Healthcare teams : a practical framework for integration

Background: Delivering integrated team care is a major priority for many countries. In Australia this is a component of the GP Super Clinic Program but it is also a focus of the broader primary care sector. Explicit consideration of human dynamics and team process is often absent from the move to integrated team care. Objective: To provide a practical framework that will inform the development and evaluation of integrated healthcare teams. Discussion: The Team Focused and Clinical Content Framework is an approach to building integrated teams. This has the potential to be used to monitor and evaluate team development and functioning. Both the framework and clinical pathways provide practical tools for clinics to address the need to build integration into teams.

Towards an integrative framework for future research on small firm growth

Our review has demonstrated that small firm growth is a complex phenomenon. The concept ‘growth’ denotes both a change in amount and the process by which that change is attained. Further, the growth can be achieved in different ways and with varying degrees of regularity, and it manifests itself along several different dimensions such as sales, employment, and accumulation of assets. This complexity has naturally led researchers to adopt different approaches to studying growth and to use different measures to assess it. Further, although our review shows that it can fruitfully be regarded as a growth issue, the research on small firms' internationalization has largely developed as a separate stream. Similarly, other relatively separate literatures have evolved, which effectively focus on different modes of growth although mostly without regarding the studies first and foremost as growth studies. This goes for topics such as mergers and acquisitions, diversification, and integration - research streams which have largely ignored the particularities of small firms and which in turn have been largely ignored among researchers focusing on small firm growth.

Speaker diarization : "who spoke when"

Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

Theoretical framework for a management decision evaluation system

A theoretical framework for a construction management decision evaluation system for project selection by means of a literature review. The theory is developed by the examination of the major factors concerning the project selection decision from a deterministic viewpoint, where the decision-maker is assumed to possess 'perfect knowledge' of all the aspects involved. Four fundamental project characteristics are identified together with three meaningful outcome variables. The relationship within and between these variables are considered together with some possible solution techniques. The theory is next extended to time-related dynamic aspects of the problem leading to the implications of imperfect knowledge and a non­deterministic model. A solution technique is proposed in which Gottinger's sequential machines are utilised to model the decision process,

Evaluating Communication for Development : A Framework for Social Change

Evaluating Communication for Development presents a comprehensive framework for evaluating communication for development (C4D). This framework combines the latest thinking from a number of fields in new ways. It critiques dominant instrumental, accountability-based approaches to development and evaluation and offers an alternative holistic, participatory, mixed methods approach based on systems and complexity thinking and other key concepts. It maintains a focus on power, gender and other differences and social norms. The authors have designed the framework as a way to focus on achieving sustainable social change and to continually improve and develop C4D initiatives. The benefits and rigour of this approach are supported by examples and case studies from a number of action research and evaluation capacity development projects undertaken by the authors over the past fifteen years. Building on current arguments within the fields of C4D and development, the authors reinforce the case for effective communication being a central and vital component of participatory forms of development, something that needs to be appreciated by decision makers. They also consider ways of increasing the effectiveness of evaluation capacity development from grassroots to management level in the development context, an issue of growing importance to improving the quality, effectiveness and utilisation of monitoring and evaluation studies in this field. The book includes a critical review of the key approaches, methodologies and methods that are considered effective for planning evaluation, assessing the outcomes of C4D, and engaging in continuous learning. This rigorous book is of immense theoretical and practical value to students, scholars, and professionals researching or working in development, communication and media, applied anthropology, and evaluation and program planning.

Porous polyethersulfone-supported zeolitic imidazolate framework membranes for hydrogen separation

ZIF-8 thin layer has been synthesized on the asymmetric porous polyethersulfone (PES) substrate via secondary seeded growth. Continuous and dense ZIF-8 layer, containing microcavities, has good affinity with the PES support. Single gas permeance was measured for H2, N2, CH4, O2, and Ar at different pressure gradients and temperatures. Molecular sieving separation has been achieved for selectively separating hydrogen from larger gases. At 333 K, the H2 permeance can reach ∼4 × 10−7 mol m−2 s−1 Pa−1, and the ideal separation factors of H2 from Ar, O2, N2, and CH4 are 9.7, 10.8, 9.9, and 10.7, respectively. Long-term hydrogen permeance and H2/N2 separation performance show the stable permeability of the derived membranes.

Bayesian computation via empirical likelihood

Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.

A framework for collecting inclusive design data for the UK population

Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on.

Public health psychology : a conceptual and practical framework

Increasingly, the development of public health infrastructures requires psychology to reevaluate its contribution to public health at local, national and global levels. Already familiar to some psychologists, particularly those in community psychology and health promotion, the expansion of public health has implications for psychology in terms of knowledge/practice and working differently in multidisciplinary settings. In this article, I provide a critical overview of the implications of the historical and international development of health psychology and the changing nature of public health to strengthen the establishment of public health psychology. A conceptual and practical framework is proposed in which public health psychology theory, methods and practice are considered as well as its relevance to the health social sciences more generally.

Integrated coastal zone management and sustainable development of coastal area : a short overview of international legal framework

This chapter contains sections titled: Introduction ICZM and sustainable development of coastal zone International legal framework for ICZM Implementation of international legal obligations in domestic arena Concluding remarks References

A context-fusion framework for enhancing context-awareness on mobile application

Mobile devices and smartphones have become a significant communication channel for everyday life. The sensing capabilities of mobile devices are expanding rapidly, and sensors embedded in these devices are cheaper and more powerful than before. It is evident that mobile devices have become the most suitable candidates to sense contextual information without needing extra tools. However, current research shows only a limited number of sensors are being explored and investigated. As a result, it still needs to be clarified what forms of contextual information extracted from mo- bile sensors are useful. Therefore, this research investigates the context sensing using current mobile sensors, the study follows experimental methods and sensor data is evaluated and synthesised, in order to deduce the value of various sensors and combinations of sensor for the use in context-aware mobile applications. This study aims to develop a context fusion framework that will enhance the context-awareness on mobile applications, as well as exploring innovative techniques for context sensing on smartphone devices.

Designing an information accountability framework for eHealth

This tutorial is primarily based on the IEEE eHealth technical committee Newsletter published in March 2013. Its main focus is on information privacy management in eHealth through information accountability. The tutorial consists of three main aspects of a proposed information accountability framework for eHealth, namely, social aspects, technical aspects and legal aspects. Following a brief introduction of the problem domain and context, we present the tutorial in these three main components. The length of the tutorial is intended to be half a day.

Practical issues when designing an information accountability framework for eHealth systems

This thesis is the result of an investigation into information privacy management in eHealth. It explores the applicability of accountability measures as a means of protection of eHealth consumer privacy. The thesis presented a new concept of Accountable eHealth Systems for achieving a balance between the information privacy concerns of eHealth consumers and the information access requirements of healthcare professionals and explored the social, technological and implementation aspects involved in such a system.

Using a Bayesian network to model colonisation with Vancomycin Resistant Enterococcus (VRE)

Objective: Effective management of multi-resistant organisms is an important issue for hospitals both in Australia and overseas. This study investigates the utility of using Bayesian Network (BN) analysis to examine relationships between risk factors and colonization with Vancomycin Resistant Enterococcus (VRE). Design: Bayesian Network Analysis was performed using infection control data collected over a period of 36 months (2008-2010). Setting: Princess Alexandra Hospital (PAH), Brisbane. Outcome of interest: Number of new VRE Isolates Methods: A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). BN enables multiple interacting agents to be studied simultaneously. The initial BN model was constructed based on the infectious disease physician‟s expert knowledge and current literature. Continuous variables were dichotomised by using third quartile values of year 2008 data. BN was used to examine the probabilistic relationships between VRE isolates and risk factors; and to establish which factors were associated with an increased probability of a high number of VRE isolates. Software: Netica (version 4.16). Results: Preliminary analysis revealed that VRE transmission and VRE prevalence were the most influential factors in predicting a high number of VRE isolates. Interestingly, several factors (hand hygiene and cleaning) known through literature to be associated with VRE prevalence, did not appear to be as influential as expected in this BN model. Conclusions: This preliminary work has shown that Bayesian Network Analysis is a useful tool in examining clinical infection prevention issues, where there is often a web of factors that influence outcomes. This BN model can be restructured easily enabling various combinations of agents to be studied.

A social justice framework for safeguarding student learning engagement

The set of social justice principles and the Social Justice Framework (SJF), developed as resources for the sector as part of an Australian Government Office for Learning and Teaching project, adopt a recognitive approach to social justice and emphasise full participation and contribution within democratic society (Gale, 2000; Gale & Densmore, 2000). The SJF is contained within the major deliverable of the project, which is A Good Practice Guide for Safeguarding Student Learning Engagement (Nelson & Creagh, 2013) and is focused on good practice for activities that monitor student learning engagement and identify students at risk of disengaging in their first year. Examination of the social justice literature and its application to the higher education sector produced a set of five principles: Self-determination, Rights, Access, Equity and Participation. Each principle was defined and elucidated by a rationale and implications for practice, thus completing the SJF. The framework: reflects the notions of equity and social justice; provides a strategic approach for safeguarding engagement activities; and is supported by a suite of resources for practice and practitioners. The aim of this poster session is to engage in conversations about the SJF and how it might be applied to other types of student engagement activities critical to the first year of university life, such as orientation and transition programs, teamwork activities, peer programs and other academic support initiatives.