Healthcare data mining from multi-source data

The "big data" challenge is changing the way we acquire, store, analyse, and draw conclusions from data. How we effectively and efficiently "mine" the data from possibly multiple sources and extract useful information is a critical question. Increasing research attention has been drawn to healthcare data mining, with an ultimate goal to improve the quality of care. The human body is complex and so too the data collected in treating it. Data noise that is often introduced via the collection process makes building Data Mining models a challenging task. This thesis focuses on the classification tasks of mining healthcare data, with the goal of improving the effectiveness of health risk prediction. In particular, we developed algorithms to address issues identified from real healthcare data, such as feature extraction, heterogeneity, label uncertainty, and large unlabeled data. The three main contributions of this research are as follows. First, we developed a new health index called Personal Health Index (PHI) that scores a person's health status based on the examination records of a given population. Second, we identified the key characteristics of the real datasets and issues that were associated with the data. Third, we developed classification algorithms to cope with those issues, particularly, the label uncertainty and large unlabeled data issues. This research takes one step forward towards scoring personal health based on mining increasingly large health records. Particularly, it pioneers exploring the mining of GHE data and tackles the associated challenges. It is our anticipation that in the near future, more robust data-mining-based health scoring systems will be available for healthcare professionals to understand people's health status and thus improve the quality of care

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

Entrepreneurial intentions and start-up realities : the case of industrial design students in South Africa

Industrial design is recognised for the value-oriented benefits it offers to businesses. Industrial design ensures that new products are more efficient, usable, convenient and safe to use within the evolving business environment. One of the important factors for the continuous achievement of high product quality and general economic growth and stability in countries such as West Germany, Korea and Japan is their sound industrial design base. Industrial design programmes can be instrumental to ignite an entrepreneurial and innovation spirit to assist in curbing the high unemployment rate and very low levels of entrepreneurial intentions in South Africa. The core of tertiary industrial design students has unique capabilities that can assist the South African economy to stimulate manufacturing, job creation and economic growth. The purpose of this study was to investigate the entrepreneurial intentions among industrial design students enrolled for the programme in Three-Dimensional Design, at Universities of Technology in South Africa. In addition, this study investigates the relationship between entrepreneurial intentions and actual business formation by graduates of the programme. Studies have been carried out in South Africa on entrepreneurial intentions, but not on the formation, occurrence and implementation of entrepreneurial intentions amongst industrial design students, specifically. To test the links between business education and entrepreneurial intentions, a research model based on Ajzen’s (1985) Theory of Planned Behaviour was adopted and tested using quantitative empirical data collected from students in industrial design at two Universities of Technology. Quantitative data were collected from a sample of 161 participants using a validated self-administered questionnaire. IBM SPSS and STATA were used to conduct descriptive statistics, Chi-square tests, factor analysis, reliability and structural equation modelling on the primary quantitative data. The empirical evidence partially supports the effectiveness of the Theory of Planned Behaviour in predicting entrepreneurial intentions. Although perceived social norms and self-efficacy is positively related to entrepreneurial intentions, results failed to reach statistical significance. However, personal attitude was found to mediate the relationship between these variables and entrepreneurial intention. Whilst business education is positively related to self-efficacy, entrepreneurial knowledge is positively related to higher levels of personal attitude and self-efficacy. The transformation of entrepreneurial intentions into actual business start-ups were investigated using qualitative empirical data collected from past graduates of the Three-Dimensional Design programme. Qualitative data were collected from a sample of 22 graduates through structured interviews. ATLAS.ti version 7.5.9 was used to analyse the qualitative data. The researcher provided evidence that there is a relationship between entrepreneurial intentions and the actual start-up of a business, as 45.5 per cent of graduates started businesses. Furthermore, business education positively influenced the actual start-up of businesses. However, graduates experienced many challenges to business start-up, with implications for the teaching of business subjects and for policy makers.Business ManagementD. Com. (Business Management

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute