The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

The Explicit Hazard Model – Part 2 : Applications

Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).

Birthing practices of traditional birth attendants in south Asia in the context of training programmes

Traditional Birth Attendants (TBA) training has been an important component of public health policy interventions to improve maternal and child health in developing countries since the 1970s. More recently, since the 1990s, the TBA training strategy has been increasingly seen as irrelevant, ineffective or, on the whole, a failure due to evidence that the maternal mortality rate (MMR) in developing countries had not reduced. Although, worldwide data show that, by choice or out of necessity, 47 percent of births in the developing world are assisted by TBAs and/or family members, funding for TBA training has been reduced and moved to providing skilled birth attendants for all births. Any shift in policy needs to be supported by appropriate evidence on TBA roles in providing maternal and infant health care service and effectiveness of the training programmes. This article reviews literature on the characteristics and role of TBAs in South Asia with an emphasis on India. The aim was to assess the contribution of TBAs in providing maternal and infant health care service at different stages of pregnancy and after-delivery and birthing practices adopted in home births. The review of role revealed that apart from TBAs, there are various other people in the community also involved in making decisions about the welfare and health of the birthing mother and new born baby. However, TBAs have changing, localised but nonetheless significant roles in delivery, postnatal and infant care in India. Certain traditional birthing practices such as bathing babies immediately after birth, not weighing babies after birth and not feeding with colostrum are adopted in home births as well as health institutions in India. There is therefore a thin precarious balance between the application of biomedical and traditional knowledge. Customary rituals and perceptions essentially affect practices in home and institutional births and hence training of TBAs need to be implemented in conjunction with community awareness programmes.

Reliability prediction using the non-parametric explicit hazard model : a case study

Survival probability prediction using covariate-based hazard approach is a known statistical methodology in engineering asset health management. We have previously reported the semi-parametric Explicit Hazard Model (EHM) which incorporates three types of information: population characteristics; condition indicators; and operating environment indicators for hazard prediction. This model assumes the baseline hazard has the form of the Weibull distribution. To avoid this assumption, this paper presents the non-parametric EHM which is a distribution-free covariate-based hazard model. In this paper, an application of the non-parametric EHM is demonstrated via a case study. In this case study, survival probabilities of a set of resistance elements using the non-parametric EHM are compared with the Weibull proportional hazard model and traditional Weibull model. The results show that the non-parametric EHM can effectively predict asset life using the condition indicator, operating environment indicator, and failure history.

Using decision trees in economizer repair decision making

The economiser is a critical component for efficient operation of coal-fired power stations. It consists of a large system of water-filled tubes which extract heat from the exhaust gases. When it fails, usually due to erosion causing a leak, the entire power station must be shut down to effect repairs. Not only are such repairs highly expensive, but the overall repair costs are significantly affected by fluctuations in electricity market prices, due to revenue lost during the outage. As a result, decisions about when to repair an economiser can alter the repair costs by millions of dollars. Therefore, economiser repair decisions are critical and must be optimised. However, making optimal repair decisions is difficult because economiser leaks are a type of interactive failure. If left unfixed, a leak in a tube can cause additional leaks in adjacent tubes which will need more time to repair. In addition, when choosing repair times, one also needs to consider a number of other uncertain inputs such as future electricity market prices and demands. Although many different decision models and methodologies have been developed, an effective decision-making method specifically for economiser repairs has yet to be defined. In this paper, we describe a Decision Tree based method to meet this need. An industrial case study is presented to demonstrate the application of our method.

Identifying familiarity to facilitate intuitive interaction for older adults

Almost every nation on the planet is experiencing increases in both the number and proportion of older adults. Research has shown that older adults use technology less intuitively than younger adults, and have more difficulty with using products effectively. With an ever-increasing population of older adults, it is necessary to understand why they often struggle to use technology, which is becoming more and more important in day to day living. Intuitive use of products is grounded in familiarity and prior experience. The aims of this research were twofold: (i) to examine the differences in familiarity between younger and older adults, to see if this could explain the difficulties faced by some older adults; (ii) to develop investigational methods to assist designers in identifying familiarity in prospective users. Two empirical studies were conducted. The first experiment was conducted in the field with 32 participants, divided across four age groups (18 – 44, 45 – 59, 60 – 74, and 75+). This experiment was conducted in the participants’ homes, with a product they were familiar with. Familiarity was measured through the analysis of data collected through interviews, observation and retrospective protocol. The results of this study show that the youngest group demonstrated significantly higher levels of familiarity with products they own than the 60 – 74 and the 75+ age groups. There were no significant differences between the 18 – 44 age group and the 45 – 59 age group and there were also no significant differences between the three oldest age groups. The second experiment was conducted with 32 participants, across the same four age groups. Four everyday products were used in this experiment. The results of Experiment 2 show that, with previously unused products, younger adults demonstrate significantly higher levels of familiarity than the three older age groups. The three oldest age groups had no significant differences between them. The results of these two studies show that younger adults are more familiar with contemporary products than older adults. They also demonstrate that in terms of familiarity, older adults do not differ significantly as they get older. The results also show that the 45 – 59 age group demonstrate higher levels of familiarity with products they have owned, in comparison with those they have not. The two older age groups did not demonstrate such differences. This suggests that interacting with products over time increases familiarity more for middle-aged adults than for older adults. As a result of this research, a method that can be used by designers to identify potential users’ product familiarity has been identified. This method is easy to use, quick, low cost, highly mobile, flexible, and allows for easy data collection and analysis. A tool has been designed that assists designers and researchers to use the method. Designers can use the knowledge gained from this tool, and integrate it into the design process, resulting in more intuitive products. Such products may lead to improvements in the quality of life of older adults, as a result of improved societal integration, better health management, and more widespread use of communications technology.

A case-control study of ambient heat exposure and urolithiasis among outdoor workers in a shipbuilding company, Guangzhou, China

Higher ambient temperatures will increase heat stress on workers, leading to impacts upon their individual health and productivity. In particular, research has indicated that higher ambient temperatures can increase the prevalence of urolithiasis. This thesis examines the relationship between ambient heat exposure and urolithiasis among outdoor workers in a shipbuilding company in Guangzhou, China, and makes recommendations for minimising the possible impacts of high ambient temperatures on urolithiasis. A retrospective 1:4 matched case-control study was performed to investigate the association between ambient heat exposure and urolithiasis. Ambient heat exposure was characterised by total exposure time, type of work, department and length of service. The data were obtained from the affiliated hospital of the shipbuilding company under study for the period 2003 to 2010. A conditional logistic regression model was used to estimate the association between heat exposure and urolithiasis. This study found that the odds ratio (OR) of urolithiasis for total exposure time was 1.5 (95% confidence interval (CI): 1.2–1.8). Eight types of work in the shipbuilding company were investigated, including welder, assembler, production security and quality inspector, planing machine operator, spray painter, gas-cutting worker and indoor employee. Five out of eight types of work had significantly higher risks for urolithiasis, and four of the five mainly consisted of outdoors work with ORs of 4.4 (95% CI: 1.7–11.4) for spray painter, 3.8 (95% CI: 1.9–7.2) for welder, 2.7 (95% CI: 1.4–5.0) for production security and quality inspector, and 2.2 (95% CI: 1.1–4.3) for assembler, compared to the reference group (indoor employee). Workers with abnormal blood pressure (hypertension) were more likely to have urolithiasis with an OR of 1.6 (95% CI: 1.0–2.5) compared to those without hypertension. This study contributes to the understanding of the association between ambient heat exposure and urolithiasis among outdoor workers in China. In the context of global climate change, this is particularly important because rising temperatures are expected to increase the prevalence of urolithiasis among outdoor workers, putting greater pressure on productivity, occupational health management and health care systems. The results of this study have clear implications for public health policy and planning, as they indicate that more attention is required to protect outdoor workers from heat-related urolithiasis.

Evidence based healthcare planning in developing countries : an informatics perspective

Most of the national Health Information Systems (HIS) in resource limited developing countries do not serve the purpose of management support and thus the service is adversely affected. While emphasising the importance of timely and accurate health information in decision making in healthcare planning, this paper explains that Health Management Information System Failure is commonly seen in developing countries as well as the developed countries. It is suggested that the possibility of applying principles of Health Informatics and the technology of Decision Support Systems should be seriously considered to improve the situation. A brief scientific explanation of the evolution of these two disciplines is included.

Reflections for the challenges of tomorrow : where we started

Dietetics in Australia commenced in the 1930’s, inspired by formation of the profession in Britain and the United States. Almost exclusively a female profession, its roots were in nursing management in Britain and food science and home economics in the US, incorporating the principles of food preparation and supply, food and medical science, public health, management, all based on principles of social justice. Victoria employed the first dietitian in 1929, followed by NSW in 1936. Right from the start there was rivalry between the two states over the standard of training, Victoria and later Western Australia, following a college based institutional management focus and NSW, university graduates in science. Both however were committed to the hospital internship as a prelude to safe practice. Soon after, professional associations arose independently in both states, the purpose being to promote appropriate standards in education and to define the level of training required to enter the profession, though it was not until 1950 that a national association was formed. Parallel to the establishment of dietetic training and professional activities, a number of significant public health and medical science initiatives influenced the scope of dietetic practice. The Commonwealth Government commissioned dietary surveys in Australian cities as well as remote communities of Aboriginal and Papuan peoples. Newly discovered components of a healthy diet provided the beginnings of nutrition policy. Pioneer dietitians were trailblazers, with few role models. Their influence ranged across Australia to the United Nations and WHO and we can learn much from their endeavour.

Data driven and practice-based evidence : design and development of efficient and effective clinical decision support system

Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

Feasibility and acceptability of wrist actigraph in assessing sleep quality and sleep quantity: A home-based pilot study in healthy volunteers

Purpose This study aimed to determine the feasibility and acceptability of actigraphy to monitor sleep quality and quantity in healthy self-rated good sleeper adults at home-based settings. Method Sixteen healthy volunteers (age > 18) were invited to participate. Each participant was provided with a wrist actigraph device to be worn for 24-hour/day for seven consecutive days to monitor their sleep-wake patterns. Actigraphy data were downloaded using-proprietary software to generate an individual-sleep report. Participants also completed a set of self-reported Health Related Quality of Life (HRQOL) using WHO (five) Well Being Index (WBI) questionnaires. Results Actigraphy was well accepted by all participants. Only 43.8% of the participants achieved normal total sleep time (TST) and 62.5% had a mean sleep efficiency value below the normal range. Despite a reduced quality of sleep among the participants, the self-reported HRQOL scores produced by the WHO-5 WBI showed a “fair” to “good” among the participants. Conclusions To maintain healthy well-being, it is vital to have efficient and quality sleep. Insufficient and poor sleep may contribute to various health problems and hazardous outcomes. People often believe they have normal and efficient sleep, not realising they may be developing poor sleep habits. This study found that actigraphy can be easily utilized to monitor sleep-wake patterns at home-based settings. We proposed that actigraphy could be adapted for use in the primary care settings (e.g. community pharmacy) to improve the sleep health management in the community.

Differences in grass pollen allergen exposure across Australia

Objective Allergic rhinitis and allergic asthma are important chronic diseases posing serious public health issues in Australia with associated medical, economic, and societal burdens. Pollen are significant sources of clinically relevant outdoor aeroallergens, recognised as both a major trigger for, and cause of, allergic respiratory diseases. This study aimed to provide a national, and indeed international, perspective on the state of Australian pollen data using a large representative sample. Methods Atmospheric grass pollen concentration is examined over a number of years within the period 1995 to 2013 for Brisbane, Canberra, Darwin, Hobart, Melbourne, and Sydney, including determination of the clinical' grass pollen season and grass pollen peak. Results The results of this study describe, for the first time, a striking spatial and temporal variability in grass pollen seasons in Australia, with important implications for clinicians and public health professionals, and the Australian grass pollen-allergic community. Conclusions These results demonstrate that static pollen calendars are of limited utility and in some cases misleading. This study also highlights significant deficiencies and limitations in the existing Australian pollen monitoring and data. Implications: Establishment of an Australian national pollen monitoring network would help facilitate advances in the clinical and public health management of the millions of Australians with asthma and allergic rhinitis.

Identification of bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei reveals distinct temperature-driven patterns

Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.