Faculty and employee ownership of inventions in Australia

A recent decision by the Australian High Court means that, unless faculty are bound by an assignment or intellectual property (IP) policy, they may own inventions resulting from their research. Thirty years after its introduction, the US Bayh-Dole Act, which vests ownership of employee inventions in the employer university or research organization, has become a model for commercialization around the world. In Australia, despite recommendations that a Bayh-Dole style regime be adopted, the recent decision in University of Western Australia (UWA) v Gray1 has moved the default legal position in a diametrically opposite direction. A key focus of the debate was whether faculty’s duty to carry out research also encompasses a duty to invent. Late last year, the Full Federal Court confirmed a lower court ruling that it does not, and this year the High Court refused leave to appeal (denied certiorari). Thus, Gray stands as Australia’s most faculty-friendly authority to date.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

A discussion of the research performance evaluation in building and construction management discipline : the journal impact factors and SCI-index journals

The trend of diminished funding, demands for greater efficiency and higher public accountability have led to a rapid expansion of interest in the bibliometric assessment of research performance of universities. A pilot research is conducted to provide a preliminary overview of the research performance of the building and construction schools or departments through the analysis of bibliometric indicators including the journal impact factor (JIF) published by Institute for Scientific Information (ISI). The suitability of bibliometric evaluation approaches as a measure of research quality in building and construction management research field is discussed.

Post-occupancy analysis of a Zero Energy Hojme (ZEH)

Zero energy buildings (ZEB) and zero energy homes (ZEH) are a current hot topic globally for policy makers (what are the benefits and costs), designers (how do we design them), the construction industry (can we build them), marketing (will consumers buy them) and researchers (do they work and what are the implications). This paper presents initial findings from actual measured data from a 9 star (as built), off-ground detached family home constructed in south-east Queensland in 2008. The integrated systems approach to the design of the house is analysed in each of its three main goals: maximising the thermal performance of the building envelope, minimising energy demand whilst maintaining energy service levels, and implementing a multi-pronged low carbon approach to energy supply. The performance outcomes of each of these stages are evaluated against definitions of Net Zero Carbon / Net Zero Emissions (Site and Source) and Net Zero Energy (onsite generation v primary energy imports). The paper will conclude with a summary of the multiple benefits of combining very high efficiency building envelopes with diverse energy management strategies: a robustness, resilience, affordability and autonomy not generally seen in housing.

Factors contributing to ethical issues in project procurement planning : a case study in Malaysia

The construction industry plays a substantial role in a country’s national economy, irrespective of the country’s levels of economic development. The Malaysian Government has given a much needed boost to the country’s construction projects under the 9th Malaysian Plan where a total of 880 projects worth RM15billion (US$48billion) is to be tendered (The Star, 2006). However, Malaysia has not escaped the problems of project failure. In 2005, 17.3% of 417 Malaysian government contracts projects were considered “sick”. Project procurement is one of the most important stages of project delivery. Even though ethics in project procurement has been identified as one of the contributors to project failure, it has not been systematically studied before from the perspective of client in Malaysia. The aim of this paper is to present an exploration to the ethical issues in project procurement in Malaysian public sector projects. By exploring ethical issues from client perspective, this could provide an ethical standpoint for the project life cycle and could maintain a good affiliation between the clients and the customers. It is expected that findings from this review will be somewhat representative of other developing countries.

A poly(D,L-lactide) resin for the preparation of tissue engineering scaffolds by stereolithography

Porous polylactide constructs were prepared by stereolithography, for the first time without the use of reactive diluents. Star-shaped poly(D,L-lactide) oligomers with 2, 3 and 6 arms were synthesised, end-functionalised with methacryloyl chloride and photocrosslinked in the presence of ethyl lactate as a non-reactive diluent. The molecular weights of the arms of the macromers were 0.2, 0.6, 1.1 and 5 kg/mol, allowing variation of the crosslink density of the resulting networks. Networks prepared from macromers of which the molecular weight per arm was 0.6 kg/mol or higher had good mechanical properties, similar to linear high molecular weight poly(D,L-lactide). A resin based on a 2-armed poly(D,L-lactide) macromer with a molecular weight of 0.6 kg/mol per arm (75 wt%), ethyl lactate (19 wt%), photo-initiator (6 wt%), inhibitor and dye was prepared. Using this resin, films and computer-designed porous constructs were accurately fabricated by stereolithography. Pre-osteoblasts showed good adherence to these photocrosslinked networks. The proliferation rate on these materials was comparable to that on high molecular weight poly(D,L-lactide) and tissue culture polystyrene.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.