L'experience regionale arabe en matiere d'education aux droits de l'homme dans les situations d'apprentissage informel

This article describes an informal approach to human rights education, which is anchored in reality and based on experience gained throughout the Arab region and more particularly within the Arab Institute for Human Rights. It is argued that the approach of the Institute could be adopted on a larger scale by organisations working in this domain, not only in the Arab region but also in other regions of the world. The article emphasises the essential role of governments and the importance of cooperation between the governmental and non-governmental levels in order to implement this type of human rights education in informal learning situations, and thus to disseminate a universal culture of human rights.     

Auswertung von elektromyographischen Signalen zur Steuerung von Exoskeletten

Zusammenfassung  Diese Arbeit stellt ein Modell und ein System zur Steuerung von Exoskeletten mit Hilfe von elektrischen Signalen vor, die an den Muskeln des Benutzers gemessen werden. Anhand dieser Signale wird der eigene Drehmomentbeitrag des Benutzer zur gewünschten Bewegung abgesch?tzt, und ein einstellbarer Faktor bestimmt das vom Exoskelett hinzugefügte Drehmoment in Bezug auf den Beitrag des Benutzers. Die Signale werden durch ein komplexes biomechanisches Modell ausgewertet. CR subject classification  J.3 ; J.7 ; I.6.5     

The Effects of Darkness and Lightness Cues in the Visual Depiction of Political Actors Involved in Scandals: An Experimental Study

Reports about political scandals have increased lately. Yet the general impact of news visuals and the specific role of lightness and darkness cues in images of scandalized politicians remain unclear. With the help of an experiment, the present pilot study examined the influence of candidate images and the effects of particular image backgrounds (light versus dark). While the foreground of the image depicting a politician involved in a scandal remained unchanged, the background was systematically altered. The results revealed that a light background had a positive effect on recipients’ attitudes toward the politician. In contrast, participants exposed to a dark image background demanded a more severe punishment for the politician.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.