Framing the FRAM: A literature review on the functional resonance analysis method

The development of the Functional Resonance Analysis Method (FRAM) has been motivated by the perceived limitations of fundamentally deterministic and probabilistic approaches to understand complex systems’ behaviour. Congruent with the principles of Resilience Engineering, over recent years the FRAM has been progressively developed in scientific terms, and increasingly adopted in industrial environments with reportedly successful results. Nevertheless, a wide literature review focused on the method is currently lacking. On these premises, this paper aims to summarise all available published research in English about FRAM. More than 1700 documents from multiple scientific repositories were reviewed through a protocol based on the PRISMA review technique. The paper aims to uncover a number of characteristics of the FRAM research, both in terms of the method's application and of the authors contributing to its development. The systematic analysis explores the method in terms of its methodological aspects, application domains, and enhancements in qualitative and quantitative terms, as well as proposing potential future research directions

Creating a climate for food security: the business, people & landscapes in food production

AbstractBalancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. Balancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. The triple-bottom-line provided a comprehensive means of addressing social, economic and ecological requirements, and the modelling showed the interacting dynamics between these dimensions. In response to climate change, the agricultural sector must now optimise practices to address the interaction between economic, social and environmental investment. Differences in positions between the industry sector, the government and research sectors demonstrate the need for closer relationships between industry and government if climate change interventions are to be effectively targeted. Modelling shows that capacity for adaptation has a significant bearing on the success of implementing intervention strategies. Without intervention strategies to build viability and support, farm businesses are more likely to fail as a consequence of climate change. A framework of capitals that includes social components - cultural, human and social capital-, economic components -economic and physical capital - and ecological components -ecological and environmental capital - should be applied to address capacities. A priority assessment of climate change intervention strategies shows that strategies categorised as ‘Technology & Extension’ are most important in minimising risk from climate change impacts. To implement interventions to achieve ‘Food Business Resilience’, ‘Business Development’ strategies and alternative business models are most effective. ‘Research and Development’ interventions are essential to achieve enhanced ‘Adaptive Capacity’.The individual components of TBL Adaptive Capacity can be achieved through ‘Policy and Governance’ interventions for building ‘Social Capital’ capacity, ‘Research and Development’ will develop ‘Economic Capital’, and ‘Business Development’ strategies will build ‘Ecological Capital’.These strategic interventions will promote food security and maintain resilience in local food systems, agricultural production communities and markets, global industrial systems, and developing world food systems. Climate change mitigation and adaptation interventions reflect a rich conceptualisation drawing from the Australian context, but also acknowledging the moral context of global association.Please cite this report as:Wardell-Johnson, A, Uddin, N, Islam, N, Nath, T, Stockwell, B, Slade, C 2013 Creating a climate for food security: the businesses, people and landscapes in food production, National Climate Change Adaptation Research Facility, Gold Coast, pp. 144.Balancing human and environmental needs is urgent where food security and sustainability are under pressure from population increases and changing climates. Requirements of food security, social justice and environmental justice exacerbate the impact of agriculture on the supporting ecological environment. Viability of the Australian rural economy is intrinsically linked to food production and food security requiring systematic evaluation of climate change adaptation strategies for agricultural productivity.This food-systems research drew on global climate change literature to identify risks and adaptation. The transdisciplinary team applied specialist experience through collaboration in social science, economics and land-management to provide comprehensive methods to engage researchers and decision-makers making decisions across the food-system. Research focus on the dairy and horticulture sectors in the SW-WA and SEQld provided a comparative context in food-systems and regional economies. Expert knowledge was engaged through a series of panel meetings to test and challenge existing practice applying conceptual and empirical approaches in Structural Equation, Value-Chain, Supply-Chain modelling and Analytical Hierarchy modelling. This iterative action-research process provided immediate generation and transfer of expert knowledge across the involved sectors. The scenarios and adaptive strategies provide evidence-based pathways to strengthen food-systems; account for climate change mitigation and adaptation; and weather-proof regional economies in the face of climate change. The triple-bottom-line provided a comprehensive means of addressing social, economic and ecological requirements, and the modelling showed the interacting dynamics between these dimensions. In response to climate change, the agricultural sector must now optimise practices to address the interaction between economic, social and environmental investment. Differences in positions between the industry sector, the government and research sectors demonstrate the need for closer relationships between industry and government if climate change interventions are to be effectively targeted. Modelling shows that capacity for adaptation has a significant bearing on the success of implementing intervention strategies. Without intervention strategies to build viability and support, farm businesses are more likely to fail as a consequence of climate change. A framework of capitals that includes social components - cultural, human and social capital-, economic components -economic and physical capital - and ecological components -ecological and environmental capital - should be applied to address capacities. A priority assessment of climate change intervention strategies shows that strategies categorised as ‘Technology & Extension’ are most important in minimising risk from climate change impacts. To implement interventions to achieve ‘Food Business Resilience’, ‘Business Development’ strategies and alternative business models are most effective. ‘Research and Development’ interventions are essential to achieve enhanced ‘Adaptive Capacity’.The individual components of TBL Adaptive Capacity can be achieved through ‘Policy and Governance’ interventions for building ‘Social Capital’ capacity, ‘Research and Development’ will develop ‘Economic Capital’, and ‘Business Development’ strategies will build ‘Ecological Capital’.These strategic interventions will promote food security and maintain resilience in local food systems, agricultural production communities and markets, global industrial systems, and developing world food systems. Climate change mitigation and adaptation interventions reflect a rich conceptualisation drawing from the Australian context, but also acknowledging the moral context of global association

Behaviour Profiling using Wearable Sensors for Pervasive Healthcare

In recent years, sensor technology has advanced in terms of hardware sophistication and miniaturisation. This has led to the incorporation of unobtrusive, low-power sensors into networks centred on human participants, called Body Sensor Networks. Amongst the most important applications of these networks is their use in healthcare and healthy living. The technology has the possibility of decreasing burden on the healthcare systems by providing care at home, enabling early detection of symptoms, monitoring recovery remotely, and avoiding serious chronic illnesses by promoting healthy living through objective feedback. In this thesis, machine learning and data mining techniques are developed to estimate medically relevant parameters from a participant‘s activity and behaviour parameters, derived from simple, body-worn sensors. The first abstraction from raw sensor data is the recognition and analysis of activity. Machine learning analysis is applied to a study of activity profiling to detect impaired limb and torso mobility. One of the advances in this thesis to activity recognition research is in the application of machine learning to the analysis of 'transitional activities': transient activity that occurs as people change their activity. A framework is proposed for the detection and analysis of transitional activities. To demonstrate the utility of transition analysis, we apply the algorithms to a study of participants undergoing and recovering from surgery. We demonstrate that it is possible to see meaningful changes in the transitional activity as the participants recover. Assuming long-term monitoring, we expect a large historical database of activity to quickly accumulate. We develop algorithms to mine temporal associations to activity patterns. This gives an outline of the user‘s routine. Methods for visual and quantitative analysis of routine using this summary data structure are proposed and validated. The activity and routine mining methodologies developed for specialised sensors are adapted to a smartphone application, enabling large-scale use. Validation of the algorithms is performed using datasets collected in laboratory settings, and free living scenarios. Finally, future research directions and potential improvements to the techniques developed in this thesis are outlined

A virtual engineering based approach to verify structural complexity of component-based automation systems in early design phase

Highly diverse factors including technological advancements, uncertain global market and mass personalisation are believed to be main causes of ever-growing complexity of manufacturing systems. Although complex systems may be needed to achieve global manufacturing requirements, complexity affects on various factors, such as: system development effort and cost, ease of re-configuration, level of skill required across the system life-cycle (e.g. design, operate and maintain). This article aims to develop a scientifically valid and industrially applicable complexity assessment approach to support early life-cycle phases of component-based automation systems against unwanted implications of structural system complexity. The presented approach defines component-based automation system as a constellation of basic components which can be represented in various design domains, such as: mechanical, electrical, pneumatic, control, etc. Accordingly, structural complexity is expressed as the combination of both inherent complexity of system entities and topological complexity resulting from the integration of elements of such constellations in a multi-layered network. The proposed approach is used to specify and implement a complexity assessment module which can be integrated into a series of virtual system design software solutions, in order to add complexity assessment as part of the design support and validation tools used by manufacturing engineers. Consequently, the proposed approach is integrated into the vueOne virtual engineering tool, wherein virtual automation system design data can be streamlined and used as input to the theoretical complexity model. In the developed tool, only mechanical and logical design domains are considered due to the limited data availability in early design phase. Inherent complexity of both mechanical and logical system entities and their interactions are expressed as a function of domain-specific design elements, and topological complexity is defined as the graph energy of the corresponding design connectivity matrix. Furthermore, the values of mathematical model parameters are determined based on an optimisation study, where subjective opinions of system/control engineers regarding the effort/difficulty associated with the development of thirty different component-based automation system designs are correlated with the corresponding complexity model outputs to minimise the prediction errors. The proposed approach is also demonstrated on a modular production system consisting of four sub-modules. The study shows that the approach can help designers/managers to better identify root causes of structural system complexity, and provides a systemic approach to compare alternate system designs during early system planning phase

Modelling and optimizing socio-technical operations in healthcare using the FRAM and reinforcement learning

This PhD research work is intended to model, analyze, and optimize socio-technical operations in healthcare using a systemic approach and reinforcement learning. An extensive literature review is presented, and the main knowledge gaps related to modelling and optimizing socio-technical operations in healthcare are clearly outlined and addressed in this research work. Introduction: Hospital to home transition processes of frail older adults include a set of actions for frail people who are discharged from hospital to their home in the community. The transition process exhibits dynamic interactions between technology, humans, organizations, and the environment. The non-linear dependencies among these influential parameters complicate the understanding of the transition process and the mechanism of modelling its operations. Objectives: The objectives of this research work are (a) To identify the strengths and shortcomings of the FRAM in modelling complex socio-technical systems; (b) To develop a comprehensive model of the hospital-to-home transition process for frail patients; (c) To capture and visualize different characteristics of variability in the transition process; (d) To monitor frail patients’ transitions from hospital to home; (e) To identify challenges of the transition process; and (f) To explore functional pathways to identify transition processes with the highest quality of care and services for frail older people. Methodology: This research work uses the Functional Resonance Analysis Method (FRAM) to study and model the complexity of the transition process. A complementary tool for the FRAM (DynaFRAM) is also used to characterize functional and system variability in order to identify the challenges of successful transition processes. Additionally, this research employs the reinforcement learning technique to explore the functional transition model generated by the FRAM to investigate a basic method to optimize the transition process for frail people. Results and discussion: The results of this research work show that FRAM-generated models can serve as a basis in further analyses regarding complexity, safety, and risk management. The results also indicate that the DynaFRAM tool helps monitor patients’ hospital-to-home transitions and characterize different types of variability in functional and system outputs. A comprehensive model¹ of the transition process was built using the FRAM. It includes a library of 38 functions classified in five categories. The outcomes of using the DynaFRAM for monitoring patients’ transitions revealed functions with significant variability. The variability observed in the outputs of these functions could be challenging as the variability of a function can reinforce the variability of down-stream functions and affect the performance of the entire transition process. Finally, the results of coupling the FRAM to reinforcement learning help evaluate the system performance in terms of accumulated action value achieved by an artificial agent during functional pathways. Conclusion: In light of the FRAM, the complexity of the transition process can be visualized and understood better. The application of the DynaFRAM helps enhance the situation awareness of frail patients through providing healthcare providers with where a patient is and what they need during the transition process. Coupling the FRAM and reinforcement learning would benefit the healthcare system by providing guidance on how to provide the best care to frail patients in the light of various circumstances. ¹The transition model is called comprehensive as it includes the perspectives of healthcare professionals, patients, and caregivers. It also involves pre-discharge and post-discharge processes

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Is my medical software allowed to go to market?

The central importance of software in healthcare practices is highlighted by the increasing regulation of medical software in order to safeguard medical activities and patient’s rights. Medical software suppliers need to meet regulatory requirements from different countries to gain market access and offer necessary compliant solutions. The present report focuses on providing methods and tools to allow software suppliers to evaluate which software products should be sold in which countries. Using design science and behavioral science two artifacts are presented integrating influence of regulatory requirements on market access and product lifecycle management. It is required to present all the regulatory information in an actionable way in order for it to be operationalized by businesses and engineering staff within a company

Transitional Challenges in Technology Adoption among Academic Communities in Indian Higher Education Institutions

Due to the lockdown and remote working practices, academic universities around the world have been forced to adopt new technology. Online courses and exams enabled the use of new applications. During the pandemic, innovative technological adoption became faster, overriding the usual diffusion time lag. The transition was so fast that it presented a slew of new challenges to India\u27s academic communities. An open-ended online survey was used to gather data from faculty members, students, and non-teaching staff at higher educational institutions. Several concepts about transitional challenges emerged from the qualitative data analysis. The results revealed the significant commitment needed to implement modern online technologies, the lack of necessary resources, and the obstacles that participants\u27 home environments presented for teaching and learning. There were also questions about the effectiveness of online learning as well as anxiety and stress could cause. Participants\u27 suggestions unraveled the importance of flexibility and change needed for the appraisal and evaluation methods employed in higher education. The results expanded the notion of the rate of adoption under the diffusion of innovation theory. The study results shed light on how academic institutions could create successful technology adoption procedures for remote learning policies