Sustainable linguistic repository built on DSpace

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A museum object repository using LIDO schema

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Leveraging open access for integrating repository data at Indiana University Libraries

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Repository sustainability

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

My repository is being aggregated: a blessing or a curse?

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

HIMALDOC: A Tool for a Regional Open Repository on Sustainable Mountain Development Issues in the Hindu Kush Himalaya

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The Human Communication Science Virtual Lab (HCS vLab): A repository microclimate in a rapidly evolving research-ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

ReShare and ReCollect: EPrints data repository solutions developed at the UK Data Archive

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Invenio as a platform to implement the SCOAP3 Repository

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

When Metadata Collides: Lessons on Combining Records from Multiple Repository Systems.

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Automatic Preparation of ETD Material from the Internet Archive for the DSpace Repository Platform

A big challenge associated with getting an institutional repository off the ground is getting content into it. This article will look at how to use digitization services at the Internet Archive alongside software utilities that the author developed to automate the harvesting of scanned dissertations and associated Dublin Core XML files to create an ETD Portal using the DSpace platform. The end result is a metadata-rich, full-text collection of theses that can be constructed for little out of pocket cost.

A lexical semantic study of Dene Suliné, an Athabaskan language

Cette thèse constitue une étude systématique du lexique du déné sųłiné, une langue athabaskane du nord-ouest canadien. Elle présente les définitions et les patrons de combinatoire syntaxique et lexicale de plus de 200 unités lexicales, lexèmes et phrasèmes, qui représentent une partie importante du vocabulaire déné sųłiné dans sept domaines: les émotions, le caractère humain, la description physique des entités, le mouvement des êtres vivants, la position des entités, les conditions atmospheriques et les formations topologiques, en les comparant avec le vocubulaire équivalent de l'anglais. L’approche théorique choisie est la Théorie Sens-Texte (TST), une approche formelle qui met l’accent sur la description sémantique et lexicographique empiriques. La présente recherche relève d'importantes différences entre le lexique du déné sųłiné et celui de l'anglais à tous les niveaux: dans la correspondence entre la représentation conceptuelle, considérée (quasi-)extralinguistique, et la structure sémantique; dans les patrons de lexicalisation des unités lexicales, et dans les patrons de combinatoire syntaxique et lexicale, qui montrent parfois des traits propres au déné sųłiné intéressants.

The Relation Between Depressive Symptoms and Semantic Memory in Amnestic Mild Cognitive Impairment and in Late-Life Depression

Semantic deficits have been documented in the prodromal phase of Alzheimer’s disease, but it is unclear whether these deficits are associated with non-cognitive manifestations. For instance, recent evidence indicates that cognitive deficits in elders with amnestic mild cognitive impairment (aMCI) are modulated by concomitant depressive symptoms. The purposes of this study were to (i) investigate if semantic memory impairment in aMCI is modulated according to the presence (aMCI-D group) or absence (aMCI group) of depressive symptoms, and (ii) compare semantic memory performance of aMCI and aMCI-D groups to that of patients with late-life depression (LLD). Seventeen aMCI, 16 aMCI-D, 15 LLD, and 26 healthy control participants were administered a semantic questionnaire assessing famous person knowledge. Results showed that performance of aMCI-D patients was impaired compared to the control and LLD groups. However, in the aMCI group performance was comparable to that of all other groups. Overall, these findings suggest that semantic deficits in aMCI are somewhat associated with the presence of concomitant depressive symptoms. However, depression alone cannot account solely for the semantic deficits since LLD patients showed no semantic memory impairment in this study. Future studies should aim at clarifying the association between depression and semantic deficits in older adults meeting aMCI criteria.