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2000 Annual Conference

Authors

Jack M. Winters; Binh Q. Tran

Session 1609 Innovative Uses of Teleconferencing Technologies for BME Education Binh Q. Tran, Jack M. Winters The Catholic University of America, Washington D.C.AbstractThe opportunities for use of teleconferencing as a teaching tool have changed dramatically in thelast few years, and more change is anticipated. The driving factor has been the introduction of aset of strong international teleconferencing standards that have had the byproduct of dramaticallyreduced prices, enhanced interoperability, and the addition of LAN-based solutions. CUA, as partof ongoing

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2000 Annual Conference

Authors

Ron Eaglin; Z. Qu; Q. Zhang; P. Wahid; Issa Batarseh

Session no. 3232 MULTI-MEDIA ENHANCEMENT OF THE ELECTRICAL ENGINEERING CORE COURSE I. Batarseh, Q. Zhang, R. Eaglin, Z. Qu, P. Wahid University of Central Florida Orlando, Fl 32816 Tel (407) 823-0185 Fax (407) 823-6332 Email: batarseh@mail.ucf.edu AbstractThe objective of this paper is to present a new multi-media teaching enhancement tools for theprinciples of electrical engineering core course at the University of Central Florida. The newteaching environment

Collection

2000 Annual Conference

Authors

Mohammad H. Alimi; Howard B. Wilson

one period and areconsumed during a subsequent period. Special cases of this problem include mortgage financingas well as pension saving.Mathematical FormulationInvestment capital Q growing due to a saving rate S (t ) while simultaneously earning acontinuously compounded, after-tax, rate of investment return R satisfies the differentialequationQ’(t ) = RQ (t ) + S (t ), Q(0) = q 0 .The general solution of this equation for constant R is tQ(t ) = e [q0 + ∫ e − Rt S (t )dt ] Rt 0Inflation usually exists in real situations so it is desirable to think in terms of inflation adjustedcapital defined by q (t ) = Q(t )e − Itwhere I is the annual inflation rate. When I is zero, then q simply reduces to Q

Collection

2000 Annual Conference

Authors

Alex O. Kalu

application ofthe proposed algorithm.II. Formulation of AlgorithmConsider two polynomials in s, N(s) and D(s) over a field, given by: N(s) = ansn + an-1sn-1 + an-2sn-2 + . . . +a , 0 and (1) D(s) = bdsd + bd-1sd-1 + bd-2sd-2 + . . . +d 0Where d > or = n. D(s) = Q(s)N(s) + R(s). (2)It can be shown that the quotient polynomial Q(s) is of the form: Q(s) = bdsd-n/an + {c1sd-n-1 + c2sd-n-2 + ... + cd-n} (3)and the remainder polynomial R(s) is given by: R(s) = r1s n-1 + r2sn-2 + . . . + rn (4)A tableau can be constructed from

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2000 Annual Conference

Authors

Chiew-Ping Bong; Laura J. Genik; Craig W. Somerton

. MATLAB Property FunctionsUsing the property evaluation stated above a series of MATLAB property functions were writtenas script files for each substance type. Table 1 show the functions available for ideal gases.The parameter IGAS identifies the specific ideal gas as shown below: IGAS = 0: air IGAS = 1: N2 IGAS = 2: O2 IGAS = 3: H2 IGAS = 4: CO IGAS = 5: OH IGAS = 6: NO IGAS = 7: H2O IGAS = 8: CO2The parameter IMS indicates if the properties are on a per mass basis (IMS = 0) or on a per molebasis (IMS = 1).For compressible substance property evaluation there is only one function used,CompSub(ISTM,T,P,v,h,s,u,Q,L,IFLD). To use the

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2000 Annual Conference

Authors

Bob Lahidji

58. Computer Skills 1 2 3 4 59. Communication Skills 1 2 3 4 510. Interpersonal/Team Work 1 2 3 4 5Survey FindingThe response to the above 10 questions were as follow: Lowest Highest 1 2 3 4 5 Q#1 0% 6% 44% 25% 25% Q#2 0% 0% 6% 62% 32% Q#3 0% 6% 25% 31% 37% Q#4 6% 6% 12% 25% 50% Q#5 6% 6% 12% 25% 56% Q#6 6% 6% 12% 25% 44% Q#7 0% 12% 12% 44% 31% Q#8

Collection

2000 Annual Conference

Authors

Ray Price; Jonathan R. Dolle

activities helpstudents get to know one another while aiding in the development of important teamwork skills.Many of the activities students participate in challenge them to reveal things about themselves toothers and to work in groups on different small projects. Sample activities frequently used by Page 5.565.3ELAs to help make students more comfortable with each other can be found in Table 2. ICE BREAKERS q Human Knot- students stand in a circle and reach across to grasp hands; they then attempt to untangle themselves without letting go q Flash- students sit

Collection

2000 Annual Conference

Authors

Donald N. Merino

. Page 5.335.3Figure. 1 – Average Scores on Survey – In order of Importance y y à v h t r t t r v y p v y q v y v p h r v r p p h y à h h y à q y r r h r

Collection

2000 Annual Conference

Authors

Andrew Sterian

inner product are pre-sented next. To illustrate these concepts, we frequently make use of both the vector space of con-tinuous polynomials over [ , ] with the inner product: 〈 S ( [ ), T ( [ ) 〉 = ∫ S ( [ )T ( [ ) G[ (2.1) and the space of finite-length discrete-time sequences of complex numbers with the inner product: 1– 〈 S [ Q ], T [ Q ]〉 = ∑ S

Collection

2000 Annual Conference

Authors

David M. Beams

tested this phase detector but itwas abandoned because it would produce erratic results in the presence of phase jitter when thephase shift of the network under test was close to an integer multiple of 360°. + z Q - R Network Under Test Voltage comparators y /Q C In Out Vφ

Collection

2000 Annual Conference

Authors

Shahram E. Zanganeh; Ahlam I. Shalaby

specific energy diagram.Mathcad Solution: Q Q 16.5 b 5.0 q q = 3.3 S o1 0.0004 S o2 0.025 b n 0.013 g 32.2a) Because the calculation must start at the control (at point B) and proceed in thedirection in which the control is being exercised; that is between points B and A, Page 5.586.6and between points B and C; first we must compute the critical depth of flow atpoint B. Because the slope between A and B appears to be mild, we expectsubcritical flow upstream of point B, and because the slope between B and Cappears to be steep, we expect

Collection

2000 Annual Conference

Authors

Nghia T. Le

528 mV Figure 8 – Waveform of vout3 C. The Butterworth Second Order Active High Pass FilterTo further prevent interference from other light sources, a Second Order Active High Pass filterwith a Q value of 6 is used. Since this filter has a high Q, around the center frequency it behaves Page 5.355.8very similarly to a band pass filter. The normalized frequency response of this filter is in Figure 9below. Magnitude 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0

Collection

2000 Annual Conference

Authors

Louis J. Plebani; Joseph C. Hartman

costs, holding costs and shortage costswith stochastic demand and lead times. The problem required students to determine a (Q, R) policy.Demand was not specified and had to be determined from samples acquired at a cost.In order to obtain demand data, the students filled in the number of demand samples desired on theaction form and submitted the request. Data was randomly generated, based on the stored problemspecific parameters, and displayed along with summary statistics (see Figure 2 for a depiction).After digesting the sampled data, the student could (1) request more data, (2) enter a solution, or (3)exit the system to return later. Students could leave the system, in order to analyze and ponder, anynumber of times for any length of time

Collection

2000 Annual Conference

Authors

Mauricio A. Colombo; Maria R Hernández; Jorge E. Gatica

analysis textbooks (cf.Chapra and Canale, 1998). For this example the authors have written their own version, but robustFORTRAN and ANSI C codes can be readily found in several public domain libraries.The solution to the set of non-linear ordinary differential equations is attained via a FORTRANprogram (“reactor.for”). This program can be run as an interactive program or on a batch mode viaan input file. The approach chosen here is the use of an input file, "reactor.ini," which defines thereactor operating conditions (cf. Fig. 4), i.e., q Inlet temperature q Inlet volumetric flow rate q Total Pressure q Inlet butene molar fraction q Dilution ratio (oxygen/butene

Collection

2000 Annual Conference

Authors

Thad Welch

students will re-examine the 16-QAMmodulator from an implementation perspective. A simplified block diagram of a 16-QAMbaseband modulator is provided in figure 1. Page 5.106.1Note: the students are not given a parts list to draw from. However, components are availablefrom several labs and the general parts rooms for the EE department. D/A conv I channel data serial data source to parallel D/A conv Q channel dataFigure 1. 16-QAM baseband modulator block diagram.A group

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2000 Annual Conference

Authors

Igor M. Verner; Jacob E. Mendelssohn; David J. Ahlgren

r ! q v v t q $ r y r p à ! r à Tqr x q $ à r v @tvrr v Q v y

Collection

2000 Annual Conference

Authors

Kenneth Kelly; Etienne Khayat; Fouad T. Mrad

DATA ACQUISITION (DAQ) MODULE ERRORThe following diagram of Figure 5 resumes the voltage signal flowing from the SCXI asVSCXI, through the DAQ module where it goes out as Vmodel.Let us summarize the terms that will be used in the following calculations, they werepresented in Table 1 and are labeled in Figure 5.• VSCXI: The output voltage of the SCXI module, it is also the input to the DAQ module.• Vmodel: Also called VDAQ, it is the final output voltage from the DAQ, the output voltage of the model.• GDAQ: the gain of the DAQ.• EGDAQ: the gain error of the DAQ.• Voff: Offset voltage in the DAQ.• EN/Q: Noise and Quantization error• % reading: Percentage of reading• Ibias: Input bias current• Ioffset: Input offset current• RoutSCXI: Output

Collection

2000 Annual Conference

Authors

Harry W. Blackwell; Charles N Eastlake

processof adjusting this set of Cost Estimating Relationship (CER) equations was begun by calculatingand tabulating the magnitude of various segments of the design and manufacturing process asgiven by the cost model. The equations break up the cost into eight major contributors:engineering hours, tooling hours, manufacturing hours, quality control hours, developmentsupport cost, flight test cost, cost of manufacturing materials, and engine production cost. Eachsegment is estimated by an equation generated by regression analysis of Department of Defensedatabase information. The equation for engineering labor hours is typical: Engineering labor hours, E = .0396 A .791 S 1.526 Q .183 where A = airframe weight in pounds

Collection

2000 Annual Conference

Authors

Howard A. Canistraro

1.5 Stress Concentration FactorKf 1 q . ( Kt 1) Fatigue Stress Concentration Factor Kf = 1.1Kts 1.0 Torsional Stress Concentration FactorKfs 1 q . ( Kts 1) Torsional Fatigue Stress Concentration Factor Kfs = 1Geometric considerations of the shaft are defined as:r 0.5 in. Radius of the pinion shaft π .r 4I in 4 Area and polar moment of inertia of the shaft I = 0.049 in 4 4 π .r 4J in 4

Collection

2000 Annual Conference

Authors

Raghu Korrapati; Nikunja K. Swain; James A. Anderson

Inc., PSPICE from MicroSim Corporation, LOGICWORKS III from Capilano Computing, C/C++, Visual Basic from Microsoft Corporationetc.) and test equipment. This CBVEL can also be accessed from remote sites using Internet. Page 5.162.1The CBVEL consists of IBM compatible computers with appropriate software and hardware(LabVIEW, HI-Q, Virtual Bench, PXI Systems, DAQ Cards, etc.) from National Instruments(NI), and is connected to School of Engineering Technology and Sciences (SETS) network andexisting equipment 1, 2. Virtual Instrument (VI) modules for different courses and research areasare currently developed. Examples of some of these VIs are

Collection

2000 Annual Conference

Authors

Richard Andres; Marty Ferman

Motion used in theflutter analyses were:b02 M hh b0 M hα   q&&h  b02ω 2h M hh 0  qh   0 b0 Ahα   qh    &&  +     = Q  0 A  q  b0 Mαh Mαα   qα   0 ω α2 Mαα  qε   αα   α whereM hh = ∫ mφ h2 dy , M hα = ∫ mrφ hφ α dy , Mαα = ∫ Ieaφ 2h dy Page 5.486.6Aαh = − ∫ CLα Cφ hφ α dy , Aαα = ∫ CLα Ceφ α2 dywhere m is the mass/span; I is the mass moment of inertia/span; r is the distance between cg andea., positive when cg aft; e is the distance between the aero center and ea., pos. when ea. aft; C isthe chord; CLα is the lift

Collection

2000 Annual Conference

Authors

Mohammad A. Zahraee; Gregory P. Neff; Susan Scachitti

vision with goals and objectives supporting it. Each goal or objective has associatedtactics or strategies that can be undertaken to implement it. The list of activities oraccomplishments generated over the year is then organized so each supports a strategy or tactic.Yearly merit raises are based on an evaluation of the report.Criterion 4 Facilities and Criterion 5 Institutional and External Support Purdue UniversityCalumet’s departments providing administrative services formed an E2=Q Quality effort(Exceeding Expectations is Quality) in 1997 [6]. Administrative services includes essentially Page 5.172.7every staff member not in an academic

Collection

2000 Annual Conference

Authors

Rudolph Marloth; Rafiqul I. Noorani; Mark A. Hinton

conduction heat transfer rates between theinlet and outlet of the control volume equal the convective heat transfer rate from the surface ofthe control volume to the surrounding fluid. That is, q I − q L = q CONV (1) where qI = conduction heat flux at inlet to control volume, BTU/(hr-ft2 ) qL = conduction heat flux at outlet to control volume, BTU/(hr-ft2 ) qCONV = convection heat flux from surface of control volume, BTU/(hr-ft2 )Using Fourier’s law for one-dimensional conduction and Newton’s law of convective coolingresults in (2

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2000 Annual Conference

Authors

Robert Davis; Laura J. Genik; Craig W. Somerton

flow rate of the refrigerant and the known enthalpyvalues at each state to solve for this value. The reduced form of the first law used for thissolution is shown below. The rate of heat rejection into the environment for our situationis solved to be 7.07 kW. This value could also be determined by applying the first law tothe cycle as a whole, as shown below.Q& H = m& (h2 − h3 )Q& H = Q& L + W& inCOP of the Refrigeration SystemFinally, we need to solve for the COP of the refrigerator. As defined previously, the COPof the system is defined as the cooling load divided by the work input. This is shown inthe relationship below and turns out to be 3.59 for this particular system. This isequivalent to saying that the refrigerant

Collection

2000 Annual Conference

Authors

Phillip R. Rosenkrantz

properties p. Product and process reliability q. Manufacturing processes r. Quality principles s. Ergonomics3. Other Sources – After looking at program specific criteria, work done with curriculum development in 1992, and the IME Department and university mission statements, the following additional outcomes were added to the list: t. Operations Research u. Knowledge of manufacturing systems v. Working knowledge of basic and engineering sciences Page 5.685.6 w. Employability x. Attitude of Social ResponsibilityThis list was considered to be

Collection

2000 Annual Conference

Authors

Yann Guezennec; Stephen Yurkovich; Gregory Washington; Giorgio Rizzoni

Transactions on Mechatronics, September 1999.2. B. Baumann, G. Rizzoni, Q. Washington, “Intelligent Control of the Ohio State University Hybrid-Electric Vehicle”, pp. 123-128, Proceedings of 2nd IFAC Workshop Advances in Automotive Control, Feb. 26-Mar. 1, 1998, Pergamon Press, ISBN 0-08-043226 3.3. John R. Josephson, B. Chandrasekaran, Mark Carroll, Naresh Iyer, Bryon Wasacz, Giorgio Rizzoni, Qingyuan Li, and David A. Erb, “An Architecture for Exploring Large Design Spaces”, Proc. of National Conference of the American Association for Artificial Intelligence. 1998, Madison, Wisconsin.4. B. Baumann, G. Rizzoni, G. Washington, (30%) “Intelligent control of hybrid vehicles using neural networks and fuzzy logic”, SAE

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2000 Annual Conference

Authors

Mahmood Nahvi

Page 5.386.9p ( t ) , P, Q, and S change for −90° < θ < 90° . Compute p(t), P, Q, and S for θ = −90° , −60° ,−45° , −30° , 0, 30° , 45° , 60° , 90° and compare with values shown on the screen. Figure 13 - AC Power in an Impedance6. Discussion: Qualitative Understanding of Circuit BehaviorIn addition to quantitative analysis methods, it is desirable and important that students develop aqualitative understanding of circuit behavior and be able to predict it under various inputconditions. This is sometimes called having a feel or intuition for the problem. It helps to choosethe best approach amongst various possible solution methods. Circuit simulation modulesdiscussed in this paper are efficient tools for

Collection

2000 Annual Conference

Authors

Bogdan M. Wilamowski

iD Y6 S RS RS (a) (b)Fig. 9. Common source configurations of single transistor amplifier: (a) circuit diagram and (b)equivalent small signal model with idealized transistor including ro parameterExample 3 Find Q-points and the differential-mode voltage gain of the opamp of in Figure 10 ifVDD=VSS=7.5V, IREF=250µA, K’n=25µA/V2, VTN=0.75V, λn=0.017V-1, K’p=10µA/V2,λp=0.017V-1, and VTP=-0.75V. +7.5 VDD

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2000 Annual Conference

Authors

Gouranga Banik

. Page 5.168.7Table 3 OSHA Regulations Subparts with 70% or more supportsSubpart YesSubpart A General 74Subpart C General Safety and Health 70Subpart E Personal Protective and Life Saving Equipment 78Subpart F Fire Protection and Prevention 74Subpart K Electrical 85Subpart L Scaffolding 81Subpart M Fall Protection 89Subpart P Excavation 81Subpart Q Concrete and Masonry Operation 70Subpart X Stairways and Ladders

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2000 Annual Conference

Authors

Serpil Guvench; Mike Denton; Mark Rollins; Mustafa Guvench

P vt hy t h hi r @ yr p h t r r à Q r à à T y Figure 1: System SchematicTo facilitate a user friendly graphical interface National Instruments’ LabView was chosen to create a virtualinstrument and its programmable controller. The graphical interface controller is used to program and automatethe measurement