12 resultados para estimator

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


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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.

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It is generally accepted that between 70 and 80% of manufacturing costs can be attributed to design. Nevertheless, it is difficult for the designer to estimate manufacturing costs accurately, especially when alternative constructions are compared at the conceptual design phase, because of the lack of cost information and appropriate tools. In general, previous reports concerning optimisation of a welded structure have used the mass of the product as the basis for the cost comparison. However, it can easily be shown using a simple example that the use of product mass as the sole manufacturing cost estimator is unsatisfactory. This study describes a method of formulating welding time models for cost calculation, and presents the results of the models for particular sections, based on typical costs in Finland. This was achieved by collecting information concerning welded products from different companies. The data included 71 different welded assemblies taken from the mechanical engineering and construction industries. The welded assemblies contained in total 1 589 welded parts, 4 257 separate welds, and a total welded length of 3 188 metres. The data were modelled for statistical calculations, and models of welding time were derived by using linear regression analysis. Themodels were tested by using appropriate statistical methods, and were found to be accurate. General welding time models have been developed, valid for welding in Finland, as well as specific, more accurate models for particular companies. The models are presented in such a form that they can be used easily by a designer, enabling the cost calculation to be automated.

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Multilevel converters provide an attractive solution to bring the benefits of speed-controlled rotational movement to high-power applications. Therefore, multilevel inverters have attracted wide interest in both the academic community and in the industry for the past two decades. In this doctoral thesis, modulation methods suitable especially for series connected H-bridge multilevel inverters are discussed. A concept of duty cycle modulation is presented and its modification is proposed. These methods are compared with other well-known modulation schemes, such as space-vector pulse width modulation and carrier-based modulation schemes. The advantage of the modified duty-cycle modulation is its algorithmic simplicity. A similar mathematical formulation for the original duty cycle modulation is proposed. The modified duty cycle modulation is shown to produce well-formed phase-to-neutral voltages that have lower total harmonic distortion than the space-vector pulse width modulation and the duty cycle modulation. The space-vector-based solution and the duty cycle modulation, on the other hand, result in a better-quality line-to-line voltage and current waveform. The voltage of the DC links in the modules of the series-connected H-bridge inverter are shown to fluctuate while they are under load. The fluctuation causes inaccuracies in the voltage production, which may result in a failure of the flux estimator in the controller. An extension for upper-level modulation schemes, which changes the switching instants of the inverter so that the output voltage meets the reference voltage accurately regardless of the DC link voltages, is proposed. The method is shown to reduce the error to a very low level when a sufficient switching frequency is used. An appropriate way to organize the switching instants of the multilevel inverter is to make only one-level steps at a time. This causes restrictions on the dynamical features of the modulation schemes. The produced voltage vector cannot be rotated several tens of degrees in a single switching period without violating the above-mentioned one-level-step rule. The dynamical capabilities of multilevel inverters are analyzed in this doctoral thesis, and it is shown that the multilevel inverters are capable of operating even in dynamically demanding metal industry applications. In addition to the discussion on modulation schemes, an overvoltage in multilevel converter drives caused by cable reflection is addressed. The voltage reflection phenomenon in drives with long feeder cables causes premature insulation deterioration and also affects the commonmode voltage, which is one of the main reasons for bearing currents. Bearing currents, on the other hand, cause fluting in the bearings, which results in premature bearing failure. The reflection phenomenon is traditionally prevented by filtering, but in this thesis, a modulationbased filterless method to mitigate the overvoltage in multilevel drives is proposed. Moreover, the mitigation method can be implemented as an extension for upper-level modulation schemes. The method exploits the oscillations caused by two consecutive voltage edges so that the sum of the oscillations results in a mitigated peak of the overvoltage. The applicability of the method is verified by simulations together with experiments with a full-scale prototype.

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The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

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Työssä toteutettiin C-kielellä luistonestojärjestelmä ja elektroninen tasauspyörästö Simulinkmallien pohjalta hybridityökoneeseen. Hybridityökoneen sähkökäytöt mahdollistavat tarkan vääntömomentin säädön, joka mahdollistaa työssä kuvatun kaltaisen järjestelmän toteuttamisen. Toteutettua järjestelmää simuloitiin MeVEA Oy:n ajoneuvomallinnukseen kehitetyssä simulaattorissa. Lisäksi järjestelmästä kehitettiin Visedo Oy:n sähkökäyttösimulaattoriin sopiva versio, jota testattiin Visedon sähkökäyttöjä simuloivan ohjelman kanssa. Simulointituloksien mukaan luistonesto estää vetäviä pyöriä luistamasta liukkaalla alustalla eikä toisaalta vähennä aiheetta kuljettajan asettamaa vääntömomenttia. Myös sähköinen tasauspyörästö toimi kuten oli suunniteltu. Työssä kehitetty luistonesto tarvitsee toimiakseen tiedon ajoneuvon kokonaismassasta, joten työssä kehitettiin myös tapa ajoneuvon massan estimoimiseksi ajoneuvon kiihdyttäessä. Massan estimointia testattiin pitävällä ja liukkaalla alustalla. Massan estimointi toimi simulaattoriympäristössä hyvällä tarkkuudella.

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Nykyajan jatkuvasti kiristyvät päästörajoitukset ja ilmastonmuutoksen uhka ovat ajavia voimia kehittämään voimalaitosten tekniikkaa energiatehokkaampaan ja ympäristöystävällisempään suuntaan. Polttomoottoritekniikan parantaminen on tärkeä osa tätä kehitystä, mutta jo nykyisiä moottoreita voitaisiin ajaa energiate-hokkaammin käyttämällä akustoa ja älykästä säätöjärjestelmää apuna. Työssä tutkitaan simulaatioiden avulla voidaanko ulkomerellä toimivan huolto-aluksen energiatehokkuutta parantaa muokkaamalla sen tehon tuottoa keskitehoes-timaattorin ja akuston avulla.

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The pulp and paper industry is currently facing broad structural changes due to global shifts in demand and supply. These changes have significant impacts on national economies worldwide. In this paper, we describe the recent trends in the pulp and recovered paper (RP) production, and estimate augmented gravity models of bilateral trade for chemical pulp and RP exports with panel data. According to our results, there is some variation in the effects of the traditional gravity-model variables between pulp grades and RP. The results imply also that, in comparison to export supply, import demand plays a larger role in determining the volume of exports. Finally, it is evident that Asia, particularly China, is the most important driver of chemical pulp and RP trade: China is hungry for fiber, and must import to satisfy its growing needs. Moreover, the speed of China’s growth in chemical pulp and RP imports has been driving the increased significance of planted forests in the exports of hardwood pulp (BHKP) as well.

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The pulp and paper industry is currently facing broad structural changes due to global shifts in demand and supply. These changes have significant impacts on national economies worldwide. Planted forests (especially eucalyptus) and recovered paper have quickly increased their importance as raw material for paper and paperboard production. Although advances in information and communication technologies could reduce the demand for communication papers, and the growth of paper consumption has indeed flattened in developed economies, particularly in North America and Western Europe, the consumption is increasing on a global scale. Moreover, the focal point of production and consumption is moving from the Western world to the rapidly growing markets of Southeast Asia. This study analyzes how the so-called megatrends (globalization, technological development, and increasing environmental awareness) affect the pulp and paper industry’s external environment, and seeks reliable ways to incorporate the impact of the megatrends on the models concerning the demand, trade, and use of paper and pulp. The study expands current research in several directions and points of view, for example, by applying and incorporating several quantitative methods and different models. As a result, the thesis makes a significant contribution to better understand and measure the impacts of structural changes on the pulp and paper industry. It also provides some managerial and policy implications.

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This thesis investigates the pressure-based control of a variable-speed-driven pump system in the case of existing output pressure measurement and in the case of sensorless system, where the actual output pressure value is calculated with the steady state estimator.

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This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

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The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.

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One of the most disputable matters in the theory of finance has been the theory of capital structure. The seminal contributions of Modigliani and Miller (1958, 1963) gave rise to a multitude of studies and debates. Since the initial spark, the financial literature has offered two competing theories of financing decision: the trade-off theory and the pecking order theory. The trade-off theory suggests that firms have an optimal capital structure balancing the benefits and costs of debt. The pecking order theory approaches the firm capital structure from information asymmetry perspective and assumes a hierarchy of financing, with firms using first internal funds, followed by debt and as a last resort equity. This thesis analyses the trade-off and pecking order theories and their predictions on a panel data consisting 78 Finnish firms listed on the OMX Helsinki stock exchange. Estimations are performed for the period 2003–2012. The data is collected from Datastream system and consists of financial statement data. A number of capital structure characteristics are identified: firm size, profitability, firm growth opportunities, risk, asset tangibility and taxes, speed of adjustment and financial deficit. A regression analysis is used to examine the effects of the firm characteristics on capitals structure. The regression models were formed based on the relevant theories. The general capital structure model is estimated with fixed effects estimator. Additionally, dynamic models play an important role in several areas of corporate finance, but with the combination of fixed effects and lagged dependent variables the model estimation is more complicated. A dynamic partial adjustment model is estimated using Arellano and Bond (1991) first-differencing generalized method of moments, the ordinary least squares and fixed effects estimators. The results for Finnish listed firms show support for the predictions of profitability, firm size and non-debt tax shields. However, no conclusive support for the pecking-order theory is found. However, the effect of pecking order cannot be fully ignored and it is concluded that instead of being substitutes the trade-off and pecking order theory appear to complement each other. For the partial adjustment model the results show that Finnish listed firms adjust towards their target capital structure with a speed of 29% a year using book debt ratio.