Risk under performance-based contracting in the UK construction sector

As a method of procuring the services of the built environment, performance-based contracting (PBC) seeks to link the building supplier to longer term commitments than has traditionally been the case in the construction sector. By rewarding the building producer according to the way that building or structure delivers the users' requirements, rather than according to a list of assembled parts, a number of additional risks are taken by contractors, including fitness for purpose, costs and briefing. The extent to which contractors recognize these risks and their methods of dealing with them vary considerably and are influenced by their attitudes towards risk. As the risks associated with PBC are seen as large, uninsurable, and vulnerable to changing client requirements, the majority of respondents would reject the use of PBC as a method of contracting. Nevertheless, PBC may be used under particular conditions, where rewards are deemed sufficient to compensate for the additional risk to the contractor of undertaking work on the basis of a stream of payments paid over the life of a structure depending on the satisfactory performance of the building or as part of a private finance initiative.

Reflections of professional practice: using electronic discourse analysis networks (EDANs) to examine embedded business emails

Emails have become a central genre in business communication, reflecting both how people communicate and how they go about their professional practices. This chapter examines embedded business emails as reflections of the professional practices of the regulatory and policy department of a multinational based in London, UK. It argues that the nature of online communication in international organisations, with its high levels of intertextuality and interdiscursivity, requires multidimensional analytical approaches that are capable of capturing its complexity and dynamics. To this end, the chapter introduces electronic discourse analysis networks (EDANs) as one example of such approaches. It begins with a brief review of the literature that has informed the study reported on here before it discusses EDANs as its analytical framework. Using a group of embedded emails and a number of networked data sets, the chapter shows how EDANs can be used to further our understanding of professional online communication.

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

Neuro-Fuzzy based Identification of Meat Spoilage using an Electronic Nose

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). An adaptive fuzzy logic system model that utilizes a prototype defuzzification scheme has been developed to classify beef samples in their respective quality class and to predict their associated microbiological population directly from volatile compounds fingerprints. Results confirmed the superiority of the adopted methodology and indicated that volatile information in combination with an efficient choice of a modeling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage