Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Making visible the coding process : Using qualitative data software in a post-structural study

Qualitative research methods require transparency to ensure the ‘trustworthiness’ of the data analysis. The intricate processes of organizing, coding and analyzing the data are often rendered invisible in the presentation of the research findings, which requires a ‘leap of faith’ for the reader. Computer assisted data analysis software can be used to make the research process more transparent, without sacrificing rich, interpretive analysis by the researcher. This article describes in detail how one software package was used in a poststructural study to link and code multiple forms of data to four research questions for fine-grained analysis. This description will be useful for researchers seeking to use qualitative data analysis software as an analytic tool.

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.

Final report of Delphi study

This is the final report of project 2002-010 Component Life – A Delphi Approach to Life Prediction of Building Material Components. A Delphi survey has been conducted to provide expert opinion on the life of components in buildings. Thirty different components were surveyed with a range of materials, coatings, environments and failure considered. These components were chosen to be representative of a wider range of components in the same building microclimate. The survey included both service life (with and without maintenance) and aesthetic life, and time to first maintenance. It included marine, industrial, and benign environments, and covered both commercial and residential buildings. In order to obtain answers to this wide range of question, but still have a survey that could be completed in a reasonable time, the survey was broken into five sections: 1 External metal components – residential buildings. 2. Internal metal components – residential buildings. 3. External metal components – commercial buildings. 4. Internal metal components – commercial buildings. 5. Metal connectors in buildings.

Value creation and value capture fro open source software publisher : a new business model based on mutualisation

Key topics: Since the birth of the Open Source movement in the mid-80's, open source software has become more and more widespread. Amongst others, the Linux operating system, the Apache web server and the Firefox internet explorer have taken substantial market shares to their proprietary competitors. Open source software is governed by particular types of licenses. As proprietary licenses only allow the software's use in exchange for a fee, open source licenses grant users more rights like the free use, free copy, free modification and free distribution of the software, as well as free access to the source code. This new phenomenon has raised many managerial questions: organizational issues related to the system of governance that underlie such open source communities (Raymond, 1999a; Lerner and Tirole, 2002; Lee and Cole 2003; Mockus et al. 2000; Tuomi, 2000; Demil and Lecocq, 2006; O'Mahony and Ferraro, 2007;Fleming and Waguespack, 2007), collaborative innovation issues (Von Hippel, 2003; Von Krogh et al., 2003; Von Hippel and Von Krogh, 2003; Dahlander, 2005; Osterloh, 2007; David, 2008), issues related to the nature as well as the motivations of developers (Lerner and Tirole, 2002; Hertel, 2003; Dahlander and McKelvey, 2005; Jeppesen and Frederiksen, 2006), public policy and innovation issues (Jullien and Zimmermann, 2005; Lee, 2006), technological competitions issues related to standard battles between proprietary and open source software (Bonaccorsi and Rossi, 2003; Bonaccorsi et al. 2004, Economides and Katsamakas, 2005; Chen, 2007), intellectual property rights and licensing issues (Laat 2005; Lerner and Tirole, 2005; Gambardella, 2006; Determann et al., 2007). A major unresolved issue concerns open source business models and revenue capture, given that open source licenses imply no fee for users. On this topic, articles show that a commercial activity based on open source software is possible, as they describe different possible ways of doing business around open source (Raymond, 1999; Dahlander, 2004; Daffara, 2007; Bonaccorsi and Merito, 2007). These studies usually look at open source-based companies. Open source-based companies encompass a wide range of firms with different categories of activities: providers of packaged open source solutions, IT Services&Software Engineering firms and open source software publishers. However, business models implications are different for each of these categories: providers of packaged solutions and IT Services&Software Engineering firms' activities are based on software developed outside their boundaries, whereas commercial software publishers sponsor the development of the open source software. This paper focuses on open source software publishers' business models as this issue is even more crucial for this category of firms which take the risk of investing in the development of the software. Literature at last identifies and depicts only two generic types of business models for open source software publishers: the business models of ''bundling'' (Pal and Madanmohan, 2002; Dahlander 2004) and the dual licensing business models (Välimäki, 2003; Comino and Manenti, 2007). Nevertheless, these business models are not applicable in all circumstances. Methodology: The objectives of this paper are: (1) to explore in which contexts the two generic business models described in literature can be implemented successfully and (2) to depict an additional business model for open source software publishers which can be used in a different context. To do so, this paper draws upon an explorative case study of IdealX, a French open source security software publisher. This case study consists in a series of 3 interviews conducted between February 2005 and April 2006 with the co-founder and the business manager. It aims at depicting the process of IdealX's search for the appropriate business model between its creation in 2000 and 2006. This software publisher has tried both generic types of open source software publishers' business models before designing its own. Consequently, through IdealX's trials and errors, I investigate the conditions under which such generic business models can be effective. Moreover, this study describes the business model finally designed and adopted by IdealX: an additional open source software publisher's business model based on the principle of ''mutualisation'', which is applicable in a different context. Results and implications: Finally, this article contributes to ongoing empirical work within entrepreneurship and strategic management on open source software publishers' business models: it provides the characteristics of three generic business models (the business model of bundling, the dual licensing business model and the business model of mutualisation) as well as conditions under which they can be successfully implemented (regarding the type of product developed and the competencies of the firm). This paper also goes further into the traditional concept of business model used by scholars in the open source related literature. In this article, a business model is not only considered as a way of generating incomes (''revenue model'' (Amit and Zott, 2001)), but rather as the necessary conjunction of value creation and value capture, according to the recent literature about business models (Amit and Zott, 2001; Chresbrough and Rosenblum, 2002; Teece, 2007). Consequently, this paper analyses the business models from these two components' point of view.

Report : analysis of maintenance database inputs

In the previous phase of this project, 2002-059-B Case-Based Reasoning in Construction and Infrastructure Projects, demonstration software was developed using a case-base reasoning engine to access a number of sources of information on lifetime of metallic building components. One source of information was data from the Queensland Department of Public Housing relating to maintenance operations over a number of years. Maintenance information is seen as being a particularly useful source of data about service life of building components as it relates to actual performance of materials in the working environment. If a building is constructed in 1984 and the maintenance records indicate that the guttering was replaced in 2006, then the service life of the gutters was 22 years in that environment. This phase of the project aims to look more deeply at the Department of Housing data, as an example of maintenance records, and formulate methods for using this data to inform the knowledge of service lifetimes.

Final Report : learning system for life prediction of infrastructure

The project has further developed two programs for the industry partners related to service life prediction and salt deposition. The program for Queensland Department of Main Roads which predicts salt deposition on different bridge structures at any point in Queensland has been further refined by looking at more variables. It was found that the height of the bridge significantly affects the salt deposition levels only when very close to the coast. However the effect of natural cleaning of salt by rainfall was incorporated into the program. The user interface allows selection of a location in Queensland, followed by a bridge component. The program then predicts the annual salt deposition rate and rates the likely severity of the environment. The service life prediction program for the Queensland Department of Public Works has been expanded to include 10 common building components, in a variety of environments. Data mining procedures have been used to develop the program and increase the usefulness of the application. A Query Based Learning System (QBLS) has been developed which is based on a data-centric model with extensions to provide support for user interaction. The program is based on number of sources of information about the service life of building components. These include the Delphi survey, the CSIRO Holistic model and a school survey. During the project, the Holistic model was modified for each building component and databases generated for the locations of all Queensland schools. Experiments were carried out to verify and provide parameters for the modelling. These included instrumentation of a downpipe, measurements on pH and chloride levels in leaf litter, EIS measurements and chromate leaching from Colorbond materials and dose tests to measure corrosion rates of new materials. A further database was also generated for inclusion in the program through a large school survey. Over 30 schools in a range of environments from tropical coastal to temperate inland were visited and the condition of the building components rated on a scale of 0-5. The data was analysed and used to calculate an average service life for each component/material combination in the environments, where sufficient examples were available.

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.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

Decision - Support Software Tool Handbook

The road and transport industry in Australia and overseas has come a long way to understanding the impact of road traffic noise on the urban environment. Most road authorities now have guidelines to help assess and manage the impact of road traffic noise on noise-sensitive areas and development. While several economic studies across Australia and overseas have tried to value the impact of noise on property prices, decision-makers investing in road traffic noise management strategies have relatively limited historic data and case studies to go on. The perceived success of a noise management strategy currently relies largely on community expectations at a given time, and is not necessarily based on the analysis of the costs and benefits, or the long-term viability and value to the community of the proposed treatment options. With changing trends in urban design, it is essential that the 'whole-of-life' costs and benefits of noise ameliorative treatment options and strategies be identified and made available for decisionmakers in future investment considerations. For this reason, CRC for Construction Innovation Australia funded a research project, Noise Management in Urban Environments to help decision-makers with future road traffic noise management investment decisions. RMIT University and the Queensland Department of Main Roads (QDMR) have conducted the research work, in collaboration with the Queensland Department of Public Works, ARUP Pty Ltd, and the Queensland University of Technology. The research has formed the basis for the development of a decision-support software tool, and helped collate technical and costing data for known noise amelioration treatment options. We intend that the decision support software tool (DST) should help an investment decision-maker to be better informed of suitable noise ameliorative treatment options on a project-by-project basis and identify likely costs and benefits associated with each of those options. This handbook has been prepared as a procedural guide for conducting a comparative assessment of noise ameliorative options. The handbook outlines the methodology and assumptions adopted in the decision-support framework for the investment decision-maker and user of the DST. The DST has been developed to provide an integrated user-friendly interface between road traffic noise modelling software, the relevant assessment criteria and the options analysis process. A user guide for the DST is incorporated in this handbook.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved