Wind energy forecasting can facilitate wind energy integration into a power system. In particular, the management of power system security would benefit from forecast information on plausible large, rapid change in wind power generation. Numerical Weather Prediction (NWP) systems are presently the best available tools for wind energy forecasting for projection times between 3 and 48 hours. In this thesis, the types of weather phenomena that cause large, rapid changes in wind power in southeast Australia are classified using observations from three wind farms. The results show that the majority of events are due to horizontal propagation of spatial weather features. A study of NWP systems reveals that they are generally good at forecasting the broad large-scale weather phenomena but may misplace their location relative to the physical world. Errors may result from developing single time-series forecasts from a single NWP grid point, or from a single interpolation of proximate grid points. This thesis presents a new approach that displays NWP wind forecast information from a field of multiple grid points around the wind farm location. Displaying the NWP wind speeds at the multiple grid points directly would potentially be misleading as they each reflect the estimated local surface roughness and terrain at a particular grid point. Thus, a methodology was developed to convert the NWP wind speeds at the multiple grid points to values that reflect surface conditions at the wind farm site. The conversion method is evaluated with encouraging results by visual inspection and by comparing with an NWP ensemble. The multiple grid point information can also be used to improve downscaling results by filtering out data where there is a large chance of a discrepancy between an NWP time-series forecast and observations. The converted wind speeds at multiple grid points can be downscaled to site-equivalent wind speeds and transformed to wind farm power assuming unconstrained wind farm operation at one or more wind farm sites. This provides a visual decision support tool that can help a forecast user assess the possibility of large, rapid changes in wind power from one or more wind farms.

P.A.Samuelson 於1954年發表了 " The Pure Theory of Public Expenditure " 一文，為純粹公共財之最適提供條件（ΣMRS＝MRT）做了一個最佳的註解，成為後人討論純粹公共財理論時之比較基礎。然而公共支出與公共收入為一體之兩面，租稅融通方式之不同將影響公共支出之水準。而 A.C. Pigou於1947年就曾提出租稅融通方式之不同，將影響公共支出之水準。亦即當政府採用扭曲性租稅來融通公共財之提供時，將造成效率上之損失，此時應將此社會成本列入為公共財提供之成本，進而修正了公共財提供之最適條件。 而本篇論文之目的，即在討論當不確定之下，最適公共財提供條件之修正，並加入了人力資本（Human Capital）之探討，分析修正項目對最適公共支出水準之影響，嘗試得出不確定因素影響公共收入面時，與公共支出間之關係，以期能做為公共決策時之考量。 本文以Eaton & Rosen (1980a)不確定工資下最適課稅的模型作為分析之基礎，並加入公共財之提供，分別以不確定工資稅、定額稅、以及不確定利息所得稅來融通公財之提供，可分別得出修正後公共財之最適提供條件。其中在不確定性之下，以定額稅來融通公共財，並不會產生社會成本，故根據所得出之公共財提供之最適條件，政府利用定額稅來融通公共支出時，只須考慮公共財提供之直接成本。但若分別以不確定工資稅及利息所得稅來融通公共財之提供時，由於其最適提供條件所產生出之修正項目，將影響其公共財之最適提供水準。故我們將分別在確定性及不確定之下分析其修正項目，並探討這些修正項目將如何影響公共財之提供水準。 結論是在確定性之下，課稅使得第二期之休閒減少，即課稅使得第二期之勞動供給增加，用以融通公共財之稅收增加，減輕了公共財融通之負擔。故其社會成本將小於直接成本，公共財提供之最適水準可以提供較多。在加入公共財時反而使得勞動供給增加時，此時之扭曲效果為負，與Pigou認為課稅之造成之扭曲效果應使公共財之最適提供水準較低之傳統理論恰好相反。公共財與所得（私有財）之間為互補之關係，則公共財之提供將使休閒增加，即勞動供給將減少，進一步使得稅收減少，以稅收來融通公共財之成本將因此增加，故社會成本大於直接成本，公共財提供之最適水準應較低；反之公共財與所得（私有財）之間為替代之關係，則公共財提供將使休閒減少，則勞動供給增加，融通公共財之成本減少，公共財供之最適水準可以較高。 但在不確定性之下，不僅會發生上述之結果，亦須考慮稅率對人力資本之影響，消費者意識到公共財之融通必須以人力資本投資之增加為代價，以及不確定性實現之程度而定。在風險趨避程度為固定，且第一期之非勞動所得大於第一期之消費時（即不工作仍有由儲蓄時），課稅將使人力資本投資增加，但仍須配合不確定性實現之程度而定。在當不確定性之程度大於其平均值時，由於消費者之風險趨避程度為固定，消費者較不能忍受風險太大之情況，將造成消費者額外之成本，公共財提供之社會成本大於直接成本，公共財可提供較少。當不確定性之程度小於其平均值時，公共財提供之社會成本小於直接成本，公共財可提供較多。

The rapid advance in information and communication technologies has effectively facilitated the development and implementation of information systems (IS) projects in modern organizations for reorganizing their business processes and streamlining the provision of their products and services in today's dynamic environment. Such a development brings organizations with numerous benefits including increased automation of business processes, improved customer service, and timely provision of effective decision support. As a result, evaluating and selecting the most appropriate IS project for development and implementation from a pool of available IS projects becomes a critical decision to make in modern organizations. Evaluating and selecting appropriate IS projects for development in an organization, however, is complex and challenging. The complexity of the evaluation and selection process is due to the multi-dimensional nature of the decision making process, the conflicting nature of the multiple selection criteria, and the presence of subjectiveness and imprecision of the human decision making process. The challenging of the evaluation and selection comes from the need for making transparent and balanced decisions based on a comprehensive evaluation of all available IS projects in a timely manner. Much research has been done on the development of various approaches for evaluating and selecting IS projects, and numerous applications of those approaches for addressing real world IS project evaluation and selection problems have been reported in the literature. In general, existing approaches can be classified into (a) cost-benefit analysis based approaches, (b) utility based approaches, and (c) optimization oriented approaches. These approaches, however, are not totally satisfactory due to various shortcomings including (a) the inability to tackle the subjectiveness and imprecision of the selection process, (b) the failure to adequately handle the multi-dimensional nature of the problem, and (c) cognitively very demanding on the decision maker. To address these issues above, this research has developed three novel approaches for effectively solving the IS project evaluation and selection problem under uncertainty in an organization. The first approach is developed for helping the decision maker better model the subjectiveness and imprecision inherent in the decision-making process with the use of linguistic variables approximated by fuzzy numbers. The second approach is designed to reduce the cognitive demanding on the decision maker in the IS project evaluation and selection process with the introduction of fuzzy pairwise comparison. The third approach is formulated with respect to the use of intelligent decision support systems for facilitating the use of specific multi-criteria analysis approaches in relation to individual IS project evaluation and selection situations. The developed approaches have been applied for solving three IS project evaluation and selection problems in the real world settings. The results show that the three developed ap proaches are of practical significance for effectively and efficiently solving the IS project evaluation and selection problem due to (a) the simplicity and comprehensibility of the underlying concept, (b) the adequate handling of inherent uncertainty and imprecision, and (c) the ability to help the decision maker better understand the IS project selection problem and the implications of their decision behaviours.

<p>The International Atomic Energy Agency (IAEA) and the World Health Organisation (WHO) operate the IAEA/WHO TLD postal dose audit programme. The purpose of the programme is to verify the beam calibration in radiotherapy centres in developing countries and to check the Secondary Standards Dosimetry Laboratories (SSDLs). Thermoluminescence dosimeters (TLDs) are used as transfer dosimeters and the evaluation of these are done at the IAEA Dosimetry Laboratory. In the present work the uncertainties in the process of dose determination from TLD readings have been evaluated.</p><p>The analysis comprises the TLD reading reproducibility, uncertainties in the calibration coefficient, and uncertainties in factors correcting for fading of TL signal, influence of TLD holder, energy response and dose response non-linearity. The individual uncertainties were combined to estimate the total uncertainty in the evaluated dose from TLD readings. Experimental data from 2001-2005 were used in the analysis.</p><p>The total uncertainty has been estimated to be 1.2 % for irradiations with 60Co -rays and 1.6 % for irradiations with high-energy X-rays. Results from irradiations by the Bureau International des Poids et Mesures (BIPM), Primary Standard Dosimetry Laboratories (PSDLs), Secondary Standard Dosimetry Laboratories (SSDLs) and reference centres compare favourably with the estimated uncertainties.</p><p>The largest uncertainty components are in the energy correction factor (for high-energy X-rays) with a value of 1.1 % and in the dose response non-linearity correction factor with a value of 0.9 %.</p><p>It has been shown that the acceptance limits of 5 % for TLD results of hospitals and 3.5 % for SSDLs are justified when related to the uncertainties in the dose calculations and the uncertainty in the determination of absorbed dose to water at the centre, as discussed in IAEA TRS-398 (IAEA, 2000), provided that it is followed.</p>

<p>Introduction: The world is changing rapidly and the uncertainty that characterizes today´s society makes companies preparations for the future crucial. </p><p>Purpose: To examine how CEO:s in small companies look at the future and what kind of preparations they make in order to meet it. Hereby, our ambition is to find out whether there is a difference between companies working in industries characterized by different degrees of stability. </p><p>Mode of procedure: The purpose of this thesis has been fulfilled by interviews with four CEO:s from industries characterized by different degrees of stability. </p><p>Result: The companies working in relatively unstable environments tended to be relatively more flexible and have an emergent strategy formation process, whereas companies working in relatively stable environments displayed relatively less flexibility and tended to have a planning strategy formation process.</p>

<p>Companies<strong> </strong>that seek to venture into providing services in addition to providing products have many business issues to consider as there are many differences between providing service and product offerings.  One factor that needs to be considered in service offerings is the aspect of time, as services are offered for an extended period of time, creating a unique type of relationship between the customer and the service provider.  With product offerings, the point of sale is usually the end of the product provider and customer relationship.  The added time aspect in the service offering brings with it the issues of uncertainty as service contracts are made for a certain period of time in the future, where things are unknown.</p><p> </p><p>This thesis looked at types of uncertainties important to service offerings, especially in the manufacturing industry.  The uncertainties have an impact on how service offering contracts are constructed, as they can affect the profit and costs of the service provider. The three types of uncertainties that were examined were product malfunction uncertainty, service delivery uncertainty, and customer requirement uncertainty. Using these three types of uncertainty, mathematical models were constructed to represent the cost and revenue of different contract types. The different contract types were identified through a case study with a product manufacturer in Sweden.  Different probability distributions were selected to model the three types of uncertainty based on a literature review.  The mathematical models were then used to construct a software program, the uncertainty simulator tool, which service contract designers can use to model how uncertainties affect cost and revenue in their contracts.</p>

<p>In Black-Scholes model, the parameters -a volatility and an interest rate were assumed as constants. In this thesis we concentrate on behaviour of the volatility as</p><p>a function and we find more realistic models for the volatility, which elimate a risk</p><p>connected with behaviour of the volatility of an underlying asset. That is</p><p>the reason why we will study the Uncertain Volatility Model. In Chapter</p><p>1 we will make some theoretical introduction to the Uncertain Volatility Model</p><p>introduced by Avellaneda, Levy and Paras and study how it behaves in the different scenarios. In</p><p>Chapter 2 we choose one of the scenarios. We also introduce the BSB equation</p><p>and try to make some modification to narrow the uncertainty bands using</p><p>the idea of a static hedging. In Chapter 3 we try to construct the proper</p><p>portfolio for the static hedging and compare the theoretical results with the real</p><p>market data from the Stockholm Stock Exchange.</p>

<p>Uncertainty is a well-known phenomenon that is recurring in biographies, imaginative literature and science, but is less studied in nursing science. The aim of this participatory action research project was to, in collaboration with nursing students; explore nursing activities for relieving patients’ uncertainty. A qualitative approach was chosen with focus groups and the text was content analyzed. The students studied their third semester on a nursing program. The findings showed two different kinds of uncertainty, existential uncertainty and care evoked uncertainty. Relieving uncertainty showed to be a process in three steps. The first step is to reach deeper understanding of what uncertainty is and how it affects patients. The second step is to develop sensibility for how to discover uncertainty and the third step is to use uncertainty relieving strategies. To do this requires courage and a wish to share power with the patient. The strategies for relieving existential and care evoked uncertainty differed.</p>

<p>Mining activities will eventually deplete any deposit. In a sustainability perspective, the deposit should therefore be utilised optimally during production. A prerequisite to achieve this is the deliberate and consistent utilisation of the variations in the deposit.</p><p>In an ideal world everything is certain. In the real world nothing is certain. In the real world everything is more or less probable.</p><p>Therefore, the question asked is how an underground iron ore mining company like Rana Gruber AS can benefit from knowing and exploiting the uncertainty and variability of decisive ore parameters. The perspective is the value chain from in-situ ore to product, whereas the focus is on deposit characterisation and production.</p><p>In order to answer this question the existing database with geodata from the Kvannevann Iron Ore is reviewed and estimation techniques based on kriging and geostatistical simulation algorithms (Turning Band) are implemented to identify and assess the ore deposit uncertainties and variations and associated risks. Emphasise is on total iron in the ore (FeTot), total iron in the ore originating from magnetite (FeMagn), manganese oxide (MnO) and joint parameters. Due to insufficient number of assays of MnO, a geochemical MnO-signature is developed using cluster analysis. This geochemical signature is applied as input in the kriging with inequalities procedure. This procedure is based on soft data (lithologies) and a conditional expectation of the MnO level in the different lithologies.</p><p>A cut-off based on both hematite and magnetite is estimated. A process analysis is performed to visualise the working processes, related inputs, outputs and controlling-, supporting- and risk elements. The process analysis is based on the IDEF process modelling methodology. Given the identified deposit uncertainties and variations, systems to evaluate potential mining stope performance are developed and implemented for one of the mining stopes. To test the possibility to decrease the ore-related uncertainty, a method for collection of drill cuttings has been developed and tested. The correlation between magnetic susceptibility and FeMagn and the correlation between ore density and FeTot are both investigated.</p><p>The results show that an illustrative and useful overview can be won by using the IDEF-based process modelling methodology. A non-linear relationship between density and FeTot is established and it is shown that the density can be used as a FeTot indicator. This relationship is also used in the reserve and resource estimation. As expected a positive correlation between FeMagn and magnetic susceptibility measured on cores could be established. However, the deviation from other reported relationships is considerable. The importance of magnetite is emphasised and quantified by the cut-off estimation. The cluster analysis reveals that the MnO levels in the different lithologies are significantly different. This result is implemented into the kriging with inequalities procedure and immediate effects can be observed.</p><p>The development of the geodata collector and the collection of drill cuttings show that it is possible to obtain precise analysis of collected drill cutting material. Although high- and low assay values have been correlated with geological observation in the mine, the accuracy has been difficult to assess.</p><p>The estimation and the simulation of the ore properties illustrate and quantify the uncertainties and variations in the ore deposit well. The structural analysis performed prior to the estimation and the simulation reveals anisotropies for all ore decisive parameters. The quantification of ore variations provides a useful input into the a-priori assessment of stope performance. It is also shown that the probability that a SMU is above or below some cut-off value can be assessed using the simulation results and the systems developed in standard software.</p><p>It is concluded that the process analysis approach offers valuable input to gain an overview of the mining value chain. It is also an approach that constitutes an important step in the identification and assessment of IT-requirements, bottlenecks, input- and output requirements and role- and skill requirements along the value chain. However, the process analysis approach requires sufficient organisational resources, which also is the case regarding the implementation of the grade- and stability issues that are presented. Further it is concluded that the ore variations can be utilised to some extent by using standard software.</p><p>The ore in question is a Neoproterozoic (600 to 700 Ma) metasedimentary magnetite-hematite ore deposited under shallow marine conditions. Primary precipitate was probably ferric hydroxide.</p><p>Applied methods have been chosen to handle the uncertainty along the value chain of Rana Gruber AS. Every aspect of these methods may therefore not be directly applicable to other mining operations. However, the general aspects have a broad area of use.</p>

This dissertation investigates the problem of uncertainty in complex ecological models. The term "complex" is used to convey both the common and scientific meanings. Increasingly, ecological models have become complex because they are more complicated; ecological models are generally multi-variate and multi-leveled in structure. Many ecological models are complex because they simulate the dynamics of complex systems. As a result, and as science moves from the modern/normal to postmodern/post-normal paradigm view of the world, the definition of uncertainty and the problem of uncertainty estimation in models tread the lines between the technical and the philosophical. With this in mind, I have chosen to examine uncertainty from several perspectives and under the premise that the needs and goals of uncertainty estimation, like ecological models themselves, are evolving. Each chapter represents a specific treatment of uncertainty and introduces new methodologies to evaluate the nature, source, and significance of model uncertainty. In the second chapter, 'Determining the significance of threshold values uncertainty in rule-based classification models', I present a sensitivity analysis methodology to determine the significance of uncertainty in spatially-explicit rule-based classification models. In the third chapter, 'Process level sensitivity analysis for complex ecological models', I present a sensitivity analysis methodology at the process level, to determine the sensitivity of a model to variations in the processes it describes. In the fourth chapter, 'A Component Based Approach for the Development of Ecological Simulations', investigate how the process of developing an ecological simulation can be advanced by using component-based simulation frameworks. I conclude with reflection on the future of modeling and studies of uncertainty. / Graduation date: 2003