997 resultados para Arakawa and Gins


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Some polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in air and have been implicated as carcinogenic materials. Therefore, literature is replete with studies that are focused on their occurrence and profiles in indoor and outdoor air samples. However, because the relative potency of individual PAHs vary widely, health risks associated with the presence of PAHs in a particular environment cannot be extrapolated directly from the concentrations of individual PAHs in that environment. In addition, database on the potency of PAH mixtures is currently limited. In this paper, we have utilized multi-criteria decision making methods (MCDMs) to simultaneously correlate PAH-related health risk in some microenvironments to the concentration levels, ethoxyresorufin-O-deethylase (EROD) activity induction equivalency factors and toxic equivalency factors (TEFs) of PAHs found in those microenvironments. The results showed that the relative risk associated with PAHs in different air samples depends on the index used. Nevertheless, this approach offers a promising tool that could help identify microenvironments of concern and assist the prioritisation of control strategies.

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Collaboration is acknowledged as a key to continued growth in the Australian construction industry. Government, as a major industry client, has an important role to play with respect to fostering collaboration and ensuring the global competitiveness of the industry. The paper draws upon data collected for the Construction 2020 study and aims to demonstrate that government can a) help to break down the adversarial situation that currently exists between clients, project managers and subcontractors; and b) allow the supply chain to collaborate more effectively in terms of satisfying the relational and financial needs of all parties. Government can also provide a clear set of guidelines (backed up by a functional dispute resolution system) that will promote confidence with respect to forging relationships. Thus, the paper will discuss the way in which public policy can be more closely aligned with actual industry needs in order to promote greater collaboration.

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Hybrid face recognition, using image (2D) and structural (3D) information, has explored the fusion of Nearest Neighbour classifiers. This paper examines the effectiveness of feature modelling for each individual modality, 2D and 3D. Furthermore, it is demonstrated that the fusion of feature modelling techniques for the 2D and 3D modalities yields performance improvements over the individual classifiers. By fusing the feature modelling classifiers for each modality with equal weights the average Equal Error Rate improves from 12.60% for the 2D classifier and 12.10% for the 3D classifier to 7.38% for the Hybrid 2D+3D clasiffier.