354,817 research outputs found
A Framework to Manage the Complex Organisation of Collaborating: Its Application to Autonomous Systems
In this paper we present an analysis of the complexities of large group
collaboration and its application to develop detailed requirements for
collaboration schema for Autonomous Systems (AS). These requirements flow from
our development of a framework for collaboration that provides a basis for
designing, supporting and managing complex collaborative systems that can be
applied and tested in various real world settings. We present the concepts of
"collaborative flow" and "working as one" as descriptive expressions of what
good collaborative teamwork can be in such scenarios. The paper considers the
application of the framework within different scenarios and discuses the
utility of the framework in modelling and supporting collaboration in complex
organisational structures
Tooling-up for infectious disease transmission modelling.
In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be
Report and papers with guidelines on calibration of urban flood models
Computer modelling offers a sound scientific framework for well-structured analysis and
management of urban drainage systems and flooding. Computer models are tools that are expected
to simulate the behaviour of the modelled real system with a reasonable level of accuracy.
Assurance of accurate representation of reality by a model is obtained through the model
calibration. Model calibration is an essential step in modelling. This report present concepts and
procedures for calibration and verification of urban flood models. The various stages in the
calibration process are presented sequentially. For each stage, a discussion of general concepts is
followed by descriptions of process elements. Finally, examples and experiences regarding
application of the procedures in the CORFU Barcelona Case Study are presented.
Calibration involves not only the adjustment of model parameters but also other activities such as
model structural and functional validation, data checking and preparation, sensitivity analysis and
model verification, that support and fortify the calibration process as a whole. The objective in
calibration is the minimization of differences between model simulated results and observed
measurements. This is normally achieved through a manual iterative parameter adjustment process
but automatic calibration routines are also available, and combination parameter adjustment
methods also exist. The focus of a model calibration exercise is not the same for all types of models.
But regardless of the model type, good modelling practice should involve thorough model
verification before application.
A well-calibrated model can give the assurance that, at least for a range of tested conditions, the
model behaves like the real system, and that the model is an accurate and reliable tool that may be
used for further analysis. However, calibration could also reveal that the model cannot be calibrated
and that the correctness of the model and its suitability as a tool for analysis and management of
real-world systems could not be proven.
The conceptualisation and simplification of real-world systems and associated processes in
modelling inevitably lead to errors and uncertainty. Various modelling components introduce errors
such as the input parameters, the model concept, scheme and corresponding model output, and the
observed response measurements. Ultimately, the quality of the model as quantified by how much
it deviates from reality is an aggregate of the errors that have been brought into it during the
modelling process. Thus, it is important to identify the different error sources in a model and also
account for and quantify them as part of the modelling.The work described in this publication was supported by the European Community’s Seventh Framework Programme through the grant to the budget of CORFU
Collaborative Research on Flood Resilience in Urban Areas, Contract 244047
Alternative representations for visual constrainst specification in the layered view model
Extensible Markup Language (XML), with its rich set of semantics and constraints, is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS) and databases. With the increased reliance on such semi-structured data and schemas, there exists a requirement to model, design, and constrain semi-structured data and the associated semantics at a higher level of abstraction than at the instance or data level. But most semi-structured schema languages lack the ability to provide higher levels of abstraction, such as visual constraints, that are easily understood by humans. Conversely, though Object-Oriented (OO) conceptual models offers the power in describing and modelling real-world data semantics, constraints and their inter-relationships in a form that is precise and comprehensible to users, they provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints. Therefore, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we present a visual constraint specification model for an XML layered view model. First we briefly outline the view model and then provide a detailed discussion on modelling issues related to view constraint specification using two OO modelling languages, namely OMG's UML/OCL and XML Semantics (XSemantic) nets. To demonstrate our concepts, we also provide an illustrative case study example based on a real-world application
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