Global ETD Search

1	The Annotation Cost of Context Switching: How Topic Models and Active Learning [May Not] Work Together Okuda, Nozomu 01 August 2017 (has links) The labeling of language resources is a time consuming task, whether aided by machine learning or not. Much of the prior work in this area has focused on accelerating human annotation in the context of machine learning, yielding a variety of active learning approaches. Most of these attempt to lead an annotator to label the items which are most likely to improve the quality of an automated, machine learning-based model. These active learning approaches seek to understand the effect of item selection on the machine learning model, but give significantly less emphasis to the effect of item selection on the human annotator. In this work, we consider a sentiment labeling task where existing, traditional active learning seems to have little or no value. We focus instead on the human annotator by ordering the items for better annotator efficiency. active learning topic modeling annotation human cost Computer Sciences
2	An exploration of indirect human costs associated with information systems adoption Ayfarah, Souad Mohamed January 2004 (has links) One of the dilemmas that information systems (IS) decision-makers encounter is the identification of the often hidden costs associated with IS adoption, particularly since most of them are reported to be external to the traditional IS budget. The review of the IS literature has identified that much effort to date has focused on the identification and measurement of direct costs, and that much less attention has been paid to indirect costs. One of the main problems reported in the literature associated with looking at indirect costs is that they are intangible and difficult to quantify, and there is evidence suggesting that these indirect costs are rarely completely budgeted for, and thus deserve a much closer consideration by decision-makers. This research investigates this view, arguing that one element of indirect costs, that is, indirect human costs (lRCs), is underestimated and little understood. The author argues that it is not possible to estimate or evaluate IHCs without first identifying all their components, yet there is an absence of models that show how such costs are allocated for IS adoption. This underpins the necessity of the present research. Proposed here is a framework of nine sequential phases for accommodating indirect human costs. In addition to this, 1) three conjectures, 2) cost taxonomy and 3) an interrelationship-mapping cost driver model of IRCs, are proposed based on the literature analysis and underpinning the conceptual phases of the framework. To test the conjectures and validate the models proposed, a case research strategy using case settings were carried out in the private sector. Empirical findings validates the models proposed and reveal that indirect human costs are perceived as costs associated with IS adoption, nevertheless not included in the evaluation process or investment proposals. However, during the empirical research, new cost factors and drivers emerged, which resulted in modifications being made to the previously proposed conceptual models. In doing so, it provides investment decision-makers with novel frames of reference and an extensive list of IRCs that can be used during both the IS budget proposals and the evaluation process of the IS investment. 658.4038011
3	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics
4	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics

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