Remaining useful life prediction using elliptical basis function network and Markov Chain

This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Estimating the cost of health care–associated infections : mind your p’s and q’s

Monetary valuations of the economic cost of health care–associated infections (HAIs) are important for decision making and should be estimated accurately. Erroneously high estimates of costs, designed to jolt decision makers into action, may do more harm than good in the struggle to attract funding for infection control. Expectations among policy makers might be raised, and then they are disappointed when the reduction in the number of HAIs does not yield the anticipated cost saving. For this article, we critically review the field and discuss 3 questions. Why measure the cost of an HAI? What outcome should be used to measure the cost of an HAI? What is the best method for making this measurement? The aim is to encourage researchers to collect and then disseminate information that accurately guides decisions about the economic value of expanding or changing current infection control activities.

Comparing cost uplift in infrastructure delivery methods : a case based approach

The alliance project delivery method is used for approximately one third of all Australian government infrastructure projects representing $8-$10 billion per annum. Despite its widespread use, little is known about the differences between estimated project cost and actual cost over the project lifecycle. This paper presents the findings of research into 14 Australian government alliance case studies investigating the observed cost uplift over each project’s lifecycle. I find that significant cost uplift is likely and that this uplift is greater than that afflicting traditional delivery methods. Furthermore, most of the cost uplift occurs at a different place in the project lifecycle, namely between Business Case and Contractual Commitment.

Integrating the resource-based view and transaction cost economics in immigrant business performance

This paper presents a new integrated framework that integrates the resource-based view and transaction cost economics to explain the phenomenon of immigrant entrepreneurship. We extend the existing literature on immigrant entrepreneurship by identifying different types of ethnic network resources and demonstrating how these resources interact with transaction costs in the context of Chinese immigrants. Thus, our study contributes to the literature by providing a theoretical framework which identifies mechanisms immigrant entrepreneurs use to strategically deploy resources to minimize costs and maximize performance outcomes.

Asset health prediction using condition indicators and operating environment indicators : a case study

Prognostics and asset life prediction is one of research potentials in engineering asset health management. We previously developed the Explicit Hazard Model (EHM) to effectively and explicitly predict asset life using three types of information: population characteristics; condition indicators; and operating environment indicators. We have formerly studied the application of both the semi-parametric EHM and non-parametric EHM to the survival probability estimation in the reliability field. The survival time in these models is dependent not only upon the age of the asset monitored, but also upon the condition and operating environment information obtained. This paper is a further study of the semi-parametric and non-parametric EHMs to the hazard and residual life prediction of a set of resistance elements. The resistance elements were used as corrosion sensors for measuring the atmospheric corrosion rate in a laboratory experiment. In this paper, the estimated hazard of the resistance element using the semi-parametric EHM and the non-parametric EHM is compared to the traditional Weibull model and the Aalen Linear Regression Model (ALRM), respectively. Due to assuming a Weibull distribution in the baseline hazard of the semi-parametric EHM, the estimated hazard using this model is compared to the traditional Weibull model. The estimated hazard using the non-parametric EHM is compared to ALRM which is a well-known non-parametric covariate-based hazard model. At last, the predicted residual life of the resistance element using both EHMs is compared to the actual life data.

Energy and cost savings from pipe insulation on domestic, pumped storage (split), solar water heating systems in Australia and New Zealand

Appropriate pipe insulation on domestic, pumped storage (split), solar water heating systems forms an integral part of energy conservation measures of well engineered systems. However, its importance over the life of the system is often overlooked. This study outlines the findings of computer modelling to quantify the energy and cost savings by using pipe insulation between the collector and storage tank. System sizes of 270 Litre storage tank, together with either selectively surfaced, flat plate collectors (4m2 area), or 30 evacuated tube collectors, were used. Insulation thicknesses of 13mm and 15mm, pipe runs both ways of 10, 15 and 20 metres and both electric and gas boosting of systems were all considered. The TRNSYS program was used to model the system performance at a representative city in each of the 6 climate zones for Australia and New Zealand, according to AS/NZS4234 – Heat Water Systems – Calculation of energy consumption and the ORER RECs calculation method. The results show:  Energy savings from pipe insulation are very significant, even in mild climates such as Rockhampton. Across all climates zones, savings ranged from 0.16 to 3.5GJ per system per year, or about 2 to 23 percent of the annual load.  There is very little advantage in increasing the insulation thickness from 13 to 15mm. For electricity at 19c/kWh and gas at 2 c/MJ, cost savings of between $27 and $100 per year are achieved across the climate zones. Both energy and cost savings would increase in colder climates with increased system size, solar contribution and water temperatures.  The pipe insulation substantially improves the solar contribution (or fraction) and Renewable Energy Certificates (RECs), as well as giving small savings in circulating pump running costs in milder climates. Solar contribution increased by up to 23 percent points and RECs by over 7 in some cases.  The study highlights the need to install and maintain the integrity of appropriate pipe insulation on solar water heaters over their life time in Australia and New Zealand.

Leg Clubs® : a clinically and cost-effective approach to lower limb management

Leg ulcers affect 55000-90000 people, predominantly aged over 65, in the UK at any one time. Traditional care, delivered in people’s homes by district nurses or in GP clinics, is costly and often not effective, with slow healing rates and a high incidence of recurrence. A social model of leg ulcer clinics developed by the author has been shown to improve healing and reduce recurrence within a highly cost-effective framework that delivers genuine patient empowerment, public health education and social outreach. This paper outlines the rationale for the Leg Club, its clinical and social impact, and the infrastructure behind it. It also considers the challenges to establishing and running a Leg Club.

Towards the adoption of low-cost rail level crossing warning devices in regional areas of Australia : a review of current technologies and reliability issues

This paper discusses major obstacles for the adoption of low cost level crossing warning devices (LCLCWDs) in Australia and reviews those trialed in Australia and internationally. The argument for the use of LCLCWDs is that for a given investment, more passive level crossings can be treated, therefore increasing safety benefits across the rail network. This approach, in theory, reduces risk across the network by utilizing a combination of low-cost and conventional level crossing interventions, similar to what is done in the road environment. This paper concludes that in order to determine if this approach can produce better safety outcomes than the current approach, involving the incremental upgrade of level crossings with conventional interventions, it is necessary to perform rigorous risk assessments and cost-benefit analyses of LCLCWDs. Further research is also needed to determine how best to differentiate less reliable LCCLWDs from conventional warning devices through the use of different warning signs and signals. This paper presents a strategy for progressing research and development of LCLCWDs and details how the Cooperative Research Centre (CRC) for Rail Innovation is fulfilling this strategy through the current and future affordable level crossing projects.

Road crash proneness prediction using data mining

Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.

Waist circumference cut-off values for the prediction of cardiovascular risk factors clustering in Chinese school-aged children : a cross-sectional study

Background: Waist circumference has been identified as a valuable predictor of cardiovascular risk in children. The development of waist circumference percentiles and cut-offs for various ethnic groups are necessary because of differences in body composition. The purpose of this study was to develop waist circumference percentiles for Chinese children and to explore optimal waist circumference cut-off values for predicting cardiovascular risk factors clustering in this population.----- ----- Methods: Height, weight, and waist circumference were measured in 5529 children (2830 boys and 2699 girls) aged 6-12 years randomly selected from southern and northern China. Blood pressure, fasting triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and glucose were obtained in a subsample (n = 1845). Smoothed percentile curves were produced using the LMS method. Receiver-operating characteristic analysis was used to derive the optimal age- and gender-specific waist circumference thresholds for predicting the clustering of cardiovascular risk factors.----- ----- Results: Gender-specific waist circumference percentiles were constructed. The waist circumference thresholds were at the 90th and 84th percentiles for Chinese boys and girls respectively, with sensitivity and specificity ranging from 67% to 83%. The odds ratio of a clustering of cardiovascular risk factors among boys and girls with a higher value than cut-off points was 10.349 (95% confidence interval 4.466 to 23.979) and 8.084 (95% confidence interval 3.147 to 20.767) compared with their counterparts.----- ----- Conclusions: Percentile curves for waist circumference of Chinese children are provided. The cut-off point for waist circumference to predict cardiovascular risk factors clustering is at the 90th and 84th percentiles for Chinese boys and girls, respectively.

Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

Information sharing with key suppliers : a transaction cost theory perspective

Purpose: The purpose of this paper is to explain variations in discretionary information shared between buyers and key suppliers. The paper also aims to examine how the extent of information shared affects buyers’ performance in terms of resource usage, output, and flexibility. ----- ----- Design/methodology/approach: The data for the paper comprise 221 Finnish and Swedish non-service companies obtained through a mail survey. The hypothesized relationships were tested using partial least squares modelling with reflective and formative constructs.----- ----- Findings: The results of the study suggest that (environmental and demand) uncertainty and interdependency can to some degree explain the extent of information shared between a buyer and key supplier. Furthermore, information sharing improves buyers’ performance with respect to resource usage, output, and flexibility.----- ----- Research limitations/implications: A limitation to the paper relates to the data, which only included buyers.Abetter approach would have been to collect data from both, buyers and key suppliers. Practical implications – Companies face a wide range of supply chain solutions that enable and encourage collaboration across organizations. This paper suggests a more selective and balanced approach toward adopting the solutions offered as the benefits are contingent on a number of factors such as uncertainty. Also, the risks of information sharing are far too high for a one size fits all approach.----- ----- Originality/value: The paper illustrates the applicability of transaction cost theory to the contemporary era of e-commerce. With this finding, transaction cost economics can provide a valuable lens with which to view and interpret interorganizational information sharing, a topic that has received much attention in the recent years.

Prediction model of the buildup of volatile organic compounds on urban roads

A model to predict the buildup of mainly traffic-generated volatile organic compounds or VOCs (toluene, ethylbenzene, ortho-xylene, meta-xylene, and para-xylene) on urban road surfaces is presented. The model required three traffic parameters, namely average daily traffic (ADT), volume to capacity ratio (V/C), and surface texture depth (STD), and two chemical parameters, namely total suspended solid (TSS) and total organic carbon (TOC), as predictor variables. Principal component analysis and two phase factor analysis were performed to characterize the model calibration parameters. Traffic congestion was found to be the underlying cause of traffic-related VOC buildup on urban roads. The model calibration was optimized using orthogonal experimental design. Partial least squares regression was used for model prediction. It was found that a better optimized orthogonal design could be achieved by including the latent factors of the data matrix into the design. The model performed fairly accurately for three different land uses as well as five different particle size fractions. The relative prediction errors were 10–40% for the different size fractions and 28–40% for the different land uses while the coefficients of variation of the predicted intersite VOC concentrations were in the range of 25–45% for the different size fractions. Considering the sizes of the data matrices, these coefficients of variation were within the acceptable interlaboratory range for analytes at ppb concentration levels.

Security analysis and enhancement of one-way hash based low-cost authentication protocol (OHLCAP)

Choi et al. recently proposed an efficient RFID authentication protocol for a ubiquitous computing environment, OHLCAP(One-Way Hash based Low-Cost Authentication Protocol). However, this paper reveals that the protocol has several security weaknesses : 1) traceability based on the leakage of counter information, 2) vulnerability to an impersonation attack by maliciously updating a random number, and 3) traceability based on a physically-attacked tag. Finally, a security enhanced group-based authentication protocol is presented.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.