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.

Business Service Management

Business Service Management describes the emerging discipline dedicated to the IT-enabled management of services as corporate assets. Business Service Management deals with the service orientation of the organisation and the provisioning and use of business services. The term business service describes an autonomous transformational capability that is offered to and consumed by external or internal customers for their benefit. The prefix ‘business’ stresses that such a service has a market value, requires the ability to be managed internally as a corporate asset and that its implementation is technology-agnostic. While business services (or so called capabilities) have attracted the attention of many vendors and organisations, a lack of understanding of the activities required for the successful management of such business services remains a critical issue. In order to fill this gap, a framework consisting of Service Lifecycle Management, Service Value Management, Service Relationship Management and Service Enablement is proposed. This Framework has the potential to provide organisations with the much needed guidance in their attempts to convert current IT-driven service initiatives into successful service-centric business models.

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.

Identification and analysis of business and software services : A consolidated approach

Although the benefits of service orientation are prevalent in literature, a review, analysis, and evaluation of the 30 existing service analysis approaches presented in this paper have shown that a comprehensive approach to the identification and analysis of both business and supporting software services is missing. Based on this evaluation of existing approaches and additional sources, we close this gap by proposing an integrated, consolidated approach to business and software service analysis that combines and extends the strengths of the examined methodologies.

Service analysis : A critical assessment of the state of the art

The service-orientation paradigm has not only become prevalent in the software systems domain in recent years, but is also increasingly applied on the business level to restructure organisational capabilities. In this paper, we present the results of an extensive literature review of 30 approaches related to service identification and analysis for both domains. Based on the consolidation of a superset of comparison criteria for service-oriented methodologies found in related literature, we compare and evaluate the different characteristics of service engineering methods with a focus on service analysis. Although a close business and IT alignment is regarded as one of the core beneficial promises of service-orientation, our analysis suggests that there is a lack of unified, comprehensive methodology for service identification and analysis integrating and addressing both domains. Thus, we discuss how our results can inform directions for future research in this area.

Business and software service lifecycle management

Although the service-oriented paradigm has been well established in the technical domain for quite some time now, service governance is still considered a research gap. To ensure adequate governance, there is a necessity to manage services as first-class assets throughout the lifecycle. Now that the concept of ser-vice-orientation is also increasingly applied on the business level to structure an organisation’s capabili-ties, the problem has become an even bigger chal-lenge. This paper presents a generic business and software service lifecycle and aligns it with the com-mon management layers in organisations. Using ser-vice analysis as an example, it moreover illustrates how activities in the service lifecycle may vary on lower levels of granularity depending on the focus on business or software services.

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.

Open Specification for BIM : Sydney Opera House Case Study

Executive Summary The objective of this report was to use the Sydney Opera House as a case study of the application of Building Information Modelling (BIM). The Sydney opera House is a complex, large building with very irregular building configuration, that makes it a challenging test. A number of key concerns are evident at SOH: • the building structure is complex, and building service systems - already the major cost of ongoing maintenance - are undergoing technology change, with new computer based services becoming increasingly important. • the current “documentation” of the facility is comprised of several independent systems, some overlapping and is inadequate to service current and future services required • the building has reached a milestone age in terms of the condition and maintainability of key public areas and service systems, functionality of spaces and longer term strategic management. • many business functions such as space or event management require up-to-date information of the facility that are currently inadequately delivered, expensive and time consuming to update and deliver to customers. • major building upgrades are being planned that will put considerable strain on existing Facilities Portfolio services, and their capacity to manage them effectively While some of these concerns are unique to the House, many will be common to larger commercial and institutional portfolios. The work described here supported a complementary task which sought to identify if a building information model – an integrated building database – could be created, that would support asset & facility management functions (see Sydney Opera House – FM Exemplar Project, Report Number: 2005-001-C-4 Building Information Modelling for FM at Sydney Opera House), a business strategy that has been well demonstrated. The development of the BIMSS - Open Specification for BIM has been surprisingly straightforward. The lack of technical difficulties in converting the House’s existing conventions and standards to the new model based environment can be related to three key factors: • SOH Facilities Portfolio – the internal group responsible for asset and facility management - have already well established building and documentation policies in place. The setting and adherence to well thought out operational standards has been based on the need to create an environment that is understood by all users and that addresses the major business needs of the House. • The second factor is the nature of the IFC Model Specification used to define the BIM protocol. The IFC standard is based on building practice and nomenclature, widely used in the construction industries across the globe. For example the nomenclature of building parts – eg ifcWall, corresponds to our normal terminology, but extends the traditional drawing environment currently used for design and documentation. This demonstrates that the international IFC model accurately represents local practice for building data representation and management. • a BIM environment sets up opportunities for innovative processes that can exploit the rich data in the model and improve services and functions for the House: for example several high-level processes have been identified that could benefit from standardized Building Information Models such as maintenance processes using engineering data, business processes using scheduling, venue access, security data and benchmarking processes using building performance data. The new technology matches business needs for current and new services. The adoption of IFC compliant applications opens the way forward for shared building model collaboration and new processes, a significant new focus of the BIM standards. In summary, 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. These BIM standards and their application to the Opera House are intended as a template for other organisations to adopt for the own procurement and facility management activities. Appendices provide an overview of the IFC Integrated Object Model and an understanding IFC Model Data.

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.

Nation & internation practices in decision support tools in road asset management

This document provides a review of international and national practices in investment decision support tools in road asset management. Efforts were concentrated on identifying analytic frameworks, evaluation methodologies and criteria adopted by current tools. Emphasis was also given to how current approaches support Triple Bottom Line decision-making. Benefit Cost Analysis and Multiple Criteria Analysis are principle methodologies in supporting decision-making in Road Asset Management. The complexity of the applications shows significant differences in international practices. There is continuing discussion amongst practitioners and researchers regarding to which one is more appropriate in supporting decision-making. It is suggested that the two approaches should be regarded as complementary instead of competitive means. Multiple Criteria Analysis may be particularly helpful in early stages of project development, say strategic planning. Benefit Cost Analysis is used most widely for project prioritisation and selecting the final project from amongst a set of alternatives. Benefit Cost Analysis approach is useful tool for investment decision-making from an economic perspective. An extension of the approach, which includes social and environmental externalities, is currently used in supporting Triple Bottom Line decision-making in the road sector. However, efforts should be given to several issues in the applications. First of all, there is a need to reach a degree of commonality on considering social and environmental externalities, which may be achieved by aggregating the best practices. At different decision-making level, the detail of consideration of the externalities should be different. It is intended to develop a generic framework to coordinate the range of existing practices. The standard framework will also be helpful in reducing double counting, which appears in some current practices. Cautions should also be given to the methods of determining the value of social and environmental externalities. A number of methods, such as market price, resource costs and Willingness to Pay, are found in the review. The use of unreasonable monetisation methods in some cases has discredited Benefit Cost Analysis in the eyes of decision makers and the public. Some social externalities, such as employment and regional economic impacts, are generally omitted in current practices. This is due to the lack of information and credible models. It may be appropriate to consider these externalities in qualitative forms in a Multiple Criteria Analysis. Consensus has been reached in considering noise and air pollution in international practices. However, Australia practices generally omitted these externalities. Equity is an important consideration in Road Asset Management. The considerations are either between regions, or social groups, such as income, age, gender, disable, etc. In current practice, there is not a well developed quantitative measure for equity issues. More research is needed to target this issue. Although Multiple Criteria Analysis has been used for decades, there is not a generally accepted framework in the choice of modelling methods and various externalities. The result is that different analysts are unlikely to reach consistent conclusions about a policy measure. In current practices, some favour using methods which are able to prioritise alternatives, such as Goal Programming, Goal Achievement Matrix, Analytic Hierarchy Process. The others just present various impacts to decision-makers to characterise the projects. Weighting and scoring system are critical in most Multiple Criteria Analysis. However, the processes of assessing weights and scores were criticised as highly arbitrary and subjective. It is essential that the process should be as transparent as possible. Obtaining weights and scores by consulting local communities is a common practice, but is likely to result in bias towards local interests. Interactive approach has the advantage in helping decision-makers elaborating their preferences. However, computation burden may result in lose of interests of decision-makers during the solution process of a large-scale problem, say a large state road network. Current practices tend to use cardinal or ordinal scales in measure in non-monetised externalities. Distorted valuations can occur where variables measured in physical units, are converted to scales. For example, decibels of noise converts to a scale of -4 to +4 with a linear transformation, the difference between 3 and 4 represents a far greater increase in discomfort to people than the increase from 0 to 1. It is suggested to assign different weights to individual score. Due to overlapped goals, the problem of double counting also appears in some of Multiple Criteria Analysis. The situation can be improved by carefully selecting and defining investment goals and criteria. Other issues, such as the treatment of time effect, incorporating risk and uncertainty, have been given scant attention in current practices. This report suggested establishing a common analytic framework to deal with these issues.

International practices in investment decision making in road sector

This document provides the findings of an international review of investment decision-making practices in road asset management. Efforts were concentrated on identifying the strategic objectives of agencies in road asset management, establishing and understanding criteria different organisations adopted and ascertaining the exact methodologies used by different countries and international organisations. Road assets are powerful drivers of economic development and social equity. They also have significant impacts on the natural and man-made environment. The traditional definition of asset management is “A systematic process of maintaining, upgrading and operating physical assets cost effectively. It combines engineering principles with sound business practices and economic theory and it provides tools to facilitate a more organised, logical approach to decision-making” (US Dept. of Transportation, 1999). In recent years, the concept has been broadened to cover the complexity of decision making, based on a wider variety of policy considerations as well as social and environmental issues rather than is covered by Benefit-Cost analysis and pure technical considerations. Current international practices are summarised in table 2. It was evident that Engineering-economic analysis methods are well advanced to support decision-making. A range of tools available supports performance predicting of road assets and associated cost/benefit in technical context. The need for considering triple plus one bottom line of social, environmental and economic as well as political factors in decision-making is well understood by road agencies around the world. The techniques used to incorporate these however, are limited. Most countries adopt a scoring method, a goal achievement matrix or information collected from surveys. The greater uncertainty associated with these non-quantitative factors has generally not been taken into consideration. There is a gap between the capacities of the decision-making support systems and the requirements from decision-makers to make more rational and transparent decisions. The challenges faced in developing an integrated decision making framework are both procedural and conceptual. In operational terms, the framework should be easy to be understood and employed. In philosophical terms, the framework should be able to deal with challenging issues, such as uncertainty, time frame, network effects, model changes, while integrating cost and non-cost values into the evaluation. The choice of evaluation techniques depends on the feature of the problem at hand, on the aims of the analysis, and on the underlying information base At different management levels, the complexity in considering social, environmental, economic and political factor in decision-making is different. At higher the strategic planning level, more non-cost factors are involved. The complexity also varies based on the scope of the investment proposals. Road agencies traditionally place less emphasis on evaluation of maintenance works. In some cases, social equity, safety, environmental issues have been used in maintenance project selection. However, there is not a common base for the applications.

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

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

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.