allows the student to view both root locus andBode information. Unlike the GUI in this paper, the built in design tools are not based on theunified design procedures of the author’s previous work.9,10 Consequently, it does not providethe same seamless integration for the students as they transition from simple classroom exercisesto more complicated lab and design projects.Compensator DesignThe integrated design procedure using time or frequency domain plant data requires ageneralization of the angle criterion from root locus design. The standard closed-loop system isshown in Figure 1 where K is the control gain, Gc (s) is the compensator and G p ( s ) representsthe plant dynamics. R ( s
the pedagogicalpuzzle. This feedback is used to refine and optimize the course for the student to get the mostfrom the experience. This optimization is heavily based upon the premise that students haveresponded to the best of their ability using their own work.When this premise is found to fail, a common response by the instructor is to reduce the courseweight of the component(s) where academic integrity may be questioned (e.g. computerprogramming laboratories). While this appears to limit the gains of the dishonest student, it willalso demotivate the honest students by: 1) Placing less emphasis on core aspects of the course building blocks, and 2) Continuing to reward questionable methods with high marks.In the effort to limit the
digital, weregularly process our signals in their digital or discrete form.Returning our discussion to the derivative operator, a student who has learned thefundamentals of the Laplace transform should recognize the derivative, d/dt as theLaplace independent variable s. In most texts, s= σ + jω , and for a discussion of thefrequency response, setting σ = 0 results in the classic result, s = jω . At this point, aSignals & Systems student should be able to recreate Figure 1. This should be recognizedas the magnitude only display of a Bode plot for the response of an ideal integrator, 1/s,and an ideal differentiator, s.Figure 1. The frequency response (magnitude only) of an ideal integrator, 1/s, and anideal differentiator, s. This is a portion
where he helped set up an innovative introductory engineering curriculum. Dr. Tanyel received his B. S. degree in electrical engineering from Bogaziçi University, Istanbul, Turkey in 1981, his M. S. degree in electrical engineering from Bucknell University, Lewisburg, PA in 1985 and his Ph. D. in biomedical engineering from Drexel University, Philadelphia, PA in 1990. Page 11.1434.1© American Society for Engineering Education, 2006 Communication Systems Toolkit As a Tool for InnovationAbstractIn previous publications, we have discussed the preparation1, the utilization2 and theeffectiveness3 of a
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create accuratemathematical plots on-the-fly, and dynamically manipulate graphical content to emphasizepoints of discussion.This paper is about realizing that potential for the purpose of teaching the relationships betweencontinuous-time (C-T) and discrete-time (D-T) systems. This is an area that requires a teacher topresent several different types of plots – time-domain response plots, frequency-response (e.g.,Bode) plots, and pole/zero maps in the s-plane and z-plane – and to discuss their inter- Page 13.1030.2relatedness.Certainly, there are problems using computers to create plots “on-the-fly” in the classroom, e.g.: ‚ delays resulting from
Applications sliding toolbars which allow a smooth variation of property values. Properly used by students, these worksheets have the potential to reinforce and enhance understanding of the fundamental interrelationships among various properties; students are free to change various parameters such as pressure, temperature, and quality, and immediately view the effect of these changes on the associated Mollier and T-s diagrams. Students may quickly visualize the effect of these changes, rather than being mired in the minutiae of table lookups, interpolation, transcription, and manual plotting. An additional benefit of the rapid and very accurate plotting of thermodynamic properties is a better
Education, 2016 123rd ASEE Annual Conference and Exposition New Orleans, LA, USA, June 26-29, 2016 Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C. A Virtual Laboratory System with Biometric Authentication and Remote Proctoring Based on Facial Recognition Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.AbstractVirtual laboratories are used in online education, corporate training and professional skilldevelopment. There are several aspects that determine the value and effectiveness of virtuallaboratories, namely (i) the cost of development which includes the cost of
14 N 14 u S 12 m t 10 b u 8 7 e d 6 4 3 r i 2 2 e 2 0 o s 1995-1999 2000-2004 2005-2009 2010-2014 2015-Present f Timeline Figure 1: Trends for Primary Framework Development.The histogram indicates that more than 80% of primary framework development has beenperformed before 2010. There is a very limited primary framework development effort in
. T Tclosed Open Is = 0 Figure 8: Control waveform Closed Vs = 0 Figure 7: Switch states Tclosed Ps = I s ⋅ V s = 0 (1) %Duty = ⋅100% (2) TFigure 9 is a discrete time PWM generator circuit implemented in the FPGA. The REG blocksare each registers. Registers store the increment value and threshold value IncVal and ThHold,respectively. The Phase value is represented with N p
system, will be based on a 2’s compliment numbering system where the concatenationof the sign bit and the 23 bits of the fraction, {S, F [22:0]}, make up a 2’s compliment numberwith a value between -110 and 0.9999998807907104492187510. Figure 2 – IEEE 754 protocol for single-precision floating point numbers [12].The exponent of the floating-point number, in contrast to IEEE’s exponent format, is also basedon 2’s compliment numbers and falls between a range of -128 and 127. Thus, the range of numbersallowed to be represented using this floating-point numbering system is -1.701412 x 103810 to1.701412 x 103810 with a resolution of 3.50325 x 10-4610. This give a level of accuracy that is veryprecise compared to fixed-point numbers
) Page 26.1305.1 c American Society for Engineering Education, 2015 122th ASEE Annual Conference and Exposition Seattle, Washington, USA, June 14-17, 2015 Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.Real-time 3D Reconstruction for Facilitating the Development of Game-based Virtual Laboratories Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.AbstractGame-based virtual laboratories (GBVLs) represent an important implementation of virtual realityand are often considered to be simulations of real or artificial environments. They are based
of Second Life. Tapir Academic Press, 2009.5. Seng, J. L. K. & Edirisinghe, E. M. N. S. (2007). Teaching computer science using Second Life as a learning environment. ICT: Providing choices for learners and learning. Proceedings ascilite Singapore 2007, Nanyang Technological University, Singapore, pp. 583-586.6. Tüzün, H., Yılmaz S., M., Karakuş, T., Inal, Y. & Kızılkaya, G. (2009). The effects of computer games on primary school students’ achievement and motivation in geography learning. Computers & Education, Vol. 52, No. 1, pp. 68-77.7. García-Zubia J., Irurzun, J., Angulo, I., Orduña, P., Ruiz-de-Garibay, J., Hernández, U. & Castro, M. (2010). Developing a Second-Life-based remote lab
Paper ID #24774Project-based Robotics Courses for the Students of Mechanical EngineeringTechnologyDr. Zhou Zhang, New York City College of Technology Assistant Professor, Ph.D. Department of Mechanical Engineering Technology, CUNY New York City College of Technology, 186 Jay St, Brooklyn, NY 11201. Email: Zhzhang@citytech.cuny.eduDr. Andy Zhang, New York City College of Technology Dr. Andy S. Zhang received his Ph.D. from the City University of New York in 1995. He is currently the program director of a mechatronics project in the New York City College of Technology/CUNY. For the past 15 years, Dr. Zhang has been
new winDSK6 module, calledCommFSK, which includes the following features: • generation of phase continuous and phase discontinuous FSK with adjustable data rate; • control of the modulated signal’s amplitude, center frequency, and frequency deviation; • source data selection from a pattern of alternating 0’s and 1’s, several PN-sequences, random data, all 0’s, all 1’s, ASCII text messages from keyboard, or data from files; • optional built-in or user-defined asynchronous communications protocol; • user defined FIR-based filtering of the resulting FSK signal; and, • full integration into the winDSK6 program. Page
and figuresprovided and mostly open white space that allowed for student work and student + instructorwork. A sample of blank note slides is provided in Figure 1. Page 14.1374.3 Root Locus – Controller Design R (s ) + 1 Y (s ) s ⋅ (s + 4 ) ⋅ (s + 6 ) K
, number of engineering courses taken and studentclassification (freshman, sophomore, etc.) in addition to student demographics and engineeringmajor. Analyzing these connections, if any, may be of great interest to researchers and practitionersattempting to affect positive change in engineering students’ affective domains.References[1] Y. Tang, R. University, S. Shetty, T. S. University, X. Chen, and R. University, “Interactive VirtualReality Games to Teaching Circuit Analysis with Metacognitive and Problem-Solving Strategies,”presented at the ASEE Annual Conference & Exposition, Vancouver, BC, June,, 2011.[2] H. Khalil and M. Ebner, “MOOCs Completion Rates and Possible Methods to Improve Retention - ALiterature Review,” In Proceedings of
Figure 3: A plot showing the z-plane annotated for discussing bandpass sampling.dents that allows them to evaluate Equation (1) in a way that promotes exploration and “what if” thinking.A simple m-file that provides this capability is shown in Listing 1, with an example output given in Figure 4for the bandpass signal parameters from Figure 2(a). Listing 1: M ATLAB program to evaluate valid sampling frequencies for bandpass sampling.f u n c t i o n vFs = bp samp ( fu , B )% vFs=bp samp ( f u , B )%% C r e a t e a s e t o f min and max v a l i d s a m p l e f r e q u e n c i e s% f o r bandpass sampling .% For Q= f u / B ,% 2B (Q / n ) <= Fs <= 2B ( ( Q− 1 ) / n −1))% where n i s an i n t e g e r s u c h t h a t 0> bp_samp
shiftsbetween the 1970’s and 2010’s.using paradigms to understand AI’s evolutionPractitioners in diverse fields define the term “paradigm” in different ways depending on theirdomains, with slight variations corresponding to norms in their respective fields. We takeKuhn’s[12] view which holds that a paradigm provides an open-ended resource that presents aframework of concepts, results and procedures within which subsequent work is structured. Acharacteristic of paradigms is that they can “shift” with new knowledge or evidence. An exampleusing human flight experience can be represented as shown in Table 2 below. The inspirationmay have originated from nature, through birds’ ability to swiftly move in air. Legends andmythology from early Greek times
asked to reflect on their experiences using the followingquestion:How often have you been in courses where some educational technology tools, especiallymobile applications, have been used? Tell us something about your experience. a. Please state the name of the application(s) or other technology tools (e.g., Clicker, CATME, Socrative, Any quiz software, etc.). b. What you liked about that application(s) and why? c. What you didn’t like and why? d. Were those applications academically relevant? If yes, why, if no, why not?Data AnalysisThe study focuses on exploring the students’ perceptions of using educational technology toolsin postsecondary STEM classrooms. To inform our study, we employed
] (8)It can readily be seen from equations (8) that X 1 ≡ 0 on choosing k2 m2 = ω 2 (absorbercondition). Other conditions on the choice of k2 and m2, such as limiting the amplitudes of X2, Page 22.247.7and / or restrictions on the allowed new natural frequencies, are then applied.Consider the following numerical values, in which the forcing frequency is close to the originalnatural frequency: m1 = 10 Kg, k1 = 2000 N/m, F1,0 = 100 N, ω = 13.5 rad/s. Note that theoriginal frequency is k1 m1 = 14.14 rad/s which is quite close to 13.5 rad/s. The absorbercondition gives: k2 m2 = 13.5 rad/s. The amplitude of X2 is F1,0 /k2 and this
. The transfer function between and an external torque, , can be expressed in the form given in Equation 3, where is the output of interest (represented by Y(s)) and is the input (represented by U(s)) Y ( s) K n2 2 U ( s ) s 2 n s 2 n (3) From Equation 2, we can see that the pendulum is a 2nd order-system (and we can compare it to the general
m =0 m yk +m , where xm is a sample of the transmittedsignal and yk+m is a sample of the return signal, 0 ≤ k ≤ N – 1, and N is the number of samples ineach sequence.Programming ConsiderationsThe program consists of a main form with three plots. User controls allow changes in thefollowing parameters: the number of cycles, amplitude, and frequency of the transmitted pulse;the delay of the received signal; and the type and amplitude of the noise. Additional controlsallow the user to have the program generate a new noise sample or display a histogram of thenoise in a pop-up window. The S/N ratio in the simulated signal plus noise is also displayed.The topmost plot displays the transmitted
anoption. The reason was that programming at the bit level could be cumbersome and it took thestudents a long time to set hardware configurations, timers, interrupts, etc. There was asignificant amount of code and hardware preparation just to get the robot going. Therefore in2009, the controller was changed to the Robotics Connection Serializer that could beprogrammed with Visual C# using MSRS services54, 55. This format was actually moreappropriate because it moved the focus from components to higher level functions and behaviors.The object oriented programming in an IDE afforded the creation of a GUI to make it possible tovisualize the framework of the student‟s work. By changing to this software platform, studentswere able to accomplish more
. Calculating the value of the curl.Figure 8. Curl vectors superimposed on a user-created vector field.Divergence ExerciseThe purpose of the Divergence exercise is to demonstrate the concept of divergence of a vectorfield. The users enter the components of a vector field which are then plotted as shown in Figure10. The users are given a “control volume” whose location can be chosen by the users. Thepurpose of this “control volume” is to provide a means to visualize whether the vector field isconverging or diverging at a particular location. Once the users choose a point that they desire,one user is prompted for an exact calculation of the divergence at the control volume‟s location.If the user answers correctly, the program continues to the next round
Tsystem was servingg a wirelesss communiccation class with 25 students.3.2 Graaphical Useer Interfacee (GUI)The seccond generaation of the eComLab e iss an advancced system with w a user friendly GU UI [9].The sysstem can be accessed by using anyy regular Weeb browser,, which makkes third partsoftwarres on user machines m unnnecessary. The remotee experimen nt room in ssecond geneerationeComL Lab is shownn in Figure 4. 4 Page 25.1116.6The eCoomLab GUI provides several s
Metaphor F-M Perceptual metaphor F-M-P Figurative Language F Lexicalized metaphor F-M-L Personification F-P Simile F-S Synecdoche F-Y Metonymy F-M Analogy F-A Question S-Q Illustrative S-E Teaching Style S Example Imagination S-I Repetition
suspension of disbelief on the part of the student. In Deshpande etal.’s [23] review of simulation games in engineering education, they found many advantages ofteaching engineering concepts through simulated environments over traditional classroominstruction, including but not limited to connecting theory to practice, customizability ofdifficulty to match students comprehension level, reduction of resistance to accepting innovativeideas and concepts, and greater retention of concepts over time. Another advantage ofsimulation-based learning is its compatibility with online learning, which continues to be agrowing trend, especially since the COVID-19 pandemic [11], [18], [31], [32].Using virtual systems to augment education is not only limited to
, K. Reitmeyer, E. Tseytlin, and R. S. Crowley,“Metacognitive scaffolds improve self-judgments of accuracy in a medical intelligent tutoringsystem,” Instructional Science, vol. 42, no. 2, pp. 159–181, Mar. 2014.[6] H. M. Ghadirli and M. Rastgarpour, “A web-based adaptive and intelligent tutor by expert systems,”Advances in Computing and Information Technology, pp. 87–95, 2013.[7] J. A. González-Calero, D. Arnau, L. Puig, and M. Arevalillo-Herráez, “Intensive scaffolding in anintelligent tutoring system for the learning of algebraic word problem solving: Intensive scaffolding in anITS for the learning of AWPS,” British Journal of Educational Technology, vol. 46, no. 6, pp. 1189–1200,Nov. 2015.[8] M. A. Ruiz-Primo and E. M. Furtak, “Exploring
information is provided: • All pipe sizes and materials • Flow rates coming in or out at points A and B, as shown in the figure Qa = 4 ft3/s A 2 C Q2 Q1 Q3 1 3 B Qb=1 ft3/s Page 11.1386.2 Figure 1. Analysis of a Simple NetworkThe problem has three unknowns, and to solve for them, three independent equations are