Source control SUDS delivery on a global scale and in Scotland including approach by responsible organisations and professional groups

Background to researchThe Sustainable Urban Drainage Scottish Working Party via CREW commissioned this work on the implementation of source control for SUDS in Scotland. The project is being carried out by researchers based at Abertay University Dundee involves three phases. These are presented in separate reports; this report covers phase 2 of that work. Source control sustainable urban drainage systems (SUDS) are an established technique in many parts of the world. Source control SUDS are a key component of what is termed the stormwater treatment train. Source controls manage the more frequent but smaller polluting rainfall events as close to the source as possible (where the rain falls). Site and regional control SUDS are larger downstream structures which manage the longer term rainfall events and provide additional treatment when required. One of the key advantages of managing the more frequent rainfall events at source is that downstream site and regional SUDS will have longer life spans resulting in overall cost efficiencies. Scotland is regarded as a frontrunner in the UK regarding implementation of SUDS with site and regional drainage structures now considered ‘business as usual’. However the uptake of source control is less routine than would be expected.Objectives of researchPhase one of this research looked at the background to the evolution of source control in Scotland to provide an insight into the enabling factors and obstacles for uptake of the systems since. Phase two(this report) appraises delivery of the systems in seven countries and case studies are developed to understand why source control was implemented and how it was achieved. The current delivery by responsible organisations and professional groups which encourage and influence the source control agenda in Scotland is also appraised. Using these findings, the transition pathway from traditional drainage to source control SUDS are reconstructed and mapped out to highlight the historical and current enabling (and disabling) factors to realise the transition to date. A transition framework is used to highlight the transition strengths developed by responsible organisations over the last two decades which had assisted in accelerating the transition.Key findings and recommendationsKey outcomes of this research include:* In Scotland the source control vision and agenda is fragmented due to different stakeholder drivers and funding mechanisms.* There are examples of the use of incentives in Scotland (i.e. legislative, regulatory, financial,social and environmental) to drive integrated agendas. However these have not been successfully showcased to provide the evidence base for encouraging replication and up-scaling of the methodologies and techniques.* There are limited frontier source control SUDS ‘niches’ to nurture innovative techniques such as raingardens – a learning by doing concept. A more focused research agenda to validate these systems as viable sustainable solutions for Scotland would assist in accelerating uptake.* Lack of sector engagement, particularly with the public is a disabling factor for uptake.A final observation from this phase of the study is that requests from various interested parties for CREW / SUDS Working Party to share outputs indicates the need for this research

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

OLEMAR: An Online Environment for Mining Association Rules in Multidimensional Data

Data warehouses and OLAP (online analytical processing) provide tools to explore and navigate through data cubes in order to extract interesting information under different perspectives and levels of granularity. Nevertheless, OLAP techniques do not allow the identification of relationships, groupings, or exceptions that could hold in a data cube. To that end, we propose to enrich OLAP techniques with data mining facilities to benefit from the capabilities they offer. In this chapter, we propose an online environment for mining association rules in data cubes. Our environment called OLEMAR (online environment for mining association rules), is designed to extract associations from multidimensional data. It allows the extraction of inter-dimensional association rules from data cubes according to a sum-based aggregate measure, a more general indicator than aggregate values provided by the traditional COUNT measure. In our approach, OLAP users are able to drive a mining process guided by a meta-rule, which meets their analysis objectives. In addition, the environment is based on a formalization, which exploits aggregate measures to revisit the definition of the support and the confidence of discovered rules. This formalization also helps evaluate the interestingness of association rules according to two additional quality measures: lift and loevinger. Furthermore, in order to focus on the discovered associations and validate them, we provide a visual representation based on the graphic semiology principles. Such a representation consists in a graphic encoding of frequent patterns and association rules in the same multidimensional space as the one associated with the mined data cube. We have developed our approach as a component in a general online analysis platform called Miningcubes according to an Apriori-like algorithm, which helps extract inter-dimensional association rules directly from materialized multidimensional structures of data. In order to illustrate the effectiveness and the efficiency of our proposal, we analyze a real-life case study about breast cancer data and conduct performance experimentation of the mining process

Organic Farming Research in the EU, towards 21st Century

Contents - Executive Summary - Research in Organic Farming in the EU - Review of Crop Production and weed Control: State of Arts and Outlook - Soil Fertility in Organic Farming - Review of Animal Health and Welfare - Review of Grassland and Fodder Production - Legal and Economical Aspects - Review of Crop Protection - Conclusions. Recommendations for Future research in Organic Farmin

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor