A distributed simulation methodology for large-scale hybrid modelling and simulation of emergency medical services

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonHealthcare systems are traditionally characterised by complexity and heterogeneity. With the continuous increase in size and shrinkage of available resources, the healthcare sector faces the challenge of delivering high quality services with fewer resources. Healthcare organisations cannot be seen in isolation since the services of one such affects the performance of other healthcare organisations. Efficient management and forward planning, not only locally but rather across the whole system, could support healthcare sector to overcome the challenges. An example of closely interwoven organisations within the healthcare sector is the emergency medical services (EMS). EMS operate in a region and usually consist of one ambulance service and the available accident and emergency (A&E) departments within the coverage area. EMS provide, mainly, pre-hospital treatment and transport to the appropriate A&E units. The life-critical nature of EMS demands continuous systems improvement practices. Modelling and Simulation (M&S) has been used to analyse either the ambulance services or the A&E departments. However, the size and complexity of EMS systems constitute the conventional M&S techniques inadequate to model the system as a whole. This research adopts the approach of distributed simulation to model all the EMS components as individual and composable simulations that are able to run as standalone simulation, as well as federates in a distributed simulation (DS) model. Moreover, the hybrid approach connects agent-based simulation (ABS) and discrete event simulation (DES) models in order to accommodate the heterogeneity of the EMS components. The proposed FIELDS Framework for Integrated EMS Large-scale Distributed Simulation supports the re-use of existing, heterogeneous models that can be linked with the High Level Architecture (HLA) protocol for distributed simulation in order to compose large-scale simulation models. Based on FIELDS, a prototype ABS-DES distributed simulation EMS model was developed based on the London EMS. Experiments were conducted with the model and the system was tested in terms of performance and scalability measures to assess the feasibility of the proposed approach. The yielded results indicate that it is feasible to develop hybrid DS models of EMS that enables holistic analysis of the system and support model re-use. The main contributions of this thesis is a distributed simulation methodology that derived along the process of conducting this project, the FIELDS framework for hybrid EMS distributed simulation studies that support re-use of existing simulation models, and a prototype distributed simulation model that can be potentially used as a tool for EMS analysis and improvement.MATCH Programm

IoT and analytical practices in traditional industries: A view of the farming and agricultural sector

IoT and analytical practices in traditional industries: A view of the farming and agricultural secto

The Reproducibility and Reusability Platform

Poster presentation at OR2020, Stellenboch, South Africa 1st - 4th June 2020

Science Reproducibility and Reusability with FutureGateway and a Zenodo-like repository: the PALMS experiment

Open Science (OS) is a powerful and novel paradigm to share knowledge across multidisciplinary scientific communities with the aim to improve the quality of science. One of the most important OS enablers are the FAIR principles, which involves the way to Find, Access, Interoperate and Reuse research data. In most of the cases published scholarship materials are not linked with computed datasets, open source software and/or virtualized computing environments and OS currently lacks of means helping to reproduce and eventually reuse cited results exploiting public or private distributed computing infrastructures (DCIs). Moreover, from the final user point of view, the best option would be the use of graphical user interfaces (GUIs) normally hosted by a Science Gateway (SG) built for a specific scientific community. The FutureGateway Framework (FGF) consists of a complete software toolkit made of different parts such as: source codes, utilities, libraries and APIs capable to comfortably build reliable Science Gateways and link them to one or more DCIs avoiding any usage complexity from the final user perspective. Moreover, since SGs based on the FGF are capable to keep track of who is accessing the DCIs, not only its usage ensures OS-compliant reproducibility and reusability but also provides a possible answer in protecting or at least simply tracking people who are accessing data and this is one of the aspects that today still makes the adoption of the OS a delicate matter. This work presents and explains how the use of the EGI's Science Software on Demand (SSOD) service, built using the FutureGatewayFramework in conjunction with the INFN Open Access Repository (OAR), based on Zenodo software, can reproduce/reuse the outputs of the agent-based Physical Activity Lifelong Modelling & Simulations (PALMS) experiment

Science Reproducibility and Reusability with FutureGateway and a Zenodo-like repository: the PALMS experiment

Open Science (OS) is a powerful and novel paradigm to share knowledge across multidisciplinary scientific communities with the aim to improve the quality of science. One of the most important OS enablers are the FAIR principles, which involves the way to Find, Access, Interoperate and Reuse research data. In most of the cases published scholarship materials are not linked with computed datasets, open source software and/or virtualized computing environments and OS currently lacks of means helping to reproduce and eventually reuse cited results exploiting public or private distributed computing infrastructures (DCIs). Moreover, from the final user point of view, the best option would be the use of graphical user interfaces (GUIs) normally hosted by a Science Gateway (SG) built for a specific scientific community. The FutureGateway Framework (FGF) consists of a complete software toolkit made of different parts such as: source codes, utilities, libraries and APIs capable to comfortably build reliable Science Gateways and link them to one or more DCIs avoiding any usage complexity from the final user perspective. Moreover, since SGs based on the FGF are capable to keep track of who is accessing the DCIs, not only its usage ensures OS-compliant reproducibility and reusability but also provides a possible answer in protecting or at least simply tracking people who are accessing data and this is one of the aspects that today still makes the adoption of the OS a delicate matter. This work presents and explains how the use of the EGI's Science Software on Demand (SSOD) service, built using the FutureGatewayFramework in conjunction with the INFN Open Access Repository (OAR), based on Zenodo software, can reproduce/reuse the outputs of the agent-based Physical Activity Lifelong Modelling & Simulations (PALMS) experiment

Science Reproducibility and Reusability with FutureGateway and a Zenodo-like repository: the PALMS experiment

Open Science (OS) is a powerful and novel paradigm to share knowledge across multidisciplinary scientific communities with the aim to improve the quality of science. One of the most important OS enablers are the FAIR principles, which involves the way to Find, Access, Interoperate and Reuse research data. In most of the cases published scholarship materials are not linked with computed datasets, open source software and/or virtualized computing environments and OS currently lacks of means helping to reproduce and eventually reuse cited results exploiting public or private distributed computing infrastructures (DCIs). Moreover, from the final user point of view, the best option would be the use of graphical user interfaces (GUIs) normally hosted by a Science Gateway (SG) built for a specific scientific community. The FutureGateway Framework (FGF) consists of a complete software toolkit made of different parts such as: source codes, utilities, libraries and APIs capable to comfortably build reliable Science Gateways and link them to one or more DCIs avoiding any usage complexity from the final user perspective. Moreover, since SGs based on the FGF are capable to keep track of who is accessing the DCIs, not only its usage ensures OS-compliant reproducibility and reusability but also provides a possible answer in protecting or at least simply tracking people who are accessing data and this is one of the aspects that today still makes the adoption of the OS a delicate matter. This work presents and explains how the use of the EGI's Science Software on Demand (SSOD) service, built using the FutureGatewayFramework in conjunction with the INFN Open Access Repository (OAR), based on Zenodo software, can reproduce/reuse the outputs of the agent-based Physical Activity Lifelong Modelling & Simulations (PALMS) experiment

Detection of Fake Generated Scientific Abstracts

The widespread adoption of Large Language Models and publicly available ChatGPT has marked a significant turning point in the integration of Artificial Intelligence into people's everyday lives. The academic community has taken notice of these technological advancements and has expressed concerns regarding the difficulty of discriminating between what is real and what is artificially generated. Thus, researchers have been working on developing effective systems to identify machine-generated text. In this study, we utilize the GPT-3 model to generate scientific paper abstracts through Artificial Intelligence and explore various text representation methods when combined with Machine Learning models with the aim of identifying machine-written text. We analyze the models' performance and address several research questions that rise during the analysis of the results. By conducting this research, we shed light on the capabilities and limitations of Artificial Intelligence generated text

Archimedes Interdisciplinary Research Programme Forges a Broad Spectrum of Academic Innovations

The basic goal of Archimedes III is to support research teams in Greek Technological Educational Institutes (TEI) and enhance their research capabilities by funding interdisciplinary and inter-institutional research. The programme aims also at attracting talented researchers and developing high quality research personnel. The TEIs, prior to their advancement to the tertiary sector in 2000, focused only on educational activities. Since then, development of research became part of their mission. In order for the Ministry of Education to support TEIsto develop their research capabilities, it designed research programmes targeting exclusively these organisations. Archimedes I and II were designed and ran in the previous programming period (2000-2006) while Archimedes III has been designed in the framework of the Operational Programme "Education and lifelong learning” of the current programming period, 2007-2013. The programme supports research projects in all research fields. However, particular emphasis is given to the fields of engineering and ICT where the main strengths of Greek Technological Educational Institutes are concentrated. The specific project of the TEI of Central Greece, described herewith, comprises 8 research subprojects in fields such as health, environment, energy and ICT with one additional subproject dedicated to management and dissemination. This paper is a comprehensive account of the research objectives and accomplishments of the research project as a whole. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Archimedes Interdisciplinary Research Programme Forges a Broad Spectrum of Academic Innovations

The basic goal of Archimedes III is to support research teams in Greek Technological Educational Institutes (TEI) and enhance their research capabilities by funding interdisciplinary and inter-institutional research. The programme aims also at attracting talented researchers and developing high quality research personnel. The TEIs, prior to their advancement to the tertiary sector in 2000, focused only on educational activities. Since then, development of research became part of their mission. In order for the Ministry of Education to support TEIsto develop their research capabilities, it designed research programmes targeting exclusively these organisations. Archimedes I and II were designed and ran in the previous programming period (2000-2006) while Archimedes III has been designed in the framework of the Operational Programme "Education and lifelong learning” of the current programming period, 2007-2013. The programme supports research projects in all research fields. However, particular emphasis is given to the fields of engineering and ICT where the main strengths of Greek Technological Educational Institutes are concentrated. The specific project of the TEI of Central Greece, described herewith, comprises 8 research subprojects in fields such as health, environment, energy and ICT with one additional subproject dedicated to management and dissemination. This paper is a comprehensive account of the research objectives and accomplishments of the research project as a whole. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

Montage: An Astronomical Image Mosaic Service for the NVO

Montage is a software system for generating astronomical image mosaics according to user-specified size, rotation, WCS-compliant projection and coordinate system, with background modeling and rectification capabilities. Its architecture has been described in the proceedings of ADASS XII and XIII (Berriman et al. 2003, 2004). It has been designed as a toolkit, with independent modules for image reprojection, background rectification and co-addition, and will run on workstations, clusters and grids. The primary limitation of Montage thus far has been in the projection algorithm. It uses a spherical trigonometry approach that is general at the expense of speed. The reprojection algorithm has now been made 30 times faster for commonly used tangent plane to tangent plane reprojections that cover up to several square degrees, through modification of a custom algorithm first derived for the Spitzer Space Telescope. This focus session will describe this algorithm, demonstrate the generation of mosaics in real time, and describe applications of the software. In particular, we will highlight one case study which shows how Montage is supporting the generation of science-grade mosaics of images measured with the Infrared Array Camera aboard the Spitzer Space Telescope