Towards dynamic context discovery and composition

Context-awareness has been identified as a key characteristic for pervasive computing systems. As a variety of context-aware environments begin to flourish, pervasive applications shall have to interact different environments well. In this paper we propose extensions to the Strathclyde Context Infrastructure that gives context-aware applications the potential to adapt to unfamiliar environments transparently. We present a vision of a context discovery technique based on automated semantic reasoning about context information and services. The technique will offer higher levels of scalability and of interoperability with new context environments that cannot be achieved with current methods

Situation determination with distributed context histories

Determining the situation within an environment is a key goal of smart environment research. A significant challenge in situation determination is reasoning about openended groups of people and devices that a smart environment may contain. Contemporary solutions are often tailored to the specific environment. In this position paper, we present a novel general situation determination framework, that by viewing people and tools as playing roles in a situation, can easily adapt recognition to incorporate the dynamic structure of a situation over time

Situation determination with reusable situation specifications

Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. In both cases, the situations are tailored to the specific environment, and are therefore not transferable to other environments. Furthermore, situations are recognised at a low-level of granularity, which limits the scope of situation-aware applications. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation specications that can be easily extended to create new speficic situations, and immediately deployed without the need of an environment expert. A proposed architecture of an accompanying situation determination middleware is provided, as well as an analysis of a prototype implementation

Towards ad-hoc situation determination

Toolkits such as PlaceLab [1] have been successful in making location information freely available for use in experimental ubiquitous computing applications. As users' expectations of ubiquitous computing applications grow, we envisage a need for tools that can deliver a much richer set of contextual information. The high-level situation of the current environment is a key contextual element, and this position paper focuses on a method to provide this information for an ad-hoc group of people and devices. The contributions of this paper are i) a demonstration of how information retrieval (IR) techniques can be applied to situation determination in context-aware systems, ii) a proposal of a novel approach to situation determination that combines these adapted IR techniques with a process of cooperative interaction, and iii) a report of preliminary results. The approach offers a high level of utility and accuracy, with a greater level of automation than other contemporary approaches

A self-managing infrastructure for ad-hoc situation determination

Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation specifications that can be easily extended to create new specific situations, and immediately deployed without the need of an environment expert. The architecture of an accompanying situation determination infrastructure is provided, which autonomously optimises and repairs itself in reaction to changes or failures in the environment

Incentives for breastfeeding and for smoking cessation in pregnancy: An exploration of types and meanings

Financial or tangible incentives are a strategy for improving health behaviours. The mechanisms of action of incentives are complex and debated. Using a multidisciplinary integrated mixed methods study, with service-user collaboration throughout, we developed a typology of incentives and their meanings for initiating and sustaining smoking cessation in pregnancy and breastfeeding. The ultimate aim was to inform incentive intervention design by providing insights into incentive acceptability and mechanisms of action. Systematic evidence syntheses of incentive intervention studies for smoking cessation in pregnancy or breastfeeding identified incentive characteristics, which were developed into initial categories. Little published qualitative data on user perspectives and acceptability was available. Qualitative interviews and focus groups conducted in three UK regions with a diverse socio-demographic sample of 88 women and significant others from the target population, 53 service providers, 24 experts/decision makers, and conference attendees identified new potential incentives and providers, with and without experience of incentives. Identified incentives (published and emergent) were classified into eight categories: cash and shopping vouchers, maternal wellbeing, baby and pregnancy-related, behaviour-related, health-related, general utility, awards and certificates, and experiences. A typology was refined iteratively through concurrent data collection and thematic analysis to explore participants' understandings of ‘incentives’ and to compare and contrast meanings across types. Our typology can be understood in three dimensions: the degree of restriction, the extent to which each is hedonic and/or utilitarian, and whether each has solely monetary value versus monetary with added social value. The layers of autonomy, meanings and the social value of incentive types influence their acceptability and interact with structural, social, and personal factors. Dimensions of incentive meaning that go beyond the simple incentive description should inform incentive programme design and are likely to influence outcomes

Data base manipulation for assessment of multiresource suitability and land change

Progress is reported in three tasks which support the overall objectives of renewable resources inventory task of the AgRISTARS program. In the first task, the geometric correction algorithms of the Master Data Processor were investigated to determine the utility of data corrected by this processor for U.S. Forest Service uses. The second task involved investigation of logic to form blobs as a precursor step to automatic change detection involving two dates of LANDSAT data. Some routine procedures for selecting BLOB (spatial averaging) parameters were developed. In the third task, a major effort was made to develop land suitability modeling approches for timber, grazing, and wildlife habitat in support of resource planning efforts on the San Juan National Forest

Tablet computers in assessing performance in a high stakes exam : opinion matters

The authors would like to thank Dr Craig brown, University of Aberdeen for assistance with data analysis.Peer reviewedPublisher PD

Longevity and mortality of owned dogs in England

Improved understanding of longevity represents a significant welfare opportunity for the domestic dog, given its unparalleled morphological diversity. Epidemiological research using electronic patient records (EPRs) collected from primary veterinary practices overcomes many inherent limitations of referral clinic, owner questionnaire and pet insurance data. Clinical health data from 102,609 owned dogs attending first opinion veterinary practices (n = 86) in central and southeast England were analysed, focusing on 5095 confirmed deaths. Of deceased dogs with information available, 3961 (77.9%) were purebred, 2386 (47.0%) were female, 2528 (49.8%) were neutered and 1105 (21.7%) were insured. The overall median longevity was 12.0 years (IQR 8.9–14.2). The longest-lived breeds were the Miniature poodle, Bearded collie, Border collie and Miniature dachshund, while the shortest-lived were the Dogue de Bordeaux and Great Dane. The most frequently attributed causes of death were neoplastic, musculoskeletal and neurological disorders. The results of multivariable modelling indicated that longevity in crossbred dogs exceeded purebred dogs by 1.2 years (95% confidence interval 0.9–1.4; P < 0.001) and that increasing bodyweight was negatively correlated with longevity. The current findings highlight major breed differences for longevity and support the concept of hybrid vigour in dogs