State of the Art About Remote Laboratories Paradigms - Foundations of Ongoing Mutations

9 pages. Litterature review made fall 2007 on exisiting Remote Laboratories approaches and technologies.International audienceIn this paper, we provide a literature review of modern remote laboratories. According to this state-of-theart, we explain why remote laboratories are at a technological crossroad, whereas they were slugging for a decade. From various observations based on our review, we try to identify possible evolutions for the next generation of remote laboratories

Flexible Macroblock Ordering for Context-Aware Ultrasound Video Transmission over Mobile WiMAX

The most recent network technologies are enabling a variety of new applications, thanks to the provision of increased bandwidth and better management of Quality of Service. Nevertheless, telemedical services involving multimedia data are still lagging behind, due to the concern of the end users, that is, clinicians and also patients, about the low quality provided. Indeed, emerging network technologies should be appropriately exploited by designing the transmission strategy focusing on quality provision for end users. Stemming from this principle, we propose here a context-aware transmission strategy for medical video transmission over WiMAX systems. Context, in terms of regions of interest (ROI) in a specific session, is taken into account for the identification of multiple regions of interest, and compression/transmission strategies are tailored to such context information. We present a methodology based on H.264 medical video compression and Flexible Macroblock Ordering (FMO) for ROI identification. Two different unequal error protection methodologies, providing higher protection to the most diagnostically relevant data, are presented

CAIN-21: Automatic adaptation decisions and extensibility in an MPEG-21 adaptation engine

This paper presents the progress and final state of CAIN-21, an extensible and metadata driven multimedia adaptation in the MPEG-21 framework. CAIN-21 facilitates the integration of pluggable multimedia adaptation tools, automatically chooses the chain of adaptations to perform and manages its execution. To drive the adaptation, it uses the description tools and implied ontology established by MPEG-21. The paper not only describes the evolution and latest version of CAIN-21, but also identifies limitations and ambiguities in the description capabilities of MPEG-21. Therefore, it proposes some extensions to the MPEG-21 description schema for removing these problems. Finally, the pros and cons of CAIN-21 with respect to other multimedia adaptation engines are discussed

Multi-fractal dimension features by enhancing and segmenting mammogram images of breast cancer

The common malignancy which causes deaths in women is breast cancer. Early detection of breast cancer using mammographic image can help in reducing the mortality rate and the probability of recurrence. Through mammographic examination, breast lesions can be detected and classified. Breast lesions can be detected using many popular tools such as Magnetic Resonance Imaging (MRI), ultrasonography, and mammography. Although mammography is very useful in the diagnosis of breast cancer, the pattern similarities between normal and pathologic cases makes the process of diagnosis difficult. Therefore, in this thesis Computer Aided Diagnosing (CAD) systems have been developed to help doctors and technicians in detecting lesions. The thesis aims to increase the accuracy of diagnosing breast cancer for optimal classification of cancer. It is achieved using Machine Learning (ML) and image processing techniques on mammogram images. This thesis also proposes an improvement of an automated extraction of powerful texture sign for classification by enhancing and segmenting the breast cancer mammogram images. The proposed CAD system consists of five stages namely pre-processing, segmentation, feature extraction, feature selection, and classification. First stage is pre-processing that is used for noise reduction due to noises in mammogram image. Therefore, based on the frequency domain this thesis employed wavelet transform to enhance mammogram images in pre-processing stage for two purposes which is to highlight the border of mammogram images for segmentation stage, and to enhance the region of interest (ROI) using adaptive threshold in the mammogram images for feature extraction purpose. Second stage is segmentation process to identify ROI in mammogram images. It is a difficult task because of several landmarks such as breast boundary and artifacts as well as pectoral muscle in Medio-Lateral Oblique (MLO). Thus, this thesis presents an automatic segmentation algorithm based on new thresholding combined with image processing techniques. Experimental results demonstrate that the proposed model increases segmentation accuracy of the ROI from breast background, landmarks, and pectoral muscle. Third stage is feature extraction where enhancement model based on fractal dimension is proposed to derive significant mammogram image texture features. Based on the proposed, model a powerful texture sign for classification are extracted. Fourth stage is feature selection where Genetic Algorithm (GA) technique has been used as a feature selection technique to select the important features. In last classification stage, Artificial Neural Network (ANN) technique has been used to differentiate between Benign and Malignant classes of cancer using the most relevant texture feature. As a conclusion, classification accuracy, sensitivity, and specificity obtained by the proposed CAD system are improved in comparison to previous studies. This thesis has practical contribution in identification of breast cancer using mammogram images and better classification accuracy of benign and malign lesions using ML and image processing techniques

MC2: MPEG-7 content modelling communities

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe use of multimedia content on the web has grown significantly in recent years. Websites such as Facebook, YouTube and Flickr cater for enormous amounts of multimedia content uploaded by users. This vast amount of multimedia content requires comprehensive content modelling otherwise retrieving relevant content will be challenging. Modelling multimedia content can be an extremely time consuming task that may seem impossible particularly when undertaken by individual users. However, the advent of Web 2.0 and associated communities, such as YouTube and Flickr, has shown that users appear to be more willing to collaborate in order to take on enormous tasks such as multimedia content modelling. Harnessing the power of communities to achieve comprehensive content modelling is the primary focus of this research. The aim of this thesis is to explore collaborative multimedia content modelling and in particular the effectiveness of existing multimedia content modelling tools, taking into account the key development challenges of existing collaborative content modelling research and the associated modelling tools. Four research objectives are pursued in order to achieve this; first, design a user experiment to study users’ tagging behaviour with existing multimedia tagging tools and identify any relationships between such user behaviour; second, design and develop a framework for MPEG-7 content modelling communities based on the results of the experiment; third, implement an online service as a proof of concept of the framework; fourth, validate the framework through the online service during a repeat of the initial user experiment. This research contributes first, a conceptual model of user behaviour visualised as a fuzzy cognitive map and, second, an MPEG-7 framework for multimedia content modelling communities (MC2) and its proof of concept as an online service. The fuzzy cognitive model embodies relationships between user tagging behaviour and context and provides an understanding of user priorities in the description of content features and the relationships that exist between them. The MC2 framework, developed based on the fuzzy cognitive model, is deep-rooted in user content modelling behaviour and content preferences. A proof of concept of the MC2 framework is implemented as an online service in which all metadata is modelled using MPEG-7. The online service is validated, first, empirically with the same group of users and through the same experiment that led to the development of the fuzzy cognitive model and, second, functionally against the folksonomy and MPEG-7 content modelling tools used in the initial experiment. The validation demonstrates that MC2 has the advantages without the shortcomings of existing multimedia tagging tools by harnessing the ease of use of folksonomy tools while producing comprehensive structured metadata.Supported by UK Engineering and Physical Sciences Research Council (EPSRC

Performing Paradise in the Early Christian Baptistery: Art, Liturgy, and the Transformation of Vision

Images representing paradise were some of the most pervasive in Early Christian churches throughout the Mediterranean from approximately the fourth to sixth centuries, but it was only through the baptistery and its attendant rituals that the Christian initiate entered the faith community and had subsequent access to the pictorial cycles within the church interior. The baptistery was both the actual and metaphysical gateway for Christian initiates entering the Church, understood symbolically as the body of Christ and physically as the primary location of Christian cult adjacent to the baptistery. The role of paradise within that space, therefore, offers unique insight into the trajectory of Early Christian beliefs in salvation, as well as the threshold of earthly and heavenly existence that Christian initiates were thought to inhabit within baptismal space. Baptistery research has surged in the last fifteen years, but the focus has been primarily architectural and typological. This dissertation shifts the discussion toward a more theoretical context for understanding how visions of paradise were constructed in Christianity’s central induction ritual. The dissertation examines the pictorial, material, and liturgical strategies employed in Early Christian baptisteries of the Mediterranean to recreate paradise sensorially. The experience of paradise not only transformed baptismal initiates into new Adams and Eves reenacting the fall of humanity upon an Edenic stage, but it also facilitated the transformation of the carnal senses into spiritual perception, deemed necessary for physical bodies occupying a liminal space that was thought to unify terrestrial and celestial realities. I examine the development and transmission of paradisiacal motifs and strategies of vision and the manipulation of sensory experience in the baptisteries of Italy, North Africa, and the southwestern Balkans, pairing them with contemporary theories of performative space and late-antique discourse on sensory perception

Contribution à l'analyse des séquences de protéines similarité, clustering et alignement

La prédiction des fonctions biologiques des protéines est primordiale en biologie cellulaire. On peut comprendre facilement tout l'enjeu de pouvoir différencier efficacement les protéines par leurs fonctions, quand on sait que ceci peut rendre possible la réparation des protéines anormales causants des maladies, ou du moins corriger ou améliorer leurs fonctions. Les méthodes expérimentales, basées sur la structure tridimensionnelle des protéines sont les plus fiables pour la prédiction des fonctions biologiques des protéines. Néanmoins, elles sont souvent coûteuses en temps et en ressources, et ne permettent pas de traiter de grands nombres de protéines. Il existe toutefois des algorithmes qui permettent aux biologistes d'arriver à de bons résultats de prédictions en utilisant des moyens beaucoup moins coûteux. Le plus souvent, ces algorithmes sont basés sur la similarité, le clustering, et l'alignement. Cependant, les algorithmes qui sont basés sur la similarité et le clustering utilisent souvent l'alignement des séquences et ne sont donc pas efficaces sur les protéines non alignables. Et lorsqu'ils ne sont pas basés sur l 'alignement, ces algorithmes utilisent souvent des approches qui ne tiennent pas compte de l'aspect biologique des séquences de protéines. D'autre part, l'efficacité des algorithmes d'alignements dépend souvent de la nature structurelle des protéines, ce qui rend difficile le choix de l'algorithme à utiliser quand la structure est inconnue. Par ailleurs, les algorithmes d'alignement ignorent les divergences entre les séquences à aligner, ce qui contraint souvent les biologistes à traiter manuellement les séquences à aligner, une tâche qui n'est pas toujours possible en pratique. Dans cette thèse nous présentons un ensemble de nouveaux algorithmes que nous avons conçus pour l'analyse des séquences de protéines. Dans le premier chapitre, nous présentons CLUSS, le premier algorithme de clustering capable de traiter des séquences de protéines non-alignables. Dans le deuxième chapitre, nous présentons CLUSS2 une version améliorée de CLUSS, capable de traiter de plus grands ensembles de protéines avec plus de de fonctions biologiques. Dans le troisième chapitre, nous présentons SCS, une nouvelle mesure de similarité capable de traiter efficacement non seulement les séquences de protéines mais aussi plusieurs types de séquences catégoriques. Dans le dernier chapitre, nous présentons ALIGNER, un algorithme d'alignement, efficace sur les séquences de protéines indépendamment de leurs types de structures. De plus, ALIGNER est capable de détecter automatiquement, parmi les protéines à aligner, les groupes de protéines dont l'alignement peut révéler d'importantes propriétés biochimiques structurelles et fonctionnelles, et cela sans faire appel à l'utilisateur

L'Africa romana: trasformazione dei paesaggi del potere nell'Africa settentrionale fino alla fine del mondo antico: atti del 19. Convegno di studio

L'opera raccoglie gli Atti del 19. Convegno internazionale L’Africa romana (Sassari, 16-19 dicembre 2010), dedicato alla trasformazione dei paesaggi del potere nell’Africa settentrionale fino alla fine del mondo antico