Consistency in Continuous Distributed Interactive Media

In this paper we investigate how consistency can be ensured for continuous distributed interactive media, i.e. distributed media which change their state in reaction to user initiated operations as well as because of the passing of time. Existing approaches to reach consistency in discrete distributed interactive media are briefly outlined and it is shown that these fail in the continuous domain. In order to allow a thorough discussion of the problem, a formal definition of the term consistency in the continuous domain is given. Based on this definition we show that an important trade off relationship exists between the responsiveness of the medium and the appearance of short term inconsistencies. Currently this trade off is not taken into consideration for consistency in the continuous domain, thereby severely limiting the consistency related fidelity for a large number of applications. We show that for those applications the fidelity can be significantly raised by voluntarily decreasing the responsiveness of the medium. This concept is called local lag and it enables the distribution of continuous interactive media which are more vulnerable to short term inconsistencies than e.g. battlefield simulations. We prove that the concept of local lag is valid by describing how local lag was successfully used to ensure consistency in a 3D telecooperation application

Cooperative Learning Supported by Telecooperation

Die Telekooperation bietet neue Möglichkeiten der Lernunterstützung durch die Integration von Informations- und Kommunikationstechnologien zu multimedialen Lernumgebungen. Die Lernwirkung lässt sich am Arbeitsplatz vervielfachen, indem die Vorteile konventioneller Methoden wie Selbstlernen mittels CBT durch tutorielle Unterstützung über Kommunikationsverbindung erheblich gesteigert werden. In dem folgenden Beitrag werden zunächst die Ziele der Telekooperation insbesondere im Hinblick auf ihre Konsequenzen für die Weiterbildung herausgearbeitet. Daran schließt sich eine Erläuterung der technischen Möglichkeiten der Telekooperation an, die durch ein Szenario zum Fernlernen und die Vorstellung der ECOLE-Lernumgebung veranschaulicht werden. Abschließend zeigt eine Zusammenfassung die zu erwartenden technologischen Entwicklungen im Hinblick auf die Weiterbildung. (DIPF/Orig.)Telecooperation offers new possibilities for learning support due to the integration of information and communication technologies into multimedia learning environments. The learning effort via desktop can be multiplied by combining conventional methods like self-learning based on CBT with a collaborative remote tutor support. This paper first explains the objectives of telecooperation especially with a view to the consequences for further education. Then an explanation of the technical possibilities of telecooperation follows. They are clarified with the help of a scenario for distance learning and the presentation of the ECOLE learning environment. Finally a conclusion shows the technological developments we may expect with regard to further education. (DIPF/Orig.

Multimedia kiosks and the ancient times : an archaeological reconstruction and history of Braga’s cathedral

Ein vom CCG, in Kooperation mit der Unidade de Arqueologia da Universidade do Minho – UAUM (Portugal), entwickelter Multimedia Kiosk präsentiert auf mehreren thematischen Ebenen die Kathedrale und die mit ihr verbundenen archäologischen Ausgrabungen. Zu jeder Ausgrabungsstätte ist der Fortgang der archäologischen Arbeiten durch kurze Textbeschreibungen, Fotografien und Zeichnungen dokumentiert. Ein Modell der Kathedrale lädt zu einem virtuellen Rundgang ein. Ziel der Präsentation ist es, nicht nur Finanzmittel für die Fortführung der archäologischen Arbeiten einzuwerben bzw. das Interesse potentieller Sponsoren zu wecken, aber auch den Besuchern der Kathedrale eine bessere und interessantere Übersicht der Geschichte des Gebäudes zu geben

Proceedings of the 4th Workshop on Interacting with Smart Objects 2015

These are the Proceedings of the 4th IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects

STATSREP-ML: Statistical Evaluation & Reporting Framework for Machine Learning Results

In this report, we present STATSREP-ML, which is an open-source solution for automating the process of evaluating machine-learning results. It calculates qualitative statistics, performs the appropriate tests and reports them in a comprehensive way. It largely, but not exclusively, relies on well-tested and robust statistics implementations in R, and uses the tests the machine-learning community largely agreed upon

DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks

In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core of the DeepAlign algorithm are two recurrent neural networks trained to predict the next event. One is reading sequences of process executions from left to right, while the other is reading the sequences from right to left. By combining the predictive capabilities of both neural networks, we show that it is possible to calculate sequence alignments, which are used to detect and correct anomalies. DeepAlign utilizes the case-level and event-level attributes to closely model the decisions within a process. We evaluate the performance of our approach on an elaborate data corpus of 252 realistic synthetic event logs and compare it to three state-of-the-art conformance checking methods. DeepAlign produces better corrections than the rest of the field reaching an overall $F_1$ score of $0.9572$ across all datasets, whereas the best comparable state-of-the-art method reaches $0.6411$