Estimating indoor air quality using integrated 3D CAD building models

The indoor air quality (IAQ) in buildings is currently assessed by measurement of pollutants during building operation for comparison with air quality standards. Current practice at the design stage tries to minimise potential indoor air quality impacts of new building materials and contents by selecting low-emission materials. However low-emission materials are not always available, and even when used the aggregated pollutant concentrations from such materials are generally overlooked. This paper presents an innovative tool for estimating indoor air pollutant concentrations at the design stage, based on emissions over time from large area building materials, furniture and office equipment. The estimator considers volatile organic compounds, formaldehyde and airborne particles from indoor materials and office equipment and the contribution of outdoor urban air pollutants affected by urban location and ventilation system filtration. The estimated pollutants are for a single, fully mixed and ventilated zone in an office building with acceptable levels derived from Australian and international health-based standards. The model acquires its dimensional data for the indoor spaces from a 3D CAD model via IFC files and the emission data from a building products/contents emissions database. This paper describes the underlying approach to estimating indoor air quality and discusses the benefits of such an approach for designers and the occupants of buildings.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

Simulations of pollutant dispersion at toll plazas using three-dimensional CFD models

Toll plazas are particularly susceptible to build-ups of vehicle-emitted pollutants because vehicles pass through in low gear. To look at this, three-dimensional computational fluid dynamics simulations of pollutant dispersion are used on the standard k e turbulence model. The effects of wind speed, wind direction and topography on pollutant dispersion were discussed. The Wuzhuang toll plaza on the Hefei-Nanjing expressway is considered, and the effects of the retaining walls along both sides of the plaza on pollutant dispersion is analysed. There are greater pollutant concentrations near the tollbooths as the angle between the direction of the wind and traffic increases implying that retaining walls impede dispersion. The slope of the walls has little influence on the variations in pollutant concentration.

An investigation of the social learning and symbolic interaction models for the development of self-concepts and self-esteem

Two studies were conducted to investigate empirical support for two models relating to the development of self-concepts and self-esteem in upper-primary school children. The first study investigated the social learning model by examining the relationship between mothers' and fathers' self-reported self-concepts and self-esteem and the self-reported self-concepts and self-esteem of their children. The second study investigated the symbolic interaction model by examining the relationship between children's perception of the frequency of positive and negative statements made by parents and their self-reported self-concepts and self-esteem. The results of these studies suggested that what parents say to their children and how they interact with them is more closely related to their children's self-perceptions than the role of modelling parental attitudes and behaviours. The findings highlight the benefits of parents talking positively to their children.

A review on degradation models in reliability analysis

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

Is the Marlboro man the only alternative? The role of gender identity and self-construal salience in evaluations of male models

This research examines how men react to male models in print advertisements. In two experiments, we show that the gender identity of men influences their responses to advertisements featuring a masculine, feminine, or androgynous male model. In addition, we explore the extent to which men feel they will be classified by others as similar to the model as a mechanism for these effects. Specifically, masculine men respond most favorably to masculine models and are negative toward feminine models. In contrast, feminine men prefer feminine models when their private self is salient. Yet in a collective context, they prefer masculine models.These experiments shed light on how gender identity and self-construal influence male evaluations and illustrate the social pressure on men to endorse traditional masculine portrayals. We also present implications for advertising practice.

Self-referencing and consumer evaluations of larger-sized female models : a weight locus of control perspective

In two experiments, we show that the beliefs women have about the controllability of their weight (i.e., weight locus of control) influences their responses to advertisements featuring a larger-sized female model or a slim female model. Further, we examine self-referencing as a mechanism for these effects. Specifically, people who believe they can control their weight (“internals”), respond most favorably to slim models in advertising, and this favorable response is mediated by self-referencing. In contrast, people who feel powerless about their weight (“externals”), self-reference larger-sized models, but only prefer larger-sized models when the advertisement is for a non-fattening product. For fattening products, they exhibit a similar preference for larger-sized models and slim models. Together, these experiments shed light on the effect of model body size and the role of weight locus of control in influencing consumer attitudes.

Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modelling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modelling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modelling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

Contemporary New Zealand coefficients for the Trauma Injury Severity Score: TRISS(NZ)

Aims – To develop local contemporary coefficients for the Trauma Injury Severity Score in New Zealand, TRISS(NZ), and to evaluate their performance at predicting survival against the original TRISS coefficients. Methods – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until presentation at Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Coefficients were estimated using ordinary and multilevel mixed-effects logistic regression models. Results – 1735 eligible patients were identified, 1672 (96%) injured from a blunt mechanism and 63 (4%) from a penetrating mechanism. For blunt mechanism trauma, 1250 (75%) were male and average age was 38 years (range: 15-94 years). TRISS information was available for 1565 patients of whom 204 (13%) died. Area under the Receiver Operating Characteristic (ROC) curves was 0.901 (95%CI: 0.879-0.923) for the TRISS(NZ) model and 0.890 (95% CI: 0.866-0.913) for TRISS (P<0.001). Insufficient data were available to determine coefficients for penetrating mechanism TRISS(NZ) models. Conclusions – Both TRISS models accurately predicted survival for blunt mechanism trauma. However, TRISS(NZ) coefficients were statistically superior to TRISS coefficients. A strong case exists for replacing TRISS coefficients in the New Zealand benchmarking software with these updated TRISS(NZ) estimates.

Using self-referencing to explain the effectiveness of ethnic minority models in advertising

Advertising research has generally not gone beyond offering support for a positive effect where ethnic models in advertising are viewed by consumers of the same ethnicity. This study offers an explanation behind this phenomenon that can be useful to marketers using self-reference theory. Our experiment reveals a strong self-referencing effect for ethnic minority individuals. Specifically, Asian subjects (the ethnic minority group) self-referenced ads with Asian models more than white subjects (the ethnic majority group). However, this result was not evident for white subjects. Implications for academics and advertisers are discussed.

Effective models of employment-based training

Australia needs highly skilled workers to sustain a healthy economy. Current employment-based training models have limitations in meeting the demands for highly skilled labour supply. The research explored current and emerging models of employment-based training to propose more effective models at higher VET qualifications that can maintain a balance between institution and work-based learning.

Images of desire : cognitive models of craving

Cognitive modelling of phenomena in clinical practice allows the operationalisation of otherwise diffuse descriptive terms such as craving or flashbacks. This supports the empirical investigation of the clinical phenomena and the development of targeted treatment interventions. This paper focuses on the cognitive processes underpinning craving, which is recognised as a motivating experience in substance dependence. We use a high-level cognitive architecture, Interacting Cognitive Subsystems (ICS), to compare two theories of craving: Tiffany's theory, centred on the control of automated action schemata, and our own Elaborated Intrusion theory of craving. Data from a questionnaire study of the subjective aspects of everyday desires experienced by a large non-clinical population are presented. Both the data and the high-level modelling support the central claim of the Elaborated Intrusion theory that imagery is a key element of craving, providing the subjective experience and mediating much of the associated disruption of concurrent cognition.

The Influence of Farm Management on NSW Rural Property Income and Total Average Annual Returns

The importance of agriculture in many countries has tended to reduce as their economies move from a resource base to a manufacturing industry base. Although the level of agricultural production in first world countries has increased over the past two decades, this increase has generally been at a less significant rate compared to other sectors of the economies. Despite this increase in secondary and high technology industries, developed countries have continued to encourage and support their agricultural industries. This support has been through both tariffs and price support. Following pressure from developing economies, particularly through the World Trade Organisation (WTO), GATT Uruguay round and the Cairns Group developed countries are now in various stages of winding back or de-coupling agricultural support within their economies. A major concern of farmers in protected agricultural markets is the impact of a free market trade in agricultural commodities on farm incomes, profitability and land values. This paper will analyse both the capital and income performance of the NSW rural land market over the period 1990-1999. This analysis will be based on several rural land use classifications and will compare the total return from rural properties based on the farm income generated by both the average farmer and those farmers considered to be in the top 20% of the various land use areas. The analysis will provide a comprehensive overview of rural production in a free trade economy.