...University of Phoenix Material Ethics Game Simulation Worksheet Student Name: ________________ Facilitator: ______________ Complete the interactive Ethics Game Simulation, located on the student website. You will only be able to go through the simulation once, so please use this worksheet to take notes. The simulation will use the following decision model with the indicated critical decision points. Take notes about your decisions or make a copy of the screen when you complete the work to assure that you have the information needed to write your reflection at the end of the simulation. |The Case of the Troubled Teen | |Step 1: |What is the issue? |Screen | |Be Attentive | |4 | | |Your notes: | | | | | | | | | | |Step 2 ...
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...Simulation Reflection The simulation was very interesting in that my partner and I were given an opportunity to think critically about how to approach to influence different managers and workers with different characteristics. By running the simulation twice, it allowed us to find out what actions have worked and what did not during the first run, and then second run allowed us to apply what we learned to complete the second simulation in a much more efficient and timely manner. There are three stages in the simulation, including mobilization, movement, and sustain phases. The simulation begins in the mobilization phase, and in this phase it was important to get everyone aware of the new change we wish to initiate in the company. The key factor in the beginning was to introduce the new project to each person on a personal level, using personal interviews, skill building, and getting consultant’s support. All of these involve personal contact and were effective in making people both aware and interested to the change. The second stage was movement phase, and the key factors that lead to success in this stages was maintaining high credibility. We could gain credibility through getting consultant’s support and getting CEO’s public support. As majority individuals got into interest and trial stages we were able to use town hall meetings and walk the talk, which attracted more workers to be in interest and trial stages. Again, maintaining high credibility was important throughout...
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...Comprehensive Simulation Reflection Seven seconds… The heroin coursing through his veins. Empty bottles and track marks provided an escape. A 38-year old Caucasian, male found on the bathroom floor by his nine-year-old daughter. This simulation provoked the need to prioritize nursing assessments and interventions for a patient presenting with a heroin overdose and alcohol toxicity. Genetic and genomic considerations were taken into account regarding substance addictions. By evaluating the life of another, personal strengths and weaknesses were discovered. Twelve minutes… The time spent lying on the bathroom floor. The patient was found unconscious. Cardiopulmonary Resuscitation (CPR) occurred and Narcan was administered. Pinpoint pupils,...
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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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...Collegiality has proven to be a key aspect of nursing as well. I experienced this through the mega simulation that I was able to participate in this semester which focused on interprofessional education. This simulation combined nursing students with students in areas such as occupational therapy, athletic training, social work, and health administration. By working together as a team throughout this simulation, we were able to implement interventions related to the case of a young, pre-diabetic college student in order to provide her with optimal healthcare. A few of the key interventions that took place were assessments performed by the nursing students within our scope of practice, creation of a care plan and healthcare goals, involvement from social work students to assist the patient in obtaining a...
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...Evaluate your personal and team performance in the simulation based on the peer evaluation report by doing the following: 2. Discuss howone of your strengths can be utilized in the workplace. 3. Discuss how you can improve uponone of your weaknesses in the workplace. 4. Discuss your role on the team. 5. Discuss the strengths of your team as a whole. 6. Discuss the weaknesses of your team as a whole. 7. Explain how you interacted with your team. 8. Explain how you overcame challenges you faced as a team. 9. Discuss what teamwork advice you would give to others who were beginning to work on the simulation. 10. Discuss the relevance of teamwork in the simulation to the context of your professional Task 2 1. Describe the impact the company strategy had on your functional area in the simulation. 2. Reflect on the decisions that were made in the simulation by doing the following: Note: Your reflection may include graphs and other data. 1. Discuss decisions that you would change. 1. Discuss decisions that had a positive impact. 3. Present your strategic outlook for your functional area in the simulation. 1. Recommend future decisions for your functional area in the simulation. 1. Submit the attached “Assignment Designation Form.” 1. Discuss the overall performance of the business compared to competitors using the financial reports from the simulation by doing the following: Note: The financial...
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...Chapter 51. Enhancing Patient Safety in Nursing Education Through Patient Simulation Carol Fowler Durham, Kathryn R. Alden Background The alarming rise in morbidity and mortality among hospitalized patients throughout the United States heightens concerns about professional competency.1 Nurses and other health care professionals are under increased scrutiny to provide safe, effective care. Likewise, nursing education programs are faced with increased pressure to produce graduates who are capable of providing safe patient care. Toward that end, nursing education programs develop curricula, hire qualified faculty, and select learning experiences for students in an effort to train and graduate competent, effective nurses. The instructional strategies utilized in both didactic and clinical components of nursing education courses are highly influential in determining critical thinking and clinical decisionmaking ability as well as in developing the psychomotor skill performance of new graduates. Of course, it is unrealistic to think that graduates of nursing education programs have received all the training they need when they depart the doors of academia. Orientation programs for new graduates and continuing education for nurses are essential tools to help practitioners improve their knowledge, skills, and expertise so that quality patient care is provided and outcomes are optimized while errors are minimized. Ongoing evaluation of nursing competence is necessary...
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...experience of learning from reflection on giving intramuscular (IM) injections, using Gibbs's (1988) reflective model. I demonstrate how practice anxiety, as a student nurse, can be dealt with through effective mentoring. I chose the seminal theory of Gibbs reflection on practice, as it illustrates six significant stages; description, feelings, evaluation, analysis of the incident, conclusion and an action plan Ghaye and Lillyman (1997). Gibbs cycle is used throughout the process of reflecting on the incident to help me make sense of my practice and understand what l could do differently to enhance good practice. I use my experience from a placement simulation as I could not be on actual placement due to unforeseen circumstances. Reflection is a process through which healthcare practitioners and students can learn from experience and use the knowledge to inform and improve practice Schon, (1983). The ability to reflect on one's actions is particularly imperative in clinical practice and discourse. As Jarvis (1992) asserted, there is no consensus on the definition of reflection as it is a broad concept. Reid (1993, p305.) define reflection as; “a course of action reviewing an occurrence of practice to describe, analyse, evaluate and so inform learning about practice” Schon (1983) identified two types of reflection which are; reflection in action, which takes place during the event where the practitioner may not be aware that it is happening and reflection on action, which takes place...
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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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