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Cal Poly Pomona - GSC - 499
GSC499 Introduction to Global GeophysicsToday's Class Today' Lecture: Seismology Types of Waves Determining Earthquake Location and Mechanism Reading: Chapter 401/14/08 01/23/08 Cal Poly PomonaGSC350: Cal Poly PomonaEarthquake Seismology
University of Illinois, Urbana Champaign - MATH - 220
Math 220, Loeb Lecture 35, November 13, 200611. A Tutoring Room is Open 7 p.m, Monday, Tuesday, Wednesday, Thursday, Room 140 Lincoln Hall. 9 2. Exam, Friday October 17, 11 a.m.On material through volumes of rotation (homework for Thursday). Se
Cal Poly Pomona - MHR - 406
SHAME:the Master Emotion?I am ashamed of my shame. I should not be ashamed but I am. To speak of my shame would only shame me more; therefore I must carry this shameful knowledge silently. To disclose it would be more than I can bear. The only way
Cal Poly Pomona - MHR - 452
Try 3 Issues Free Magazine Customer Service Subscribe to FORTUNESearch FORTUNE Archive Current Issue| Companies | CEOs | Investing | Careers | Technology | Small Business | Downloads WHISTLEBLOWING 'It's a Living Hell' Whistleblowing makes
University of Illinois, Urbana Champaign - CS - 591
Compressing Historical Information in Sensor NetworksAntonios DeligiannakisUniversity of MarylandYannis KotidisAT&T Labs-ResearchNick RoussopoulosUniversity of Marylandadeli@cs.umd.edukotidis@research.att.comnick@cs.umd.eduABSTRACTWe
University of Illinois, Urbana Champaign - CS - 591
Clustering Objects on a Spatial NetworkMan Lung YiuDepartment of Computer Science University of Hong Kong mlyiu2@csis.hku.hkNikos MamoulisDepartment of Computer Science University of Hong Kong nikos@csis.hku.hkAbstractClustering is one of t
University of Illinois, Urbana Champaign - CS - 231
CS231: Computer Architecture I Friday, April 4, 20081AnnouncementsMidterm Exam 2 Monday, April 7, 2008 151 Everitt Lab 7:00 9:00 pm Bring your Ids Covers lectures from (and including) Feb 25 through Apr 2 Familiarity with Midterm1 materi
University of Illinois, Urbana Champaign - CS - 414
Symphony: An Integrated Multimedia File System*Prashant J. Shenoy, Pawan Goyal, Sriram S. Rao, and Harrick M. VinDistributed Multimedia Computing Laboratory Department of Computer Sciences, University of Texas at Austin Taylor Hall 2.124, Austin, T
University of Illinois, Urbana Champaign - CS - 231
Other memories Last time we showed how to build arbitrarily-large static memories from single-bit RAM cells. Today well look at some other kinds of memories. Dynamic RAM is used for the bulk of computer memory. Read-only memories and PLAs are two
University of Illinois, Urbana Champaign - CS - 527
"Requirements-Based Automated Black-Box Test Generation"Luay H. Tahat, Boris Vaysburg, Bogdan Korel, and Atef BaderCOMPSAC 2001PRESENTED BY SCOTT PETERSON UNIVERSITY OF ILLINOIS11PROBLEMS WITH STATUS QUOHow much testing is enough? Large so
University of Illinois, Urbana Champaign - ECE - 534
University of Illinois at Urbana-ChampaignECE 534: RANDOM PROCESSES Fall 2007 Midterm 1 Monday, October 8, 2007Name: This is a closed-book exam. You may consult both sides of one sheet of notes, typed in font size 10 or equivalent handwriting siz
University of Illinois, Urbana Champaign - ECE - 534
ECE 434 - RANDOM PROCESSES 1999 October 18,1999FALL Exam IYou have 75 minutes to complete the exam. The exam will be closed book, except you may consult one page of notes. You must show your work for full credit. There are three problems on three
University of Illinois, Urbana Champaign - ECE - 598
ECE 598: Modeling and Verication of Real-time and Hybrid SystemsFall 2008Lecture 12 October 7th , 2008 Multi-rate and Rectangular Hybrid AutomataProf. Sayan Mitra Scribe: YOUR NAMEIn the last lecture we saw how an Integral Timed Automaton can
University of Illinois, Urbana Champaign - MATH - 461
(1) Let X Binomial(4, 1 ). Evaluate E[X sin(X/2)]. 412(2) Write cumulative distribution function F for X Exponential(). Find density of the random variable Y = F (X). Name this density.3(3) An item is manufactured so that its width is nor
University of Illinois, Urbana Champaign - MATH - 571
10. Algebraic Closure in Minimal Structures Throughout this section let A denote an infinite minimal L-structure with underlying set A. We will write cl(X) in place of aclA (X) for X A. From Proposition 9.3 we know that cl is a closure operation of
University of Illinois, Urbana Champaign - ECE - 313
University of IllinoisSpring 2009ECE 313: Problem Set 3 Functions of discrete random variables, and parameter estimationDue: Reading: Noncredit Exercises: Wednesday February 11 at 4 p.m. Ross Sections 4.1-4.6. Chapter 4, Ross, Problems 1-42, The
University of Illinois, Urbana Champaign - ECE - 313
University of Illinois Assigned: Due: Reading:Problem Set #8 Page 1 of 1ECE 413 Fall 2004Wednesday, October 27 Wednesday, November 3 Lectures 25, 26, 27 from Lecture notes on class webpage. Chapter 5, Sections 5.4 (pp. 199-210), 5.7 (pp. 223-22
University of Illinois, Urbana Champaign - ECE - 313
University of Illinois ECE 413: Problem Set 12Spring 2007Functions of random variables; conditional pdfs, covariance Due: 4/25/07 at the beginning of class Reading: Chapters 6 and 7 of the textbook Noncredit Exercises: Chapter 6, Problems 26, 28-
University of Illinois, Urbana Champaign - ECE - 313
University of IllinoisFall 2008ECE 313: Problem Set 13 Covariance and Correlation, Minimum-Mean-Square-Error Estimation, Jointly Gaussian Random VariablesThis Problem Set contains ve problems Due: Reading: Noncredit exercises: Wednesday December
University of Illinois, Urbana Champaign - ECE - 313
University of IllinoisSpring 2009ECE 313: Problem Set 4 Binomial, Geometric, and Poisson Random VariablesDue: Reading: Noncredit Exercises: Wednesday February 18 at 4 p.m. Ross Sections 4.7-4.10. Chap. 4: Problems 43-85 Theoretical Exercises 10,
University of Illinois, Urbana Champaign - ECE - 313
University of Illinois 1.(a) (b)Problem Set #5: Solutions Page 1 of 2ECE 313 Spring 2002^ The maximum-likelihood estimate of p is the observed relative frequency, i.e. p = X/N. Since E[X] = Np and var(X) = Np(1p), the Chebyshev inequality gives
University of Illinois, Urbana Champaign - ECE - 313
Assigned: Wednesday, April 17, 2002 Due: Wednesday, April 24, 2002 Reading: Ross, Chapter 6 and Chapter 7 Noncredit Exercises: Ross, Chapter 6: Problems 26, 28-30, 41-43, 51, 54; University of Illinois Fall 2006 Theoretical Exercises: 8, 14, 22, 23,
University of Illinois, Urbana Champaign - ECE - 313
University of IllinoisSpring 2005ECE 413: Problem Set 13University Problem Set #13 ECE 313 WednesdayPage 1 of 2the beginning of class. April 27 at of Due: Illinois Spring 2002 Reading: Ross, Chapter Assigned: Wednesday, April 17, 2002 6 and 7 No
University of Illinois, Urbana Champaign - ECE - 313
University Problem Set #9 ECE 313 of Illinois Page 1 of 2 Fall 2001 Assigned: Wednesday, October 17, 2001 Due: Wednesday, October 24, 2001 Reading: Ross, Chapter 5 Noncredit Exercises: Ross: Chapter 5: Problems 18, 11, 1519, 23, 29, 30, 31; Theoretic
University of Illinois, Urbana Champaign - ECE - 313
ECE 313 Probability with Engineering ApplicationsFall 2000Review Independent TrialslReview Random VariablesX is a random variable dened on the simple experiment. l Xi is the value of X on i-th subexperiment l (X1, X2, X 3, ) is called a ra
University of Illinois, Urbana Champaign - ECE - 313
University of IllinoisFall 2003ECE 313: Problem Set #10Assigned: Due: Friday, November 7, 2003 Friday, November 14, 20031. Consider a sphere whose radius is a random variable, R, with pdf fR (u) = 2u for 0 < u < 1. (a) What is the average radi
University of Illinois, Urbana Champaign - ECE - 462
ECE 462 Logic DesignHomework 11) Logic gates Label the inputs so that the output is a.c [2 points]2) Boolean algebra Logic circuit simulation programs employ extra logic to capture dynamic behavior within a logical framework. A = {0,1,R,F,X} is
University of Illinois, Urbana Champaign - AGE - 357
DISTRIBUTION FITTING THEORYChoosing a distribution The usual approach to distribution fitting is to fit as many distributions as possible and use goodness-of-fit tests to determine the best fit. This method, the empirical method, is subjective and i
University of Illinois, Urbana Champaign - STAT - 426
#1. data computer; input age $ usage $ count; datalines; young yes 130 middle yes 30 senior yes 45 young no 100 middle no 70 senior no 125 ; run; proc freq data=computer order=data; weight count; tables usage*age / chisq trend; run;Table of usage b
University of Illinois, Urbana Champaign - STAT - 426
STAT 426 HW2 2.5. a. Neither. "1.7 times more ." would mean a relative risk of 2.7. b. Let 1 denote the probability of getting invasive breast cancer for the women taking the drug and let 2 denote the probability of getting invasive breast cancer for
University of Illinois, Urbana Champaign - STAT - 426
STAT 426 HW3 1. (1) Pearsons chi-square test statistic is 42.745 and the p-value is less than 0.0001 Therefore, we reject the null hypothesis of the independence. (2) The p-value from the Cochran-Armitage test is less than 0.0001. Therefore, there is
University of Illinois, Urbana Champaign - STAT - 426
Statistics 426 Sample Exam PRINT your name here: Important Notes: There are a total of three problems. You need to complete all parts with enough detail in your solutions to receive full credit. This is a closed-book exam, but you may use any calcula
University of Illinois, Urbana Champaign - STAT - 426
Statistics 426 Homework #3 1. A study on the computer usage and age based on a random sample of 500 people gave the following results. Three age groups are used in the study: young (20-30 years old), middle age (30-50 years old) and senior (over 50).
University of Illinois, Urbana Champaign - STAT - 426
Statistics 426 Homework #4 1. In a 2 by 2 table with nij as the cell counts, the conditional distribution of n11 given the row totals (n1+ , n2+ ) and the column totals (n+1 , n+2 ) is hypergeometric under the assumption of no association. Derive the
University of Illinois, Urbana Champaign - CS - 173
CS173: Discrete Mathematical Structures Spring 2006 Homework #9 Due 03/30/06, 8am1) Express E[X2] in terms of E[X] and Var[X]. 2) Let E1,E2,.,EN be N events from finite sample space. prove by induction that P(1 2 . )>=P(E1)+P(E2)+.+P(EN )-(n-1). 3)
University of Illinois, Urbana Champaign - CS - 473
CS 473ug: AlgorithmsMahesh Viswanathan vmahesh@cs.uiuc.edu 3232 Siebel CenterUniversity of Illinois, Urbana-ChampaignSpring 2006ViswanathanCS473ugIntroduction Solving Linear Programs DualityPart I Introduction to Linear ProgrammingViswa
Cal Poly Pomona - PHY - 133
Cal Poly Pomona, Physics 133L FALL 2008 Instructor: Dr. Nina Abramzon Office: Building 8 Room 224 email:nabramzon@csupomona.edu Phone: 869-4021Office Hours: Mon, Tue, Wed 10:00-11:00 , or by appointmentText: 133 Lab Manual Class web page: http:/ww
Cal Poly Pomona - PHY - 121
Cal Poly Pomona, Physics 121L FALL 2008 Instructor: Dr. Nina Abramzon Office: Building 8 Room 224 email:nabramzon@csupomona.edu Phone: 869-4021Office Hours: Mon, Wed 11:00-12:00 , or by appointmentText: 121 Lab Manual Class web page: http:/www.csu
Cal Poly Pomona - PHY - 133
Cal Poly Pomona, Physics 133 FALL 2008 Instructor: Dr. Nina Abramzon email:nabramzon@csupomona.edu Office: Building 8 Room 224 Phone: 869-4021 Office Hours: Mon, Wed. 11:00-12:00, or by appointment Materials: Text: Physics for Scientists and Enginee
Cal Poly Pomona - PHY - 299
Cal Poly Pomona, Physics 133 Recitation FALL 2008 Instructor: Dr. Nina Abramzon email:nabramzon@csupomona.edu Office: Building 8 Room 224 Phone: 909-869-4021 Office Hours: Mon, Wed. 11:00-12:00, or by appointment Materials: Text: The materials will
Cal Poly Pomona - PHY - 133
Grade Histogram16 14 12 # of Students 10 8 6 4 2 0> 55> 50> 38> 31ABGradeCDFClass average: 43/62 ( 70/100)
Cal Poly Pomona - PHYS - 130
Exam1Exam2Exam311, 1213, 1416, 1719, 2022, 2324, 2511, 1213, 1415-1718-2024,255/17/2008 10:36 A A A A A B B B B B B C C C C C 89.0% 86.2% 85.3% 84.7% 84.6% 84.1% 83.9% 83.2% 79.0% 78.9% 75.7% 71.9% 71.7% 68.8% 64.6% 62.5%
Cal Poly Pomona - APM - 300
APM300C - N5 Intro to Business May 2005 Room 112A B C D F 5 3 3 2 0 13.6% Extra Curve Class GPA 2.79 # of Students Ch 3&4 (3 in class) Ch 4&5 (4 in class) 13Instructor: Steve Boddeker Westwood-Anaheim B-Plan Presentation4-Team Project (Name) 5, 6
Cal Poly Pomona - SG - 150
SG150C - N5 SOFTWARE DEVELOPMENT LIFE CYCLE Jan 2006 Room 223 Instructor: Steve Boddeker Westwood-AnaheimA B C D F # of Students 12 Final Project (90%)87Class GPA 3.13 5.7%MidTerm7627-Jan010-Mar Final010-Feb c8, c14aDaily Grade2
Cal Poly Pomona - HUM - 400
6.4, 6.9, 6Polit, 7masc, why, 7reli, 7treCh 1,2 Thinking Critically (70% skipMaC3,4-Solving/Perceiving(60% skip4.3)Ch 8, 9 - Relate-Report/InferCh 8-9 Problem StatementCh 1,2 Thinking Critically5.2-5.8-5Atomic-6PaintHUM400C - N5 Creativ
Cal Poly Pomona - MTH - 111
MTH111C - N5 Algebra II Mar 2008 Rm111 F 6-10pm Westwood-AnaheimB C D F + A AB+ B+ C+ D+ D+ D D 2 1 4 0 5 -1 99% 90% 87% 83% 78% 67% 66% 65% 63%Instructor: Steve BoddekerDaily AssignmentsA2Students 9Curve20.0%q 6.3, 6.4q 8.1, 8.2q
University of Illinois, Urbana Champaign - CS - 273
University of Illinois at Urbana-Champaign Department of Computer ScienceHomework Assignment 4CS 273 Introduction to Theoretical Computer Science Fall Semester, 2005Due: Thursday, November 3, at the beginning of classTo facilitate grading, plea
University of Illinois, Urbana Champaign - CS - 591
FARMER: Finding Interesting Rule Groups in Microarray DatasetsGao Cong, Anthony K. H. Tung , Xin Xu, Feng PanDept. of Computer Science Natl. University of Singapore{conggao,atung,xuxin,panfeng}@comp.nus.edu.sgJiong YangDept. of Computer Science
University of Illinois, Urbana Champaign - CS - 498
Combinatorial Pattern MatchingCS 498 SS Saurabh SinhaGenomic Repeats Example of repeats: ATGGTCTAGGTCCTAGTGGTC Motivation to find them: Genomic rearrangements are often associated with repeats Trace evolutionary secrets Many tumors are chara
University of Illinois, Urbana Champaign - CS - 329
Technical Metrics for OO Systems1Technical Metrics A Metrics Suite for Object Oriented Design, Shyam R. Chidamber and Chris F. Kemerer IEEE Transactions on Software Engineering, June 1994, pp 476-493 Chapter 4 of Hamlet and Maybe, especially 4.
Cal Poly Pomona - SCI - 400
BIOLOGY 122 GUIDESci 400 Fall 2007Star Williams1CELLCYCLEParts of the Cell Cycle:1) M-phase (Mitotic phase) a. Prophase b. Metaphase c. Anaphase d. Telophase 2) Interphase a. Gap 1 (first growth phase) normal processes in the cell resum
Cal Poly Pomona - SCI - 400
Tutoring and Active Listening Techniques or "How to Get Your Tutee to Talk More Than You" TEN SECOND RULE After asking a question or follow up question, or beginning a problem, allow at least ten seconds for the student to respond. This may seem like
Cal Poly Pomona - SCI - 400
Instructor: Marcia Murry, Ph.D. 909.869.3446mmewers@csupomona.eduCourse DescriptionThe course is designed for students who are currently working as Instructional Student Assistants (ISAs) in the MaSH Center (Math Student Help Center) and CML labs
Cal Poly Pomona - SCI - 400
Sydney Henderson Star William Monica Truelson Huma Malik Winter 2008 MaSH Project Summary There are four different learning styles that students possess. They are visual, auditory, kinesthetic, and tactile learning style. Knowing what learning style
Cal Poly Pomona - SCI - 400
CHEMISTRY 122MaSH Center ManualSci 400 Fall 2007Huma MalikIntroduction to EquilibriumTwo types of reactions: irreversible and reversible. Concept of equilibrium only applies to reversible reactions.A+BC + D (reversible) Equilibriu
Cal Poly Pomona - SCI - 400
Cal Poly Pomona - SCI - 400
fi
Cal Poly Pomona - SCI - 400
Suggestions for Projects in Spring QuarterWeek 4: Work in groups to outline projects. Write a group proposal outlining members of your group and a description of your proposed project. One proposal per group should be e-mailed before next class meet
Cal Poly Pomona - SCI - 400
Case 2: Tutee expects tutor to do his/her work We are going to act out a scenario when a tutee comes in and expects us to complete his or her work. We will show what we should do as good tutors.CASE 2.Student: I need help. Can anybody come to my r
Cal Poly Pomona - EGR - 403
Chapter 7 - Rate of Return AnalysisEGR 403 Capital Allocation Theory Dr. Phillip R. RosenkrantzIndustrial & Manufacturing Engineering Department Cal Poly PomonaClick here for Streaming Audio To Accompany PresentaEGR 403 - The Big Picture Frame
Cal Poly Pomona - CH - 301
6The Manager as a Decision MakerIrwin/McGraw-Hill6-1The McGraw-Hill Companies, Inc., 20006-2Managerial Decision MakingDecisionmaking: the process by which managers respond to opportunities and threats by analyzing options, and making dec