The expectation-performance gap in generic skills in accounting graduates : Evidence from Sri Lanka

Purpose
The purpose of this paper is to investigate the generic skills that are important for the career success of accounting graduates in Sri Lanka from the perspectives of university educators and employers.

Design/methodology/approach
Bui and Porter's (2010) expectation-performance gap framework was modified to match with the context of the current study. Data collected via questionnaire survey was analysed for non-parametric tests: the Wilcoxon signed-rank test and the Mann-Whitney test, using SPSS version 20, and quantified the expectation-performance gap and its components.

Findings
The major finding of this research is that the main cause for the expectation-performance gap, as identified in the analysis of the constraint gap is university educators’ low confidence in teaching the required generic skills for career success of graduates. However, university educators are aware of the employer expectations of graduate accountants in terms of generic skills. Employers indicated that many of the generic skills are not achieved by the accounting graduates.

Practical implications
Findings of this study reflect the importance of expanding the accounting curricula by embedding and assessing generic skill development activities. In addition, it is vital to develop the capacities of university educators in terms of teaching and assessing generic skills in accounting degree programmes.

Originality/value
This study contributes to the literature as one of few studies that investigate the generic skills development of accounting graduates in Asia, particularly in Sri Lanka.

Impact of policy changes on the efficiency and returns-to-scale of Japanese financial institutions: an evaluation

This paper examines the impact of FSA's (Financial Services Agency) recent policy changes on the efficiency and returns-to-scale (RTS) of Japanese financial institutions including banks, securities companies and bank holding companies. Three kinds of efficiency are investigated namely, technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) using the non-parametric methodology named data envelopment analysis (DEA). The DEA analysis shows a substantial improvement in the overall efficiency of Japanese banks, albeit a significant difference of efficiency scores between the major/city banks and the regional banks. Results are robust to alternative specifications of efficiency and scale changes.

Factorial multi-task learning : a Bayesian nonparametric approach

Multi-task learning is a paradigm shown to improve the performance of related tasks through their joint learning. However, for real-world data, it is usually difficult to assess the task relatedness and joint learning with unrelated tasks may lead to serious performance degradations. To this end, we propose a framework that groups the tasks based on their relatedness in a subspace and allows a varying degree of relatedness among tasks by sharing the subspace bases across the groups. This provides the flexibility of no sharing when two sets of tasks are unrelated and partial/total sharing when the tasks are related. Importantly, the number of task-groups and the subspace dimensionality are automatically inferred from the data. To realize our framework, we introduce a novel Bayesian nonparametric prior that extends the traditional hierarchical beta process prior using a Dirichlet process to permit potentially infinite number of child beta processes. We apply our model for multi-task regression and classification applications. Experimental results using several synthetic and real datasets show the superiority of our model to other recent multi-task learning methods. Copyright 2013 by the author(s).

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.

Hydrologic landscape regionalisation using deductive classification and random forests

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Concurrent momentum and contrarian strategies in the Australian stock market

We investigate the coexistence of momentum and contrarian strategies in the Australian equity market from 1992 to 2011. We show that contrarian strategies prevail in the short-term investment horizon while momentum strategies dominate in the intermediate- and long-term horizons. However, only short-term contrarian strategies significantly outperform the simple buy-and-hold strategy of investing in the market index over the same period. Further examination of these strategies shows that the Australian mining sector undermines the performance of momentum while enhancing performance of contrarian strategies. Lastly, using both parametric and non-parametric approaches, we show that these strategies’ returns are persistent anomalies and not completely explained by standard return-generating models.

How do postgraduate qualifications in medical education impact on health professionals?

Background and Purpose: The number of degree-awarding programmes in medical education is steadily increasing. Despite the popularity and extensive investment in these courses, there is little research into their impact. This study investigated the perceived impact of an internationally-renowned postgraduate programme in medical education on health professionals’ development as educators.

Methods: An online survey of the 2008–12 graduates from the Centre for Medical Education, University of Dundee was carried out. Their self-reported shifts in various educational competencies and scholarship activities were analysed using non-parametric statistics. Qualitative data were also collected and analysed to add depth to the quantitative findings.

Results: Of the 504 graduates who received the online questionnaire 224 responded. Participants reported that a qualification in medical education had significantly (p < 0.001) improved their professional educational practices and engagement in scholarly activities. Masters graduates reported greater impact compared to Certificate graduates on all items, including ability to facilitate curriculum reforms, and in assessment and feedback practices. Masters graduates also reported more engagement in scholarship activities, with significantly greater contributions to journals. These qualifications equally benefited all participants regardless of age. International graduates reported greater impact of the qualification than their UK counterparts.

Conclusion: A postgraduate medical education programme can significantly impact on the practices and behaviours of health professionals in education, improving self-efficacy and instilling an increased sense of belonging to the educational community.

The relationships between illness and treatment perceptions with adherence to diabetes self-care: A comparison between Arabic-speaking migrants and Caucasian English-speaking patients

Aims
To compare illness and treatment perceptions between Arabic-speaking immigrants and Caucasian English-speaking people with type 2 diabetes, and explore the relationships between these beliefs and adherence to self-care activities.
Methods

A cross-sectional study was conducted in healthcare settings with large Arabic populations in metropolitan and rural Victoria, Australia. Adherence to self-care activities, illness and treatment perceptions, and clinical data were recorded. Bivariate associations for continuous normally distributed variables were tested with Pearson's correlation. Non-parametric data were tested using Spearman's rank correlation coefficient.
Results

701 participants were recruited; 392 Arabic-speaking participants (ASPs) and 309 English-speaking participants (ESPs). There were significant relationships between participants’ illness and treatment perceptions and adherence to diabetes self-care activities. ASPs’ negative beliefs about diabetes were strongly and significantly correlated with poorer adherence to diet recommendations, exercise, blood glucose testing and foot care. ASPs were significantly less adherent to all aspects of diabetes self-care compared with ESPs: dietary behaviours (P = <0.01; 95% confidence interval (CI) = −1.17, −0.84), exercise and physical activity (P = <0.001, 95% CI −1.14, −0.61), blood glucose testing (P = <0.001) and foot-care (P = <0.001). 52.8% of ASPs were sceptical about prescribed diabetes treatment compared with only 11.2% of the ESPs. 88.3% of ASPs were non-adherent to prescribed medication, compared with 45.1% of ESPs.

Conclusions
Arabic-speaking migrants’ illness and treatment perceptions were significantly different from the English-speaking group. There is a pressing need to develop new innovative interventions that deliver much-needed improvements in adherence to self-care activities and key health outcomes.

Can the direct medical cost of chronic disease be transferred across different countries? Using cost-of-illness studies on type 2 diabetes, epilepsy and schizophrenia as examples

OBJECTIVES: To systematically review cost of illness studies for schizophrenia (SC), epilepsy (EP) and type 2 diabetes mellitus (T2DM) and explore the transferability of direct medical cost across countries.

METHODS: A comprehensive literature search was performed to yield studies that estimated direct medical costs. A generalized linear model (GLM) with gamma distribution and log link was utilized to explore the variation in costs that accounted by the included factors. Both parametric (Random-effects model) and non-parametric (Boot-strapping) meta-analyses were performed to pool the converted raw cost data (expressed as percentage of GDP/capita of the country where the study was conducted).

RESULTS: In total, 93 articles were included (40 studies were for T2DM, 34 studies for EP and 19 studies for SC). Significant variances were detected inter- and intra-disease classes for the direct medical costs. Multivariate analysis identified that GDP/capita (p<0.05) was a significant factor contributing to the large variance in the cost results. Bootstrapping meta-analysis generated more conservative estimations with slightly wider 95% confidence intervals (CI) than the parametric meta-analysis, yielding a mean (95%CI) of 16.43% (11.32, 21.54) for T2DM, 36.17% (22.34, 50.00) for SC and 10.49% (7.86, 13.41) for EP.

CONCLUSIONS: Converting the raw cost data into percentage of GDP/capita of individual country was demonstrated to be a feasible approach to transfer the direct medical cost across countries. The approach from our study to obtain an estimated direct cost value along with the size of specific disease population from each jurisdiction could be used for a quick check on the economic burden of particular disease for countries without such data.

Classification of 5-S epileptic EEG recordings using distribution entropy and sample entropy

Epilepsy is an electrophysiological disorder of the brain, the hallmark of which is recurrent and unprovoked seizures. Electroencephalogram (EEG) measures electrical activity of the brain that is commonly applied as a non-invasive technique for seizure detection. Although a vast number of publications have been published on intelligent algorithms to classify interictal and ictal EEG, it remains an open question whether they can be detected using short-length EEG recordings. In this study, we proposed three protocols to select 5 s EEG segment for classifying interictal and ictal EEG from normal. We used the publicly-accessible Bonn database, which consists of normal, interical, and ictal EEG signals with a length of 4097 sampling points (23.6 s) per record. In this study, we selected three segments of 868 points (5 s) length from each recordings and evaluated results for each of them separately. The well-studied irregularity measure-sample entropy (SampEn)-and a more recently proposed complexity measure-distribution entropy (DistEn)-were used as classification features. A total of 20 combinations of input parameters m and τ for the calculation of SampEn and DistEn were selected for compatibility. Results showed that SampEn was undefined for half of the used combinations of input parameters and indicated a large intra-class variance. Moreover, DistEn performed robustly for short-length EEG data indicating relative independence from input parameters and small intra-class fluctuations. In addition, it showed acceptable performance for all three classification problems (interictal EEG from normal, ictal EEG from normal, and ictal EEG from interictal) compared to SampEn, which showed better results only for distinguishing normal EEG from interictal and ictal. Both SampEn and DistEn showed good reproducibility and consistency, as evidenced by the independence of results on analysing protocol.

Ecology of urban malaria vectors in Niamey, Republic of Niger

BACKGROUND: Urbanization in African cities has major impact on malaria risk. Niamey, the capital of the Republic of Niger, is situated in the West African Sahel zone. The short rainy season and human activities linked with the Niger River influence mosquito abundance. This study aimed at deciphering the factors of distribution of urban malaria vectors in Niamey.

METHODS: The distribution of mosquito aquatic stages was investigated monthly from December 2002 to November 2003, at up to 84 breeding sites, throughout Niamey. An exploratory analysis of association between mosquito abundance and environmental factors was performed by a Principal Component Analysis and confirmed by Kruskall-Wallis non-parametric test. To assess the relative importance of significant factors, models were built for Anopheles and Culicinae. In a second capture session, adult mosquitoes were collected weekly with pyrethrum sprays and CDC light-traps from June 2008 to June 2009 in two differentiated urban areas chosen after the study's first step. Members of the Anopheles gambiae complex were genotyped and Anopheles females were tested for the presence of Plasmodium falciparum circumsporozoite antigens using ELISA.

RESULTS: In 2003, 29 % of 8420 mosquitoes collected as aquatic stages were Anopheles. They were significantly more likely to be found upstream, relatively close to the river and highly productive in ponds. These factors remained significant in regression and generalized linear models. The Culicinae were found significantly more likely close to the river, and in the main temporary affluent stream. In 2009, Anopheles specimens, including Anopheles gambiae s.l. (95 %), but also Anopheles funestus (0.6 %) accounted for 18 % of the adult mosquito fauna, with a large difference between the two sampled zones. Three members of the An. gambiae complex were found: Anopheles arabiensis, Anopheles coluzzii, and An. gambiae. Nineteen (1.3 %) out of 1467 females tested for P. falciparum antigen were found positive.

CONCLUSION: The study provides valuable update knowledge on malaria vector ecology and distribution in Niamey. The identification of spatial and environmental risk factors could pave the way to larval source management strategy and allow malaria vector control to focus on key zones for the benefit of the community.

Intensive care nurses' knowledge of enteral nutrition: a descriptive questionnaire

BACKGROUND: Nurses have an important role in the delivery and management of enteral nutrition in critically ill patients, to prevent iatrogenic malnutrition. It is not clear how nurses source enteral nutrition information. 

Construction industry performance measurement with carbon reduction

The research developed non-parametric approaches for measuring construction industry performance in sustainable development. The research results support the improvement of value added and the reduction of carbon emissions, which have positive environmental and economic implications in the Australian construction industry.