In this thesis, using the principles of confirmatory factor analysis (CFA) and the cause-effect concept associated with structural equation modelling (SEM), a new flexible statistical framework for evaluation of climate model simulations against observational data is suggested. The design of the framework also makes it possible to investigate the magnitude of the influence of different forcings on the temperature as well as to investigate a general causal latent structure of temperature data. In terms of the questions of interest, the framework suggested here can be viewed as a natural extension of the statistical approach of 'optimal fingerprinting', employed in many Detection and Attribution (D&amp;A) studies. Its flexibility means that it can be applied under different circumstances concerning such aspects as the availability of simulated data, the number of forcings in question, the climate-relevant properties of these forcings, and the properties of the climate model under study, in particular, those concerning the reconstructions of forcings and their implementation. It should also be added that although the framework involves the near-surface temperature as a climate variable of interest and focuses on the time period covering approximately the last millennium prior to the industrialisation period, the statistical models, included in the framework, can in principle be generalised to any period in the geological past as soon as simulations and proxy data on any continuous climate variable are available.  Within the confines of this thesis, performance of some CFA- and SEM-models is evaluated in pseudo-proxy experiments, in which the true unobservable temperature series is replaced by temperature data from a selected climate model simulation. The results indicated that depending on the climate model and the region under consideration, the underlying latent structure of temperature data can be of varying complexity, thereby rendering our statistical framework, serving as a basis for a wide range of CFA- and SEM-models, a powerful and flexible tool. Thanks to these properties, its application ultimately may contribute to an increased confidence in the conclusions about the ability of the climate model in question to simulate observed climate changes. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript. Paper 3: Manuscript.</p>

This diploma thesis is focused on object detections through general-purpose computing on graphics processor units. There is an explanation of graphics adapters work and basics of their architecture in this thesis. Based on the adapters, there is the effective work in libraries for general-purpose computing on graphics processor units demonstrated in this thesis. Further, the thesis shows the available algorithms for object detection and which ones from them are possible to be effectively parallelized. In conclusion of this thesis, there is a comparison of the object detections speeds to common implementations on classical processors.

This thesis concentrates on regression models with a categorical response. It focuses on the model of logistic regression with binary response and its generalization in which two models are distinguished: multinomial regression with nominal response and multinomial regression with ordinal response. For all three models separately, the Wald test and the likelihood ratio test are derived. These theoretical derivations are then used to calculate the test statistics for specific examples in statistical software R. The theory described in the thesis is illustrated by examples with small and large number of explanatory variables.

Four interval estimation methods for the ratio of marginal binomial proportions are compared in terms of expected interval width and exact coverage probability. Two new methods are proposed that are based on combining two Wilson score intervals. The new methods are easy to compute and perform as well or better than the method recently proposed by Nam and Blackwelder. Two sample size formulas are proposed to approximate the sample size required to achieve an interval estimate with desired confidence level and width.

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Waldwege erfüllen heute viele Funktionen. Sie werden von Wanderern und Radfahrern genutzt ebenso wie zur Abfuhr von Holz oder dienen als Rettungsweg. Das Faltblatt stellt die verschiedenen Nutzungen vor. Redaktionsschluss: 30.10.2020

Von 2006 bis 2016 erfolgte die erste landesweite Aktualisierung der Waldbiotopkartierung. Sie dokumentiert Anzahl und Lage gesetzlich geschützter und anderer wertvoller Biotope sowie den Zustand der Lebensraumtypen innerhalb und außerhalb der FFH-Gebiete. Die Ergebnisse sind in dieser Veröffentlichung anschaulich aufbereitet. Redaktionsschluss: 30.10.2018

Das Walderlebniszentrum Leupoldishain ist eines der wenigen rollstuhlgerechten Einrichtungen dieser Art in Deutschland. Das Faltblatt informiert über Angebote und Lehrinhalte. Redaktionsschluss: 20.03.2019

Das Walderlebniszentrum befindet sich im Waldgebiet Massenei, das sich östlich von Dresden zwischen den Orten Arnsdorf, Großröhrsdorf und Großharthau erstreckt. Aufgrund der Lage an einer Kreuzung verschiedener Wald- bzw. Wanderwege, die in der Region als »Kleiner Stern« bekannt ist, erhielt das WaldHaus diesen Namen. Redaktionsschluss: 20.03.2019

In nächster Nähe zum Waldgebiet Oberholz und direkt im Botanischen Garten Großpösna steht unser Blockhaus, das Basisstation für große und kleine Forscher ist. Wir bieten waldpädagogische Programme und geführte Waldwanderungen an. Je nach Alter und Interesse der Besucher stehen verschiedene Themen zur Auswahl. Die Programme für Schüler basieren dabei auf den Vorgaben der sächsischen Lehrpläne. Redaktionsschluss: 15.07.2020