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.

Neurolinguistic contributions to understanding the bilingual mental lexicon

Introduction Many bilinguals will have had the experience of unintentionally reading something in a language other than the intended one (e.g. MUG to mean mosquito in Dutch rather than a receptacle for a hot drink, as one of the possible intended English meanings), of finding themselves blocked on a word for which many alternatives suggest themselves (but, somewhat annoyingly, not in the right language), of their accent changing when stressed or tired and, occasionally, of starting to speak in a language that is not understood by those around them. These instances where lexical access appears compromised and control over language behavior is reduced hint at the intricate structure of the bilingual lexical architecture and the complexity of the processes by which knowledge is accessed and retrieved. While bilinguals might tend to blame word finding and other language problems on their bilinguality, these difficulties per se are not unique to the bilingual population. However, what is unique, and yet far more common than is appreciated by monolinguals, is the cognitive architecture that subserves bilingual language processing. With bilingualism (and multilingualism) the rule rather than the exception (Grosjean, 1982), this architecture may well be the default structure of the language processing system. As such, it is critical that we understand more fully not only how the processing of more than one language is subserved by the brain, but also how this understanding furthers our knowledge of the cognitive architecture that encapsulates the bilingual mental lexicon. The neurolinguistic approach to bilingualism focuses on determining the manner in which the two (or more) languages are stored in the brain and how they are differentially (or similarly) processed. The underlying assumption is that the acquisition of more than one language requires at the very least a change to or expansion of the existing lexicon, if not the formation of language-specific components, and this is likely to manifest in some way at the physiological level. There are many sources of information, ranging from data on bilingual aphasic patients (Paradis, 1977, 1985, 1997) to lateralization (Vaid, 1983; see Hull & Vaid, 2006, for a review), recordings of event-related potentials (ERPs) (e.g. Ardal et al., 1990; Phillips et al., 2006), and positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies of neurologically intact bilinguals (see Indefrey, 2006; Vaid & Hull, 2002, for reviews). Following the consideration of methodological issues and interpretative limitations that characterize these approaches, the chapter focuses on how the application of these approaches has furthered our understanding of (1) selectivity of bilingual lexical access, (2) distinctions between word types in the bilingual lexicon and (3) control processes that enable language selection.

Geek goddesses go to school : A study of female pre-service teachers in information technology courses

Various reasons have been proffered for female under-representation in tertiary information technology (IT) courses and the IT industry with most relating to cultural moirés. The 2006 Geek Goddess calendar was designed to alter IT’s “geeky image” and the term is used here to represent young women enrolled in pre-service IT teaching courses. Their special mix of IT and teaching draws on conflicting stereotypes and represents a micro-climate which is typically lost in studies of IT occupations because of the aggregation of all IT roles. This paper will report on a small-scale investigation of female students (N=25) at a university in Queensland (Australia) studying to become teachers of secondary IT subjects. They are entering the IT industry, gendered as a “male” occupation, through the safe space of teaching a discipline allied to feminine qualities of nurturing. They are “geek goddesses” who – perhaps to balance the masculine and feminine of these occupations - have decided to go to school rather than into corporations or government.

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.

Building Information Modelling for FM at Sydney Opera House

“SOH see significant benefit in digitising its drawings and operation and maintenance manuals. Since SOH do not currently have digital models of the Opera House structure or other components, there is an opportunity for this national case study to promote the application of Digital Facility Modelling using standardized Building Information Models (BIM)”. The digital modelling element of this project examined the potential of building information models for Facility Management focusing on the following areas: • The re-usability of building information for FM purposes • BIM as an Integrated information model for facility management • Extendibility of the BIM to cope with business specific requirements • Commercial facility management software using standardised building information models • The ability to add (organisation specific) intelligence to the model • A roadmap for SOH to adopt BIM for FM The project has established that BIM – building information modelling - is an appropriate and potentially beneficial technology for the storage of integrated building, maintenance and management data for SOH. Based on the attributes of a BIM, several advantages can be envisioned: consistency in the data, intelligence in the model, multiple representations, source of information for intelligent programs and intelligent queries. The IFC – open building exchange standard – specification provides comprehensive support for asset and facility management functions, and offers new management, collaboration and procurement relationships based on sharing of intelligent building data. The major advantages of using an open standard are: information can be read and manipulated by any compliant software, reduced user “lock in” to proprietary solutions, third party software can be the “best of breed” to suit the process and scope at hand, standardised BIM solutions consider the wider implications of information exchange outside the scope of any particular vendor, information can be archived as ASCII files for archival purposes, and data quality can be enhanced as the now single source of users’ information has improved accuracy, correctness, currency, completeness and relevance. SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. There have been remarkably few technical difficulties in converting the House’s existing conventions and standards to the new model based environment. This demonstrates that the IFC model represents world practice for building data representation and management (see Sydney Opera House – FM Exemplar Project Report Number 2005-001-C-3, Open Specification for BIM: Sydney Opera House Case Study). Availability of FM applications based on BIM is in its infancy but focussed systems are already in operation internationally and show excellent prospects for implementation systems at SOH. In addition to the generic benefits of standardised BIM described above, the following FM specific advantages can be expected from this new integrated facilities management environment: faster and more effective processes, controlled whole life costs and environmental data, better customer service, common operational picture for current and strategic planning, visual decision-making and a total ownership cost model. Tests with partial BIM data – provided by several of SOH’s current consultants – show that the creation of a SOH complete model is realistic, but subject to resolution of compliance and detailed functional support by participating software applications. The showcase has demonstrated successfully that IFC based exchange is possible with several common BIM based applications through the creation of a new partial model of the building. Data exchanged has been geometrically accurate (the SOH building structure represents some of the most complex building elements) and supports rich information describing the types of objects, with their properties and relationships.

Information literacy and learning

This book explores the relationship between information literacy and learning. It reports on the findings of research into the experience of students studying music and tax law in higher edcuation; investigating in depth the way in which they approach the twin activities of information use and discipline learning. The key findings of this study include: • A description of the nature of the experienced relationship between information literacy and learning in music composition and tax law as 1) Applying, 2) Discovering and 3) Expressing (music) or Understanding (tax law); • the theoretical GeST windows model and alignment of the model with the empirical study; • the presentation of curriculum implications in music and tax law, and • an exploration of the nature of information as-it-is-experienced. The findings may be used by teachers, students, librarians, academic skills advisors,academic developers and policy makers in higher education.

Brite phase 1 report to industry : innovate – now

Trying to innovate or wanting to? Making a start is the most difficult step on any journey. Whether trying to innovate for the first time, or seeking improvements on current performance, organisations are confronted with a plethora of options. Innovate ― Now! makes action easier by presenting some of the key considerations for improving innovation performance. This guide has been based on the outcomes of a survey and case studies conducted between 2003 and 2005 in the Australian property and construction industry and therefore contains unique and up-to-date information, examples and suggestions tailored specifically to your industry needs.

Innovate now : Improving performance in the building and construction industry

Trying to innovate or wanting to? Making a start is the most difficult step on any journey. Whether trying to innovate for the first time, or seeking improvements on current performance, organisations are confronted with a plethora of options. Innovate now! makes action easier by presenting some of the key considerations for improving innovation performance. This guide has been based on the outcomes of a survey and case studies conducted between 2003 and 2005 in the Australian property and construction industry and therefore contains unique and up-to-date information, examples and suggestions tailored specifically to your industry needs. The large-scale industry survey and 12 innovation case studies on which this guide are based were carried out by The BRITE (Building Research, Innovation, Technology and Environment) Project as part of research for the Cooperative Research Centre for Construction Innovation. The stakeholders volunteering to take part in BRITE research included over 400 businesses, 14 government organisations, 8 industry associations and 4 universities.

Attention and memory bias for body image and health related information using an Emotional Stroop task in a non-clinical sample

It has been proposed that body image disturbance is a form of cognitive bias wherein schemas for self-relevant information guide the selective processing of appearancerelated information in the environment. This threatening information receives disproportionately more attention and memory, as measured by an Emotional Stroop and incidental recall task. The aim of this thesis was to expand the literature on cognitive processing biases in non-clinical males and females by incorporating a number of significant methodological refinements. To achieve this aim, three phases of research were conducted. The initial two phases of research provided preliminary data to inform the development of the main study. Phase One was a qualitative exploration of body image concerns amongst males and females recruited through the general community and from a university. Seventeen participants (eight male; nine female) provided information on their body image and what factors they saw as positively and negatively impacting on their self evaluations. The importance of self esteem, mood, health and fitness, and recognition of the social ideal were identified as key themes. These themes were incorporated as psycho-social measures and Stroop word stimuli in subsequent phases of the research. Phase Two involved the selection and testing of stimuli to be used in the Emotional Stroop task. Six experimental categories of words were developed that reflected a broad range of health and body image concerns for males and females. These categories were high and low calorie food words, positive and negative appearance words, negative emotion words, and physical activity words. Phase Three addressed the central aim of the project by examining cognitive biases for body image information in empirically defined sub-groups. A National sample of males (N = 55) and females (N = 144), recruited from the general community and universities, completed an Emotional Stroop task, incidental memory test, and a collection of psycho-social questionnaires. Sub-groups of body image disturbance were sought using a cluster analysis, which identified three sub-groups in males (Normal, Dissatisfied, and Athletic) and four sub-groups in females (Normal, Health Conscious, Dissatisfied, and Symptomatic). No differences were noted between the groups in selective attention, although time taken to colour name the words was associated with some of the psycho-social variables. Memory biases found across the whole sample for negative emotion, low calorie food, and negative appearance words were interpreted as reflecting the current focus on health and stigma against being unattractive. Collectively these results have expanded our understanding of processing biases in the general community by demonstrating that the processing biases are found within non-clinical samples and that not all processing biases are associated with negative functionality

Multiple-choice versus short-response items: Differences in omit behavior

The overall rate of omission of items for 28,331 17 year old Australian students on a high stakes test of achievement in the common elements or cognitive skills of the senior school curriculum is reported for a subtest in multiple choice format and a subtest in short response format. For the former, the omit rates were minuscule and there was no significant difference by gender or by type of school attended. For the latter, where an item can be 'worth' up to five times that of a single multiple choice item, the omit rates were between 10 and 20 times that for multiple choice and the difference between male and female omit rate was significant as was the difference between students from government and non-government schools. For both formats, females from single sex schools omitted significantly fewer items than did females from co-educational schools. Some possible explanations of omit behaviour are alluded to.

Older patients request more information : a survey of use of written patient education materials in general practice

Objectives: To determine GPs' reported use of written education materials with older patients and older patients' reported receipt of these materials. To determine GPs' and older patients' perceptions of written materials.---------- Method: Using self-report questionnaires, two populations were surveyed; a randomised sample of 50 GPs (29 males and 21 females) practising in Brisbane's southern suburbs and a convenience sample of 188 older community-dwelling people (aged over 64 years).----------- Results: All GPs reported using written materials with patients, although 28% had not given any to the Last 10 patients. This increased to 46% when patients were older. Twenty percent of patients wanted more written information from their GP, while some GPs believed that older patients preferred verbal information and gave out written information only when they perceived patient interest. All GPs reported giving written materials at the time of consultation and over two thirds discussed the content with patients. Just over 50% of patients reported receiving written information from GPs in the Last six months and only hall of these again discussed it directly with their GP. Overall, patients were more positive than GPs about the value of written education materials.---------- Conclusions: Older patients' desire for written information may be better met if they are more assertive in requesting this of GPs and GPs may better serve their patients' needs if they make written information more readily available to them. Better access to materials and more financial incentives to give them out might also increase GPs' use of written materials.

Building information modelling for FM using IFC

Facility managers have to acquire, integrate, edit and update diverse facility information ranging from building elements & fabric data, operational costs, contract types, room allocation, logistics, maintenance, etc. With the advent of standardized Building Information Models (BIM) such as the Industry Foundation Classes (IFC) new opportunities are available for Facility Managers to manage their FM data. The usage of IFC supports data interoperability between different software systems including the use of operational data for facility management systems. Besides the re-use of building data, the Building Information Model can be used as an information framework for storing and retrieving FM related data. Currently several BIM driven FM systems are available including IFC compliant ones. These systems have the potential to not only manage primary data more effectively but also to offer practical systems for detailed monitoring, and analysis of facility performance that can underpin innovative and more cost effective management of complex facilities.

Developing within-company information and communication technologies (ICT) innovation diffusion networks : a study of three Australian major contractors

The innovation diffusion and knowledge management literature strongly supports the importance of communities of practice (COP) for enabling knowledge about how to use and adopt innovation initiatives. One of the most powerful tools for innovation diffusion is word-of-mouth wisdom from committed individuals who mentor and support each other. Close proximity for face-to-face interaction is highly effective, however, many organisations are geographically dispersed with projects being virtual linked sub-organisations using ICT to communicate. ICT has also introduced a useful facilitating technology for developing knowledge networks. This paper presents findings from a research program concentrating on ICT innovation diffusion in the Australian construction industry. One way in which ICT diffusion is taking place was found to be through within-company communities of practice. We undertook in-depth unstructured interviews with three of the major 10 to 15 contractors in Australia to discuss their ICT diffusion strategies. We discovered that in all three cases,within company networked communities of practice was a central strategy. Further, effective diffusion of ICT groupware tools can be critical in developing COP where they are geographically dispersed.

Extending the advanced forensic format to accommodate multiple data sources, logical evidence, arbitrary information and forensic workflow

Forensic analysis requires the acquisition and management of many different types of evidence, including individual disk drives, RAID sets, network packets, memory images, and extracted files. Often the same evidence is reviewed by several different tools or examiners in different locations. We propose a backwards-compatible redesign of the Advanced Forensic Formatdan open, extensible file format for storing and sharing of evidence, arbitrary case related information and analysis results among different tools. The new specification, termed AFF4, is designed to be simple to implement, built upon the well supported ZIP file format specification. Furthermore, the AFF4 implementation has downward comparability with existing AFF files.