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(2013)
Bei der hier vorgestellten Anwendung handelt es sich um den Prototypen einer webbasierten Applikation zur Analyse von Nutzungsdaten der AnwenderInnen von eLearning-Angeboten. Die Applikation wurde dabei explizit für unterschiedliche Zielgruppen wie eLearning-AnbieterInnen, Lehrende und WissenschaftlerInnen entworfen. Die Anwendung kann Daten verschiedener Lernplattformen auswerten und nutzt hierbei Methoden des Educational Data Mining. Sie unterstützt dabei sowohl klassische Plattformen mit personalisiertem Zugang sowie offene Plattformen, deren Angebote ohne Registrierung zugänglich sind.
Problem solving is one of the central activities performed by computer scientists as well as by computer science learners. Whereas the teaching of algorithms and programming languages is usually well structured within a curriculum, the development of learners’ problem-solving skills is largely implicit and less structured. Students at all levels often face difficulties in problem analysis and solution construction. The basic assumption of the workshop is that without some formal instruction on effective strategies, even the most inventive learner may resort to unproductive trial-and-error problemsolving processes. Hence, it is important to teach problem-solving strategies and to guide teachers on how to teach their pupils this cognitive tool. Computer science educators should be aware of the difficulties and acquire appropriate pedagogical tools to help their learners gain and experience problem-solving skills.
This thesis rests on two large Active Galactic Nuclei (AGNs) surveys. The first survey deals with galaxies that host low-level AGNs (LLAGN) and aims at identifying such galaxies by quantifying their variability. While numerous studies have shown that AGNs can be variable at all wavelengths, the nature of the variability is still not well understood. Studying the properties of LLAGNs may help to understand better galaxy evolution, and how AGNs transit between active and inactive states. In this thesis, we develop a method to extract variability properties of AGNs. Using multi-epoch deep photometric observations, we subtract the contribution of the host galaxy at each epoch to extract variability and estimate AGN accretion rates. This pipeline will be a powerful tool in connection with future deep surveys such as PANSTARS. The second study in this thesis describes a survey of X-ray selected AGN hosts at redshifts z>1.5 and compares them to quiescent galaxies. This survey aims at studying environments, sizes and morphologies of star-forming high-redshift AGN hosts in the COSMOS Survey at the epoch of peak AGN activity. Between redshifts 1.5<z<3.8, the COSMOS HST/ACS imaging probes the UV regime, where separating the AGN flux from its host galaxy is very challenging. Nevertheless, we successfully derived the structural properties of 249 AGN hosts using two-dimensional surface-brightness profile fitting with the GALFIT package. This is the largest sample of AGN hosts at redshift z>1.5 to date. We analyzed the evolution of structural parameters of AGN and non-AGN host galaxies with redshift, and compared their disturbance rates to identify the more probable AGN triggering mechanism in the 43.5<log_10 L_X<45 luminosity range. We also conducted mock AGN and quiescent galaxies observations to determine errors and corrections for the derived parameters. We find that the size-absolute magnitude relations of AGN hosts and non-AGN galaxies are very similar, with estimated mean sizes in both samples decreasing by ~50% between redshifts z=1.5 and z=3.5. Morphological classification of both active and quiescent galaxies shows that the majority of the AGN host galaxies are disc-dominated, with disturbance rates that are significantly lower than among the non-AGN galaxies. Such a finding suggests that Major Mergers are probably not responsible for triggering AGN accretion in most of these galaxies. Other secular mechanisms should therefore be responsible.
In the context of ecological risk assessment of chemicals, individual-based population models hold great potential to increase the ecological realism of current regulatory risk assessment procedures. However, developing and parameterizing such models is time-consuming and often ad hoc. Using standardized, tested submodels of individual organisms would make individual-based modelling more efficient and coherent. In this thesis, I explored whether Dynamic Energy Budget (DEB) theory is suitable for being used as a standard submodel in individual-based models, both for ecological risk assessment and theoretical population ecology. First, I developed a generic implementation of DEB theory in an individual-based modeling (IBM) context: DEB-IBM. Using the DEB-IBM framework I tested the ability of the DEB theory to predict population-level dynamics from the properties of individuals. We used Daphnia magna as a model species, where data at the individual level was available to parameterize the model, and population-level predictions were compared against independent data from controlled population experiments. We found that DEB theory successfully predicted population growth rates and peak densities of experimental Daphnia populations in multiple experimental settings, but failed to capture the decline phase, when the available food per Daphnia was low. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detecting gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. In addition to theoretical explorations, we tested the potential of DEB theory combined with IBMs to extrapolate effects of chemical stress from the individual to population level. For this we used information at the individual level on the effect of 3,4-dichloroanailine on Daphnia. The individual data suggested direct effects on reproduction but no significant effects on growth. Assuming such direct effects on reproduction, the model was able to accurately predict the population response to increasing concentrations of 3,4-dichloroaniline. We conclude that DEB theory combined with IBMs holds great potential for standardized ecological risk assessment based on ecological models.