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Course: EE 3161, Fall 2008School: Minnesota
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EE Recitation 3161 Spring 2008 1) For a germanium crystal at room temperature what is the position of the intrinsic Fermi level? Intuitively, why is it closer to Ev or Ec? (Germanium data is on pages 32 and 34 of Pierret).
2) For the diffused resistor what below, is the resistance? The resistor is 100 m long. Acceptors at a concentration of Na = 1017 cm-3 have been implanted over the area show...
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Minnesota - EE - 3161
Recitation 8EE 3161 Spring 2008 1) In the following two diagrams, are the BJTs shown biased in Forward Active, Inverse Active, Saturation, or Cutoff? Sketch your own plot of log(n,p) vs. x for the case of an npn transistor in saturation.2) For th
Minnesota - EE - 3161
[o t no rb m1m d r ea #,pi 20] S l i tpol , i e xm 1sr g 07 uo e tm n
Minnesota - EE - 3161
Minnesota - EE - 3161
Recitation 5EE 3161 Spring 2008 1) For the n-p junction drawn below, draw a band diagram. Find xn and xp. Also draw (x), (x), and V(x) for thermal equilibrium and reverse bias. What is the maximum electric field in the junction for a reverse bias o
Minnesota - EE - 3161
Recitation 11EE 3161 Spring 2008 1) For the MOS transistor drawn below, assume that the gate voltage is biased for inversion, and the labeled regions correspond to the inversion channel. What are the scattering mechanisms that affect region I? What
Minnesota - EE - 3161
Minnesota - EE - 3161
Recitation 7EE 3161 Spring 2008 1) Consider the real diodes below.a) Which will have the highest small signal capacitance for Va = -5V? b) In some cases, a reverse biased diode can be modeled by the circuit diagram shown below. What is the curren
Minnesota - EE - 3161
Minnesota - EE - 3161
Minnesota - EE - 3161
Minnesota - EE - 3161
Recitation 10EE 3161 Spring 2008 1) For the MOS capacitor shown below, a) Qualitatively show how the band diagram at threshold changes if the substrate doping is changed from Na = 1016 cm-3 to Na = 1017 cm-3. b) What is the electric field across th
Minnesota - CSCI - 2021
CSCI 2021 Machine Architecture and Organization Written Assignment Due on May 9th, in class 4Name: _ ITLAB Account Name: _ Student ID: _! ! ! !Fill up the above blanks. Write your answer legibly in the space provided. The problems cover Chapter
Minnesota - CSCI - 4041
Algorithms and Data Structures CSCI 4041 Session 231Depth-First Searchdfs(Graph G): for each Vertex u vertices(G) col(u) WHITE, p(u) NIL time 0 for each Vertex u vertices(G) if col(u) WHITE then dfsVisit(u) 2Depth-First Search (1)dfs
Minnesota - CSCI - 4041
Algorithms and Data Structures CSCI 4041 Session 131Red-Black InsertrbInsert(Tree T, Node z): loop from y nil(T), x root(T) while x nil(T) y x, if key(z) key(x) then x left(x) else x right(x) p(z) y if y nil(T) then root(T) z else if key(z) key
Minnesota - CSCI - 5511
CSci 5511Homework 2Spring, 2007Name: Student ID: Instructions: Write and test the following Lisp functions. Please refer to the Lisp page on the class web site for information about various Lisp interpreters available to you and for links to a
Minnesota - CSCI - 4041
Algorithms and Data Structures CSCI 4041 Session 231Breadth-First Searchbfs(Graph G, Vertex s): for each Vertex u vertices(G)- s col(u) WHITE, d(u) , p(u) NIL / col(s) GRAY, d(s) 0, p(s) NIL, Q 0, enqueue(Q,s) / while Q 0 u dequeue(Q), col(u) B
Minnesota - SENG - 5801
Lecture 10 (or so) - Model Checking IntroductionFall 2008Topics for TodayIntroduction to Model Checkinghttp:/www.umsec.umn.edu The Idea of Model Checking Basic Idea of Explicit State Model CheckingExplicit Search Basic Idea Behind Symboli
Minnesota - CSCI - 5211
Topics for Today More on Ethernet Topology and Wiring Switched Ethernet Fast Ethernet Gigabit Ethernet Wireless LANs Readings 4.3 to 4.41Original Ethernet WiringHeavy coaxial cable, called thicknet, 10Base52Second Generation Ethernet
Minnesota - SENG - 5801
Lecture 10 (or so) - Model Checking IntroductionFall 2008Introduction to Model CheckingA *very* brief start.Fall 2008SEng 5801 - Dr. Mats Heimdahl1Topics for Today The Idea of Model Checking Basic Idea of Explicit State Model Checking
Minnesota - CSCI - 5271
CSci 5271: Introduction to Computer SecurityExercise 12 due: October 21, 2008 Ground Rules. You may choose to complete this problem with a partner or by yourself. If you work with a partner, turn in one copy with both of your names on it. You may ch
Minnesota - CSCI - 8211
Detection of Invalid Routing Announcement in the Internet Xiaoliang Zhao, Dan Pei, Lan Wang, Dan Massey, Allison Mankin, S. Felix Wu,Lixia Zhang AbstractNetwork measurement has shown that a specific IP address prefix may be announced by more than
Minnesota - CSCI - 8211
Computing the Types of the Relationships between Autonomous SystemsGiuseppe Di Battista, Maurizio Patrignani, and Maurizio PizzoniaDipartimento di Informatica e Automazione, Universit` di Roma Tre, Rome, Italy a Email: {gdb,patrigna,pizzonia}@dia.u
Minnesota - CSCI - 1902
/ Example 16/ A 2-dimensional array example / Builds an array of powerspublic class Array2d { public static void main(String[] args) { final int LENGTH = 10; / declaration of a symbolic constant final int WIDTH = 5; / ano
Minnesota - CSCI - 1902
/ Example 16.5/ Ragged arrays of 2 dimensions/ "rows" of 2-dimensional arrays need not be all the same length/ even though the base type (here int) must be the same for all/ the lowest level elements./ Here, each element of the first dimension
Minnesota - CSCI - 5271
Anti-Jamming: A StudyKarthikeyan Mahadevan, Sojeong Hong, John Dullum December 14, 2005AbstractAddressing jamming in wireless networks is important as the number of wireless networks is on the increase. In this paper, we present a new mechanism t
Minnesota - CSCI - 5980
YCheng,GMChurchProcIntConfIntellSystMol Biol,2000Biclustering:groupsgenesandconditions simultaneously. Selectgeneandconditionswithmorecoherent measurement Groupitemsbasedonasimilaritymeasuresthat dependsonabestdefinedsubsetofattributes. Allowrow
Minnesota - PHELP - 008
THE WILSON ADMINISTRATION IN LATIN AMERICAWilson wanted an orderly democratization in Latin America and continued economic opportunities for American businesses; when he couldn't get everything he wanted in the region, he made the maintenance of or
Minnesota - PHELP - 008
WORLD WAR I AS AN OPPORTUNITY FOR CHANGEAmerican traditions of non-involvement with European political affairs and free access to foreign markets came into conflict during World War I; initial American neutrality increasingly gave way to a pro-Allie
Minnesota - MOORE - 144
-.=.Center t o Study Human-Animal R e l a t i o n s h i p s and Environments Box 197 Mayo Bldg. 420 Delaware S t . SE Minneapolis, MN 55455 CEN/SHARE B u l l e t i n , No. 1 S u b j e c t : Pet Therapy(Other terms: Pet F a c i l i t a t e d T
Minnesota - MOORE - 144
:~.UNIVERSITY OF MINNESOTA NEWS SERVICE, S-68 NORRILL HALL E?IIWEAPOLIS, MINNESOTA 55455 AUGUST 29, 1975 NEWS PEOPLE: For further information contact BOB LEE, 373-7510 40 ' ' MEDICAL STUDENTS TO BE U RURAL PIIYSICIAN ASSOCIATES (FOR IMMEDIATE REL
Minnesota - STAT - 8311
Stat 8311 Estimating treatment means, unbalanced data> searle <- data.frame(soil = rep(c("s1", "s2"), c(7, 8), + var = c("v1", "v2", "v3")[c(1, 1, 1, 2, 2, 3, 3, 1, 1, + 1, 1, 2, 3, 3, 3)], y = c(6, 10, 11, 13, 15, 14, + 22, 12, 15, 19, 18, 31, 18,
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Turkey dataThese data are from an experment to compare sources of an essential amino acid called methionine in turkey diets. Sixty pens of turkeys recieved a similar diet, supplemented with methionine from one of three sources
Minnesota - STAT - 8053
Mixed Effects Models for Fish GrowthSanford Weisberg, sandy@stat.umn.edu October 18, 2008Much like tree rings on trees, many fish preserve a record of their growth history in annular rings on fish scales and other bony parts. The number of rings pr
Minnesota - STAT - 8053
Stat 8053, Fall 2008: GLMMsFrom the lme4 package in R: Contagious bovine pleuropneumonia (CBPP) is a major disease of cattle in Africa, caused by a mycoplasma. This dataset describes the serological incidence of CBPP in zebu cattle during a follow-u
Minnesota - STAT - 5302
Physics Data Handout, Stat 5302> Output from Table Data. . . item. Data set = Physics, Data listing Col. 1 = Case-numbers Col. 2 = x Col. 3 = y Col. 4 = S -0 0.345 367 17 1 0.287 311 9 2 0.251 295 9 3 0.225 268 7 4 0.207 253 7 5 0.186 239 6 6 0.161
Minnesota - STAT - 8061
Minnesota - STAT - 5421
Stat 5421, Fall 2006: Blowdown data, part 4Here is another version of the blowdown data, this time using the species balsam r (BF), Aspen (A) black ash (BA). We consider the predictor D as well as SPP. > > > > + > > options(width = 68) loc <- "http:
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Chapter 11 Cluster AnalysisThe rst example looks at economic data from 69 world cities in 2003, provided by the Union Bank of Switzerland. The variables are: BigMac = Minutes of labor to purchase a Big Mac; Bread = Minutes of l
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Proportional Odds ModelsThe proportional odds model cannot be fit with the glm function. However, this model is so common that software for it is readily available, for example in proc logistic in SAS, in JMP, in special purpos
Minnesota - STAT - 8053
Stat 8053, Fall 2008: L1 and Quantile RegressionReference: R. Koenker (2005). Quantile Regression, Cambridge University Press. See also the vignette for the quantreg package in R on the class website.Sample and population quantilesGiven an distri
Minnesota - STAT - 8051
1Stat 8051, Fall 2007: Logistic RegressionLogistic regression is the forward problem of the study of the distribution of (y|x). Since y can only equal two values, there is value in study of the inverse problem of x|y through the conditional densi
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Logistic RegressionOn July 4, 1999 a huge windstorm caused widespread devastation of trees in the Boundary Water Canoe Area Wilderness in northern Minnesota. A survey done later examined trees to provide data to model survival
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Smoothing, Ch. 11Kernel smoothingKernel smoothing is essentially weighted local averaging. It balances bias and variability using a smoothing parameter that essentially controls how many points get high weight in the averaging
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Chapter 9This follows the results in Chapter 9 of Hrdle and Simar on principal component analysis. The a first example is the banknote data discussed in this book, in Faraway, and in Weisberg (1985). > data(banknote, package =
Minnesota - STAT - 8051
Stat 8051, Fall 2007: More TransformationsBox-Cox transformation of the response> > > > > > > + library(alr3) library(MASS) data(wool) par(mfrow = c(1, 2) m1 <- lm(Cycles ~ ., wool) boxcox(m1) boxcox(Days + 1 ~ Eth * Sex * Age * Lrn, data = quine,
Minnesota - STAT - 8051
Stat 8051, Fall 2007: PrestigeThese data are the running example in the car package. The response is the prestige rating of 102 professions. Potential predictors are income, education and women, the fraction of the profession that is women. An addit
Minnesota - STAT - 5401
THE UNIVERSITY OF MINNESOTA Statistics 5401/8401 Solutions to Sample Midterm Examination The exhibits that were in a separate booklet are included here. Instead of tables of Bonferronized F-probability points, MacAnova output is used. Exhibit 1 (for
Minnesota - STAT - 5401
THE UNIVERSITY OF MINNESOTA Statistics 5401 Multi-group Profile Analysis Example This handout provides an analysis of some artificial data from Example 5.9 on p. 240 of Multivariate Statistical Methods, 3rd Edition by Donald F. Morrison, McGraw Hill
Minnesota - STAT - 5401
C ( SSSS hhhh TTTT AeTUUUU SSSS TTT UUUU eee UUUU SSSS iPpppp PPP eeee iii iiii QQQQ dSSSS(Ud3Qdd UUU QQQ RRRR iiii HHHH hhhh ffff gggg eeee eeee UUUU eeee ffff gggg TTTT ffff eeee dddd cccc # 7 B7@%(A$3 4(%'%&4% 3 B4 % A &%A D#%#7%(7A1@ #155(@7#4
Minnesota - STAT - 8401
L30data 100 5 LABELS) Artifical data generated from factor analytic model with) m = 2 factors, used in Lecture 30, 11/16/05)"%lf %lf %lf %lf %lf" 70.6 36.5 109.5 104.0 73.6 33.3 44.9 102.2 107.4 81.8 68.1 54.6 118.0 102.0 62
Minnesota - CH - 5021
# File ex12_030.txt from publisher's web site# Data for Ex. 12.30, p. 789 of IPS4# Col. 1: id = board number (1-24)# Col. 2: color (factor, 1=Blue, 2=green, 3=Lemon, 4=White)# Col. 3: insects = number of cerial leaf beetles trapped id color in
Minnesota - STAT - 5021
# Data on y = Nickel/Iron ratio in oat plants grown# in sand cultures for x = 4 days# Col. 1: days = Time (days) in sand cultures# Col. 2: ni_fe = Nickel/Iron ratio in oat plantsdays ni_fe 4 0.32 9 0.41 14 0.79 18 0.86 22
Minnesota - CH - 5021
# File ex12_016.txt from publisher's web site# Data for Ex. 12.16, p. 785 of IPS4 (Table 12.3)# Col. 1: id = subject number (1-160)# Col. 2: promotions = number of promotions# Col. 3: price = estimated price of supermarket product ($)# Use group
Minnesota - CH - 5021
# File ex13_012.txt from publisher's web site# Data for Ex. 13.12, p. 820 of IPS4# Col. 1: id = group number (1-6)# Col. 2: gender (factor, 1=Females, 2=Males)# Col. 3: major (factor, 1=CS, 2=EO, 3=O)# Col. 4: grades = mean high school math grad
Minnesota - CH - 5021
# File ex12_013.txt from publisher's web site# Data for Ex. 12.13, p. 784 of IPS4# Col. 1: id = case number (1-10)# Col. 2: time = days after baking# Col. 3: vitamina = Vitamin A content (mg/100 g)# Col. 4: vitamine = Vitamin E content (mg/100 g
Minnesota - CH - 5021
# File ex12_021.txt from publisher's web site# Data for Ex. 12.21, p. 786 of IPS4# Col. 1: id = infant number (1-45)# Col. 2: bftime (factor, 1=BF4, 2=BF5, 3=BF6, months)# Col. 3: energy = energy intake, (kcal/d) id bftime energy 1 BF4 499
Minnesota - CH - 5021
# File ex11_051.txt from publisher's web site# Data for Ex. 11.51, p. 743 of IPS4 (Table 10.1, p. 694)# Col. 1: id = woman number (1-60)# Col. 2: wages = proportional to weekly wages# Col. 3: los = length of service (months)# Col. 4: size = ban
Minnesota - STAT - 5931
cross$ export LD_LIBRARY_PATH=/APPS/ggobi/libcross$ R> library("Rggobi")>> data(mtcars)>> class(mtcars)[1] "data.frame"> names(mtcars) [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"[11] "carb"> help(mtcars)> gg
Minnesota - STAT - 5303
Stat 5303Designing ExperimentsFall Semester 2007Time: Location: Textbook: Web page: Instructor:10:10 a.m. to 11:00 a.m. on Mondays, Wednesdays, and Fridays Ford 115 A First Course in Design and Analysis of Experiments by Oehlert http:/www.sta