...by applying theories to your own behaviour. In this assessment, you will submit three (3) out of six (6) tutorial worksheets as part of a portfolio. You must submit worksheet 1 and then choose any two (2) from worksheet 2 to 6. The tutorial program has been designed to assist your learning and is directly linked to this assessment. You should aim to attend most of the tutorials if you seek a good mark. Consumer Behaviour List In the first tutorial, you will be select ONE consumer behaviour from the list below that you have done in the last three months. You will then complete worksheets in the tutorials of weeks 2 – 7 on that consumer behaviour. Once you have selected a behaviour you cannot change as your assessment requires to submit worksheets on the same behaviour. List of Consumer Behaviours * Buying a PC/laptop/high-technology item * Booking/arranging/going on an overseas holiday * Selecting a university * Going to the movies * Choosing a restaurant for a special occasion * Evaluating and selecting a mobile phone plan * Choosing to do volunteer work * Buying a fashion item * Going to a concert * Changing a bad habit (smoking, reducing alcohol intake, getting fit, eating better) Assignment structure and requirements You must follow this structure, do not change the order of the content of the worksheets in any way as this may result in reduced marks. This assignment requires the use of first-person language. The total...
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...DIPLOMA IN PRE-PRIMARY TEACHERS TRAINING MID TERM ASSIGNMENT ON COMMUNITY HELPER Topic: Community Helpers Subject : Environment Studies Level / Class : GRADE II No. of students : 16 Time : 40 mins Age Group : 6-7 years Teaching Aids : Flash Cards, Marker, VCD, Reference Book “Hello Earth” Aim of the Lesson: a) Main focus - To develop understanding in young learners about Helpers in our community and how they help us? b) General Aim - To develop listening and speaking skills. To enhance their knowledge about community helpers. To enhance the volume of their vocabulary. To develop memorization and imaginative skills. Concepts Introduced: a. Identification of Community Helpers. b. Tools used by Community Helpers. c. Work Place of Community Helpers. d. Dress up of Community Helpers. e. Dramatization of Community Helpers. Time Allotted | Activity Planned | Teacher’s Activity | Student’s Activity | Anticipated Problems (Teacher’s Point of View) | 10 min | Warm...
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...Math 100 Review for Test III As college students, you are expected to be able to review on your own, and carefully manage your time. That is, the primary responsibility for mastering the material is your own. Here are some suggestions that may help in preparing for your first test. As listed in the Course syllabus, you may bring one sheet of self-prepared notes. You are cautioned that spending too much time searching through notes can be fatal. You should know the material well enough that only a quick glance at notes will suffice. A very good source for review is the Worksheets that you have been printing during the term. Printing one or two Worksheets each week is a good study skill. Click on Worksheet in the blue bar in Aleks. This will show the Worksheets and answers. You can also get ALEKS to suggest Review problems for you. Click on Review in the blue bar in ALEKS. You should see something similar to what is below. You should look over the list, and decide for yourself which problems you had trouble with and need to review. Clicking on any topic listed will bring you to Practice on that topic. This test will cover Chapters 5. There are 23 possible topics that were covered. I will certainly not ask a question from every one of these topics, but ... you should be prepared to answer questions on any of them. And there might be a review topic from the first two tests. Based on your work to date, I expect all of you to do very well....
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...Website Planning Worksheet n o This worksheet can help you to lay a solid foundation for your web sit e. It will help define your goals along with setting a o o r t p r guidelines to make sure your website is complete and useful for your visitors. If you don't know an answer or feel like it e k m s r o w l a t e doesn't apply to you, then simply leave it blank. If you have any quest ions; please call and I'll be happy to help you Name Address r City State Zip Code Business Phone n Home Phone Cell Phone Description of your business c o s (One Paragraph) e [Type a quote from the document o or the summa ary of an inte eresting point. You can t position t the text box a anywhere in the document t t. Use the Dra awing Tools t tab to change the e formattin ng of the pull quote text bo ox.] Description of services c e , (Separated by commas) Example: Pizza, Restaurant, Take Out, Salads, Italian, Entrees, Pasta, a m p s e [Type a quote from the u e document o or the summa ary of an interesting point. You can t anywhere in the document t. Use the Dra awing Tools tab to change e position the text box a the forma atting of the p pull quote tex xt box.] 1 What is your "Motto· or ·Slogan"? Do you want people to: ☐ Learn more about your business or organization? ☐ Hire you to perform a service? ☐ Buy products from you...
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...Monte Carlo Simulation Tutorial This tutorial shows how to use Microsoft Excel to develop Monte Carlo simulations without the use of add-ins or special software (such as @RISK or Crystal Ball). (Note, however, that there are some important advantages of using these dedicated software packages.) After completing the tutorial you should have a sufficient understanding of Monte Carlo concepts and Excel capabilities to begin building your own Monte Carlo simulations applied to a wide range of business problems, including the construction of short-term profit plans (otherwise referred to as “Cost-Volume-Profit” models, covered in Chapter 9 of the text). Monte Carlo refers to a widely used approach for solving complex problems using computer algorithms to simulate the variables in the model (e.g., a CVP model). Typically, an algorithm is developed to "model" the problem, and then the algorithm is run many times (from a few hundred up to millions) in order to develop a statistical data set for how the model behaves. Simple Example: Tossing a “Fair” Coin—Heads vs. Tails? For the simplest example, consider the basic coin toss. This is a process which has two possible outcomes (heads or tails), each with a 50% probability. In a million coin tosses, roughly half will be “heads” and half will be “tails.” A simple Monte Carlo simulation would support this conclusion. If you were to develop a spreadsheet with a random number generator resulting in 0 for “heads” and 1 for “tails,” then...
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...This report provides an in-depth analysis of the two Everest Simulations conducted by Group 10 of MGMT1001 Thursday Tutorial. This task required students to form teams consisting of five to six members whose goals were to summit Mount Everest. While it provided us with a rich experience in team dynamics and collaboration, it also enabled us to explore key managerial concepts taught in the course, consisting of: • Communication • Groups and Teams • Leadership In this report, we examine the effectiveness of Face to Face Communication (FTFC) versus Computer Mediated Communication (CMC), and the problems encountered through the utilisation of the virtual medium including efficiency of the feedback system, loss of personal focus and other emergent issues. It includes personal reflections on attitudes and perceptions, as well as group performance and strategies adopted in the second Simulation in order to create a more positive team experience. Theories which relate to interpersonal communication have also been integrated in the report to illustrate its relation to certain situations encountered during the Simulation. Additionally, we provide a multifaceted analysis on the notion of team cohesiveness and how it attributes to better performance outcomes. An overview on the different intragroup conflicts encountered in the Simulation has been included, examining the positive and negative impact that conflict had on team experience and performance, and how mutual agreements were reached...
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...is a computer necessary in conducting a realworld simulation? Answer It is important because there are many different types of outcomes that comes in with simulation. Computers are used in daily life activities and it is necessary. 14-11 What is operational gaming? What is systems simulation? Give examples of how each may be applied. Answer Operational gaming is the use of simulation in competitive situations such as military games and business or management. System simulation ls that deal with the dynamics of large organizational or governmental systems. Validation The process of comparing a model to the real system that it represents to make sure that it is accurate. 14-17 (a) Resimulate the number of stockouts incurred over a 20-week period (assuming Higgins maintains a constant supply of 8 heaters). (b) Conduct this 20-week simulation two more times and compare your answers with those in part (a). Did they change significantly? Why or why not? (c) What is the new expected number of sales per week? Answer A. The number of stockouts incurred over a 20 week period is HOT WATER NUMBER OF HEATER SALES WEEKS THIS PER WEEK NUMBER WAS SOLD 3 2 4 9 5 10 6 15 7 25 8 12 9 12 10 10 B, Two more times would give us the value of a multiplied by 2. c. 25 14-18 A. 15 days of barge uploadings and average number of barges delayed B, They both are probabilistic simulations. Chapter 5 HW 5-14 Using MAD, determine whether...
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...A SYSTEM SIMULATION STUDY ON THE THREE FAST MOVING PRODUCTS (MARLBORO, C2, VIVA) OF THE COLLEGE VARIETY SHOPPE USING THE MONTE CARLO SIMULATION IN INVENTORY MANAGEMENT EXECUTIVE SUMMARY This study shows how the selected three fast moving products (Marlboro cigarettes, C2, Viva mineral water) move from the current Inventory Management technique of the College Variety Shoppe from its distributors to its warehouse storage to the end user or customer. An excel program and a simulation model was made to observed its current performance. After the observation, the group performs an experimentation that will improve the current technique of the College Variety Shoppe. After simulating the experimentation, the group then give conclusions and recommendations on how to improve the College Variety Shoppe’s current Inventory Management. TABLE OF CONTENTS Title Page ........................................................ 1 Executive Summary ........................................................ 2 Table of Contents ........................................................ 3 Introduction ........................................................ 4 Methodology ........................................................ 6 Model Development ........................................................ 7 Model Validation ........................................................ 11 Experimentation, Results .......
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...Initial operations strategy Prior to the commencement of the simulation, we examined the 50 days of historical data to glean as much information as we could about the operations. We performed some analysis in Excel and created a dashboard to illustrate various data. Specifically, we regressed the prior 50 days of jobs accepted to forecast demand over the next 2 - 3 months within a 95% confidence interval. The yellow and grey lines represent the maximum and minimum variability, respectively, based on two standard deviations (95%). Exhibit 1: Forecasted and actual demand by Day 50 and Day 270 Our two primary goals at the beginning of the simulation were as follows: 1) Eliminate bottlenecks and increase capacity in order to meet forecasted demand 2) Decrease lead time to 0.25 days in order to satisfy Contract 2 and maximize revenue In order to achieve these goals, we would need to know the capacity and throughput time of the entire system. We used the time required by each machine to process a lot to calculate capacity per station and then capacity of the entire production line (380 kits/day or 6 orders/day). In Exhibit 2 we can observe that the capacity of the production line is given by the station that produces the least number of units per day. Exhibit 2: Capacity of the production line The Decisions We decided to work with the maximum variability of demand because there was a penalty for late jobs and because there was no revenue for orders that took more than “x”...
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...Monte Carlo Statistical Analysis Name Course Instructor Date The Monte Carlo method is a mathematical method used for problem solving through the generation of random numbers and then observing a fraction of these numbers and the properties they obey. It is useful in obtaining numerical solutions to problems that are too complicated for analytical solutions. It is a form of probability used to understand the impact of risk and uncertainty in various areas such as financial and cost forecasting. It involves computation of the likelihood of given events occurring or not occurring, without taking into account the interaction of the elements involved in influencing the occurrence. The mathematical method was invented by Stanislaw Ulam in 1946 and named by Nicholas Metropolis after a classy gambling resort in Monaco, where a relative of Ulam frequently gambled [ (Fishman, 1996) ]. Concepts of the Monte Carlo method Uncertainty Being a forecasting model, there are assumptions that need to be made due to the uncertainty of various factors. One therefore needs to be able to make estimations of the expected results as they cannot predict with certainty what the end value will be. Important factors such as historical data and past experiences in the field can be helpful in making an accurate estimate. Estimation In some cases, estimation may be possible but in others it is not. In situations where estimation is possible, it is wise to use a wide range of possible values instead...
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...materials such as Ultra/Advanced High Strength Steels (U/AHSS), aluminum alloys, magnesium alloys and boron steels in automotive industry is increasing to reduce vehicle weight and increase crash performance. The use of these relatively new materials requires advanced and reliable techniques to a) obtain data on material properties and flow stress, b) predicting springback and fracture in bending and flanging, c) selecting lubricants and die materials/coatings for stamping and forging and d) designing tools for blanking and shearing. In addition, designing the process and tooling for a) hot stamping of boron steels, b) warm forming of Al and Mg alloys, and c) optimizing the use of servo-drive presses require advanced Finite Element based simulation methods. CPF is conducting R&D in most of these topics and also in many hot and cold forging related topics. This paper gives an overview of this research and discusses how the research results are applied in cooperation with industry. Keywords: Metal Forming, Sheet metal, Forging, FEM 1 INTRODUCTION The Center for Precision Forming (CPF) has been established with funding from the National Science Foundation (NSF) and a number of companies (www.cpforming.org). CPF is an outgrowth of the Engineering Research Center for Net Shape Manufacturing (ERC/NSM – www.ercnsm.org) and conducts research in sheet metal forming while ERC/NSM focuses on cold and hot forging related R&D projects. Both Centers work closely with industry under contract....
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...Introduction This chapter describes our work in evolution of buildable designs using miniature plastic bricks as modular components. Lego 1 bricks are well known for their flexibility when it comes to creating low cost, handy designs of vehicles and structures. Their simple modular concept make toy bricks a good ground for doing evolution of computer simulated structures which can be built and deployed. Instead of incorporating an expert system of engineering knowledge into the program, which would result in more familiar structures, we combined an evolutionary algorithm with a model of the physical reality and a purely utilitarian fitness function, providing measures of feasibility and functionality. Our algorithms integrate a model of the physical properties of Lego structures with an evolutionary process that freely combines bricks of different shape and size into structures that are evaluated by how well they perform a desired function. The evolutionary process runs in an environment that has not been unnecessarily constrained by our own preconceptions on how to solve the problem. The results are encouraging. The evolved structures have a surprisingly alien look: they are not based in common knowledge on how to build with brick toys; instead, the computer found ways of its own through the evolutionary search process. We were able to assemble the final designs manually and confirm that they accomplish the objectives introduced with our fitness functions. This chapter...
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...developed, operated and maintained the Concept Simulator since 1998. The Concept Simulator models the functional operation and inter-operation of key components of train control system architecture and the external systems to which the system interfaces. The simulator is valuable in the development and analysis of operational principles, and in assessing design trade-offs. The SEA-designed facility simulates operation at ERTMS Levels 1, 2, and 3. Components include a Communications Network, a Network Management Centre, a generic Interlocking, a Radio Block Centre, a Track Simulator including both conventional and TCS equipment, a Driver Desk, a European Vital Computer and a Driver MMI. The components are modelled using software-based simulations hosted on networked PCs. The simulator has been valuable in the engineering evaluation and validation of emergent system architectures, and enables system constraints to be explored and defined. ERTMS operational modes and the transitions between them are simulated and ERTMS principles and procedures are followed. Innovative Customer Information System (ICIS) SEA's Innovative Customer Information System (ICIS) is capable of managing and displaying customer information, including real time information, in a visually dynamic manner. The system utilises intelligent screens and wireless technology to distribute data, thus minimising installation and commissioning efforts. The system will be suitable for any transport environment, mobile...
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...Brooklyn Warren Chapter 10 Simulation Modeling What is Simulation? * To try to duplicate the features, appearance, and characteristics of a real system. * Imitate a real-world situation mathematically. * Study its properties and operating characteristics. * Draw conclusions and make action decisions based on the results. Processes of Simulation: 1. Define Problem 2. Introduce Important Variables 3. Construct Simulation Model 4. Specify Values of Variables to Be Tested 5. Conduct the Simulation 6. Examine the Results 7. Select Best Course of Action Advantages of Simulation: * Straightforward and flexible. * Can handle large and complex systems. * Allows "what-if" questions. * Does not interfere with real-world systems. * Study interactions among variable. * "Time comparison" is possible. * Handles complications that other methods can't. Disadvantages of Simulation: * Can be expensive and time consuming. * Does not generate optimal solutions. * Managers must generate all conditions and constraints. * Each model is unique. Monte Carlo Simulation: Can be used with variables that are probabilistic. Steps: * Establish the probability distribution for each random variable. * Use random numbers to generate random values. * Repeat for some number of replications. Probability Distributions: Historical data Goodness-of-fit tests for common distributions: ...
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...678-679 of the text. Using simulation estimate the loss of revenue due to copier breakdown for one year, as follows: 1. In Excel, use a suitable method for generating the number of days needed to repair the copier, when it is out of service, according to the discrete distribution shown. 2. In Excel, use a suitable method for simulating the interval between successive breakdowns, according to the continuous distribution shown. 3. In Excel, use a suitable method for simulating the lost revenue for each day the copier is out of service. 4. Put all of this together to simulate the lost revenue due to copier breakdowns over 1 year to answer the question asked in the case study. 5. In a word processing program, write a brief description/explanation of how you implemented each component of the model. Write 1-2 paragraphs for each component of the model (days-to-repair; interval between breakdowns; lost revenue; putting it together). 6. Answer the question posed in the case study. How confident are you that this answer is a good one? What are the limits of the study? Write at least one paragraph. There are two deliverables for this Case Problem, the Excel spreadsheet and the written description/explanation. Please submit both of them electronically via the dropbox. The assignment will be graded using the associated rubric. |Outcome Assessed: |Create statistical analysis of simulation results. ...
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