Utilising semantic technologies for decision support in dementia care

The main objective of this work is to discuss our experience in utilising semantic technologies for building decision support in Dementia care systems that are based on the non-intrusive on the non-intrusive monitoring of the patient’s behaviour. Our approach adopts context-aware modelling of the patient’s condition to facilitate the analysis of the patient’s behaviour within the inhabited environment (movement and room occupancy patterns, use of equipment, etc.) with reference to the semantic knowledge about the patient’s condition (history of present of illness, dependable behaviour patterns, etc.). The reported work especially focuses on the critical role of the semantic reasoning engine in inferring medical advice, and by means of practical experimentation and critical analysis suggests important findings related to the methodology of deploying the appropriate semantic rules systems, and the dynamics of the efficient utilisation of complex event processing technology in order to the meet the requirements of decision support for remote healthcare systems

Improving access to high-quality primary care for socioeconomically disadvantaged older people in rural areas: a mixed method study protocol

Introduction: The UK has an ageing population, especially in rural areas, where deprivation is high among older people. Previous research has identified this group as at high risk of poor access to healthcare. The aim of this study is to generate a theory of how socioeconomically disadvantaged older people from rural areas access primary care, to develop an intervention based on this theory and test it in a feasibility trial. Methods and analysis: On the basis of the MRC Framework for Developing and Evaluating Complex Interventions, three methods will be used to generate the theory. First, a realist review will elucidate the patient pathway based on existing literature. Second, an analysis of the English Longitudinal Study of Ageing will be completed using structural equation modelling. Third, 15 semistructured interviews will be undertaken with patients and four focus groups with health professionals. A triangulation protocol will be used to allow each of these methods to inform and be informed by each other, and to integrate data into one overall realist theory. Based on this theory, an intervention will be developed in discussion with stakeholders to ensure that the intervention is feasible and practical. The intervention will be tested within a feasibility trial, the design of which will depend on the intervention. Lessons from the feasibility trial will be used to refine the intervention and gather the information needed for a definitive trial. Ethics and dissemination: Ethics approval from the regional ethics committee has been granted for the focus groups with health professionals and interviews with patients. Ethics approval will be sought for the feasibility trial after the intervention has been designed. Findings will be disseminated to the key stakeholders involved in intervention development, to researchers, clinicians and health planners through peer-reviewed journal articles and conference publications, and locally through a dissemination event

Semantic Technologies for Manuscript Descriptions — Concepts and Visions

The contribution at hand relates recent developments in the area of the World Wide Web to codicological research. In the last number of years, an informational extension of the internet has been discussed and extensively researched: the Semantic Web. It has already been applied in many areas, including digital information processing of cultural heritage data. The Semantic Web facilitates the organisation and linking of data across websites, according to a given semantic structure. Software can then process this structural and semantic information to extract further knowledge. In the area of codicological research, many institutions are making efforts to improve the online availability of handwritten codices. If these resources could also employ Semantic Web techniques, considerable research potential could be unleashed. However, data acquisition from less structured data sources will be problematic. In particular, data stemming from unstructured sources needs to be made accessible to SemanticWeb tools through information extraction techniques. In the area of museum research, the CIDOC Conceptual Reference Model (CRM) has been widely examined and is being adopted successfully. The CRM translates well to Semantic Web research, and its concentration on contextualization of objects could support approaches in codicological research. Further concepts for the creation and management of bibliographic coherences and structured vocabularies related to the CRM will be considered in this chapter. Finally, a user scenario showing all processing steps in their context will be elaborated on

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

Retail Big-Box Development and Small Business Strategy at the Local Level

The big-box superstore has created a dramatic effect on the retail landscape since its appearance in 1962. As big-box stores proliferate, small business owners continue to struggle with how to compete. The purpose of this multiple case study was to identify and explore strategies small business owners use to maintain or grow profit margins post big-box store market entry. The sample consisted of 5 small business owners in Kansas City, Missouri who survived the entry of the big-box store for at least 1 year. The conceptual framework was the general systems theory and systems thinking. Data were collected using semistructured interviews, archival data, and data mining. I used Yin\u27s five-phase process of compiling, disassembling, reassembling, interpreting, and concluding for data analysis where 3 themes emerged that contributed to the case study\u27s small businesses maintaining or increasing profits. These themes were employees and customers, finances, and organizational strategies. Key findings within the themes indicated that innovation, product differentiation, and flexibility were keys to profitability. The sustainability of small business in communities brings a variety of benefits to include social, economic, environmental, and aesthetic. These benefits can translate into tangible results such as a reduction in crime, increased social interaction, a stronger sense of identity, increased diversity, and more equity. Empowering local small business owners with sustainable business strategies could result in more businesses remaining profitable, leading to an improved standard of living for business owners and urban redevelopment as businesses flourish while contributing to local economies

Resource Control for Synchronous Cooperative Threads

We develop new methods to statically bound the resources needed for the execution of systems of concurrent, interactive threads. Our study is concerned with a \emph{synchronous} model of interaction based on cooperative threads whose execution proceeds in synchronous rounds called instants. Our contribution is a system of compositional static analyses to guarantee that each instant terminates and to bound the size of the values computed by the system as a function of the size of its parameters at the beginning of the instant. Our method generalises an approach designed for first-order functional languages that relies on a combination of standard termination techniques for term rewriting systems and an analysis of the size of the computed values based on the notion of quasi-interpretation. We show that these two methods can be combined to obtain an explicit polynomial bound on the resources needed for the execution of the system during an instant. As a second contribution, we introduce a virtual machine and a related bytecode thus producing a precise description of the resources needed for the execution of a system. In this context, we present a suitable control flow analysis that allows to formulte the static analyses for resource control at byte code level

Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data

Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user’s ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data. We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive