29 resultados para State And Transition Models

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


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The aim of this master’s thesis was to document the present state and to create a development plan for Moventas Wind’s cost accounting. The current cost accounting system was evaluated and most fundamental problems were chosen as areas of focus in development work. The development plan includes both short- and long-term development proposals for problems identified. This report presents two alternative models for product costing. Benchmarking of cost accounting practices and modern cost accounting theories were used in development of cost accounting. It was found that the current cost accounting system functions quite well and the adjustments in unit cost rate calculation have only a minor influence on costs of goods sold. An OEE-based standard cycle concept was also developed and it was found that the implementation of this new system is worthwhile in the long-term.

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This research focused on operation of a manpower pool within a service business unit in Company X and aimed to identify how the operation should be improved in order to get most out of it concerning the future prospects of the service business unit. This was done by analyzing the current state of the manpower pool related operations in means of project business, project management and business models. The objective was to deepen the understanding and to highlight possible areas of improvement. The research was conducted as a qualitative single-case study utilizing also an action research method; the research approach was a combination of conceptual, action-oriented and constructive approaches. The primary data was collected with executing a comprehensive literature review and semi-structured theme interviews. The main results described how the manpower pool operates as part of the service business unit in project business by participating in different types of delivery projects; process flows for the project types were mapped. Project management was analyzed especially from the resource management point of view, and an Excel-based skills analysis model was constructed for this purpose. Utilization of operational business models was also studied to define strategic direction for development activities. The results were benchmarked against two competitors in order to specify lessons to be learnt from their use of operational business models.

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State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

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Selostus: Viljelyvyöhykkeiden ja kasvumallien soveltaminen ilmastonmuutoksen tutkimisessa: Mackenzien jokialue, Kanada

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Tämä työ luo katsauksen ajallisiin ja stokastisiin ohjelmien luotettavuus malleihin sekä tutkii muutamia malleja käytännössä. Työn teoriaosuus sisältää ohjelmien luotettavuuden kuvauksessa ja arvioinnissa käytetyt keskeiset määritelmät ja metriikan sekä varsinaiset mallien kuvaukset. Työssä esitellään kaksi ohjelmien luotettavuusryhmää. Ensimmäinen ryhmä ovat riskiin perustuvat mallit. Toinen ryhmä käsittää virheiden ”kylvöön” ja merkitsevyyteen perustuvat mallit. Työn empiirinen osa sisältää kokeiden kuvaukset ja tulokset. Kokeet suoritettiin käyttämällä kolmea ensimmäiseen ryhmään kuuluvaa mallia: Jelinski-Moranda mallia, ensimmäistä geometrista mallia sekä yksinkertaista eksponenttimallia. Kokeiden tarkoituksena oli tutkia, kuinka syötetyn datan distribuutio vaikuttaa mallien toimivuuteen sekä kuinka herkkiä mallit ovat syötetyn datan määrän muutoksille. Jelinski-Moranda malli osoittautui herkimmäksi distribuutiolle konvergaatio-ongelmien vuoksi, ensimmäinen geometrinen malli herkimmäksi datan määrän muutoksille.

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This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

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The Standard Model of particle physics is currently the best description of fundamental particles and their interactions. All particles save the Higgs boson have been observed in particle accelerator experiments over the years. Despite the predictive power the Standard Model there are many phenomena that the scenario does not predict or explain. Among the most prominent dilemmas is matter-antimatter asymmetry, and much effort has been made in formulating scenarios that accurately predict the correct amount of matter-antimatter asymmetry in the universe. One of the most appealing explanations is baryogenesis via leptogenesis which not only serves as a mechanism of producing excess matter over antimatter but can also explain why neutrinos have very small non-zero masses. Interesting leptogenesis scenarios arise when other possible candidates of theories beyond the Standard Model are brought into the picture. In this thesis, we have studied leptogenesis in an extra dimensional framework and in a modified version of supersymmetric Standard Model. The first chapters of this thesis introduce the standard cosmological model, observations made on the photon to baryon ratio and necessary preconditions for successful baryogenesis. Baryogenesis via leptogenesis is then introduced and its connection to neutrino physics is illuminated. The final chapters concentrate on extra dimensional theories and supersymmetric models and their ability to accommodate leptogenesis. There, the results of our research are also presented.

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In this work emission, optical, electrical and magnetic properties of the d- and f- elements doped zinc selenide crystals were investigated within a wide temperature range. Doping was performed in various technological processes: during the growth by chemical vapor transport method; by thermal diffusion from the Bi or Zn melt. Concentration of the doping impurity in the crystals was controlled by amount of the dopant in the source material or by its concentration in the doping media. Special interest in the work was paid to the influence of the different concentrations of Cr and Yb impurities on ZnSe crystals’ properties, correlations between observed effects and similarities with the Ni, Mn and Gd dopants are analysed. Possibility of formation of the excitons bound to the doping d-ions was shown. In contrast to this, it was observed that f-elements do not bound excitons, but prevent formation of excitons bound to some uncontrolled impurities. A mechanism of Cr doping impurity interaction with background impurities and zinc selenide structural defects was proposed based on experimental data. An assumption about resonant energy transfer between double charged chromium ions and complexes based on crystals’ vacancy defects was made. A correlation between emission and magnetic properties of the d- ions doped samples was established. Based on this correlation a mechanism explaining the concentration quench of the emission was proposed. It was found that f-ions bind electrically active shallow and deep donor and acceptor states of background impurity to electrically neutral complexes. This may be observed as “purification” of ZnSe crystals by doping with the rare-earth elements, resulting i tendency of the properties of f-ion doped crystals to the properties of intrinsic crystals, but with smaller concentration of uncontrolled native and impurity defects. A possible interpretation of this effect was proposed. It was shown that selenium substituting impurities decrease efficiency of the Yb doping. Based on this experimental results an attempt to determine ytterbium ion surroundings in the crystal lattice was made. It was shown that co-doping of zinc selenide crystals with the d- and f- ions leads to the combination of the impurities influence on the material’s properties. On the basis of obtained data an interaction mechanism of the d- and f-elements co-dopants was proposed. Guided by the model of the ytterbium ion incorporation in the selenide sublattice of the ZnSe crystals, an assumption about stabilization of single charged chromium ions in the zinc sublattice crystal nodes, by means of formation of the local charge compensating clusters, was made.