Indoor exposure to submicrometer particles and PM2.5 in residential houses in Brisbane, Australia

As part of a large study investigating indoor air in residential houses in Brisbane, Australia, the purpose of this work was to quantify indoor exposure to submicrometer particles and PM2.5 for the inhabitants of 14 houses. Particle concentrations were measured simultaneously for more than 48 hours in the kitchens of all the houses by using a condensation particle counter (CPC) and a photometer (DustTrak). The occupants of the houses were asked to fill in a diary, noting the time and duration of any activity occurring throughout the house during measurement, as well as their presence or absence from home. From the time series concentration data and the information about indoor activities, exposure to the inhabitants of the houses was calculated for the entire time they spent at home as well as during indoor activities resulting in particle generation. The results show that the highest median concentration level occurred during cooking periods for both particle number concentration (47.5´103 particles cm-3) and PM2.5 concentration (13.4 mg m-3). The highest residential exposure period was the sleeping period for both particle number exposure (31%) and PM2.5 exposure (45.6%). The percentage of the average residential particle exposure level in total 24h particle exposure level was approximating 70% for both particle number and PM2.5 exposure.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Can IT Security be improved with better IT Leadership in the 21st Century University?

Organizations generally are not responding effectively to rising IT security threats because people issues receive inadequate attention. The stark example of IT security is just the latest strategic IT priority demonstrating deficient IT leadership attention to the social dimension of IT. Universities in particular, with their devolved people organization, diverse adoption of IT, and split central/local federated approach to governance and leadership of IT, demand higher levels of interpersonal sophistication and strategic engagement from their IT leaders. An idealized model for IT leaders for the 21st century university is proposed to be developed as a framework for further investigation. The testing of this model in an action research study is proposed.