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Alepis E.,University of Piraeus | Stathopoulou I.-O.,University of Piraeus | Virvou M.,University of Piraeus | Tsihrintzis G.A.,University of Piraeus | Kabassi K.,Technological Educational Institute of the Ionian Islands
Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Towards building a multimodal affect recognition system, we have built a facial expression recognition system and a audio-lingual affect recognition system. In this paper, we present and discuss the development and evaluation process of the two subsystems, concerning the recognition of emotions from audio-lingual and visual-facial modalities. Many researchers agree that these modalities are complementary to each other and that the combination of the two can improve the accuracy in affective user models. Therefore in this paper we present a combination of two modes using multi-criteria decision making theories. The resulted system takes advantage of the strengths of each mode and is more accurate in emotion recognition. © 2010 IEEE. Source

Megalovasilis P.,Technological Educational Institute of the Ionian Islands | Papastergios G.,Aristotle University of Thessaloniki | Filippidis A.,Aristotle University of Thessaloniki
Environmental Monitoring and Assessment

The Kozani-Ptolemais-Amyntaio basin constitutes the principal coal field of Greece. Approximately 50 % of the total power production of Greece is generated by five power stations operating in the area. Lignite samples, together with the corresponding fly ash and bottom ash were collected, over a period of 3 months, from the power plant of Amyntaio and analyzed for their content in 16 trace elements. The results indicate that Y, Nb, U, Rb, Zr, Ni, Pb, Ba, Zn, Sr, Cu, and Th demonstrate an organic affinity during the combustion of lignite, while V has an inorganic affinity. Three elements (Co, Cr, and Sc) show an intermediate affinity. © 2012 Springer Science+Business Media Dordrecht. Source

Kabassi K.,Technological Educational Institute of the Ionian Islands | Virvou M.,University of Piraeus
IEEE Transactions on Human-Machine Systems

This research investigates the novel combination of multicriteria decision-making theories with a cognitive theory called human plausible reasoning (HPR) to provide personalized assistance via graphical user interfaces (GUIs). A GUI called intelligent file manipulator (IFM) helps with organizing computer file storage. The system reasons about user actions, goals, plans, and possible errors and offers automatic assistance in case of a problematic situation. Three multicriteria decision-making theories [simple additive weighting, multiattribute utility theory, and data envelopment analysis] were adapted, implemented, and combined with HPR, in turn. This process resulted in three different versions of IFM that were evaluated. The protocols of 30 users of different levels of expertise were provided to the system with each of the versions and to ten human experts. The responses of the experts and the different versions of the system were compared. The evaluation revealed that decision-making theories can increase control in an intelligent user interface. They can be combined with a cognitive theory like HPR. There was 66-81% compatibility of the different systems' responses to the proposals of the majority of experts. All decision-making theories were better in simulating the human experts' reasoning when there was unanimity of the human experts' opinion. In such cases, there was 68-84% compatibility of the different systems' responses to the experts' proposals. This research supports that HPR could successfully be completed by a multicriteria decision-making theory, and such combination can be effectively used for providing personalized help in GUIs. © 2013 IEEE. Source

James E.A.,Benaroya Research Institute | Moustakas A.K.,Technological Educational Institute of the Ionian Islands | Bui J.,Benaroya Research Institute | Papadopoulos G.K.,Epirus Institute of Technology | And 3 more authors.
Arthritis and Rheumatism

Objective. HLA-DRB1*1001 (DR1001) is a shared epitope allele associated with rheumatoid arthritis (RA). The present study was undertaken to assess the capacity of DR1001 to accommodate citrulline in its binding pockets and to identify citrullinated T cell epitopes derived from joint-associated proteins. Methods. The binding of peptide derivatives containing citrulline, arginine, and other amino acid substitutions was measured. A prediction algorithm was developed to identify arginine-containing sequences from joint-associated proteins that preferentially bind to DR1001 upon citrullination. Unmodified and citrullinated versions of these sequences were synthesized and were utilized to stimulate CD4+ T cells from healthy subjects and RA patients. Responses were measured by class II major histocompatibility complex tetramer staining and confirmed by isolating CD4+ T cell clones. Results. DR1001 accepted citrulline, but not arginine, in 3 of its anchoring pockets. The prediction algorithm identified sequences that preferentially bound to DR1001 with arginine replaced by citrulline. Three of these sequences elicited CD4+ T cell responses. T cell clones specific for these sequences proliferated only in response to citrullinated peptides. Conclusion. Conversion of arginine to citrulline generates "altered-self" peptides that can be bound and presented by DR1001. Responses to these peptides implicate the corresponding proteins (fibrinogen α, fibrinogen β, and cartilage intermediate-layer protein) as relevant antigens. The finding of preferential responses to citrullinated sequences suggests that altered peptide binding affinity due to this posttranslational modification may be an important factor in the initiation or progression of RA. As such, measuring responsiveness to these peptides may be useful for immunologic monitoring. © 2010, American College of Rheumatology. Source

Virvou M.,University of Piraeus | Tsihrintzis G.A.,University of Piraeus | Alepis E.,University of Piraeus | Stathopoulou I.-O.,University of Piraeus | Kabassi K.,Technological Educational Institute of the Ionian Islands
International Journal on Artificial Intelligence Tools

In this paper, we present and discuss a novel approach for the integration of audio-lingual and visual-facial modalities in a bi-modal user interface for affect recognition. As it is widely acknowledged, two or more modalities of interaction can provide complementary information to each other with respect to affect recognition. However, satisfactory progress has not yet been achieved towards the integration of these modalities, since the problem of combining them effectively is quite complicated. In our research, we combine the two modalities from the perspective of a human observer by employing a multi-criteria decision making theory for dynamic affect recognition of computer users. An important research milestone that is required in our approach is the specification of the strengths and weaknesses of each modality with respect to affect recognition concerning 6 basic emotion states. These emotion states are happiness, sadness, surprise, anger and disgust as well as the emotionless state which we refer to as neutral. For this purpose, we describe two empirical studies that we have conducted involving human users and human observers concerning the recognition of emotions from audio-lingual and visual-facial modalities. The results of the empirical studies have been used to assign weights to criteria for the application of a multi-criteria decision making theory. Moreover, the results of the empirical studies provide information that may be used by other researchers in the field of affect recognition. © 2012 World Scientific Publishing Company. Source

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