A METHOD FOR SEMANTIC WEB SERVICE COMPOSITION BASED ON PATTERN MATCHING

The composition of semantic web services is a very important and actual problem in the semantic web services research area. There are several semi-automatic approaches for this problem, but most of the results are related to automatic approaches. In this paper we present an automatic approach for the composition of semantic web services based on pattern matching. We consider a special type of semantic description, represented as a list of semantic descriptions corresponding to several semantic web services. The semantic description related to the semantic web service that we want to obtain is decomposed until all the parts of the semantic description correspond to semantic web services from a library. In the end, all the necessary semantic web services found in the library are composed in order to obtain the semantic web service that we wanted to construct.semantic web service composition, semantic description decomposition, pattern matching

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Mobile Learning Business Model Framework

M-learning has become more and more important but still is a young educational and economical (Edu-Eco) technology. M-learning strategies are aimed at economic, academic and technological objectives, however they lack in modeling ensured economic measurements in the sense of profitable products. Throughout this paper, we discuss the prime categories of elements that participate in the m-learning value net and give an overview of their business models. In addition to considering the mobile and e-learning business, business models, we deconstruct the m-learning value net, and also use a literature review in order to identify different actors in a business model for M-learning

Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache

Spark solutions for discovering fuzzy association rules in Big Data

The research reported in this paper was partially supported the COPKIT project from the 8th Programme Framework (H2020) research and innovation programme (grant agreement No 786687) and from the BIGDATAMED projects with references B-TIC-145-UGR18 and P18-RT-2947.The high computational impact when mining fuzzy association rules grows significantly when managing very large data sets, triggering in many cases a memory overflow error and leading to the experiment failure without its conclusion. It is in these cases when the application of Big Data techniques can help to achieve the experiment completion. Therefore, in this paper several Spark algorithms are proposed to handle with massive fuzzy data and discover interesting association rules. For that, we based on a decomposition of interestingness measures in terms of α-cuts, and we experimentally demonstrate that it is sufficient to consider only 10equidistributed α-cuts in order to mine all significant fuzzy association rules. Additionally, all the proposals are compared and analysed in terms of efficiency and speed up, in several datasets, including a real dataset comprised of sensor measurements from an office building.COPKIT project from the 8th Programme Framework (H2020) research and innovation programme 786687BIGDATAMED projects B-TIC-145-UGR18 P18-RT-294

Vers un profil UML pour la conception de composants multivues

International audienceThis paper aims to present an UML profile based on multiviews components. A multiviews component allows to encapsulate and deliver information according to the user's point of view and offers mechanisms to manage the dynamic evolution of viewpoints and consistency among views. In this paper, we first present the notion of multiviews component and its integration into a UML profile, and thus detail an object-oriented multiviews modelling applied to a concrete example. The transition to the coding stage is described through a generic implementation pattern.L' objectif de cet article est de présenter un profil UML permettant la construction de composants logiciels multivues. Un composant multivues est une extension de la notion de composant UML permettant de stocker et restituer de l' information en fonction du profil de l' utilisateur (point de vue), et offrant la possibilité de changement dynamique de point de vue. Dans cet article, nous présentons tout d' abord la notion de classe multivues, puis le composant multivues et son intégration dans un profil UML. Nous illustrons à l' aide d' un exemple concret la mise en oeuvre d' une modélisation objet multivues. La transition vers la phase de codage est présentée à travers un patron d'implémentation générique

Информационная технология добавления виртуального объекта в реальный мир. Часть 1

The paper presents information technology for immersion of arbitrary computer-synthesized virtual object, in particularly, robot-manipulator, into real environment. Developed technology provides visual and tactile-force effects of perception. The technology realizes so called Augmented Reality which is fast developing branch of Virtual Reality. Virtual object in this case is augmentation to Reality. Unlike from the known variants the technology presented by the paper provides more realistic perception of the virtual object into the real environment and this technology requests more small expenditure. In this issue the first part of paper is presented which is devoted theoretical description of technology. Second part of paper will be presented in the next volume of issue, it is devoted experimental results.В статье описана информационная технология "погружения" произвольного компьютерно-синтезированного виртуального объекта, в частности, робота-манипулятора, в реальную внешнюю среду. Разработанная технология обеспечивает как визуальный, так и тактильно-силовой эффект восприятия. Эта технология реализует так называемую добавленную реальность (Augmented Reality), быстро развивающееся направление виртуальной реальности (Virtual Reality). Виртуальный объект в этом случае является добавлением к реальности. В отличие от известных вариантов, описанная в статье технология обеспечивает более реалистичное восприятие виртуального объекта в реальном мире и является менее затратной. В этом выпуске журнала представлена первая часть статьи, посвященная описанию теории. Вторая часть статьи, посвященная описанию экспериментальных результатов, будет представлена в следующем томе выпуска