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Koblenz, Germany

The University of Koblenz and Landau is a university located in Koblenz and Landau, Germany. It was founded in 1990. Wikipedia.

Thimm M.,University of Koblenz-Landau
International Journal of Approximate Reasoning | Year: 2016

Inconsistency measures have been proposed to assess the severity of inconsistencies in knowledge bases of classical logic in a quantitative way. In general, computing the value of inconsistency is a computationally hard task as it is based on the satisfiability problem which is itself NP-complete. In this work, we address the problem of measuring inconsistency in knowledge bases that are accessed in a stream of propositional formulæ. That is, the formulæ of a knowledge base cannot be accessed directly but only once through processing of the stream. This work is a first step towards practicable inconsistency measurement for applications such as Linked Open Data, where huge amounts of information is distributed across the web and a direct assessment of the quality or inconsistency of this information is infeasible due to its size. Here we discuss the problem of stream-based inconsistency measurement on classical logic, in order to make use of existing measures for classical logic. However, it turns out that inconsistency measures defined on the notion of minimal inconsistent subsets are usually not apt to be used in the streaming scenario. In order to address this issue, we adapt measures defined on paraconsistent logics and also present a novel inconsistency measure based on the notion of a hitting set. We conduct an extensive empirical analysis on the behavior of these different inconsistency measures in the streaming scenario, in terms of runtime, accuracy, and scalability. We conclude that for two of these measures, the stream-based variant of the new inconsistency measure and the stream-based variant of the contension inconsistency measure, large-scale inconsistency measurement in streaming scenarios is feasible. © 2015 Elsevier Inc. All rights reserved.

Both genetic cohesion among local populations of animals and range expansion depend on the frequency of dispersers moving at an interpatch scale. Animal movement has an individual component that reflects behaviour and an ecological component that reflects the spatial organization of populations. The total movement capacity of an individual describes maximum movement distance theoretically achievable during a lifetime, whereas its variation among the members of a local population determines the magnitude of interpatch movements and thus of gene flow between neighbouring patches within metapopulation or patchy population systems. Here, I review information on dispersal and migration as components of the movement capacity of juvenile and adult pond-breeding amphibians and discuss how these components inform the spatial structure of populations. Amphibians disperse as juveniles and adults, but movement distances detected in tracking or capture- mark-recapture studies are usually far below the corresponding estimates based on molecular gene-flow data. This discrepancy reflects the constraints of available tracking methods for free-ranging individuals leading to inappropriate surrogates of annual movement capacity, but can be resolved using probabilistic approaches based on dispersal functions. There is remarkable capacity for and plasticity in movements in amphibians. Annual within-patch movements (migrations) of individuals can be large and likely represent an underestimated capacity for movement at the interpatch scale. Landscape resistance may influence the paths of dispersing amphibians, but rarely impedes interpatch movements. Juveniles emigrating unpredictably far from the natal pond and adults switching from within-patch migrations to dispersal to another patch demonstrate the plasticity of individual movement behaviour. Three basic conclusions can be drawn with respect to the linkage of individual movement behaviour and spatial or genetic structure of local amphibian populations embedded in a heterogeneous landscape: (1) individual movements or consecutive short-term series of movements are misleading surrogate measures of total movement capacity; (2) probabilistic modelling of movement capacity is the best available behavioural predictor of interpatch gene flow; (3) connectivity of local populations in heterogeneous landscapes is less affected by landscape resistance than previously expected.

Sizov S.,University of Koblenz-Landau
ACM Transactions on Intelligent Systems and Technology | Year: 2012

Multimodal understanding of shared content is an important success factor for many Web 2.0 applications and platforms. This article addresses the fundamental question of geo-spatial awareness in social media applications. In this context, we introduce an approach for improved characterization of social media by combining text features (e.g., tags as a prominent example of short, unstructured text labels) with spatial knowledge (e.g., geotags, coordinates of images, and videos). Our model-based framework GeoFolk combines these two aspects in order to construct better algorithms for content management, retrieval, and sharing. We demonstrate in systematic studies the benefits of this combination for a broad spectrum of scenarios related to social media: recommender systems, automatic content organization and filtering, and event detection. Furthermore, we establish a simple and technically sound model that can be seen as a reference baseline for future research in the field of geotagged social media. © 2012 ACM.

Schafer R.B.,University of Koblenz-Landau
Science of the Total Environment | Year: 2012

This Special Issue focuses on the questions if and how biodiversity, ecosystem functions and resulting services could be incorporated into the Ecological Risk Assessment (ERA). Therefore, three articles provide a framework for the integration of ecosystem services into ERA of soils, sediments and pesticides. Further articles demonstrate ways how stakeholders can be integrated into an ecosystem service-based ERA for soils and describe how the current monitoring could be adapted to new assessment endpoints that are directly linked to ecosystem services. Case studies show that the current ERA may not be protective for biodiversity, ecosystem functions and resulting services and that both pesticides and salinity currently adversely affect ecosystem functions in the field. Moreover, ecological models can be used for prediction of new protection goals and could finally support their implementation into the ERA. Overall, the Special Issue stresses the urgent need to enhance current procedures of ERA if biodiversity, ecosystem functions and resulting services are to be protected. © 2011 Elsevier B.V..

Thimm M.,University of Koblenz-Landau
Artificial Intelligence | Year: 2013

Inconsistencies in knowledge bases are of major concern in knowledge representation and reasoning. In formalisms that employ model-based reasoning mechanisms inconsistencies render a knowledge base useless due to the non-existence of a model. In order to restore consistency an analysis and understanding of inconsistencies are mandatory. Recently, the field of inconsistency measurement has gained some attention for knowledge representation formalisms based on classical logic. An inconsistency measure is a tool that helps the knowledge engineer in obtaining insights into inconsistencies by assessing their severity. In this paper, we investigate inconsistency measurement in probabilistic conditional logic, a logic that incorporates uncertainty and focuses on the role of conditionals, i.e. if-then rules. We do so by extending inconsistency measures for classical logic to the probabilistic setting. Further, we propose novel inconsistency measures that are specifically tailored for the probabilistic case. These novel measures use distance measures to assess the distance of a knowledge base to a consistent one and therefore takes the crucial role of probabilities into account. We analyze the properties of the discussed measures and compare them using a series of rationality postulates. © 2013 Elsevier B.V.

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