956 resultados para Process uncertainty


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Complexity is a major concern which is aimed to be overcome by people through modeling. One way of reducing complexity is separation of concerns, e.g. separation of business process from applications. One sort of concerns are cross-cutting concerns i.e. concerns which are scattered and tangled through one of several models. In business process management, examples of such concerns are security and privacy policies. To deal with these cross-cutting concerns, the aspect orientated approach was introduced in the software development area and recently also in the business process management area. The work presented in this paper elaborates on aspect oriented process modelling. It extends earlier work by defining a mechanism for capturing multiple concerns and specifying a precedence order according to which they should be handled in a process. A formal syntax of the notation is presented precisely capturing the extended concepts and mechanisms. Finally, the relevant of the approach is demonstrated through a case study.

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This chapter describes a university/high school partnership focused on digital storytelling. It also explains the multi-stage process used to establish this successful partnership and project. The authors discuss the central role that technology played in developing this university/high school partnership, a collaboration that extended the impact of a digital storytelling project to reach high school students, university students, educators, high school administrators, and the local community. Valuing a reflective process that can lead to the creation of a powerful final product, the authors describe the impact of digital storytelling on multiple stakeholders, including the 13 university students and 33 culturally and linguistically diverse high school youth who participated during the fall of 2009. In addition, the chapter includes reflections from university and high school student participants expressed during focus groups conducted throughout the project. While most participants had a positive experience with the project, complications with the technology component often caused frustrations and additional challenges. Goals for sharing this project are to critically evaluate digital storytelling, describe lessons learned, and recommend good practices for others working within a similar context or with parallel goals.

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Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

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User needs are a fundamental element of design. If the design process does not properly reflect user needs, the design will be severely compromised. Therefore, it is worthwhile to investigate how the user is, and user needs are, understood in the design process. In this article, three accepted linear process models for web site and interactive media design are reviewed in terms of the designer and user participation. The article then proposes a user-evolving collaborative design process which is built on co-creation activities between designer and user. Co-creation activities across the entire design process structurally and ontologically reposition the users, and user needs, centrally, which allows the designers to holistically approach to the user needs through building a partnership with the users. Co-creation creates an equal evolving participatory process between user and designer towards sharing values and knowledge and creating new domains of collective creativity.

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This paper is a selected review of research on issues surrounding the investigation of intra-familial child sexual abuse for children aged eight and above, in the criminal justice system. Particular attention is paid to features of the investigative interview in relation to the child's level of understanding, ability to report and likely emotional response when the proceedings take place. Best practice by police and social care agencies involves establishing valid and reliable information from children while attending to their developmental level and emotional state. The review aims to distil principles optimising this process from both the investigative judicial perspective and the child's focus, as well as from the inter-agency perspective and information sharing. Recommendations are made for improving the interview process based on research and methods from a range of disciplines and to optimise information recording in a format easily shared between agencies. Updated and ongoing training procedures are key to successful practice with training shared across police and social work agencies. The focus of this review is informed by preliminary findings from pilot research in progress on behalf of the Metropolitan Police Child Abuse Investigation Command.

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The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.