Augmented Reality Process Modelling Tool

Video presented as part of BPM2011 demonstration(France). In this video we show a prototype BPMN process modelling tool which uses Augmented Reality techniques to increase the sense of immersion when editing a process model. The avatar represents a remotely logged in user, and facilitates greater insight into the editing actions of the collaborator than present 2D web-based approaches in collaborative process modelling. We modified the Second Life client to integrate the ARToolkit in order to support pattern-based AR.

Development and validation of an instrument to measure organizational cultures' support of business process management

The purpose of Business Process Management (BPM) is to increase the efficiency and effectiveness of organizational processes through improvement and innovation. Despite a common understanding that culture is an important element in these efforts, there is a dearth of theoretical and empirical research on culture as a facilitator of successful BPM. We develop the BPM culture construct and propose a validated instrument with which to measure organizational cultures’ support of BPM. The operationalization of the BPM culture concept provides a theoretical foundation for future research and a tool to assist organizations in developing a cultural environment that supports successful BPM.

Validation of a new tool to measure responsiveness and structure in the feeding context : the Authoritative Feeding Practices Questionnaire

How mothers interact with their toddlers around food lays the foundations for healthy eating and healthy weight gain in later life. This research involving 467 Australian first-time mothers of 2-year-old children resulted in the development of a new self-report tool, the Authoritative Feeding Practices Questionnaire, assessing maternal responsive feeding and mealtime structure. Secondary analysis of the NOURISH randomised controlled trial included theory-driven item selection, confirmatory factor analysis, evaluation of psychometric properties and construct validation. The result is a brief, reliable and valid new tool for evaluating the maternal feeding practices that support children to become healthy, independent eaters.

The structured and practical approach in development of decision support system for consultant selection in public sector infrastructure project

Nowadays, most of the infrastructure development projects undertaken are complex in nature. Practically, public clients who do not have a good understanding of the design and management may suffer severe losses, especially for infrastructure projects. There is a need for luring the right consultant to secure client's investment in infrastructure developments. Throughout the project life cycle, consultants play vital role from the inception to completion stage of a project. A few studies in Malaysia show that infrastructure projects involving irrigation and drainage have experience problems such as poor workmanship, delay and cost overrun due to the consultant's inability or the client incompetence of recruiting consultants in time. This highlights the need of aided decision making and an efficient system to select the best consultant by using Decision Support System (DSS). On the other hand, recent trends reveal that most DSS in construction only concentrate on decision model development. These models are impractical and unused as they are complicated or difficult for laymen such as project managers to utilize. Thus, this research attempts to develop an efficient DSS for consultant selection namely consultDeSS. Driven by the motivation and research aims, this study deployed Design Science Research Methodology (DSRM) dominant with a combination of case studies at the Malaysian Department of Irrigation and Drainage (DID). Two real projects involving irrigation and drainage infrastructure were used to design, implement and evaluate the artefact. The 3-tier consultDeSS was revised after the evaluation and the design was significantly improved based on user feedback. By developing desirable tools that fit client's needs will enhance the productivity and minimize conflict within groups and organisations. The tool is more usable and efficient compared to previous studies in construction. Thus, this research has demonstrated a purposeful artefact with a practical and valid structured development approach that is applicable in a variety of problems in construction discipline.

A demand-responsive decision support system for coal transportation

In this paper, a demand-responsive decision support system is proposed by integrating the operations of coal shipment, coal stockpiles and coal railing within a whole system. A generic and flexible scheduling optimisation methodology is developed to identify, represent, model, solve and analyse the coal transport problem in a standard and convenient way. As a result, the integrated train-stockpile-ship timetable is created and optimised for improving overall efficiency of coal transport system. A comprehensive sensitivity analysis based on extensive computational experiments is conducted to validate the proposed methodology. The mathematical proposition and proof are concluded as technical and insightful advices for industry practice. The proposed methodology provides better decision making on how to assign rail rolling-stocks and upgrade infrastructure in order to significantly improve capacity utilisation with the best resource-effectiveness ratio. The proposed decision support system with train-stockpile-ship scheduling optimisation techniques is promising to be applied in railway or mining industry, especially as a useful quantitative decision making tool on how to use more current rolling-stocks or whether to buy additional rolling-stocks for mining transportation.

Using NVivo as a research management tool : a case narrative

This paper presents an illustrative demonstration of the qualitative data analysis tool NVivo (version 2.0), as employed across a multi-method research design as a comprehensive tool in support of overall research management. The paper will be of interest to (a) novice researchers, as a reference in their research design efforts; (b) academics, involved in research training, where this narrative can be used as a rich teaching case and; potentially to (c) vendors, of similar software tools, who may identify potential new tool applications and valuable tool enhancements.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Measuring ward-based multidisciplinary healthcare team functioning : a validation study of the Team Functioning Assessment Tool (TFAT)

The team functioning assessment tool (TFAT) has been shown to be a reliable behavioral marker tool for assessing nontechnical skills that are critical to the success of ward-based healthcare teams. This paper aims to refine and shorten the length of the TFAT to improve usability, and establish its reliability and construct validity. Psychometric testing based on 110 multidisciplinary healthcare teams demonstrated that the TFAT is a reliable and valid tool for measuring team members’ nontechnical skills in regards to Clinical Planning, Executive Tasks, and Team Functioning. Providing support for concurrent validity, high TFAT ratings were predicted by low levels of organizational constraints and high levels of group potency. There was also partial support for the negative relationships between time pressure, leadership ambiguity, and TFAT ratings. The paper provides a discussion on the applicability of the tool for assessing multidisciplinary healthcare team functioning in the context of improving team effectiveness and patient safety for ward-based hospital teams.

Pipeline renewal decision support : a case study using LinEAR in a water pipeline network

This paper presents a case study for the application of a Linear Engineering Asset Renewal decision support software tool (LinEAR) at a water distribution network in Australia. This case study examines how the LinEAR can assist water utilities to minimise their total pipeline management cost, to make a long-term budget based on mathematically predicted expenditure, and to present calculated evidence for supporting their expenditure requirements. The outcomes from the study on pipeline renewal decision support demonstrate that LinEAR can help water utilities to improve the decision process and save renewal costs over a long-term by providing an optimum renewal schedules. This software can help organisation to accumulate technical knowledge and prediction future impact of the decision using what-if analysis.

Supporting residents’ expression of sexuality : the initial construction of a sexuality assessment tool for residential aged care facilities

Background: Sexuality is a key component of quality of life and well-being and a need to express one’s sexuality continues into old age. Staff and families in residential aged care facilities often find expressions of sexuality by residents, particularly those living with dementia, challenging and facilities often struggle to address individuals’ needs in this area. This paper describes the development of an assessment tool which enables residential aged care facilities to identify how supportive their organisation is of all residents’ expression of their sexuality, and thereby improve where required. Methods: Multi-phase design using qualitative methods and a Delphi technique. Tool items were derived from the literature and verified by qualitative interviews with aged care facility staff, residents and families. The final item pool was confirmed via a reactive Delphi process. Results: A final item pool of sixty-nine items grouped into seven key areas allows facilities to score their compliance with the areas identified as being supportive of older people’s expression of their sexuality in a residential aged care environment. Conclusions: The sexuality assessment tool (SexAT) guides practice to support the normalization of sexuality in aged care homes and assists facilities to identify where enhancements to the environment, policies, procedures and practices, information and education/training are required. The tool also enables facilities to monitor initiatives in these areas over time.

Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

A simple nutrition screening tool for paediatric inpatients

Background: Pediatric nutrition risk screening tools are not routinely implemented throughout many hospitals, despite prevalence studies demonstrating malnutrition is common in hospitalized children. Existing tools lack the simplicity of those used to assess nutrition risk in the adult population. This study reports the accuracy of a new, quick, and simple pediatric nutrition screening tool (PNST) designed to be used for pediatric inpatients. Materials and Methods: The pediatric Subjective Global Nutrition Assessment (SGNA) and anthropometric measures were used to develop and assess the validity of 4 simple nutrition screening questions comprising the PNST. Participants were pediatric inpatients in 2 tertiary pediatric hospitals and 1 regional hospital. Results: Two affirmative answers to the PNST questions were found to maximize the specificity and sensitivity to the pediatric SGNA and body mass index (BMI) z scores for malnutrition in 295 patients. The PNST identified 37.6% of patients as being at nutrition risk, whereas the pediatric SGNA identified 34.2%. The sensitivity and specificity of the PNST compared with the pediatric SGNA were 77.8% and 82.1%, respectively. The sensitivity of the PNST at detecting patients with a BMI z score of less than -2 was 89.3%, and the specificity was 66.2%. Both the PNST and pediatric SGNA were relatively poor at detecting patients who were stunted or overweight, with the sensitivity and specificity being less than 69%. Conclusion: The PNST provides a sensitive, valid, and simpler alternative to existing pediatric nutrition screening tools such as Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), Screening Tool Risk on Nutritional status and Growth (STRONGkids), and Paediatric Yorkhill Malnutrition Score (PYMS) to ensure the early detection of hospitalized children at nutrition risk.

Large scale multiuser digital mind mapping tool : a study in usability

Project work can involve multiple people from varying disciplines coming together to solve problems as a group. Large scale interactive displays are presenting new opportunities to support such interactions with interactive and semantically enabled cooperative work tools such as intelligent mind maps. In this paper, we present a novel digital, touch-enabled mind-mapping tool as a first step towards achieving such a vision. This first prototype allows an evaluation of the benefits of a digital environment for a task that would otherwise be performed on paper or flat interactive surfaces. Observations and surveys of 12 participants in 3 groups allowed the formulation of several recommendations for further research into: new methods for capturing text input on touch screens; inclusion of complex structures; multi-user environments and how users make the shift from single- user applications; and how best to navigate large screen real estate in a touch-enabled, co-present multi-user setting.

Psychometric properties of an Australian supportive care needs assessment tool for Indigenous patients with cancer

BACKGROUND There are significant disparities in cancer outcomes between Indigenous and non-Indigenous Australians. Identifying the unmet supportive care needs of Indigenous Australians with cancer is imperative to improve their cancer care. The purpose of this study was to test the psychometric properties of a supportive care needs assessment tool for Indigenous Australian (SCNAT-IP) cancer patients. METHODS The SCNAT-IP was administered to 248 Indigenous Australians diagnosed with a range of cancer types and stages, and received treatment in one of four Queensland hospitals. All 39 items were assessed for ceiling and floor effects and analysed using exploratory factor analysis (EFA) to determine construct validity. Identified factors were assessed for internal consistency and convergent validity to validated psychosocial tools. RESULTS EFA revealed a four-factor structure (physical and psychological, hospital care, information and communication, and practical and cultural needs) explaining 51% of the variance. Internal consistency of four subscales was good, with Cronbach Alpha reliability coefficients ranging from 0.70-0.89. Convergent validity was supported by significant correlations between the SCNAT-IP with the Distress Thermometer (r=0.60, p<0.001), and The Cancer Worry Chart (r=0.58, p<0.001) and a moderately strong negative correlation with Assessment of Quality of Life questionnaire (r=-0.56, p<0.001). CONCLUSION These data provide initial support for the SCNAT-IP a measure of multiple supportive care needs domains specific to Indigenous Australian cancer patients undergoing treatment.

Designing a mobile social tool that moderates drinking

A novel mobile social networking tool uses peer support to facilitate responsible drinking among young women. Focus group reports indicate that the tool’s design is easy to use and its functionalities would help peers reduce risk during drinking sessions.