High performance computing based simulation for healthcare decision support

Due to the complexity and crucial role of an Emergency Department (ED) in the healthcare system. The ability to more accurately represent, simulate and predict performance of ED will be invaluable for decision makers to solve management problems. One way to realize this requirement is by modeling and simulation. The objective of this research is to grasp the non-linear association between macro-level features and micro-level behavior with the goal of better understanding the bottleneck of ED performance and provide ability to quantify such performance on defined condition. Agent-based modeling approach was used to model the healthcare staff, patient and physical resources in ED. Instead of describe all the potential causes of this complex issue. Rather, in this thesis, a layerbased application framework will be presented to discover knowledge of a complex system through simulating micro-level behaviors of its components to facilitate a systematic understanding of the aggregate behavior

Modeling Of Socio-economic Factors And Adverse Events In An Active War Theater By Using A Cellular Automata Simulation Approach

Department of Defense (DoD) implemented Human Social Cultural and Behavior (HSCB) program to meet the need to develop capability to understand, predict and shape human behavior among different cultures by developing a knowledge base, building models, and creating training capacity. This capability will allow decision makers to subordinate kinetic operations and promote non-kinetic operations to govern economic programs better in order to initiate efforts and development to address the grievances among the displeased by adverse events. These non-kinetic operations include rebuilding indigenous institutions’ bottom-up economic activity and constructing necessary infrastructure since the success in non-kinetic operations depends on understanding and using social and cultural landscape. This study aims to support decision makers by building a computational model to understand economic factors and their effect on adverse events. In this dissertation, the analysis demonstrates that the use of cellular automata has several significant contributions to support decision makers allocating development funds to stabilize regions with higher adverse event risks, and to better understand the complex socio-economic interactions with adverse events. Thus, this analysis was performed on a set of spatial data representing factors from social and economic data. In studying behavior using cellular automata, cells in the same neighborhood synchronously interact with each other to determine their next states, and small changes in iteration may yield to complex formations of adverse event risk after several iterations of time. The modeling methodology of cellular automata for social and economic analysis in this research was designed in two major implementation levels as follows: macro and micro-level. In the macro-level, the modeling framework integrates iv population, social, and economic sub-systems. The macro-level allows the model to use regionalized representations, while the micro-level analyses help to understand why the events have occurred. Macro-level subsystems support cellular automata rules to generate accurate predictions. Prediction capability of cellular automata is used to model the micro-level interactions between individual actors, which are represented by adverse events. The results of this dissertation demonstrate that cellular automata model is capable of evaluating socio-economic influences that result in changes in adverse events and identify location, time and impact of these events. Secondly, this research indicates that the socioeconomic influences have different levels of impact on adverse events, defined by the number of people killed, wounded or hijacked. Thirdly, this research shows that the socio-economic, influences and adverse events that occurred in a given district have impacts on adverse events that occur in neighboring districts. The cellular automata modeling approach can be used to enhance the capability to understand and use human, social and behavioral factors by generating what-if scenarios to determine the impact of different infrastructure development projects to predict adverse events. Lastly, adverse events that could occur in upcoming years can be predicted to allow decision makers to deter these events or plan accordingly if these events do occur

e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit

The impact of human relationship on bankruptcy-related evolution of inter-firm trade network

This paper studies the impact of human relationship on the evolution of inter-firm trade network emerged from bankruptcy. Based on the extracted properties of Japanese firm data in 10 years, we propose an agent-based model and conduct series of simulation experiments to evaluate several aspects of human relationship effects. The simulation results indicate that human relationship delays the bankrupt spread and promotes the average performance of firms. By examining different scenarios, we found the influential features of human relationship that are likely to help firms to survive in the bankrupt propagation process

Urban land expansion model based on SLEUTH, a case study in Dongguan city, China

The SLEUTH urban model is developed with sets of predefined growing rules involving Spontaneous Growth, New Spreading Center Growth, Edge Growth, Road Influenced Growth and Self-modification. They are applied continuously to lead the urban simulation to a specific morphology. A SLEUTH land use model was set up to simulate urban growth trajectory of Dongguan city from 1997 to 2009. The accuracy of localized parameters was evaluated to illuminate the growth pattern of Dongguan. Two different scenarios were set to predict the urban development from 2022 to 2030. Edge Growth is the dominant force of Dongguan's urbanization: regions adjacent to growth centers are more likely to be urbanized than remote area in general. Rapid urban expansion takes up large amount of other land types, around 2030, urbanization will reach the critical state in spatial. Unlike excessive growth rate in scenario 1, the urbanization speed is obviously more reasonable and sustainable in scenario 2, which confirms SLEUTH urban model is a good assistant of urban planning to avoid willful expansion with a scenario forecast. To protect ecological environment and promoting sustainable development of the region, relevant decision makers should take effective strategies to control urban sprawl. By the set of forecast scenarios, SLEUTH can certainly predict future urban development as an auxiliary to urban planners and government.Dongguan is under rapid urbanization in these decades. SLEUTH is an urban land use model named after the six input layers (Slope, Land use, Excluded, Urban, Transportation and Hill shade), and it is applied for simulating how surrounding land use changes due to urban expansion. A SLEUTH model was coupled with multi-source GIS (Geographic Information Systems) and RS (Remote Sensing) data to simulate urban growth trajectory of Dongguan city from 1997 to 2009. The accuracy of localized parameters was evaluated to illuminate the growth pattern of Dongguan. Based on the hypothesis that the urbanization process is as fast as before, a historical scenario from 2010 to 2050 was built up to choose the suitable study periods. In order to prove SLEUTH is able to offer reasonable outcomes for urban plan, two different scenarios were set to predict the urban development from 2022 to 2030, which shows SLEUTH is able to offer reasonable outcomes to government policy makers. Finally, the dynamic mechanism of urban growth combined with local characteristics was discussed. Some suggestions were also proposed for future urban planning and policy making in this study

Architecting system of systems: artificial life analysis of financial market behavior

This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as promoters or inhibitors of change in human systems. Computational intelligence tools have been successfully used in analysis of Complex Adaptive Systems. Since a System of Systems is a collection of Complex Adaptive Systems, a framework utilizing combination of these tools can be developed. Financial markets are selected to demonstrate the various architectures developed from the analysis framework --Introduction, page 3

A Comprehensive Study on Pedestrians' Evacuation

Human beings face threats because of unexpected happenings, which can be avoided through an adequate crisis evacuation plan, which is vital to stop wound and demise as its negative results. Consequently, different typical evacuation pedestrians have been created. Moreover, through applied research, these models for various applications, reproductions, and conditions have been examined to present an operational model. Furthermore, new models have been developed to cooperate with system evacuation in residential places in case of unexpected events. This research has taken into account an inclusive and a 'systematic survey of pedestrian evacuation' to demonstrate models methods by focusing on the applications' features, techniques, implications, and after that gather them under various types, for example, classical models, hybridized models, and generic model. The current analysis assists scholars in this field of study to write their forthcoming papers about it, which can suggest a novel structure to recent typical intelligent reproduction with novel features

Understanding Urban Mobility and Pedestrian Movement

Urban environments continue to expand and mutate, both in terms of size of urban area and number of people commuting daily as well as the number of options for personal mobility. City layouts and infrastructure also change constantly, subject to both short-term and long-term imperatives. Transportation networks have attracted particular attention in recent years, due to efforts to incorporate “green” options, enabling positive lifestyle choices such as walking or cycling commutes. In this chapter we explore the pedestrian viewpoint, aids to familiarity with and ease of navigation in the urban environment, and the impact of novel modes of individual transport (as options such as smart urban bicycles and electric scooters increasingly become the norm). We discuss principal factors influencing rapid transit to daily and leisure destinations, such as schools, offices, parks, and entertainment venues, but also those which facilitate rapid evacuation and movement of large crowds from these locations, characterized by high occupation density or throughput. The focus of the chapter is on understanding and representing pedestrian behavior through the agent-based modeling paradigm, allowing both large numbers of individual actions with active awareness of the environment to be simulated and pedestrian group movements to be modeled on real urban networks, together with congestion and evacuation pattern visualization

Integrated nonlinear modelling strategies for the seismic analysis of masonry structures

In the last decades, significant interest has raised in modelling and analysing the structural response of unreinforced masonry (URM) buildings. This aims at conceiving and designing effective interventions to reduce the vulnerability towards seismic actions. Studies based on costly structural testing are often limited to few benchmark cases, making numerical modelling an excellent option to extend experimental results and a valid solution for understanding URM structural behaviour. Advanced discrete models are widely employed among the available numerical strategies to predict the URM dynamic response, thanks to their ability to account for the heterogeneous nature of masonry and to simulate its behaviour up to the complete collapse. If, on the one hand, the low degree of idealisation of discrete models allows their employment for the extension of experimental tests, on the other hand, they require expert users, the definition of a large number of mechanical parameters and a high computational effort. This last drawback often limits the use of advanced discontinuum models in the engineering practice or for seismic risk studies, which require the execution of multiple analyses. In this work, a modelling approach, based on the Applied Element Method (AEM), was combined with more simplified models to exploit the discrete model potential and overcome its limits. To this aim, the AEM was employed as a benchmark to calibrate/validate simplified modelling strategies, improving their reliability when compared to advanced model outcomes. In this context, AEM models were used as a reference to enhance the Equivalent Frame Model (e.g. the presence of irregular distribution of openings) and to validate a new strength criterion associated with the failure mechanism encountered in a new masonry typology. In the absence of a large suite of experimental tests exploring all the possible setup or configurations, the AEM can provide precious information. On the other hand, the AEM can help to investigate situations requiring a higher level of detail, such as the design of the timber retrofitting system analysed in this work. The ability of the AEM to simulate the structural behaviour up to the complete collapse was also used to investigate the effect of different percentages of ground floor opening on the dynamic response of Dutch terraced houses, performing benchmark analyses to calibrate SDOF models employed for the development of fragility functions associated with the different layouts. Finally, AEM models were employed for substructuring façade models of masonry buildings whose global response was effectively studied by equivalent frame models. The aim of the study was to predict the debris extent involved in the collapse of URM façades in case of earthquake loadings. Such an integrated numerical procedure allowed considering a large suite of seismic inputs, overcoming the time-consuming issue