The practice of sustainable facilities management: Design sentiments and the knowledge chasm

The construction industry with its nature of project delivery is very fragmented in terms of the various processes that encompass design, construction, facilities and assets management. Facilities managers are in the forefront of delivering sustainable assets management and hence further the venture for mitigation and adaptation to climate change. A questionnaire survey was conducted to establish perceptions, level of commitment and knowledge chasm in practising sustainable facilities management (FM). This has significant implications for sustainable design management, especially in a fragmented industry. The majority of questionnaire respondents indicated the importance of sustainability for their organization. Many of them stated that they reported on sustainability as part of their organization annual reporting with energy efficiency, recycling and waste reduction as the main concern for them. The overwhelming barrier for implementing sound, sustainable FM is the lack of consensual understanding and focus of individuals and organizations about sustainability. There is a knowledge chasm regarding practical information on delivering sustainable FM. Sustainability information asymmetry in design, construction and FM processes render any sustainable design as a sentiment and mere design aspiration. Skills and training provision, traditionally offered separately to designers and facilities managers, needs to be re-evaluated. Sustainability education and training should be developed to provide effective structures and processes to apply sustainability throughout the construction and FM industries coherently and as common practice.

Investigation of support vector machine for the detection of architectural distortion in mammographic images

This paper investigates detection of architectural distortion in mammographic images using support vector machine. Hausdorff dimension is used to characterise the texture feature of mammographic images. Support vector machine, a learning machine based on statistical learning theory, is trained through supervised learning to detect architectural distortion. Compared to the Radial Basis Function neural networks, SVM produced more accurate classification results in distinguishing architectural distortion abnormality from normal breast parenchyma.

Fruit and vegetables, and the role they have played in determining the EU’s aggregate measurement of support

In its periodic declarations of domestic support to the WTO, the EU has progressively reduced its amber-box declarations in line with its changing system of farm support. Surprisingly, however, in 2007/08 it managed to more than halve its amber box compared with that of the previous year, easily achieving the reduction targets being touted in the Doha Round. This was largely due to a change in the calculations for fresh fruits and vegetables. These had been linked to the entry price system, which was not affected by the 2008 fruit and vegetables reform. Why the EU chose to make this change during the ongoing Doha Round negotiations remains unclear.