Energy conservation in mobile devices and applications: A case for context parsing, processing and distribution in clouds

Context information consumed and produced by the applications on mobile devices needs to be represented, disseminated, processed and consumed by numerous components in a context-aware system. Significant amounts of context consumption, production and processing takes place on mobile devices and there is limited or no support for collaborative modelling, persistence and processing between device-Cloud ecosystems. In this paper we propose an environment for context processing in a Cloud-based distributed infrastructure that offloads complex context processing from the applications on mobile devices. An experimental analysis of complexity based context-processing categories has been carried out to establish the processing-load boundary. The results demonstrate that the proposed collaborative infrastructure provides significant performance and energy conservation benefits for mobile devices and applications

Survey of context provisioning middleware

In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles. © 2009-2012 IEEE

Face processing in autism: Reduced integration of cross-feature dynamics

Characteristic problems with social interaction have prompted considerable interest in the face processing of individuals with Autism Spectrum Disorder (ASD). Studies suggest that reduced integration of information from disparate facial regions likely contributes to difficulties recognizing static faces in this population. Recent work also indicates that observers with ASD have problems using patterns of facial motion to judge identity and gender, and may be less able to derive global motion percepts. These findings raise the possibility that feature integration deficits also impact the perception of moving faces. To test this hypothesis, we examined whether observers with ASD exhibit susceptibility to a new dynamic face illusion, thought to index integration of moving facial features. When typical observers view eye-opening and -closing in the presence of asynchronous mouth-opening and -closing, the concurrent mouth movements induce a strong illusory slowing of the eye transitions. However, we find that observers with ASD are not susceptible to this illusion, suggestive of weaker integration of cross-feature dynamics. Nevertheless, observers with ASD and typical controls were equally able to detect the physical differences between comparison eye transitions. Importantly, this confirms that observers with ASD were able to fixate the eye-region, indicating that the striking group difference has a perceptual, not attentional origin. The clarity of the present results contrasts starkly with the modest effect sizes and equivocal findings seen throughout the literature on static face perception in ASD. We speculate that differences in the perception of facial motion may be a more reliable feature of this condition

Independence of face identity and expression processing: exploring the role of motion

According to the classic Bruce and Young (1986) model of face recognition, identity and emotional expression information from the face are processed in parallel and independently. Since this functional model was published, a growing body of research has challenged this viewpoint and instead support an interdependence view. In addition, neural models of face processing (Haxby, Hoffman & Gobbini, 2000) emphasise differences in terms of the processing of changeable and invariant aspects of faces. This article provides a critical appraisal of this literature and discusses the role of motion in both expression and identity recognition and the intertwined nature of identity, expression and motion processing. We conclude, by discussing recent advancements in this area and research questions that still need to be addressed

A framework for cloud-based context-aware information services for citizens in smart cities

© 2014 Khan et al.; licensee Springer. Background: In the context of smart cities, public participation and citizen science are key ingredients for informed and intelligent planning decisions and policy-making. However, citizens face a practical challenge in formulating coherent information sets from the large volumes of data available to them. These large data volumes materialise due to the increased utilisation of information and communication technologies in urban settings and local authorities’ reliance on such technologies to govern urban settlements efficiently. To encourage effective public participation in urban governance of smart cities, the public needs to be facilitated with the right contextual information about the characteristics and processes of their urban surroundings in order to contribute to the aspects of urban governance that affect them such as socio-economic activities, quality of life, citizens well-being etc. The cities on the other hand face challenges in terms of crowd sourcing with quality data collection and standardisation, services inter-operability, provisioning of computational and data storage infrastructure. Focus: In this paper, we highlight the issues that give rise to these multi-faceted challenges for citizens and public administrations of smart cities, identify the artefacts and stakeholders involved at both ends of the spectrum (data/service producers and consumers) and propose a conceptual framework to address these challenges. Based upon this conceptual framework, we present a Cloud-based architecture for context-aware citizen services for smart cities and discuss the components of the architecture through a common smart city scenario. A proof of concept implementation of the proposed architecture is also presented and evaluated. The results show the effectiveness of the cloud-based infrastructure for the development of a contextual service for citizens

A context provisioning middleware with support for evolving awareness

This thesis contributes to the research domain of Ubiquitous and Context-aware Computing. It presents a novel middleware (entitled Context Provisioning Middleware with Support for Evolving Awareness; C- ProMiSE) that applies a consumer-producer role model as architectural basis. The middleware aims at supporting diverse applications and services to easily and coherently acquire relevant context information. A mediat- ing Context Broker facilitates the coordination between distributed Context Provider, Context Source and Context Consumer components. The chosen design principles support' self-management capabilities and modular extendibility during run-time. Communication is based on the Representational State Transfer (REST) approach. Context is represented in ContextML, an XML-based modelling schema, enabling a structured generally applicable basis for various context domains, e.g. spatial, temporal, device-specific and user-centric prop- erties. This combination of context management and context representation model allows for gradual and distributed context processing and reasoning. Context is abstracted in various layers from primitive data up to high-level interpretation, e.g. users' activities. Specific emphasis is put on probabilistic reasoning of data originating from physical, virtual and logical sensors. In addition to the conceptualisation, a specific prototype implementation is presented and utilised as ex- perimentation testbed. Its functional evaluation covers field tests and context emulation. With regard to quantitative evaluation, the C-ProMiSE performance is finally assessed by applying both black-box tests of specific prototype components and Discrete Event Simulation at system level. Focus of the experimen- tation is to estimate the responsive context provisioning behaviour realistically. The obtained results lend weight to the argument that a consumer-producer-broker based framework can serve as basis to realise a distributed multi-domain context provisioning middleware that does not only scale physically but also functionally with regard to context processing capabilities. Furthermore, the con- text management, context representation and context processing concepts allow for supporting a variety of emerging and evolving context-aware applications and services.EThOS - Electronic Theses Online ServiceGBUnited Kingdo