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This Thesis was devoted to the study of the coupled system composed by El Niño/Southern Oscillation and the Annual Cycle. More precisely, the work was focused on two main problems: 1. How to separate both oscillations into an affordable model for understanding the behaviour of the whole system. 2. How to model the system in order to achieve a better understanding of the interaction, as well as to predict future states of the system. We focused our efforts in the Sea Surface Temperature equations, considering that atmospheric effects were secondary to the ocean dynamics. The results found may be summarised as follows: 1. Linear methods are not suitable for characterising the dimensionality of the sea surface temperature in the tropical Pacific Ocean. Therefore they do not help to separate the oscillations by themselves. Instead, nonlinear methods of dimensionality reduction are proven to be better in defining a lower limit for the dimensionality of the system as well as in explaining the statistical results in a more physical way [1]. In particular, Isomap, a nonlinear modification of Multidimensional Scaling methods, provides a physically appealing method of decomposing the data, as it substitutes the euclidean distances in the manifold by an approximation of the geodesic distances. We expect that this method could be successfully applied to other oscillatory extended systems and, in particular, to meteorological systems. 2. A three dimensional dynamical system could be modeled, using a backfitting algorithm, for describing the dynamics of the sea surface temperature in the tropical Pacific Ocean. We observed that, although there were few data points available, we could predict future behaviours of the coupled ENSO-Annual Cycle system with an accuracy of less than six months, although the constructed system presented several drawbacks: few data points to input in the backfitting algorithm, untrained model, lack of forcing with external data and simplification using a close system. Anyway, ensemble prediction techniques showed that the prediction skills of the three dimensional time series were as good as those found in much more complex models. This suggests that the climatological system in the tropics is mainly explained by ocean dynamics, while the atmosphere plays a secondary role in the physics of the process. Relevant predictions for short lead times can be made using a low dimensional system, despite its simplicity. The analysis of the SST data suggests that nonlinear interaction between the oscillations is small, and that noise plays a secondary role in the fundamental dynamics of the oscillations [2]. A global view of the work shows a general procedure to face modeling of climatological systems. First, we should find a suitable method of either linear or nonlinear dimensionality reduction. Then, low dimensional time series could be extracted out of the method applied. Finally, a low dimensional model could be found using a backfitting algorithm in order to predict future states of the system.
The separation of natural and anthropogenically caused climatic changes is an important task of contemporary climate research. For this purpose, a detailed knowledge of the natural variability of the climate during warm stages is a necessary prerequisite. Beside model simulations and historical documents, this knowledge is mostly derived from analyses of so-called climatic proxy data like tree rings or sediment as well as ice cores. In order to be able to appropriately interpret such sources of palaeoclimatic information, suitable approaches of statistical modelling as well as methods of time series analysis are necessary, which are applicable to short, noisy, and non-stationary uni- and multivariate data sets. Correlations between different climatic proxy data within one or more climatological archives contain significant information about the climatic change on longer time scales. Based on an appropriate statistical decomposition of such multivariate time series, one may estimate dimensions in terms of the number of significant, linear independent components of the considered data set. In the presented work, a corresponding approach is introduced, critically discussed, and extended with respect to the analysis of palaeoclimatic time series. Temporal variations of the resulting measures allow to derive information about climatic changes. For an example of trace element abundances and grain-size distributions obtained near the Cape Roberts (Eastern Antarctica), it is shown that the variability of the dimensions of the investigated data sets clearly correlates with the Oligocene/Miocene transition about 24 million years before present as well as regional deglaciation events. Grain-size distributions in sediments give information about the predominance of different transportation as well as deposition mechanisms. Finite mixture models may be used to approximate the corresponding distribution functions appropriately. In order to give a complete description of the statistical uncertainty of the parameter estimates in such models, the concept of asymptotic uncertainty distributions is introduced. The relationship with the mutual component overlap as well as with the information missing due to grouping and truncation of the measured data is discussed for a particular geological example. An analysis of a sequence of grain-size distributions obtained in Lake Baikal reveals that there are certain problems accompanying the application of finite mixture models, which cause an extended climatological interpretation of the results to fail. As an appropriate alternative, a linear principal component analysis is used to decompose the data set into suitable fractions whose temporal variability correlates well with the variations of the average solar insolation on millenial to multi-millenial time scales. The abundance of coarse-grained material is obviously related to the annual snow cover, whereas a significant fraction of fine-grained sediments is likely transported from the Taklamakan desert via dust storms in the spring season.
The ultimate aim of this study is to better understand the relevance of weak electricity in the adaptive radiation of the African mormyrid fish. The chosen model taxon, the genus Campylomormyrus, exhibits a wide diversity of electric organ discharge (EOD) waveform types. Their EOD is age, sex, and species specific and is an important character for discriminating among species that are otherwise cryptic. After having established a complementary set of molecular markers, I examined the radiation of Campylomormyrus by a combined approach of molecular data (sequence data from the mitochondrial cytochrome b and the nuclear S7 ribosomal protein gene, as well as 18 microsatellite loci, especially developed for the genus Campylomormyrus), observation of ontogeny and diversification of EOD waveform, and morphometric analysis of relevant morphological traits. I built up the first convincing phylogenetic hypothesis for the genus Campylomormyrus. Taking advantage of microsatellite data, the identified phylogenetic clades proved to be reproductively isolated biological species. This way I detected at least six species occurring in sympatry near Brazzaville/Kinshasa (Congo Basin). By combining molecular data and EOD analyses, I could show that there are three cryptic species, characterised by their own adult EOD types, hidden under a common juvenile EOD form. In addition, I confirmed that adult male EOD is species-specific and is more different among closely related species than among more distantly related ones. This result and the observation that the EOD changes with maturity suggest its function as a reproductive isolation mechanism. As a result of my morphometric shape analysis, I could assign species types to the identified reproductively isolated groups to produce a sound taxonomy of the group. Besides this, I could also identify morphological traits relevant for the divergences between the identified species. Among them, the variations I found in the shape of the trunk-like snout, suggest the presence of different trophic specializations; therefore, this trait might have been involved in the ecological radiation of the group. In conclusion, I provided a convincing scenario envisioning an adaptive radiation of weakly electric fish triggered by sexual selection via assortative mating due to differences in EOD characteristics, but caused by a divergent selection of morphological traits correlated with the feeding ecology.
This thesis discusses challenges in IT security education, points out a gap between e-learning and practical education, and presents a work to fill the gap. E-learning is a flexible and personalized alternative to traditional education. Nonetheless, existing e-learning systems for IT security education have difficulties in delivering hands-on experience because of the lack of proximity. Laboratory environments and practical exercises are indispensable instruction tools to IT security education, but security education in conventional computer laboratories poses particular problems such as immobility as well as high creation and maintenance costs. Hence, there is a need to effectively transform security laboratories and practical exercises into e-learning forms. In this thesis, we introduce the Tele-Lab IT-Security architecture that allows students not only to learn IT security principles, but also to gain hands-on security experience by exercises in an online laboratory environment. In this architecture, virtual machines are used to provide safe user work environments instead of real computers. Thus, traditional laboratory environments can be cloned onto the Internet by software, which increases accessibility to laboratory resources and greatly reduces investment and maintenance costs. Under the Tele-Lab IT-Security framework, a set of technical solutions is also proposed to provide effective functionalities, reliability, security, and performance. The virtual machines with appropriate resource allocation, software installation, and system configurations are used to build lightweight security laboratories on a hosting computer. Reliability and availability of laboratory platforms are covered by a virtual machine management framework. This management framework provides necessary monitoring and administration services to detect and recover critical failures of virtual machines at run time. Considering the risk that virtual machines can be misused for compromising production networks, we present a security management solution to prevent the misuse of laboratory resources by security isolation at the system and network levels. This work is an attempt to bridge the gap between e-learning/tele-teaching and practical IT security education. It is not to substitute conventional teaching in laboratories but to add practical features to e-learning. This thesis demonstrates the possibility to implement hands-on security laboratories on the Internet reliably, securely, and economically.