An investigation on multi-vehicle motorcycle crashes using log-linear models

Motorcyclists are the most crash-prone road-user group in many Asian countries including Singapore; however, factors influencing motorcycle crashes are still not well understood. This study examines the effects of various roadway characteristics, traffic control measures and environmental factors on motorcycle crashes at different location types including expressways and intersections. Using techniques of categorical data analysis, this study has developed a set of log-linear models to investigate multi-vehicle motorcycle crashes in Singapore. Motorcycle crash risks in different circumstances have been calculated after controlling for the exposure estimated by the induced exposure technique. Results show that night-time influence increases crash risks of motorcycles particularly during merging and diverging manoeuvres on expressways, and turning manoeuvres at intersections. Riders appear to exercise more care while riding on wet road surfaces particularly during night. Many hazardous interactions at intersections tend to be related to the failure of drivers to notice a motorcycle as well as to judge correctly the speed/distance of an oncoming motorcycle. Road side conflicts due to stopping/waiting vehicles and interactions with opposing traffic on undivided roads have been found to be as detrimental factors on motorcycle safety along arterial, main and local roads away from intersections. Based on the findings of this study, several targeted countermeasures in the form of legislations, rider training, and safety awareness programmes have been recommended.

R&D investment in green building initiatives in Western Australia

This paper reports on a current case study of green building initiatives implemented by the Western Australian government in the past decade. The intent is to provide a qualitative understanding of past R&D investments in the Australian built environment. The case method was selected to illustrate three sector-based investments, one of which is reported on here. The conceptual framework underpinning interview design and data analysis uses dynamic capability, absorptive capacity and open innovation theories to better understand the organisational environment in which these initiatives were implemented. Data has been thematically coded to criteria identified from the literature to illustrate organisational characteristics which may have contributed to dissemination and impact. The results will be combined with two further case studies (construction safety and digital modelling), to inform this research. This industry supported project will conclude by developing policy guidelines for future R&D investment in the built environment.

A multilevel investigation of inequalities in clinical and psychosocial outcomes for women after breast cancer

Background In Australia, breast cancer is the most common cancer affecting Australian women. Inequalities in clinical and psychosocial outcomes have existed for some time, affecting particularly women from rural areas and from areas of disadvantage. We have a limited understanding of how individual and area-level factors are related to each other, and their associations with survival and other clinical and psychosocial outcomes. Methods/Design This study will examine associations between breast cancer recurrence, survival and psychosocial outcomes (e.g. distress, unmet supportive care needs, quality of life). The study will use an innovative multilevel approach using area-level factors simultaneously with detailed individual-level factors to assess the relative importance of remoteness, socioeconomic and demographic factors, diagnostic and treatment pathways and processes, and supportive care utilization to clinical and psychosocial outcomes. The study will use telephone and self-administered questionnaires to collect individual-level data from approximately 3, 300 women ascertained from the Queensland Cancer Registry diagnosed with invasive breast cancer residing in 478 Statistical Local Areas Queensland in 2011 and 2012. Area-level data will be sourced from the Australian Bureau of Statistics census data. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to diagnostic and treatment centres. Data analysis will include a combination of standard empirical procedures and multilevel modelling. Discussion The study will address the critical question of: what are the individual- or area-level factors associated with inequalities in outcomes from breast cancer? The findings will provide health care providers and policy makers with targeted information to improve the management of women with breast cancer, and inform the development of strategies to improve psychosocial care for women with breast cancer.

Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

Critical sustainability factors in industrialised building systems

Purpose – This paper presents findings of a research study aimed at identifying critical sustainability factors for improved implementation of Industrialised Building Systems (IBS). It also highlights the importance of decision support, through the establishment of decision making guidelines, for sustainability deliverables in IBS development. Design/methodology/approach – A broad range of sustainability factors, as perceived by researchers and practitioners, are identified through a comprehensive literature study. A study of the survey and statistical data analysis is conducted to examine the criticality of these sustainability factors in IBS implementation. Findings – 18 sustainability factors are identified as critical to IBS implementation. Their interrelationships and driving forces are explored, which leads to the development of a conceptual model to map these factors for actions or potential solutions. The work provides a sound basis towards a set of decision making guidelines for sustainable IBS implementation. Originality/value – Compared with previous studies that focus on technical or economical aspects, this study extends existing knowledge on construction prefabrication by linking all aspects of sustainability issues with the design process. It also covers industry characteristics of developing countries, as represented by Malaysia’s scenarios.

Exploring information experiences through phenomenography

Phenomenography is a qualitative research approach that seeks to explore variation in how people experience various aspects of their world. Phenomenography has been used in numerous information research studies that have explored various phenomena of interest in the library and information sphere. This paper provides an overview of the phenomenographic method and discusses key assumptions that underlie this approach to research. Aspects including data collection, data analysis and the outcomes of phenomenographic research are also detailed. The paper concludes with an illustration of how phenomenography was used in research to investigate students’ experiences of web-based information searching. The results of this research demonstrate how phenomenography can reveal variation, making it possible to develop greater understanding of the phenomenon as it was experienced, and to draw upon these experiences to improve and enhance current practice.

An expanded critical incident approach for exploring information use and learning

Critical incidents offer a focus for exploratory research about human experiences, including information use and information literacy learning. This paper describes how critical incidents underpinned research about international students’ use of online information resources at two Australian universities. It outlines the development and application of an expanded critical incident approach (ECIA), explaining how ECIA built upon critical incident technique (CIT) and incorporated information literacy theory. It discusses points of expansion (differences) between CIT and ECIA. While CIT initially proved useful in structuring the research, the pilot study revealed methodological limitations. ECIA allowed more nuanced data analysis and the integration of reflection. The study produced a multifaceted word picture of international students’ experience of using online information resources to learn, and a set of critical findings about their information literacy learning needs. ECIA offers a fresh approach for researching information use, information experience, evidence-based practice, information literacy and informed learning.

Quantile regression without the curse of unsmoothness

We consider quantile regression models and investigate the induced smoothing method for obtaining the covariance matrix of the regression parameter estimates. We show that the difference between the smoothed and unsmoothed estimating functions in quantile regression is negligible. The detailed and simple computational algorithms for calculating the asymptotic covariance are provided. Intensive simulation studies indicate that the proposed method performs very well. We also illustrate the algorithm by analyzing the rainfall–runoff data from Murray Upland, Australia.

Observational research and verbal protocol methods

This paper describes observational research and verbal protocols methods, how these methods are applied and integrated within different contexts, and how they complement each other. The first case study focuses on nurses’ interaction during bandaging of patients’ lower legs. To maintain research rigor a triangulation approach was applied that links observations of current procedures, ‘talk-aloud’ protocol during interaction and retrospective protocol. Maps of interactions demonstrated that some nurses bandage more intuitively than others. Nurses who bandage intuitively assemble long sequences of bandaging actions while nurses who bandage less intuitively ‘focus-shift’ in between bandaging actions. Thus different levels of expertise have been identified. The second case study consists of two laboratory experiments. It focuses on analysing and comparing software and product design teams and how they approached a design problem. It is based on the observational and verbal data analysis. The coding scheme applied evolved during the analysis of the activity of each team and is identical for all teams. The structure of knowledge captured from the analysis of the design team maps of interaction is identified. The significance of this work is within its methodological approach. The maps of interaction are instrumental for understanding the activities and interactions of the people observed. By examining the maps of interaction, it is possible to draw conclusions about interactions, structure of knowledge captured and level of expertise. This research approach is transferable to other design domains. Designers will be able to transfer the interaction maps outcomes to systems and services they design.

Teaching Teachers for the Future (TTF) project TPACK Survey : summary of the key findings

This paper presents a summary of the key findings of the TTF TPACK Survey developed and administered for the Teaching the Teachers for the Future (TTF) Project implemented in 2011. The TTF Project, funded by an Australian Government ICT Innovation Fund grant, involved all 39 Australian Higher Education Institutions which provide initial teacher education. TTF data collections were undertaken at the end of Semester 1 (T1) and at the end of Semester 2 (T2) in 2011. A total of 12881 participants completed the first survey (T1) and 5809 participants completed the second survey (T2). Groups of like-named items from the T1 survey were subject to a battery of complementary data analysis techniques. The psychometric properties of the four scales: Confidence - teacher items; Usefulness - teacher items; Confidence - student items; Usefulness- student items, were confirmed both at T1 and T2. Among the key findings summarised, at the national level, the scale: Confidence to use ICT as a teacher showed measurable growth across the whole scale from T1 to T2, and the scale: Confidence to facilitate student use of ICT also showed measurable growth across the whole scale from T1 to T2. Additional key TTF TPACK Survey findings are summarised.

The psychometric properties of the Spanish version of the Foot Health Status Questionnaire

Purpose: Clinical studies suggest that foot pain may be problematic in one-third of patients in early disease. The Foot Health Status Questionnaire (FHSQ) was developed and validated to evaluate the effectiveness of conservative (orthoses, taping, stretching) and surgery interventions. Despite this fact, there are few validated instruments that measure foot health status in Spanish. Thus, the primary aim of the current study was to translate and evaluate psychometrically a Spanish version of FHSQ. Methods: A cross-sectional study was designed in a university community-based podiatric clinic located in south of Spain. All participants (n = 107) recruited consecutively completed a Spanish version of FHSQ and EuroQoL Health Questionnaire 5 dimensions, and 29 participants repeated these same measures 48 h later. Data analysis included test–retest reliability, construct and criterion-related validity and factor analyses. Results: Construct validity was appropriate with moderate-to-high corrected item–subscale correlations (α = ≥0.739) for all subscales. Test–retest reliability was satisfactory (ICC > 0.932). Factor analysis revealed four dimensions with 86.6 % of the common variance explained. The confirmatory factor analysis findings demonstrated that the proposed structure was well supported (comparative fit index = 0.92, standardized root mean square = 0.09). The Spanish EuroQoL 5D score negatively correlated with the FHSQ pain (r = −0.445) and positively with general foot health and function (r = 0.261 − 0.579), confirming criterion-related validity. Conclusion: The clinimetric properties of the Spanish version of FHSQ were satisfactory.

Ensemble-based DDoS detection and mitigation model

This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.

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).

Quality of work life among primary health care nurses in the Jazan region, Saudi Arabia : a crosssectional study

Background: Quality of work life (QWL) is defined as the extent to which employee is satisfied with personal and working needs through participating in the workplace while achieving the organisation’s goals. QWL has been found to influence the commitment and productivity of employees in healthcare organisations, as well as in other industries. However, reliable information on the QWL of PHC nurses is limited. The purpose of this study was to assess the QWL among PHC nurses in the Jazan region, Saudi Arabia. Methods: A descriptive research design, namely, a cross-sectional survey was used in this study. Data were collected using Brooks’ survey of quality of nursing work life (QNWL) and demographic questions. A convenience sample was recruited from 143 PHC centres in Jazan, Saudi Arabia. The Jazan region is located in the southern part of Saudi Arabia. A response rate of 91% (N = 532/585) was achieved (effective RR = 87%, n = 508). Data analysis consisted of descriptive statistics, t-test and one way-analysis of variance. Total scores and sub-scores for QWL Items and item summary statistics were computed and reported, using SPSS version 17 for Windows. Results: Findings suggested that the respondents were dissatisfied with their work life. The major influencing factors were unsuitable working hours/shifts, lack of facilities for nurses, inability to balance work with family needs, inadequacy of family-leave time, poor staffing, management and supervision practices, lack of professional development opportunities, and inappropriate working environment in terms of the level of security, patient care supplies and equipment, and recreation facilities (Break-area). Other essential factors include the community’s view of nursing and inadequate salary. More positively, the majority of nurses were satisfied with their co-workers, satisfied to be nurses and had a sense of belonging in their workplaces. Significant differences were found according to gender, age, marital status, dependent children, dependent adults, nationality, ethnicity, nursing tenure, organisational tenure, positional tenure, and payment per month. No significant differences were found according to education level and location of PHC. Conclusions: These findings can be used by PHC managers and policy makers for developing and appropriately implementing successful plans to improve the QWL. This will help to enhance the home and work environments, improve individual and organisation performance and increase nurses’ commitment.