Ontology-based user modeling in an augmented audio reality system for museums

Ubiquitous computing is a challenging area that allows us to further our understanding and techniques of context-aware and adaptive systems. Among the challenges is the general problem of capturing the larger context in interaction from the perspective of user modeling and human–computer interaction (HCI). The imperative to address this issue is great considering the emergence of ubiquitous and mobile computing environments. This paper provides an account of our addressing the specific problem of supporting functionality as well as the experience design issues related to museum visits through user modeling in combination with an audio augmented reality and tangible user interface system. This paper details our deployment and evaluation of ec(h)o – an augmented audio reality system for museums. We explore the possibility of supporting a context-aware adaptive system by linking environment, interaction object and users at an abstract semantic level instead of at the content level. From the user modeling perspective ec(h)o is a knowledge based recommender system. In this paper we present our findings from user testing and how our approach works well with an audio and tangible user interface within a ubiquitous computing system. We conclude by showing where further research is needed

Adaptive manuals as assistive technology to support and train people with acquired brain injury in their daily life activities

The final publication is available at Springer via http://dx.doi.org/10.1007/s00779-012-0560-zAssistive technologies and ubiquitous computing can be related since both try to help people in their lives. This common objective motivated us to develop and evaluate a system that puts ubiquitous computing technologies into the rehabilitation process of people with acquired brain injury. Thus, in this paper, we present and evaluate a system that shows adaptive manuals for daily-life activities for people with acquired brain injury. This first evaluation allowed us to validate our approach and also to extract valuable information about these systems as well as environmental factors that may affect the patients.This work was partially funded by ASIES (Adapting Social & Intelligent Environments to Support people with special needs), Ministerio de Ciencia e Innovación - TIN2010-17344, and e-Madrid (Investigación y desarrollo de tecnologías para el e-learning en la Comunidad de Madrid) S2009/TIC-1650

Conflicts treatment for ubiquitous collective and context-aware applications

Context-aware computing is a research field that defines systems capable of adapting their behavior according to any relevant information about entities (e.g., people, places and objects) of interest. The ubiquitous computing is closely related to the use of contexts, since it aims to provide personalized, transparent and on-demand services. Ubiquitous systems are frequently shared among multiple users, which may lead to conflicts that occur during adaptation actions due to individual profiles divergences and/or environment resources incompatibility. In such situations it is interesting to detect and solve those conflicts, considering what is better for the group but also being fair enough with each individual demand, whenever possible. This work presents the important concepts on the collective ubiquitous context-aware applications field. Furthermore, it proposes a novel methodology for conflicts detection and resolution that considers the trade-off between quality of services and resources consumption. A case study based on a collective tourist guide was implemented as a proof-of-study to the proposed methodology.Key words: context and awareness in collaborative systems, ubiquitous computing, adaptive collaborative environments

Self-adaptive unobtrusive interactions of mobile computing systems

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This infrastructure works from a set of high-level models that define the unobtrusive adaptation behavior and its implication with the interaction resources in a technology-independent way. Our infrastructure has been validated through several experiments to assess its correctness, performance, and the achieved user experience through a user study.This work has been developed with the support of MINECO under the project SMART-ADAPT TIN2013-42981-P, and co-financed by the Generalitat Valenciana under the postdoctoral fellowship APOSTD/2016/042.Gil Pascual, M.; Pelechano Ferragud, V. (2017). Self-adaptive unobtrusive interactions of mobile computing systems. Journal of Ambient Intelligence and Smart Environments. 9(6):659-688. https://doi.org/10.3233/AIS-170463S65968896Aleksy, M., Butter, T., & Schader, M. (2008). Context-Aware Loading for Mobile Applications. 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Computational Imaging Systems for High-speed, Adaptive Sensing Applications

Driven by the advances in signal processing and ubiquitous availability of high-speed low-cost computing resources over the past decade, computational imaging has seen the growing interest. Improvements on spatial, temporal, and spectral resolutions have been made with novel designs of imaging systems and optimization methods. However, there are two limitations in computational imaging. 1), Computational imaging requires full knowledge and representation of the imaging system called the forward model to reconstruct the object of interest. This limits the applications in the systems with a parameterized unknown forward model such as range imaging systems. 2), the regularization in the optimization process incorporates strong assumptions which may not accurately reflect the a priori distribution of the object. To overcome these limitations, we propose 1) novel optimization frameworks for applying computational imaging on active and passive range imaging systems and achieve 5-10 folds improvement on temporal resolution in various range imaging systems; 2) a data-driven method for estimating the distribution of high dimensional objects and a framework of adaptive sensing for maximum information gain. The adaptive strategy with our proposed method outperforms Gaussian process-based method consistently. The work would potentially benefit high-speed 3D imaging applications such as autonomous driving and adaptive sensing applications such as low-dose adaptive computed tomography(CT)

Semantic-based policy engineering for autonomic systems

This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

An Adaptive Design Methodology for Reduction of Product Development Risk

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an essential step in the development of any system, especially for Embedded System. This paper introduces a novel adaptive design methodology, which incorporates step-wise prototyping and verification. With each adaptive step product-realization level is enhanced while decreasing the level of product uncertainty, thereby reducing the overall costs. The back-bone of this frame-work is the development of Domain Specific Operational (DOP) Model and the associated Verification Instrumentation for Test and Evaluation, developed based on the DOP model. Together they generate functionally valid test-sequence for carrying out prototype evaluation. With the help of a case study 'Multimode Detection Subsystem' the application of this method is sketched. The design methodologies can be compared by defining and computing a generic performance criterion like Average design-cycle Risk. For the case study, by computing Average design-cycle Risk, it is shown that the adaptive method reduces the product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure

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