Proceedings of the West Africa Built Environment Research (WABER) Conference 2010

FOREWORD Welcome to this West Africa Built Environment Research (WABER) conference taking place here in Ghana. Thank you for coming and welcome to Accra. The main aims of the WABER conference are: to help young researchers and early-career scholars in West Africa to develop their research work and skills through constructive face-to-face interaction with experienced academics; to provide a platform for networking and collaborative work among senior built environment academics in West Africa; and to serve as a vehicle for developing the field of construction management and economics in Africa. Waber 2009 The WABER event in 2009 was held at the British Council in Accra, Ghana on 2-3 June. The event was a resounding success. It attracted participation from 32 researchers, from 12 different institutions, who presented their work to an audience of approximately 100 people. Each presenter received immediate and constructive feedback from an international panel. The event was opened by Professor K.K. Adarkwa, Vice Chancellor of KNUST, Kumasi, Ghana, with several senior academics and researchers from universities, polytechnics, and other institutions in Ghana and Nigeria in attendance. There was also a significant level of attendance by senior construction practitioners in Ghana. Thank you to the School of Construction Management and Engineering, University of Reading, UK for funding the inaugural event in 2009. We are also grateful to all of you who helped to make the event a success and to those of you who have joined us here today to build upon the success and legacy of WABER 2009. Waber 2010 This year, we have 60+ peer-reviewed papers and presentations on topics relating to Building services and maintenance, Construction costs, Construction design and technology, Construction education, Construction finance, Construction procurement, Contract administration, Contract management, Contractor development, Decision support systems, Dispute resolution, Economic development, Energy efficiency, Environment and sustainability, Health and safety, Human resources, Information technology, Marketing, Materials science, Organisation strategy and business performance, Productivity, Project management, Quantity surveying, Real estate and planning, Solar energy systems, Supply chain management and Urban development. We hope that these papers will generate interest among delagates and stimulate discussion here and beyond the conference into the wider community of academia and industry. The delegates at this conference come from 10 different countries. This provides a rich international and multicultural blend and a perfect platform for networking and developing collaborations. This year we are blessed to have three high profile keynote speakers in the persons of Professor George Ofori (National University of Singapore), Dr Roine Leiringer (University of Reading, UK) and Professor Will Hughes (University of Reading, UK). We are also thankful to Dr Chris Harty (University of Reading, UK) who is facilitating the Research Skills Workshop on ‘Writing a scientific article’. Thank you to Dr Sena Agyepong of our conference organising team for her capable management of local organising arrangements. And above all, thank you to all of you for coming to this conference. Enjoy and have a safe journey back home. Dr Samuel Laryea School of Construction Management and Engineering University of Reading, July 2010

Interpreting information about medication side effects: differences in risk perception and intention to comply when medicines are prescribed for adults or young children

This study investigates whether, and how, people's perception of risk and intended health behaviours are affected by whether a medicine is prescribed for themselves or for a young child. The question is relevant to the issue of whether it is beneficial to produce medicines information that is tailored to particular subgroups of the population, such as parents of young children. In the experiment, participants read scenarios which referred either to themselves or their (imagined) 1-year-old child, and were required to make a number of risk judgements. The results showed that both parents and non-parents were less satisfied, perceived side effects to be more severe and more likely to occur, risk to health to be higher, and said that they would be less likely to take (or give) the medicine when the recipient was the child. On the basis of the findings, it is suggested that it may well be beneficial to tailor materials to broader classes of patient type.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

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