Appendix B). 26 of the 58 students in the class participated in the survey Page 15.814.6
homeworksystem and an invaluable teaching and learning tool.References1 Bugbee, A. C. (1996). The Equivalence of Paper-and-Pencil and Computer-Based Testing. Journal of Research onComputing in Education, 28(3), 282-299, 1996.2 Bonham, S., Beichner, R., Titus, A., and Martin, L. (2000). Education research using web-based assessmentsystems. Journal of Research on Computing in Education, 33, 28-45.3 Tang, G. and Titus, A., (2002). Increasing Students’ Time on Task in Calculus and Physics Courses throughWebAssign. Proceedings of the 2002 ASEE Conference.4 Thoennessen, M and Harrison, M. J. (1996) “Computer-Assisted Assignments in a Large Physics Class.”Computers and Education, 27,141 1996.5 Hall, M, Parker, J, Minaei-Gigdoli, B., Albertelli, G., Kortemeyer
Design and Applications with the 68HC12 and HCS12. Upper Saddle River: Prentice Hall, 2005.3. Abramovici, Miron, Melvin A. , Arthur D. Friedman. Digital Systems Testing and Testable Design. Hoboken: Wiley, 1994.4. McCormack, John B., Robert K. Morrow, Harold F. Bare, Robert J. Burns, and James L. Rasmussen. The Complementary Roles of Laboratory Notebooks and Laboratory Reports. Proceedings: 1990 American Society for Engineering Educators Annual Conference, June 1990, Toronto, Canada, 1990.5. Kobryn, Chris. ``UML 2001,'' Communications of the ACM, October 1999, Volume 42, Number 10, pages 29-376. Fowler, Martin and Kendall Scott. UML Distilled - A Brief Guide to the Standard Object Modeling Language. Boston: 2nd ed. Addison-Wesley
videos? (choose up to 3 A) Homework Help options) B) Prepare for Lecture A) Homework Help C) Videos Shown in Class B) Prepare for Lecture D) Lecture Capture C) Videos Shown in Class E) Test Prep (FE Exam, midterms, D) Lecture Capture finals, etc.) E) Test Prep (FE Exam, midterms, F) Supplement Course Content finals, etc.) G) Other F) Supplement Course Content G) Other Q3: What qualities or
articulation also makes a difference. Interdentals (θ, ð) are made by putting thetongue between the front teeth; bilabial sounds (p, b, and m) are made by bringing both lipscloser together; and labiodental consonants (f, v) are made with the lower lip against the upperfront teeth. 8 To improve the quality of pronunciation, learners should notice the position changesof jaw, lip, teeth, and part of the tongue.Computer-Assisted Pronunciation TrainingFraser stated that a good way for educators to teach English pronunciation is by “having asuitable curriculum, being student-centered, helping learners become self-reliant, givingopportunities to practice, and knowing what’s best.” 9 Of these five principles, being student-centered and giving opportunities to
capabilities. However, weare working on extending its functionalities to infer from student-activities a student's conceptualstate in order to introduce more effective learning opportunities by developing machine learningtechniques. Furthermore, we are interested in developing a framework for studying how learnersevaluate different sources of information, how they make resource-based decisions, and evaluatepotential individualized learning sequences in the hope of developing a tailored educationalexperience.References1. J. D. Karpicke and H. L. Roediger III, “The critical importance of retrieval for learning,” Science,319(5865):966-968, Feb. 2008.2. J. D. Karpicke and J. B. Blunt, “Retrieval practice produces more learning than elaborative studying
plotted, the I-Q plot is difficult to interpret. A very simple symbolaveraging system is implemented to alleviate this problem. Figure 2 – (a) Raw VSA output for 8 QAM, and (b) symbol averaged outputIt first attempts to acquire the symbol timing and then averages the signal across each symbolinterval as is done in a classic correlation receiver. This has the effect of reducing noise power,and collapsing each symbol to a single point. The VSA plot shown in Figure 2b is much clearerthan that in 2a, and it is much easier to extract the relevant information.3. Student experiments using the VSAIn this section we describe how the VSA can be used in communication theory laboratoryexercises. Ideally, these exercises are introduced after the
and desired output. This equation is: e(n) vDes (n) vAct (n) govin (n) Gb(n)vin (n) (12)By constraining the input based on a narrow input power range, the non-linear term of G(·) canbe made smaller such that G(·) becomes a roughly linear function of the input signal. This allowsreplacing non-linear function G(·) with a scalar value G. Dividing the actual and desired outputsignals by go, the nominal PA gain, makes it such that the expected gain of each path is 1.Taking the expectation because of randomness in G due to assumption error, variation, andnoise, the complex LMS algorithm will minimize the expected error power. The iterativeequation used is: b(n 1
Chemical Engineering Department of the University of Utah. He received his B. S. and Ph. D. from the University of Utah and a M. S. from the University of California, San Diego. His teaching responsibilities include the senior unit operations laboratory and freshman design laboratory. His research interests focus on undergraduate education, targeted drug delivery, photobioreactor design, and instrumentation. Page 26.214.1 c American Society for Engineering Education, 2015 Analysis of Student Interactions with Browser-Based Interactive Simulations
the feedback they received; the intent was to discern if therewas a difference between the Tegrity and Standard written feedback sections in this respect. Thisquestion was utilized in the Fall, 2013, Spring 2014 and Fall 2014 semesters. Forty four studentsin the Tegrity feedback sections and 66 students in the Standard Written feedback sectionsanswered this particular question. It was phrased as follows: Page 26.279.8Answer the following question(s) about feedback and circle all that apply: a. I understood the feedback my instructor gave me. b. The feedback I received conveyed enthusiasm and helpfulness on the part
and deleting several variables, the finalcodebook consisted of 28 variables and their associated codes.The two phases of formative coding played an important role in (a) selecting, shaping andclarifying the variables and codes in the codebook, and (b) preparing the reviewers toindependently code the primary research with a high degree of reliability. Table 1 shows asample of the variables and codes in the final version of the codebook.Table 1. A Sample of the Variables and Codes used in the Systematic ReviewResearch Type Design proposal Empirical evaluation Review OtherStudent Model Type Model tracing only Knowledge tracing Constraint-based modeling Bayesian network modeling Expectation
(using the option Draw point for cross section point plot). 9. Find the functional relation between the time of testing and defect depth for the given object parameters and temperature conditions.Finally students prepare a report with analysis of received results.Appendix B: The results of students’ progress testing Percentage of good marks Student quiz 1 midterms quiz 2 final test groups Controllable 78 74 76 72 Experimental 86 80 85 79 Difference 8 6 9 7
position as the subject walks (Fig. 7a). Theycan derive all necessary kinematic parameters, solve the kinetics problem, and extract forces andmoments at each joint while walking (Fig. 7b). In lieu of a force plate, the ground reaction forcescome from normal-gait force data [9]. Next year, when students from the redesigned MATLABlaboratory sequence perform the same experiment, we will have a more quantitative measure ofhow their programming skills have improved. Fig. 7: Gait analysis. (a) Joint positions during video. (b) Schematic representation of gait with qualitative force vectors at each joint.DiscussionThe relatively stagnant evaluation scores during the lab changeover between 2014 and 2015 weredue mostly to technical problems
included as control variables that would allow theresearchers to examine the influence of prior knowledge, frequency of simulation interaction,and perceived preparation.There were also two items on the survey where students were asked to “Select all the skills youfeel MyITLab prepared you for” (simulation preparation) and “Select all of the skills you feltwere on the Excel exam” (application). Each list contained the same 19 skills including: skills a)taught in the simulation (MyITLab) and tested with the application (Excel Exam); b) taught inthe simulation, but not tested for with the application; c) not taught in the simulation, but testedfor with the application; and d) not taught in the simulation nor tested for with the application.These
. Cambridge Univ. Press, 2005. 7. D Wiley. The instructional use of learning objects. Association for Instructional Technology, 2002. 8. D Jonassen, K Peck, and B Wilson. Learning with technology: A constructivist perspective. Merrill/Prentice-Hall, 1999. 9. S Papert. Computer-based microworlds as incubators for powerful ideas. In The computer in the school: Tutor, tool, and tutee, pages 203–210. College Press, 1981.10. M Scardamalia, C Bereiter, RS McLean, J Swallow, and E Woodruff. Computer supported intentional learning Page 22.1700.13 environments. Journal of Educational Computing Research, 5:51–68, 1989.11. D Jonassen
column represents the number of daysduring which the feature was available for the feature selection process, aside hundreds of others. Number of times Availability (out Feature selected (out of 7) of 7)(a) Number of compiler errors encountered in 6 7 assignment X(b) Error Quotient of the student 5 7(c) Binary variable - 1 if the student solved 4 7 assignment Y, else 0(d) Amount of time spent on assignment X
_random_numb use seedVal ers • Using %9 instead of %1034% 2_11_2_Success char letterStart; char letterStartA = 'a'; • Missing cin() ive char letterStartB = 'b'; • Missing cout() after _letters cin >> letterStart; cin() cout << letterStart; letterStartB = letterStartA + 1; • Missing incrementing letterStart
transition concerning FLI students (i.e. Economics andBelonging) are reiterated by the blog entries of students, as shown in Section 4.2.1. Some of themajor insights that college administrators obtain from these aggregated results are: (a) students arestressed and nervous during the first few weeks of school, (b) students look for financial aid, and(c) students have or seek on-campus and off-campus jobs.This knowledge could lead to scheduling additional counselling support at the start of the semesterand communicate the service to new students. Financial aid, a notoriously confusing system, maybe even more confusing to new students. Administrators could create special workshops at the startof the semester or preferably before the semester begins
completeprogram, as shown in Program 1, is written which moves the robot forward.#include CLinkbotI r o b o t ;double d i s t a n c e = 5 , r a d i u s = 1 . 7 5 ;robot . connect ( ) ;r o b o t . moveDistance ( d i s t a n c e , r a d i u s ) ; Program 1: Single robot control code.Only five lines of code are necessary to connect to the robot and move it forward. The firstline is C++ syntax to allow the code to know about all of the functions available to controlthe robot. The second line creates the robot within the code so that the functions can Page 24.1058.10interact with the correct robot. Variables are created to store
developed in subsequentyears may either add to existing VREUN modules (such that students will be able to follow theprogress of the research over time) or be based on new nanotechnology projects. Over time alibrary of such modules will be made available over the web. Adaptation of the modules to makethe material more accessible for younger students for the purposes of K12 outreach is alsoenvisioned. Figure 4. Examples of nanotechnology topics for the initial VREUN modules: (a) electrospinning of nanofibers, (b) fabrication of nanoshells for surface-enhanced Raman scattering, (c) nanohydrogels. Page
individually watch the corresponding video lecture(s). Thestudent will then be required to log into the CONSIDER system where she will be presented withthe quiz related to the topic. The quizzes will be similar to the example above but, for now, let usassume there is only one question, in particular, item (3) from the example. The student will berequired to make a specific choice (such as “domain” or “problem” or “solution”) and, in addition,will be required to include a brief explanation of her choice.The figure shows the loginscreen and the next screenof the current prototypeof the CONSIDER system,implemented as an Androidapp. Once the student hassuccessfully logged in, thesystem displays the quiz,Fig. 1(b). The student doesnot need to submit the an
. Page 22.532.10Figure 2. Student view of LectureTools. At Point “A” students can choose for the list ofcourses that have adopted LectureTools. At “B” (and similar areas) they can type notes,synchronized with the lecture slides. At “C” they are asked to self-assess their confidence inunderstanding the material being discussed. At “D” they can pose a question during lecture thatwill stream on the instructor’s web site and the web site of the assigned teaching Assistants forwhich they can post responses without the name of the questioner attached. At “E” the studentcan pop up the slide, draw on it and save the drawing. “F” represents an opportunity for studentresponse to a question. Clicking there offers the question for consideration. Button “G
; Leifer, L. (2005). Engineering design thinking, teaching, andlearning.6. Shaha, S. H. (1998). Integrated outcomes: Where CIOs need to be thinking. Health Management Technology,19(10), 447. Vazsonyi, A. (1999). Which door has the Cadillac. Decision Line, 30(1), 17-198. Abt, C. C. Serious Games. Lanham (1987), Serious games-Reprint.New York: Viking Press9. Prensky, M. (2001). Digital game-based learning. New York, NY: McGraw-Hill10. Hernandez, N. V., & Rangel, G. D. (2010). Improving engineering design education: From skills to educationalobjectives. ASME.11. Pahl, G., et al. (2007). Engineering design: A systematic approach. Springer.12. Biggs, J. B. (1970). Personality correlates of certain dimensions of study behavior. Australian Journal
of Computer Systems Organization,” IEEE Trans.On Education, Vol. 37, No. 3, pp. 247 - 256, August 1994.3. York, George, Fogg, Ruth D., “VISICOMP: The Visible Computer,” ASEE Annual Conference Proceedings,June 1996.4. Barrett, S. F., Pack, D. J., York, G. W. P., Neal, P. J., Fogg, R. D., Doskocz E. K., Stefanov, E. K., Neal, P. C.,Wright, C. H. G. and Klayton, A. R., “Student-Centered Educational Tools for the Digital Systems Curriculum,”ASEE Computers in Education Journal, Vol. IX, pp. 6 - 11, Jan - Mar 1999.5. IEEE Computer Society, Association of Computing Machines (ACM), “Computer Engineering 2004:Curriculum Guidelines for Undergraduate Degree Programs in Computer Engineering.” 12 December 2004.6. Peterson, B. and Clark, A., “PRISM: A
Conference & Exposition, American Society for Engineering Education(2009).5Doering, E., and Mu, X., “Circuits Learned By Example Online (CLEO)”, Proceedings of the 2007 ASEE AnnualConference & Exposition, American Society for Engineering Education (2007).6 Gao, Z., Varma, V., and Houck, C., “Investigation of Developing and Delivering On-Line Courses in ConstructionManagement”, Proceedings of the 2006 ASEE Annual Conference & Exposition, American Society for EngineeringEducation (2006).7 Class-Morales, F., Leake, J., and Hall, B., “Development of a Standalone Computer-Aided Tutorial to IntegrateComputational Tools into a Mechanical Design Curriculum”, Proceedings of the 2007 ASEE Annual Conference &Exposition, American Society for
main(){ InitRS232(uartOne,baudRate9600); // need this for VEX multi-robot wait1Msec(1000); motor[rightMotor] = 63; // move forward for 1 second motor[leftMotor] = 63; wait1Msec(1000); motor[rightMotor] = 0; // stop motors motor[leftMotor] = 0; string message = “RobotB Go"; SendString(message); // send message to Robot B to move}Figure 3. Multi-robot Transmitter (Robot A)#include "XbeeTools.h " // Wait for a message from Robot A, then move forwward for 1 secondtask main(){ InitRS232(uartOne,baudRate9600); // need this for VEX multi-robot wait1Msec(500); string message; ReceiveString(message); // wait for a message from Robot A motor[rightMotor] = 63; // move forward for 1
a theme (for example: Computing & Creativity) which will be presented to the facultyfellows at the beginning of the session, followed by the faculty working on their individualcourse projects. In preparation for the pilot, each faculty member was asked to pose a researchquestion with regard to computing in their course and they will use the iterative processassociated with action research to test out potential strategies. According to Kemmis as cited byHopkins: Action research is a form of self-reflective enquiry undertaken by participants in social(including educational) situations in order to improve the rationality and justice of (a) their ownsocial or educational practices, (b) their understanding of these practices, and (c) the
Stone. Haptic feedback: A brief history from telepresence to virtual reality. In Haptic Human-Computer Interaction, pages 1–16. Springer, 2001.[21] OAJ Van der Meijden and MP Schijven. The value of haptic feedback in conventional and robot-assisted minimal invasive surgery and virtual reality training: a current review. Surgical endoscopy, 23(6):1180–1190, 2009.[22] Richard Q Van der Linde, Piet Lammertse, Erwin Frederiksen, and B Ruiter. The hapticmaster, a new high-performance haptic interface. In Proc. Eurohaptics, pages 1–5, 2002.[23] N. Hungr, B. Roger, A.J. Hodgson, and C. Plaskos. Dynamic physical constraints: Emulating hard surfaces with high realism. Haptics, IEEE Transactions on, 5(1):48–57, Jan 2012.[24] R.Q. van