Semantics-based web service discovery using information retrieval techniques

This paper demonstrates an experimental study that examines the accuracy of various information retrieval techniques for Web service discovery. The main goal of this research is to evaluate algorithms for semantic web service discovery. The evaluation is comprehensively benchmarked using more than 1,700 real-world WSDL documents from INEX 2010 Web Service Discovery Track dataset. For automatic search, we successfully use Latent Semantic Analysis and BM25 to perform Web service discovery. Moreover, we provide linking analysis which automatically links possible atomic Web services to meet the complex requirements of users. Our fusion engine recommends a final result to users. Our experiments show that linking analysis can improve the overall performance of Web service discovery. We also find that keyword-based search can quickly return results but it has limitation of understanding users’ goals.

The economics of happiness : a lifetime perspective

The three studies in this thesis focus on happiness and age and seek to contribute to our understanding of happiness change over the lifetime. The first study contributes by offering an explanation for what was evolving to a ‘stylised fact’ in the economics literature, the U-shape of happiness in age. No U-shape is evident if one makes a visual inspection of the age happiness relationship in the German socio-economic panel data, and, it seems counter-intuitive that we just have to wait until we get old to be happy. Eliminating the very young, the very old, and the first timers from the analysis did not explain away regression results supporting the U-shape of happiness in age, but fixed effect analysis did. Analysis revealed found that reverse causality arising from time-invariant individual traits explained the U-shape of happiness in age in the German population, and the results were robust across six econometric methods. Robustness was added to the German fixed effect finding by replicating it with the Australian and the British socio-economic panel data sets. During analysis of the German data an unexpected finding emerged, an exceedingly large negative linear effect of age on happiness in fixed-effect regressions. There is a large self-reported happiness decline by those who remain in the German panel. A similar decline over time was not evident in the Australian or the British data. After testing away age, time and cohort effects, a time-in-panel effect was found. Germans who remain in the panel for longer progressively report lower levels of happiness. Because time-in-panel effects have not been included in happiness regression specifications, our estimates may be biased; perhaps some economics of the happiness studies, that used German panel data, need revisiting. The second study builds upon the fixed-effect finding of the first study and extends our view of lifetime happiness to a cohort little visited by economists, children. Initial analysis extends our view of lifetime happiness beyond adulthood and revealed a happiness decline in adolescent (15 to 23 year-old) Australians that is twice the size of the happiness decline we see in older Australians (75 to 86 yearolds), who we expect to be unhappy due to declining income, failing health and the onset of death. To resolve a difference of opinion in the literature as to whether childhood happiness decreases, increases, or remains flat in age; survey instruments and an Internet-based survey were developed and used to collect data from four hundred 9 to 14 year-old Australian children. Applying the data to a Model of Childhood Happiness revealed that the natural environment life-satisfaction domain factor did not have a significant effect on childhood happiness. However, the children’s school environment and interactions with friends life-satisfaction domain factors explained over half a steep decline in childhood happiness that is three times larger than what we see in older Australians. Adding personality to the model revealed what we expect to see with adults, extraverted children are happier, but unexpectedly, so are conscientious children. With the steep decline in the happiness of young Australians revealed and explanations offered, the third study builds on the time-invariant individual trait finding from the first study by applying the Australian panel data to an Aggregate Model of Average Happiness over the lifetime. The model’s independent variable is the stress that arises from the interaction between personality and the life event shocks that affect individuals and peers throughout their lives. Interestingly, a graphic depiction of the stress in age relationship reveals an inverse U-shape; an inverse U-shape that looks like the opposite of the U-shape of happiness in age we saw in the first study. The stress arising from life event shocks is found to explain much of the change in average happiness over a lifetime. With the policy recommendations of economists potentially invoking unexpected changes in our lives, the ensuing stress and resulting (un)happiness warrant consideration before economists make policy recommendations.

Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

A proposed validation framework for expert elicited Bayesian Networks

The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.

Creating new possibilities : using design processes to overcome constraints

This paper describes how a team from a large company, when faced with a challenge to develop new customers in fast growing international markets, carried out the exploration of the needs of new clients in the largely unexplored market space of a developing country. This team used design methods and processes to identify the latent needs of new customers in situations of major economic, geographical, cultural and financial constraints. This encapsulation of the life experiences of potential customers is used extensively in some new product development, but is largely novel to business practices and in processes of developing new services. This research links with the sub-theme of discovering creativity in necessity and highlights the potential benefits of design methodologies to create new possibilities for better accessibility of the company’s products to new clients, with future implications for organizational strategy. The overall theme of Design for the Colloquium encourages exploration of the ways and means of developing new ideas for new business with better outcomes, using design concepts and design technologies.

An evolving perspective on physical activity counselling by medical professionals

Background Physical inactivity is a modifiable risk factor for many chronic conditions and a leading cause of premature mortality. An increasing proportion of adults worldwide are not engaging in a level of physical activity sufficient to prevent or alleviate these adverse effects. Medical professionals have been identified as potentially powerful sources of influence for those who do not meet minimum physical activity guidelines. Health professionals are respected and expected sources of advice and they reach a large and relevant proportion of the population. Despite this potential, health professionals are not routinely practicing physical activity promotion. Discussion Medical professionals experience several known barriers to physical activity promotion including lack of time and lack of perceived efficacy in changing physical activity behaviour in patients. Furthermore, evidence for effective physical activity promotion by medical professionals is inconclusive. To address these problems, new approaches to physical activity promotion are being proposed. These include collaborating with community based physical activity behaviour change interventions, preparing patients for effective brief counselling during a consultation with the medical professional, and use of interactive behaviour change technology. Summary It is important that we recognise the latent risk of physical inactivity among patients presenting in clinical settings. Preparation for improving patient physical activity behaviours should commence before the consultation and may include physical activity screening. Medical professionals should also identify suitable community interventions to which they can refer physically inactive patients. Outsourcing the majority of a comprehensive physical activity intervention to community based interventions will reduce the required clinical consultation time for addressing the issue with each patient. Priorities for future research include investigating ways to promote successful referrals and subsequent engagement in comprehensive community support programs to increase physical activity levels of inactive patients. Additionally, future clinical trials of physical activity interventions should be evaluated in the context of a broader framework of outcomes to inform a systematic consideration of broad strengths and weaknesses regarding not only efficacy but cost-effectiveness and likelihood of successful translation of interventions to clinical contexts.

The mystery of the U-shaped relationship between happiness and age

In this paper, we address the puzzle of the relationship between age and happiness. Whilst the majority of psychologists have concluded there is not much of a relationship at all, the economic literature has unearthed a possible U-shape relationship with the minimum level of satisfaction occurring in middle age (35–50). In this paper, we look for a U-shape in three panel data sets, the German Socioeconomic Panel (GSOEP), the British Household Panel Survey (BHPS) and the Household Income Labour Dynamics Australia (HILDA). We find that the raw data mainly supports a wave-like shape that only weakly looks U-shaped for the 20–60 age range. That weak U-shape in middle age becomes more pronounced when allowing for socio-economic variables. When we then take account of selection effects via fixed-effects, however, the dominant age-effect in all three panels is a strong happiness increase around the age of 60 followed by a major decline after 75, with the U-shape in middle age disappearing such that there is almost no change in happiness between the age of 20 and 50.

Behavioural beliefs concerning gender and high-risk sexual behaviours in the context of HIV/AIDS in PNG : views from within teacher education

Education is often viewed as a key approach to address sexual-health issues; the current concern is the burgeoning HIV/AIDS epidemic. This ethnographic study investigates the gender practices associated with high-risk sexual behaviour in Papua New Guinea as viewed by educators there. A number of practices, including gender inequality and associated sexual behaviours have been highlighted by male and female participants as escalating PNG’s HIV/AIDS epidemic. The study finds that although participants were well-informed concerning HIV/AIDS, they had varying beliefs concerning the prevailing gender/sexual issues involved in escalating highrisk behaviour and how to address the problem. The study further examines the behavioural beliefs and intentions of the educators themselves. Subsequently, within the data a number of underpinning factors, pertaining to gender, education and life experience, were found to be related to the behaviour beliefs and intentions of participants towards embracing change with regard to behaviours associated with gender equality in PNG. These factors appeared to encourage participants to adopt healthier gender and sexual behavioural intentions and, arguably, could provide the basis for ways to help address the gender inequality and high-risk behaviours associated with HIV/AIDS in PNG.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

A qualitative approach to assessing the validity of the posttraumatic growth inventory

The Posttraumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996) is the most commonly used measure of positive psychological change that can result from negotiating a traumatic experience. Whilst the PTGI has strong internal reliability, validity studies are still sparse. The presented research details trauma survivors’ understanding of items comprising the PTGI in order to qualitatively assess content validity. Participants were 14 trauma survivors who completed the PTGI and participated in a semi-structured interview. Thematic Analysis was conducted on participant’s transcribed interviews. One latent theme was identified reflecting that questions were consistently understood. A relationship was found between the constituent themes identified and the five factors of the PTGI. Participants answered the PTGI statements in a way that is consistent with the purpose of the instrument with only a small discrepancy found when some participants used the PTGI scale to indicate when a decrease in an element of the inventory had been experienced. Overall results supported the content validity of the PTGI.

Termites did not undermine sale

The New South Wales Court of Appeal decision of Wood v Balfour [2011] NSWCA 382 presents an interesting factual matrix relating to the obligation of a seller to disclose significant latent defects in quality of title to a buyer, in this instance, severe termite damage. It offers insights into the difficulty of a buyer proving the existence of the element of deceit in the making of a representation with respect to quality and reinforces the importance of the rule caveat emptor as being an article of faith for every buyer of real estate.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Preparation and thermal energy storage properties of paraffin/calcined diatomite composites as form-stable phase change materials

A composite paraffin-based phase change material (PCM) was prepared by blending composite paraffin and calcined diatomite through the fusion adsorption method. In this study, raw diatomite was purified by thermal treatment in order to improve the adsorption capacity of diatomite, which acted as a carrier material to prepare shape-stabilized PCMs. Two forms of paraffin (paraffin waxes and liquid paraffin) with different melting points were blended together by the fusion method, and the optimum mixed proportion with a suitable phase-transition temperature was obtained through differential scanning calorimetry (DSC) analysis. Then the prepared composite paraffin was adsorbed in calcined diatomite. The prepared paraffin/calcined diatomite composites were characterized by the scanning electron microscope (SEM) and Fourier transformation infrared (FT-IR) analysis techniques. Thermal energy storage properties of the composite PCMs were determined by DSC method. DSC results showed that there was an optimum adsorption ratio between composite paraffin and calcined diatomite and the phase-transition temperature and the latent heat of the composite PCMs were 33.04 ◦C and 89.54 J/g, respectively. Thermal cycling test of composite PCMs showed that the prepared material is thermally reliable and chemically stable. The obtained paraffin/calcined diatomite composites have proper latent heat and melting temperatures, and show practical significance and good potential application value.