910 resultados para Prediction method
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Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.
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The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.
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PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.
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Diplomityön tavoitteena on selvittää Loviisan ydinvoimalaitoksen höyryturbiinin hyötysuhteen parantamismahdollisuuksia. Työn kuvaan liittyvät oleellisesti höyryturbiinin siipivyöhykkeiden nopeuskolmioiden sekä hyötysuhteiden laskenta. Höyryturbiinien kehityskaarta sekä turbiinin häviökerrointen laskentayhtälöitä on esitetty useasta eri lähteestä ja vuosikymmeniltä. Työssä selvitettiin uusimpia ydinvoimalaitosten kostea höyryturbiinien suunnitteluperusteita lukuisista eri lähteistä. Kaikkien lähteiden mukaan kostean höyryn alueella tapahtuvaa paisuntaa on haasteellista mallintaa. Työssä on esitelty artikkeleissa tulleita eri näkökulmia höyryturbiinien suorituskyvyn parantamiseksi, sekä rakenteellisia että laskennallisia. Työssä esitellään monia turbiinin virtauksen ja suorituskyvyn laskentamenetelmiä. Esimerkiksi Baumannin säännön laskenta on yksinkertainen tapa käsitellä turbiinin suorituskykyä kostean höyryn alueella. Keskeisimpiä tehtyjä havaintoja oli se, että korkeapaineturbiinin ensimmäisestä vaiheesta löytyi mahdollista parannuspotentiaalia Loviisaan ydinvoimalaitoksen tehon lisäämiseksi. Ensimmäisessä vaiheessa on oletettu siipien olevan Laval –tyyppisiä, mutta käytännössä näin ei ole. Korkeapaineturbiinin nykyisen turbosuuttimen toimintaa voitaisiin tehostaa. Lisäksi Loviisan matalapaineturbiinin viimeisen siipivaiheen jälkeen aiheutuu suuret ulosvirtaushäviöt. Osa suurinopeuksisen virtauksen energiasta pystyttäisiin kuitenkin hyödyntämään vielä ulosvirtauskanavassa olevalla diffuusorilla.
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Context: BL Lacs are the most numerous extragalactic objects which are detected in Very High Energy (VHE) gamma-rays band. They are a subclass of blazars. Large flux variability amplitude, sometimes happens in very short time scale, is a common characteristic of them. Significant optical polarization is another main characteristics of BL Lacs. BL Lacs' spectra have a continuous and featureless Spectral Energy Distribution (SED) which have two peaks. Among 1442 BL Lacs in the Roma-BZB catalogue, only 51 are detected in VHE gamma-rays band. BL Lacs are most numerous (more than 50% of 514 objects) objects among the sources that are detected above 10 GeV by FERMI-LAT. Therefore, many BL Lacs are expected to be discovered in VHE gamma-rays band. However, due to the limitation on current and near future technology of Imaging Air Cherenkov Telescope, astronomers are forced to predict whether an object emits VHE gamma-rays or not. Some VHE gamma-ray prediction methods are already introduced but still are not confirmed. Cross band correlations are the building blocks of introducing VHE gamma-rays prediction method. Aims: We will attempt to investigate cross band correlations between flux energy density, luminosity and spectral index of the sample. Also, we will check whether recently discovered MAGIC J2001+435 is a typical BL Lac. Methods: We select a sample of 42 TeV BL Lacs and collect 20 of their properties within five energy bands from literature and Tuorla blazar monitoring program database. All of the data are synchronized to be comparable to each other. Finally, we choose 55 pair of datasets for cross band correlations finding and investigating whether there is any correlation between each pair. For MAGIC J2001+435 we analyze the publicly available SWIFT-XRT data, and use the still unpublished VHE gamma-rays data from MAGIC collaboration. The results are compared to the other sources of the sample. Results: Low state luminosity of multiple detected VHE gamma-rays is strongly correlated luminosities in all other bands. However, the high state does not show such strong correlations. VHE gamma-rays single detected sources have similar behaviour to the low state of multiple detected ones. Finally, MAGIC J2001+435 is a typical TeV BL Lac. However, for some of the properties this source is located at the edge of the whole sample (e.g. in terms of X-rays flux). Keywords: BL Lac(s), Population study, Correlations finding, Multi wavelengths analysis, VHE gamma-rays, gamma-rays, X-rays, Optical, Radio
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The results of applying a fragment-based protein tertiary structure prediction method to the prediction of 14 CASP5 target domains are described. The method is based on the assembly of supersecondary structural fragments taken from highly resolved protein structures using a simulated annealing algorithm. A number of good predictions for proteins with novel folds were produced, although not always as the first model. For two fold recognition targets, FRAGFOLD produced the most accurate model in both cases, despite the fact that the predictions were not based on a template structure. Although clear progress has been made in improving FRAGFOLD since CASP4, the ranking of final models still seems to be the main problem that needs to be addressed before the next CASP experiment
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Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.
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Results are presented of a study of a performance of various track-side railway noise barriers, determined by using a two- dimensional numerical boundary element model. The basic model uses monopole sources and has been adapted to allow the sources to exhibit dipole-type radiation characteristics. A comparison of boundary element predictions of the performance of simple barriers and vehicle shapes is made with results obtained by using the standard U.K. prediction method. The results obtained from the numerical model indicate that modifying the source to exhibit dipole characteristics becomes more significant as the height of the barrier increases, and suggest that for any particular shape, absorbent barriers provide much better screening efficiency than the rigid equivalent. The cross-section of the rolling stock significantly affects the performance of rigid barriers. If the position of the upper edge is fixed, the results suggest that simple absorptive barriers provide more effective screening than tilted barriers. The addition of multiple edges to a barrier provides additional insertion loss without any increase in barrier height.
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In this paper we consider a self-excited mechanical system by dry friction in order to study the bifurcational behavior of the arisen vibrations. The oscillating system consists of a mass block-belt-system which is self-excited by static and Coulomb friction. We analyze the system behavior numerically through bifurcation diagrams, phase portraits, frequency spectra and Poincare maps, which show the existence of nonhomoclinic and homoclinic chaos and a route to homoclinic chaos. The homoclinic chaos is also analyzed analytically via the Melnikov prediction method. The system dynamic is characterized by the existence of two potential wells in the phase plane which exhibit rich bifurcational and chaotic behavior.
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Pós-graduação em Ciências Odontológicas - FOAR
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A number of autonomous underwater vehicles, AUV, are equipped with commercial ducted propellers, most of them produced originally for the remote operated vehicle, ROV, industry. However, AUVs and ROVs are supposed to work quite differently since the ROV operates in almost the bollard pull condition, while the AUV works at larger cruising speeds. Moreover, they can have an influence in the maneuverability of AUV due to the lift the duct generates in the most distant place of the vehicle's center of mass. In this work, it is proposed the modeling of the hydrodynamic forces and moment on a duct propeller according to a numerical (CFD) simulation, and analytical and semi-empirical, ASE, approaches. Predicted values are compared to experimental results produced in a towing tank. Results confirm the advantages of the symbiosis between CFD and ASE methods for modeling the influence of the propeller duct in the AUV maneuverability. (C) 2012 Elsevier Ltd. All rights reserved.
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The dynamic behaviour of a fishing vessel in waves is studied in order to reveal its parametric rolling characteristics. This paper presents experimental and numerical results in longitudinal regular waves. The experimental results are compared against the results of a time-domain non-linear strip theory model of ship motions in six degrees-of-freedom. These results contribute to the validation of the parametric rolling prediction method, so that it can be used as an assessment tool to evaluate both the susceptibility and severity of occurrence of parametric rolling at the early design stage of these types of vessels.
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Este estudio profundiza en la estimación de variables forestales a partir de información LiDAR en el Valle de la Fuenfría (Cercedilla, Madrid). Para ello se dispone de dos vuelos realizados con sensor LiDAR en los años 2002 y 2011 y en el invierno de 2013 se ha realizado un inventario de 60 parcelas de campo. En primer lugar se han estimado seis variables dasométricas (volumen, área basimétrica, biomasa total, altura dominante, densidad y diámetro medio cuadrático) para 2013, tanto a nivel de píxel como a nivel de rodal y monte. Se construyeron modelos de regresión lineal múltiple que permitieron estimar con precisión dichas variables. En segundo lugar, se probaron diferentes métodos para la estimación de la distribución diamétrica. Por un lado, el método de predicción de percentiles y, por otro lado, el método de predicción de parámetros. Este segundo método se probó para una función Weibull simple, una función Weibull doble y una combinación de ambas según la distribución que mejor se ajustaba a cada parcela. Sin embargo, ninguno de los métodos ha resultado suficientemente válido para predecir la distribución diamétrica. Por último se estimaron el crecimiento en volumen y área basimétrica a partir de la comparación de los vuelos del 2002 y 2011. A pesar de que la tecnología LiDAR era diferente y solo se disponía de un inventario completo, realizado en 2013, los modelos construidos presentan buenas bondades de ajuste. Asimismo, el crecimiento a nivel de pixel se ha mostrado estar relacionado de forma estadísticamente significativa con la pendiente, orientación y altitud media del píxel. ABSTRACT This project goes in depth on the estimation of forest attributes by means of LiDAR data in Fuenfria’s Valley (Cercedilla, Madrid). The available information was two LiDAR flights (2002 and 2011) and a forest inventory consisting of 60 plots (2013). First, six different dasometric attributes (volume, basal area, total aboveground biomass, top height, density and quadratic mean diameter) were estimated in 2013 both at a pixel, stand and forest level. The models were developed using multiple linear regression and were good enough to predict these attributes with great accuracy. Second, the measured diameter distribution at each plot was fitted to a simple and a double Weibull distribution and different methods for its estimation were tested. Neither parameter prediction method nor percentile prediction method were able to account for the diameter distribution. Finally, volume and top height growths were estimated comparing 2011 LiDAR flight with 2002 LiDAR flight. Even though the LiDAR technology was not the same and there was just one forest inventory with sample plots, the models properly explain the growth. Besides, growth at each pixel is significantly related to its average slope, orientation and altitude.
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"February 22, 1977."