A distributed computing framework for all-to-all comparison problems

Distributed computation and storage have been widely used for processing of big data sets. For many big data problems, with the size of data growing rapidly, the distribution of computing tasks and related data can affect the performance of the computing system greatly. In this paper, a distributed computing framework is presented for high performance computing of All-to-All Comparison Problems. A data distribution strategy is embedded in the framework for reduced storage space and balanced computing load. Experiments are conducted to demonstrate the effectiveness of the developed approach. They have shown that about 88% of the ideal performance capacity have be achieved in multiple machines through using the approach presented in this paper.

Medical negligence, causation and liability for non-disclosure of risk : a post-wallace framework and critique

Through an examination of Wallace v Kam, this article considers and evaluates the law of causation in the specific context of a medical practitioner’s duty to provide information to patients concerning material risks of treatment. To supply a contextual background for the analysis which follows, Part II summarises the basic principles of causation law, while Part III provides an overview of the case and the reasoning adopted in the decisions at first instance and on appeal. With particular emphasis upon the reasoning in the courts of appeal, Part IV then examines the implications of the case in the context of other jurisprudence in this field and, in so doing, provides a framework for a structured consideration of causation issues in future non-disclosure cases under the Australian civil liability legislation. As will become clear, Wallace was fundamentally decided on the basis of policy reasoning centred upon the purpose behind the legal duty violated. Although the plurality in Rogers v Whitaker rejected the utility of expressions such as ‘the patient’s right of self-determination’ in this context, some Australian jurisprudence may be thought to frame the practitioner’s duty to warn in terms of promoting a patient’s autonomy, or right to decide whether to submit to treatment proposed. Accordingly, the impact of Wallace upon the protection of this right, and the interrelation between it and the duty to warn’s purpose, is investigated. The analysis in Part IV also evaluates the courts’ reasoning in Wallace by questioning the extent to which Wallace’s approach to liability and causal connection in non-disclosure of risk cases: depends upon the nature and classification of the risk(s) in question; and can be reconciled with the way in which patients make decisions. Finally, Part V adopts a comparative approach by considering whether the same decision might be reached if Wallace was determined according to English law.

A framework for people capability enhancement to support sustainable facility management practices

Spanning over a considerable length of time, facility management is a key phase in the development cycle of built assets. Therefore facility managers are in a commanding position to maximise the potential of sustainability through the operation, maintenance and upgrade of built facilities leading to decommission and deconstruction. Sustainability endeavours in facility management practices will not only contribute to reducing energy consumption, waste and running costs, but also help improve organisational productivity, financial returns and community standing of the organisation. At the forefront facing sustainability challenge, facility manager should be empowered with the necessary knowledge and capabilities. However, literature studies show a gap between the current level of awareness and the specific knowledge and necessary skills required to pursue sustainability in the profession. People capability is considered as the key enabler in managing the sustainability agenda as well as being central to the improvement of competency and innovation in an organization. This paper aims to identify the critical factors for enhancing people capabilities in promoting the sustainability agenda in facility management practices. Starting with a total of 60 factors identified through literature review, the authors conducted a questionnaire survey to assess the perceived importance of these factors. The findings reveal 23 critical factors as significantly important. They form the basis of a mechanism framework developed to equip facility managers with the right knowledge, to continue education and training and to develop new mind-sets to enhance the implementation of sustainability measures in FM practices.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Children's emotions and multimodal appraisal of places : walking with the camera

This sensory ethnography explores the affordances and constraints of multimodal design to represent emotions and appraisal associated with experiencing local places. Digital video production, walking with the camera, and the use of a think-aloud protocol to reflect on the videos, provided an opportunity for the primary school children to represent their emotions and appraisal of places multimodally. Applying a typology from Martin and White's (2005) framework for the Language of Evaluation, children's multimodal emotional responses to places in this study tended toward happiness, security, and satisfaction. The findings demonstrate an explicit connection between children's emotions in response to local places through video, while highlighting the potential for teachers to use digital filmmaking to allow children to reflect actively on their placed experiences and represent their emotional reactions to places through multiple modes.

Happiness online : supporting the emotions of emergent teachers in a virtual community

Extending Lash and Urry's (1994) notion of new "imagined communities" through information and communication structures, I ask the question: Are emergent teachers happy when they interact in online learning environments? This question is timely in the context of the ubiquity of online media and its pervasiveness in teachers' everyday work and lives. The research is important nationally and internationally, because the current research is contradictory. On the one hand, feelings of isolation and frustration have been cited as common emotions experienced in many online environments (Su, Bonk, Magjuka, Liu, & Lee, 2005). Yet others report that online communities encourage a sense of belonging and support (Mills, 2011). Emotions are inherently social, are central to learning and online interaction (Shen, Wang, & Shen, 2009). The presentations reports the use of e-motion blogs to explore emotional states of emergent primary teachers in an online learning context as they transition into their first field experience in schools. The original research was conducted with a graduate class of 64 secondary science pre-service teachers in Science Education Curriculum Studies in a large Australian university, including males and females from a variety of cultural backgrounds, aged 17-55 years. Online activities involved the participants watching a series of streamed live lectures within a course of 8 weeks duration, providing a varied set of learning experiences, such as viewing live teaching demonstrations. Each week, participants provided feedback on learning by writing and posting an e-motion diary or web log about their emotional response. The blogs answered the question: What emotions you experience during this learning experience? The descriptive data set included 284 online posts, with students contributing multiple entries. The Language of Appraisal framework, following Martin and White (2005), was used to cluster the discrete emotions within six affect groups. The findings demonstrated that the pre-service teachers' emotional responses tended towards happiness and satisfaction within the typology of affect groups - un/happiness, in/security, and dis/satisfaction. Fewer participants reported that online learning mode triggered negative feelings of frustration, and when this occurred, it often pertained expectations of themselves in the forthcoming field experience in schools or as future teachers. The findings primarily contribute new understanding about emotional states in online communities, and recommendations are provided for supporting the happiness and satisfaction of emergent teachers as they interact in online communities. It demonstrates that online environments can play an important role in fulfilling teachers' need for social interaction and inclusion.

Beyond competencies : using a capability framework in developing practice standards for advanced practice nursing

AIM This paper presents a discussion on the application of a capability framework for advanced practice nursing standards/competencies. BACKGROUND There is acceptance that competencies are useful and necessary for definition and education of practice-based professions. Competencies have been described as appropriate for practice in stable environments with familiar problems. Increasingly competencies are being designed for use in the health sector for advanced practice such as the nurse practitioner role. Nurse practitioners work in environments and roles that are dynamic and unpredictable necessitating attributes and skills to practice at advanced and extended levels in both familiar and unfamiliar clinical situations. Capability has been described as the combination of skills, knowledge, values and self-esteem which enables individuals to manage change, be flexible and move beyond competency. DESIGN A discussion paper exploring 'capability' as a framework for advanced nursing practice standards. DATA SOURCES Data were sourced from electronic databases as described in the background section. IMPLICATIONS FOR NURSING As advanced practice nursing becomes more established and formalized, novel ways of teaching and assessing the practice of experienced clinicians beyond competency are imperative for the changing context of health services. CONCLUSION Leading researchers into capability in health care state that traditional education and training in health disciplines concentrates mainly on developing competence. To ensure that healthcare delivery keeps pace with increasing demand and a continuously changing context there is a need to embrace capability as a framework for advanced practice and education.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

A framework for model integration and holistic modelling of socio-technical systems

This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

A framework for sustainable energy reduction in modern breweries

This thesis examines the existing frameworks for energy management in the brewing industry and details the design, development and implementation of a new framework at a modern brewery. The aim of the research was to develop an energy management framework to identify opportunities in a systematic manner using Systems Engineering concepts and principles. This work led to a Sustainable Energy Management Framework, SEMF. Using the SEMF approach, one of Australia's largest breweries has achieved number 1 ranking in the world for water use for the production of beer and has also improved KPI's and sustained the energy management improvements that have been implemented during the past 15 years. The framework can be adapted to other manufacturing industries in the Australian context and is considered to be a new concept and a potentially important tool for energy management.