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Foliicolous lichens are one of the most abundant epiphytes in tropical rainforests and one of the few groups of organisms that characterize these forests. Tropical rainforests are increasingly affected by anthropogenic disturbance resulting in forest destruction and degradation. However, not much is known on the effects of anthropogenic disturbance on the diversity of foliicolous lichens. Understanding such effects is crucial for the development of appropriate measures for the conservation of such organisms. In this study, foliicolous lichens diversity was investigated in three tropical rainforests in East Africa. Godere Forest in Southwest Ethiopia is a transitional rainforest with a mixture of Afromontane and Guineo-Congolian species. The forest is secondary and has been affected by shifting cultivation, semi-forest coffee management and commercial coffee plantation. Budongo Forest in West Uganda is a Guineo-Congolian rainforest consisting of primary and secondary forests. Kakamega Forest in western Kenya is a transitional rainforest with a mixture of Guineo-Congolian and Afromontane species. The forest is a mosaic of near-primary forest, secondary forests of different seral stages, grasslands, plantations, and natural glades.
The automatic detection of position and orientation of subsea cables and pipelines in camera images enables underwater vehicles to make autonomous inspections. Plants like algae growing on top and nearby cables and pipelines however complicate their visual detection: the determination of the position via border detection followed by line extraction often fails. Probabilistic approaches are here superior to deterministic approaches. Through modeling probabilities it is possible to make assumptions on the state of the system even if the number of extracted features is small. This work introduces a new tracking system for cable/pipeline following in image sequences which is based on particle filters. Extensive experiments on realistic underwater videos show robustness and performance of this approach and demonstrate advantages over previous works.
Querying for meta knowledge
(2008)
The Semantic Web is based on accessing and reusing RDF data from many different sources, which one may assign different levels of authority and credibility. Existing Semantic Web query languages, like SPARQL, have targeted the retrieval, combination and reuse of facts, but have so far ignored all aspects of meta knowledge, such as origins, authorship, recency or certainty of data, to name but a few. In this paper, we present an original, generic, formalized and implemented approach for managing many dimensions of meta knowledge, like source, authorship, certainty and others. The approach re-uses existing RDF modeling possibilities in order to represent meta knowledge. Then, it extends SPARQL query processing in such a way that given a SPARQL query for data, one may request meta knowledge without modifying the query proper. Thus, our approach achieves highly flexible and automatically coordinated querying for data and meta knowledge, while completely separating the two areas of concern.
Social networking platforms as creativity fostering systems: research model and exploratory study
(2008)
Social networking platforms are enabling users to create their own content, share this content with anyone they invite and organize connections with existing or new online contacts. Within these electronic environments users voluntarily add comments on virtual boards, distribute their search results or add information about their expertise areas to their social networking profiles and thereby share it with acquaintances, friends and increasingly even with colleagues in the corporate world. As a result, it is most likely that the underlying knowledge sharing processes result in many new and creative ideas. The objective of our research therefore is to understand if and how social social networking platforms can enforce creativity. In addition, we look at how these processes could be embedded within the organizational structures that influence innovative knowledge sharing behavior. The basis for our research is a framework which focuses on the relations between intrinsic motivation, creativity and social networking platforms. First results of our empirical investigation of a social software platform called "StudiVZ.net" proved that our two propositions are valid.
The internet is becoming more and more important in daily life. Fundamental changes can be observed in the private sector as well as in the public sector. In the course of this, active involvement of citizens in planning political procedures is more and more supported electronically. The expectations culminate in the assumption that information and communication technology (ICT) can enhance civic participation and reduce disenchantment with politics. Out of these expectations, a lot of eparticipation projects were initiated in Germany. Initiatives were established, e.g. the "Initiative eParticipation", which gave many incentives of electronic participation for policy and administration in order to strengthen decision-making processes with internet supported participation practices. This thesis consists of two major parts. In the first part, definitions of the essential terms are presented. The position of e-participation within the dimension of ebusiness is pointed out. In order to explain e-participation, basics of the classical offline participation are delivered. It will be shown that a change is in progress, not only because of the deployment of ICT. Subsequently, a framework to characterize eparticipation is presented. The European Union is encouraging the implementation of e-participation. So, the city of Koblenz should be no exception. But what is the current situation in Koblenz? To provide an answer to this question, the status quo was examined with the help of a survey among the citizens of Koblenz, which was developed, conducted and evaluated. This is the second major part of this thesis.
Probability propagation nets
(2008)
This work introduces a Petri net representation for the propagation of probabilities and likelihoods, which can be applied to probabilistic Horn abduction, fault trees, and Bayesian networks. These so-called "probability propagation nets" increase the transparency of propagation processes by integrating structural and dynamical aspects into one homogeneous representation. It is shown by means of popular examples that probability propagation nets improve the understanding of propagation processes - especially with respect to the Bayesian propagation algorithms - and thus are well suited for the analysis and diagnosis of probabilistic models. Representing fault trees with probability propagation nets transfers these possibilities to the modeling of technical systems.
CAMPUS NEWS - artificial intelligence methods combined for an intelligent information network
(2008)
In this paper we describe a network for distributing personalised information with the usage of artificial intelligence methods. Reception of this information should be possible with everyday mobile equipment. Intelligent filtering and spam protection aim at integrating this technology into our environment. Information on the system architecture and usage of the installation are also presented.
The present thesis investigates attitudes and prosocial behavior between workgroups from a social identity and intergroup contact perspective. Based on the Common In-group Identity Model (CIIM; Gaertner & Dvoidio, 2000), it is hypothesized that "optimal" conditions for contact (Allport, 1954) create a common identity at the organizational level which motivates workgroups to cooperate and show organizational citizenship behavior (OCB) rather than intergroup bias. Predictions based on the CIIM are extended with hypotheses derived from the In-group Projection Model (IPM; Mummendey & Wenzel, 1999) and the Self-Categorization Model of Group Norms (Terry & Hogg, 1996). Hypotheses are tested with data from N1 = 281 employees of N2 = 49 different workgroups and their workgroup managers of a German mail-order company (Study 1). Results indicate that group- and individual-level contact conditions are predictive of lower levels of intergroup bias and higher levels of cooperation and helping behavior. A common in-group representation mediates the effect on out-group attitudes and intergroup cooperation. In addition, the effect of a common in-group representation on intergroup bias is moderated by relative prototypicality, as predicted by the IPM, and the effect of prosocial group norms on helping behavior is moderated by workgroup identification, as predicted by the Self-Categorization Model of Group Norms. A longitudinal study with Ntotal = 57 members of different student project groups replicates the finding that contact under "optimal" conditions reduces intergroup bias and increases prosocial behavior between organizational groups. However, a common in-group representation is not found to mediate this effect in Study 2. Initial findings also indicate that individual-level variables, such as helping behavior toward members of another workgroup, may be better accounted for by variables at the same level of categorization (cf. Haslam, 2004). Thus, contact in a context that makes personal identities of workgroup members salient (i.e., decategorization) may be more predictive of interpersonal prosocial behavior, while contact in a context that makes workgroup identities salient (i.e., categorization) may be more predictive of intergroup prosocial behavior (cf. Tajfel, 1978). Further data from Study 1 support such a context-specific effect of contact between workgroups on interpersonal and intergroup prosocial behavior, respectively. In the last step, a temporal integration of the contact contexts that either lead to decategorization, categorization, or recategorization are examined based on the Longitudinal Contact Model (Pettigrew, 1998). A first indication that a temporal sequence from decategorization via categorization to recategorization may be particularly effective in fostering intergroup cooperation is obtained with data from Study 2. In order to provide a heuristic model for research on prosocial behavior between workgroups, findings are integrated into a Context-Specific Contact Model. The model proposes specific effects of contact in different contexts on prosocial behavior at different levels of categorization. Possible mediator and moderator processes are suggested. A number of implications for theory, future research and the management of relations between workgroups are discussed.