Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

The effect of consumer risk perceptions and information search on willingness to buy GM food products: A cross cultural analysis

This paper seeks to address the widespread call in the literature for the cross-cultural examination ( and validation) of accepted concepts within consumer behaviour, such as consumer risk perceptions and information search. The findings of the study provide support for a number of accepted relationships, whilst identifying distinct cross cultural differences in external information search and willingness to buy genetically modified (GM) food products by consumers.

In search of a theory of integrated marketing communication

For the most part, the literature base for Integrated Marketing Communication (IMC) has developed from an applied or tactical level rather than from an intellectual or theoretical one. Since industry, practitioner and even academic studies have provided little insight into what IMC is and how it operates, our approach has been to investigate that other IMC community, that is, the academic or instructional group responsible for disseminating IMC knowledge. We proposed that the people providing course instruction and directing research activities have some basis for how they organize, consider and therefore instruct in the area of IMC. A syllabi analysis of 87 IMC units in six countries investigated the content of the unit, its delivery both physically and conceptually, and defined the audience of the unit. The study failed to discover any type of latent theoretical foundation that might be used as a base for understanding IMC. The students who are being prepared to extend, expand and enhance IMC concepts do not appear to be well-served by the curriculum we found in our research. The study concludes with a model for further IMC curriculum development.

Search engine content analysis

Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.

E-business adoption in construction : international review on impediments

The adoption of e-business by the Australian construction industry lags other service and product industries. It is assumed that slow adoption rate does not reflect the maturity of the technology but is due to adoption impediments peculiar to the nature of construction. This chapter examines impediments to the uptake of e-business nationally and internationally. A systematic and extensive literature search of impediments (also referred to as obstacles, impediments or hindrances) to adoption has been undertaken and the findings discussed in this chapter. This review included more that 200 documents and these have been published in a searchable database as part of a larger research initiative funded by the Cooperative Research Centre for Construction Innovation. The influence of levels of e-business maturity seen in other sectors such as retail, tourism and manufacturing was also captured and a number of major impediments were identified some including: privacy, trust, uncertainty of financial returns, lack of reliable measurement, fraud, lack of support and system maintenance. A total of 23 impediments were assessed in terms of impact to organisational type and size across reviewed documents. With this information it was possible to develop a reference framework for measuring maturity levels and readiness to uptake e-business in construction. Results have also shown that impediments to e-business adoption work differently according to organisational type and culture. Areas of training and people development need to be addressed. This would include a more sensitive approach to the nature of construction organisations, especially to those small and medium enterprises. Raising levels of awareness and creating trust for on-line collaboration are other aspects that need attention, which current studies confirm as lacking. An empirical study within construction, to validate these findings, forms the subsequent phase of this research.