Recent decades have seen an increasing importance of large-scale ecological research, driven by i... more Recent decades have seen an increasing importance of large-scale ecological research, driven by increased awareness of the global influence of human activities on the biosphere. Such research requires species observation data covering many years, large areas and a broad range of taxonomic groups. As such data sets often cover small areas, and have been collected using varying methods, they can only be combined in a single analysis if they are made available at the same location and translated into a single format. Over the past decade, catalysed by the growth of the Internet, various technologies for data dissemination and data integration have been developed and applied in projects such as the Global Biodiversity Information Facility, the Knowledge Network for Biocomplexity, BioCASE and the British National Biodiversity Network (NBN). In the Netherlands, data are now made available from the National Database of Flora and Fauna (NDFF), which currently contains approximately 40 million observation records covering a broad variety of species. The NDFF uses a standardised, semantically integrated data model to combine effectively species observation data of various kinds. In this paper, we evaluate this approach and the NDFF data model, by comparison with Darwin Core, Access to Biological Collections Data (ABCD) and the Recorder 2000 model used by the NBN. We conclude that the high degree of standardisation in the NDFF data model has led to somewhat increased cost in data conversion, but also to improved semantic integration and ease-ofuse of species observation data. Together with the relative simplicity, completeness and flexibility of the model, this enables effective reuse of species observations in a user-friendly manner.
Recent decades have seen an increasing importance of large-scale ecological research, driven by i... more Recent decades have seen an increasing importance of large-scale ecological research, driven by increased awareness of the global influence of human activities on the biosphere. Such research requires species observation data covering many years, large areas and a broad range of taxonomic groups. As such data sets often cover small areas, and have been collected using varying methods, they can only be combined in a single analysis if they are made available at the same location and translated into a single format. Over the past decade, catalysed by the growth of the Internet, various technologies for data dissemination and data integration have been developed and applied in projects such as the Global Biodiversity Information Facility, the Knowledge Network for Biocomplexity, BioCASE and the British National Biodiversity Network (NBN). In the Netherlands, data are now made available from the National Database of Flora and Fauna (NDFF), which currently contains approximately 40 million observation records covering a broad variety of species. The NDFF uses a standardised, semantically integrated data model to combine effectively species observation data of various kinds. In this paper, we evaluate this approach and the NDFF data model, by comparison with Darwin Core, Access to Biological Collections Data (ABCD) and the Recorder 2000 model used by the NBN. We conclude that the high degree of standardisation in the NDFF data model has led to somewhat increased cost in data conversion, but also to improved semantic integration and ease-ofuse of species observation data. Together with the relative simplicity, completeness and flexibility of the model, this enables effective reuse of species observations in a user-friendly manner.
Abstra t The Distributed ASCI Super omputer (DAS) is a homogeneous wide-area distributed system o... more Abstra t The Distributed ASCI Super omputer (DAS) is a homogeneous wide-area distributed system onsisting of four luster omputers at di erent lo ations. DAS has been used for resear h on ommuni ation software, parallel languages and programming systems, s hedulers, parallel appli ations, and distributed appli ations. The paper gives a preview of the most interesting resear h results obtained so far in the DAS proje t. 1 1 More information about the DAS proje t an be found on http://www. s.vu.nl/das/
The BAMBAS (Bird Avoidance Model/Bird Avoidance System) team aims at developing a Bird Avoidance ... more The BAMBAS (Bird Avoidance Model/Bird Avoidance System) team aims at developing a Bird Avoidance Model (BAM) to predict spatial (horizontal and vertical) and temporal bird densities under changing meteorological conditions. The BAM will be used as a decision support tool for experts in the Royal Netherlands Air Force providing bird hazard warnings in real time and predictions for flight planning to reduce the risk of bird aircraft collisions. The BAM consists of several models that will be linked after their completion. In this paper we present results from the flight altitude and bird distribution models and describe how these will be integrated into an operating system. The distribution of birds in the Netherlands is being modelled based using the large SOVON database of a spatially dense network of counts in the breeding season and around Christmas. Observations have been analysed in relation to several variables including land cover, landscape characteristics, and vegetation to interpolate densities at places and at times where measurements are lacking. Regression analysis and spatial statistics have been integrated to develop these predictions, visualized in GIS. These spatial distributions with low temporal resolution were combined with time series obtained from systematic daily observations at airfields, to generate a 2D+time evolution over 25 years. Several models have been developed that predict flight altitudes of birds using different flight strategies in relation to local meteorological conditions. A bird's flight altitude and flight strategy is strongly influenced by weather. Weather has a stronger influence on the flight altitudes of birds using predominantly soaring and gliding flight. The main factors influencing flight altitudes differ between flight strategy groups. Local real time or forecast weather conditions are used as input to the flight altitude models directly linked to the distribution models to create the high-resolution full 3D+time predictions of bird densities under changing environmental conditions.
Recent superscalar processors highly depend on ecient branch prediction to exploit instruction le... more Recent superscalar processors highly depend on ecient branch prediction to exploit instruction level parallelism. Many strategies to improve branch prediction accuracy have been proposed, the most successful ones can adapt predictions dynamically based on the outcomes of previous branches. In this paper we present a dierent strategy, that is partially non{adaptive. We will show that patterns in the outcomes of individual branch instructions are more important than the global pattern of consecutive branch instructions and we will show that some patterns in the outcomes of branch instructions are much more frequent than other patterns. We will propose a classication of patterns in outcomes of individual branch instructions, based on their frequentness and how well they can be predicted by Two Level Adaptive Branch Predictors. We will analyze six traces of benchmark applications with respect to the occurrence of these patterns. We will present a mechanism (HW, Hard Wired) that dynamically discriminates between instructions based on this categorization. This mechanism can predict trivial and loop patterns almost perfectly with a hard wired look{up table. We will discuss the usage of HW as a prediction strategy in its own and its usage as a pre{stage to other branch prediction strategies. \Predicting is hard, especially the future." Winston Churchill Chapter 1
The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting... more The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project.
Recent decades have seen an increasing importance of large-scale ecological research, driven by i... more Recent decades have seen an increasing importance of large-scale ecological research, driven by increased awareness of the global influence of human activities on the biosphere. Such research requires species observation data covering many years, large areas and a broad range of taxonomic groups. As such data sets often cover small areas, and have been collected using varying methods, they can only be combined in a single analysis if they are made available at the same location and translated into a single format. Over the past decade, catalysed by the growth of the Internet, various technologies for data dissemination and data integration have been developed and applied in projects such as the Global Biodiversity Information Facility, the Knowledge Network for Biocomplexity, BioCASE and the British National Biodiversity Network (NBN). In the Netherlands, data are now made available from the National Database of Flora and Fauna (NDFF), which currently contains approximately 40 million observation records covering a broad variety of species. The NDFF uses a standardised, semantically integrated data model to combine effectively species observation data of various kinds. In this paper, we evaluate this approach and the NDFF data model, by comparison with Darwin Core, Access to Biological Collections Data (ABCD) and the Recorder 2000 model used by the NBN. We conclude that the high degree of standardisation in the NDFF data model has led to somewhat increased cost in data conversion, but also to improved semantic integration and ease-ofuse of species observation data. Together with the relative simplicity, completeness and flexibility of the model, this enables effective reuse of species observations in a user-friendly manner.
Recent decades have seen an increasing importance of large-scale ecological research, driven by i... more Recent decades have seen an increasing importance of large-scale ecological research, driven by increased awareness of the global influence of human activities on the biosphere. Such research requires species observation data covering many years, large areas and a broad range of taxonomic groups. As such data sets often cover small areas, and have been collected using varying methods, they can only be combined in a single analysis if they are made available at the same location and translated into a single format. Over the past decade, catalysed by the growth of the Internet, various technologies for data dissemination and data integration have been developed and applied in projects such as the Global Biodiversity Information Facility, the Knowledge Network for Biocomplexity, BioCASE and the British National Biodiversity Network (NBN). In the Netherlands, data are now made available from the National Database of Flora and Fauna (NDFF), which currently contains approximately 40 million observation records covering a broad variety of species. The NDFF uses a standardised, semantically integrated data model to combine effectively species observation data of various kinds. In this paper, we evaluate this approach and the NDFF data model, by comparison with Darwin Core, Access to Biological Collections Data (ABCD) and the Recorder 2000 model used by the NBN. We conclude that the high degree of standardisation in the NDFF data model has led to somewhat increased cost in data conversion, but also to improved semantic integration and ease-ofuse of species observation data. Together with the relative simplicity, completeness and flexibility of the model, this enables effective reuse of species observations in a user-friendly manner.
Abstra t The Distributed ASCI Super omputer (DAS) is a homogeneous wide-area distributed system o... more Abstra t The Distributed ASCI Super omputer (DAS) is a homogeneous wide-area distributed system onsisting of four luster omputers at di erent lo ations. DAS has been used for resear h on ommuni ation software, parallel languages and programming systems, s hedulers, parallel appli ations, and distributed appli ations. The paper gives a preview of the most interesting resear h results obtained so far in the DAS proje t. 1 1 More information about the DAS proje t an be found on http://www. s.vu.nl/das/
The BAMBAS (Bird Avoidance Model/Bird Avoidance System) team aims at developing a Bird Avoidance ... more The BAMBAS (Bird Avoidance Model/Bird Avoidance System) team aims at developing a Bird Avoidance Model (BAM) to predict spatial (horizontal and vertical) and temporal bird densities under changing meteorological conditions. The BAM will be used as a decision support tool for experts in the Royal Netherlands Air Force providing bird hazard warnings in real time and predictions for flight planning to reduce the risk of bird aircraft collisions. The BAM consists of several models that will be linked after their completion. In this paper we present results from the flight altitude and bird distribution models and describe how these will be integrated into an operating system. The distribution of birds in the Netherlands is being modelled based using the large SOVON database of a spatially dense network of counts in the breeding season and around Christmas. Observations have been analysed in relation to several variables including land cover, landscape characteristics, and vegetation to interpolate densities at places and at times where measurements are lacking. Regression analysis and spatial statistics have been integrated to develop these predictions, visualized in GIS. These spatial distributions with low temporal resolution were combined with time series obtained from systematic daily observations at airfields, to generate a 2D+time evolution over 25 years. Several models have been developed that predict flight altitudes of birds using different flight strategies in relation to local meteorological conditions. A bird's flight altitude and flight strategy is strongly influenced by weather. Weather has a stronger influence on the flight altitudes of birds using predominantly soaring and gliding flight. The main factors influencing flight altitudes differ between flight strategy groups. Local real time or forecast weather conditions are used as input to the flight altitude models directly linked to the distribution models to create the high-resolution full 3D+time predictions of bird densities under changing environmental conditions.
Recent superscalar processors highly depend on ecient branch prediction to exploit instruction le... more Recent superscalar processors highly depend on ecient branch prediction to exploit instruction level parallelism. Many strategies to improve branch prediction accuracy have been proposed, the most successful ones can adapt predictions dynamically based on the outcomes of previous branches. In this paper we present a dierent strategy, that is partially non{adaptive. We will show that patterns in the outcomes of individual branch instructions are more important than the global pattern of consecutive branch instructions and we will show that some patterns in the outcomes of branch instructions are much more frequent than other patterns. We will propose a classication of patterns in outcomes of individual branch instructions, based on their frequentness and how well they can be predicted by Two Level Adaptive Branch Predictors. We will analyze six traces of benchmark applications with respect to the occurrence of these patterns. We will present a mechanism (HW, Hard Wired) that dynamically discriminates between instructions based on this categorization. This mechanism can predict trivial and loop patterns almost perfectly with a hard wired look{up table. We will discuss the usage of HW as a prediction strategy in its own and its usage as a pre{stage to other branch prediction strategies. \Predicting is hard, especially the future." Winston Churchill Chapter 1
The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting... more The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project.
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Papers by Floris Sluiter