Context-aware mobile learning on the semantic web / by Xiaoyun Zhang.

Progress made in Semantic Web technologies and Ubiquitous Computing has lead to the development of mobile learning services that can adapt to the learner's background, learner's needs, and surrounding environment. In particular, the emerging techniques from these two technologies have the potential to revolutionize the way mobile learning services available on the web are discovered, adapted, and delivered according to context. Context acquisition and management, conceptual knowledge modeling and reasoning, and adaptive services discovery are the main ingredients for designing such context-aware mobile learning systems. However, a number of challenges are still facing the research community in this field. These can be summarized in the following: (i) current mobile learning services act as passive components rather than active components that can be embedded with context awareness mechanisms, (ii) existing approaches for service composition neglect contextual information on surrounding environment, and (iii) lack of context modeling and reasoning techniques for integrating the various contextual features for better personalization. In this thesis an attempt is made to solve the above-mentioned problems. These challenges are addressed by proposing a personalized mobile learning system based on a global ontology space to aggregate and manage context information related to the learner, the used device, the surrounding environment, and the task at hand. The system adopts a unified reasoning mechanism, around the global ontology space, in order to adapt the learning sequence and the learning content based on the learner profile and the perceived contextual information. The adopted approach for ontology reasoning aims at achieving two types of adaptations--system-centric adaptation and--learner-centric adaptation. These are implemented on a Run-Time Environment that identifies new contextual changes and translates them into new adaptation constraints. We developed and tested our system on a number of subject-domain ontologies using various learning scenarios, and the obtained experimental results are very promising

Conceptual spatial representations for indoor mobile robots

We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of typical indoor environments. Following findings in cognitive psychology, our model is composed of layers representing maps at different levels of abstraction. The complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. The system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. Finally, we discuss the capabilities of the integrated system

Collaboration in the Semantic Grid: a Basis for e-Learning

The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

Sensory semantic user interfaces (SenSUI)

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology

Service-oriented Context-aware Framework

Location- and context-aware services are emerging technologies in mobile and desktop environments, however, most of them are difficult to use and do not seem to be beneficial enough. Our research focuses on designing and creating a service-oriented framework that helps location- and context-aware, client-service type application development and use. Location information is combined with other contexts such as the users' history, preferences and disabilities. The framework also handles the spatial model of the environment (e.g. map of a room or a building) as a context. The framework is built on a semantic backend where the ontologies are represented using the OWL description language. The use of ontologies enables the framework to run inference tasks and to easily adapt to new context types. The framework contains a compatibility layer for positioning devices, which hides the technical differences of positioning technologies and enables the combination of location data of various sources

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges