The underlying vision of the Digital Earth(DE)calls for applications that can embed vast quantities of geo-referenced data and allow users to study and analyse of our planet.Since the declaration of this vision in the...The underlying vision of the Digital Earth(DE)calls for applications that can embed vast quantities of geo-referenced data and allow users to study and analyse of our planet.Since the declaration of this vision in the late 90s,a significant number of DE data-sets have been created by the industry,governments,non-governmental organisations and individuals.An overwhelming majority of the successful applications that use DE data-sets has its end-user applications running on the desktop.While these applications are great tools,they remain inaccessible to the community as a whole.In this paper,we present a framework for the development of cyber-applications.We define an abstract architecture for cyber-applications based on the model-view-controller paradigm,which allows the dynamic inclusion of functional and data components into its execution engine at run-time.We define the operational characteristics of cyber-applica-tions.We also specify the interface of pluggable components to the architecture.Finally,we demonstrate the appropriateness of the abstract architecture by means of a case study.展开更多
Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimen...Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.展开更多
文摘The underlying vision of the Digital Earth(DE)calls for applications that can embed vast quantities of geo-referenced data and allow users to study and analyse of our planet.Since the declaration of this vision in the late 90s,a significant number of DE data-sets have been created by the industry,governments,non-governmental organisations and individuals.An overwhelming majority of the successful applications that use DE data-sets has its end-user applications running on the desktop.While these applications are great tools,they remain inaccessible to the community as a whole.In this paper,we present a framework for the development of cyber-applications.We define an abstract architecture for cyber-applications based on the model-view-controller paradigm,which allows the dynamic inclusion of functional and data components into its execution engine at run-time.We define the operational characteristics of cyber-applica-tions.We also specify the interface of pluggable components to the architecture.Finally,we demonstrate the appropriateness of the abstract architecture by means of a case study.
基金This work was supported by the Malaysian Ministry of Education(SLAI)and Universiti Teknologi Malaysia(UTM).
文摘Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.
