La sécurité routière est un enjeu majeur de santé publique et de protection des personnes. D'après l'organisation mondiale de la santé (OMS), près de 1,2 millions de personnes meurent chaque année dans le monde suite à des accidents de la route (2015). D’après des données accidentologiques, 36,7% des blessures graves ont pour origine des lésions au thorax (Page et collab., 2012). La biomécanique en sécurité passive a pour rôle d'améliorer notre compréhension du corps humain dans le but de construire de meilleurs outils pour évaluer le risque de blessure.Les modèles numériques d'être humain sont employés pour simuler virtuellement les conditions d'un accident. Aujourd'hui, ils sont de plus en plus utilisés par les constructeurs automobiles et équipementiers pour mieux comprendre les mécanismes lésionnels. Cependant, ils n’existent que dans certaines tailles et ne prennent alors pas en compte les variations morphologiques observées dans la population.L'imagerie médicale 3D donne accès aux géométries des différentes structures anatomiques composant le corps humain. Les hôpitaux regorgent aujourd'hui de quantités d'images 3D couvrant une très large partie de la population en termes d'âge, de corpulence et de sexe.L’objectif global de cette thèse est de modéliser statistiquement la géométrie 3D de la cage thoracique à partir d'images médicales afin de personnaliser un modèle numérique de corps humain pour simuler par éléments finis des conditions de choc automobile. Le premier objectif est d’élaborer un protocole de segmentation une base de CT-scans de manière à obtenir des données géométriques adaptées à la construction d’un modèle statistique de forme de la cage thoracique.Le deuxième objectif est de construire un modèle statistique de forme de la cage thoracique, en prenant en compte sa structure articulée.Le troisième objectif est d’utiliser le modèle statistique de la cage thoracique pour déformer un modèle numérique d’être humain, de manière à étudier l’influence de certains paramètres sur le risque de blessure. / Road safety is a major issue of public health and personal safety. According to the World Health Organization (WHO), nearly 1.2 million people die each year worldwide due to road accidents (2015). According to accident data, 36.7% of serious injuries are caused by thoracic injuries (Page et al., 2012). The aim of biomechanics in passive safety is to improve our understanding of the human body in order to build better tools for assessing the risk of injury.Numerical human body models are used to virtually simulate the conditions of an accident. Today, they are increasingly used by car manufacturers and equipment manufacturers to better understand injury mechanisms. However, they exist only in few sizes and do not take into account the morphological variations observed in the population.3D medical imaging gives access to the geometries of the different anatomical structures that make up the human body. Today, hospitals are full of 3D images covering a very large part of the population in terms of age, body size and sex.The overall objective of this thesis is to statistically model the 3D geometry of the rib cage from medical images in order to personalize a numerical human body model to simulate car crash conditions.The first objective is to develop a segmentation process based on CT-scans in order to obtain geometric data adapted to the construction of a statistical model of shape of the rib cage.The second objective is to build a statistical model of the shape of the rib cage, taking into account its articulated structure.The third objective is to use the statistical model of the rib cage to deform a numerical human body model, in order to study the influence of certain parameters on the risk of injury.

Made available in DSpace on 2016-04-04T18:31:34Z (GMT). No. of bitstreams: 1 Alan Menk dos Santos.pdf: 6433244 bytes, checksum: d8118b5fa4198a1f3792738316afd65a (MD5) Previous issue date: 2012-12-03 / With the implementation of the Brazilian Digital TV System (SBTVD) comes a range of new opportunities and possibilities both for viewer and TV stations. For the viewers, they will have an immense amount of channels, programs and interactive advertisements. For TV stations, it increases the possibility of advertising in new media. In this context, the opportunity arises for a recommendation system for applications and interactivity portals. This dissertation presents a proposal of advertising personalization into applications and portals of digital TV environment in order to bring a better experience to the viewer, a new form of income for the broadcasters and also a greater acceptance of specialized products for use. This work develops an application for interactive Digital TV called Smart Marketing capable of capturing viewer navigation data through both implicit and explicit means by performing customized advertising from the process of knowledge discovery. Developed from AstroTV middleware, compatible with the Brazilian specification, its application was evaluated by means of experiment that used varied user profiles, applying into the generated database the process of knowledge discovery, which used tasks of classification and grouping. The results indicated the quality of the recommendation generated by Smart Marketing. / Com a implanta??o do Sistema Brasileiro de TV Digital (SBTVD), inicia-se uma gama de novas oportunidades e possibilidades tanto para o telespectador quanto as emissoras de TV. Para os Telespectadores, eles ter?o uma imensa quantidade de canais, programas e propagandas interativas. Para as emissoras de TV, aumenta a possibilidade de propagandas em novos meios de comunica??o. Neste contexto, surge a oportunidade de um sistema de recomenda??o para os aplicativos e portais de interatividade. Esta disserta??o apresenta uma proposta de personaliza??o de propaganda em aplicativos e portais do ambiente de TV Digital com o objetivo de trazer uma melhor experi?ncia ao telespectador, uma nova forma de obten??o de recursos por parte das teledifusoras e tamb?m uma maior aceita??o de produtos especializados, para uso. Este trabalho desenvolve um aplicativo para a TV Digital interativa denominado Smart Marketing capaz de capturar os dados de navega??o do telespectador tanto por meio impl?cito quanto explicito, realizando a apresenta??o de publicidades personalizadas a partir do processo de descoberta do conhecimento. Elaborado a partir do middleware AstroTV, compat?vel com a especifica??o brasileira, sua aplica??o foi avaliada por meio do experimento que se utilizou, de usu?rios com perfis variados, aplicando na base de dados gerada o processo de descoberta de conhecimento, o qual utilizou-se das tarefas de classifica??o e agrupamento. Os resultados obtidos indicaram a qualidade da recomenda??o gerada pelo Smart Marketing.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-06-13T13:27:34Z No. of bitstreams: 1 Thiago Silva de Souza_.pdf: 4022356 bytes, checksum: a1501abc241ec37282c058d610c0508e (MD5) / Made available in DSpace on 2016-06-13T13:27:34Z (GMT). No. of bitstreams: 1 Thiago Silva de Souza_.pdf: 4022356 bytes, checksum: a1501abc241ec37282c058d610c0508e (MD5) Previous issue date: 2016-03-21 / Nenhuma / O modo como as pessoas fazem turismo mudou consideravelmente nas últimas décadas. Essas mudanças de comportamento foram influenciadas, entre outros, por fatores tecnológicos, pois os turistas agora possuem diversas ferramentas de apoio desde o momento em que se pensa em fazer turismo, durante o turismo propriamente dito, e até mesmo após ele. Com isso, espera-se muito mais dessas ferramentas de apoio no quesito utilidade, confiabilidade e qualidade no serviço prestado. Muitos estudos têm sido conduzidos nesse sentido, diversos avanços já foram alcançados e atualmente já existem ferramentas que atendem várias demandas atuais dos turistas em seus itinerários. No entanto, a maioria delas não levam em consideração alguns aspectos importantes para que o turista seja realmente auxiliado, como por exemplo, encontrar informações turísticas sobre cidades consideradas de pequeno porte ou distantes de locais turísticos expressivos. O que muito se nota nessas ferramentas atuais, até mesmo nas de cunho comercial, é que somente são contempladas as cidades de grande porte, de alto fluxo de turistas. As demais cidades, que também possuem seus atrativos turísticos, são deixadas de lado. Outra característica comum nas ferramentas atuais é que os guias são gerados previamente e são entregues muitos dados estáticos aos turistas. No modelo de arquitetura desenvolvido neste trabalho, a coleta por informações turísticas acontece de maneira dinâmica, realizando buscas de conteúdo na web em diversas bases de conhecimento abertas e que estão em constante atualização. A partir daí essas informações são organizadas e armazenadas em ontologia, e por fim, entregues ao turista, baseadas em princípios de computação ubíqua. Essa capacidade de realizar buscas na web faz com que um número maior de cidades possa ser encontrado e se consiga chegar a um bom nível de satisfação do turista no uso da ferramenta, bem como eleva a percepção do grau de utilidade da arquitetura proposta. Portanto, o objetivo deste trabalho é desenvolver um modelo de arquitetura de sistema para o turismo ubíquo, baseado em dispositivos móveis, chamado de Ataîru, que na língua indígena Tupi-Guarani significa “companheiro de viagem”. O modelo considera dados sobre a localização e perfil do turista, bem como sobre dados climáticos, data e hora do local pesquisado, para prover respostas personalizadas aos turistas. Para avaliar o modelo proposto, foram utilizadas três técnicas pertinentes, a saber: avaliação por cenários, avaliação de desempenho e avaliação de usabilidade. Na avaliação de desempenho mostrou-se a viabilidade do modelo através de testes feitos no ambiente de nuvem computacional. Na avaliação de usabilidade foram convidados voluntários para usarem o aplicativo móvel cliente Ataîru, onde o objetivo foi avaliar a (1º) percepção de facilidade de uso e (2º) percepção de utilidade do aplicativo, e a (3º) percepção de utilidade das informações apresentadas, alcançando percentuais de concordância total de 72,5%, 82,5% e 67,5%, respectivamente e de concordância parcial de 27,5%, 15% e 30%, respectivamente. Isso mostra que o modelo supre a necessidade dos turistas de informações turísticas de cidades consideradas pequenas ou distantes de locais turísticos expressivos, tanto no aspecto quantitativo quanto qualitativo. / The way people do tourism has changed considerably in recent decades. These behavioral changes were influenced, among others, by technological factors, because tourists now have several tools to support from the moment in which it thinks about doing tourism, during the tour itself, and even after it. Thus, it is expected more of these support tools in the category utility, reliability and quality of service provided. Many studies have been conducted in this direction, several advances have been achieved and currently there are already several tools that meet current demands of tourists in their itineraries. However, most of them do not take into account some important aspects for the tourist really be helped, for example, find tourist information about cities considered small or far from significant tourist sites. What very noticeable in these current tools, even in commercial nature, is that only the large cities are contemplated, high flow of tourists. The other cities, which also have their tourist attractions, are set aside. Another common feature in today's tools is that the guides are pre-generated and delivered many static data to tourists. In architectural model developed in this work, the collection of tourist information happens dynamically, making content web searches in several open knowledge bases and are constantly updated. From there the information is organized and stored in ontology, and finally delivered to the tourist, based on principles of ubiquitous computing. This ability to search the web makes a larger number of cities can be found and can reach a good level of tourist satisfaction in using the tool as well as increases the perception of the degree of usefulness of the proposed architecture. Therefore, the objective of this work is to develop a system architecture model for the ubiquitous tourism, based mobile devices, called Ataîru, which in the indigenous language Tupi-Guarani means "traveling companion". The model takes into account data on the location and tourist profile, as well as weather data, date and time of the searched location, to provide personalized answers to tourists. To evaluate the proposed model, we used three techniques relevant, namely: evaluation of scenarios, performance evaluation and evaluation of usability. In performance evaluation proved the viability of the model by testing done in the cloud computing environment. In evaluating usability volunteered invited to use the mobile client application Ataîru, where the objective was to evaluate (1) perceived ease of use and (2) application utility perception, and (3) perceived usefulness of the information presented, increasing percentage of total concordance of 72.5%, 82.5% and 67.5%, respectively, and partial concordance 27.5%, 15% and 30%, respectively. This shows that the model supplies the need of tourist of tourist information about cities considered small or far from significant tourist sites, both in quantitative and qualitative aspect.

L'évolution rapide du web a changé la façon dont l'information est créée, distribuée, évaluée et consommée. L'utilisateur est dorénavant mis au centre du web en devenant le générateur de contenu le plus prolifique. Pour évoluer dans le flot d'informations, les utilisateurs ont besoin de filtrer le contenu en fonction de leurs centres d'intérêts. Pour bénéficier de contenus personnalisés, les utilisateurs font appel aux réseaux sociaux ou aux systèmes de recommandations exploitant leurs informations privées. Cependant, ces systèmes posent des problèmes de passage à l'échelle, ne prennent pas en compte la nature dynamique de l'information et soulèvent de multiples questions d'un point de vue de la vie privée. Dans cette thèse, nous exploitons les architectures pair-à-pair pour implémenter des systèmes de recommandations pour la dissémination personnalisée des news. Une approche pair-à-pair permet un passage à l'échelle naturel et évite qu'une entité centrale contrôle tous les profils des utilisateurs. Cependant, l'absence de connaissance globale fait appel à des schémas de filtrage collaboratif qui doivent palier les informations partielles et dynamiques des utilisateurs. De plus, ce schéma de filtrage doit pouvoir respecter la vie privée des utilisateurs. La première contribution de cette thèse démontre la faisabilité d'un système de recommandation de news totalement distribué. Le système proposé maintient dynamiquement un réseau social implicit pour chaque utilisateur basé sur les opinions qu'il exprime à propos des news reçues. Les news sont disséminées au travers d'un protocole épidémique hétérogène qui (1) biaise l'orientation des cibles et (2) amplifie la dissémination de chaque news en fonction du niveau d'intérêt qu'elle suscite. Ensuite, pour améliorer la vie privée des utilisateurs, nous proposons des mécanismes d'offuscation permettant de cacher le profil exact des utilisateurs sans trop dégrader la qualité de la recommandation fournie. Enfin, nous explorons un nouveau modèle tirant parti des avantages des systèmes distribués tout en conservant une architecture centralisée. Cette solution hybride et générique permet de démocratiser les systèmes de recommandations en offrant aux fournisseurs de contenu un système de personnalisation à faible coût. / The rapid evolution of the web has changed the way information is created, distributed, evaluated and consumed. Users are now at the center of the web and becoming the most prolific content generators. To effectively navigate through the stream of available news, users require tools to efficiently filter the content according to their interests. To receive personalized content, users exploit social networks and recommendation systems using their private data. However, these systems face scalability issues, have difficulties in coping with interest dynamics, and raise a multitude of privacy challenges. In this thesis, we exploit peer-to-peer networks to propose a recommendation system to disseminate news in a personalized manner. Peer-to-peer approaches provide highly-scalable systems and are an interesting alternative to Big brother type companies. However, the absence of any global knowledge calls for collaborative filtering schemes that can cope with partial and dynamic interest profiles. Furthermore, the collaborative filtering schemes must not hurt the privacy of users. The first contribution of this thesis conveys the feasibility of a fully decentralized news recommender. The proposed system constructs an implicit social network based on user profiles that express the opinions of users about the news items they receive. News items are disseminated through a heterogeneous gossip protocol that (1) biases the orientation of the dissemination, and (2) amplifies dissemination based on the level of interest in each news item. Then, we propose obfuscation mechanisms to preserve privacy without sacrificing the quality of the recommendation. Finally, we explore a novel scheme leveraging the power of the distribution in a centralized architecture. This hybrid and generic scheme democratizes personalized systems by providing an online, cost-effective and scalable architecture for content providers at a minimal investment cost.

Les nouveaux besoins en matière de soins et de prise en charge des patients ont contribué à la création des réseaux de santé. En plein développement, ils font partie intégrante du paysage du système sanitaire français. L’impact, pour les professionnels de santé, du travail en réseau fait aujourd’hui l’objet de plusieurs recherches et résultats contrastés, mais a peu été étudié du point de vue de la Psychologie Sociale, du Travail et des Organisations. Cette thèse a pour objectifs d’une part, de décrire les effets de la participation à un réseau de santé au niveau des pratiques professionnelles et au niveau de la santé psychique au travail, et d’autre part, d’examiner les variables et processus pouvant rendre compte de la variabilité de ces effets. Cette recherche privilégie une approche du réseau de santé comme un lieu potentiel de socialisation et de personnalisation (Malrieu & Malrieu, 1973) pour les professionnels qui en font partie La recherche sur le terrain a été réalisée en collaboration avec le réseau de santé ville-hôpital RéPPOP Midi-Pyrénées (Réseau Prévention et Prise en charge Obésité Pédiatrique) qui a la particularité de fonctionner sur la base de Trios/Duos de partenaires pour la prise en charge de l’enfant. Autour du médecin référent, ces partenaires peuvent être des diététicien(ne)s, des psychologues, des kinésithérapeutes… Nous posons l’hypothèse selon laquelle les effets de l’appartenance à un réseau de santé varient en fonction de variables individuelles (ancienneté de l’appartenance au réseau de santé et motivations initiales d’adhésion) et de variables organisationnelles (structuration en Duo/Trio et liens avec l’équipe de coordination du RéPPOP Midi-Pyrénées). Pour autant, une variable-clé, susceptible de moduler ces relations, sera placée au centre de notre recherche : la dynamique collective des Trios/Duos, analysée en référence aux concepts de « travail collectif », « collectif de travail » et « activité collective » (Caroly, 2010).Une étude par entretiens semi-directifs de recherche a été menée auprès de 20 professionnels libéraux et membres du réseau RéPPOP Midi-Pyrénées répartis en 4 Trios et 4 Duos. L’analyse des données a permis de caractériser trois types de dynamiques collectives différenciées quant aux ressorts du travail collectif, aux étayages du collectif de travail et à l’orientation intra-RéPPOP ou hors-RéPPOP de l’activité collective. Les résultats permettent d’appréhender comment chacune peut influer sur la relation entre transformation des pratiques et évolution de la santé psychique. De nouvelles perspectives de recherche et d’action auprès des partenaires du réseau sont proposées à l’issue de ces analyses. / The new needs as regards care and taking charge of patients have contributed to the creation of health networks. As they are growing fast, they are an integral part of the French sanitation system. The impact, on the health professionals, of networking is, today, the object of contrasted research and results, but has little been studied as far as Social Psychology, Work and Organizations are concerned. The aim of this thesis is, on the one hand, to describe the effects of the participation to a health network where professional practices and psychic health at work are concerned and, on the other hand, to examine the variables and process accounting for the variability of these effects. This research privileges an approach to the health network as a place of socialization and personalization (Malrieu & Malrieu, 1973). The research on the ground is carried out in collaboration with the health network town-hospital RéPPOP Midi-Pyrénées (Prevention and Taking charge of Pediatric Obesity Network) , which has the specificity to work on the basis of Trios/Duos of partners to take charge of children. Those partners can be doctors, dieticians, psychologists, physiotherapists… However , another key-variable, able to moderate these relationships, will be taken into account : the collective dynamics will be analyzed according to the theoretical concepts of “collective work”, “working collective” and collective activity (Caroly, 2010).We assume that the effects of being part of a health network vary according to individual variables ( length of time in the health network and initial adhesion motivations ) and to organizational variables ( structuring in Trios/Duos and links with the coordination team of the RePPOP Midi-Pyrénées ). Which will be modulated by the functioning dynamics between partners of the Trio/Duo. In a clinical approach, we have carried out semi-guided interviews with twenty private professionals and members of the RePPOP Midi-Pyrénées network, divided into 4 Trios and 4 Duos. The data analysis enabled us to characterize three kinds of collective dynamics, distinguished on collective work resources, working collective stayings and collective activity orientation. The results show how each pattern can have an influence on the relationship between practices changes and psychological health evolution. The results have enabled us to identify new explanatory elements of the variability due to belonging to a health network which supports research and application prospects on the ground next to the concerned professionals.

As information continues to grow at a very fast pace, our ability to access this information effectively does not, and we are often realize how harder is getting to locate an object quickly and easily. The so-called personalization technology is one of the best solutions to this information overload problem: by automatically learning the user profile, personalized information services have the potential to offer users a more proactive and intelligent form of information access that is designed to assist us in finding interesting objects. Recommender systems, which have emerged as a solution to minimize the problem of information overload, provide us with recommendations of content suited to our needs. In order to provide recommendations as close as possible to a user&rsquo / s taste, personalized recommender systems require accurate user models of characteristics, preferences and needs. Collaborative filtering is a widely accepted technique to provide recommendations based on ratings of similar users, But it suffers from several issues like data sparsity and cold start. In one-class collaborative filtering, a special type of collaborative filtering methods that aims to deal with datasets that lack counter-examples, the challenge is even greater, since these datasets are even sparser. In this thesis, we present a series of experiments conducted on a real-life customer purchase database from a major Turkish E-Commerce site. The sparsity problem is handled by the use of content-based technique combined with TFIDF weights, memory based collaborative filtering combined with different similarity measures and also hybrids approaches, and also model based collaborative filtering with the use of Singular Value Decomposition (SVD). Our study showed that the binary similarity measure and SVD outperform conventional measures in this OCCF dataset.

Den här uppsatsen är en studie om hur politiker ser på bloggen som ett politiskt verktyg. I dagens samhälle har tekniken öppnat upp för nya kommunikationskanaler och internet har blivit en plattform för interaktion. Bloggen har skapat nya möjligheter för politikern att sprida budskap till medborgarna och medierna eftersom den ger politikern kontroll över det egna ordet. Syftet är att undersöka på vilket sätt politiker i Kungsbacka kommun på lokal-, regional- och riksnivåanvänder sig av bloggar, och hur de ser på bloggen som verktyg för att sprida budskap, skapa opinion och ha kontroll över ordet. Studiens frågeställningar är: Hur ser innehållet på bloggarna ut, vad är politikerns syfte med bloggen, och hur ser interaktionen med medborgarna ut på bloggarna. I studien har vi använt flera teorier som ligger inom medie- ochkommunikationsvetenskap med fokusering på politisk kommunikation. Dessa teorier är kommunikationsteorin, politisk kommunikation, professionalisering, personifiering, medialisering, dagordningsteorin, opinionsbildning och gatekeepingteorin. Undersökningen bygger på kvalitativa samtalsintervjuer med politiker i Kungsbacka kommun. Vi har även gjorten kvantitativ innehållsanalys av dessa politikers bloggar. Studien visar att samtliga politiker serbloggen som ett verktyg att sprida sina budskap med. De beskrev bloggen som enenvägskommunikation som används för att direkt påverka medborgarna eller för att påverka mediers dagordning, och på så sätt påverka medborgarna indirekt. Interaktionen med medborgarna genom bloggen förekom sällan.

Recently, it has become more and more difficult for the existing web based systems to locate or retrieve any kind of relevant information, due to the rapid growth of the World Wide Web (WWW) in terms of the information space and the amount of the users in that space. However, in today&#039 / s world, many systems and approaches make it possible for the users to be guided by the recommendations that they provide about new items such as articles, news, books, music, and movies. However, a lot of traditional recommender systems result in failure when the data to be used throughout the recommendation process is sparse. In another sense, when there exists an inadequate number of items or users in the system, unsuccessful recommendations are produced. Within this thesis work, ReMovender, a web based movie recommendation system, which uses a content boosted collaborative filtering approach, will be presented. ReMovender combines the local/global similarity and missing data prediction v techniques in order to handle the previously mentioned sparseness problem effectively. Besides, by putting the content information of the movies into consideration during the item similarity calculations, the goal of making more successful and realistic predictions is achieved.

Die Notwendigkeit zur Nutzung von nicht-individuell entwickelter Software entsteht im Geschäfts- und Arbeitsfeld auf Grund der Entwicklung in diesem Bereich. Unternehmen müssen sich ständig ändernden Anforderungen im Geschäftsumfeld stellen. Mit dem immer stärker werdenden Wettbewerb ist es erforderlich, sich auf eigene Kernkompetenzen zu konzentrieren und zeitliche Kooperation bzw. Beziehungen mit anderen Organisationen einzugehen. Um diesen Beziehungen und Anforderungen gerecht zu werden, müssen Software bzw. Softwarebausteine flexibel und temporär bezogen werden. Um den Nutzern dieser Software eine bestmögliche Unterstützung bei der Auswahl ihrer bedarfsgerechten Komponenten zu geben, sollen Ihnen, anhand von Entscheidungen bereits bestehender Kunden, Vorschläge für Objekte unterbreitet werden. Diese Objekte können je nach System zum Beispiel Konfigurationseigenschaften, Inhaltsmodule oder Layoutdarstellungen sein. Es wird davon ausgegangen, dass ähnliche Nutzer auch ähnliche Objekte benötigen. Aus diesem Grund sollen die Nutzer miteinander verglichen werden. Das Problem liegt an dieser Stelle in der Beschreibung eines Nutzers. Dieser kann durch eine Vielzahl von Merkmalen gekennzeichnet werden, welche je nach Objekt eine unterschiedliche Wichtigkeit bei der Entscheidung haben. Aus diesem Grund müssen die einzelnen Merkmale unabhängig von einander betrachtet werden. Bei der Bewertung eines Objektes sollen dann entsprechende Wichtungen für das jeweilige Merkmal integriert werden. Der Vergleich ist erst dadurch möglich, dass der Kontext und damit die Aufgabe des Nutzers bekannt sind. Nur mit diesen Informationen können gezielte Empfehlungen erstellt werden. Es wird ein Verfahren vorgestellt, welches die priorisierte Bewertung einzelner Merkmale einbezieht. Ausgehend von diesem Verfahren wird ein Algorithmus vorgestellt, welcher Nutzer anhand ihrer Merkmale vergleicht und daraus folgend Empfehlungen für Objekte ausgibt. Der Algorithmus soll in ein Recommender-System integriert werden.

Τα τελευταία χρόνια η αυξανόμενη σημασία της πληροφορίας και της συνεχιζόμενης μάθησης έχει καταστήσει τη χρήση των τεχνολογιών πληροφορικής και επικοινωνιών (Τ.Π.Ε.) στην εκπαίδευση καθώς και την εξ αποστάσεως εκπαίδευση μέσω e-learning συστημάτων, ως επιτακτική ανάγκη. Το κυριότερο πλεονέκτημα των e-learning συστημάτων είναι ότι παρέχουν τη δυνατότητα στον κόσμο να παρακολουθήσει ένα μάθημα, ακόμα κι ένα ολόκληρο πρόγραμμα σπουδών εξ αποστάσεως, μέσω της σύγχρονης και παγκοσμίως πλέον διαδεδομένης μεθόδου των online courses. Τα περισσότερα μεγάλης εμβέλειας και αναγνωρισιμότητας, πανεπιστήμια του εξωτερικού προσφέρουν online μαθήματα μέσω τεχνολογιών του διαδικτύου, χρησιμοποιώντας διαφάνειες, βιντεο-διαλέξεις και online εκπαιδευτικές δραστηριότητες. Ένας τομέας όμως στον οποίο υστερεί η εκπαίδευση εξ αποστάσεως, ακόμα και στα πιο πρόσφατα ανεπτυγμένα e-learning συστήματα, είναι ο τομέας της προσωποποίησης του σπουδαστή και εξατομίκευσης του συστήματος στις ανάγκες του. Η παρούσα διπλωματική εργασία παρουσιάζει τις δυνατότητες που παρέχονται από τα ήδη υπάρχοντα συστήματα e-learning, την τωρινή κατάσταση με τα παρεχόμενα online μαθήματα από πανεπιστήμια του εξωτερικού και το ερευνητικό κενό που υπάρχει σχετικά με την «προσωποποίηση» (personalization) του σπουδαστή και την προσαρμογή (adaptation) του συστήματος στις ανάγκες του. Μελετάται η μοντελοποίηση του χρήστη (user modeling), τα μαθησιακά προφίλ, ο εμπλουτισμός του προφίλ του σπουδαστή ώστε να παρέχει περισσότερες και αξιόλογες πληροφορίες, καθώς και οι δυνατότητες εξατομίκευσης του συστήματος στον εκάστοτε σπουδαστή, ώστε να επιτευχθεί η επιτάχυνση και αποτελεσματικότητα της ηλεκτρονικής μάθησης. Στα πλαίσια της παρούσας διπλωματικής εργασίας σχεδιάστηκε και υλοποιήθηκε ένα σύστημα ηλεκτρονικής μάθησης, το οποίο στηρίζεται στο λογισμικό Moodle και έχουν αναπτυχθεί σε αυτό, νέες υπηρεσίες εξατομίκευσης και προσαρμοστικότητας του συστήματος στις ανάγκες και προτιμήσεις του εκπαιδευομένου. Το Moodle LMS (Modular Object Oriented Dynamic Learning Environment) είναι ελεύθερο λογισμικό διαχείρισης εκπαιδευτικού περιεχομένου και χρησιμοποιείται από πολλά πανεπιστήμια παγκοσμίως. Είναι ευέλικτο, εύκολο στην εκμάθηση και αρκετά ασφαλές για την ασύγχρονη εκπαίδευση από απόσταση. Ενσωματώνει πληθώρα λειτουργιών και δυνατοτήτων που επιτρέπουν στο διδάσκοντα να διαμορφώσει ένα καλά οργανωμένο και ευχάριστο μάθημα με ευρεία κλίμακα δραστηριοτήτων. Στο εξατομικευμένο και προσαρμοστικό σύστημα ηλεκτρονικής μάθησης που αναπτύχθηκε, διαμορφώθηκε ένα μάθημα με πλούσιο εκπαιδευτικό υλικό, το οποίο απαρτίζουν πολλά και διαφορετικού τύπου μαθησιακά αντικείμενα (πηγές πληροφόρησης, δραστηριότητες, κ.α.). Εμπλουτίστηκε το προφίλ χρήστη με περισσότερες προσωπικές πληροφορίες γι αυτόν και στη συνέχεια αναπτύχθηκαν μαθησιακά μονοπάτια που στηρίζονται είτε στα πεδία προφίλ χρήστη, είτε στο μαθησιακό στυλ του εκπαιδευομένου, είτε σε άλλους παράγοντες που παρουσιάζονται αναλυτικά στην εργασία. Για την εξατομίκευση του συστήματος αναπτύχθηκε μία ενότητα «Pre-course test» η οποία περιλαμβάνει δύο νέες υπηρεσίες για την άντληση πληροφοριών του χρήστη, μορφωτικό υπόβαθρο, μαθησιακό στυλ, προηγούμενη γνώση στο αντικείμενο του μαθήματος κ.α. Τα αποτελέσματα που προκύπτουν από εκεί, αξιοποιούνται κατάλληλα για τη διαμόρφωση ομάδων των εκπαιδευομένων και για τις υπηρεσίες προσαρμοστικότητας του συστήματος. Επίσης, στο διαδικτυακό αυτό σύστημα ηλεκτρονικής μάθησης έχουν αναπτυχθεί μαθησιακά αντικείμενα που ενισχύουν στη συνεργατική μάθηση, βελτιώνουν την ποιότητα του μαθήματος και έτσι αυξάνεται το κίνητρο του σπουδαστή. / Nowdays, e-learning environments have become increasingly popular in educational establishments. The rapid growth of e-learning has changed traditional learning behavior and presented a new situation to both educators (lecturers) and learners (students). The majority of current e-learning systems are based on Learning Management Systems (LMS), which allow students attending courses free from space and time limitations. They can attend the class anytime they are available and regardless of the place. LMS are web-based educational systems that offer students an active role in their own education through a variety of learning activities and different kinds of learning content, that the educator has produced. Although this fact, most Learning Management Systems lack of personalization and adaptivity features. The modern trend in education is the production and organization of Massive Open Online Courses (MOOCs) from large and internationally recognized Universities. So, they focus on gathering too many people in these courses (MOOCs) and not on personalization and adaptivity. Personalization in web-based systems means “attention to the user and his needs”. Web-based systems, such as e-commerce sites, focus on personalization by observing the user, his common actions and navigation paths, in order to understand his preferences and what he is looking for. So they differentiate each individual according to his interests, preferences, and generally his “profile”. Then, they adapt the content appropriately to his needs, and the user watches first the content that may interest him. Traditional and commonly used e-learning platforms offer to their users same educational content, same learning activities and possibilities, and generally exactly the same content, with no further personalization support. Some existing open source e-Learning systems may support, under certain circumstances adaptation and personalization features, but need extension and elaboration to acquire sufficiently these characteristics. Especially in the case of distance learning, that teacher and students have no face-to-face communication, learner’s personalization is essential in order the teacher to be aware of each learner’s characteristics. In e-learning systems, personalization could be achieved with an integrated user profile (student profile), which would include except from the classic information (name, surname, email) more specific and useful information. If the teacher had more information about each student, he could be able to guide him more effectively and evaluate him more correctly. In addition to that, if teacher was aware of each learner’s profile, meaning his learning style, interests, preferences and his previous knowledge of the course topics, he would be able to adapt the learning content to his needs. That would increase student’s satisfaction, motivation and consequently his participation in the course. In this master thesis, a personalized and adaptive e-learning system has been developed. The development of this integrated personalized e-learning system, is based on a very popular open source LMS, which in this case is used for further extension and development of new features. The most suitable LMS for implementing those new features is Moodle (Modular Object-oriented Dynamic Learning Environment), due to its modularity and extensibility as well as its vast community of users. There have been added new features in order to enrich student’s profile and adjust learning material to the learner, depending on his profile and learning progress. The teacher has the ability to organize suitable learning objects and learning paths for each student, depending on particular user profile fields, learning styles and student’s performance. This personalized and adaptive e-learning system increases student’s motivation and participation.