Effective punishment experiences : the need for a more comprehensive approach to conceptualising behavioural punishers and reinforcers in a road safety context

Determining what consequences are likely to serve as effective punishment for any given behaviour is a complex task. This chapter focuses specifically on illegal road user behaviours and the mechanisms used to punish and deter them. Traffic law enforcement has traditionally used the threat and/or receipt of legal sanctions and penalties to deter illegal and risky behaviours. This process represents the use of positive punishment, one of the key behaviour modification mechanisms. Behaviour modification principles describe four types of reinforcers: positive and negative punishments and positive and negative reinforcements. The terms ‘positive’ and ‘negative’ are not used in an evaluative sense here. Rather, they represent the presence (positive) or absence (negative) of stimuli to promote behaviour change. Punishments aim to inhibit behaviour and reinforcements aim to encourage it. This chapter describes a variety of punishments and reinforcements that have been and could be used to modify illegal road user behaviours. In doing so, it draws on several theoretical perspectives that have defined behavioural reinforcement and punishment in different ways. Historically, the main theoretical approach used to deter risky road use has been classical deterrence theory which has focussed on the perceived certainty, severity and swiftness of penalties. Stafford and Warr (1993) extended the traditional deterrence principles to include the positive reinforcement concept of punishment avoidance. Evidence of the association between punishment avoidance experiences and behaviour has been established for a number of risky road user behaviours including drink driving, unlicensed driving, and speeding. We chose a novel way of assessing punishment avoidance by specifying two sub-constructs (detection evasion and punishment evasion). Another theorist, Akers, described the idea of competing reinforcers, termed differential reinforcement, within social learning theory (1977). Differential reinforcement describes a balance of reinforcements and punishments as influential on behaviour. This chapter describes comprehensive way of conceptualising a broad range of reinforcement and punishment concepts, consistent with Akers’ differential reinforcement concept, within a behaviour modification framework that incorporates deterrence principles. The efficacy of three theoretical perspectives to explain self-reported speeding among a sample of 833 Australian car drivers was examined. Results demonstrated that a broad range of variables predicted speeding including personal experiences of evading detection and punishment for speeding, intrinsic sensations, practical benefits expected from speeding, and an absence of punishing effects from being caught. Not surprisingly, being younger was also significantly related to more frequent speeding, although in a regression analysis, gender did not retain a significant influence once all punishment and reinforcement variables were entered. The implications for speed management, as well as road user behaviour modification more generally, are discussed in light of these findings. Overall, the findings reported in this chapter suggest that a more comprehensive approach is required to manage the behaviour of road users which does not rely solely on traditional legal penalties and sanctions.

A RBF meshless approach for modeling a fractal mobile/immobile transport model

A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

Brand value of property in Bangkok Metropolitan Region (BMR), Thailand

This paper aims to evaluate the brand value of property in subdivision developments in the Bangkok Metropolitan Region (BMR), Thailand. The result has been determined by the application of a hedonic price model. The development of the model is developed based on a sample of 1,755 property sales during the period of 1992-2010 in eight zones of the BMR. The results indicate that the use of a semi-logarithmic model has stronger explanatory power and is more reliable. Property price increases 12.90% from the branding. Meanwhile, the price annually increases 2.96%; lot size and dwelling area have positive impacts on the price. In contrast, duplexes and townhouses have a negative impact on the price compared to single detached houses. Moreover, the price of properties which are located outside the Bangkok inner city area is reduced by 21.26% to 43.19%. These findings also contribute towards a new understanding of the positive impact of branding on the property price in the BMR. The result is useful for setting selling prices for branded and unbranded properties, and the model could provide a reference for setting property prices in subdivision developments in the BMR.

Real-time video event detection in crowded scenes using MPEG derived features : a multiple instance learning approach

This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

InterLACE : a new international collaboration for a Life course approach to women's reproductive health and chronic disease events.

Evidence from population-based studies of women increasingly points to the inter-related nature of reproductive health, lifestyle, and chronic disease risk. This paper describes the recently established International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease. InterLACE aims to advance the evidence base for women's health policy beyond associations from disparate studies by means of systematic and culturally sensitive synthesis of longitudinal data. Currently InterLACE draws on individual level data for reproductive health and chronic disease among 200,000 women from over thirteen studies of women's health in seven countries. The rationale for this multi-study research programme is set out in terms of a life course perspective to reproductive health. The research programme will build a comprehensive picture of reproductive health through life in relation to chronic disease risk. Although combining multiple international studies poses methodological challenges, InterLACE represents an invaluable opportunity to strength evidence to guide the development of timely and tailored preventive health strategies.

The impact of mining and smelting activities on property values : a study of Mount Isa city, Queensland, Australia

Much publicity has been given to the problem of high levels of environmental contaminants, most notably high blood lead concentration levels among children in the city of Mount Isa because of mining and smelting activities. The health impacts from mining-related pollutants are now well documented. This includes published research being discussed in an editorial of the Medical Journal of Australia (see Munksgaard et al. 2010). On the other hand, negative impacts on property prices, although mentioned, have not been examined to date. This study rectifies this research gap. This study uses a hedonic property price approach to examine the impact of mining- and smelting-related pollution on nearby property prices. The hypothesis is that those properties closer to the lead and copper smelters have lower property (house) prices than those farther away. The results of the study show that the marginal willingness to pay to be farther from the pollution source is AUS $13 947 per kilometre within the 4 km radius selected. The study has several policy implications, which are discussed briefly. We used ordinary least squares, geographically weighted regression, spatial error and spatial autoregressive or spatial lag models for this analysis.

A CLASS act : the teaching team approach to subject coordination

Advancing the development of good practice around the teaching team has been the focus of a recently completed, nationally funded Australian grant entitled Coordinators Leading Advancement of Sessional Staff (CLASS). The project focused on developing leadership capacity of subject coordinators to provide supportive contexts for sessional staff to enhance their knowledge of teaching practice and contribute to subject improvement through a team approach. An action learning approach and notions of distributed leadership underpinned the activities of the teaching teams in the program. This paper provides an overview of a practical approach, led by the subject coordinator, to engaging sessional staff through the facilitation of a supportive network within the teaching team. It addresses some of the gaps identified in the recent literature which includes lack of role clarity for all members of the team and provides some examples of initiatives that teams engaged with to address some of the challenges identified. Resources to support this approach were developed and are shared through the project website. Recommendations for future direction include improved policy and practice at the institutional level, better recognition and reward for subject coordinators and resourcing to support the participation and professional development needs of sessional staff.

Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.

A proposed approach to monitor private-sector policies and practices related to food environments, obesity and non-communicable disease prevention

Private-sector organizations play a critical role in shaping the food environments of individuals and populations. However, there is currently very limited independent monitoring of private-sector actions related to food environments. This paper reviews previous efforts to monitor the private sector in this area, and outlines a proposed approach to monitor private-sector policies and practices related to food environments, and their influence on obesity and non-communicable disease (NCD) prevention. A step-wise approach to data collection is recommended, in which the first (‘minimal’) step is the collation of publicly available food and nutrition-related policies of selected private-sector organizations. The second (‘expanded’) step assesses the nutritional composition of each organization's products, their promotions to children, their labelling practices, and the accessibility, availability and affordability of their products. The third (‘optimal’) step includes data on other commercial activities that may influence food environments, such as political lobbying and corporate philanthropy. The proposed approach will be further developed and piloted in countries of varying size and income levels. There is potential for this approach to enable national and international benchmarking of private-sector policies and practices, and to inform efforts to hold the private sector to account for their role in obesity and NCD prevention.

Assessing the suitability of market approach valuation methods for mine and quarry valuations

An area of property valuation that has attracted less attention than other property markets over the past 20 years has been the mining and extractive industries. These operations can range from small operators on leased or private land to multinational companies. Although there are a number of national mining standards that indicate the type of valuation methods that can be adopted for this asset class, these standards do not specify how or when these methods are best suited to particular mine operations. The RICS guidance notes and the draft IVSC guidance notes also advise the various valuations methods that can be used to value mining properties; but, again they do not specify what methods should be applied where and when. One of the methods supported by these standards and guidelines is the market approach. This paper will carry out an analysis of all mine, extractive industry and waste disposal sites sale transactions in Queensland Australia, a major world mining centre, to determine if a market valuation approach such as direct comparison is actually suitable for the valuation of a mine or extractive industry. The analysis will cover the period 1984 to 2011 and covers sale transactions for minerals, petroleum and gas, waste disposal sites, clay, sand and stone. Based on this analysis, the suitability of direct comparison for valuation purposes in this property sector will be tested.

Development of a bi-material representative volume element using damaged homogenisation approach

Most civil engineering structures are formed using a number of materials that are bonded to each other with their surface-to-surface interaction playing key role on the overall response of the structure. Unfortunately these interactions are extremely variable; simplified and extremely detailed models trialed to date prove quite complex. Models that assume perfect interaction, on the other hand, predict unsafe behavior. In this paper a damage mechanics based interaction between two materials of different softening properties is developed using homogenisation approach. This paper describes the process of developing a bi-material representative volume element (RVE) using damaged homogenisation approach. The novelty in this paper is the development of non-local transient damage identification algorithm. Numerical examples prove the stability of the approach for a simplified RVE and encourage application to other shapes of RVEs.

Monitoring and benchmarking population diet quality globally : a step-wise approach

INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support) aims to monitor and benchmark the healthiness of food environments globally. In order to assess the impact of food environments on population diets, it is necessary to monitor population diet quality between countries and over time. This paper reviews existing data sources suitable for monitoring population diet quality, and assesses their strengths and limitations. A step-wise framework is then proposed for monitoring population diet quality. Food balance sheets (FBaS), household budget and expenditure surveys (HBES) and food intake surveys are all suitable methods for assessing population diet quality. In the proposed ‘minimal’ approach, national trends of food and energy availability can be explored using FBaS. In the ‘expanded’ and ‘optimal’ approaches, the dietary share of ultra-processed products is measured as an indicator of energy-dense, nutrient-poor diets using HBES and food intake surveys, respectively. In addition, it is proposed that pre-defined diet quality indices are used to score diets, and some of those have been designed for application within all three monitoring approaches. However, in order to enhance the value of global efforts to monitor diet quality, data collection methods and diet quality indicators need further development work.

Quantitative proteomic approach to study subcellular localization of membrane proteins

As proteins within cells are spatially organized according to their role, knowledge about protein localization gives insight into protein function. Here, we describe the LOPIT technique (localization of organelle proteins by isotope tagging) developed for the simultaneous and confident determination of the steady-state distribution of hundreds of integral membrane proteins within organelles. The technique uses a partial membrane fractionation strategy in conjunction with quantitative proteomics. Localization of proteins is achieved by measuring their distribution pattern across the density gradient using amine-reactive isotope tagging and comparing these patterns with those of known organelle residents. LOPIT relies on the assumption that proteins belonging to the same organelle will co-fractionate. Multivariate statistical tools are then used to group proteins according to the similarities in their distributions, and hence localization without complete centrifugal separation is achieved. The protocol requires approximately 3 weeks to complete and can be applied in a high-throughput manner to material from many varied sources.

Measuring global economic interdependence : a hierarchical network approach

This paper investigates the business cycle co-movement across countries and regions since 1950 as a measure for quantifying the economic interdependence in the ongoing globalisation process. Our methodological approach is based on analysis of a correlation matrix and the networks it contains. Such an approach summarises the interaction and interdependence of all elements, and it represents a more accurate measure of the global interdependence involved in an economic system. Our results show (1) the dynamics of interdependence has been driven more by synchronisation in regional growth patterns than by the synchronisation of the world economy, and (2) world crisis periods dramatically increase the global co-movement in the world economy.

A data mining approach to improve the automated quality of data

This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.