• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 64
  • 44
  • 30
  • 20
  • 4
  • Tagged with
  • 171
  • 121
  • 119
  • 71
  • 71
  • 71
  • 65
  • 62
  • 62
  • 62
  • 44
  • 38
  • 33
  • 30
  • 30
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Analysis and Modeling of Planetary Gearbox Vibration Data for Early Fault Detection

Yip, Lawrence 04 January 2012 (has links)
Planetary gearboxes are key rotating motion transmission components used in many types of machinery. Syncrude Canada uses planetary gearboxes in their Fort McMurray oil sands field operations to transport stockpile for further downstream processing. There is currently no condition monitoring capability for these gearboxes. As such, unexpected failures are not detected in advance. Failure of these gearboxes results in costly bottlenecks and secondary damages. Routine inspections to check on condition of the gearbox, requiring the gearbox to be off-line, are also costly. This thesis investigates into condition monitoring for Syncrude's planetary gearbox through analyzing the data collected at a test rig that is modeled after the one used in field operations. The condition at specific points in the testing is analyzed, and the desired fault to be detected early is identified. The Time Synchronous Averaging (TSA) preprocessing technique is applied to the original data, and results show that it is superior for modeling purposes. Health indicators and statistical control charts are applied based on the TSA model, and show clear indication of deterioration.
2

Analysis and Modeling of Planetary Gearbox Vibration Data for Early Fault Detection

Yip, Lawrence 04 January 2012 (has links)
Planetary gearboxes are key rotating motion transmission components used in many types of machinery. Syncrude Canada uses planetary gearboxes in their Fort McMurray oil sands field operations to transport stockpile for further downstream processing. There is currently no condition monitoring capability for these gearboxes. As such, unexpected failures are not detected in advance. Failure of these gearboxes results in costly bottlenecks and secondary damages. Routine inspections to check on condition of the gearbox, requiring the gearbox to be off-line, are also costly. This thesis investigates into condition monitoring for Syncrude's planetary gearbox through analyzing the data collected at a test rig that is modeled after the one used in field operations. The condition at specific points in the testing is analyzed, and the desired fault to be detected early is identified. The Time Synchronous Averaging (TSA) preprocessing technique is applied to the original data, and results show that it is superior for modeling purposes. Health indicators and statistical control charts are applied based on the TSA model, and show clear indication of deterioration.
3

A Look at Model Uncertainty in the Evaluation of Commodity Contingent Claims: A Practitioner's Guide

Lukovich, Jovan 15 July 2013 (has links)
Model uncertainty in financial markets is prevalent by the very nature of how models are constructed and used by financial practitioners. As such, a proper characterization of model uncertainty should be paramount in the eyes of every practitioner, and furthermore, a proper framework for implementing such a characterization towards financial activities should be implicit. While model uncertainty is acknowledged by practitioners, a cohesive and robust framework for determining a model uncertainty risk measure that is broadly accepted by practitioners is missing. We acknowledge this deficiency and provide a practitioner's guide for evaluating a modern characterization of model uncertainty, specifically that of Li and Kwon, as applied to a subset of derivative related calculations, with the goal of promoting its implementation by practitioners. We promote its implementation by demonstrating the utility and flexibility of such a characterization relative to another modern model uncertainty risk measure, specifically that of Cont.
4

A Look at Model Uncertainty in the Evaluation of Commodity Contingent Claims: A Practitioner's Guide

Lukovich, Jovan 15 July 2013 (has links)
Model uncertainty in financial markets is prevalent by the very nature of how models are constructed and used by financial practitioners. As such, a proper characterization of model uncertainty should be paramount in the eyes of every practitioner, and furthermore, a proper framework for implementing such a characterization towards financial activities should be implicit. While model uncertainty is acknowledged by practitioners, a cohesive and robust framework for determining a model uncertainty risk measure that is broadly accepted by practitioners is missing. We acknowledge this deficiency and provide a practitioner's guide for evaluating a modern characterization of model uncertainty, specifically that of Li and Kwon, as applied to a subset of derivative related calculations, with the goal of promoting its implementation by practitioners. We promote its implementation by demonstrating the utility and flexibility of such a characterization relative to another modern model uncertainty risk measure, specifically that of Cont.
5

Stochastic Mixed-integer Programming for Financial Planning Problems using Network Flow Structure

Alimardani, Masoud 17 March 2014 (has links)
Portfolio design is one of the central topics in finance. The original attempt dates back to the mean-variance model developed for a single period portfolio selection. To have a more realistic approach, multi-period selections were developed in order to manage uncertainties associated with the financial markets. This thesis presents a multi-period financial model proposed on the basis of the network flow structure with many planning advantages. This approach comprises two main steps, dynamic portfolio selection, and dynamic portfolio monitoring and rebalancing throughout the investment horizon. To build a realistic yet practical model that can capture the real characteristics of a portfolio a set of proper constraints is designed including restrictions on the size of the portfolio as well as the number of transactions, and consequently the management costs. The model is solved for two-stage financial planning problems to demonstrate the main advantages as well as characteristics of the presented approach.
6

Stochastic Mixed-integer Programming for Financial Planning Problems using Network Flow Structure

Alimardani, Masoud 17 March 2014 (has links)
Portfolio design is one of the central topics in finance. The original attempt dates back to the mean-variance model developed for a single period portfolio selection. To have a more realistic approach, multi-period selections were developed in order to manage uncertainties associated with the financial markets. This thesis presents a multi-period financial model proposed on the basis of the network flow structure with many planning advantages. This approach comprises two main steps, dynamic portfolio selection, and dynamic portfolio monitoring and rebalancing throughout the investment horizon. To build a realistic yet practical model that can capture the real characteristics of a portfolio a set of proper constraints is designed including restrictions on the size of the portfolio as well as the number of transactions, and consequently the management costs. The model is solved for two-stage financial planning problems to demonstrate the main advantages as well as characteristics of the presented approach.
7

Comprehensive Robustness via Moment-based Optimization : Theory and Applications

Li, Jonathan 17 December 2012 (has links)
The use of a stochastic model to predict the likelihood of future outcomes forms an integral part of decision optimization under uncertainty. In classical stochastic modeling uncertain parameters are often assumed to be driven by a particular form of probability distribution. In practice however, the distributional form is often difficult to infer from the observed data, and the incorrect choice of distribution can lead to significant quality deterioration of resultant decisions and unexpected losses. In this thesis, we present new approaches for evaluating expected future performance that do not rely on an exact distributional specification and can be robust against the errors related to committing to a particular specification. The notion of comprehensive robustness is promoted, where various degrees of model misspecification are studied. This includes fundamental one such as unknown distributional form and more involved ones such as stochastic moments and moment outliers. The approaches are developed based on the techniques of moment-based optimization, where bounds on the expected performance are sought based solely on partial moment information. They can be integrated into decision optimization and generate decisions that are robust against model misspecification in a comprehensive manner. In the first part of the thesis, we extend the applicability of moment-based optimization to incorporate new objective functions such as convex risk measures and richer moment information such as higher-order multivariate moments. In the second part, new tractable optimization frameworks are developed that account for various forms of moment uncertainty in the context of decision analysis and optimization. Financial applications such as portfolio selection and option pricing are studied.
8

Comprehensive Robustness via Moment-based Optimization : Theory and Applications

Li, Jonathan 17 December 2012 (has links)
The use of a stochastic model to predict the likelihood of future outcomes forms an integral part of decision optimization under uncertainty. In classical stochastic modeling uncertain parameters are often assumed to be driven by a particular form of probability distribution. In practice however, the distributional form is often difficult to infer from the observed data, and the incorrect choice of distribution can lead to significant quality deterioration of resultant decisions and unexpected losses. In this thesis, we present new approaches for evaluating expected future performance that do not rely on an exact distributional specification and can be robust against the errors related to committing to a particular specification. The notion of comprehensive robustness is promoted, where various degrees of model misspecification are studied. This includes fundamental one such as unknown distributional form and more involved ones such as stochastic moments and moment outliers. The approaches are developed based on the techniques of moment-based optimization, where bounds on the expected performance are sought based solely on partial moment information. They can be integrated into decision optimization and generate decisions that are robust against model misspecification in a comprehensive manner. In the first part of the thesis, we extend the applicability of moment-based optimization to incorporate new objective functions such as convex risk measures and richer moment information such as higher-order multivariate moments. In the second part, new tractable optimization frameworks are developed that account for various forms of moment uncertainty in the context of decision analysis and optimization. Financial applications such as portfolio selection and option pricing are studied.
9

Job and career satisfaction of management dietitians

Sauer, Kevin L. January 1900 (has links)
Doctor of Philosophy / Department of Hospitality Management and Dietetics / Deborah D. Canter / Despite the enormous amount of research about job satisfaction and intent to leave, few studies have focused on Registered Dietitians (RDs) with management responsibilities. Even less is known about the level of career satisfaction or intent to leave the dietetics profession. This study examined job and career satisfaction among members of four dietetic practice groups (DPGs). An online questionnaire included 36 items of the Job Satisfaction Survey (JSS), career satisfaction and intent to leave measures. Data were analyzed from 966 dietitians in management and clinical practice using traditional statistical procedures. Management dietitians had significantly higher composite scores for six out of nine facets of job satisfaction than dietitians in non-managerial positions. Overall satisfaction scores for management dietitians (M = 153.75 ± 26.68) were also significantly higher compared to non-management dietitians (M = 140.79 ± 30.26, t = 4.368, p < 0.001). Overall satisfaction scores also differed significantly across seven groups of management dietitians, F (6, 844) = 4.41, p < 0.001. The majority of dietitians in this study did not intend to seek other jobs or leave their current jobs. Overall, management dietitians were satisfied with their careers (19.82 ± 3.73). In contrast, non-management dietitians were closer to neutral and significantly less satisfied with their careers (16.44 ± 5.06, t = 6.907, p < 0.001). Career satisfaction scores also differed significantly across seven job titles of managers, F (6, 839) = 5.69, p < 0.001. Intent to leave the profession was not observed for the majority of dietitians in this study. Additional results, implications for the dietetics profession and recommendations for future research are discussed.
10

Bankruptcy Prediction of Companies in the Retail-apparel Industry using Data Envelopment Analysis

Kingyens, Angela Tsui-Yin Tran 17 December 2012 (has links)
Since 2008, the world has been in recession. As daily news outlets report, this crisis has prompted many small businesses and large corporations to file for bankruptcy, which has grave global social implications. Despite government intervention and incentives to stimulate the economy that have put nations in hundreds of billions of dollars of debt, and have reduced the prime rates to almost zero, efforts to combat the increase in unemployment rate as well as the decrease in discretionary income have been troublesome. It is a vicious cycle: consumers are apprehensive of spending due to the instability of their jobs and ensuing personal financial problems; businesses are weary from the lack of revenue and are forced to tighten their operations which likely translates to layoffs; and so on. Cautious movement of cash flows are rooted in and influenced by the psychology of the players (stakeholders) of the game (society). Understandably, the complexity of this economic fallout is the subject of much attention. And while the markets have recovered much of the lost ground as of late, there is still great opportunity to learn about all the possible factors of this recession, in anticipation of and bracing for one more downturn before we emerge from this crisis. In fact, there is no time like today more appropriate for research in bankruptcy prediction because of its relevance, and in an age where documentation is highly encouraged and often mandated by law, the amount and accessibility of data is paramount – an academic’s paradise! The main objective of this thesis was to develop a model supported by Data Envelopment Analysis (DEA) to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports – specifically from financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report. It was hypothesized that the inclusion of variables which reflect managerial decision-making and economic factors would enhance the predictive power of current mathematical models that consider financial data exclusively. With a unique and comprehensive dataset of 85 companies, new metrics based on different aspects of the annual reports were created then combined with a slacks-based measure of efficiency DEA model and modified layering classification technique to capture the multidimensional complexity of bankruptcy. This approach proved to be an effective prediction tool, separating companies with a high risk of bankruptcy from those that were healthy, with a reliable accuracy of 80% – an improvement over the widely-used Altman bankruptcy model having 70%, 58% and 50% accuracy when predicting cases today, from one year back and from two years back, respectively. It also provides a probability of bankruptcy based on a second order polynomial function in addition to targets for improvement, and was designed to be easily adapted for analysis of other industries. Finally, the contributions of this thesis benefit creditors with better risk assessment, owners with time to improve current operations as to avoid failure altogether, as well as investors with information on which healthy companies to invest in and which unhealthy companies to short.

Page generated in 0.6735 seconds