On adaptive HMM state estimation

In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.

A critical review of structural equation modeling applications in construction research

Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.

The elaboration likelihood model : review, critique and research agenda

Purpose: The purpose of this paper is to review, critique and develop a research agenda for the Elaboration Likelihood Model (ELM). The model was introduced by Petty and Cacioppo over three decades ago and has been modified, revised and extended. Given modern communication contexts, it is appropriate to question the model’s validity and relevance. Design/methodology/approach: The authors develop a conceptual approach, based on a fully comprehensive and extensive review and critique of ELM and its development since its inception. Findings: This paper focuses on major issues concerning the ELM. These include model assumptions and its descriptive nature; continuum questions, multi-channel processing and mediating variables before turning to the need to replicate the ELM and to offer recommendations for its future development. Research limitations/implications: This paper offers a series of questions in terms of research implications. These include whether ELM could or should be replicated, its extension, a greater conceptualization of argument quality, an explanation of movement along the continuum and between central and peripheral routes to persuasion, or to use new methodologies and technologies to help better understanding consume thinking and behaviour? All these relate to the current need to explore the relevance of ELM in a more modern context. Practical implications: It is time to question the validity and relevance of the ELM. The diversity of on- and off-line media options and the variants of consumer choice raise significant issues. Originality/value: While the ELM model continues to be widely cited and taught as one of the major cornerstones of persuasion, questions are raised concerning its relevance and validity in 21st century communication contexts.

Transport and health in China : recent collaborative research relating to vehicle factors and pollution

The nature of the transport system contributes to public health outcomes in a range of ways. The clearest contribution to public health is in the area of traffic crashes, because of their direct impact on individual death and disability and their direct costs to the health system. Other papers in this conference address these issues. This paper outlines some collaborative research between the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) at QUT and Chinese researchers in areas that have indirect health impacts. Heavy vehicle dynamics: The integrity of the road surface influences crash risk, with ruts, pot-holes and other forms of road damage contributing to increased crash risks. The great majority of damage to the road surface from vehicles is caused by heavy trucks and buses, rather than cars or smaller vehicles. In some cases this damage is due to deliberate overloading, but in other cases it is due to vehicle suspension characteristics that lead to occasional high loads on particular wheels. Together with a visiting researcher and his colleagues, we have used both Queensland and Chinese data to model vehicle suspension systems that reduce the level of load, and hence the level of road damage and resulting crash risk(1-5). Toll worker exposure to vehicle emissions: The increasing construction of highways in China has also involved construction of a large number of toll roads. Tollbooth workers are potentially exposed to high levels of pollutants from vehicles, however the extent of this exposure and how it relates to standards for exposure are not well known. In a study led by a visiting researcher, we conducted a study to model these levels of exposure for a tollbooth in China(6). Noise pollution: The increasing presence of high speed roads in China has contributed to an increase in noise levels. In this collaborative study we modelled noise levels associated with a freeway widening near a university campus, and measures to reduce the noise(7). Along with these areas of research, there are many other areas of transport with health implications that are worthy of exploration. Traffic, noise and pollution contribute to a difficult environment for pedestrians, especially in an ageing society where there are health benefits to increasing physical activity. By building on collaborations such as those outlined, there is potential for a contribution to improved public health by addressing transport issues such as vehicle factors and pollution, and extending the research to other areas of travel activity. 1. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2014). Stiffness-damping matching method of an ECAS system based on LQG control. Journal of Central South University, 21:439-446. DOI: 10.1007/s1177101419579 2. Chen, Y., He, J., King, M., Feng, Z. and Chang, W. (2013). Comparison of two suspension control strategies for multi-axle heavy truck. Journal of Central South University, 20(2): 550-562. 3. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2013). Effect of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions. Science China Technological Sciences, 56(3): 666-676. DOI: 10.1007/s11431-012-5091-3 4. Chen, Y., He., J., King, M., Chen, W. and Zhang, W. (2013). Model development and dynamic load-sharing analysis of longitudinal-connected air suspensions. Strojniški Vestnik - Journal of Mechanical Engineering, 59(1):14-24. 5. Chen, Y., He, J., King, M., Liu, H. and Zhang, W. (2013). Dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-1117. 6. He, J., Qi, Z., Hang, W., King, M., and Zhao, C. (2011). Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models. Transportation Research Part C, 19(2011):510-520. 7. Zhang, C., He, J., Wang, Z., Yin, R. and King, M. (2013). Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-2016.

Re-valuing construction materials and components through design for disassembly

The construction industry accounts for a significant portion of the material consumption of our industrialised societies. That material consumption comes at an environmental cost, and when buildings and infrastructure projects are demolished and discarded, after their useful lifespan, that environmental cost remains largely unrecovered. The expected operational lifespan of modern buildings has become disturbingly short as buildings are replaced for reasons of changing cultural expectations, style, serviceability, locational obsolescence and economic viability. The same buildings however are not always physically or structurally obsolete; the materials and components within them are very often still completely serviceable. While there is some activity in the area of recycling of selected construction materials, such as steel and concrete, this is almost always in the form of down cycling or reprocessing. Very little of this material and component resource is reuse in a way that more effectively captures its potential. One significant impediment to such reuse is that buildings are not designed in a way that facilitates easy recovery of materials and components; they are designed and built for speed of construction and quick economic returns, with little or no consideration of the longer term consequences of their physical matter. This research project explores the potential for the recovery of materials and components if buildings were designed for such future recovery; a strategy of design for disassembly. This is not a new design philosophy; design for disassembly is well understood in product design and industrial design. There are also some architectural examples of design for disassembly; however these are specialist examples and there is no significant attempt to implement the strategy in the main stream construction industry. This paper presents research into the analysis of the embodied energy in buildings, highlighting its significance in comparison with operational energy. Analysis at material, component, and whole-of-building levels shows the potential benefits of strategically designing buildings for future disassembly to recover this embodied energy. Careful consideration at the early design stage can result in the deconstruction of significant portions of buildings and the recovery of their potential through higher order reuse and upcycling.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Associated schools of construction of southern Africa infrastructure design and delivery workshop - Report. CIB task group 91 infrastructure

This workshop comprised a diverse group of African construction experts, ranging far wider than RSA. Each of the attendees had attended the annual ASOCSA conference and was additionally provided with a short workshop pre-brief. The aim was to develop a view of their 15-20 year vision of construction improvement in RSA and the steps necessary to get there. These included sociological, structural, technical and process changes. Whilst some suggestions are significantly challenging, none are impossible, given sufficient collaboration between government, industry, academia and NGOs. The highest priority projects (more properly, programmes) were identified and further explored. These are: 1. Information Hub (‘Open Africa’). Aim – to utilise emerging trends in Open Data to provide a force for African unity. 2. Workforce Development. Aim – to rebuild a competent, skilled construction industry for RSA projects and for export. 3. Modular DIY Building. Aim – to accelerate the development of sustainable, cost-efficient and desirable housing for African economic immigrants and others living in makeshift and slum dwellings. Open Data is a maturing theme in different cities and governments around the world and the workshop attendees were very keen to seize such a possibility to assist in developing an environment where Africans can share information and foster collaboration. It is likely that NGOs might be keen to follow up such an initiative. There are significant developments taking place around the world in the construction sector currently, with comparatively large savings being made for taxpayers (20% plus in the UK). Not all of these changes would be easy to transplant to RSA (even more so to much of the rest of Africa). Workforce development was a keen plea amongst the attendees, who seemed concerned that expertise has leaked away and is not being replaced with sufficient intensity. It is possible today to develop modular buildings in such a way that even unskilled residents can assist in their construction, and even their appropriate design. These buildings can be sited nearly autonomously from infrastructures, thus relieving the tensions on cities and townships, whilst providing humane accommodation for the economically disadvantaged. Development of suitable solutions could either be conducted with other similarly stressed countries or developed in-country and the expertise exported. Finally, it should be pointed out that this was very much a first step. Any opportunity to collaborate from an Australian, QUT or CIB perspective would be welcomed, whilst acknowledging that the leading roles belong to RSA, CSIR, NRF, ASOCSA and the University of KwaZulu-Natal.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Urinary tract infection of mice to model human disease: Practicalities, implications and limitations

Urinary tract infections (UTIs) are among the most common bacterial infections in humans. Murine models of human UTI are vital experimental tools that have helped to elucidate UTI pathogenesis and advance knowledge of potential treatment and infection prevention strategies. Fundamentally, several variables are inherent in different murine models, and understanding the limitations of these variables provides an opportunity to understand how models may be best applied to research aimed at mimicking human disease. In this review, we discuss variables inherent in murine UTI model studies and how these affect model usage, data analysis and data interpretation. We examine recent studies that have elucidated UTI host–pathogen interactions from the perspective of gene expression, and review new studies of biofilm and UTI preventative approaches. We also consider potential standards for variables inherent in murine UTI models and discuss how these might expand the utility of models for mimicking human disease and uncovering new aspects of pathogenesis

Relations between chronic regulatory focus and future time perspective: Results of a cross-lagged structural equation model

Future time perspective - the way individuals perceive their remaining time in life - importantly influences socio-emotional goals and motivational outcomes. Recently, researchers have called for studies that investigate relationships between personality and future time perspective. Using a cross-lagged panel design, this study investigated effects of chronic regulatory focus dimensions (promotion and prevention orientation) on future time perspective dimensions (focus on opportunities and limitations). Survey data were collected two times, separated by a 3. month time lag, from 85 participants. Results of structural equation modeling showed that promotion orientation had a positive lagged effect on focus on opportunities, and prevention orientation had a positive lagged effect on focus on limitations.

The UNCITRAL Model Law on Cross-border Insolvency and its Potential Role in Upholding the Rule of Law

The rule of law is understood to be a core aspect in achieving a stable economy and an ordered society. Without the elements that are inherent in this principle the possibilities of anarchy, unfairness and uncertainty are amplified, which in turn can result in an economy with dramatic fluctuations. In this regard, commentators do not always agree that the rule of law is strictly adhered to in the international legal context. Therefore, this paper will explore one aspect of international regulation and consider whether the UNCITRAL Model Law on Cross-border Insolvency (1997) (‘Model Law’) and its associated Guide to Enactment and Interpretation (2013) contribute to the promotion of the key elements of the rule of law.

Organisational culture and quality management system implementation in Indonesian construction companies

The study of the organisational culture in the construction industry is still in the stage of debate (Oney-Yazıcı et al., 2007). Despite the complexities involved in measuring the culture of the construction industry (Tijhuis and Fellows, 2012), this culture is regarded as being worthy of research, especially in relation to the organisational culture needed to support quality management systems (Koh and Low, 2008; Watson and Howarth, 2011) and to improve organisational effectiveness, and therefore, organisational performance (Coffey, 2010; Cheung et al., 2011). A number of recent studies have examined the construction companies’ organisational culture within the context of the use of Cameron and Quinn’s Competing Value Framework (CVF), as well as the use of their Organizational Culture Assessment Instrument (OCAI) as the conceptual paradigm for the analyses (Thomas et al., 2002; Nummelin, 2006; Oney- Yazıcı et al., 2007; Koh and Low, 2008). However, there has been little research based on the use of Cameron and Quinn’s CVF-OCAI tool for identifying types of construction companies’ organisational culture and their influences on the implementation of QMS-ISO 9001. Research output and information is also very limited relating to the strength of the companies’ organisational culture driving an effective QMS-ISO 9001 implementation, affecting the companies’ effectiveness. To rectify these research gaps, the research has been aimed to study organisational culture types (based on CVF) and their influences on the implementation of QMS-ISO 9001:2008 principles and elements, which eventually lead to improved companies’ quality performance. In order to fully examine the status of the QMS being implemented, the research has studied the relationships of the barriers of QMS implementation with the implementation of QMS-ISO 9001:2008 principles and elements and with the business performance of the companies, as well as the examination of the relationships of the implementation of QMS-ISO 9001:2008 principles and elements with the companies’ business performance. The research output has been the development of fundamental and original studies on the study topics, to provide the knowledge for improvements in Indonesian construction companies’ quality performance and quality outcomes.

A psychosocial analysis of parent's decisions for limiting their young child's screen time: An examination of attitudes, social norms and roles, and control perceptions

- Objectives Preschool-aged children spend substantial amounts of time engaged in screen-based activities. As parents have considerable control over their child's health behaviours during the younger years, it is important to understand those influences that guide parents' decisions about their child's screen time behaviours. - Design A prospective design with two waves of data collection, 1 week apart, was adopted. - Methods Parents (n = 207) completed a Theory of Planned Behaviour (TPB)-based questionnaire, with the addition of parental role construction (i.e., parents' expectations and beliefs of responsibility for their child's behaviour) and past behaviour. A number of underlying beliefs identified in a prior pilot study were also assessed. - Results The model explained 77% (with past behaviour accounting for 5%) of the variance in intention and 50% (with past behaviour accounting for 3%) of the variance in parental decisions to limit child screen time. Attitude, subjective norms, perceived behavioural control, parental role construction, and past behaviour predicted intentions, and intentions and past behaviour predicted follow-up behaviour. Underlying screen time beliefs (e.g., increased parental distress, pressure from friends, inconvenience) were also identified as guiding parents' decisions. - Conclusion Results support the TPB and highlight the importance of beliefs for understanding parental decisions for children's screen time behaviours, as well as the addition of parental role construction. This formative research provides necessary depth of understanding of sedentary lifestyle behaviours in young children which can be adopted in future interventions to test the efficacy of the TPB mechanisms in changing parental behaviour for their child's health.