Paper ID #6095Development of a Senior Mechatronics Course for Mechanical EngineeringStudentProf. John G. Cherng P.E., University of Michigan-Dearborn Received M.S and Ph. D. degrees from Mehanical and Aerospace Engineering, University of Tennessee, Knoxviell, Tennessee in 1975 and 1978 repectively. Teaching undergraduate and graduate courses in heat transfer, instrumentation, mechatronics, turbomachinery, vibrations and acoustics. Research interests inculde turbomachinery, vibration and acoustics, and nano materials.Dr. Ben Q. Li, University of Michigan, DearbornDr. Narasimhamurthi Natarajan, University of Michigan, Dearborn
Paper ID #6375Using Mixed Mobile Computing Devices for Real-Time Formative Assess-mentProf. Frank V Kowalski, Colorado School of Mines Prof. Frank Kowalski has been teaching physics at Colorado School of Mines since 1980.Susan E. Kowalski, Colorado School of Mines Susan Kowalski is project coordinator at Colorado School of Mines.Dr. Tracy Q Gardner, Colorado School of Mines Page 23.1328.1 c American Society for Engineering Education, 2013 Using Mixed Mobile Computing Devices for
humanitarian endeavors. He founded and currently serves as CEO and President of LIMBS International (LIMBS.org) a non-profit entity which develops low-cost pros- thetic devices for under-developed areas of the world. Gonzalez has worked with students in Africa, Asia, Europe, Australia, and Latin and South America on various international engineering research and hu- manitarian projects. He also has been awarded the American Society of Engineering Educators Teaching Award and the Minnie Stevens Piper Foundation Award as a Texas Piper Professor of 2008. He also serves as an engineering program evaluator for ABET (Accrediting Board for Engineering and Technology).Ms. Elsa Q. Villa, University of Texas, El PasoDr. Peter Golding
University of Wisconsin-Stoutq Founded (1891) q Malcolm Baldrige Award (2001) q UW System Polytechnic designaBon (2007) q Career focus q Applied learning q Collabora3on q Colleges reorganized (2008) q 45 undergraduate/23 graduate degree programs q Over 11,000 students q 780+ students in 500+ co-‐op sites q 97.9% graduate employment rate Discovery Center: UW-Stout’s Gateway to Applied Research and Technical Assistanceq Launched (2009) with endowment support to: q Advance applied research, innova3on and interdisciplinary collabora3on q Solve industry challenges through contract
methodologies. In this paper is the extended of ourlaboratory 4 in Linear Circuit course at the U.S. Coast Guard Academy.The current paper presents some of the successful design and compensation techniques from onelaboratory in a junior-level Linear Circuits class that reinforces student learning about finitegain-bandwidth product limitations. Students learn graphical technique in the classroom thatpredicts the impact of Gain-Bandwidth Product limitation of a µA741op-amp.In this lab, students are asked to design two Sallen-Key second order low pass sections, using aµA741op-amp, in order to meet two specific resonant frequencies. In their first design( f o = 72.3 kHz and Q = 2) , students typically fall short of the desired resonant frequency by15% or
. 2) Draw the normal probability plots to show whether the grades are from the normal distribution. If the sample is normal, the plot will be approximately linear. Other distribution types will introduce strong nonlinearity in the plots. 3) Draw the quantile-quantile (Q-Q) plot to show whether the two grade samples come from the same unknown distribution. If the two samples do come from the same unknown distribution, the plot will be linear. 4) Use the Shapiro-Wilk test to see if the two grade samples are both from the normal distribution family. If both samples are from the normal distribution family, the F-test and the t-test are further used to see if the
were designed to assess student learning andthe effectiveness of the new course design. In order to evaluate the student background inLLL (step 1), a survey was administered at the beginning of the semester. A copy of thesurvey is presented in Table 1. Page 23.223.4Table 1. Survey questions used to evaluate the student background and understanding of Life-long learning. Q-1 From the following four options, select the one that describe your personal knowledge of the concept of “Life-long learning”? A. Extensive B. Moderate C. Limited D.No idea Q-2
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2 1 0 0 1 2 3 4 5 1 2 3 4 5 Student response Student response Figure 1. Responses to Q. 1 INL Wind Figure 2. Responses to Q. 2 INL Wind 12 8 10 Student count Student count 6 8 6 4 4
that is known to have properties such as being symmetrical (no skew) and kurtosis (clustering near the tails of the distribution) of zero. Examining normal Q-Q plots gives an indication of normality. Freidman’s ANOVA is a non-parametric test of whether more than two related groups differ that could compensate for non-normality. However, there are only two treatment groups in this study, so it cannot be performed if the assumption of normality is violated. Page 23.731.9INCORPORATING ENGINEERING IN MIDDLE SCHOOL SCIENCE 9 3. Homogeneity of variance is the
Confirmation CE1: Failure to clarify body in equilibrium Q-1,3,17,18,19 Moderate CE2: Failure to treat parts as single system Q-1,3,4,5,14,15, 17,18,19 Weak CE3: Leaving force off FBD Q-1,3,14,15,17,18,19 No Evidence CE4: Including internal force in FBD Q-1,3 Strong CE5: Including non-acting force in FBD Q-1,3 Strong CE6: Failure to account for force pair between separated bodies Q-4,5,7,8 Moderate CE7: Couple between bodies Q-7,8,27 No
the optical receiver. To evaluate the performance of the system, expensive equipment such as psudo-random binary sequence (PRBS) generator and bit-error-rate (BER) tester are required. When these equipment are not readily available, simulation software often provides an alternative way of studying the fiber optic communication systems. In this course, OptiPerformer was selected to study the performance of fiber optic communication systems 4. This category includes two activities: a. OptiPerformer #1: The objective of this activity is to study the bit-error-rate (BER)and Q-factor. The BER is a key performance parameter of the optical communication system.It is defined as the probability of a bit being incorrectly identified by
can be guided to acareer in STEM disciplines. Also, the camp activities were expanded to include some of theengineering projects in CNC machine and SolidWorks CAD software.Summer Camp EvaluationsThe following two figures (Fig 7 and 8) show students’ evaluations of the 2011 and 2012summer camps. Pre-Survey Post-Survey Q 1. Computer is fun Q 2. Computing is hard Q 3. I am good at computing Q 4. I like computing Q 5. I know more than my friends about computing Q 6. I can become good at computing Q 7. I like the challenge of computing
boiling regime as shown in figure 3 with black coloredsymbols. It is also observed experimentally that the probability of the occurrence of the 1stboiling curve decreases with increasing water loading.The observed random behavior of the nanoemulsion boiling also coincides with the dynamicsand microstructure within the nanoemulsion fluids. Figure 4 shows the Small Angle NeutronScattering(SANS) data for water-in-PAO nanoemulsion fluids with water volumetricconcentration covering 1.8 Vol% to 10.3 Vol%. Two empirical fittings are used to find out theinner structure.[22-25]Figure 4 shows the processed SANS data for water volumetric concentrations covering 1.8 Vol%to 10.3 Vol%. The scattering intensity I varies with the scattering vector q = 4π sin(θ/2
biomedical imagingapplications is Alzheimer's disease classification. The proposed paper talks about the feature extraction of the MRImages in Alzheimer’s disease. Here we introduce the concept of Non-Separable Wavelet Transform which can beused as an image segmentation technique. We use the Q-shift 10 length filter bank combination which reveals moreinformation in the low frequency signals, thus segmenting the image to highlight the portion of concern. Then weuse the area technique to classify the image. Finally, a GUI is used to show the results based on the proposedmethod.Keywords: - MR Images, DWT, 2DT-CWT, Alzheimer’s disease, Segmented Image.Introduction:Diagnosing patients affected by Alzheimer’s disease at an early stage plays a crucial role
Page 23.716.5understanding of the problem as they have described it. Table 1 also shows the specificcollaborative aspects present during this phase of the model. Table 1. Stage 1, Phase 2 of the CCMQuestions for Problem Formulation (Stage 1) Example of the internal structure of the CCMPreliminary Mental Model (Phase 2): for Stage 1, phase 2. Collaborative Modality: Q: What are the goals of the system? message board for Problem Understanding Q: Do any of these goals require clarification? Collaborative Processes: Q: Are there any other explicit or implicit pull and push information from the
Competitiveness • PCAST reports • Letter to U.S. Congress from 150 university presidents (9/30/2012) http://www.renewoureconomy.org/index.php? q=150%20university%20presidentsASEE EDI 2013, STEM Immigration Reform Issues April 16, 2013 Why Is STEM Immigration Important? • As a nation of immigrants, economic progress has been driven by talent • Innovation and knowledge-based economy more important than ever • Economic studies have shown impact of foreign born leaders in U.S. company formation, venture capital, patents, etc. • International competitivenessASEE EDI 2013, STEM Immigration Reform Issues April 16, 2013
Competitiveness • PCAST reports • Letter to U.S. Congress from 150 university presidents (9/30/2012) http://www.renewoureconomy.org/index.php? q=150%20university%20presidentsASEE EDI 2013, STEM Immigration Reform Issues April 16, 2013 Why Is STEM Immigration Important? • As a nation of immigrants, economic progress has been driven by talent • Innovation and knowledge-based economy more important than ever • Economic studies have shown impact of foreign born leaders in U.S. company formation, venture capital, patents, etc. • International competitivenessASEE EDI 2013, STEM Immigration Reform Issues April 16, 2013
point of Q is a saddle point, and differentiating Q can provide the formulas asfollows, using Lagrangian multiplier method to solve the formulas: 𝜕𝑄 = 𝑤 − 𝑙𝑖=1 ∝ 𝑖 ∅ 𝑥 𝑖 = 0 (2) 𝜕𝑤 𝑙 𝜕𝑄 =− ∝𝑖= 0 𝜕𝑏 𝑖=1 𝜕𝑄 = 𝑤 𝑇 − ∅ xi + b + 𝜀 𝑖 − 𝑦 𝑖 = 0 𝜕∝ 𝜕𝑄 = 𝐶𝜀 𝑖 −∝ 𝑖 = 0 𝜕𝜀 𝑖From formulas above: 1 𝑙 1 ∝ 𝑖 ∅(𝑥 𝑖 ) 𝑙𝑗 =1 ∝ 𝑗 ∅ 𝑥𝑗 + 2𝐶 𝑙
){ // displays hex integer as decimal to lcd int valcopy; // abbreviations: R. = remainder, Q. = quotient char dig[5] = {0}; // storage for R.'s int i = 0; // index into array called dig[ ] if(val == 0) lcd_putchar('0'); // statements below do nothing if val==0 if(val < 0){ val = ((~val)+1); // get hex magnitude if negative and... lcd_putchar('-'); // ...display minus sign in front } Page 23.263.13 valcopy = val; // successive /10 to generate R.'s while(val){ // keep looping until Q. drops to 0 val /= 10; // 1st Q., next Q., etc. dig[i++] = (char)(valcopy % 10); // 1st R., store it, next R.. etc. valcopy = val; // copy of
of impacts dialoguesStrategiesAdvocates /Allies Male Faculty Gender Equity M M M M M M M M MgroupsFaculty Advancement Lectures and Panels Q Q
/2003 – 05/2003), University of Minnesota, Department of Geology and Geophysics • Research/Teaching Assistant (07/1998 – 02/2000), Nanjing University, Department of Earth Science, China • Construction Engineer and Geotechnical En- gineer (06/1994 – 06/1998) Nanjing Construction Company, China PUBLICATIONS Book Chapter Sediment pollution, Handbook of Hydrology, 2012 Journal paper 1. Qian, Q., Voller, V. and Stefan, H., 2010, Can the ”dispersion tensor model” for solute exchange in the sediment bed of a stream or lake be simplified? Advances in Water Resources 33 (2010) 1542–1550. DOI:10.1016/j.advwatres.2010.09.001 2. Qian, Q., Voller, V. and Stefan, H., 2009, Mod- eling of vertical solute dispersion in a sediment
specific course learning objective. The student assigns one ifhe/she strongly agrees with the statement and 5 if he/she strongly disagrees. It may be noted thatthe developed method can be used not only for evaluating student outcome f but also the courseitself. Table 3: ETME 1300: Computer Graphics - Assessment Method (Mapping) P Direct Assessment Learning ri Indirect Objectives/ m Assessment/ Remarks Student a Q Q Q Q Q Survey
ceiling at42,950 feet (i.e., when specific excess power equals 100 feet per minute).A velocity versus load factor (V-n) diagram was constructed using the calculated stall velocity,given load limits5, and the calculated dynamic pressure (q) limit. At sea level, the q limit isdefined as the dynamic pressure corresponding to the maximum level velocity where thrustavailable equals the thrust required. This value of dynamic pressure is used at other altitudes anddensities to solve for the corresponding Mach number. The data indicates a similar method wasused to obtain the q limit of the published data. The calculated T-38 V-n diagrams for sea leveland 15,000 feet are shown in Figure 6. Proceedings of the
represents heat transferout of the system. From different cycles, we have:For power cycle Wcycle = Qin – Qout, thermal efficiency η = Wcycle/Qin (7)For refrigeration cycle Wcycle = Qout – Qin, coefficient of performance β = Qin/Wcycle (8)For heat pump cycle Wcycle = Qout – Qin, coefficient of performance γ = Qout/Wcycle (9) Proceedings of the 2013 ASEE Gulf-Southwest Annual Conference, The University of Texas at Arlington, March 21 – 23, 2013. Copyright©2013, American Society for Engineering EducationIn above equations the Wcycle, Qin, Qout can also be replaced by the rate form Wcycle , Q in , andQ out , which
" 18" A s= 1 .7 6 A s'= 0 .2 2 P (4 )-# 6 B a rs B o tto m , G ra d e 6 0 # 3 T ie s 26" 10" 1 5 '-6 " # 6 B a r: D ia m e te r= 0 .7 5 ", A re a = 0 .4 4 S q u a re In ch # 3 B a r: D ia m e te r= 0 .3 7 5 ", A re a = 0
parents tendto have smaller numbers of children, assume that the birth rate a is reduced by 5 percent. Hint: Problem 6 can be done by using solution tool for (5) in two steps: First, work withthe current population, birth and death rates to find Spain's population four years from now. Readoff this population as best you can from the graph and use it as the new value for P0. Also findthe modified values of a and b to calculate the population change over the next four years. Page 23.1333.7 Project 2: Electrical LRC Series CircuitsThe charge q(t) as a function of t in an electrical LRC series circuit, see Figure 2
sidewalk improvements, vending and Café Q food service improvements, building security, and promotion of design team membership. 4TOM C. ROBERTS, P.E., FASEE, FNSPEAssistant Dean, Recruitment and Leadership Development, College of Engineering, Kansas State UniversityTom has more than 30 years experience in planning, organizational development, and leadership training programs.He worked for Black & Veatch for 16 years, formed Upward Consulting in 1989 and has served as a learning organ-ization and process improvement consultant for a number of manufacturing and service companies, and
through each branch in m3 /s. Analysis: For each pipe: 4 Q Flow rate and velocity: Q = VA ⇒ V = [m/s] (1) π D2 ρV D Re = (2) µ 1 ε 2.51 For turbulent flow 0.5 = −2.0 log + (3) f 3.7D Re · f 0.5