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University of Florida - ESI - 6323
Lecture 18: DatapathsMultipliersShiftersComparatorsCountersLFSRsMultiplication Example:1100 : 12100101 : 510110000001100000000111100 : 6010multiplicandmultiplierpartialproductsproduct M x N-bit multiplication Produce N M-bit partial p
University of Florida - ESI - 6323
Lecture 19: Clock DistributionClock distribution trendsDistribution networksClock PowerClock SkewTiming Definitions Source: Ch 7 J. Rabaey notes, Weste and Harris Notes, S. Russu, ISSCC,Clocking Synchronous systems use a clock to keep operations
University of Florida - ESI - 6323
Lecture 20: Sequential Circuits Sequencing Elements Simple Latch/FF Timing Definitions Source: Ch 7 (W&H)SequencingUse flip-flops to delay fast tokens so they move throughexactly one stage each cycle.Inevitably adds some delay to the slow tokensC
University of Florida - ESI - 6323
Lecture 21: Sequential CircuitsSetup and Hold timeMS FF Power PCPulsed FF HLFF, SDFF, SAFFSource: Ch 7 J. Rabaey notes, Weste and Harris NotesReview: Timing Definitions TCQ: Propagation Delay from Ck to Q, assuming D has been setearly enough relat
University of the East - BUS - 101
Active CellIn a worksheet, the cell with the black outline. Data is always entered into the active cell.Column LetterColumns run vertically on a worksheet and each one is identified by a letter in the columnheader.Formula BarLocated above the worksh
Grand Canyon - MKT - 607
Week 3 DB Due by day 3With respect to the articles assigned and any otherarticles/research that you are able to draw upon, do marketershave an obligation to avoid marketing to vulnerable consumers asdefined by Smith and Cooper-Martin in "Ethics and Ta
Grand Canyon - MKT - 607
Week 3 DB due by day 5Explain the reason for positioning and repositioning products. Choose a product with which youare familiar, preferably one in your industry, and explain how it might berepositioned. Indicateits current position in the market, a de
Grand Canyon - MKT - 607
Week 4 DB Due by day 3As stated in this week's reading, "Whether a company grows,survives, and makes a profit could depend upon how theirproducts or services are defined." What does this statement meanin to a company or to consumer perception?Greetin
Grand Canyon - MKT - 607
Week 4 DB Due by day 5Keller, in "Branding Shortcuts," provides some shortcuts toestablishing a brand. Which of his suggestions resonates withyou and why?Greetings Class,The suggestion that resonates with me is memorability. Thissuggestion resonates
Grand Canyon - MKT - 607
Week 5 DB Due by day 3Define integrated marketing communications (IMC) and discuss theimportance of teamwork in achieving a successful IMC effort.Provide examples of how this concept would apply to a specificorganization. Use the Schultz and Kitchen a
Grand Canyon - MKT - 607
Week 5 DB Due by day 5Identify possible ethical issues involved with the dominance oflarge retailers (e.g., Wal-Mart, Home Depot, etc.). Explain yourposition regarding these issues and propose possible solutionsfor avoiding such issues if possible.Gr
Rutgers - PHARM - 300
! http:/www.pitt.edu/~super1 JIT http:/www.pitt.edu/~super1 : . . . . :
Rutgers - PHARM - 300
Medical Aspects of Blast InjuriesAssistant Professor of Emergency Medicine Mayo Clinic sztajnkrycer.matthew@mayo.eduMatthew D. Sztajnkrycer, MD, PhDAmado Alejandro Bez MD Mscbaez.amado@mayo.eduLearning Objectivess Discuss the epidemiology of blast
Rutgers - PHARM - 300
Disaster and Multi-Casualty TriageAmado Alejandro Bez MD MSc Matthew Sztajnkrycer MD PhDLearning Objectives Describe the key elements of disaster triage Understand the basic principles of Mass Casualty Triage (START)Performance Objectives At the end
Rutgers - PHARM - 300
Kansas 9/14/04 TornadoSpring storm and tornadoes in KansasSatellite image taken Thursday at 11:15 p.m. EDT.
Rutgers - PHARM - 300
TornadoesScott R. Lillibridge, M.D.Centers for Disease Control & PreventionINTRODUCTIONBackground and Nature of the ProblemTornadoes are funnel-shaped wind storms that occur when masses of air with differing physical qualities (e.g., density, tempera
Rutgers - PHARM - 300
TORNADO-RELATED DEATHS AND INJURIES DUE TO THE MAY 3, 1999 TORNADOESSheryll Brown, Pam Archer, Elizabeth Kruger, and Sue MalloneeInjury Prevention Service Oklahoma State Department of HealthPath of F5 Tornado Through MooreOBJECTIVESInjuryepidemiolog
Rutgers - PHARM - 300
Public Health Consequences of Earthquakes. Part II.Eric K. Noji, M.D., M.P.H.Centers for Disease Control and Prevention Washington, D.C.PREVENTION AND CONTROL MEASURESUntil earthquake prevention and control measures are adopted and mitigation actions
Rutgers - PHARM - 300
Access to and Need for Counseling Among Children after the September 11th Attacks on the World Trade CenterGerry Fairbrother, PhDNew York Academy of MedicinePresentation to the 2003 Pediatric Academic Societies Annual Meeting May 3-6, 2003 Seattle, WA
Rutgers - PHARM - 300
Laboratory Criteria for Identification of B. anthracisssFrom clinical samples, such as blood, cerebrospinal fluid (CSF), skin lesion (eschar), or oropharyngeal ulcer Encapsulated gram-positive rods on Gram stain From growth on sheep blood agar: Large g
Rutgers - PHARM - 300
Identification of Bioterrorism AgentsRashid A. Chotani, M.D., MPHAssistant Professor of Medicine & Public Health Director, Global Infectious Disease Surveillance & Alert System Johns Hopkins University President, Pakistan Public Health FoundationGIDSAS
Rutgers - PHARM - 300
Assault with a Chemical Weapon: Its worse out there than just BioterrorismFrank Paloucek DABATBiological warfare in history ? 6th Cent Romans 1346 1800's WWI 1933-45 Feces-smeared arrows Assyrians poison wells with ergot Animal cadavers into well wate
Rutgers - PHARM - 300
Cyber Terrorism Part 2 of 2(When the Hackers Grow Up)05/01/09Hacking as Warfare1CYBER WARFIGHTER Terrorists Terrorist sympathizers Government agents Organized Crime Thrill seekersIncidents normally take the form of organized Asymmetric Attacks.05/0
Rutgers - PHARM - 300
Emergencies in the ClassroomGregg S. Margolis, MS, NREMT-PAssistant Professor, Emergency Medicine Program University of Pittsburgh School of Health and Rehabilitation SciencesToday's goalDevelop strategies to deal with emergencies that are most likely
Rutgers - PHARM - 300
Disaster and Hospital Functions - In Relations with Information Transmission -[Slide1] Ladies and Gentlemen, it is my great pleasure to visit Santa Cruz de la Sierra, one of the most beautiful cities in South America and to share a wonderful time with al
LSE - ECON - 201
EC201Lent TermErik EysterFinding a General Competitive Equilibrium in an ExchangeEconomy.1. In an exchange economy, Agent A has endowment (2, 2) and preferences uA (xA , xA ) = xA1215xA22, while Agent B has endowment (2, 1)and preferences uB
LSE - ECON - 201
EC201Lent 2011Erik EysterSecond Worked Example of General Competitive EquilibriumIn this worked example, we use the example of two wheat farmers tradingwheat now for wheat later to explore interest rates set by a competitivemarket.Two farmers trade
LSE - ECON - 201
MACROECONOMICS TEST 1 (Dr Ashwin MOHEEPUT)GENERAL KNOWLEDGE QUESTIONSQuestion 1Suppose a car manufacturer is choosing between two production options. It can produce 100cars with 200 workers and 50 machines, or it can produce 166 cars with 300 workers
LSE - ECON - 201
EC201Lent TermErik EysterFinding a General Competitive Equilibrium in an ExchangeEconomy.1. In an exchange economy, Agent A has endowment (2, 2) and preferences uA (xA , xA ) = xA1215xA22, while Agent B has endowment (2, 1)and preferences uB
LSE - ECON - 201
EC201Lent 2011Erik EysterSecond Worked Example of General Competitive EquilibriumIn this worked example, we use the example of two wheat farmers tradingwheat now for wheat later to explore interest rates set by a competitivemarket.Two farmers trade
LSE - ECON - 201
Dear EconomistsAs the exams are approaching and we all start digging into past exam papers and old supervisions,Economics Society invites everybody to join our Unofficial Solutions Database.We are going to start accumulating student-made answers on our
LSE - ECON - 201
Dear EconomistsAs the exams are approaching and we all start digging into past exam papers and old supervisions,Economics Society invites everybody to join our Unofficial Solutions Database.We are going to start accumulating student-made answers on our
LSE - ECON - 201
MACROECONOMICS TEST 1 (Dr Ashwin MOHEEPUT)GENERAL KNOWLEDGE QUESTIONSQuestion 1Suppose a car manufacturer is choosing between two production options. It can produce 100cars with 200 workers and 50 machines, or it can produce 166 cars with 300 workers
LSE - ECON - 201
DEMAND FOR INSURANCEA consumer begins with initial wealth w and faces probability p of a loss of L in anaccident. She has concave utility of wealth function u(w) and strictly decreasing marginalutility. Lets call her risky no-insurance endowment X .Th
LSE - ECON - 201
models.CSystematic 2 T O O L S Fis R astlyM P A R A T I and S T A T I C S much less likely to occur. Indeed, suppose34H A P T E R 1 elimination O v C O simpler, V E errors arean economic model reduces to a system of two linear equations in two unknowns
LSE - ECON - 201
Responses to Serial CorrelationIf the disturbances are serially correlated OLS parameter estimates are unbiased OLS parameter estimates are inefficient the OLS standard errors are incorrect (there aremethods which correct for this)There are two poss
LSE - ECON - 201
Regression using time series data stationary I(0) seriesProcedures to be adopted depend on whether timeseries are stationary or nonstationaryHence we need to pretest data using DF and ADFtests Modelling I(0) series - ie all the series are stationary
LSE - ECON - 201
Testing time series for unit rootsWe know that a random walk is a particular type ofAR(1) processwith = 1xt = xt-1 + etHence to test whether xt is a random walk (with zeromean), we could estimatext = xt-1 + etand testH0 : = 1nonstationarityagai
LSE - ECON - 201
Nonstationary stochastic processesStationary processes satisfyE[xt] = Var[xt] = 2 < Cov[xs,xt] = t-sall independent of tMany economic series do not satisfy these conditionsE[GDP1970] > E[GDP1870]Hence they are nonstationary and cannot berepresent
LSE - ECON - 201
Time series - processes andrealisationsWith random sampling the key concepts are populationand sampleThe population can be real (Census) or hypothetical(continuous distribution)Sample statistics are (imprecise) estimates oftheunderlying population
LSE - ECON - 201
Introduction to time series analysisIn many cases (especially in macroeconomics) a sampleconsists of a set of observations measured over timeSuch data cannot be treated as a random sample - infact we need new concept of population and sampleIn time s
LSE - ECON - 201
Variables usedAGEWAGELNWAGEIndividuals ageHourly wage (in $)Log of wageOCC1Categorical variable for occupational category (seebelow)Categorical variable for industrial category (see below)1 if union member, 0 otherwiseIND1UNIONGRADEMARRIED
LSE - ECON - 201
Introduction to Diagnostic TestingIn a regression equation the N observations generate K regression coefficients N residuals with (N - K) distinct components(because ei = 0 etc)These residuals should not have a systematic patternDiagnostic statistic
LSE - ECON - 201
Forecasting and regressionFor a simple regression, given OLS estimates of the regression coefficients e, e the forecast value of X, XpThe point forecast isyp = e + eXp since E[up] = 0The forecast error isep = y - yp= ( + Xp + up) - (e + eXp)= ( -
LSE - ECON - 201
Model SpecificationWe do not know from economic theory which regressorsshould be included in a multiple regression. Thischoice is a form of hypothesis testingWe distinguish between nested and non-nested modelsModel 1 Y = + X + Z + U1Model 2 Y = + X
LSE - ECON - 201
Multiple Regression: Goodness of FitWe can decompose Var(Y) using a multiple regressionyi = + xi + zi + uiVar(Y) = cfw_(e)2Var(X) + 2eeCov(X,Z) + (e)2Var(Z)+ Var(Ue)(Other terms such as Cov(e, X) and Cov(X,Ue are 0)As in simple regression, this deco
LSE - ECON - 201
Multiple RegressionSupposeyi = + xi + zi + wi + uiIn science (experimental control) and economic theory(ceteris paribus) we can hold z, w constant soyi = ( + z* + w*) + xi + uiwhich is a simple regression. This simplification is notpossible in appl
LSE - ECON - 201
Properties of OLS residualsThe aim of regression analysis is to partition y intosystematic and nonsystematic components. Adesirable estimator generates ui which are notsystematicFor OLS the mean value of ue (the regression residuals) iszero if the
LSE - ECON - 201
Properties of hypothesis testsType I error - sizeConstruct the test statistict = coefficient/standard deviationfor each experiment, and look at frequency with whichnull is rejected when it is true (by design)This is an empirical measure of the proba
LSE - ECON - 201
Sampling distributions and MonteCarlo experimentsGenerate artificial data samples from known probabilitydistributionEach experiment (replication) is a sample of Nprimitive experimentsWe can establish sampling distribution of statisticsexperimentall
LSE - ECON - 201
Introduction to Econometrics My email address - awap@cam.ac.uk My office- Room 20 My office hours - Tuesday 1030, Thursday1030 My telephone- 35220 or 34913 Webpage- go to People / Peterson/ TeachingSuggested Reading S RossIntroductory Statist
LSE - ECON - 201
Introduction to EconometricsLecture 16: Designing and estimating dynamic regression modelsThe main aim of this lecture is to go through a practical example illustrating some of the issues whicharise when we try to model the behaviour of aggregate consu
LSE - ECON - 201
Introduction to EconometricsLecture 15: Multiple regression and the analysis of time seriesMultiple regression using time series dataThis lecture is an introduction to the problems which arise when we try to explain the relationship betweeneconomic ti
LSE - ECON - 201
Introduction to EconometricsLecture 14: Testing time series for nonstationarityTesting stationarity - non-trended dataTo test the null hypothesis that xt is nonstationary against the alternative of a stationary process, firstconsider the simplest poss
LSE - ECON - 201
Introduction to EconometricsLecture 13: Linear trends and random walksNonstationary stochastic processesStationary stochastic processes satisfy the conditionsE[xt] = Var[xt] = 2 < Cov[xs,xt] = t-swhere all population parameters are independent of t
LSE - ECON - 201
Introduction to EconometricsLecture 12: Stationary stochastic processesProcesses and realisationsWith random sampling the key concepts are the population and the sample. The population can be real, (aswhen a Census of Population uses a 10% sample) or
LSE - ECON - 201
Introduction to EconometricsLecture 11: Introduction to time series analysisIntroductionMuch of the data analysed by economists takes the form of time series. These differ from the randomsamples discussed so far, and analysing them statistically requi
LSE - ECON - 201
Introduction to EconometricsLecture 10: Model design and specificationIntroductionThis lecture is an illustration of the process that an investigator might go through in trying to specify andestimate a simple econometric model using multiple regressio
LSE - ECON - 201
Introduction to EconometricsLecture 9: Diagnostic Tests - Nonlinearity and HeteroscedasticityIntroduction to Diagnostic TestingEstimating a regression equation uses N pieces of information (the observations) to compute K regressioncoefficients. The re
LSE - ECON - 201
Introduction to EconometricsLecture 8: Forecasts and Structural BreaksForecasting and Forecast Confidence IntervalsIn a simple regression, if we know the forecast value of the regressor Xp, we can forecast Y conditional onX usingYp = e + eXpsince E[
LSE - ECON - 201
Introduction to EconometricsLecture 7: Multiple Regression - Hypotheses about Coefficients and Sets of CoefficientsAn Outline of the Specification ProblemWith multiple regression we need to decide which explanatory variables to include in an equation.