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Binary relations with certain properties such as biorders, equivalences or difunctional relations can be represented as particular matrices. In order for these properties to be identified usually a rearrangement of rows and columns is required in order to reshape it into a recognisable normal form. Most algorithms performing these transformations are working on binary matrix representations of the underlying relations. This paper presents an approach to use the RLE-compressed matrix representation as a data structure for storing relations to test whether they are biorders in a hopefully more efficient way.
Annual Report 2013 - 2014
(2015)
The Federal Ministry of Labour and Social Affairs (Bundesministerium für Arbeit und Soziales, BMA) is supporting 73 projects in Germany using European Union (EU) funds in the amount of € 26 million. By providing the subsidies, the European Commission and the German Federal Government are hoping to implement Corporate Social Responsibility (CSR) among German small and medium-sized businesses (SMBs). The project run by Bonn-Rhein-Sieg University is one of these CSR projects. It is aimed at providing comprehensive information on CSR to the businesses in question and at emphasizing their responsibility along the supply chain.
Ein Projektvertrag bietet den Geschäftspartnern rechtliche Sicherheit. Häufig wird er von Anwälten aufgesetzt. Insbesondere in kleinen und mittelständischen Unternehmen ist es aber auch oft der Projektleiter, der den Vertrag formuliert. Prof. Dr. Uwe Braehmer erklärt, unter welchen Bedingungen man einen Vertrag ohne juristische Beratung erstellen kann und liefert eine Checkliste mit den Regelungen, die ein Vertrag enthalten sollte.
Fallstrick Arbeitsrecht
(2005)
This master thesis describes a supervised approach to the detection and the identification of humans in TV-style video sequences. In still images and video sequences, humans appear in different poses and views, fully visible and partly occluded, with varying distances to the camera, at different places, under different illumination conditions, etc. This diversity in appearance makes the task of human detection and identification to a particularly challenging problem. A possible solution of this problem is interesting for a wide range of applications such as video surveillance and content-based image and video processing. In order to detect humans in views ranging from full to close-up view and in the presence of clutter and occlusion, they are modeled by an assembly of several upper body parts. For each body part, a detector is trained based on a Support Vector Machine and on densely sampled, SIFT-like feature points in a detection window. For a more robust human detection, localized body parts are assembled using a learned model for geometric relations based on Gaussians. For a flexible human identification, the outward appearance of humans is captured and learned using the Bag-of-Features approach and non-linear Support Vector Machines. Probabilistic votes for each body part are combined to improve classification results. The combined votes yield an identification accuracy of about 80% in our experiments on episodes of the TV series "Buffy the Vampire Slayer". The Bag-of-Features approach has been used in previous work mainly for object classification tasks. Our results show that this approach can also be applied to the identification of humans in video sequences. Despite the difficulty of the given problem, the overall results are good and encourage future work in this direction.
This project investigated the viability of using the Microsoft Kinect in order to obtain reliable Red-Green-Blue-Depth (RGBD) information. This explored the usability of the Kinect in a variety of environments as well as its ability to detect different classes of materials and objects. This was facilitated through the implementation of Random Sample and Consensus (RANSAC) based algorithms and highly parallelized workflows in order to provide time sensitive results. We found that the Kinect provides detailed and reliable information in a time sensitive manner. Furthermore, the project results recommend usability and operational parameters for the use of the Kinect as a scientific research tool.
Förderpreise 2014
(2014)
Praxisorientierte, wissenschaftliche Lehre und Forschung in enger Zusammenarbeit mit Unternehmen, Organisationen und gesellschaftlichen Gruppierungen ist das zentrale Leitbild des Fachbereichs Wirtschaftswissenschaften an der Hochschule Bonn-Rhein-Sieg.