11 research outputs found

    Traditional kinship structures and European-derived diseases at Mission San Diego, California : a study of the 1805-1806 measles epidemic

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    "May 2014."Dissertation Supervisor: Dr. Lisa Sattenspiel.Includes vita.European diseases were a significant cause of morbidity and mortality in Native American communities after contact with any European colonizers. Studies of Native Californian communities have documented the effects of European diseases such as smallpox, measles and whooping cough, but only at a few of the 21 Spanish missions established during the Mission Period and primarily late in the historic period. This study used archival and historical records, combined with later ethnographic materials, to investigate the potential impact of a measles epidemic in 1806. This epidemic was documented at other missions and was known to have caused mortality of up to 25% in certain populations, but no direct evidence of illness was recorded at Mission San Diego. Using an agent-based model designed to reflect both the structure of the historic population and the behavioral patterns of neophyte populations, simulated measles epidemics in the mission population were examined. Simulation results indicate that the pattern of recorded deaths in the winter of 1805/1806 is not consistent with a virgin soil measles epidemic (as produced by the model), but could not rule out measles as a cause of increased deaths.Includes bibliographical references (pages 138-149)

    Best-subset Selection for Complex Systems using Agent-based Simulation

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    It is difficult to analyze and determine strategies to control complex systems due to their inherent complexity. The complex interactions among elements make it difficult to develop and test decision makers' intuition of how the system will behave under different policies. Computer models are often used to simulate the system and to observe both direct and indirect effects of alternative interventions. However, many decision makers are unwilling to concede complete control to a computer model because of the abstractions in the model, and the other factors that cannot be modeled, such as physical, human, social and organizational relationship constraints. This dissertation develops an agent-based simulation (ABS) model to analyze a complex system and its policy alternatives, and contributes a best-subset selection (BSS) procedure that provides a group of good performing alternatives to which decision makers can then apply their subject and context knowledge in making a final decision for implementation. As a specific example of a complex system, a mass casualty incident (MCI) response system was simulated using an ABS model consisting of three interrelated sub-systems. The model was then validated by a series of sensitivity analysis experiments. The model provides a good test bed to evaluate various evacuation policies. In order to find the best policy that minimizes the overall mortality, two ranking-and-selection (R&S) procedures from the literature (Rinott (1978) and Kim and Nelson (2001)) were implemented and compared. Then a new best-subset selection (BSS) procedure was developed to efficiently select a statistically guaranteed best-subset containing all alternatives that are close enough to the best one for a pre-specified probability. Extensive numerical experiments were organized to prove the effectiveness and demonstrate the performance of the BSS procedure. The BSS procedure was then implemented in conjunction with the MCI ABS model to select the best evacuation policies. The experimental results demonstrate the feasibility and effectiveness of our agent-based optimization methodology for complex system policy evaluation and selection

    C-EMO: A Modeling Framework for Collaborative Network Emotions

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    Recent research in the area of collaborative networks is focusing on the social and organizational complexity of collaboration environments as a way to prevent technological failures and consequently contribute for the collaborative network’s sustainability. One direction is moving towards the need to provide “human-tech” friendly systems with cognitive models of human factors such as stress, emotion, trust, leadership, expertise or decision-making ability. In this context, an emotion-based system is being proposed with this thesis in order to bring another approach to avoid collaboration network’s failures and help in the management of conflicts. This approach, which is expected to improve the performance of existing CNs, adopts some of the models developed in the human psychology, sociology and affective computing areas. The underlying idea is to “borrow” the concept of human-emotion and apply it into the context of CNs, giving the CN players the ability to “feel emotions”. Therefore, this thesis contributes with a modeling framework that conceptualizes the notion of “emotion” in CNs and a methodology approach based on system dynamics and agent-based techniques that estimates the CN player’s “emotional states” giving support to decision-making processes. Aiming at demonstrating the appropriateness of the proposed framework a simulation prototype was implemented and a validation approach was proposed consisting of simulation of scenarios, qualitative assessment and validation by research community peers.Recentemente a área de investigação das redes colaborativas tem vindo a debruçar-se na complexidade social e organizacional em ambientes colaborativos e como pode ser usada para prevenir falhas tecnológicas e consequentemente contribuir para redes colaborativas sustentáveis. Uma das direcções de estudo assenta na necessidade de fornecer sistemas amigáveis “humano-tecnológicos” com modelos cognitivos de factores humanos como o stress, emoção, confiança, liderança ou capacidade de tomada de decisão. É neste contexto que esta tese propõe um sistema baseado em emoções com o objectivo de oferecer outra aproximação para a gestão de conflitos e falhas da rede de colaboração. Esta abordagem, que pressupõe melhorar o desempenho das redes existentes, adopta alguns dos modelos desenvolvidos nas áreas da psicologia humana, sociologia e affective computing. A ideia que está subjacente é a de “pedir emprestado” o conceito de emoção humana e aplicá-lo no contexto das redes colaborativas, dando aos seus intervenientes a capacidade de “sentir emoções”. Assim, esta tese contribui com uma framework de modelação que conceptualiza a noção de “emoção” em redes colaborativas e com uma aproximação de metodologia sustentada em sistemas dinâmicos e baseada em agentes que estimam os “estados emocionais” dos participantes e da própria rede colaborativa. De forma a demonstrar o nível de adequabilidade da framework de modelação proposta, foi implementado um protótipo de simulação e foi proposta uma abordagem de validação consistindo em simulação de cenários, avaliação qualitativa e validação pelos pares da comunidade científica

    Powering Accra: Projecting Electricity Demand for Ghana‘s Capital City

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    The purpose of this research was to create an agent-based urban simulation based on land use at the plot level for projecting the disaggregated electricity demand of the Greater Accra Metropolitan Area (GAMA). A simulation system comprised of location choice, regression, and simple models were used to project household, employment and land development decisions. Households, persons, and jobs tables were synthetically generated from GLSS5 (Ghana Living Standards Survey 2005) data using Stata, built in a MySQL database and incorporated for use in the Open Platform for Urban Simulation (OPUS). Electricity demand was projected for each of the simulation years based on a regression model. Numerous geospatial datasets were projected and edited in ArcGIS which describe the physical composition of Accra in its totality, including buildings, roads and electricity infrastructure. Household mobility was estimated from a modified Cox Regression of residential mobility in Accra (Bertrand et al.) and applied to the GLSS5 for use in the location choice model, while employment coefficients and parameters describing land value were derived from literature (Buckley et al.). The model has been applied for projecting the electricity demand of the Korle Bu district in terms of high, medium and low economic and population growth rates for the time period 2006 until 2025, based on monthly electricity consumption per meter. An additional phase of this research envisions including all 12 GAMA districts (using data which has been obtained); infrastructure models to project demand for transportation, water & sewer, and solid waste facilities; as well as comparing weak and strong sustainability scenarios with the business-as-usual development path for cost-benefit analysis of proposed public policies

    Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

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    This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

    Advances in Computational Social Science and Social Simulation

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    Aquesta conferència és la celebració conjunta de la "10th Artificial Economics Conference AE", la "10th Conference of the European Social Simulation Association ESSA" i la "1st Simulating the Past to Understand Human History SPUHH".Conferència organitzada pel Laboratory for Socio­-Historical Dynamics Simulation (LSDS-­UAB) de la Universitat Autònoma de Barcelona.Readers will find results of recent research on computational social science and social simulation economics, management, sociology,and history written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences constitute annual events which serve as an international platform for the exchange of ideas and discussion of cutting edge research in the field of social simulations, both from the theoretical as well as applied perspective, and the 2014 edition benefits from the cross-fertilization of three different research communities into one single event. The volume consists of 122 articles, corresponding to most of the contributions to the conferences, in three different formats: short abstracts (presentation of work-in-progress research), posters (presentation of models and results), and full papers (presentation of social simulation research including results and discussion). The compilation is completed with indexing lists to help finding articles by title, author and thematic content. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of computational social sciences and social simulation researc

    Computer simulation research for Infant Industry Theory based on Repast Simphony

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    Through analyzing logical defects of Friedrich List’s infant industry theory, this paper obtains two hypothesis. One is that no industry is with single product portfolios, and so it is difficult for the developed countries defeating under-developed countries’ infant industry completely according to the comparative advantage theory. This implies that under-developed country could obtain more survival opportunities if it leverages appropriate product diverse strategies. The other hypothesis is protecting infant industry by tariff barriers would increase the cost of whole society, which slows down the development of infant industry, and that damaging interests of both backward country and powerful country. We construct a computer simulation model on Repast Simphony platform to verify the above two hypothesizes, and our simulation results show that the above two hypotheses make sense. We also got an unexpected result that it will lead to significant decline of the yield of the infant industry if one country in the trade exerts tariff barriers, meanwhile, the yield of the other countries will also decline but the decreased amount of the infant industry of the under-developed country obviously exceed the developed country, which means the trade protection damages both side of trade and the underdeveloped country get more injury. That implies the assumption of the tariff barriers protecting and accelerating the development of infant industry does not make sense

    Computer simulation research for Infant Industry Theory based on Repast Simphony

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    Agent-based modelling of social risk amplification during product crises

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    Public response to risk is socially shaped in a way that often over- or under-estimates expert risk assessments. One of the main theoretical tools to examine public risk perception is the social amplification of risk framework (SARF). This framework proposes a mechanism through which risk responses arise from interactions among various social actors, but past empirical work has been mainly concerned with correlations between structural variables rather than the mechanism of amplification and the process over time by which it develops. And more importantly, there has been quite limited modelling of risk amplification to date. This study aims to discover a way of formalising social risk amplification, to find out what are the necessary assumptions for modelling risk amplification, and to work out what consequences this modelling would predict. It is an attempt to model collective response to risks that are significant at a societal level but which materialise in a distributed way across a population. The natural heterogeneity of individual risk perceivers, the emergence of behaviour through interactions of social actors, and the complex feedback loops linking risk perception with risk related behaviour point to using an agent-based model as a modelling medium. The study is developed in the context of product contamination scandals such as the recent cases in China of contaminated milk products. One of the important features of contamination crises is that product recall has become an increasingly inevitable part and is often a key element in risk communication during such crises. Yet recalls send ambiguous signals about the misconduct of the organization in question: they clearly indicate some kind of failure, and possibly negligence, in the product that are associated with a risk of significant harm; but they also suggest that the organization is concerned with consumers’ welfare. The model that was developed is based on the principle that risk perceivers have to assimilate risk through the risk beliefs of others, their direct experience of a risk, and communications about the risk from organizations (including their product recall decisions) and the media. And it is based on the principle that, as well as discovering the nature of a risk, risk perceivers also make judgments about wrongfulness (which Freudenburg called recreancy) – and this also shapes the strength of risk responses. The model is partially calibrated with a consumer survey carried out in the context of a Chinese milk contamination scandal that took place in recent years. Simulation results from the model show that public risk perception grows progressively toward an exogenous peak before it immediately decays, and that there is a relatively high residue of concern after the crisis is resolved. The objectivity of media coverage appears to be inversely related to risk amplification: a media that simply follows public opinion is associated more strongly with exaggerated risk perceptions than an objective one. A sensitivity analysis indicates that the initial conditions, objective risk level, duration of contamination, and variation of recreancy perception are the most significant influences on the degree of social amplification. This knowledge helps prioritize data collection for future research and identify important aspects that particularly require managerial attention. The main contribution of this study is to develop a process of modelling social risk amplification that consists of three steps of increasing contextualisation. The first step involves a basic model that captures social risk amplification as a general theory relative to all kinds of risk event. The second step contextualises this model specifically for product recall crises. It involves extracting agent decision rules from the literature on product recall, based on statistical associations found in empirical work on recall crises. And the third step contextualises the model for a specific population. It involves calibrating the relative importance of different information sources for the heterogeneous agent population using a survey of Chinese consumers responding to a milk contamination crisis. One important insight from the process of modelling risk amplification is that SARF is not sufficient for modelling particular crises. It seems essential that modelling of SARF should involve a clearly defined context in which risk responses arise
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