University of the Aegean

About: University of the Aegean is a education organization based out in Mytilene, Greece. It is known for research contribution in the topics: Population & Context (language use). The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Human-centered ontology engineering: The HCOME methodology

Abstract: The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human-Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology.

Issues in computer supported inquiry learning in science

Abstract: Current views on science learning state that this should not involve learning just about the established results of science, including well-established theories such as Newtonian mechanics or the evolution of species as well as important empirical discoveries such as Young’s double slit experiment or the structure of DNA. Instead science learning should also focus on the processes and methods used by scientists to achieve such results. One obvious way to bring students into contact with the scientific way of working is to have them engage in the processes of scientific inquiry themselves, by offering them environments and tasks that allow them to carry out the processes of science: orientation, stating hypotheses, experimentation, creating models and theories, and evaluation (de Jong 2006a). Involving students in the processes of science brings them into the closest possible contact with the nature of scientific understanding, including its strengths, problems and limitations (Dunbar 1999). This is the main claim of inquiry learning: engaging learners in scientific processes helps them build a personal knowledge base that is scientific, in the sense that they can use this knowledge to predict and explain what they observe in the natural world. For about the last 20 years, computers have been used to create environments that engage learners in scientific inquiry activities. The virtue of the computer is that it allows the scaling down of inquiry tasks to a manageable size for learners who are inexperienced with inquiry processes. There are several ways in which computers can help create challenging and manageable environments for inquiry learning: • Replacing the natural world by a computer simulation can help make available on a wide scale the phenomena to be investigated. Moreover, the simulation may be simplified and/or emphasize certain aspects of the domain that can help learners observe critical features of the domain (van Joolingen & de Jong 1991a; de Jong & van Joolingen 1998; de Jong 2006a). • The computer can offer tools that support the inquiry processes, such as tools to analyse or visualize data, tools that help learners state hypotheses and tools that help learners manage the learning process (van Joolingen 1999; Linn et al. 2004a; Quintana et al. 2004; de Jong 2006b). • The computer can support collaboration between learners, allowing them to communicate, share data, results and ideas, and discuss consequences for the knowledge that is under construction (Okada & Simon 1997; van Joolingen et al. 2005). • Computer-based modeling tools allow learners to express their theories in models that can be simulated. In this way learners can use their theories operationally, confronting themselves with the consequences of their ideas (Hestenes 1987; Schecker 1993; Jackson et al. 1996; Fretz et al. 2002; Zhang et al. 2002; Schwarz & White 2005).

Search for Higgs boson pair production in the γ γ bb¯ final state with 13 TeV pp collision data collected by the ATLAS experiment

Abstract: A search is performed for resonant and non-resonant Higgs boson pair production in the $ \upgamma \upgamma b\overline{b} $ final state. The data set used corresponds to an integrated luminosity of 36.1 fb$^{−1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No significant excess relative to the Standard Model expectation is observed. The observed limit on the non-resonant Higgs boson pair cross-section is 0.73 pb at 95% confidence level. This observed limit is equivalent to 22 times the predicted Standard Model cross-section. The Higgs boson self-coupling (κ$_{λ}$ = λ$_{HHH}$/λ$_{HHH}^{SM}$ ) is constrained at 95% confidence level to −8.2 < κ$_{λ}$ < 13.2. For resonant Higgs boson pair production through $ X\to HH\to \upgamma \upgamma b\overline{b} $ , the limit is presented, using the narrow-width approximation, as a function of m$_{X}$ in the range 260 GeV < m$_{X}$ < 1000 GeV. The observed limits range from 1.1 pb to 0.12 pb over this mass range.