University of Piraeus

About: University of Piraeus is a education organization based out in Piraeus, Attiki, Greece. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 1731 authors who have published 6209 publications receiving 106699 citations.

Analysis and design of a web-based authoring tool generating intelligent tutoring systems

Abstract: Authoring tools for intelligent tutoring systems (ITSs) are meant to provide environments where instructors may author their own ITSs in varying domains. In this way, painful constructions of ITSs, which are not reusable, may be avoided. However, the construction of an authoring tool is associated with many problems, such as the generality of the techniques incorporated, domain-independence, effectiveness for the prospective authors (instructors), and effectiveness for the students who will use the resulting ITSs. In this paper we will report on an empirical study that we conducted in order to design and develop WEAR, an ITS authoring tool for Algebra-related domains. In the study we investigated several aspects concerning the attitude and behaviour of both students and instructors. The study revealed important issues and was then used for the specification of the design of WEAR. A brief description of the developed system is also included in the paper so that the way that the design specifications were put into practice may be shown. However, a lot of the authoring tool's requirements that came to light could be applicable to other authoring tools as well. The most important requirement of this kind was the need for an instructor modelling component so that adaptivity could be provided to human instructors (authors). The provision of such facility is a novelty in the area of ITS authoring tools.

SimHuman: A Platform for Real-Time Virtual Agents with Planning Capabilities

Abstract: In this paper, we present SimHuman, a platform for the generation of real-time 3D environments with virtual agents. SimHuman is highly dynamic and configurable, as it is not based on fixed scenes and models, and has an embedded physically based modelling engine. Its agents can use features such as path finding, inverse kinematics and planning to achieve their goals. The paper explains in detail design and implementation issues and presents the architecture of the system as well as an illustrative example.

Key elements composing self-rated health in older adults: a comparative study of 11 European countries

Abstract: Self-rated health (SRH) is a multidimensional measure, predictive of morbidity and mortality. Comparative studies of determinants, however, are rare due to a lack of comparable cross-national data. This paper contributes towards filling in this gap, using data for persons aged 50 or higher in 11 European countries from the SHARE study (2004). The analysis aims at identifying key elements composing SRH using multinomial logistic regression models. In addition, the homogeneity of associations across populations is assessed. The findings indicate that education, depression, chronic conditions, mobility difficulties, somatic symptoms and levels of physical activity constitute important components of SRH; ADLs and obesity, on the other hand, are not significant and IADLs are important only in a few countries. All these associations point to the expected direction and are homogeneous across countries. However, demographic factors, age and gender, though significant in many countries have divergent associations. Effects of smoking also differentiate between southern and northern Europe.

From product recommendation to cyber-attack prediction: Generating attack graphs and predicting future attacks

Abstract: Modern information society depends on reliable functionality of information systems infrastructure, while at the same time the number of cyber-attacks has been increasing over the years and damages have been caused. Furthermore, graphs can be used to show paths than can be exploited by attackers to intrude into systems and gain unauthorized access through vulnerability exploitation. This paper presents a method that builds attack graphs using data supplied from the maritime supply chain infrastructure. The method delivers all possible paths that can be exploited to gain access. Then, a recommendation system is utilized to make predictions about future attack steps within the network. We show that recommender systems can be used in cyber defense by predicting attacks. The goal of this paper is to identify attack paths and show how a recommendation method can be used to classify future cyber-attacks in terms of risk management. The proposed method has been experimentally evaluated and validated, with the results showing that it is both practical and effective.