16 research outputs found

    Smart Query Answering for Marine Sensor Data

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    We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks

    A Dynamic Data-driven Decision Support for Aquaculture Farm Closure

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    We present a dynamic data-driven decision support for aquaculture farm closure. In decision support, we use machine learning techniques in predicting closures of a shellfish farm. As environmental time series are used in closure, we propose two approaches using time series and machine learning for closure prediction. In one approach, we consider time series prediction and then usingexpert rulesto predict closure. In otherapproach,we usetime seriesclassificationfor closure prediction. Both approaches exploit a dynamic data-driven technique where prediction models are updated with the update of new data to predict closure decisions. Experimental results at a case study shellfish farm validate the applicability of the proposed method in aquaculture decision support

    Towards the preservation of functional dependency in XML data transformation

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    With the advent of XML as a data representation and exchange format over the web, a massive amount of data is being stored in XML. As the use of XML grows rapidly, the task of data transformation for integration purposes in XML is getting much importance to the research community. In XML data transformation, a source schema and its conforming data are transformed to a target schema and its conforming data respectively. The source schema often has integrity constraints to enforce semantics. One type of constraints is XML functional dependency (XFD). When a source schema is transformed to a target schema, XFDs can also be transformed. Thus, the problem how schema and data transformation should cause XFD transformation becomes important. In this paper, we study the transformation of XFDs. Towards this problem, we first define the XFDs over the XML document type definition (DTD) and the satisfactions of XFDs. We then show how XFDs are transformed and whether XFDs are valid when the DTDs are transformed. We further investigate whether the transformed XFDs are preserved by the transformed data.

    Perception and Barriers to Implementation of Intensive and Extensive Green Roofs in Dhaka, Bangladesh

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    Buildings are one of the biggest consumers of fossil fuels, and thus, contribute largely to greenhouse gas emissions. As a result, a large number of studies have been conducted and innovative ideas or green solutions have been invented, adopted, and implemented across the globe. These solutions are often contextual and heavily dependent on local environmental and socio-economic factors. Green roofs are such an example. Green roofs (both intensive and extensive) for buildings have been successfully adopted in many countries around the world. Bangladesh, a developing country that can benefit from green roofs, seems to remain in complete darkness regarding its potential. The objective of this study is to identify the reasons why green roofs have not been widely implemented in Bangladesh, especially in the capital Dhaka, even though, theoretically, the climatic conditions of this country favor this technology. This study focuses on the perception of the construction industry to comprehend the possible obstacles they are facing towards using green roofs in their designs. A questionnaire study was conducted among architects, engineers, construction managers, contractors, and owners who are at different levels of experience in their respective fields. The results indicate a gap in knowledge and misconceptions, which are major hindrances to the implementation of green roofs
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