No description available.

No description available.

Selecting the best set of tools to produce certain geometrical shapes/features in sheet metal punching is one of the problems that has a great effect on product development time, cost and achieved quality. The trend nowadays is, where at all possible, to limit design to the use of standard tools. Such an option makes the problem of selecting the appropriate set of tools even more complex, especially when considering that sheet metal features can have a wide range of complex shapes. Another dimension of complexity is limited tool rack capacity. Thus, an inappropriate tool selection strategy will lead to punching inefficiency and may require frequent stopping of the machine and replacing the required tools, which is a rather expensive and time consuming exercise. This work demonstrates that the problem of selecting the best set of tools is actually a process of searching an explosive decision tree. The difficulty in searching such types of decision trees is that intermediate decisions do not necessarily reflect the total cost implication of carrying out such a decision. A new approach to solve such a complex optimisation problem using the Monte Carlo Simulation Methods has been introduced in this thesis. The aim of the present work was to establish the use of Monte Carlo methods as an "assumptions or rule free" baseline or benchmark for the assessment of search strategies. A number of case studies are given, where the feasibility of Monte Carlo Simulation Methods as an efficient and viable method to optimise such a complex optimisation problem is demonstrated. The use of a Monte Carlo approach for selecting the best set of punching tools, showed an interesting point, that is, the effect of dominant "one-to-one" feature/tool matches on the efficiency of the search. This naturally led on to the need of a search methodology that will be more efficient than the application of the Monte Carlo method alone. This thesis presents some interesting speculations for a hybrid approach to tool selection to achieve a better solution than the use of the Monte Carlo method alone to achieve the optimum solution in a shorter time.

Objective: To explore interventions that support children and parents making health decisions. Systematic Review: A systematic review was conducted to synthesize evidence on interventions that support children’s health decision making. Five studies of variable quality were included. Interventions that improved decision making were decision coaching with or without an educational resource, or education alone. Pre-/post-test pilot: A pre-/post-test study evaluated the feasibility and acceptability of decision coaching guided by the Ottawa Family Decision Guide for children with type 1 diabetes and their parents. Of 16 families invited, 7 participated. Compared to children/parents who preferred one option at baseline, participants who were unsure of the best option rated decision coaching as more acceptable and had larger decreases in decisional conflict. Conclusions: Few studies have evaluated interventions supporting children’s decision making. The piloted decision support intervention was feasible and acceptable, particularly with children and parents who were unsure of the best option.

In today's world education and the resulting production of knowledge is highly valued as it can open the door to socioeconomic status and mobility. As a result, many students choose cultural and educational exchanges in a foreign country. The goal of this thesis is to better understand the decision making process international students experience prior to their study at an American university. Anchored in structuration theory, a two-step methodology was applied. First, a brief questionnaire survey was administered as a pilot study to gather preliminary data and initiate contact with participants. Second, interviews were conducted with foreign students to obtain background information and their reasoning for studying abroad. While most international students share common experiences in the decision making process, the temporal progression of "action steps" varies considerably among students. / Department of Geography

No description available.

This thesis explores the ability of Wi-Fi technology and the Institute of Electrical and Electronic Engineers (IEEE) 802.11 capability to disseminate various forms of information through densely vegetated, high humidity and high temperature environments. Using a lighter-than-air vehicle (balloon) and existing commercial-off-the- shelf, 802.11b and 802.16 wireless components, real-time information can be brought to the war-fighter. In particular, this thesis experiments with the use of commercially available wireless equipment and various antennae all attached to a helium-filled balloon to send and receive video, audio and digital information. This information is then disbursed to individual members of an established network over a specified land-mass. The balloon plays an important role in connecting network members to information that helps local and national commanders in making tactical decisions. These decisions consist of deploying forces, identifying and targeting the enemy, and deterring hostilities. Identifying the best method to supply real-time data to facilitate the movement of military assets and enhance a military s ability to engage an enemy decisively. Employing commercial-off-the-shelf (COTS) systems to disseminate real-time information is a potentially inexpensive solution to enable air and ground components to survey and target adversaries instantaneously. The ability to provide actionable information to the soldier serves as a force multiplier and increases the probability of mission success.

This thesis explores the utility of market mechanisms for Department of Defense (DOD) command, control, communication and collaboration (C4). Shortfalls in current C4 systems found by the Defense Science Board, Office of Force Transformation, and Command and Control Research Program are presented. Alternative C4 internal market structures that can help achieve the principles of Network-Centric Operations are illustrated. Then, using the principles of mathematical model development, the thesis builds a testable "E-Bay" type model for applying markets in the DOD. The model is not validated or tested in the space of this thesis and should undergo experimentation. Next, this thesis walks through an intelligence use case and presents a number of testable hypotheses for model validation. Two Appendices are included, the first discusses decision making in markets by taking existing decision making tools to show how the cycle of information can be improved for the decision making commander in market transaction space. The second appendix is a briefing that highlights the key points of the Virtual Military Market (VMM) and the intelligence use case. The thesis concludes that "practiced adhocracy" and improved decision making can be achieved by the VMM and that DOD should explore this concept further.

For organizations with training pipelines, this study offers insight to help identify and minimize undesirable effects which may result from often unavoidable demand variations within a resource and time constrained environment. The highly complex Naval aviation training process is used as a case study. However, any organization with a training pipeline may find this study to be useful. Within a training pipeline, like any resource constrained production line, variability may cause undesirable results to occur. Variability includes any change in the number of students to train, time-to-train, instructor availability, material availability, and other supporting factors. Undesirable effects may include: delayed time-to-train, wasted valuable resources, reduced morale, reduced quality of training, or an increase in undesirable behaviors as a result of perceived production pressures. "Wasted valuable resources" includes human capital, money, material, and time. Although other sources of variability will be discussed, this study will primarily examine the cause and effect relationships resulting from variations in the number of students to train. Potential solutions are explored.

This thesis examines the following hypothesis: Through the combined use of common training and collaborative planning, a decision maker may sufficiently alleviate the harmful effects of an environment of information so that he/she can continue to make effective decisions. An environment of extreme information ambiguity, a dependent variable, is one of the most difficult components of a battle where the decision maker may reach a confusing and debilitating point where surviving seems less and less likely. Common training, an independent variable, purports that everyone who is relevant to the situation in the battlespace has similar skills, education, doctrine, and standards of performance coupled with comparable experiences. Collaborative planning, an independent variable, connotes a sharing of ideas; synchronization of assets, use of information technology, global real-time mission planning, face-to-face meetings, and other information sharing techniques for situations of collective concern. This thesis is a unique and in depth exploration of the relation of these three variables. Until now, no other research has looked at the relation of common training and collaborative planning with respect to decision making in environments of extreme information ambiguity. In order to explore the model the researcher analyzed two historical military battles: the Battle of Trafalgar and the Battle of Midway. Detailed research using a case study method was conducted to determine if the battles substantiated the thesis model. Research results indicate that for the maritime battles studied, the model appears to be a useful tool for interpretation and description of events and their outcomes. However, future studies should also increase the number and type of battles and other factors such as time and leadership should be considered.