Summary of achievements Sample Clauses

Summary of achievements. Summarize major results and achievements and evaluate them compared with the objectives.
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Summary of achievements. The CITYkeys set of indicators consists of a mixture of quantitative and semi-quantitative indicators. The semi-quantitative indicators for example provide an assessment of the way smart city projects are executed, the way the city government stimulates smart city development and of the potential of smart city projects to be taken up by other cities. For the semi-quantitative indicators data needs to be collected using interviews or an analysis of project or policy documents. There is a difference in the data collection process between the project and the city indicators. The project indicators are meant for assessing the success and potential for replication of smart city projects. In individual project assessments data needs to be collected from the project office, the project leader and/or others closely involved in the project. Cities might want to streamline the data collection for all their smart city projects, creating a reporting system and specific databases, but even then a number of the project indicators will require (qualitative) information that can only be gathered by involving persons involved in the project (e.g. through interviews, questionnaires). Data for the majority of the city indicators can be retrieved from statistical sources within the city administration or national or European level. The problem of such data is that it typically presents average (annual) figures for the whole city. For a city it may however be more interesting to analyse the differences between districts. Spatial data makes it possible to calculate indicators also for geographically restricted areas such as city districts. It is expected that CITYkeys testing phase will allow, to some extent, the evaluation of a project’s impact on city level as CITYkeys KPIs contain project-to-city link for many indicators. Additional sources of open data and public data can be found in national or European institutions (e.g. statistics bureaus). In any case, national data sources provide excellent support for data availability in all the five partner cities. EUROSTAT is potentially also of support for many data, but the problem is that information is given for regions and not for cities or municipalities as defined nationally. It is important to note that data for all indicators will obviously not be available immediately. A city that engages in smart city indicators starts a process. The CITYkeys indicator framework is a methodology for such a process. The city will need to ...
Summary of achievements. For the 55 outputs contracted for delivery SACTCG delivered a total of 128. Key Outputs • 19 events • 17 grant applications • 59 individual communication pieces Partners and stakeholders • 11 small community groups, members of SACTCG, were supported under this program, including 3 new member groups. • 18 partners were engaged in the delivery of the 3 workplans. Below is a sample list: o University of Canberra o SEE-Change Tuggeranong o Tuggeranong Community Council o Woden Community Council x Xxxxxx resident’s association o Wanniassa Shops Association o Australian Association of Environmental Education (AAEE) ACT Chapter o Holy Family Primary School Gowrie o Lake Tuggeranong College o Bunnings - multiple locations Future work These programs have built significant momentum in community stewardship of public lands in Southern ACT. They have established strong foundation partnerships for both the delivery of community engagement and education activities that will grow these programs in 2020-2021.
Summary of achievements. We briefly summarise what has been achieved with this model. The model is intended as an illustration. When the informal safety requirements have been finalised, this model may require revision to make it more realistic. For example the model does not consider the possibility of track being bi-directional. Other formalisations of the safety requirements may also be required in other formal notations. The model illustrates how some example hazards can be used to derive safety requirements. To derive safety requirements it was first necessary to introduce some concepts that are present in the domain. We also made explicit which hazards are not covered by an interlocking system. The four invariants given in Figure 5.8 are a formalisation of the relevant safety requirements in terms of these domain concepts. In addition, we introduced some very abstract behaviour and proved that this behaviour satisfies the formalised safety requirements. By modelling the safety requirements and a behaviour that is safe, and proving this to be true, we gain confidence that the safety requirements are consistent. By keeping the model simple and abstract we gain confidence that the safety requirements are correct. We should also validate the model by animation. Using refinement (according to the Rodin tools upon which UML-B is based) it would be possible to make this abstract model more detailed until it describes an interlocking system. The Rodin tools force us to prove that the more detailed model is a proper refinement of this abstract one and hence that the interlocking system also satisfies these safety requirements.

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