Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Skill development for innovative procurement environments in construction

The construction industry should be a priority to all governments because it impacts economically and socially on all citizens. Sector turnover in industrialised economies typically averages 8-12% of GDP. Further, construction is critical to economic growth. Recent Australian studies estimate that a 10% gain in efficiency in construction translates to a 2.5% increase in GDP Inefficiencies in the Australian construction industry have been identified by a number of recent studies modelling the building process. They have identified potential savings in time of between 25% and 40% by reducing non-value added steps in the process. A culture of reform is now emerging in the industry – one in which alternate forms of project delivery are being trialed. Government and industry have identified Alliance Contracting as a means to increase efficiency in the construction industry as part of a new innovative procurement environment. Alliance contracting requires parties to form relationships and work cooperatively to provide a more complete service. This is a significant cultural change for the construction industry, with its well-known adversarial record in traditional contracting. Alliance contracts offer enormous potential benefits, but the Australian construction industry needs to develop new skills to effectively participate in the new relationship environment. This paper describes a collaborative project identifying skill needs for clients and construction professionals to more effectively participate in an increasingly sophisticated international procurement environment. The aim of identifying these skill needs is to assist industry, government, and skill developers to prepare the Australian construction workforce for the future. The collaborating Australian team has been fortunate to secure the Australian National Museum in Canberra as its live case study. The Acton Peninsula Development is the first major building development in the world awarded on the basis of a joint alliance contract.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

High quality indoor environments for office buildings

The quality of office indoor environments is considered to consist of those factors that impact the occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. It can be estimated that the potential cost of lost productivity from poor IEQ may be much in excess of other operating costs of a building. However, the relative productivity impacts of each of the four indicators is largely unknown. The CRC Project ‘Regenerating Construction to Enhance Sustainability’ has a focus on IEQ impacts before and after building refurbishment. This paper provides an overview of IEQ impacts and criteria and the implementation of a CRC project that is currently researching these factors during the refurbishment of a Melbourne office building. IEQ measurements and their impacts will be reported in a future paper

High quality indoor environments for sustainable office buildings

The quality of office indoor environments is considered to consist of those factors that impact occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. While the potential cost of lost productivity from poor IEQ has been estimated to exceed building operation costs, the level of impact and the relative significance of the above four indicators are largely unknown. However, they are key factors in the sustainable operation or refurbishment of office buildings. This paper presents a methodology for assessing indoor environment quality (IEQ) in office buildings, and indicators with related metrics for high performance and occupant comfort. These are intended for integration into the specification of sustainable office buildings as key factors to ensure a high degree of occupant habitability, without this being impaired by other sustainability factors. The assessment methodology was applied in a case study on IEQ in Australia’s first ‘six star’ sustainable office building, Council House 2 (CH2), located in the centre of Melbourne. The CH2 building was designed and built with specific focus on sustainability and the provision of a high quality indoor environment for occupants. Actual IEQ performance was assessed in this study by field assessment after construction and occupancy. For comparison, the methodology was applied to a 30 year old conventional building adjacent to CH2 which housed the same or similar occupants and activities. The impact of IEQ on occupant productivity will be reported in a separate future paper

Media scepticism, media diets and media landscapes: A consideration of US versus Australian political information environments

The range of political information sources available to modern Australians is greater and more varied today than at any point in the nation’s history, incorporating print, broadcast, Internet, mainstream and non-mainstream media. In such a competitive media environment, the factors which influence the selection of some information sources above others are of interest to political agents, media institutions and communications researchers alike. A key factor in information source selection is credibility. At the same time that the range of political information sources is increasing rapidly, due to the development of new information and communication technologies, audience research suggests that trust in mainstream media organisations in many countries is declining. So if people distrust the mainstream media, but have a vast array of alternative political information sources available to them, what do their personal media consumption patterns look like? How can we analyse such media consumption patterns in a meaningful way? In this paper I will briefly map the development of media credibility research in the US and Australia, leading to a discussion of one of the most recent media credibility constructs to be shown to influence political information consumption, media scepticism. Looking at the consequences of media scepticism, I will then consider the associated media consumption construct, media diet, and evaluate its usefulness in an Australian, as opposed to US, context. Finally, I will suggest alternative conceptualisations of media diets which may be more suited to Australian political communications research.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

The importance of ecological scale for wildlife conservation in naturally fragmented environments: A case study of the Brush-Tailed Rock-Wallaby (Petrogale Penicillata)

Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.

Medienvermittelte transnationale Öffentlichkeiten im Zeitalter praktischer Hybridisierung (English title: Mediated transnational publics in environments of practical hybridisation)

This article is concerned with the repercussions of societal change on transnational media. It offers a new understanding of multilingual programming strategies by examining “Radio MultiKulti” (RM), a public service radio station discontinued from 1/1/2009 by Rundfunk Berlin-Brandenburg. In its fourteen years of existence, “RM” had to implement a well-intended and politically-motivated logic of ‘multiethnic, intercultural service station’. However, as we demonstrate, such a direction, despite some achievements, has resulted in the constraints to RM’s journalistic activities and language policy, drawing criticism for the station’s economic viability. This paper proposes that multilingual media services are to be framed by the concept of practical hybridity that allows a necessary responsiveness towards an ever-changing media environment, at the moment within digital culture. Our approach draws on Mikhail Bakhtin’s and Yuri Lotman’s theoretical approaches to hybridity, as well as in-depth interviews conducted with “RM” staff from 2005 onwards, further interviews with key agents outside RM and a continuous monitoring of the public debate which culminated at the end of 2008 in the controversial decision to close the radio station. Against this background, the concluding remarks are meant to contribute to the scholarly debate on hybridization as well as to inform multilingual media policy in the 21st century.

Evaluation of piezoelectric poly(vinylidene fluoride) polymers for use in space environments. I. Temperature limitations

Smart materials, such as thin-film piezoelectric polymers, are interesting for potential applications on Gossamer spacecraft. This investigation aims to predict the performance and long-term stability of the piezoelectric properties of poly(vinylidene fluoride) (PVDF) and its copolymers under conditions simulating the low-Earthorbit environment. To examine the effects of temperature on the piezoelectric properties of PVDF, poly(vinylidenefluoride-co-trifluoroethylene), and poly(vinylidenefluoride-cohexafluoropropylene), the d33 piezoelectric coefficients were measured up to 160 8C, and the electric displacement/electric field (D–E) hysteresis loops were measured from �80 to þ110 8C. The room-temperature d33 coefficient of PVDF homopolymer films, annealed at 50, 80, and 125 8C, dropped rapidly within a few days of thermal exposure and then remained unchanged. In contrast, the TrFE copolymer exhibited greater thermal stability than the homopolymer, with d33 remaining almost unchanged up to 125 8C. The HFP copolymer exhibited poor retention of d33 at temperatures above 80 8C. In situ D–E loop measurements from �80 to þ110 8C showed that the remanent polarization of the TrFE copolymer was more stable than that of the PVDF homopolymer. D–E hysteresis loop and d33 results were also compared with the deflection of the PVDF homopolymer and TrFE copolymer bimorphs tested over a wide temperature range.

Selection and optimization of piezoelectric polyvinylidene fluoride polymers for adaptive optics in space environments

Various piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films depend on charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to deteriorate owing to strong vacuum UV, � -, X-ray, energetic particles and atomic oxygen exposure. We have investigated the degradation of PVDF and its copolymers under various stress environments detrimental to reliable operation in space. Initial radiation aging studies have shown complex material changes with lowered Curie temperatures, complex material changes with lowered melting points, morphological transformations and significant crosslinking, but little influence on piezoelectric d33 constants. Complex aging processes have also been observed in accelerated temperature environments inducing annealing phenomena and cyclic stresses. The results suggest that poling and chain orientation are negatively affected by radiation and temperature exposure. A framework for dealing with these complex material qualification issues and overall system survivability predictions in low earth orbit conditions has been established. It allows for improved material selection, feedback for manufacturing and processing, material optimization/stabilization strategies and provides guidance on any alternative materials.

Piezoelectric PVDF materials performance and operation limits in space environments

Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films are achieved via charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to suffer due to strong vacuum UV, gamma, X-ray, energetic particles and atomic oxygen under low earth orbit exposure conditions. The degradation of PVDF and its copolymers under various stress environments has been investigated. Initial radiation aging studies using gamma- and e-beam irradiation have shown complex material changes with significant crosslinking, lowered melting and Curie points (where observable), effects on crystallinity, but little influence on overall piezoelectric properties. Surprisingly, complex aging processes have also been observed in elevated temperature environments with annealing phenomena and cyclic stresses resulting in thermal depoling of domains. Overall materials performance appears to be governed by a combination of chemical and physical degradation processes. Molecular changes are primarily induced via radiative damage, and physical damage from temperature and AO exposure is evident as depoling and surface erosion. Major differences between individual copolymers have been observed providing feedback on material selection strategies.