appropriate realistic constraints, including consideration of health, safety, etc., to the engineering problem for the capstone design. Measure: Evaluated in final CPEN 3850 report • Competency: Students demonstrate ability to generate effective solution(s) to the capstone design problem formulated in CPEN 3850, including identified constraints. Measure: Evaluated in final CPEN 4850 report [1]Thus, in order to determine whether students can both identify and apply appropriate standardsand constraints, and apply these in an engineering design, it was decided that it was necessary toevaluate students continuously working on a project; therefore, measuring in sequentialsemesters was specified. Other required
-depletion is far more than privileges need to be defined over time and space, not traditional systems. just by the user.Figure 3. Traditional vs. IWMDs security (comparison for teaching and research integration).Identifying the modularity of different cryptographic algorithms: These include algorithmssuch as SHA3 and the Advanced Encryption Standard (AES). The sub-step includes applyingfault diagnosis and tolerance techniques specified for IWMDs.Fig. 4 shows the first part of an S-box structure for the Pomaranch cipher. The structure ofPomaranch is based on linear feedback shift registers (LFSRs) which allow fast implementationand produce sequences with large period if the feedback polynomial is chosen
shown in Figure 6. Page 14.98.9 Figure 6. PSpice schematics for the simulation.The second model is based on the calculated system transfer function shown below and used forthe MATLAB simulation. 1 s 2 ∗L3 − L2 + − s ∗R2 − R3 + −H (s) ? C L
was video-taped. Students were asked to verbalize what theywere doing as they took the practical examination and, if necessary, were prompted by the TA.Coding is currently being developed to analyze these videos.The second technician aspect students were trained in was analyzing and graphing acquired data.Students were shown how to upload data from the test instrumentation to LabView then exportthis data to Matlab. Data was presented in the form of Smith charts, and graphs of S parameters.Students were also shown how to distinguish theoretical from measured data. The measurementsperformed by students and data presentation assignments were designed to illustrate limitationsof the measurement instrumentation. Specific data analysis tasks
, “Learning and understanding key concepts of electricity,” in Connecting research in physics education with teacher education, A. Tiberghien, L. Jossem, and J. Barojas, Eds. 1998.[2] A. H. Johnstone, “Why is science difficult to learn? Things are seldom what they seem,” J. Comput. Assist. Learn., vol. 7, pp. 75–83, 1991.[3] P. Licht, “Teaching electrical energy, voltage and current: An alternative approach,” Phys. Educ., vol. 26, pp. 272–277, Sep. 1991.[4] G. Biswas, D. Schwartz, B. Bhuva, S. Brophy, T. Balac, and T. Katzlberger, “Analysis of student understanding of basic AC concepts,” 1998.[5] G. Biswas, D. L. Schwartz, B. Bhuva, J. Bransford, D. Holton, A. Verma, and J. Pfaffman, “Assessing problem
further analyses. According to student survey feedback, allparticipants were impressed by the new pulse oximeter module and found the laboratory to beenjoyable and informative. The survey-based laboratory assessment indicated a 40% qualitativeimprovement in students’ self-perceptions of their abilities relative to the learning objectives forthe laboratory. Page 15.40.11References[1] S. Warren, J. Yao, and G. E. Barnes, "Wearable Sensors and Component-Based Design for Home Health Care," in 2nd Joint EMBS-BMES Conference, Houston, TX, Oct. 23-26, 2002, pp. 1871-1872[2] M. J. Drinnan, J. Allen, and A. Murray, "Relation
AC 2007-2504: INTRODUCING MICROFLUIDICS TO ELECTRICALENGINEERS: AN INTEGRATED PROBLEM-BASED LEARNING EXPERIENCEIan Papautsky, University of Cincinnati IAN PAPAUTSKY received his Ph.D. in bioengineering from the University of Utah in 1999. He is currently a tenured Associate Professor of in the Department of Electrical and Computer Engineering at the University of Cincinnati. His research and teaching interests include application of MEMS and microfluidics to biology and medicine.Ali Asgar Bhagat, University of Cincinnati ALI ASGAR S. BHAGAT received his M.S. in electrical engineering from the University of Cincinnati in 2006, and is currently pursuing his Ph.D. His research interests include
components) to be executed at different update rates, cycles can befreed up for executing the subsystem(s) that need to be updated faster.The real time multi-distributed modelling can involve different real time operating systems.Real time operating systems (RTOS) are those operating systems that guarantee that thesystem will respond in a predetermined amount of time. Real time operating system (e.g.QNX, Linux) reduces considerably the simulation time requirement.This paper describes a real time simulator for motor drives, and outlines its software andhardware subsystems. Examples and implementation of different motor control algorithmsusing this simulator are also discussed.System DescriptionThe software and hardware tools used in the development
embedded systems; advanced methods for improving hardware and physical network security; evolvable hardware; and evolutionary and recon- figurable computing. He is a senior member of the IEEE organization and several societies, a member of the ASEE and ACM organizations.H. Shelton Jacinto, Boise State University H S. Jacinto received his B.S. degree in electrical and computer engineering from Boise State University, Boise, Idaho, USA, in 2017, and is currently a Ph.D. candidate in electrical and computer engineering from Boise State University, Boise, Idaho, USA. From 2015 to 2017 he worked with Idaho National Labs in conjunction with the Advanced Energy Lab conducting research on self-powered wireless sensor
. Guskey, and L. A. Jung, “Response-to-intervention and mastery learning: tracing roots and seekingcommon ground,” The Clearing House, vol. 84, no. 6, pp. 249-255, 2011[3] – M. W. Bonner, “Grading rigor in counselor education: a specifications grading framework,” EducationalResearch Quarterly, vol. 39, no. 4, pp 21-42, 2016[4] – G. G. Shaker, and S. K. Nathan, “Teaching about celebrity and philanthropy: a case study of backward coursedesign,” The Journal of Nonprofit Education and Leadership, vol. 8, nr. 4, pp 403-421, 2018[5] – J. Ring, “Specifications Grading in the Flipped Organic Classroom,” Journal of Chemical Education, vol. 94,no. 12, pp 2005-2006, 2017[6] – L. Pope, H. B. Parker, and S. Ultsch, “Assessment of specifications grading in an
must build and demonstrate an SDR that addresses the problem(s) defined by the WirelessInnovation Forum and supporting the target waveform(s). The SDR domains provides a methodto tie together many of the subjects in a typical electrical engineering and computer science andengineering undergraduate’s curriculum. Although student teams may choose to use whateverdevelopment environment they wish, we have had success with the GNU Radio developmentenvironment as well as the MATLAB Simulink environment. Simulink allows a model-baseddesign approach, which allows students to take a systems approach to designing the overall SDRtransceiver, which provides them with exposure to this important aspect of project development.In this paper, we discuss the
Protoboard Type Specification Type Specification Value ELVIS II Board Channels 2 EE Board 4 ELVIS II Board Resolution 16 bit DAC EE Board 14 bit DAC 1 channel: 2.8 MS/s ELVIS II Board Sample rate both channels: 2.0 MS/s EE Board 40 MS/s ELVIS II Board Overdrive protection
a strong programming capability. The benefits of such a laboratory course are twofold.Firstly, students learn simulation, which is widely used by engineers in the industry to verify andvalidate system designs. Secondly, these laboratory projects have been designed following theGagne‟s nine events of instruction15 which leads to an enhanced learning environment. Also,when compared to hardware based labs, such as with EMONA TIMS16, Mobile Studio17 andEttus USRP18, Simulink has the advantage of lower cost and ease of maintenance.Simulink Laboratory Projects for Communication Systems CourseSix Simulink laboratory projects are constructed to teach Simulink skills in parallel with thetheory. Table 1 enumerates topics covered in the six labs and
modules will be used within our outreach program to students withinhigh needs inner-city schools in the Buffalo Public Schools system. The developed modules willexploit a shared undergraduate nanotechnology education laboratory.IntroductionThe integration of nanotechnology and Sensing Data Storagephotonics continues to advance. Pho ton s Opt ical Lithog rap hy
answer key isQuestion 1 2 3 4 5 6 7 8 9 10Answer c a B a c c d b c aEven though many questions had 4 multiple choice answers some students chose the 5th answerto indicate the did not know the answer. They were asked to chose (e.) if they did not understandto discourage guessing.Problem 2 Laplace Transform (50 pts.)Find the Laplace Transform, G(s) of the following signal, g(t).g(t) = e-2t sin (3wt)3 out of 10 gave correct responses, 3 gave incorrect responses, 5 had no clue.SOLUTIONLet f(t) = sin (wt), then F(s) = w/(s2 + w2)Apply scaling propertyIf f(t) ú F(s), then f(at) ú 1/a F(s/a)Therefore,Let p(t) = sin
tomention a few.3.3 The Lookup Table and Intensity TransformationAll the above intensity transformation (point-processing) operations can be viewed as directly orindirectly performing a lookup table (LUT) based mapping on the input pixel intensities of animage to produce a new set of output pixel intensities for the corresponding pixels, and therebyproducing a modified image. It should be noted that as the name implies, a lookup table is atable that contains a set of all possible (full range) input intensity values arranged in increasingorder R = { r0=0, r1=1 r2=2 …, rk=k …, rL-1=L-1}, and a corresponding set of output (mapped,reassigned) intensity values S = {s0, s1, s2, …, sk, …, sL-1} into which the input intensity valuesare correspondingly
Development Evaluation A http://jdsp.asu.edu Upgrades and T Software Development E for labs in: J-DSP Software Technology Enables: CRS 1: Multimedia A - students to run web simulations/visualization Computing, S CRS 2 : Networks, Local Lab S
; advanced methods for improving hardware and physical network security; evolvable hardware; and evolutionary and recon- figurable computing. He is a senior member of the IEEE organization and several societies, a member of the ASEE and ACM organizations.H. Shelton Jacinto, Boise State University H S. Jacinto received his BS degree in electrical and computer engineering from Boise State University, Boise, Idaho, USA, in 2017, and is currently pursuing a PhD in electrical and computer engineering from Boise State University. From 2015 to 2017 he worked with Idaho National Labs conducting research on self-powered wireless sensor networks and their security. From 2016 he now works in the High Per- formance Reconfigurable
Emulation Engine (BEE) (both Ettus Research and BeeCube were part of NationalInstruments Corporation now), Rice University’s Wireless Open-Access Research Platform(WARP), Microsoft Research’s Software Radio Platform for Academic Use (SORA), andDatasoft’s Typhoon SDR Development Platform. Due to the highest versatility for lowest cost,USRP N200 kit 18 and SBX daughterboard 18 that provides 400 MHz-4400 MHz accessiblefrequency range were selected for the REU project and the educational module presented in thefollowing two sections. The main component of the USRP N200 kit is a motherboard thatconsists of a Xilinx Spartan FPGA for all the physical layer functions such as filtering,modulation/demodulation and other baseband signal processing, 100 MS/s
protocols for interference mitigation.The WSU author had the privilege of teaching a senior/first-year graduate student class onantennas and RF propagation in the Fall 2020. The anTpaTT system was demonstrated andmeasured results were compared to simulated results as part of the exercise.Students employed by a DoD contractor expressed appreciation for ‘real-world’ applications thatapplied directly to their job(s). Course evaluations were positive, and the department plans tocontinue a long-term plan to build an applied-EM curriculum.The anTpaTT system also offers opportunities for a wide variety of undergraduate research andsenior capstone projects due to its interdisciplinary nature; potential topics include signalprocessing to improve pattern
necessary as sometimes we are interested inless information. The Routh Table allows us to quickly find out if there are roots in the right hand side of the s-plane and, if there are, how many. This indicates stability or instability of the closed loop system.The following steps show how to obtain the Routh Table for our specific example. 50 1+ 2 =0 𝑠(1 + 𝑠⁄20) The equation can be rewritten as: 2 𝑠(1 + 𝑠⁄20) + 50 = 0 1 1 𝑠3
) ( (b)Figure 3.. The Robotiics-I course student s interrests in a) Roobotics, and b) A career in Roboticsbefore annd after this classThe studeents also rateed the Robotics-I activitties that increeased their robotics r undeerstanding and ainterests,, engineering g interests ass well as theiir improved skills, as shoown in Fig. 4-a-b, whereeteamworkk and engineeering designn skills, andd BEST robotics competiition along with w middle-highschool mentoring m greeatly benefittted the
pattern in the database that mostclosely matches the learner’s error. Once the most similar error pattern has been identified, themisunderstood concept(s) will be displayed for the learner to see. System randomly selects and administers test questions at Pre-test various knowledge levels Questions
. “Derive and expression for the resistance, Req, for the small-signal circuit.”This homework was graded and returned to the students. If they did not do well, they were givenadditional problems to complete. About a week later, the first quiz was administered. Theresults of this initial change showed marked improvement in the student’s scores on the first quizand exam of the microelectronics course. Details of the improvement are discussed in the resultssection.After the first feedback cycle, a year later, the professors met for a second round of discussionsto find further improvement techniques. This discussion brought to light one of the majordifferences found between the sophomore and junior level courses – other than s-domainanalysis, which was
, midterm examinations, and the final examination. Final grades are thencomputed as a weighted average of the objective assessment scores.Before the introduction of SBG, the course was taught using a traditional “chalk-and-talk”lecture style. Homework discussion sessions were offered on a weekly basis. Interactivemodules for convolution and Fourier series signal and system analysis were developed [17] asadditional homework assignments. The course was graded based on homework scores, midtermexam scores, and the final exam score. Students would have only been aware of theirperformance on a course concept by identifying the concept(s) involved with a homework orexam problem and comparing their score to the standard institutional grading scale.After
outcome of the approach using tools like questionnaires, tests and projects. In addition, preand post surveys will be administered in order to gauge the student‟s understanding and skilllevel before and after the hands-on experience. The AD boards have been partially integrated inCircuit Analysis I and II courses over the duration of two semesters, and the results, althoughpreliminary, have been positive. Current and future work includes continued efforts for acomprehensive integration of the boards into the Electrical Engineering curriculum. The underlying goal of this work is to promote innovation and creativity througheducation, and to better prepare undergraduates for careers in the electrical engineeringworkforce. The authors are
electromagnetic problems, transient heat flow and solid state structural analysis using finite element routines, EMI and EMC characterization, S-parameter permittivity extraction routines, Synthetic Aperture Radar (SAR) design and data processing routines, and the use of Genetic Algorithms for antenna optimization. Dr. Baginski is a member of Eta Kappa Nu, Sigma Xi, the New York Academy of Sciences, and the IEEE Education and Electromagnetic Compatibility Societies. He is also a member of Who’s Who in Science and Engineering and Who’s Who Among America’s Teachers. Page 15.728.1© American Society for
Circuit analysis in the s-domain Topics not explicitly introduced or covered in detail Scaling y, z, and h parameters Convolution* Fourier analysis* *Topic in the text that is sometimes, but not always covered in an EE circuits sequence. Figure 1: Circuits I Coverage Compared to a Traditional Two-Semester Circuits SequenceFigure 2 lists the labs associated with Circuits I content that is covered at either an intermediate- or anintroductory-level. More information about labs in
thathave collaborated with educational institutions to make curriculum more responsive to workforceneeds. The technology trends listed above are further enabled by industries such as thesemiconductor [3] and wireless [4], both of which are facing acute shortage of new talent. Hence,in addition to employer-specific training, it is imperative that engineering programs update theircurricula and pedagogy to include experiential learning experiences that would better preparegraduates to meet industry expectations. Building the workforce of tomorrow is the sharedresponsibility of industry and higher education establishments.As part of the National Science Foundation (NSF) and the American Society for EngineeringEducation (ASEE)’s joint initiative called
13 10 10 14 M 1 2 5 5 2 I 3 1 1 1 0 A 75% 81% 63% 63% 88% M 6% 13% 31% 31% 13% I 19% 6% 6% 6% 0% Table 1. 2006-07 Electrical Engineering Senior Design – S. Williams Student Group Page 13.1070.9 Program Outcomes Assessment Results: EE-407, EE