Using Emotional Intelligence in Personalized Adaptation

Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 1716-1742). IGI Publishing.The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the evelopment of more sophisticated environments, the need for them to take into account the user’s traits, as well as the user’s devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web.PROLEARN - Network of Excellence in Professional Learnin

Stackelberg Security Game for Optimizing Security of Federated Internet of Things Platform Instances

This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model

Functional Programming Way to Interact with Software Attacks and Vulnerabilities

Abstract—This paper proposes using functional programming style in a way to respond to detection of and interaction with the software attacks and vulnerabilities. Additionally, our approach considers involving Description Logics, as a basis for the use of the Semantic Web and meta-programming to produce executable ontologies and to enable semantic reasoning over behavior and interaction with software attacks and vulnerabilities. Accordingly, we introduce Magic Potion, a recently defined Domain Specific meta-Language that uses Modeling Spaces framework to study heterogeneous modeling and meta-modeling problems inspired by Model Driven Architecture. As an example of formalism for modeling software attacks and vulnerabilities, we explore Attack Tree, which provides a formal methodology for analyzing the security of the system. Based on Attack Tree, which is herein specified for a particular problem of dealing with known attacks and vulnerabilities of the security layer of the Wireless Application Protocol, and which is particularly built on top of Magic Potion specification, we define our specific Domain Specific Language that we call Attack Tree Domain Specific Language. It is envisioned as a tool for modeling and interacting with software attacks and vulnerabilities. Keywords-Software vulnerability; Functional Programming

Using Emotional Intelligence in Personalized Adaptation

Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 1716-1742). IGI Publishing.The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the evelopment of more sophisticated environments, the need for them to take into account the user’s traits, as well as the user’s devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web.PROLEARN - Network of Excellence in Professional Learnin

Using Emotional Intelligence in Personalized Adaptation

The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the evelopment of more sophisticated environments, the need for them to take into account the user’s traits, as well as the user’s devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web

Semiotics for Ontologies and Knowledge Representation

Abstract. The Semantic Web implies the comprehensive use of the main semiotic postulates on the Web. One of the most important facts about human understanding comes from the area of linguistics and semiotics. The semiotic techniques, such as syntagm and paradigm are explained through the examples in learning environment, in the context of logical understanding and knowledge representation on the Web.

Using Emotional Intelligence in Personalized Adaptation

The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the evelopment of more sophisticated environments, the need for them to take into account the user’s traits, as well as the user’s devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web

Approaching OWL and MDA through Technological Spaces

Web Ontology Language (OWL) and Model-Driven Architectures (MDA) are two technologies being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far stressed this problem and have proposed several solutions. The result of these efforts is the recent OMG's initiative for defining an ontology development platform. However, the problem of transformation between an ontology and MDA-based languages has been solved using rather partial and ad hoc solutions, most often by XSLT. In this paper we analyze OWL and MDA-compliant languages as separate technological spaces. In order to achieve a synergy between these technological spaces we define ontology languages in terms of MDA standards, recognize relations between OWL and MDA-based ontology languages, and propose mapping techniques. In order to illustrate the approach, we use an MDA-defined ontology architecture that includes ontology metamodel and ontology UML Profile. Based on this approach, we have implemented a transformation of the ontology UML Profile into OWL representation