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In a number of experiments, emotional pictures elicited a frontal positive slow wave in the event-related potential (ERP). This slow wave was initially interpreted as an indes of affective information processing, but one experiment showed that this component was also elicited by emotional neutral pictures in a cognitiven processing task. The aim of the present work was to reanalyse the functional significance of this slow wave. A first section of this work presents a theoretical examination of visual pathways by the brain. This section is supplemented by an overview of the principals of ERP methodology and a review of methods to correct ocular artifacts in the ERP. A second section describes two experiments. The aim of the first experiment was to examine the hypothesis that the frontal positive slow wave is an artifact of eye movements due to the presentation of visual stimuli. This hypothesis was examined with a paradigm that facilitates a systematic variation of eye movements by the visual presentation of matrices. The aim of the second experiment was to examine the hypothesis that a mere perceptual analysis of pictures does not elicit the frontal positive slow wave, but that a content analysis of the pictures is required to elicit this component. This hypothesis was investigated by a variation of content processing demands while the pictures were presented. The results of both experiments confirmed the main hypotheses.
Gegenstand dieser Studien ist die elektronische Version der Erstausgabe der Deutschen Wörterbuchs von Jacob Grimm und Wilhelm Grimm (=DWB). Auf verschiedenen Ebenen werden dabei die Möglichkeiten einer solchen elektronischen Wörterbuchversion für eine Reihe metalexikographischer Fragestellungen genutzt, und es wir gezeigt, dass vorher unmögliche oder nur mit unvertretbarem Aufwand durchführbare Untersuchungen nun durchführbar werden. Weiterhin wird gezeigt, dass die in der Metalexikographie bisher üblichen Schätzungen und Untersuchungen kleiner Teilabschnitte eines Wörterbuchs, die in der Regel zu Extrapolationen über die Gesamtinhalte von Wörterbüchern dienten, durch die Verfügbarkeit elektronischer Wörterbücher nun durch exaktere Untersuchungen und Ergebnisse ersetzt werden können. Zunächst wird die exakte Anzahl der im DWB aufgenommenen Stichwörter ermittelt - darüber liegen bisher lediglich Schätzungen vor. In einem zweiten Schritt wird der Umfang jedes einzelnen Artikels ds DWB ermittelt. Dies ermöglicht nicht nur Aussagen über die Beschaffenheit von Wörterbüchern und den darin enthaltenen Artikeln, die über einen Vergleich mit anderen Wörterbüchern zu einer ausgewogeneren Darstellung des Wortschatzes in zukünftigen Wörterbüchern führen könnten, sondern ermöglicht auch den gezielten Zugang zu einer bestimmten Gruppe von DWB-Artikeln, die im folgenden Gegenstand der Untersuchung sind - den kurzen Artikeln im DWB. Die systematische metalexikographische Untersuchung einer großen Anzahl von kurzen DWB-Artikeln zeigt schließlich, dass die vielerorts beschworene Heterogenität des DWB zumindest in der Hinsicht zu relativieren ist, indem kurze Artikel größtenteils bestimmten Aufbauprinzipien folgen - und das unabhängig vom Entstehungszeitupunkt des Artikels (Entstehungszeitraum des DWB: über 100 Jahre) - diese Aufbauprinzipien des DWB-Wörterbuchartikels spiegeln sich auch in den umfangreicheren Artikeln, und sie belegen eine Konstante lexikographischer Tätigkeit, die angesichts der immer wieder beschworenen Heterogenität gerade dieses Wörterbuchs (und auch in der gedruckten Version nicht mit vertretbarem Aufwand ermittelbar) bisher nicht wahr genommen worden ist. Den Abschluss der Untersuchungen bildet eine Untersuchung der Gliederungsprinzipien umfangreicher DWB-Artikel. Dabei werden die verschiedenen Bearbeitungsgrundsätze der am DWB beteiligten Lexikographen bei der Artikelgliederung durch Gliederungsmarken offenbar. Die Untersuchungen sollen insgesamt exemplarisch darstellen, welche Möglichkeiten metalexikographischer Untersuchungen sich durch die Verfügbarkeit elektronischer (digitalisierter) Wörterbücher eröffnen.
Vier Untersuchungen anhand eines modifizierten Ersparnisparadigmas zeigten, dass Eigenschaften spontan aus Verhalten erschlossen werden. In zwei der vier Untersuchungen offenbarte sich ein impliziter Einfluss des Altersstereotyps: Es förderte das spontane Erschließen stereotypkongruenter Eigenschaften. Dagegen wurde ein expliziter Einfluss des Altersstereotyps nicht eindeutig aufgezeigt; es ergaben sich jedoch Hinweise auf einen Reproduktionsvorteil zugunsten stereotypkongruenter Eigenschaften. Des Weiteren legten einige Befunde nahe, dass Mitglieder der "in-group" einfacher zu differenzieren sind als Mitglieder der "out-group". Nicht eindeutig geklärt werden konnte, ob die Aktivierung eines relevanten Stereotyps oder der Kontext, in den eine stereotype Information eingebettet ist, das Ausmaß der Stereotypisierung beeinflusst. Das Alter der Versuchspersonen (jüngere studentische Versuchspersonen in den Untersuchungen 1 bis 3 vs. ältere Versuchspersonen (M = 68.30) in der Untersuchung 4) beeinflusste zwar die Reproduktionsleistungen, nicht aber das spontane Erschließen von Eigenschaften oder das Ausmaß der impliziten bzw. expliziten Stereotypisierung.
Because EU water quality policy can result in infrastructure creation or adaptation at the local level across member states, compliance cases are worth examining critically from a sustainable spatial planning perspective. In this study, the 2000 EU Water Framework Directive’s (WFD) reach to local implementation efforts in average towns and cities is shown through the case study of nonconforming household wastewater infrastructure in the German state of Rhineland Palatinate. Seeing wastewater as a socio-technical infrastructure, we ask how the WFD implementation can be understood in the context of local infrastructure development, sustainability, and spatial planning concepts. In particular, this study examines what compliance meant for the centralization or decentralization of local wastewater infrastructure systems—and the sustainability implications for cities
from those choices.
Dry tropical forests undergo massive conversion and degradation processes. This also holds true for the extensive Miombo forests that cover large parts of Southern Africa. While the largest proportional area can be found in Angola, the country still struggles with food shortages, insufficient medical and educational supplies, as well as the ongoing reconstruction of infrastructure after 27 years of civil war. Especially in rural areas, the local population is therefore still heavily dependent on the consumption of natural resources, as well as subsistence agriculture. This leads, on one hand, to large areas of Miombo forests being converted for cultivation purposes, but on the other hand, to degradation processes due to the selective use of forest resources. While forest conversion in south-central rural Angola has already been quantitatively described, information about forest degradation is not yet available. This is due to the history of conflicts and the therewith connected research difficulties, as well as the remote location of this area. We apply an annual time series approach using Landsat data in south-central Angola not only to assess the current degradation status of the Miombo forests, but also to derive past developments reaching back to times of armed conflicts. We use the Disturbance Index based on tasseled cap transformation to exclude external influences like inter-annual variation of rainfall. Based on this time series, linear regression is calculated for forest areas unaffected by conversion, but also for the pre-conversion period of those areas that were used for cultivation purposes during the observation time. Metrics derived from linear regression are used to classify the study area according to their dominant modification processes.rnWe compare our results to MODIS latent integral trends and to further products to derive information on underlying drivers. Around 13% of the Miombo forests are affected by degradation processes, especially along streets, in villages, and close to existing agriculture. However, areas in presumably remote and dense forest areas are also affected to a significant extent. A comparison with MODIS derived fire ignition data shows that they are most likely affected by recurring fires and less by selective timber extraction. We confirm that areas that are used for agriculture are more heavily disturbed by selective use beforehand than those that remain unaffected by conversion. The results can be substantiated by the MODIS latent integral trends and we also show that due to extent and location, the assessment of forest conversion is most likely not sufficient to provide good estimates for the loss of natural resources.
Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an approach to modeling similarity measures based on embedding semantic graphs via Graph Neural Networks (GNNs). Therefore, we first examine how arbitrary semantic graphs, including node and edge types and their knowledge-rich semantic annotations, can be encoded in a numeric format that is usable by GNNs. Given this, the architecture of two generic graph embedding models from the literature is adapted to enable their usage as a similarity measure for similarity-based retrieval. Thereby, one of the two models is more optimized towards fast similarity prediction, while the other model is optimized towards knowledge-intensive, more expressive predictions. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of a graph-matching-based similarity measure for two semantic graph domains. The results show the great potential of the approach for use in a retrieval scenario, either as a preselection model or as an approximation of a graph similarity measure.
There are large health, societal, and economic costs associated with attrition from psychological services. The recently emerged, innovative statistical tool of complex network analysis was used in the present proof-of-concept study to improve the prediction of attrition. Fifty-eight patients undergoing psychological treatment for mood or anxiety disorders were assessed using Ecological Momentary Assessments four times a day for two weeks before treatment (3,248 measurements). Multilevel vector autoregressive models were employed to compute dynamic symptom networks. Intake variables and network parameters (centrality measures) were used as predictors for dropout using machine-learning algorithms. Networks for patients differed significantly between completers and dropouts. Among intake variables, initial impairment and sex predicted dropout explaining 6% of the variance. The network analysis identified four additional predictors: Expected force of being excited, outstrength of experiencing social support, betweenness of feeling nervous, and instrength of being active. The final model with the two intake and four network variables explained 32% of variance in dropout and identified 47 out of 58 patients correctly. The findings indicate that patients" dynamic network structures may improve the prediction of dropout. When implemented in routine care, such prediction models could identify patients at risk for attrition and inform personalized treatment recommendations.
The reduction of information contained in model time series through the use of aggregating statistical performance measures is very high compared to the amount of information that one would like to draw from it for model identification and calibration purposes. It is readily known that this loss imposes important limitations on model identification and -diagnostics and thus constitutes an element of the overall model uncertainty as essentially different model realizations with almost identical performance measures (e.g. r-² or RMSE) can be generated. In three consecutive studies the present work proposes an alternative approach towards hydrological model evaluation based on the application of Self-Organizing Maps (SOM; Kohonen, 2001). The Self-Organizing Map is a type of artificial neural network and unsupervised learning algorithm that is used for clustering, visualization and abstraction of multidimensional data. It maps vectorial input data items with similar patterns onto contiguous locations of a discrete low-dimensional grid of neurons. The iterative training of the SOM causes the neurons to form a discrete, data-compressed representation of the high-dimensional input data. Using appropriate visualization techniques, information on distributions, patterns and relationships in complex data sets can be extracted. Irrespective of their potential, SOM applications have earned very little attention in hydrological modelling compared to other artificial neural network techniques. Therefore, the aim of the present work is to demonstrate that the application of Self-Organizing Maps has very high potential to address fundamental issues of model evaluation: It is shown that the clustering and classification of model time series by means of SOM can provide useful insights into model behaviour. In combination with the diagnostic properties of Signature Indices (Gupta et al., 2008; Yilmaz et al., 2008) SOM provides a novel tool for interpreting the model parameters in the hydrological context and identifying parameter sets that simultaneously meet multiple objectives, even if the corresponding model realizations belong to different models. Moreover, the presented studies and reviews also encourage further studies on the application of SOM in hydrological modelling.
Evidence points to autonomy as having a place next to affiliation, achievement, and power as one of the basic implicit motives; however, there is still some research that needs to be conducted to support this notion.
The research in this dissertation aimed to address this issue. I have specifically focused on two issues that help solidify the foundation of work that has already been conducted on the implicit autonomy motive, and will also be a foundation for future studies. The first issue is measurement. Implicit motives should be measured using causally valid instruments (McClelland, 1980). The second issue addresses the function of motives. Implicit motives orient, select, and energize behavior (McClelland, 1980). If autonomy is an implicit motive, then we need a valid instrument to measure it and we also need to show that it orients, selects, and energizes behavior.
In the following dissertation, I address these two issues in a series of ten studies. Firstly, I present studies that examine the causal validity of the Operant Motive Test (OMT; Kuhl, 2013) for the implicit affiliation and power motives using established methods. Secondly, I developed and empirically tested pictures to specifically assess the implicit autonomy motive and examined their causal validity. Thereafter, I present two studies that investigated the orienting and energizing effects of the implicit autonomy motive. The results of the studies solidified the foundation of the OMT and how it measures nAutonomy. Furthermore, this dissertation demonstrates that nAutonomy fulfills the criteria for two of the main functions of implicit motives. Taken together, the findings of this dissertation provide further support for autonomy as an implicit motive and a foundation for intriguing future studies.