Publications by Dima

simulateBankSystems

09.05.2024

Name:Shahad Al Jahwari, ID:133011 Name:Fatma Al Nadabi, ID:134288 Name:Dima Al Maawali, ID:135069 Introduction: In this report, we simulate a sequential, two-stage queuing system in a bank setting, with a single reception desk and a single bank employee. Customers must visit the reception first, followed by the bank employee for further assista...

4415 sym R (4774 sym/24 pcs) 3 img

fist2 services

08.05.2024

Name:Dima Al Maawali, ID:135069 Name:……………., ID:…….. Name:……………., ID:…….. Introduction: In this report, we simulate a sequential, two-stage queuing system in a bank setting, with a single reception desk and a single bank employee. Customers must visit the reception first, followed by the bank employee for further ass...

3233 sym R (4774 sym/24 pcs) 3 img

2 services

29.04.2024

Lab Exercise IV: Single Server Queuing System Given queuing system for 10 customers with the following inter-arrival time (ITA) and service time (ST): ST 4 1 4 3 2 4 5 4 5 3 ITA - 8 6 1 8 3 8 7 2 3 IAT = c(0,8,6,1,8,3,8,7,2,3) ST = c(4,1,4,3,2,4,5,4,5,3) AT= cumsum(IAT) TSB = c() TCW= c() TSE=c() TCSS=c() idl=c() for (i in 1:length(IAT...

897 sym 1 tbl

SP24- Assignment Iment

28.03.2024

Question 1: [ 5 points] Toss a coin until you obtain \(k\) consecutive heads. Write a function with call form ngtm(k,m,nreps) that uses the Monte Carlo simulation to find and return the approximate probability that it takes more than \(m\) tosses to achieve the goal. set.seed(123) ngtm = function(k,m,nreps){ morem= 0 for (i in 1:nreps) ...

1051 sym 1 img

e2

17.03.2024

Lab Exercise II: Generating Continuous Random Variables The Inverse Transform Method Let \(U\) be a uniform \((0, 1)\) random variable. For any continuous distribution function \(F\) the random variable \(X\) defined by \(X = F^{−1}(U)\) has distribution \(F\). [\(F^{−1}(u)\) is defined to be that value \(x\) such that \(F(x) = u\).] Alg...

3000 sym 4 img

ITM and ARM

24.04.2023

The Inverse Transform Method (ITM) Acceptance-Rejection Method(ARM) # plot density func curve(4*exp(-4*x),from = 0, to = NULL) true.mean= 1/4 true.sd= sqrt(1/4^2) inf.fn = function(u){ x= -(1/4)*log(1-u) x } inf.fn(u= 0.8) ## [1] 0.4023595 N= 1000 n= 500 mean.est = numeric(N) sd.est = numeric(N) for (i in 1:N) { u = runif(n,0,1)...

2411 sym Python (5966 sym/108 pcs) 4 img