Public awareness of ‘green’ residential property – an empirical survey based on data from New Zealand and Germany

Over the last few years more stringent environmental laws (e.g. the German “Energie¬ein-sparverordnung ENEV” - Energy Performance of Buildings Directive) and soaring energy prices has increased the need for the real estate industry to react and participate in overall energy reduction through efficient house construction and design, as well as upgrading the existing housing stock to be more energy efficient. Therefore the Property Economics Group at Queensland University of Technology in Australia and Nuertingen-Geislingen University in Germany are carrying out research in relation to sustainable housing construction and public awareness of “green” residential property. Part of this research is to gain an understanding of the level of knowledge and importance of these issues to the house buyer and to determine the importance of sustainable housing to the general public. The paper compares data from two different empirical studies; one of studies analyzes the situation in New Zealand, the other is focused on Germany.

Legal Issues Relating to the Notification of Australian Data Breaches

Advances in information and communications technologies during the last two decades have allowed organisations to capture and utilise data on a vast scale, thus heightening the importance of adequate measures for protecting unauthorised disclosure of personal information. In this respect, data breach notification has emerged as an issue of increasing importance throughout the world. It has been the subject of law reform in the United States and in other international jurisdictions. Following the Australian Law Reform Commission’s review of privacy, data breach notification will soon be addressed in Australia. This article provides a review of US and Australian legal initiatives regarding the notification of data breaches. The authors highlight areas of concern based on the extant US literature that require specific consideration in Australia regarding the development of an Australian legal framework for the notification of data breaches.

A framework for network RTK data processing based on grid computing

Real-Time Kinematic (RTK) positioning is a technique used to provide precise positioning services at centimetre accuracy level in the context of Global Navigation Satellite Systems (GNSS). While a Network-based RTK (N-RTK) system involves multiple continuously operating reference stations (CORS), the simplest form of a NRTK system is a single-base RTK. In Australia there are several NRTK services operating in different states and over 1000 single-base RTK systems to support precise positioning applications for surveying, mining, agriculture, and civil construction in regional areas. Additionally, future generation GNSS constellations, including modernised GPS, Galileo, GLONASS, and Compass, with multiple frequencies have been either developed or will become fully operational in the next decade. A trend of future development of RTK systems is to make use of various isolated operating network and single-base RTK systems and multiple GNSS constellations for extended service coverage and improved performance. Several computational challenges have been identified for future NRTK services including: • Multiple GNSS constellations and multiple frequencies • Large scale, wide area NRTK services with a network of networks • Complex computation algorithms and processes • Greater part of positioning processes shifting from user end to network centre with the ability to cope with hundreds of simultaneous users’ requests (reverse RTK) There are two major requirements for NRTK data processing based on the four challenges faced by future NRTK systems, expandable computing power and scalable data sharing/transferring capability. This research explores new approaches to address these future NRTK challenges and requirements using the Grid Computing facility, in particular for large data processing burdens and complex computation algorithms. A Grid Computing based NRTK framework is proposed in this research, which is a layered framework consisting of: 1) Client layer with the form of Grid portal; 2) Service layer; 3) Execution layer. The user’s request is passed through these layers, and scheduled to different Grid nodes in the network infrastructure. A proof-of-concept demonstration for the proposed framework is performed in a five-node Grid environment at QUT and also Grid Australia. The Networked Transport of RTCM via Internet Protocol (Ntrip) open source software is adopted to download real-time RTCM data from multiple reference stations through the Internet, followed by job scheduling and simplified RTK computing. The system performance has been analysed and the results have preliminarily demonstrated the concepts and functionality of the new NRTK framework based on Grid Computing, whilst some aspects of the performance of the system are yet to be improved in future work.

Library technician course recognition : meeting the challenge of a distributed national education program

This paper looks at the challenges presented for the Australian Library and Information Association by its role as the professional association responsible for ensuring the quality of Australian library technician graduates. There is a particular focus on the issue of course recognition, where the Association's role is complicated by the need to work alongside the national quality assurance processes that have been established by the relevant technical education authorities. The paper describes the history of course recognition in Australia; examines the relationship between course recognition and other quality measures; and describes the process the Association has undertaken recently to ensure appropriate professional scrutiny in a changing environment of accountability.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

EPR, UV-visible and near infrared spectroscopic characterization of dolomite

Dolomite mineral samples having white and light green colours of Indian origin have been characterized by EPR, optical and NIR spectroscopy. The optical spectrum exhibits a number of electronic bands due to presence of Fe(III) ions in the mineral. From EPR studies, the parameters of g for Fe(III) and g, A and D for Mn(II) are evaluated and the data confirm that the ions are in distorted octahedron. Optical absorption studies reveal that Fe(III) is in distorted octahedron. The bands in NIR spectra are due to the overtones and combinations of water molecules. Thus EPR and optical absorption spectral studies have proven useful for the study of the chemistry of dolomite.

Effect of inaccuracies in anthropometric data and linked-segment inverse dynamic modeling on kinetics of gait in persons with partial foot amputation

The accuracy of data derived from linked-segment models depends on how well the system has been represented. Previous investigations describing the gait of persons with partial foot amputation did not account for the unique anthropometry of the residuum or the inclusion of a prosthesis and footwear in the model and, as such, are likely to have underestimated the magnitude of the peak joint moments and powers. This investigation determined the effect of inaccuracies in the anthropometric input data on the kinetics of gait. Toward this end, a geometric model was developed and validated to estimate body segment parameters of various intact and partial feet. These data were then incorporated into customized linked-segment models, and the kinetic data were compared with that obtained from conventional models. Results indicate that accurate modeling increased the magnitude of the peak hip and knee joint moments and powers during terminal swing. Conventional inverse dynamic models are sufficiently accurate for research questions relating to stance phase. More accurate models that account for the anthropometry of the residuum, prosthesis, and footwear better reflect the work of the hip extensors and knee flexors to decelerate the limb during terminal swing phase.

X-ray your data with Rasch

By using the Rasch model, much detailed diagnostic information is available to developers of survey and assessment instruments and to the researchers who use them. We outline an approach to the analysis of data obtained from the administration of survey instruments that can enable researchers to recognise and diagnose difficulties with those instruments and then to suggest remedial actions that can improve the measurement properties of the scales included in questionnaires. We illustrate the approach using examples drawn from recent research and demonstrate how the approach can be used to generate figures that make the results of Rasch analyses accessible to non-specialists.

Towards Humane Technologies: Biotechnologies, New Media and Ethics

What are the ethical and political implications when the very foundations of life —things of awe and spiritual significance — are translated into products accessible to few people? This book critically analyses this historic recontextualisation. Through mediation — when meaning moves ‘from one text to another, from one discourse to another’ — biotechnology is transformed into analysable data and into public discourses. The unique book links biotechnology with media and citizenship. As with any ‘commodity’, biological products have been commodified. Because enormous speculative investment rests on this, risk will be understated and benefit will be overstated. Benefits will be unfairly distributed. Already, the bioprospecting of Southern megadiverse nations, legally sanctioned by U.S. property rights conventions, has led to wealth and health benefits in the North. Crucial to this development are biotechnological discourses that shift meanings from a “language of life” into technocratic discourses, infused with neo-liberal economic assumptions that promise progress and benefits for all. Crucial in this is the mass media’s representation of biotechnology for an audience with poor scientific literacy. Yet, even apparently benign biotechnology spawned by the Human Genome Project such as prenatal screening has eugenic possibilities, and genetic codes for illness are eagerly sought by insurance companies seeking to exclude certain people. These issues raise important questions about a citizenship that is founded on moral responsibility for the wellbeing of society now and into the future. After all, biotechnology is very much concerned with the essence of life itself. This book provides a space for alternative and dissident voices beyond the hype that surrounds biotechnology.

Mapping personal trip OD from probe data

The paper analyses the expected value of OD volumes from probe with fixed error, error that is proportional to zone size and inversely proportional to zone size. To add realism to the analysis, real trip ODs in the Tokyo Metropolitan Region are synthesised. The results show that for small zone coding with average radius of 1.1km, and fixed measurement error of 100m, an accuracy of 70% can be expected. The equivalent accuracy for medium zone coding with average radius of 5km would translate into a fixed error of approximately 300m. As expected small zone coding is more sensitive than medium zone coding as the chances of the probe error envelope falling into adjacent zones are higher. For the same error radii, error proportional to zone size would deliver higher level of accuracy. As over half (54.8%) of the trip ends start or end at zone with equivalent radius of ≤ 1.2 km and only 13% of trips ends occurred at zones with equivalent radius ≥2.5km, measurement error that is proportional to zone size such as mobile phone would deliver higher level of accuracy. The synthesis of real OD with different probe error characteristics have shown that expected value of >85% is difficult to achieve for small zone coding with average radius of 1.1km. For most transport applications, OD matrix at medium zone coding is sufficient for transport management. From this study it can be drawn that GPS with error range between 2 and 5m, and at medium zone coding (average radius of 5km) would provide OD estimates greater than 90% of the expected value. However, for a typical mobile phone operating error range at medium zone coding the expected value would be lower than 85%. This paper assumes transmission of one origin and one destination positions from the probe. However, if multiple positions within the origin and destination zones are transmitted, map matching to transport network could be performed and it would greatly improve the accuracy of the probe data.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Information enrichment for quality recommender systems

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Temperature enhanced effects of ozone on cardiovascular mortality in 95 large US communities, 1987-2000 - assessment using the NMMAPS data

A few studies examined interactive effects between air pollution and temperature on health outcomes. This study is to examine if temperature modified effects of ozone and cardiovascular mortality in 95 large US cities. A nonparametric and a parametric regression models were separately used to explore interactive effects of temperature and ozone on cardiovascular mortality during May and October, 1987-2000. A Bayesian meta-analysis was used to pool estimates. Both models illustrate that temperature enhanced the ozone effects on mortality in the northern region, but obviously in the southern region. A 10-ppb increment in ozone was associated with 0.41 % (95% posterior interval (PI): -0.19 %, 0.93 %), 0.27 % (95% PI: -0.44 %, 0.87 %) and 1.68 % (95% PI: 0.07 %, 3.26 %) increases in daily cardiovascular mortality corresponding to low, moderate and high levels of temperature, respectively. We concluded that temperature modified effects of ozone, particularly in the northern region.

Deposition of combustion aerosols in the human respiratory tract : comparison of theoretical predictions with experimental data

Total deposition of petrol, diesel and environmental tobacco smoke (ETS) aerosols in the human respiratory tract for nasal breathing conditions was computed for 14 nonsmoking volunteers, considering the specific anatomical and respiratory parameters of each volunteer and the specific size distribution for each inhalation experiment. Theoretical predictions were 34.6% for petrol, 24.0% for diesel, and 18.5% for ETS particles. Compared to the experimental results, predicted deposition values were consistently smaller than the measured data (41.4% for petrol, 29.6% for diesel, and 36.2% for ETS particles). The apparent discrepancy between experimental data on total deposition and modeling results may be reconciled by considering the non-spherical shape of the test aerosols by diameter-dependent dynamic shape factors to account for differences between mobility-equivalent and volume-equivalent or thermodynamic diameters. While the application of dynamic shape factors is able to explain the observed differences for petrol and diesel particles, additional mechanisms may be required for ETS particle deposition, such as the size reduction upon inspiration by evaporation of volatile compounds and/or condensation-induced restructuring, and, possibly, electrical charge effects.