155 research outputs found

    My Story. Digital Storytelling across Europe for Social Cohesion

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    ‘My Story’ (Mysty) is a pan-European, Erasmus+ funded Digital Storytelling project focused on intercultural competency. It has eight partners (HE, secondary schools and NGOs) across four countries (Austria, Italy, Hungary and the UK) and involves the collection, editing and uploading of digital stories to a shared ‘toolbox’. These stories focus on ‘food’, ‘family’ and ‘festival’ and act as a platform for diversity awareness and digital upskilling. The project is driven by the principle that innovative teaching resources form part of broader pedagogic strategies that can actively help tackle issues of diversity common across the EU. The paper discusses the process the project went through, some of its challenges and its results and, on the basis of these, looks at the role digital storytelling as a way of expressing different ethical, cultural or personal issues

    Object narratives, imaginings and multilingual communities: young people’s digital stories in the making

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    This paper draws on research from a global 5-year project, Critical Connections: Multilingual Digital Storytelling (2012-2017), which links language and intercultural learning with literacy, active citizenship and the arts. A critical ethnographic approach was adopted in the research project and the multilingual digital stories were an integral part of the research process. With the project’s focus on multilingualism and creation of bilingual digital texts, young people had to imagine how to use language in new contexts, uncover narratives around objects, and negotiate interfaces between different cultural landscapes. The research findings revealed the complexity of multilingual digital storytelling and how young people (aged 6-18 years old) learnt to become meaning makers discovering their own voices in unfamiliar contexts. Through these digital stories the young people forged strong links with the past and created new multilingual communities

    Reconnaissance des expressions faciales pour l’assistance ambiante

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    Au cours de ces derniĂšres dĂ©cennies, le monde a connu d’importants changements dĂ©mographiques et notamment au niveau de la population ĂągĂ©e qui a fortement augmentĂ©. La prise d’ñge a comme consĂ©quence directe non seulement une perte progressive des facultĂ©s cognitives, mais aussi un risque plus Ă©levĂ© d’ĂȘtre atteint de maladies neurodĂ©gĂ©nĂ©ratives telles qu’Alzheimer et Parkinson. La perte des facultĂ©s cognitives cause une diminution de l’autonomie et par consĂ©quent, une assistance quotidienne doit ĂȘtre fournie Ă  ces individus afin d’assurer leur bien-ĂȘtre. Les Ă©tablissements ainsi que le personnel spĂ©cialisĂ© censĂ©s les prendre en charge reprĂ©sentent un lourd fardeau pour l’économie. Pour cette raison, d’autres solutions moins coĂ»teuses et plus optimisĂ©es doivent ĂȘtre proposĂ©es. Avec l’avĂšnement des nouvelles technologies de l’information et de la communication, il est devenu de plus en plus aisĂ© de dĂ©velopper des solutions permettant de fournir une assistance adĂ©quate aux personnes souffrant de dĂ©ficiences cognitives. Les maisons intelligentes reprĂ©sentent l’une des solutions les plus rĂ©pandues. Elles exploitent diffĂ©rents types de capteurs pour la collecte de donnĂ©es, des algorithmes et mĂ©thodes d’apprentissage automatique pour l’extraction/traitement de l’information et des actionneurs pour le dĂ©clenchement d’une rĂ©ponse fournissant une assistance adĂ©quate. Parmi les diffĂ©rentes sources de donnĂ©es qui sont exploitĂ©es, les images/vidĂ©os restent les plus riches en termes de quantitĂ©. Les donnĂ©es rĂ©coltĂ©es permettent non seulement la reconnaissance d’activitĂ©s, mais aussi la dĂ©tection d’erreur durant l’exĂ©cution de tĂąches/activitĂ©s de la vie quotidienne. La reconnaissance automatique des Ă©motions trouve de nombreuses applications dans notre vie quotidienne telles que l’interaction homme-machine, l’éducation, la sĂ©curitĂ©, le divertissement, la vision robotique et l’assistance ambiante. Cependant, les Ă©motions restent un sujet assez complexe Ă  cerner et de nombreuses Ă©tudes en psychologie et sciences cognitives continuent d’ĂȘtre effectuĂ©es. Les rĂ©sultats obtenus servent de base afin de dĂ©velopper des approches plus efficaces. Les Ă©motions humaines peuvent ĂȘtre perçues Ă  travers diffĂ©rentes modalitĂ©s telle que la voix, la posture, la gestuelle et les expressions faciales. En se basant sur les travaux de Mehrabian, les expressions faciales reprĂ©sentent la modalitĂ© la plus pertinente pour la reconnaissance automatique des Ă©motions. Ainsi, l’un des objectifs de ce travail de recherche consistera Ă  proposer des mĂ©thodes permettant l’identification des six Ă©motions de base Ă  savoir : la joie, la peur, la colĂšre, la surprise, le dĂ©goĂ»t et la tristesse. Les mĂ©thodes proposĂ©es exploitent des donnĂ©es d’entrĂ©e statiques et dynamiques, elles se basent aussi sur diffĂ©rents types de descripteurs/reprĂ©sentations (gĂ©omĂ©trique, apparence et hybride). AprĂšs avoir Ă©valuĂ© les performances des mĂ©thodes proposĂ©es avec des bases de donnĂ©es benchmark Ă  savoir : JAFFE, KDEF, RaFD, CK+, MMI et MUG. L’objectif principal de ce travail de recherche rĂ©side dans l’utilisation des expressions faciales afin d’amĂ©liorer les performances des systĂšmes d’assistance existants. Ainsi, des expĂ©rimentations ont Ă©tĂ© conduites au sein de l’environnement intelligent LIARA afin de collecter des donnĂ©es de validation, et ce, en suivant un protocole d’expĂ©rimentation spĂ©cifique. Lors de l’exĂ©cution d’une tĂąche de la vie quotidienne (prĂ©paration du cafĂ©), deux types de donnĂ©es ont Ă©tĂ© rĂ©coltĂ©s. Les donnĂ©es RFID ont permis de valider la mĂ©thode de reconnaissance automatique des actions utilisateurs ainsi que la dĂ©tection automatique d’erreurs. Quant aux donnĂ©es faciales, elles ont permis d’évaluer la contribution des expressions faciales afin d’amĂ©liorer les performances du systĂšme d’assistance en termes de dĂ©tection d’erreurs. Avec une rĂ©duction du taux de fausses dĂ©tections dĂ©passant les 20%, l’objectif fixĂ© a Ă©tĂ© atteint avec succĂš

    Emotion and Stress Recognition Related Sensors and Machine Learning Technologies

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    This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective

    Faculty Publications & Presentations, 2005-2006

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    My Story. Digital Storytelling across Europe for Social Cohesion

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    ‘My Story’ (Mysty) is a pan-European, Erasmus+ funded Digital Storytelling project focused on intercultural competency. It has eight partners (HE, secondary schools and NGOs) across four countries (Austria, Italy, Hungary and the UK) and involves the collection, editing and uploading of digital stories to a shared ‘toolbox’. These stories focus on ‘food’, ‘family’ and ‘festival’ and act as a platform for diversity awareness and digital upskilling. The project is driven by the principle that innovative teaching resources form part of broader pedagogic strategies that can actively help tackle issues of diversity common across the EU. The paper discusses the process the project went through, some of its challenges and its results and, on the basis of these, looks at the role digital storytelling as a way of expressing different ethical, cultural or personal issues

    Advances in Human Factors in Wearable Technologies and Game Design

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    Ira-Paul Schwarz. Impressions of a Cloud and Romantic Mementos: Duets with Piano.

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