Consider a single server queuing system in the bank. The system starts at time t=0. The arrival time of customers is: 0.4, 1.6, 2.1, 3.8, 4.0, 5.6, 5.8, and 7.2. The departure times are: 2.4, 3.1, 3.3, 4.9, and 8.6. Time is in minutes. The first in first out queuing discipline is followed. Simulate this system for six clients and estimate: i. The expected average number of clients in the in the at any tim
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SIMULATION AND MODELING
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- . Draw the ERD for the following scenario. In a university, a Lecturer can teach many different courses and even the same course numerous times. Courses can also be taught by many lecturers. A student is enrolled in only one program but a program can contain many students. Students can be rolled in many courses at the same time and the courses have many students enrolled.1. Suppose you are developing the simulation model of a communication system where the incoming calls are being served by a single service person. Assume the arrival of the calls as well as their service times are random. Identify some entities, attributes, activities, events and states variables for this simulation mode b. Is very necessary to carryout an output analysis of simulation model. Why? Are the output data from simulation normally distributed? Discuss your answer with exampleThe language must be in python. Neural Network Units weights of [-1.2, -1.1, 3.3, -2.1] two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examples
- A queueing system has 1 server and two phases. The interarrival time is uniform between 20 and 50 seconds. The service times of the first phase is exponential with an average of 75 seconds, and the second phase exponential with an average of 90 seconds. Use a simulation run length of 1,000 arrivals. Explain what is the point estimate for the total number of customers and the time they will spend in the system?Suppose you are developing the simulation model of a telecommunication systemwhere the incoming calls are being served by a single service person. Assume the arrival of the calls as well as their service times are random. Identify some entities, attributes, activities, events and states variables for this simulation model.Let's talk about the four most important components of continuous event simulation, which are as follows:
- You are developing a simulation model of a service system and are trying to create an input model of the customer arrival Process, You have the following four observations of the process of interest [86, 24,9, 50] and you are considering either an exponential distribution Of a uniform distribution for the model. Using the data to estimate any necessary distribution Parameters, write the steps to plot Q-Q plots for both cases i.e. exponential and uniform.Using Microsoft Excel, create a spreadsheet to simulate a finite element analysis of heat transfer in a sheet of metal which is heated to soldering temperature at one corner. Assume that the temperature of any single cell is equal to the average of the temperatures of the four cells which share a side with it. Create a 10 by 10 cell finite element model with the temperature of the top edge (all 10 cells) is held to 20 degrees C, and the temperature along the right side is also held to 20 degrees. Make the lower left corner "hot" -- you can pick a value similar to a that of a soldering iron (look up temperatures of soldering iron tips). You can then add values long the bottom going from high down to 20 degrees, decreasing from left to right -- choose any starting rate you like. You can do the same for the left side, going from 20 degrees at the top and going up to the high temperature you have assigned in the lower left corner. Once you have made sure your spread sheet model…Do you see yourself using email in the not-too-distant future? The path of an email message starts with the sender and concludes with the receiver of the message. Take careful notes on everything you discover. Is there a rationale to the differences, and if so, what are they? Consider the possibility that there exist several models, each of which has a unique level of complexity (or abstraction).
- The language for coding must be in python Neural Network Units Implement a single sigmoid neural network unit with weights of [-1.2, -1.1, 3.3, -2.1] Calculate the outputs for two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Assuming that a sigmoid unit response >0.5 denotes a positive class and <0.5 is negative class, is example 1 positive or negative? is example 2 positive or negative? Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examplesSuppose a business person launches new cinema at Islamabad and ask his team to develop a ticket system for box office. He assigns some requirements about system that how should it work. The requirements are such a way that there are only '5' number of box office windows in the theatre. Each window can have at max '20' number of people waiting in line. To start with, only one window is opened. If the number of people waiting in line in that window exceeds 20, then the next window is opened and people can join the line in that window. Likewise, if both the first and second windows have n number of people waiting in each queue, then a third window is opened. This can go on until the maximum number of windows w is reached. Let us assume that once a window is opened it never closes. A new window is only opened if all open windows are full. Each person can buy only one ticket. So, the system should not allot more than one ticket per person. Let us assume that the system issues one ticket…Give an example of a network with two communities such its modularity is at least 1/2. Its a real world network question.