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Up-to-date information about the type and spatial distribution of forests is an essential element in both sustainable forest management and environmental monitoring and modelling. The OpenStreetMap (OSM) database contains vast amounts of spatial information on natural features, including forests (landuse=forest). The OSM data model includes describing tags for its contents, i.e., leaf type for forest areas (i.e., leaf_type=broadleaved). Although the leaf type tag is common, the vast majority of forest areas are tagged with the leaf type mixed, amounting to a total area of 87% of landuse=forests from the OSM database. These areas comprise an important information source to derive and update forest type maps. In order to leverage this information content, a methodology for stratification of leaf types inside these areas has been developed using image segmentation on aerial imagery and subsequent classification of leaf types. The presented methodology achieves an overall classification accuracy of 85% for the leaf types needleleaved and broadleaved in the selected forest areas. The resulting stratification demonstrates that through approaches, such as that presented, the derivation of forest type maps from OSM would be feasible with an extended and improved methodology. It also suggests an improved methodology might be able to provide updates of leaf type to the OSM database with contributor participation.
In dem Gebiet der Informationsextraktion angesiedelt kombiniert diese Arbeit mehrere Verfahren aus dem Bereich des maschinellen Lernens. Sie stellt einen neuen Algorithmus vor, der teil-überwachtes Lernen mit aktivem Lernen verknüpft. Ausgangsbasis ist die Analyse der Daten, indem sie in mehrere Sichten aufgeteilt werden. Hier werden die Eingaben verschiedener Personen unterteilt. Jeweils getrennt voneinander erzeugt der Algorithmus mittels Klassifizierern Modelle, die aus den individuellen Auszeichnungen der Personen aufgebaut werden. Um die dafür benötigte Datenmenge zu erhalten wird Crowdsourcing genutzt, dass es ermöglicht eine große Anzahl an Personen zu erreichen. Die Personen erhalten die Aufgabe, Texte zu annotieren. Einerseits wird dies initial für einen historischen Textkorpus vorgenommen. Dabei wird aufgeführt, welche Schritte notwendig sind, um die Annotationsaufgabe in Crowdsourcing-Portalen zur Bearbeitung anzubieten und durchzuführen. Andererseits wird ein aktueller Datensatz von Kurznachrichten genutzt. Der Algorithmus wird auf diese Beispieldatensätze angewandt. Durch Experimente wird die Ermittlung der optimalen Parameterauswahl durchgeführt. Außerdem werden die Ergebnisse mit den Resultaten bisheriger Algorithmen verglichen.
Im Rahmen eines Lehrforschungsprojekts setzten sich Studierende der Angewandten Geographie an der Universität Trier über zwei Semester in den Jahren 2016 und 2017 mit der Anpassung an den Klimawandel im Weinbau auseinander. Ziel des Lehrforschungsprojektes war es, besser zu verstehen wie Winzer*innen den Klimawandel wahrnehmen, welche Rolle der Klimawandel in (betrieblichen) Entscheidungen spielt und welche Anpassungspraktiken bereits beobachtbar sind.Der vorliegende Bericht fasst einige Ergebnisse der empirischen Untersuchung knapp zusammen.
Digitalisierung wirkt sich in radikaler Weise auf alle Lebensbereiche aus. Durch die technische Vernetzung und die Umwandlung analoger in digitale Daten entstehen umfassende Datenmengen. Aus ihrer Verknüpfung und Verarbeitung lassen sich Regelmäßigkeiten erkennen und Anwendungen generieren, deren soziale, ethische, politische, rechtliche, arbeitsweltliche und ökonomische Folgen heute noch nicht ansatzweise abzuschätzen sind.
La numérisation a des répercussions non négligeables sur tous les aspects de la vie. La mise en réseau technique et la conversion de données analogiques en données numériques sont à l’origine d’énormes quantités de données. Il est possible d’identifier des régularités dans leur mise en rapport et leur traitement, et de générer des applications dont les conséquences sociales, éthiques, politiques, juridiques, professionnelles et économiques sont encore difficiles à évaluer.
The dissertation includes three published articles on which the development of a theoretical model of motivational and self-regulatory determinants of the intention to comprehensively search for health information is based. The first article focuses on building a solid theoretical foundation as to the nature of a comprehensive search for health information and enabling its integration into a broader conceptual framework. Based on subjective source perceptions, a taxonomy of health information sources was developed. The aim of this taxonomy was to identify most fundamental source characteristics to provide a point of reference when it comes to relating to the target objects of a comprehensive search. Three basic source characteristics were identified: expertise, interaction and accessibility. The second article reports on the development and evaluation of an instrument measuring the goals individuals have when seeking health information: the ‘Goals Associated with Health Information Seeking’ (GAINS) questionnaire. Two goal categories (coping focus and regulatory focus) were theoretically derived, based on which four goals (understanding, action planning, hope and reassurance) were classified. The final version of the questionnaire comprised four scales representing the goals, with four items per scale (sixteen items in total). The psychometric properties of the GAINS were analyzed in three independent samples, and the questionnaire was found to be reliable and sufficiently valid as well as suitable for a patient sample. It was concluded that the GAINS makes it possible to evaluate goals of health information seeking (HIS) which are likely to inform the intention building on how to organize the search for health information. The third article describes the final development and a first empirical evaluation of a model of motivational and self-regulatory determinants of an intentionally comprehensive search for health information. Based on the insights and implications of the previous two articles and an additional rigorous theoretical investigation, the model included approach and avoidance motivation, emotion regulation, HIS self-efficacy, problem and emotion focused coping goals and the intention to seek comprehensively (as outcome variable). The model was analyzed via structural equation modeling in a sample of university students. Model fit was good and hypotheses with regard to specific direct and indirect effects were confirmed. Last, the findings of all three articles are synthesized, the final model is presented and discussed with regard to its strengths and weaknesses, and implications for further research are determined.
Das Grundgesetz ist keine bloße Neuauflage, sondern vielmehr eine Weiterentwicklung der Weimarer Reichsverfassung. Obwohl dem Namen nach gar keine „Verfassung“, wird das Grundgesetz spätestens seit der Wiedervereinigung nicht mehr als vorläufige, sondern als endgültige gesamtdeutsche Verfassung angesehen. Strikte Gewaltenteilung, Rechtsstaatlichkeit, umfassender Grundrechtsschutz und die Einführung der sog. „Ewigkeitsklausel“ (Art. 79 Abs. 3 GG) sind nur einige Elemente, mit denen „Bonn“ korrigierte, was „Weimar“ noch nicht vermochte. Nicht zuletzt die umfangreiche Rechtsprechung des Bundesverfassungsgerichts hat das Grundgesetz zu dem umfassenden Regelwerk gemacht, das nunmehr 70 Jahre ohne eine größere Verfassungskrise überdauert hat.
Die in dieser Ausgabe zusammengefassten Beiträge, die im Mai 2019 im Rahmen einer Festveranstaltung im Rokoko-Saal der Aufsichts- und Dienstleistungsdirektion in Trier gehalten wurden, beleuchten aus unterschiedlichen Perspektiven die Hintergründe der deutschen Verfassungsrechtsgeschichte und bieten eine Bestandsaufnahme über aktuelle Entwicklungen.
Laboratory landslide experiments enable the observation of specific properties of these natural hazards. However, these observations are limited by traditional techniques: frequently used high-speed video analysis and wired sensors (e.g. displacement). These techniques lead to the drawback that either only the surface and 2D profiles can be observed or wires confine the motion behaviour. In contrast, an unconfined observation of the total spatiotemporal dynamics of landslides is needed for an adequate understanding of these natural hazards.
The present study introduces an autonomous and wireless probe to characterize motion features of single clasts within laboratory-scale landslides. The Smartstone probe is based on an inertial measurement unit (IMU) and records acceleration and rotation at a sampling rate of 100 Hz. The recording ranges are ±16 g (accelerometer) and ±2000∘ s−1 (gyroscope). The plastic tube housing is 55 mm long with a diameter of 10 mm. The probe is controlled, and data are read out via active radio frequency identification (active RFID) technology. Due to this technique, the probe works under low-power conditions, enabling the use of small button cell batteries and minimizing its size.
Using the Smartstone probe, the motion of single clasts (gravel size, median particle diameter d50 of 42 mm) within approx. 520 kg of a uniformly graded pebble material was observed in a laboratory experiment. Single pebbles were equipped with probes and placed embedded and superficially in or on the material. In a first analysis step, the data of one pebble are interpreted qualitatively, allowing for the determination of different transport modes, such as translation, rotation and saltation. In a second step, the motion is quantified by means of derived movement characteristics: the analysed pebble moves mainly in the vertical direction during the first motion phase with a maximal vertical velocity of approx. 1.7 m s−1. A strong acceleration peak of approx. 36 m s−2 is interpreted as a pronounced hit and leads to a complex rotational-motion pattern. In a third step, displacement is derived and amounts to approx. 1.0 m in the vertical direction. The deviation compared to laser distance measurements was approx. −10 %. Furthermore, a full 3D spatiotemporal trajectory of the pebble is reconstructed and visualized supporting the interpretations. Finally, it is demonstrated that multiple pebbles can be analysed simultaneously within one experiment. Compared to other observation methods Smartstone probes allow for the quantification of internal movement characteristics and, consequently, a motion sampling in landslide experiments.
Estimation and therefore prediction -- both in traditional statistics and machine learning -- encounters often problems when done on survey data, i.e. on data gathered from a random subset of a finite population. Additional to the stochastic generation of the data in the finite population (based on a superpopulation model), the subsetting represents a second randomization process, and adds further noise to the estimation. The character and impact of the additional noise on the estimation procedure depends on the specific probability law for subsetting, i.e. the survey design. Especially when the design is complex or the population data is not generated by a Gaussian distribution, established methods must be re-thought. Both phenomena can be found in business surveys, and their combined occurrence poses challenges to the estimation.
This work introduces selected topics linked to relevant use cases of business surveys and discusses the role of survey design therein: First, consider micro-econometrics using business surveys. Regression analysis under the peculiarities of non-normal data and complex survey design is discussed. The focus lies on mixed models, which are able to capture unobserved heterogeneity e.g. between economic sectors, when the dependent variable is not conditionally normally distributed. An algorithm for survey-weighted model estimation in this setting is provided and applied to business data.
Second, in official statistics, the classical sampling randomization and estimators for finite population totals are relevant. The variance estimation of estimators for (finite) population totals plays a major role in this framework in order to decide on the reliability of survey data. When the survey design is complex, and the number of variables is large for which an estimated total is required, generalized variance functions are popular for variance estimation. They allow to circumvent cumbersome theoretical design-based variance formulae or computer-intensive resampling. A synthesis of the superpopulation-based motivation and the survey framework is elaborated. To the author's knowledge, such a synthesis is studied for the first time both theoretically and empirically.
Third, the self-organizing map -- an unsupervised machine learning algorithm for data visualization, clustering and even probability estimation -- is introduced. A link to Markov random fields is outlined, which to the author's knowledge has not yet been established, and a density estimator is derived. The latter is evaluated in terms of a Monte-Carlo simulation and then applied to real world business data.
In light of an alarming increase of sick leave and early retirement because of mental diseases, the public, political and scientific interest in an effective protection of psychological health within organizational context has been increasing for years. More and more the focus is especially on executives who influence the mental health of their employees by leadership behavior within interactions and by designing work tasks and working pro-cesses. In this regard classical and modern, explicit health-oriented leadership approaches provide valuable insights but also neglect the important influence of leadership situation on health-oriented leadership. This situation reduces the explanatory and predictive potential of available health-oriented leadership concepts.
In article 1 a conceptual framework model called Systemic Salutogenic Interaction Model (SSIM) is developed and justified that is based on findings of evidence-based leadership research but also integrates systemic concepts and key elements of the theory of saluto-genesis. The SSIM distinguishes between two levels: Within the primary system of salutogenic interaction salutogenic leadership and employees behavior for the first time are conceptualized as recipocal influence factors that influence each other (level 1). The organizational context is explicitly taken into account as significant factor outside the primary system that effects the behavior of both interaction partners mediated via cognitive pro-cesses (level 2). Due to this focus on interactions und context factors for the first time leadership situation becomes an explicit component of a health-oriented leadership concept.
First of all, article 2 focusses on the systematic analysis of the relative importance health related leadership aspects. For this purpose the TIMP-inventory was developed that records three distinct core-factors of salutogenic leadership (trust, incident management and pressure) which explain more variance of the Work-SoC construct than established general approaches and health-related leadership concepts.
In article 3 the results of a cross-sectional multilevel analysis indicate that the perceived leadership situation significantly explains variance of salutogenic leadership between teams. For the first time, this shows a significant correlation between specific aspects of leadership situation und salutogenic leadership behavior.
Within the frame of a quasi-experimental study (article 4), for the first time, a correlation is shown between salutogenic target-setting processes on executive’s side and the Work-SoC of team members. These results support an essential effect mechanism that is postulated in the SSIM. Furthermore these findings indicate that the SSIM can profitably be used within the context of salutogenic coachings, underlining its practical benefit.
Taken together the empirical findings of this dissertation support the assumption that the new SSIM approach significantly expands the explanatory und predictive potential of the health-oriented leadership concepts so far available. The results also raise a number of new, interesting questions for future research. Furthermore the SSIM broadens the perspective regarding the strategic orientation of human resource and organizational devel-opment. Especially out of the SSIM important guiding principles and innovative concepts for a target-oriented diagnostic und effective interventions can be derived. Thus this dissertation lays the foundation for a coherent, holistic oriented salutogenic leadership research und practice.