88,638 research outputs found
Application of context knowledge in supporting conceptual design decision making
Conceptual design is the most important phase of the product life cycle as the decisions taken at conceptual design stage affect the downstream phases (manufacture, assembly, use, maintenance, and disposal) in terms of cost, quality and function performed by the product. This research takes a holistic view by incorporating the knowledge related to the whole context (from the viewpoint of product, user, product's life cycle and environment in which the product operates) of a design problem for the consideration of the designer to make an informed decision making at the conceptual design stage. The design context knowledge comprising knowledge from these different viewpoints is formalised and a new model and corresponding computational framework is proposed to support conceptual design decision making using this formalised context knowledge. Using a case study, this paper shows the proof of the concept by selecting one concept among different design alternatives using design context knowledge thereby proactively supporting conceptual design decision making for an informed and effective decision making
Designing theoretically-informed implementation interventions.
Canadian Institutes of Health Research; Ontario Ministry of Healt
Recommended from our members
Designing theoretically-informed implementation interventions
Clinical and health services research is continually producing new findings that may contribute to effective and efficient patient care. However, the transfer of research findings into practice is unpredictable and can be a slow and haphazard process. Ideally, the choice of implementation strategies would be based upon evidence from randomised controlled trials or systematic reviews of a given implementation strategy. Unfortunately, reviews of implementation strategies consistently report effectiveness some, but not all of the time; possible causes of this variation are seldom reported or measured by the investigators in the original studies. Thus, any attempts to extrapolate from study settings to the real world are hampered by a lack of understanding of the effects of key elements of individuals, interventions, and the settings in which they were trialled. The explicit use of theory offers a way of addressing these issues and has a number of advantages, such as providing: a generalisable framework within which to represent the dimensions that implementation studies address, a process by which to inform the development and delivery of interventions, a guide when evaluating, and a way to allow for an exploration of potential causal mechanisms. However, the use of theory in designing implementation interventions is methodologically challenging for a number of reasons, including choosing between theories and faithfully translating theoretical constructs into interventions. The explicit use of theory offers potential advantages in terms of facilitating a better understanding of the generalisability and replicability of implementation interventions. However, this is a relatively unexplored methodological area
Visual Integration of Data and Model Space in Ensemble Learning
Ensembles of classifier models typically deliver superior performance and can
outperform single classifier models given a dataset and classification task at
hand. However, the gain in performance comes together with the lack in
comprehensibility, posing a challenge to understand how each model affects the
classification outputs and where the errors come from. We propose a tight
visual integration of the data and the model space for exploring and combining
classifier models. We introduce a workflow that builds upon the visual
integration and enables the effective exploration of classification outputs and
models. We then present a use case in which we start with an ensemble
automatically selected by a standard ensemble selection algorithm, and show how
we can manipulate models and alternative combinations.Comment: 8 pages, 7 picture
Growing Philanthropy through Giving Circles: Lessons Learned from Start-up to Grantmaking
Individual donors coming together to pool their funds and to make grants, that is the idea behind giving circles. Emerging as a new trend in the United States, giving circles are typically organized around a particular issue or area of interest and are considered a high engagement form of philanthropy. The circle's grantmaking functions, proposal review, and site visits engage members in a participatory process that, when combined with the increased impact of pooled charitable resources, has strong appeal to many donors. The Baltimore Giving Project, housed at the Association of Baltimore Area Grantmakers (USA), has supported the growth of many giving circles since 2000. Its report details the growth and lessons learned from two of these circles
- âŠ