Report : wireless data throughput testing on a mobile device using WiFi and GPRS

This project report presents the results of a study on wireless communication data transfer rates for a mobile device running a custombuilt construction defect reporting application. The study measured the time taken to transmit data about a construction defect, which included digital imagery and text, in order to assess the feasibility of transferring various types and sizes of data and the ICT-supported construction management applications that could be developed as a consequence. Data transfer rates over GPRS through the Telstra network and WiFi over a private network were compared. Based on the data size and data transfer time, the rate of transfer was calculated to determine the actual data transmission speeds at which the information was being sent using the wireless mobile communication protocols. The report finds that the transmission speeds vary considerably when using GPRS and can be significantly slower than what is advertised by mobile network providers. While WiFi is much faster than GPRS, the limited range of WiFi limits the protocol to residential-scale construction sites.

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.

Towards a Rule-based matrix for evaluating distress mechanisms in bridges

One of the key issues facing public asset owners is the decision of refurbishing aged built assets. This decision requires an assessment of the “remaining service life” of the key components in a building. The remaining service life is significantly dependent upon the existing condition of the asset and future degradation patterns considering durability and functional obsolescence. Recently developed methods on Residual Service Life modelling, require sophisticated data that are not readily available. Most of the data available are in the form of reports prior to undertaking major repairs or in the form of sessional audit reports. Valuable information from these available sources can serve as bench marks for estimating the reference service life. The authors have acquired similar informations from a public asset building in Melbourne. Using these informations, the residual service life of a case study building façade has been estimated in this paper based on state-of-the-art approaches. These estimations have been evaluated against expert opinion. Though the results are encouraging it is clear that the state-of-the-art methodologies can only provide meaningful estimates provided the level and quality of data are available. This investigation resulted in the development of a new framework for maintenance that integrates the condition assessment procedures and factors influencing residual service life

Benchmarks for recycling practices in commercial office building refurbishment : data collection challenges

In recent years considerable effort has gone into quantifying the reuse and recycling potential of waste generated by residential construction. Unfortunately less information is available for the commercial refurbishment sector. It is hypothesised that significant economic and environmental benefit can be derived from closer monitoring of the commercial construction waste stream. With the aim of assessing these benefits, the authors are involved in ongoing case studies to record both current standard practice and the most effective means of improving the eco-efficiency of materials use in office building refurbishments. This paper focuses on the issues involved in developing methods for obtaining the necessary information on better waste management practices and establishing benchmark indicators. The need to create databases to establish benchmarks of waste minimisation best practice in commercial construction is stressed. Further research will monitor the delivery of case study projects and the levels of reuse and recycling achieved in directly quantifiable ways

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Adopting BIM for Facilities Adopting BIM for Facilities Management : Solutions for Managing the Sydney Opera House

The digital modelling research stream of the Sydney Opera House FM Exemplar Project has demonstrated significant benefits in digitising design documentation and operational and maintenance manuals. Since Sydney Opera House did not have digital models of its structure, there was an opportunity to investigate the application of digital modelling using standardised Building Information Models (BIM) to support facilities management (FM).The focus of this investigation was on the following areas:the re-usability of standardised BIM for FM purposesthe potential of BIM as an information framework acting as integrator for various FM data sources the extendibility and flexibility of the BIM to cope with business-specific data and requirements commercial FM software using standardised BIMthe ability to add (organisation-specific) intelligence to the modela roadmap for Sydney Opera House to adopt BIM for FM.

A medical data reliability assessment model

There is currently a strong focus worldwide on the potential of large-scale Electronic Health Record (EHR) systems to cut costs and improve patient outcomes through increased efficiency. This is accomplished by aggregating medical data from isolated Electronic Medical Record databases maintained by different healthcare providers. Concerns about the privacy and reliability of Electronic Health Records are crucial to healthcare service consumers. Traditional security mechanisms are designed to satisfy confidentiality, integrity, and availability requirements, but they fail to provide a measurement tool for data reliability from a data entry perspective. In this paper, we introduce a Medical Data Reliability Assessment (MDRA) service model to assess the reliability of medical data by evaluating the trustworthiness of its sources, usually the healthcare provider which created the data and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record. The result is then expressed by manipulating health record metadata to alert medical practitioners relying on the information to possible reliability problems.

Building information modelling project decision support framework

Building Information Modelling (BIM) is an information technology [IT] enabled approach to managing design data in the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry. BIM enables improved interdisciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. Despite the apparent benefits the adoption of BIM in practice has been slow. Workshops with industry focus groups were conducted to identify the industry needs, concerns and expectations from participants who had implemented BIM or were BIM “ready”. Factors inhibiting BIM adoption include lack of training, low business incentives, perception of lack of rewards, technological concerns, industry fragmentation related to uneven ICT adoption practices, contractual matters and resistance to changing current work practice. Successful BIM usage depends on collective adoption of BIM across the different disciplines and support by the client. The relationship of current work practices to future BIM scenarios was identified as an important strategy as the participants believed that BIM cannot be efficiently used with traditional practices and methods. The key to successful implementation is to explore the extent to which current work practices must change. Currently there is a perception that all work practices and processes must adopt and change for effective usage of BIM. It is acknowledged that new roles and responsibilities are emerging and that different parties will lead BIM on different projects. A contingency based approach to the problem of implementation was taken which relies upon integration of BIM project champion, procurement strategy, team capability analysis, commercial software availability/applicability and phase decision making and event analysis. Organizations need to understand: (a) their own work processes and requirements; (b) the range of BIM applications available in the market and their capabilities (c) the potential benefits of different BIM applications and their roles in different phases of the project lifecycle, and (d) collective supply chain adoption capabilities. A framework is proposed to support organizations selection of BIM usage strategies that meet their project requirements. Case studies are being conducted to develop the framework. The results of the preliminary design management case study is presented for contractor led BIM specific to the design and construct procurement strategy.

Estimating total cross sections from neutron-nucleus collisions using a simple functional form

Total cross sections for neutron scattering from nuclei, with energies ranging from 10 to 600 MeV and from many nuclei spanning the mass range 6Li to 238U, have been analyzed using a simple, three-parameter, functional form. The calculated cross sections are compared with results obtained by using microscopic (g-folding) optical potentials as well as with experimental data. The functional form reproduces those total cross sections very well. When allowance is made for Ramsauer-like effects in the scattering, the parameters of the functional form required vary smoothly with energy and target mass. They too can be represented by functions of energy and mass.

Vision, functional and cognitive determinants of motor vehicle incidents in older drivers

Background: The proportion of older individuals in the driving population is predicted to increase in the next 50 years. This has important implications for driving safety as abilities which are important for safe driving, such as vision (which accounts for the majority of the sensory input required for driving), processing ability and cognition have been shown to decline with age. The current methods employed for screening older drivers upon re-licensure are also vision based. This study, which investigated social, behavioural and professional aspects involved with older drivers, aimed to determine: (i) if the current visual standards in place for testing upon re-licensure are effective in reducing the older driver fatality rate in Australia; (ii) if the recommended visual standards are actually implemented as part of the testing procedures by Australian optometrists; and (iii) if there are other non-standardised tests which may be better at predicting the on-road incident-risk (including near misses and minor incidents) in older drivers than those tests recommended in the standards. Methods: For the first phase of the study, state-based age- and gender-stratified numbers of older driver fatalities for 2000-2003 were obtained from the Australian Transportation Safety Bureau database. Poisson regression analyses of fatality rates were considered by renewal frequency and jurisdiction (as separate models), adjusting for possible confounding variables of age, gender and year. For the second phase, all practising optometrists in Australia were surveyed on the vision tests they conduct in consultations relating to driving and their knowledge of vision requirements for older drivers. Finally, for the third phase of the study to investigate determinants of on-road incident risk, a stratified random sample of 600 Brisbane residents aged 60 years and were selected and invited to participate using an introductory letter explaining the project requirements. In order to capture the number and type of road incidents which occurred for each participant over 12 months (including near misses and minor incidents), an important component of the prospective research study was the development and validation of a driving diary. The diary was a tool in which incidents that occurred could be logged at that time (or very close in time to which they occurred) and thus, in comparison with relying on participant memory over time, recall bias of incident occurrence was minimised. Association between all visual tests, cognition and scores obtained for non-standard functional tests with retrospective and prospective incident occurrence was investigated. Results: In the first phase,rivers aged 60-69 years had a 33% lower fatality risk (Rate Ratio [RR] = 0.75, 95% CI 0.32-1.77) in states with vision testing upon re-licensure compared with states with no vision testing upon re-licensure, however, because the CIs are wide, crossing 1.00, this result should be regarded with caution. However, overall fatality rates and fatality rates for those aged 70 years and older (RR=1.17, CI 0.64-2.13) did not differ between states with and without license renewal procedures, indicating no apparent benefit in vision testing legislation. For the second phase of the study, nearly all optometrists measured visual acuity (VA) as part of a vision assessment for re-licensing, however, 20% of optometrists did not perform any visual field (VF) testing and only 20% routinely performed automated VF on older drivers, despite the standards for licensing advocating automated VF as part of the vision standard. This demonstrates the need for more effective communication between the policy makers and those responsible for carrying out the standards. It may also indicate that the overall higher driver fatality rate in jurisdictions with vision testing requirements is resultant as the tests recommended by the standards are only partially being conducted by optometrists. Hence a standardised protocol for the screening of older drivers for re-licensure across the nation must be established. The opinions of Australian optometrists with regard to the responsibility of reporting older drivers who fail to meet the licensing standards highlighted the conflict between maintaining patient confidentiality or upholding public safety. Mandatory reporting requirements of those drivers who fail to reach the standards necessary for driving would minimise potential conflict between the patient and their practitioner, and help maintain patient trust and goodwill. The final phase of the PhD program investigated the efficacy of vision, functional and cognitive tests to discriminate between at-risk and safe older drivers. Nearly 80% of the participants experienced an incident of some form over the prospective 12 months, with the total incident rate being 4.65/10 000 km. Sixty-three percent reported having a near miss and 28% had a minor incident. The results from the prospective diary study indicate that the current vision screening tests (VA and VF) used for re-licensure do not accurately predict older drivers who are at increased odds of having an on-road incident. However, the variation in visual measurements of the cohort was narrow, also affecting the results seen with the visual functon questionnaires. Hence a larger cohort with greater variability should be considered for a future study. A slightly lower cognitive level (as measured with the Mini-Mental State Examination [MMSE]) did show an association with incident involvement as did slower reaction time (RT), however the Useful-Field-of-View (UFOV) provided the most compelling results of the study. Cut-off values of UFOV processing (>23.3ms), divided attention (>113ms), selective attention (>258ms) and overall score (moderate/ high/ very high risk) were effective in determining older drivers at increased odds of having any on-road incident and the occurrence of minor incidents. Discussion: The results have shown that for the 60-69 year age-group, there is a potential benefit in testing vision upon licence renewal. However, overall fatality rates and fatality rates for those aged 70 years and older indicated no benefit in vision testing legislation and suggests a need for inclusion of screening tests which better predict on-road incidents. Although VA is routinely performed by Australian optometrists on older drivers renewing their licence, VF is not. Therefore there is a need for a protocol to be developed and administered which would result in standardised methods conducted throughout the nation for the screening of older drivers upon re-licensure. Communication between the community, policy makers and those conducting the protocol should be maximised. By implementing a standardised screening protocol which incorporates a level of mandatory reporting by the practitioner, the ethical dilemma of breaching patient confidentiality would also be resolved. The tests which should be included in this screening protocol, however, cannot solely be ones which have been implemented in the past. In this investigation, RT, MMSE and UFOV were shown to be better determinants of on-road incidents in older drivers than VA and VF, however, as previously mentioned, there was a lack of variability in visual status within the cohort. Nevertheless, it is the recommendation from this investigation, that subject to appropriate sensitivity and specificity being demonstrated in the future using a cohort with wider variation in vision, functional performance and cognition, these tests of cognition and information processing should be added to the current protocol for the screening of older drivers which may be conducted at licensing centres across the nation.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Functional outcome of transfemoral amputees fitted with an osseointegrated fixation : temporal gait characteristics

The purpose of this study was to characterise the functional outcome of 12 transfemoral amputees fitted with osseointegrated fixation using temporal gait characteristics. The objectives were (A) to present the cadence, duration of gait cycle, support and swing phases with an emphasis on the stride-to-stride and participant-to-participant variability, and (B) to compare these temporal variables with normative data extracted from the literature focusing on transfemoral amputees fitted with a socket and able-bodied participants. The temporal variables were extracted from the load applied on the residuum during straight level walking, which was collected at 200 Hz by a transducer. A total of 613 strides were assessed. The cadence (46±4 strides/min), the duration of the gait cycle (1.29±0.11 s), support (0.73±0.07 s, 57±3% of CG) and swing (0.56±0.07 s, 43±3% of GC) phases of the participants were 2% quicker, 3%, 6% shorter and 1% longer than transfemoral amputees using a socket as well as 11% slower, 9%, 6% and 13% longer than able-bodied, respectively. All combined, the results indicated that the fitting of an osseointegrated fixation has enabled this group of amputees to restore their locomotion with a highly functional level. Further longitudinal and cross-sectional studies would be required to confirm these outcomes. Nonetheless, the data presented can be used as benchmark for future comparisons. It can also be used as input in generic algorithms using templates of patterns of loading to recognise activities of daily living and to detect falls.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.