18 resultados para Small-error approximation

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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The purpose of this bachelor's thesis was to chart scientific research articles to present contributing factors to medication errors done by nurses in a hospital setting, and introduce methods to prevent medication errors. Additionally, international and Finnish research was combined and findings were reflected in relation to the Finnish health care system. Literature review was conducted out of 23 scientific articles. Data was searched systematically from CINAHL, MEDIC and MEDLINE databases, and also manually. Literature was analysed and the findings combined using inductive content analysis. Findings revealed that both organisational and individual factors contributed to medication errors. High workload, communication breakdowns, unsuitable working environment, distractions and interruptions, and similar medication products were identified as organisational factors. Individual factors included nurses' inability to follow protocol, inadequate knowledge of medications and personal qualities of the nurse. Developing and improving the physical environment, error reporting, and medication management protocols were emphasised as methods to prevent medication errors. Investing to the staff's competence and well-being was also identified as a prevention method. The number of Finnish articles was small, and therefore the applicability of the findings to Finland is difficult to assess. However, the findings seem to fit to the Finnish health care system relatively well. Further research is needed to identify those factors that contribute to medication errors in Finland. This is a necessity for the development of methods to prevent medication errors that fit in to the Finnish health care system.

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The goal of this thesis is to implement software for creating 3D models from point clouds. Point clouds are acquired with stereo cameras, monocular systems or laser scanners. The created 3D models are triangular models or NURBS (Non-Uniform Rational B-Splines) models. Triangular models are constructed from selected areas from the point clouds and resulted triangular models are translated into a set of quads. The quads are further translated into an estimated grid structure and used for NURBS surface approximation. Finally, we have a set of NURBS surfaces which represent the whole model. The problem wasn’t so easy to solve. The selected triangular surface reconstruction algorithm did not deal well with noise in point clouds. To handle this problem, a clustering method is introduced for simplificating the model and removing noise. As we had better results with the smaller point clouds produced by clustering, we used points in clusters to better estimate the grids for NURBS models. The overall results were good when the point cloud did not have much noise. The point clouds with small amount of error had good results as the triangular model was solid. NURBS surface reconstruction performed well on solid models.

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The thesis examines the risk-adjusted performance of European small cap equity funds between 2008 and 2013. The performance is measured using several measures including Sharpe ratio, Treynor ratio, Modigliani measure, Jensen alpha, 3-factor alpha and 4-factor alpha. The thesis also addresses the issue of persistence in mutual fund performance. Thirdly, the relationship between the activity of fund managers and fund performance is investigated. The managerial activity is measured using tracking error and R-squared obtained from a 4-factor asset pricing model. The issues are investigated using Spearman rank correlation test, cross-sectional regression analysis and ranked portfolio tests. Monthly return data was provided by Morningstar and consists of 88 mutual funds. Results show that small cap funds earn back a significant amount of their expenses, but on average loose to their benchmark index. The evidence of performance persistence over 12-month time period is weak. Managerial activity is shown to positively contribute to fund performance

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Jarmo Rintasalo, Pentti Tapio

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Työn kirjallisuusosassa perehdytään paperikoneen online-mittarien toimintaan, poikkisuuntaisten profiilien säätämiseen ja kalanterointiin. Työn tavoitteena oli löytää syyt erään hienopaperikoneen heikkoon paksuusprofiiliin ja siitä aiheutuvaan suureen rullahylkymäärään. Syitä heikkoon paksuusprofiiliin on haettu kalanterin, päällystysasemien ja laatusäätöjärjestelmän toiminnoista. Työssä on tutkittu myös karheusprofiilin vaikutusta paksuusmittaukseen. Työssä löydettiin selvä yhteys paperin karheusprofiilin ja paperikoneen paksuusmittarin mittaaman paksuusprofiilin välille. Radan reuna-alueiden karheus suurentaa online-paksuusmittarin mittaustulosta. Karheusprofiili ei kuitenkaan vaikuta laboratoriomittareilla mitattuun paksuusprofiiliin. Paperikoneen onlinepaksuusmittarin mittausvirhe on kompensoitava, jotta paperin todellinen paksuusprofiili saadaan suoraksi. Työssä tehtyjen tutkimusten perusteella muodostettiin ajomalli, jolla ajettiin koeajojakso. Ajomallin päällimmäinen tarkoitus oli kompensoida paperikoneen online- paksuusmittarin mittausvirhe. Koeajo onnistui hyvin. Koeajojakson profiilivioista johtuva rullahylyn määräoli merkittävästi pienempi kuin referenssijakson profiilivioista johtuva rullahylyn määrä.

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Nowadays the used fuel variety in power boilers is widening and new boiler constructions and running models have to be developed. This research and development is done in small pilot plants where more faster analyse about the boiler mass and heat balance is needed to be able to find and do the right decisions already during the test run. The barrier on determining boiler balance during test runs is the long process of chemical analyses of collected input and outputmatter samples. The present work is concentrating on finding a way to determinethe boiler balance without chemical analyses and optimise the test rig to get the best possible accuracy for heat and mass balance of the boiler. The purpose of this work was to create an automatic boiler balance calculation method for 4 MW CFB/BFB pilot boiler of Kvaerner Pulping Oy located in Messukylä in Tampere. The calculation was created in the data management computer of pilot plants automation system. The calculation is made in Microsoft Excel environment, which gives a good base and functions for handling large databases and calculations without any delicate programming. The automation system in pilot plant was reconstructed und updated by Metso Automation Oy during year 2001 and the new system MetsoDNA has good data management properties, which is necessary for big calculations as boiler balance calculation. Two possible methods for calculating boiler balance during test run were found. Either the fuel flow is determined, which is usedto calculate the boiler's mass balance, or the unburned carbon loss is estimated and the mass balance of the boiler is calculated on the basis of boiler's heat balance. Both of the methods have their own weaknesses, so they were constructed parallel in the calculation and the decision of the used method was left to user. User also needs to define the used fuels and some solid mass flowsthat aren't measured automatically by the automation system. With sensitivity analysis was found that the most essential values for accurate boiler balance determination are flue gas oxygen content, the boiler's measured heat output and lower heating value of the fuel. The theoretical part of this work concentrates in the error management of these measurements and analyses and on measurement accuracy and boiler balance calculation in theory. The empirical part of this work concentrates on the creation of the balance calculation for the boiler in issue and on describing the work environment.

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We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.