ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / The measurement result is complete only if it contains the measurand and its units, uncertainty and coverage factor. The uncertainty estimation for the parameters acquired by the FTI is a known process. To execute this task the Institute of Research and Flight Test (IPEV) developed the SALEV© system which is fully compliant with the applicable standards. But the measurement set also includes Derived Parameters. The uncertainty evaluation of these parameters can be solved by cumbersome partial derivates. The search for a simpler solution leads us to a Monte-Carlo based algorithm. The result of using this approach are presented and discussed.

This thesis explores different paradigms for incorporating uncertainty with optimization frameworks for applications in chemical engineering and site-wide operations. First, we address the simulation optimization problem, which deals with the search for optimal input parameters to black-box stochastic simulations which are potentially expensive to evaluate. We include a comprehensive literature survey of the state-of-the-art in the area, propose a new provably convergent trust region-based algorithm, and discuss implementation details along with extensive computational experience, including examples for chemical engineering applications. Next, we look at the problem of long-term site-wide maintenance turnaround planning. Turnarounds involve the disruption of production for significant periods of time, and may incur enormous costs in terms of maintenance manpower as well as lost sales. The problem involves (1) the simulation of profit deterioration due to wear and tear followed by the determination of how frequently a particular turnaround should take place; and (2) the consideration of site network structure and turnaround frequencies to determine how turnarounds of different plants may be coordinated over a long-term horizon. We investigate two mixed-integer models, the first of which determines optimal frequencies of individual plant turnarounds, while the second considers maximizing long-term profit through coordination of turnarounds across the site. We then turn to more conventional methods of dealing with optimization under uncertainty, and make use of a combined robust optimization and stochastic programming approach to medium-term maintenance planning in integrated chemical sites. The nature of the uncertainty considered affects two aspects of maintenance planning, one of which is most suitably addressed through a robust optimization framework, while the other is better handled with stochastic programming models. In summary, we highlight the importance of considering uncertainty in optimization as well as the choice of approach or paradigm used through chemical engineering applications that span varied domains and time scales.

This thesis focused on the physiological impact of uncertainty on caregivers of Alzheimer's disease victims. A convenience sample of 30 subjects was used. The uncertainty level was assessed using Parent's Perception of Uncertainty in Illness Scale. Physiological arousal was determined by assaying urinary cortisol and catecholamine levels. The results of the study showed that uncertainty and physiological stress were inversely related. This led to the conclusion that uncertainty was beneficial in that it offered a degree of hope. Knowledge of the disease process increased the stress perceived due to the devastation of Alzheimer's disease and its incurable state. Younger individuals had higher physiological stress than older individuals for comparable amounts of uncertainty. Multiple reasons for this finding are postulated. They include the thought that the younger caregivers may fear developing the disease. It also may be that younger individuals need certainty about the future.

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In the publish/subscribe paradigm, information providers disseminate publications to all consumers who have expressed interest by registering subscriptions. This paradigm has found wide-spread applications, ranging from selective information dissemination to network management. However, all existing publish/subscribe systems cannot capture uncertainty inherent to the information in either subscriptions or publications. In many situations the large number of data sources exhibit various kinds of uncertainties. Examples of imprecision include: exact knowledge to either specify subscriptions or publications is not available; the match between a subscription and a publication with uncertain data is approximate; the constraints used to define a match is not only content based, but also take the semantic information into consideration. All these kinds of uncertainties have not received much attention in the context of publish/subscribe systems. In this thesis, we propose new publish/subscribe models to express uncertainties and semantics in publications and subscriptions, along with the matching semantics for each model. We also develop efficient algorithms to perform filtering for our models so that it can be applied to process the rapidly increasing information on the Internet. A thorough experimental evaluation is presented to demonstrate that the proposed systems can offer scalability to large number of subscribers and high publishing rates.

A fuzzy approach for handling uncertain preferences is developed within the paradigm of the Graph Model for Conflict Resolution and new advances in trust modeling and assessment are put forward for permitting decision makers (DMs) to decide with whom to cooperate and trust in order to move from a potential resolution to a more preferred one that is not attainable on an individual basis. The applicability and the usefulness of the fuzzy preference and trust research for giving an enhanced strategic understanding about a dispute and its possible resolution are demonstrated by employing a realworld environmental conflict as well as two generic games that represent a wide range of real life encounters dealing with trust and cooperation dilemmas. The introduction of the uncertain preference representation extends the applicability of the Graph Model for Conflict Resolution to handle conflicts with missing or incomplete preference information. Assessing the presence of trust will help to compensate for the missing information and bridge the gap between a desired outcome and a feared betrayal. These advances in the areas of uncertain preferences and trust have potential applications in engineering decision making, electronic commerce, multiagent systems, international trade and many other areas where conflict is present. In order to model a conflict, it is assumed that the decision makers, options, and the preferences of the decision makers over possible states are known. However, it is often the case that the preferences are not known for certain. This could be due to lack of information, impreciseness, or misinformation intentionally supplied by a competitor. Fuzzy logic is applied to handle this type of information. In particular, it allows a decision maker to express preferences using linguistic terms rather than exact values. It also makes use of data intervals rather than crisp values which could accommodate minor shifts in values without drastically changing the overall results. The four solution concepts of Nash, general metarationality, symmetric metarationality, and sequential stability for determining stability and potential resolutions to a conflict, are extended to accommodate the new fuzzy preference representation. The newly proposed solution concepts are designed to work for two and more than two decision maker cases. Hypothetical and real life conflicts are used to demonstrate the applicability of this newly proposed procedure. Upon reaching a conflict resolution, it might be in the best interests of some of the decision makers to cooperate and form a coalition to move from the current resolution to a better one that is not achievable on an individual basis. This may require moving to an intermediate state or states which may be less preferred by some of the coalition members while being more preferred by others compared to the original or the final state. When the move is irreversible, which is the case in most real life situations, this requires the existence of a minimum level of trust to remove any fears of betrayal. The development of trust modeling and assessment techniques, allows decision makers to decide with whom to cooperate and trust. Illustrative examples are developed to show how this modeling works in practice. The new theoretical developments presented in this research enhance the applicability of the Graph Model for Conflict Resolution. The proposed trust modeling allows a reasonable way of analyzing and predicting the formation of coalitions in conflict analysis and cooperative game theory. It also opens doors for further research and developments in trust modeling in areas such as electronic commerce and multiagent systems.

M.Ing. / Experiments are being conducted with regard to heat exchange systems. However, there are errors and uncertainties attached to each system. Journals, which publish articles concerning heat transfer experiments, require an estimate of this uncertainty. These uncertainties must be calculated in order to determine how valid a set of results is. The uncertainty describes to what level one may rely on a set of experimental results and conclusions. The uncertainty was calculated by the formulation of an uncertainty equation with the use of various statistical methods. Adjustments or modifications had to be made to the present uncertainty equations in order to calculate the uncertainty in heat transfer systems. Uncertainty based on a general uncertainty equation by Schultz and Cole (1979) enabled the derivation of the equations to calculate the necessary uncertainty factor for heat transfer systems. Implementation of the equations in various experimental set-ups was achieved. The uncertainty equations yielded results that seemed consistent with the subjective view of the experimenter. Therefore, the equations were considered valid.

This study sets out to understand how international development projects supporting labor activism work in contemporary China. It focuses on the lived experiences of and relationships among a group of grassroots⁠ labor NGOs in the province of Guangdong, South China; intermediary NGOs in Hong Kong; and Western funding agencies that try to bring about social change in postsocialist China where the political climate is still highly restrictive and the limits of the state’s tolerance for activism are ambiguous and uncertain. Foregrounding the notion of uncertainty, this study investigates how state control is exercised by examining a specific logic of practices, discourses, and a mode of existence that constantly mask and unmask the state. More specifically, this study explores how the uncertainty about the boundaries of permissible activism is generative of a sociopolitical realm in which variously positioned subjects mobilize around the idea of the state, which in turn leads to articulations and practices conducive to both self-censorship and a contingent space of activism. Viewed as such, the idea of uncertainty becomes an enabler through which certain kinds of practices, relationships, and networks are made possible and enacted, and through which a sociopolitical realm of intimacy is constituted by and constitutive of these relationships, networks, and practices. Situated in the domain of uncertainty, this study examines the ways in which uncertainty, both as an analytical idea and an ontological existence, produces an intimate space where labor activists not only effectively self-censor but also skillfully map the gray zone between the relatively safe and the unacceptably risky choices.