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Distanzvektor-Routing-Protokolle sind Interior-Gateway-Protokolle, bei denen jeder Router anhand der Informationen, die er von seinen Nachbarn erhält, eine Routingtabelle mit den kürzesten Wegen und dazugehörigen Kosten zu allen anderen Routern des Netzwerks aufbaut. Distanzvektor-Routing-Protokolle sehen jedoch nur unzureichende Mechanismen vor, um die Sicherheit ihrer Operationen zu gewährleisten. Es wird vielmehr einfach davon ausgegangen, dass die Umgebung vertrauenswürdig ist. Router können sich aber aus verschiedenen Gründen böswillig verhalten und falsche Routingupdates einschleusen um das Routing zu manipulieren. Authentizität und Integrität der übermittelten Routinginformationen müssen daher sichergestellt werden; dabei soll eine Balance zwischen Nutzen und Performance gefunden werden.
Diese Arbeit untersucht verschiedene Lösungsansätze, die sich die Erfüllung dieser Anforderungen zum Ziel gesetzt haben, und stellt deren Vor- und Nachteile einander gegenüber.
Confidentiality, integrity, and availability are often listed as the three major requirements for achieving data security and are collectively referred to as the C-I-A triad. Confidentiality of data restricts the data access to authorized parties only, integrity means that the data can only be modified by authorized parties, and availability states that the data must always be accessible when requested. Although these requirements are relevant for any computer system, they are especially important in open and distributed networks. Such networks are able to store large amounts of data without having a single entity in control of ensuring the data's security. The Semantic Web applies to these characteristics as well as it aims at creating a global and decentralized network of machine-readable data. Ensuring the confidentiality, integrity, and availability of this data is therefore also important and must be achieved by corresponding security mechanisms. However, the current reference architecture of the Semantic Web does not define any particular security mechanism yet which implements these requirements. Instead, it only contains a rather abstract representation of security.
This thesis fills this gap by introducing three different security mechanisms for each of the identified security requirements confidentiality, integrity, and availability of Semantic Web data. The mechanisms are not restricted to the very basics of implementing each of the requirements and provide additional features as well. Confidentiality is usually achieved with data encryption. This thesis not only provides an approach for encrypting Semantic Web data, it also allows to search in the resulting ciphertext data without decrypting it first. Integrity of data is typically implemented with digital signatures. Instead of defining a single signature algorithm, this thesis defines a formal framework for signing arbitrary Semantic Web graphs which can be configured with various algorithms to achieve different features. Availability is generally supported by redundant data storage. This thesis expands the classical definition of availability to compliant availability which means that data must only be available as long as the access request complies with a set of predefined policies. This requirement is implemented with a modular and extensible policy language for regulating information flow control. This thesis presents each of these three security mechanisms in detail, evaluates them against a set of requirements, and compares them with the state of the art and related work.
Binnengewässer spielen eine aktive Rolle im globalen Kohlenstoffkreislauf. Sie nehmen Kohlenstoff von stromaufwärts gelegenen Landmassen auf und transportieren ihn stromabwärts, bis er schließlich den Ozean erreicht. Auf diesem Weg sind vielfältige Prozesse zu beobachten, die zu einer (dauerhaften) Rückhaltung des Kohlenstoffs durch Einlagerung in Sedimenten sowie zu direkter Emission in die Atmosphäre führen. Es ist dringend notwendig diese Kohlenstoffflüsse und ihre anthropogene Veränderung zu quantifizieren. In diesem Zusammenhang muss die Aufmerksamkeit auf ein weit verbreitetes Merkmal von Gewässern gerichtet werden: ihre teilweise Austrocknung. Dies führt dazu, dass ehemals überschwemmte Sedimente in direkten Kontakt mit der Atmosphäre gelangen, genannt „dry inland waters“. Ein Merkmal der „dry inland waters“ sind überproportional hohe Kohlendioxid (CO2)-Emissionen. Diese Erkenntnis beruhte jedoch bisher auf lokalen Fallstudien, und es fehlt an Wissen über die globale Verbreitung und die grundlegenden Mechanismen dieser Emissionen. Vor diesem Hintergrund zielt diese Arbeit darauf ab, das Ausmaß und die Mechanismen der Kohlenstoffemissionen der „dry inland waters“ auf globaler und lokaler Ebene besser zu verstehen und die Auswirkungen von „dry inland waters“ auf den globalen Kohlenstoffkreislauf zu bewerten. Die spezifischen Forschungsfragen dieser Arbeit lauteten: (1) Wie fügen sich gasförmige Kohlenstoffemissionen von „dry inland waters“ in den globalen Kohlenstoffkreislauf und in die globalen Treibhausgasbudgets ein? (2) Welche Auswirkungen haben saisonale und langfristige Austrocknung auf den Kohlenstoffkreislauf von Gewässern? Diese Arbeit hat gezeigt, dass „dry inland waters“im globalen Maßstab unverhältnismäßig große Mengen an CO2 emittieren und dass diese Emissionen in allen Ökosystemen vergleichbaren Mechanismen folgen. Die Quantifizierung der globalen Wasserstandsschwankungen in Stauseen und die globale Berechnung der Kohlenstoffflüsse legen nahe, dass Stauseen mehr Kohlenstoff freisetzen als sie in den Sedimenten einlagern, was das derzeitige Verständnis von Stauseen als Nettokohlenstoffsenken in Frage stellt. Auf lokaler Ebene hat diese Arbeit gezeigt, dass sowohl die heterogenen Emissionsmuster verschiedener typischer Uferbereiche als auch die saisonalen Schwankungen der Kohlenstoffemissionen aus der „drawdown area“ berücksichtigt werden müssen. Darüber hinaus hat diese Arbeit gezeigt, dass die Remobilisierung von Kohlenstoff aus den Sedimenten bei dauerhafter Austrocknung von Gewässern die beobachteten Emissionsraten erklären kann, was die Hypothese einer positiven Rückkopplung zwischen Klimawandel und der Austrocknung von Gewässern unterstützt. Insgesamt unterstreicht die vorliegende Arbeit die Bedeutung der Emissionen aus trockenen Gewässerbereichen für den globalen Kohlenstoffkreislauf von Gewässern.
Although most plastic pollution originates on land, current research largely remains focused on aquatic ecosystems. Studies pioneering terrestrial microplastic research have adapted analytical methods from aquatic research without acknowledging the complex nature of soil. Meanwhile, novel methods have been developed and further refined. However, methodical inconsistencies still challenge a comprehensive understanding of microplastic occurrence and fate in and on soil. This review aims to disentangle the variety of state-of-the-art sample preparation techniques for heterogeneous solid matrices to identify and discuss best-practice methods for soil-focused microplastic analyses. We show that soil sampling, homogenization, and aggregate dispersion are often neglected or incompletely documented. Microplastic preconcentration is typically performed by separating inorganic soil constituents with high-density salt solutions. Not yet standardized but currently most used separation setups involve overflowing beakers to retrieve supernatant plastics, although closed-design separation funnels probably reduce the risk of contamination. Fenton reagent may be particularly useful to digest soil organic matter if suspected to interfere with subsequent microplastic quantification. A promising new approach is extraction of target polymers with organic solvents. However, insufficiently characterized soils still impede an informed decision on optimal sample preparation. Further research and method development thus requires thorough validation and quality control with well-characterized matrices to enable robust routine analyses for terrestrial microplastics.
Das Internet der Dinge (IoT) ist ein Konzept, bestehend aus vernetzten physischen Objekten, welche in die virtuelle Welt integriert werden um aktive Teilnehmer von Geschäfts- und Alltagsprozessen zu werden (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). Es wird erwartet, dass dieses Konzept einen großen Einfluss auf Unternehmen haben wird (Council, Nic and Intelligence, 2008). Geschäftsmodelle kleiner und mittelständischer Unternehmen (KMU) sind bedroht, sollten sie den sich abzeichnenden Trend nutzen (Sommer, 2015). Daher ist das Ziel dieser Arbeit, eine exemplarische Implementierung von vernetzten Geräten in einem kleinen Unternehmen um seine Vorteile darzustellen.
Diese Arbeit verwendet Design Science Research (DSR) um einen Prototyp zu entwickeln, der auf dem Anwendungsfall einer Holzwerkstatt aufbaut. Der Prototyp besteht aus einem physischen Sensor und einer Webapplikation, welche von dem kleinen Unternehmen zur Verbesserung seiner Prozesse genutzt werden kann. Die Arbeit dokumentiert den iterativen Entwicklungsprozess der Prototypen von Grund auf zu nutzbarer Hard- und Software.
Der Hauptbeitrag dieser Arbeit ist die beispielhafte Anwendung und Nutzung von IoT in einem kleinen Unternehmen.
The increasing, anthropogenic demand for chemicals has created large environmental problems with repercussions for the health of the environment, especially aquatic ecosystems. As a result, the awareness of the public and decision makers on the risks from chemical pollution has increased over the past half-century, prompting a large number of studies in the field of ecological toxicology (ecotoxicology). However, the majority of ecotoxicological studies are laboratory based, and the few studies extrapolating toxicological effects in the field are limited to local and regional levels. Chemical risk assessment on large spatial scales remains largely unexplored, and therefore, the potential large-scale effects of chemicals may be overlooked.
To answer ecotoxicological questions, multidisciplinary approaches that transcend classical chemical and toxicological concepts are required. For instance, the current models for toxicity predictions - which are mainly based on the prediction of toxicity for a single compound and species - can be expanded to simultaneously predict the toxicity for different species and compounds. This can be done by integrating chemical concepts such as the physicochemical properties of the compounds with evolutionary concepts such as the similarity of species. This thesis introduces new, multidisciplinary tools for chemical risk assessments, and presents for the first time a chemical risk assessment on the continental scale.
After a brief introduction of the main concepts and objectives of the studies, this thesis starts by presenting a new method for assessing the physiological sensitivity of macroinvertebrate species to heavy metals (Chapter 2). To compare the sensitivity of species to different heavy metals, toxicity data were standardized to account for the different laboratory conditions. These rankings were not significantly different for different heavy metals, allowing the aggregation of physiological sensitivity into a single ranking.
Furthermore, the toxicological data for macroinvertebrates were used as input data to develop and validate prediction models for heavy metal toxicity, which are currently lacking for a wide array of species (Chapter 3). Apart from the toxicity data, the phylogenetic information of species (evolutionary relationships among species) and the physicochemical parameters for heavy metals were used. The constructed models had a good explanatory power for the acute sensitivity of species to heavy metals with the majority of the explained variance attributed to phylogeny. Therefore, the integration of evolutionary concepts (relatedness and similarity of species) with the chemical parameters used in ecotoxicology improved prediction models for species lacking experimental toxicity data. The ultimate goal of the prediction models developed in this thesis is to provide accurate predictions of toxicity for a wide range of species and chemicals, which is a crucial prerequisite for conducting chemical risk assessment.
The latter was conducted for the first time on the continental scale (Chapter 4), by making use of a dataset of 4,000 sites distributed throughout 27 European countries and 91 respective river basins. Organic chemicals were likely to exert acute risks for one in seven sites analyzed, while chronic risk was prominent for almost half of the sites. The calculated risks are potentially underestimated by the limited number of chemicals that are routinely analyzed in monitoring programmes, and a series of other uncertainties related with the limit of quantification, the presence of mixtures, or the potential for sublethal effects not covered by direct toxicity.
Furthermore, chemical risk was related to agricultural and urban areas in the upstream catchments. The analysis of ecological data indicated chemical impacts on the ecological status of the river systems; however, it is difficult to discriminate the effects of chemical pollution from other stressors that river systems are exposed to. To test the hypothesis of multiple stressors, and investigate the relative importance of organic toxicants, a dataset for German streams is used in chapter 5. In that study, the risk from abiotic (habitat degradation, organic chemicals, and nutrients enrichment) and biotic stressors (invasive species) was investigated. The results indicated that more than one stressor influenced almost all sites. Stream size and ecoregions influenced the distribution of risks, e.g., the risks for habitat degradation, organic chemicals and invasive species increased with the stream size; whereas organic chemicals and nutrients were more likely to influence lowland streams. In order to successfully mitigate the effects of pollutants in river systems, co-occurrence of stressors has to be considered. Overall, to successfully apply integrated water management strategies, a framework involving multiple environmental stressors on large spatial scales is necessary. Furthermore, to properly address the current research needs in ecotoxicology, a multidisciplinary approach is necessary which integrates fields such as, toxicology, ecology, chemistry and evolutionary biology.
Statistical Shape Models (SSMs) are one of the most successful tools in 3Dimage analysis and especially medical image segmentation. By modeling the variability of a population of training shapes, the statistical information inherent in such data are used for automatic interpretation of new images. However, building a high-quality SSM requires manually generated ground truth data from clinical experts. Unfortunately, the acquisition of such data is a time-consuming, error-prone and subjective process. Due to this effort, the majority of SSMs is often based on a limited set of this ground truth training data, which makes the models less statistically meaningful. On the other hand, image data itself is abundant in clinics from daily routine. In this work, methods for automatically constructing a reliable SSM without the need of manual image interpretation from experts are proposed. Thus, the training data is assumed to be the result of any segmentation algorithm or may originate from other sources, e.g. non-expert manual delineations. Depending on the algorithm, the output segmentations will contain errors to a higher or lower degree. In order to account for these errors, areas of low probability of being a boundary should be excluded from the training of the SSM. Therefore, the probabilities are estimated with the help of image-based approaches. By including many shape variations, the corrupted parts can be statistically reconstructed. Two approaches for reconstruction are proposed - an Imputation method and Weighted Robust Principal Component Analysis (WRPCA). This allows the inclusion of many data sets from clinical routine, covering a lot more variations of shape examples. To assess the quality of the models, which are robust against erroneous training shapes, an evaluation compares the generalization and specificity ability to a model build from ground truth data. The results show, that especially WRPCA is a powerful tool to handle corrupted parts and yields to reasonable models, which have a higher quality than the initial segmentations.
This paper describes the robots TIAGo and Lisa used by
team homer@UniKoblenz of the University of Koblenz-Landau, Germany,
for the participation at the RoboCup@Home 2019 in Sydney,
Australia. We ended up first at RoboCup@Home 2019 in the Open Platform
League and won the competition in our league now three times
in a row (four times in total) which makes our team the most successful
in RoboCup@Home. We demonstrated approaches for learning from
demonstration, touch enforcing manipulation and autonomous semantic
exploration in the finals. A special focus is put on novel system components
and the open source contributions of our team. We have released
packages for object recognition, a robot face including speech synthesis,
mapping and navigation, speech recognition interface, gesture recognition
and imitation learning. The packages are available (and new packages
will be released) on http://homer.uni-koblenz.de.
This paper describes the robots TIAGo and Lisa used by team homer@UniKoblenz of the University of Koblenz-Landau, Germany, for the participation at the RoboCup@Home 2018 in Montreal, Canada. Further this paper serves as qualification material for the RoboCup-@Home participation in 2018. A special focus is put on novel system components and the open source contributions of our team. This year the team from Koblenz won the biggest annual scientianc robot competition in Montreal in the RoboCup@Home Open Platform track for the third time and also won the RoboCup@Home German Open for the second time. As a research highlight a novel symbolic imitation learning approach was demonstrated during the annals. The TIAGo robotic research platform was used for the first time by the team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg. Further information can be found on our project page http://homer.uni-koblenz.de.
This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2017 in Nagoya, Japan. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on
http://wiki.ros.org/agas-ros-pkg.