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.

Competitive advantage through safety compliance : smaller firm responses to changes in the Australian occupational health and safety regulatory context

Smaller firms are often viewed as resistant to regulation due to cost burdens. However, evidence indicates that for some compliance is beneficial under certain conditions. Drawing on data on attitudes and responses of smaller firm owner-managers to changes in Australia’s harmonising work health and safety context we report on smaller firms’ responses to these changes. Despite uncertainty due to incomplete harmonisation, many owner-managers viewed safety compliance as important and necessary to do business. Those with negative views still linked positive safety performance to business outcomes. We categorise smaller firms’ responses and in this sample most are Positive Responders. We suggest ways forward for policy-makers to support smaller firms in complying with occupational health and safety regulation.

Increasing the confidence and knowledge of occupational therapy and physiotherapy students when communicating with people with aphasia: A pre–post intervention study

This study investigated occupational therapy and physiotherapy students' level of confidence and knowledge of strategies for communicating with people with aphasia (PWA) before and after a communication partner-training (CPT) program. Twenty-eight physiotherapy and occupational therapy students participated in a pre–post CPT program. Students completed a customized mixed-methods questionnaire before and after the intervention. The CPT program involved a lecture about effective communication strategies followed by a conversation with PWA to practice strategies learnt. Before CPT, students were not confident with the possibility of communicating with PWA. Students demonstrated rudimentary knowledge of supported conversation, identifying a maximum of five strategies for communicating effectively with PWA. Following intervention, students demonstrated increased confidence. Students' knowledge of effective communication strategies improved, with students identifying a maximum of 16 suitable strategies post-training. The results suggest that occupational therapy and physiotherapy students have potential to benefit from practical training in supported communication with PWA, which may assist them during placements in clinical settings with neurological patients or subsequent employment.

Dynamics of industry architecture and firm’s capability development : role of knowledge integration within product innovation

Aligned with the decline of Marshalian view of industry as constituting homogeneous set of firms, the new perspective is emerging by concentrating more on dynamics of sectors as the building block of industrial changes. Based on new assumptions, much of the action in terms of strategy, technology, and knowledge development does not happen either among firms within a stable industry, or through the growth or decline of certain sectors compared to others. Instead, the action happens in terms of the definition, redefinition, drawing, and redrawing of the very nature of these sectors. Technology does not progress and develop within a sector; rather it shapes (and is shaped by) the encompassing architecture of multiple sectors.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Health care consumers’ perspectives on pharmacist integration into private general practitioner clinics in Malaysia: A qualitative study

Background Pharmacists are considered medication experts but are underutilized and exist mainly at the periphery of the Malaysian primary health care team. Private general practitioners (GPs) in Malaysia are granted rights under the Poison Act 1952 to prescribe and dispense medications at their primary care clinics. As most consumers obtain their medications from their GPs, community pharmacists’ involvement in ensuring safe use of medicines is limited. The integration of a pharmacist into private GP clinics has the potential to contribute to quality use of medicines. This study aims to explore health care consumers’ views on the integration of pharmacists within private GP clinics in Malaysia. Methods A purposive sample of health care consumers in Selangor and Kuala Lumpur, Malaysia, were invited to participate in focus groups and semi-structured interviews. Sessions were audio recorded and transcribed verbatim and thematically analyzed using NVivo 10. Results A total of 24 health care consumers participated in two focus groups and six semi-structured interviews. Four major themes were identified: 1) pharmacists’ role viewed mainly as supplying medications, 2) readiness to accept pharmacists in private GP clinics, 3) willingness to pay for pharmacy services, and 4) concerns about GPs’ resistance to pharmacist integration. Consumers felt that a pharmacist integrated into a private GP clinic could offer potential benefits such as to provide trustworthy information on the use and potential side effects of medications and screening for medication misadventure. The potential increase in costs passed on to consumers and GPs’ reluctance were perceived as barriers to integration. Conclusion This study provides insights into consumers’ perspectives on the roles of pharmacists within private GP clinics in Malaysia. Consumers generally supported pharmacist integration into private primary health care clinics. However, for pharmacists to expand their capacity in providing integrated and collaborative primary care services to consumers, barriers to pharmacist integration need to be addressed.

GABAA and NMDA receptors contribute to synaptic integration in lateral amygdala neurons

In classical fear conditioning a neutral conditioned stimulus (CS), is paired with an aversive unconditioned stimulus (US). The CS thereby acquires the capacity to elicit a fear response. This type of associative learning is thought to require co-activation of principal neurons in the lateral nucleus of the amygdala (LA) by two sets of synaptic inputs...

GABAa receptors contribute to synaptic integration in lateral amygdala neurons

In classical fear conditioning a neutral conditioned stimulus (CS) such as a tone, is paired with an aversive unconditioned stimulus (US) such as a shock. The CS thereby acquires the capacity to elicit a fear response. This type of associative learning is thought to require co-activation of principle neurons in the lateral nucleus of the amygdala (LA) by two sets of synaptic inputs, a weak CS and a strong US...

Exploring and validating the internal dimensions of occupational stress: Evidence from construction cost estimators in China

A recurring feature of modern practice is occupational stress of project professionals, with both debilitating effects on the people concerned and indirectly affecting project success. Previous research outside the construction industry has involved the use of a psychology perceived stress questionnaire (PSQ) to measure occupational stress, resulting in the identification of one stressor – demand - and three sub-dimensional emotional reactions in terms of worry, tension and joy. The PSQ is translated into Chinese with a back translation technique and used in a survey of young construction cost professionals in China. Principal component analysis and confirmatory factor analysis are used to test the divisibility of occupational stress - little mentioned in previous research on stress in the construction context. In addition, structural equation modelling is used to assess nomological validity by testing the effects of the three dimensions on organizational commitment, the main finding of which is that lack of joy has the sole significant effect. The three-dimensional measurement framework facilitates the standardizing measurement of occupational stress. Further research will establish if the findings are also applicable in other settings and explore the relations between stress dimensions and other managerial concepts.

Integration of Opinion Mining into customer analysis model

This research proposes a multi-dimensional model for Opinion Mining, which integrates customers' characteristics and their opinions about products (or services). Customer opinions are valuable for companies to deliver right products or services to their customers. This research presents a comprehensive framework to evaluate opinions' orientation based on products' hierarchy attributes. It also provides an alternative way to obtain opinion summaries for different groups of customers and different categories of produces.

A Web-based system enabling the integration, analysis, and 3D sub-surface visualization of groundwater monitoring data and geological models

The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.

Integration over song classification replicates: song variant analysis in the hihi

Human expert analyses are commonly used in bioacoustic studies and can potentially limit the reproducibility of these results. In this paper, a machine learning method is presented to statistically classify avian vocalizations. Automated approaches were applied to isolate bird songs from long field recordings, assess song similarities, and classify songs into distinct variants. Because no positive controls were available to assess the true classification of variants, multiple replicates of automatic classification of song variants were analyzed to investigate clustering uncertainty. The automatic classifications were more similar to the expert classifications than expected by chance. Application of these methods demonstrated the presence of discrete song variants in an island population of the New Zealand hihi (Notiomystis cincta). The geographic patterns of song variation were then revealed by integrating over classification replicates. Because this automated approach considers variation in song variant classification, it reduces potential human bias and facilitates the reproducibility of the results.