This study investigates on the planimetric (x, y) positional accuracy of the National Shoreline (NSL) data, produced in collaboration between the Swedish mapping agency Lantmäteriet and the Swedish Maritime Administration (SMA). Due to the compound nature of shorelines, such data is afflicted by substantial positional uncertainties. In contrast, the positional accuracy requirements of NSL data are high. An apparent problem is that Lantmäteriet do not measure the positional accuracy of NSL in accordance to the NSL data product specification. In addition, currently, there is little understanding of the latent positional changes of shorelines affected by the component of time, in direct influence of the accuracy of NSL. Therefore, in accordance to the two specific aims of this study, first, an accuracy assessment technique is applied so that to measure the positional accuracy of NSL. Second, positional time changes of NSL are analysed. This study provides with an overview of potential problems and future prospects of NSL, which can be used by Lantmäteriet to improve the quality assurance of the data. Two line-based NSL data sets within the NSL classified regions of Sweden are selected. Positional uncertainties of the selected NSL areas are investigated using two distinctive methodologies. First, an accuracy assessment method is applied and accuracy metrics by the root-means-square error (RMSE) are derived. The accuracy metrics are checked toward specification and standard accuracy tolerances. Results of the assessment by the calculated RMSE metrics in comparison to tolerances indicate on an approved accuracy of tested data. Second, positional changes of NSL data are measured using a proposed space-time analysis technique. The results of the analysis reveal significant discrepancies between the two areas investigated, indicating that one of the test areas are influenced by much greater positional changes over time. The accuracy assessment method used in this study has a number of apparent constraints. One manifested restriction is the potential presence of bias in the derived accuracy metrics. In mind of current restrictions, the method to be preferred in assessment of the positional accuracy of NSL is a visual inspection towards aerial photographs. In regard of the result of the space-time analysis, one important conclusion can be made. Time-dependent positional discrepancies between the two areas investigated, indicate that Swedish coastlines are affected by divergent degrees of positional changes over time. Therefore, Lantmäteriet should consider updating NSL data at different time phases dependent on the prevailing regional changes so that to assure the currently specified positional accuracy of the entire data structure of NSL.

Submitted in fulfilment of the requirements of the Degree Doctor of Technology: Quality, Durban University of Technology. 2014. / The South African automotive sector is often plagued with complex and competitive business challenges owing to globalisation, economic uncertainty and fluctuating market demands. These challenges prompt business leaders in South Africa to improve their operations and to enhance innovations in processes, products and services in a very reactive manner. Literature shows that one such initiative that can assist the automotive sector to compete with the rest of the world where productivity, quality and operational costs reduction are crucial for economic success is the adoption of the integrated Lean Six Sigma tool. The automotive sector, which purports to be at the forefront of best industry manufacturing practices in South Africa, is certainly lacking in this area. The purpose of this thesis was to assess Lean and Six Sigma techniques as standalone systems, the integration of Lean and Six Sigma as a unified approach to continuous improvement and to develop a proposed Lean Six Sigma framework for the automotive component manufacturing organisations in KwaZulu-Natal (KZN), South Africa. Due to the nature and complexity of this project, it was decided to adopt the action-based research strategy and include both qualitative and quantitative techniques. Two hypotheses were formulated to guide the research. The study was confined to the greater Durban region in KZN, which formed the target population of forty two organisations within the Durban Automotive Cluster (DAC). A survey questionnaire was designed in measurable format to gather practical information from the sample organisations on the status of their existing business improvement programs and quality practices. This information was necessary to critique the sample organisations for Lean and Six Sigma requirements and compare it to the literature in terms of the KZN context. A pilot study was conducted with senior management at five automotive manufacturing organisations to determine if the participants encountered any problems in answering the questionnaire and if the methodology adopted would meet the objectives of this project. The results of the pilot study indicated high reliability scores which were sustainable for the main study. The survey questionnaire was reviewed by Lean and Six Sigma Experts, Academics and members of the DAC executive team to ensure the validity of the questionnaire to the KZN context. The logistics of the main study followed a similar format as the pilot study and the questionnaires were distributed within the DAC over a three month period. A census sample was used in the field study to collect primary data. A response rate of 75% was achieved. The results of the empirical findings revealed that the sample organisations had a very low success rate of Lean and Six Sigma adoption as standalone systems. The sample organisations only practiced certain Lean and Six Sigma tools and techniques as they found it difficult to maintain the complete transition from theory to practice. The synergies that emerged from the study of Lean and Six Sigma that affect manufacturing performance suggested that they complemented and supported each other by tailoring the deficiencies to the given environment. This information was translated into practical considerations for constructing the proposed Lean Six Sigma framework from a KZN perspective. The conclusion of the main study was that if an organisation wants improvement to happen on an ongoing basis, it needs to recognise that there are significant interactions between their management system and the improvement technique. When the organisations understand the characteristics of the environment in which they operate, they will be able to configure appropriate follow up processes to sustain their management systems. The study demonstrated that Lean Six Sigma integration repackages the stronger focus areas of Lean and Six Sigma to create its own unique approach on improving an organisation’s performance. It is anticipated that organisations which implement the proposed Lean Six Sigma framework could contribute significantly to the growth of the South African economy in terms of increased productivity, improved international competition and job creation. The value of this research is that the proposed Lean Six Sigma framework affords the KZN automotive sector a unique opportunity to create its own brand of quality that compliments its management style and industry demands. Future research should focus on testing the applicability of the proposed Lean Six Sigma framework in a real case scenario to ensure that the critical outcomes are adequately ingrained to achieve perceived organisational performance. Lastly, it is recommended that a list of performance evaluators is developed and follow up procedures to monitor the progress of the Lean Six Sigma technique is implemented.

There are two main defined classes of uncertainty namely: fuzziness and ambiguity, where ambiguity is ‘one-to-many’ relationship between syntax and semantic of a proposition. This definition seems that it ignores ‘many-to-many’ relationship ambiguity type of uncertainty. In this thesis, we shall use complex-uncertainty to term many-to-many relationship ambiguity type of uncertainty. This research proposes a new approach for handling the complex ambiguity type of uncertainty that may exist in data, for software engineering of predictive Data Mining (DM) classification models. The proposed approach is based on Relative-Fuzzy Logic (RFL), a novel type of fuzzy logic. RFL defines a new formulation of the problem of ambiguity type of uncertainty in terms of States Of Proposition (SOP). RFL describes its membership (semantic) value by using the new definition of Domain of Proposition (DOP), which is based on the relativity principle as defined by possible-worlds logic. To achieve the goal of proposing RFL, a question is needed to be answered, which is: how these two approaches; i.e. fuzzy logic and possible-world, can be mixed to produce a new membership value set (and later logic) that able to handle fuzziness and multiple viewpoints at the same time? Achieving such goal comes via providing possible world logic the ability to quantifying multiple viewpoints and also model fuzziness in each of these multiple viewpoints and expressing that in a new set of membership value. Furthermore, a new architecture of Hierarchical Neural Network (HNN) called ML/RFL-Based Net has been developed in this research, along with a new learning algorithm and new recalling algorithm. The architecture, learning algorithm and recalling algorithm of ML/RFL-Based Net follow the principles of RFL. This new type of HNN is considered to be a RFL computation machine. The ability of the Relative Fuzzy-based DM prediction model to tackle the problem of complex ambiguity type of uncertainty has been tested. Special-purpose Integrated Development Environment (IDE) software, which generates a DM prediction model for speech recognition, has been developed in this research too, which is called RFL4ASR. This special purpose IDE is an extension of the definition of the traditional IDE. Using multiple sets of TIMIT speech data, the prediction model of type ML/RFL-Based Net has classification accuracy of 69.2308%. This accuracy is higher than the best achievements of WEKA data mining machines given the same speech data.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / This presentation summarizes a study characterizing strain gages and pressure transducers used to measure the fluid pressure within aircraft hydraulic lines. A series of laboratory calibrations and finite element analyses was performed to demonstrate the quality of data from both pressure transducers and strain gages under variations in both temperature and external strains on the hydraulic lines. Strain gages showed a marked susceptibility to external strains on hydraulic lines, and wide variations in susceptibility to temperature changes. Pressure transducers were found to be relatively immune to both conditions. It is recommended that strain gages be used for trend data only.

The study of expected utility maximization in continuous-time stochastic market models dates back to the seminal work of Merton 1969 and has since been central to the area of Mathematical Finance. The associated stochastic optimization problems have been extensively studied. The problem formulation relies on two strong underlying assumptions: the ability to specify the underpinning market model and the knowledge of the investor's risk preferences. However, neither of these inputs is easily available, if at all. Resulting issues have attracted continuous attention and prompted very active and diverse lines of research. This thesis seeks to contribute towards this literature and questions related to both of the above issues are studied. Specifically, we study the implications of certain qualitative properties of the utility function; we introduce, and study various aspects of, the notion of robust forward investment criteria; and we study the investment problem associated with risk- and ambiguity-averse preference criteria defined in terms of quasiconcave utility functionals.

Uncertainty is inherent in many real-world settings; for example, in a combat situation, darkness may prevent a soldier from classifying approaching troops as friendly or hostile. In an environment plagued with uncertainty, decision-support systems, such as sensor-based networks, may make faulty assumptions about field conditions, especially when information is incomplete, or sensor operations are disrupted. Displaying the factors that contribute to uncertainty informs the decision-making process for a human operator, but at the expense of limited cognitive resources, such as attention, memory, and workload. This research applied principles of perceptual cognition to human-computer interface design to introduce uncertainty visualizations in an adaptive approach that improved the operator's decision-making process, without unduly burdening the operator's cognitive load. An adaptive approach to uncertainty visualization considers the cognitive burden of all visualizations, and reduces the visualizations according to relevancy as the user's cognitive load increases. Experiments were performed using 24 volunteer participants using a simulated environment that featured both intrinsic load, and characteristics of uncertainty. The experiments conclusively demonstrated that adaptive uncertainty visualization reduced the cognitive burden on the operator's attention, memory, and workload, resulting in increased accuracy rates, faster response times, and a higher degree of user satisfaction. This research adds to the body of knowledge regarding the use of uncertainty visualization in the context of cognitive load. Existing research has not identified techniques to support uncertainty visualization, without further burdening cognitive load. This research identified principles, such as goal-oriented visualization, and salience, which promote the use of uncertainty visualization for improved decision-making without increasing cognitive load. This research has extensive significance in fields where both uncertainty and cognitive load factors can reduce the effectiveness of decision-makers, such as sensor-based systems used in the military, or in first-responder situations.

Agriculture has been reported to contribute a significant amount of greenhouse gases to the atmosphere among other anthropogenic activities. With still more than 870 million people in the world suffering from under-nutrition and a growing global food demand, it is relevant to study ways for mitigating the environmental impact of food production. The objective of this work was to identify gaps in the knowledge regarding the main factors affecting greenhouse gas (GHG) emissions from beef farming systems, to reduce the uncertainty on carbon footprint predictions, and to study the relative importance of mitigation options at the system level. A lack of information in the literature was identified regarding the quantification of the relevant animal characteristics of extensive beef systems that can impact on methane (CH4) outputs. In a meta-analysis study, it was observed that the combination of physiological stage and type of diet improved the accuracy of CH4 emission rate predictions. Furthermore, when applied to a system analysis, improved equations to predict CH4 from ruminants under different physiological stages and diet types reduced the uncertainty of whole-farm enteric CH4 predictions by up to 7% over a year. In a modelling study, it was demonstrated that variations in grazing behaviour and grazing choice have a potentially large impact upon CH4 emissions, which are not normally mentioned within carbon budget calculations at either local or national scale. Methane estimations were highly sensitive to changes in quality of the diet, highlighting the importance of considering animal selectivity on carbon budgets of heterogeneous grasslands. Part of the difficulties on collecting reliable information from grazing cattle is due to some limitations of available techniques to perform CH4 emission measurements. Thus, the potential use of a Laser Methane Detector (LMD) for remote sensing of CH4 emissions from ruminants was evaluated. A data analysis method was developed for the LMD outputs. The use of a novel technique to assess CH4 production from ruminants showed very good correlations with independent measurements in respiration chambers. Moreover, the use of this highly sensitive technique demonstrates that there is more variability associated with the pattern of CH4 emissions which cannot be explained by the feed nutritional value. Lastly, previous findings were included in a deterministic model to simulate alternative management options applied to upland beef farming systems. The success of the suggested management technologies to mitigate GHG emissions depends on the characteristics of the farms and management previously adopted. Systems with high proportion of their land unsuitable for cropping but with an efficient use of land had low and more certain GHG emissions, high human-edible returns, and small opportunities to further reduce their carbon footprint per unit of product without affecting food production, potential biodiversity conservation and the livelihood of the region. Altogether, this work helps to reduce the uncertainty of GHG predictions from beef farming systems and highlights the essential role of studies with a holistic approach to issues related to climate change that encompass the analysis of a large range of situations and management alternatives.

In this thesis a method for verification, validation and uncertainty quantification (VV&UQ) has been tested and evaluated on a fuel transfer application in the fuel rig currently used at Saab. A simplified model has been developed for the limited part of the fuel system in the rig that is affected in the transfer, and VV&UQ has been performed on this model. The scope for the thesis has been to investigate if and how simulation models can be used for certification of the fuel system in a fighter aircraft. The VV&UQ-analysis was performed with the limitation that no probability distributions for uncertainties were considered. Instead, all uncertainties were described using intervals (so called epistemic uncertainties). Simulations were performed on five different operating points in terms of fuel flow to the engine with five different initial conditions for each, resulting in 25 different operating modes. For each of the 25 cases, the VV&UQ resulted in a minimum and maximum limit for how much fuel that could be transferred. 6 cases were chosen for validation measurements and the resulting amount of fuel transferred ended up between the corresponding epistemic intervals. Performing VV&UQ is a time demanding and computationally heavy task, which quickly grows as the model becomes more complex. Our conclusion is that a pilot study is necessary, where time and costs are evaluated, before choosing to use a simulation model and perform VV&UQ for certification. Further investigation of different methods for increasing confidence in simulation models is also needed, for which VV&UQ is one suitable option.

This thesis investigates how A-level students (aged 17-26) in and around Kampala, Uganda, manage uncertainties in their present lives and futures. There are large discrepancies between international and national discourses on education, the students’ ambitious hopes and dreams, and the realities they witness. The research’s main source of data are 63 semi-structured interviews with high school students of various socio-economic backgrounds in four different schools. The thesis provides an analysis of the tactical agency the students display while negotiating with discourses, networks and steep competition. The main argument of the thesis is that uncertainty can be a productive force, and tactical agency necessary to navigate an African urban space at present.

The shear strength of the concrete-rock interface is an important parameter in sliding stability analyses of concrete dams founded on rock and depends, in addition to the normal stress state, on the bonding conditions of the interface; concrete-rock interfaces can be either unbonded, partially bonded or fully bonded. In the Swedish guidelines for dam safety all dam-foundation contacts are treated as unbonded. This has the benefit of eliminating all uncertainties related to the cohesive strength of bonded contacts but it might also lead to unnecessary strengthening of dams. Other national guidelines deal with the uncertainties related to cohesion by applying higher safety factors, mainly determined based on previous experience, when both cohesion and friction are taken into account. The main objective of this project is to study if and how cohesion can be included when evaluating the shear strength of bonded or partially bonded interfaces. To accomplish this, uncertainties associated with cohesion are identified and their influence on the assessed stability is investigated. The results show that the influence on the assessed sliding stability is strongly dependent on the magnitude of the involved uncertainties that might vary significantly for different dams. It is thus questionable if one safety factor applicable for all dams can be established for use in deterministic analyses. Taking into account cohesion when reliability methods are used is somewhat less complicated because of the possibility of directly incorporating the uncertainties in the analysis. The main challenge in such cases is the quantification of the involved uncertainties due to lack of proper data and, in some cases, knowledge. In this thesis, a framework for quantification of parameter uncertainty is suggested and the model error due to brittle failure in combination with spatial variation in cohesion is analysed. Areas that require more research to further refine the analysis are also identified. / Skjuvhållfastheten i betong-berggränssnittet är en avgörande faktor vid glidstabilitetsutvärderingar av befintliga betongdammar grundlagda på berg och beror dels på normalspänningsfördelningen och dels på kontaktytans status med avseende på vidhäftning, vilken kan delas in i tre separata fall; då vidhäftning existerar och kohesion medräknas (intakt), då vidhäftning aldrig funnits eller förlorats (bruten), samt en kombination av föregående (delvis intakt). I RIDAS, de svenska riktlinjerna för dammsäkerhet, behandlas alla berg-betonggränssnitt som brutna. Detta förhållningssätt har fördelen att det utelämnar all osäkerhet förknippad med intakta kontaktytors kohesion men det kan också resultera i icke nödvändiga förstärkningar av dammar. I andra nationella riktlinjer för dammsäkerhet beaktas osäkerheterna förknippade med kohesion genom att högre säkerhetsfaktorer, i huvudsak bestämda baserat på erfarenhet, tillämpas då både kohesion och friktion används vid beräkning av kontaktytans skjuvhållfasthet. Det övergripande syftet med detta doktorandprojekt är att studera om och hur kohesion kan medräknas vid stabilitetsutvärderingar av befintliga betongdammar med helt eller delvis intakta betong-berggränssnitt. För att uppnå detta, identifieras osäkerheter förknippande med kohesionen och deras inverkan på den bedömda glidstabiliteten utvärderas. Resultaten från projektet visar att osäkerheternas inverkan på den uppskattade glidstabiliteten är starkt beroende av osäkerheternas storlek, vilken varierar för olika dammar. Det är således tveksamt om en säkerhetsfaktor giltig för alla dammar kan bestämmas för användning i deterministiska stabilitetsanalyser. När sannolikhetsbaserade metoder används kan osäkerheterna införlivas direkt i analysen. Kvantifieringen av osäkerheterna förknippade med ett specifikt fall utgör då den huvudsakliga utmaningen. I denna avhandling presenteras ett ramverk för att uppskatta de statistiska parametrarna hos de ingående variablerna. Dessutom studeras modellosäkerheten förknippad med intakta gränssnitts spröda brott i kombination med kohesionens rumsliga variation i detalj. Områden som fordrar ytterligare forskning i syfte att förbättra analysen identifieras också. / <p>QC 20160411</p>