Shifting the Airline Business Model - Current Struggles of National Carriers to Become Profitable Passenger Experience Companies

National flag carriers are struggling for survival, not only due to classical reasons such as increase in fuel and tax or natural disasters, but largely due to the inability to quickly adapt to its competitive environment – the emergence of budget and Persian Gulf airlines. In this research, we investigate how airlines can transform their business models via technological and strategic capabilities to become profitable and sustainable passenger experience companies. To formulate recommendations, we analyze customer sentiments via social media to understand what people are saying about the airlines.

A study on the effects of routing symbol design on process model comprehension

Process modeling grammars are used to create models of business processes. In this paper, we discuss how different routing symbol designs affect an individual's ability to comprehend process models. We conduct an experiment with 154 students to ascertain which visual design principles influence process model comprehension. Our findings suggest that design principles related to perceptual discriminability and pop out improve comprehension accuracy. Furthermore, semantic transparency and aesthetic design of symbols lower the perceived difficulty of comprehension. Our results inform important principles about notational design of process modeling grammars and the effective use of process modeling in practice.

Students’ approaches to learning a new mathematical model

In this article, we report on the findings of an exploratory study into the experience of undergraduate students as they learn new mathematical models. Qualitative and quanti- tative data based around the students’ approaches to learning new mathematical models were collected. The data revealed that students actively adopt three approaches to under- standing a new mathematical model: gathering information for the task of understanding the model, practising with and using the model, and finding interrelationships between elements of the model. We found that the students appreciate mathematical models that have a real world application and that this can be used to engage students in higher level learning approaches.

A flexible asset maintenance decision-making process model

Optimal Asset Maintenance decisions are imperative for efficient asset management. Decision Support Systems are often used to help asset managers make maintenance decisions, but high quality decision support must be based on sound decision-making principles. For long-lived assets, a successful Asset Maintenance decision-making process must effectively handle multiple time scales. For example, high-level strategic plans are normally made for periods of years, while daily operational decisions may need to be made within a space of mere minutes. When making strategic decisions, one usually has the luxury of time to explore alternatives, whereas routine operational decisions must often be made with no time for contemplation. In this paper, we present an innovative, flexible decision-making process model which distinguishes meta-level decision making, i.e., deciding how to make decisions, from the information gathering and analysis steps required to make the decisions themselves. The new model can accommodate various decision types. Three industrial case studies are given to demonstrate its applicability.

APQL : a process-model query language

As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation.

Delineating the practice profile of advanced practice nursing : a cross-sectional survey using the modified strong model of advanced practice

AIMS: To test a model that delineates advanced practice nursing from the practice profile of other nursing roles and titles. BACKGROUND: There is extensive literature on advanced practice reporting the importance of this level of nursing to contemporary health service and patient outcomes. Literature also reports confusion and ambiguity associated with advanced practice nursing. Several countries have regulation and delineation for the nurse practitioner, but there is less clarity in definition and service focus of other advanced practice nursing roles. DESIGN: A statewide survey. METHODS: Using the modified Strong Model of Advanced Practice Role Delineation tool, a survey was conducted in 2009 with a random sample of registered nurses/midwives from government facilities in Queensland, Australia. Analysis of variance compared total and subscale scores across groups according to grade. Linear, stepwise multiple regression analysis examined factors influencing advanced practice nursing activities across all domains. RESULTS: There were important differences according to grade in mean scores for total activities in all domains of advanced practice nursing. Nurses working in advanced practice roles (excluding nurse practitioners) performed more activities across most advanced practice domains. Regression analysis indicated that working in clinical advanced practice nursing roles with higher levels of education were strong predictors of advanced practice activities overall. CONCLUSION: Essential and appropriate use of advanced practice nurses requires clarity in defining roles and practice levels. This research delineated nursing work according to grade and level of practice, further validating the tool for the Queensland context and providing operational information for assigning innovative nursing service.

Developing a model for collaborative research

Collaboration between nurses in clinical and educational settings has been advocated as a means of ensuring nursing research is both practice oriented and scientifically valid. This paper describes a model, jointly developed by colleagues from the Nursing Departments of Alfred Hospital and La Trobe University, to foster collaborative research and steer research projects generated by clinical nurses from conceptualisation to publication.

International conventions and model laws : their impact on domestic commercial law

Panellist commentary on delivered conference papers on the topic of ‘International Conventions and Model Laws - Their Impact on Domestic Commercial Law’.

Recovery model of care within the PICU

Nurses are the primary care providers of consumers admitted to the High Dependency Ward (HDU) or Psychiatric Intensive Care Unit (PICU). They are the largest professional group providing care to the acutely unwell, managing crisis and complex clinical psychiatric scenarios. It is timely to review the skills and expertise of this nursing specialty for further definition and acknowledgement.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Spatial mapping of city-wide PBDE levels using an exponential decay model

Passive air samplers (PAS) consisting of polyurethane foam (PUF) disks were deployed at 6 outdoor air monitoring stations in different land use categories (commercial, industrial, residential and semi-rural) to assess the spatial distribution of polybrominated diphenyl ethers (PBDEs) in the Brisbane airshed. Air monitoring sites covered an area of 1143 km2 and PAS were allowed to accumulate PBDEs in the city's airshed over three consecutive seasons commencing in the winter of 2008. The average sum of five (∑5) PBDEs (BDEs 28, 47, 99, 100 and 209) levels were highest at the commercial and industrial sites (12.7 ± 5.2 ng PUF−1), which were relatively close to the city center and were a factor of 8 times higher than residential and semi-rural sites located in outer Brisbane. To estimate the magnitude of the urban ‘plume’ an empirical exponential decay model was used to fit PAS data vs. distance from the CBD, with the best correlation observed when the particulate bound BDE-209 was not included (∑5-209) (r2 = 0.99), rather than ∑5 (r2 = 0.84). At 95% confidence intervals the model predicts that regardless of site characterization, ∑5-209 concentrations in a PAS sample taken between 4–10 km from the city centre would be half that from a sample taken from the city centre and reach a baseline or plateau (0.6 to 1.3 ng PUF−1), approximately 30 km from the CBD. The observed exponential decay in ∑5-209 levels over distance corresponded with Brisbane's decreasing population density (persons/km2) from the city center. The residual error associated with the model increased significantly when including BDE-209 levels, primarily due to the highest level (11.4 ± 1.8 ng PUF−1) being consistently detected at the industrial site, indicating a potential primary source at this site. Active air samples collected alongside the PAS at the industrial air monitoring site (B) indicated BDE-209 dominated congener composition and was entirely associated with the particulate phase. This study demonstrates that PAS are effective tools for monitoring citywide regional differences however, interpretation of spatial trends for POPs which are predominantly associated with the particulate phase such as BDE-209, may be restricted to identifying ‘hotspots’ rather than broad spatial trends.

An integrated educational model for continuing nurse education

Aim This paper reports on the development and evaluation of an integrated clinical learning model to inform ongoing education for surgical nurses. The research aim was to evaluate the effectiveness of implementing a Respiratory Skills Update (ReSKU) education program, in the context of organisational utility, on improving surgical nurses' practice in the area of respiratory assessment. Background Continuous development and integration of technological innovations and research in the healthcare environment mandate the need for continuing education for nurses. Despite an increased worldwide emphasis on this, there is scant empirical evidence of program effectiveness. Methods A quasi experimental pre test, post test non–equivalent control group design evaluated the impact of the ReSKU program on surgical nurses' clinical practice. The 2008 study was conducted in a 400 bed regional referral public hospital and was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies. Findings The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group's reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales. Conclusion The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful reflection, was a powerful educational strategy to enhance competency and capability in clinicians.

Application of a digital elevation model for flood modeling for the Pagsangaan River in Leyte

Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen as the DEM. Although the horizontal spatial resolution of 30 m is rather desirable, it contains substantial vertical errors. These were identified, different correction methods were tested and the resulting DEM was used for flood modelling. The above mentioned data were combined with cross-sections at various strategic locations of the river network, meteorological records, river water level, and current velocity to develop the 1D-2D flood model. SOBEK was used as modelling software to create different rainfall scenarios, including historic flooding events. Due to the lack of scientific data for the verification of the model quality, interviews with local stakeholders served as the gauge to judge the quality of the generated flood maps. According to interviewees, the model reflects reality more accurately than previously available flood maps. The resulting flood maps are now used by the operations centre of a local flood early warning system for warnings and evacuation alerts. Furthermore these maps can serve as a basis to identify flood hazard areas for spatial land use planning purposes.

Nambour : the model rural school

This paper examines the Rural Schools of Queensland. Starting with Nambour in 1917, the scheme incorporated thirty schools, and operated for over forty years. The rhetoric of the day was that boys and girls from the senior classes of primary school would be provided with elementary instruction of a practical character. In reality, the subjects taught were specifically tailored to provide farm skills to children in rural centres engaged in farming, dairying or fruit growing. Linked to each Rural School was a number of smaller surrounding schools, students from which travelled to the Rural School for special agricultural or domestic instruction. Through this action, the Queensland Department of Public Instruction left no doubt it intended to provide educational support for agrarian change and development within the state; in effect, they had set in motion the creation of a Queensland yeoman class. The Department’s intention was to arrest or reverse the trend toward urbanisation — whilst increasing agricultural productivity — through the making of a farmer born of the land and accepting of the new scientific advances in agriculture.

Upper-body morbidity after breast cancer : incidence and evidence for evaluation, prevention, and management within a prospective surveillance model of care

The purpose of this paper is to review the incidence of upper-body morbidity (arm and breast symptoms, impairments, and lymphedema), methods for diagnosis, and prevention and treatment strategies. It was also the purpose to highlight the evidence base for integration of prospective surveillance for upper-body morbidity within standard clinical care of women with breast cancer. Between 10% and 64% of women report upper-body symptoms between 6 months and 3 years after breast cancer, and approximately 20% develop lymphedema. Symptoms remain common into longer-term survivorship, and although lymphedema may be transient for some, those who present with mild lymphedema are at increased risk of developing moderate to severe lymphedema. The etiology of morbidity seems to be multifactorial, with the most consistent risk factors being those associated with extent of treatment. However, known risk factors cannot reliably distinguish between those who will and will not develop upper-body morbidity. Upper-body morbidity may be treatable with physical therapy. There is also evidence in support of integrating regular surveillance for upper-body morbidity into the routine care provided to women with breast cancer, with early diagnosis potentially contributing to more effective management and prevention of progression of these conditions.