Search for dissertations about: "kvalitetskontroll"
Showing result 1 - 5 of 21 swedish dissertations containing the word kvalitetskontroll.
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1. Observational Uncertainties in Water-Resources Modelling in Central America : Methods for Uncertainty Estimation and Model Evaluation
Abstract : Knowledge about spatial and temporal variability of hydrological processes is central for sustainable water-resources management, and such knowledge is created from observational data. Hydrologic models are necessary for prediction for time periods and areas lacking data, but are affected by observational uncertainties. READ MORE
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2. The existence of logistics quality deficiencies and the impact of information quality in the dyadic order fulfillment process
Abstract : Measuring logistics quality is related to meeting customer expectations and needs, regardless of what those may be. Both over- and under-performance of logistics quality were found in previous studies. Diverging perceptions of logistics performance between customer and supplier were also fo.und in previous studies. READ MORE
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3. Disinformative and Uncertain Data in Global Hydrology : Challenges for Modelling and Regionalisation
Abstract : Water is essential for human well-being and healthy ecosystems, but population growth and changes in climate and land-use are putting increased stress on water resources in many regions. To ensure water security, knowledge about the spatiotemporal distribution of these resources is of great importance. READ MORE
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4. Data-driven quality management using explainable machine learning and adaptive control limits
Abstract : In industrial applications, the objective of statistical quality management is to achieve quality guarantees through the efficient and effective application of statistical methods. Historically, quality management has been characterized by a systematic monitoring of critical quality characteristics, accompanied by manual and experience-based root cause analysis in case of an observed decline in quality. READ MORE
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5. Improving diagnosis of acute coronary syndromes in an emergency setting: A machine learning approach
Abstract : Acute coronary syndrome (ACS) is the biggest people killer in the western world today. Despite well trained physicians and reliable diagnostic tools, diagnosing ACS early in the emergency departments (ED) remains a challenge. READ MORE