Tax morale and conditional cooperation

Why so many people pay their taxes, even though fines and audit probability are low, is a central question in the tax compliance literature. Positing a homo oeconomicus having a refined motivation structure sheds light on this puzzle. This paper provides empirical evidence for the relevance of conditional cooperation, using survey data from 30 West and East European countries. We find a high correlation between perceived tax evasion and tax morale. The results remain robust after exploiting endogeneity and conducting several robustness tests. We also observe a strong positive correlation between institutional quality and tax mmorale. Keywords: Tax morale; Tax compliance; Tax evasion; Pro-social behavior; Institutions

Identify disorders in health records using Conditional Random Fields and Metamap: AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1

The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

An exploration of the role of web and mobile social media in the implementation of e-Government in Malaysia

This paper reports on an exploratory study of the role of web and social media in e-governments, especially in the context of Malaysia, with some comparisons and contrasts from other countries where such governmental efforts have been underway for awhile. It describes the current e-government efforts in Malaysia, and proposes that applying a theoretical framework would help understand the context and streamline these ongoing efforts. Specifically, it lays out a theoretical and cultural framework based on Mary Douglas’ (1996) Grid-Group Theory, Mircea Georgescu’s (2005) Three Pillars of E-Government, and Gerald Grant’s and Derek Chau’s (2006) Generic Framework for E-Government. Although this study is in its early stages, it has relevance to everyone who is interested in e-government efforts across the world, and especially relevant to developing countries.

Big-five personality factors affecting pedestrian crossing behaviours

Human personality is an important component of psychological factors affecting pedestrian crossing. This paper reports a questionnaire survey on the effects of pedestrian personalities (including neuroticism, extraversion, openness, agreeableness and conscientiousness) on pedestrian violation in China. 675 feedbacks were obtained, of which 535 samples were valid for analysis. The results of the hierarchical regression analysis showed that educational level had significant effect on violation; agreeableness had significant effect on violation, conditional compliance and unconditional compliance; consciousness had significant effect on violation and conditional compliance; extraversion had significant effect on unconditional compliance; neuroticism had significant effect on violation; educational level had significant effect on violation. The results implied that psychological measures played a very important role in pedestrian safety.

Changing relationships : engaging students and staff in the design studio

QUT Learning and Teaching Unit Seminar Making a Real Difference: Learning and Teaching Grants Showcase This event recognised and shared teaching innovations, including those from faculty learning and teaching grants. The Showcase featured four ALTC Grant project leaders (Helen Partridge, Sylvia Edwards, Robyn Nash and Mary Ryan) who had recently completed or were about to complete their grants. Each QUT faculty nominated two 2010 faculty teaching and learning grant recipients to showcase grant outcomes via a poster. Poster: Shannon Satherley & Abbe Winter Changing Relationships: Engaging Students and Staff in the Design Studio 'In the design studio learning environment, traditional student and staff expectations are of close contact teaching and learning. However, in recent years increasing class sizes have meant students experiencing reduced personal staff attention, and increasingly feeling “anonymous” and correspondingly disengaged, to the detriment of quality learning (Carbone 1998: 8; Biggs 2003). Concurrently, there has been a necessary increase in teaching by sessional (casual) teaching staff at QUT, with varied levels of experience and assurance. While teachers primarily regard engagement as “cognitive and conative,” for students it is emotional: “... an essential need to feel that they were engaged with the context of their learning and that it was meaningful in some way” (Solomonides and Martin 2008: 18). As a response to these conditions, the Changing Relationships action-research project was run within a QUT School of Design studio unit in 2009 and 2010, based on the premise that engaged teaching can encourage emotionally engaged learning. The project inverted the structure of the traditional QUT studio unit, empowering both students and sessional staff with a sense of increased autonomy: literally changing the relationships within the studio learning environment.'

Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

Background & aims The confounding effect of disease on the outcomes of malnutrition using diagnosis-related groups (DRG) has never been studied in a multidisciplinary setting. This study aims to determine the impact of malnutrition on hospitalisation outcomes, controlling for DRG. Methods Subjective Global Assessment was used to assess the nutritional status of 818 patients within 48 hours of admission. Prospective data were collected on cost of hospitalisation, length of stay (LOS), readmission and mortality up to 3 years post-discharged using National Death Register data. Mixed model analysis and conditional logistic regression matching by DRG were carried out to evaluate the association between nutritional status and outcomes, with the results adjusted for gender, age and race. Results Malnourished patients (29%) had longer hospital stays (6.9±7.3 days vs. 4.6±5.6 days, p<0.001) and were more likely to be readmitted within 15 days (adjusted relative risk = 1.9, 95%CI 1.1–3.2, p=0.025). Within a DRG, the mean difference between actual cost of hospitalisation and the average cost for malnourished patients was greater than well-nourished patients (p=0.014). Mortality was higher in malnourished patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5% vs. 9.9%); p<0.001 for all. Overall, malnutrition was a significant predictor of mortality (adjusted hazard ratio = 4.4, 95%CI 3.3-6.0, p<0.001). Conclusions Malnutrition was evident in up to one third of inpatients and led to poor hospitalisation outcomes, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed.

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Shared common variants in prostate cancer and blood lipids

Background Epidemiological and clinical studies suggest comorbidity between prostate cancer (PCA) and cardiovascular disease (CVD) risk factors. However, the relationship between these two phenotypes is still not well understood. Here we sought to identify shared genetic loci between PCA and CVD risk factors. Methods We applied a genetic epidemiology method based on conjunction false discovery rate (FDR) that combines summary statistics from different genome-wide association studies (GWAS), and allows identification of genetic overlap between two phenotypes. We evaluated summary statistics from large, multi-centre GWA studies of PCA (n = 50 000) and CVD risk factors (n = 200 000) [triglycerides (TG), low-density lipoprotein (LDL) cholesterol and high-density lipoprotein (HDL) cholesterol, systolic blood pressure, body mass index, waist-hip ratio and type 2 diabetes (T2D)]. Enrichment of single nucleotide polymorphisms (SNPs) associated with PCA and CVD risk factors was assessed with conditional quantile-quantile plots and the Anderson-Darling test. Moreover, we pinpointed shared loci using conjunction FDR. Results We found the strongest enrichment of P-values in PCA was conditional on LDL and conditional on TG. In contrast, we found only weak enrichment conditional on HDL or conditional on the other traits investigated. Conjunction FDR identified altogether 17 loci; 10 loci were associated with PCA and LDL, 3 loci were associated with PCA and TG and additionally 4 loci were associated with PCA, LDL and TG jointly (conjunction FDR < 0.01). For T2D, we detected one locus adjacent to HNF1B. Conclusions We found polygenic overlap between PCA predisposition and blood lipids, in particular LDL and TG, and identified 17 pleiotropic gene loci between PCA and LDL, and PCA and TG, respectively. These findings provide novel pathobiological insights and may have implications for trials using targeting lipid-lowering agents in a prevention or cancer setting.

Gendered perceptions of experiential value in using web-based retail channels

Purpose – This paper compares the experiential consumption values that motivate consumer choice to purchase online for both male and female purchasers and non-purchasers. Design/methodology/approach – Using the theory of consumption value the study examines gendered perceptions of the functional, social and conditional value of using a virtual consumption setting for purchasing. Data was collected through an online survey and analysed using multiple discriminant analysis to determine meaningful differences between male and female purchasers and non-purchasers. Findings – The findings show that male online purchasers are discriminated from female purchasers by social value and from male non-purchasers by conditional value. Female purchasers are discriminated from male purchasers by functional value and from female non-purchasers by social value. Female non-purchasers are discriminated from female purchasers by conditional value. Male non-purchasers are discriminated from male purchasers by functional and social value. Research limitations/implications – Limitations include using an Internet survey and an Australian sample which may impact the generalisability of the findings to a wider population of Internet users. Future research should involve replication of the study in a country more or less developed in terms of gender composition of internet users to extend the generalisability of the findings. Additionally, researchers should examine whether other dimensions of consumption value,such as social influence through on- and off-line communication networks, may influence consumer choice to purchase online. Practical implications – The study provides practical implications for marketers to leverage consumption values that influence male and female consumers’ choice to purchase online and then drive their behaviour online through integrated marketing campaigns that involve both on- and offline strategies. Originality/value – The research makes an original contribution to the consumer behaviour literature as to date, no research has been found that undertakes such a comprehensive gender-based comparison of the perceived value of using a virtual consumption setting for purchasing.

Forecasting time-varying value-at-risk

In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

The development of an on-line module for students on “Working in Inter-cultural Teams”

Since 2005 QUT through a number of large Teaching and Learning Grants has sponsored a range of teamwork learning initiatives to assist students to develop the teamwork skills demanded by industry. After a suite of six online team learning modules was developed, first year unit coordinators requested an additional module to address the challenges of working with the diverse range of social, cultural and personal values that students from different backgrounds bring to student teams. The Intercultural Teams module asks students to map themselves against a Cultural Orientations Framework so they can understand their own cultural beliefs. By learning about other cultural orientations and comparing and analysing their effects, team members can develop communication and team process management strategies to leverage their differences to realise effective and creative outcomes. The interactive session will demonstrate the elements of the Intercultural Teams module and ask participants to consider ways the module can be integrated into classroom learning to support the development of students’ intercultural competencies.

Strategic technology management : case study development in innovative building products

National and international competition demands that Australian organisations become more competent at making the strategic technological decisions that impact their future in the international business economy. A new subject unit, Management of Technology is now offered in the popular Master of Project Management and Master of Business Administration programs at the Queensland University of Technology. This cross-disciplinary subject provides students with a theoretical foundation and practical tools to improve the efficiency and competitiveness of technically-oriented organisations. Applied case studies—shown to be the most appropriate mode of learning for mature-age students—form an integral component of the teaching program. In the first offerings of this subject during 1995 and 1996, American case studies were used. QUT has now supported the development of Australian case study packages for technology management through its Teaching and Learning Grants Scheme. The first case developed—Inland Oil Refiners’ Microstill Project—was completed in early 1996. A newly developed case—Automated Door Opening System for Wheelchair Access—is currently being completed. This case (comprising case study documentation and video presentation) tracks a cross-disciplinary product development driven by legislative and community pressures. It also reinforces the importance of personal relationships in the technology and business development that has taken this young Brisbane-based company from its embryonic beginnings on the Queensland Cultural Centre in 1994 to a national and export-focussed organisation in 1997. This paper reviews the need to develop Australian case material in Management of Technology, discusses the case study documentation and supporting video developed, and application of the case study approach in this teaching initiative in QUT’s Master of Project Management and Master of Business Administration programs.

Colour by numbers in Excel 2007 : solving algebraic equations without algebra

This is an update of an earlier paper, and is written for Excel 2007. A series of Excel 2007 models is described. The more advanced versions allow solution of f(x)=0 by examining change of sign of function values. The function is graphed and change of sign easily detected by a change of colour. Relevant features of Excel 2007 used are Names, Scatter Chart and Conditional Formatting. Several sample Excel 2007 models are available for download, and the paper is intended to be used as a lesson plan for students having some familiarity with derivatives. For comparison and reference purposes, the paper also presents a brief outline of several common equation-solving strategies as an Appendix.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

Inclusion?

Whilst inclusive education is a relatively recent advance in our thinking about schooling and pedagogy, it is rapidly establishing movement simultaneously reflected in and refracted by education policy, research, and scholarship. This is manifest in the proliferation of policy texts and programmes generated by education jurisdictions globally and locally, and in the burgeoning number of scholarly texts, academic conferences, and research grants dedicated to inclusive education.