A new first-order decision-making model for the procurement of public sector infrastructure: Procedures and Testing

Given global demand for new infrastructure, governments face substantial challenges in funding new infrastructure and delivering Value for Money (VfM). As part of the background to this challenge, a critique is given of current practice in the selection of the approach to procure major public sector infrastructure in Australia and which is akin to the Multi-Attribute Utility Approach (MAUA). To contribute towards addressing the key weaknesses of MAUA, a new first-order procurement decision-making model is presented. The model addresses the make-or-buy decision (risk allocation); the bundling decision (property rights incentives), as well as the exchange relationship decision (relational to arms-length exchange) in its novel approach to articulating a procurement strategy designed to yield superior VfM across the whole life of the asset. The aim of this paper is report on the development of this decisionmaking model in terms of the procedural tasks to be followed and the method being used to test the model. The planned approach to testing the model uses a sample of 87 Australian major infrastructure projects in the sum of AUD32 billion and deploys a key proxy for VfM comprising expressions of interest, as an indicator of competition.

Internet usage trends in medical informatics

Technological growth in the 21st century is exponential. Simultaneously, development of the associated risk, uncertainty and user acceptance are scattered. This required appropriate study to establish people accepting controversial technology (PACT). The Internet and services around it, such as World Wide Web, e-mail, instant messaging and social networking are increasingly becoming important in many aspects of our lives. Information related to medical and personal health sharing using the Internet is controversial and demand validity, usability and acceptance. Whilst literature suggest, Internet enhances patients and physicians’ positive interactions some studies establish opposite of such interaction in particular the associated risk. In recent years Internet has attracted considerable attention as a means to improve health and health care delivery. However, it is not clear how widespread the use of Internet for health care really is or what impact it has on health care utilisation. Estimated impact of Internet usage varies widely from the locations locally and globally. As a result, an estimate (or predication) of Internet use and their effects in Medical Informatics related decision-making is impractical. This open up research issues on validating and accepting Internet usage when designing and developing appropriate policy and processes activities for Medical Informatics, Health Informatics and/or e-Health related protocols. Access and/or availability of data on Internet usage for Medical Informatics related activities are unfeasible. This paper presents a trend analysis of the growth of Internet usage in medical informatics related activities. In order to perform the analysis, data was extracted from ERA (Excellence Research in Australia) ranked “A” and “A*” Journal publications and reports from the authenticated public domain. The study is limited to the analyses of Internet usage trends in United States, Italy, France and Japan. Projected trends and their influence to the field of medical informatics is reviewed and discussed. The study clearly indicates a trend of patients becoming active consumers of health information rather than passive recipients.

Higher order thinking in chemistry curriculum and its assessment

Higher-order thinking has featured persistently in the reform agenda for science education. The intended curriculum in various countries sets out aspirational statements for the levels of higher-order thinking to be attained by students. This study reports the extent to which chemistry examinations from four Australian states align and facilitate the intended higher-order thinking skills stipulated in curriculum documents. Through content analysis, the curriculum goals were identified for each state and compared to the nature of question items in the corresponding examinations. Categories of higher-order thinking were adapted from the OECD’s PISA Science test to analyze question items. There was considerable variation in the extent to which the examinations from the states supported the curriculum intent of developing and assessing higher-order thinking. Generally, examinations that used a marks-based system tended to emphasize lower-order thinking, with a greater distribution of marks allocated for lower-order thinking questions. Examinations associated with a criterion-referenced examination tended to award greater credit for higher-order thinking questions. The level of complexity of chemistry was another factor that limited the extent to which examination questions supported higher-order thinking. Implications from these findings are drawn for the authorities responsible for designing curriculum and assessment procedures and for teachers.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

Regulating bereavement : inquests, family pressure and the gate keeping of suicide statistics

This study of English Coronial practice raises a number of questions, not only regarding state investigations of suicide, but also of the role of the Coroner itself. Following observations at over 20 inquests into possible suicides, and in-depth interviews with six Coroners, three main issue emerged: first, there exists considerable slippage between different Coroners over which deaths are likely to be classified as suicide; second, the high standard of proof required, and immense pressure faced by Coroners from family members at inquest to reach any verdict other than suicide, can significantly depress likely suicide rates; and finally, Coroners feel no professional obligation, either individually or collectively, to contribute to the production of consistent and useful social data regarding suicide—arguably rendering comparative suicide statistics relatively worthless. These issues lead, ultimately, to a more important question about the role we expect Coroners to play within social governance, and within an effective, contemporary democracy.

Pseudo-marginal algorithms with multiple CPUs

The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

An investigation of factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam

Background: In diabetes care, health care professionals need to provide support for their patients. In order to provide good diabetes self-management support for adults with type 2 diabetes in Vietnam, it is important that health care professionals in Vietnam understand the factors influencing diabetes self-management among these people. However, knowledge about factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam is limited. Objectives: This study aimed to investigate factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam. Methodology: A cross-sectional survey with convenience sampling was conducted on 198 adults with type 2 diabetes in VietnamData collection was administeted via interview. Descriptive statistics, simple correlation statistics and structural equation modelling statistics were used for data analysis. Results: Adults with type 2 diabetes in Vietnam had limited diabetes knowledge (Median = 6.0). The majority of the study participants (72.7%) believed that performing diabetes self-management activities was very important or extremely important for controlling their blood glucose levels and for preventing complications from diabetes; about half usually received support from their family and friends’ (48.5%), and around two thirds rarely received support from their health care providers (68.2%). Many of the participants (41.4%) had limited confidence to perform diabetes management activities. The practices of diabetes self-management were limited among the study population (Mean = 96.7, SD = 19.4). Diabetes knowledge (β = 0.17, p < .001), belief in treatment effectiveness (β = 0.13, p < .01), family and friends’ support (β = 0.13, p < .001), health care providers’ support (β = 0.27, p < .001) and diabetes management self-efficacy (β = 0.43, p < .001) directly influenced their diabetes self-management. Diabetes knowledge, and family and friends’ support also indirectly influenced diabetes self-management among these people through their belief in treatment effectiveness and their diabetes management self-efficacy (p < .05). Conclusion: Findings in this study indicated that health care professionals should provide diabetes self-management support for adults with type 2 diabetes in Vietnam in the future. The adapted theory-based model of factors influencing diabetes self-management among adults with type 2 diabetes in Vietnam found in this study could be a useful framework to develop this supporting program.

Projecting the trend in the Canadian gender wage gap 2001-2031: Will an increase in female education acquisition and commitment be enough?

The paper projects the gender wage gap for 25-64 year-olds in Canada over the period 2001-2031. The empirical analysis uses the Survey of Labour and Income Dynamics together with Statistics Canada demographic projections. The methodology combines the population projections with assumptions relating to the evolution of educational attainment in order to first project the future distribution of human capital skills and, based on these projections, the future size of the gender wage gap. The projections suggest continued gender wage convergence produced by changing skills characteristics. However, a substantial pay gap will remain in 2031.

The gender wage gap in Australia - The path of future convergence

The paper attempts to project the future trend of the gender wage gap in Australia up to 2031. The empirical analysis utilises the Income Distribution Survey (1996) together with Australian Bureau of Statistics (ABS) demographic projections. The methodology combines the ABS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. The analysis suggests that female relative pay will continue to rise up to 2031. However, gender wage convergence will be relatively slow, with a substantial gap remaining in 2031.

Projections of the future path of the gender wage gap in Great Britain

Purpose – The paper attempts to project the future trend of the gender wage gap in Great Britain up to 2031. Design/methodology/approach – The empirical analysis utilises the British Household Panel Study Wave F together with Office for National Statistics (ONS) demographic projections. The methodology combines the ONS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. Findings – The analysis suggests that gender wage convergence will be slow, with little female progress by 2031 unless there is a large rise in returns to female experience. Originality/value – The paper has projected the pattern of male and female skill acquisition together with the associated trend in wages up to 2031.

Identifying important success factors in new venture creation

This paper seeks to uncover the factors that lead to a successful entrepreneurial experience and or venture. Findings of interest in this paper include: • A venture’s initial aspirations are a double edged sword. Ambition may lead to improved performance by striving to reach harder goals. Harder goals are more difficult therefore this may lead to some dissatisfaction, and possibly abandonment of the venture. • Venture legitimacy is important to establish where possible. Firms that formalize their legal form are more successful, as are those set up a shop-front in order to makes sales. • Increased use of technology and higher levels of novelty does not guarantee success early on. Firms of this nature have longer processes, and attempting to create brand new markets is difficult to achieve. At the same time developing your own technology and securing this intellectual property is important for success. • Having goals to work towards and business planning may be useful, but only if the plan is actively revised. Just having a business plan does not matter. Business plans are more useful as a thinking tool than as a blueprint for action. It is the process of thinking through while reviewing the plan that provides the benefit, not following its instruction to the letter.

Professional development and technology in second language learning : do best practices work?

This study was undertaken to examine the influence that a set of Professional Development (PD) initiatives had on faculty use of Moodle, a well known Course Management System. The context of the study was a private language university just outside Tokyo, Japan. Specifically, it aimed to identify the way in which the PD initiatives adhered to professional development best practice criteria; how faculty members perceived the PD initiatives; what impact the PD initiatives had on faculty use of Moodle; and other variables that may have influenced faculty in their use of Moodle. The study utilised a mixed methods approach. Participants in the study were 42 teachers who worked at the university in the academic year 2008/9. The online survey consisted of 115 items, factored into 10 constructs. Data was collected through an online survey, semi-structured face-to-face interviews, post-workshop surveys, and a collection of textual artefacts. The quantitative data were analysed in SPSS, using descriptive statistics, Spearman's Rank Order correlation tests and a Kruskal-Wallis means test. The qualitative data was used to develop and expand findings and ideas. The results indicated that the PD initiatives adhered closely to criteria posited in technology-related professional development best practice criteria. Further, results from the online survey, post workshop surveys, and follow up face-to-face interviews indicated that while the PD initiatives that were implemented were positively perceived by faculty, they did not have the anticipated impact on Moodle use among faculty. Further results indicated that other variables, such as perceptions of Moodle, and institutional issues, had a considerable influence on Moodle use. The findings of the study further strengthened the idea that the five variables Everett Rogers lists in his Diffusion of Innovations model, including perceived attributes of an innovation; type of innovation decision; communication channels; nature of the social system; extent of change agents' promotion efforts, most influence the adoption of an innovation. However, the results also indicated that some of the variables in Rogers' DOI seem to have more of an influence than others, particularly the perceived attributes of an innovation variable. In addition, the findings of the study could serve to inform universities that have Course Management Systems (CMS), such as Moodle, about how to utilise them most efficiently and effectively. The findings could also help to inform universities about how to help faculty members acquire the skills necessary to incorporate CMSs into curricula and teaching practice. A limitation of this study was the use of a non-randomised sample, which could appear to have limited the generalisations of the findings to this particular Japanese context.

Postnatal depression in Central Vietnam

Postnatal depression (PND) is a significant global health issue, which not only impacts maternal wellbeing, but also infant development and family structures. Mental health disorders represent approximately 14% of global burden of disease and disability, including low and middle-income countries (LMIC), and PND has direct relevance to the Millennium Development Goals of reducing child mortality, improving maternal health, and creating global partnerships (United Nations, 2012; Guiseppe, Becker & Farmer, 2011). Emerging evidence suggests that PND in LMIC is similar to, or higher than in high-income countries (HIC), however, less than 10% of LMIC have prevalence data available (Fisher, Cabral de Mello, & Izutsu 2009; Lund et al., 2011). Whilst a small number of studies on maternal mental disorders have been published in Vietnam, only one specifically focuses on PND in a hospital-based sample. Also, community based mental health studies and information on mental health in rural areas of Vietnam is still scarce. The purpose of this study was to determine the prevalence of PND, and its associated social determinants in postnatal women in Thua Thien Hue Province, Central Vietnam. In order to identify social determinants relevant to the Central Vietnamese context, two qualitative studies and one community survey were undertaken. Associations between maternal mental health and infant health outcomes were also explored. The study was comprised of three phases. Firstly, iterative, qualitative interviews with Vietnamese health professionals (n = 17) and postpartum women (n = 15) were conducted and analysed using Kleinman's theory of explanatory models to identify narratives surrounding PND in the Vietnamese context (Kleinman, 1978). Secondly, a participatory concept mapping exercise was undertaken with two groups of health professionals (n = 12) to explore perceived risk and protective factors for postnatal mental health. Qualitative phases of the research elucidated narratives surrounding maternal mental health in the Vietnamese context such as son preference, use of traditional medicines, and the popularity of confinement practices such as having one to three months of complete rest. The qualitative research also revealed the construct of depression was not widely recognised. Rather, postpartum changes in mood were conceptualised as a loss of 'vital strength' following childbirth or 'disappointment'. Most women managed postpartum changes in mood within the family although some sought help from traditional medicine practitioners or biomedical doctors. Thirdly, a cross-sectional study of twelve randomly selected communes (six urban, six rural) in Thua Thien Hue Province was then conducted. Overall, 465 women with infants between 4 weeks and six months old participated, and 431 questionnaires were analysed. Women from urban (n = 216) and rural (n = 215) areas participated. All eligible women completed a structured interview about their health, basic demographics, and social circumstances. Maternal depression was measured using the Edinburgh Postnatal Depression Scale (EPDS) as a continuous variable. Multivariate generalised linear regression was conducted using PASW Statistics version 18.0 (2009). When using the conventional EPDS threshold for probable depression (EPDS score ~ 13) 18.1% (n = 78) of women were depressed (Gibson, McKenzie-McHarg, Shakespeare, Price & Gray, 2009). Interestingly, 20.4% of urban women (n = 44) had EPDS scores~ 13, which was a higher proportion than rural women, where 15.8% (n = 34) had EPDS scores ~ 13, although this difference was not statistically significant: t(429) = -0.689, p = 0.491. Whilst qualitative narratives identified infant gender and family composition, and traditional confinement practices as relevant to postnatal mood, these were not statistically significant in multivariate analysis. Rather, poverty, food security, being frightened of your husband or family members, experiences of intimate partner violence and breastfeeding difficulties had strong statistical associations. PND was also associated with having an infant with diarrhoea in the past two weeks, but not infant malnutrition or acute respiratory infections. This study is the first to explore maternal mental health in Central Vietnam, and provides further evidence that PND is a universally experienced phenomenon. The independent social risk factors of depressive symptoms identified such as poverty, food insecurity, experiences of violence and powerlessness, and relationship adversity points to women in a context of social suffering which is relevant throughout the world (Kleinman, Das & Lock, 1997). The culturally specific risk factors explored such as infant gender were not statistically significant when included in a multivariable model. However, they feature prominently in qualitative narratives surrounding PND in Vietnam, both in this study and previous literature. It appears that whilst infant gender may not be associated with PND per se, the reactions of close relatives to the gender of the baby can adversely affect maternal wellbeing. This study used a community based participatory research approach (CBPR) (Israel.2005). This approach encourages the knowledge produced to be used for public health interventions and workforce training in the community in which the research was conducted, and such work has commenced. These results suggest that packages of interventions for LMIC devised to address maternal mental health and infant wellbeing could be applied in Central Vietnam. Such interventions could include training lay workers to follow up postpartum women, and incorporating mental health screening and referral into primary maternal and child health care (Pate! et al., 2011; Rahman, Malik, Sikander & Roberts, 2008). Addressing the underlying social determinants of PND through poverty reduction and violence elimination programs is also recommended.

Spatio-temporal modelling of ultrafine particle number concentration

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

Building an augmented map for road risk assessment

Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.