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Process evaluation of European ‘Healthy Stadia’ program
"... Healthy Stadia (HS) is a European public health pilot-program started in 2007 to support sports stadia in promot-ing the health of people who work and visit sports stadia, as well as inhabitants of the surrounding communities. The aim of this study is to describe the process evaluation of the progra ..."
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Healthy Stadia (HS) is a European public health pilot-program started in 2007 to support sports stadia in promot-ing the health of people who work and visit sports stadia, as well as inhabitants of the surrounding communities. The aim of this study is to describe the process evaluation of the program, from its beginning in July 2007 to December 2009, in order to assess the feasibility and sustainability of an HS network across Europe. The program involved nine associate partners involved in the coordination of activities at a local level, in the recruitment of stadia, in the develop-ment of specific program tasks and in the dissemination of the program at a national level. The activities of associate partners were evaluated through structured questionnaires administered every 6 months. The questionnaire response rate from associate partners was 77.8 % for the first and third evaluations and 88.9 % for the second and fourth eva-luations. According to the evaluation’s results, several good practices such as alcohol prevention policies and those sup-porting people with disabilities were implemented in stadia over the course of the program. Conversely, practices sup-porting mental health and green transport were generally not achieved. The implemented activities mainly involved staff and visitors. Lack of human and economic resources, especially toward the end of the program, was considered the principal challenge for program development. In con-clusion, the process evaluation presented the feasibility of the HS program and the development of health promoting practices in sport stadia over time. Key words: settings approach; health promotion programs; evaluating health promotion; process evaluation
1.3. THE CONVENTIONAL DEVELOPMENT PARADIGM 3 1.4. SUSTAINABILITY: A NEW DEVELOPMENT PRINCIPLE 4
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Systems Thinking in Biology – The case for Qualitative Representations and Reasoning 1
"... Although biology textbooks are still full of factual knowledge, the tendency to teach science using a systems perspective is emerging. Qualitative representations are well suited to express, reason and communicate systems knowledge, particularly for science education. This contribution shows how a s ..."
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Although biology textbooks are still full of factual knowledge, the tendency to teach science using a systems perspective is emerging. Qualitative representations are well suited to express, reason and communicate systems knowledge, particularly for science education. This contribution shows how a systems perspective can be imposed on typical problems taken from biology textbooks. The presented approach is generic and can be transferred to other areas such as economics and physics. Moreover, the detailed and explicit representations inherent to the Qualitative Reasoning approach make it possible to build knowledgeable dialogue systems, all working on the same underlying domain independent representation. 1.
A Common Framework for Qualitative and Quantitative Modelling
, 2007
"... The paper introduces model ensembles as a common framework for understanding qualitative differential equations (QDEs) and differential inclusions in a precise mathematical sense. It provides basic insights into the communalities and differences of both approaches to model under uncertainty. On this ..."
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The paper introduces model ensembles as a common framework for understanding qualitative differential equations (QDEs) and differential inclusions in a precise mathematical sense. It provides basic insights into the communalities and differences of both approaches to model under uncertainty. On this basis, a set of established methods for QDEs, some hybrid methods and standard quantitative methods can be classified, the notion of a “spurious behaviour” is clarified more thoroughly, and the importance of generality as a concept complementary to uncertainty is underpinned. Further paths for extending qualitative reasoning are outlined.
A Qualitative Learning System for Human Sensory Abilities in Adjustment Tasks
"... The development of learning systems based on expert knowledge is moving towards inclusion of cognitive processes. Creating, designing and adjusting are essential decision processes in highly creative industries, such as the paint, perfume, food and beverage sectors. These processes require continuou ..."
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The development of learning systems based on expert knowledge is moving towards inclusion of cognitive processes. Creating, designing and adjusting are essential decision processes in highly creative industries, such as the paint, perfume, food and beverage sectors. These processes require continuous supervision and participation of professionals with highlydeveloped expert sensory abilities. This paper proposes a new methodology that uses on a machine learning tool (previously trained with ‘state-action ’ type patterns provided by experts) as well as an actions ’ generator module. The methodology proposed is applied to a real case study: color-adjustment in the automotive painting industry.
Copyright c ○ 2012, The University of AberdeenQML-Morven: A Novel Framework for Learning Qualitative Models
, 2012
"... Abstract: In this report, a novel qualitative model learning (QML) framework named QML-Morven is presented. QML-Morven is an extensible framework and currently includes three QML subsystems, which employ either symbolic or evolutionary approaches as their learning strategies. QML-Morven uses the for ..."
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Abstract: In this report, a novel qualitative model learning (QML) framework named QML-Morven is presented. QML-Morven is an extensible framework and currently includes three QML subsystems, which employ either symbolic or evolutionary approaches as their learning strategies. QML-Morven uses the formalism of Morven, a fuzzy qualitative simulator, to represent and reason about qualitative models, and it also utilises Morven to verify candidate models. Based on this framework, a series ofexperiments were designed and carried out to: (1) verify the results obtained by the previous QML system ILP-QSI; (2) investigate factors that influence the learning precision and minimum data requirement for successful learning; (3) address the scalability issue of QML systems.
