Austria e Ungaria

Kartalla myös: Alla libraria de l'insegna del S. Marco Donato Bertelli domenego

Propability of bark stripping damage by red deer (Cervus elaphus) in Austria

Abstract

Mobile robot localization using sonar ranging and wlan intensity maps

 Main goal of this thesis was to implement a localization system which uses sonars and WLAN intensity maps to localize an indoor mobile robot. A probabilistic localization method, Monte Carlo Localization is used in localization. Also the theory behind probabilistic localization is explained. Two main problems in mobile robotics, path tracking and global localization, are solved in this thesis. Implemented system can achieve acceptable performance in path tracking. Global localization using WLAN received signal strength information is shown to provide good results, which can be used to localize the robot accurately, but also some bad results, which are no use when trying to localize the robot to the correct place. Main goal of solving ambiguity in office like environment is achieved in many test cases.

Distortion properties of quasiconformal maps

In this Licentiate thesis we investigate the absolute ratio δ, j, ˜j and hyperbolic ρ metrics and their relations with each other. Various growth estimates are given for quasiconformal mpas both in plane and space. Some Hölder constants were refined with respect δ, j ˜j metrics. Some new results regarding the Hölder continuity of quasiconformal and quasiregular mapping of unit ball with respect to Euclidean and hyperbolic metrics are given, which were obtained by many authors in 1980’s. Applications are given to the study of metric space, quasiconformal and quasiregular maps in the plane and as well as in the space.

2014 Census of Open Access Repositories in Germany, Austria and Switzerland

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Macroalgae across environmental gradients : tools for managing rocky coastal areas of the northern Baltic Sea

Macroalgae are the main primary producers of the temperate rocky shores providing a three-dimensional habitat, food and nursery grounds for many other species. During the past decades, the state of the coastal waters has deteriorated due to increasing human pressures, resulting in dramatic changes in coastal ecosystems, including macroalgal communities. To reverse the deterioration of the European seas, the EU has adopted the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD), aiming at improved status of the coastal waters and the marine environment. Further, the Habitats Directive (HD) calls for the protection of important habitats and species (many of which are marine) and the Maritime Spatial Planning Directive for sustainability in the use of resources and human activities at sea and by the coasts. To efficiently protect important marine habitats and communities, we need knowledge on their spatial distribution. Ecological knowledge is also needed to assess the status of the marine areas by involving biological indicators, as required by the WFD and the MSFD; knowledge on how biota changes with human-induced pressures is essential, but to reliably assess change, we need also to know how biotic communities vary over natural environmental gradients. This is especially important in sea areas such as the Baltic Sea, where the natural environmental gradients create substantial differences in biota between areas. In this thesis, I studied the variation occurring in macroalgal communities across the environmental gradients of the northern Baltic Sea, including eutrophication induced changes. The aim was to produce knowledge to support the reliable use of macroalgae as indicators of ecological status of the marine areas and to test practical metrics that could potentially be used in status assessments. Further, the aim was to develop a methodology for mapping the HD Annex I habitat reefs, using the best available data on geology and bathymetry. The results showed that the large-scale variation in the macroalgal community composition of the northern Baltic Sea is largely driven by salinity and exposure. Exposure is important also on smaller spatial scales, affecting species occurrence, community structure and depth penetration of algae. Consequently, the natural variability complicates the use of macroalgae as indicators of human-induced changes. Of the studied indicators, the number of perennial algal species, the perennial cover, the fraction of annual algae, and the lower limit of occurrence of red and brown perennial algae showed potential as usable indicators of ecological status. However, the cumulated cover of algae, commonly used as an indicator in the fully marine environments, showed low responses to eutrophication in the area. Although the mere occurrence of perennial algae did not show clear indicator potential, a distinct discrepancy in the occurrence of bladderwrack, Fucus vesiculosus, was found between two areas with differing eutrophication history, the Bothnian Sea and the Archipelago Sea. The absence of Fucus from many potential sites in the outer Archipelago Sea is likely due to its inability to recover from its disappearance from the area 30-40 years ago, highlighting the importance of past events in macroalgal occurrence. The methodology presented for mapping the potential distribution and the ecological value of reefs showed, that relatively high accuracy in mapping can be achieved by combining existing available data, and the maps produced serve as valuable background information for more detailed surveys. Taken together, the results of the theses contribute significantly to the knowledge on macroalgal communities of the northern Baltic Sea that can be directly applied in various management contexts.

Online peer to peer lending: clustering borrowers using self-organizing maps

The purpose of this thesis is to find out whether all the peer to peer lenders are unworthy of credit and also if there are single qualities or combinations of qualities that determine the probability of default of a person or group of people. Distinguishing qualities are searched with self-organizing maps (SOM). Qualities and groups of people found by the self-organizing map are then compared to the average. The comparison is carried out by looking how big proportion of borrowers meeting the criteria is two months or more behind with their payments. Research data used is collected by an Estonian peer to peer lending company during the years of 2011-2014. Data consists of peer to peer borrowers and information gathered from them.

Opera di M. Giacomo Gastaldi Piamontese cosmografo in Venetia disegno, particolare de regni e regioni, che son da Venetia, a Constantinopoli, et da Constantinopoli, a Vienna, d'Austria et da Vienna ..

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Opera di M. Giacomo Gastaldi Piamontese cosmografo in Venetia disegno, particolare de regni e regioni, che son da Venetia, a Constantinopoli, et da Constantinopoli, a Vienna, d'Austria et da Vienna ..

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.