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Search results for: fotogrametria cyfrowa
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The XRD diffraction patterns of Ce(Pr,Sm)O2-s samples
Open Research DataThe dataset includes XRD diffraction patterns of Ce(Pr,Sm)O2-s samples of various stoichiometries of Pr and Sm dopants. Samples were produced using aqueous soft chemistry methods (microemulsion method).
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The electrical properties mesurements of SOFC with Ce0.8Pr0.15Sm0.05O2-s layer
Open Research DataThe dataset includes The electrical properties mesurements of SOFC with Ce0.8Pr0.15Sm0.05O2-s layer. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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The electrical properties mesurements of SOFC with Ce0.8Pr0.2O2-s layer
Open Research DataThe dataset includes The electrical properties mesurements of SOFC with Ce0.8Pr0.2O2-s layer. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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The electrical properties mesurements of SOFC with Ce0.8Sm0.2O2-s layer
Open Research DataThe dataset includes The electrical properties mesurements of SOFC with Ce0.8Sm0.2O2-s layer. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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The electrical properties mesurements of SOFC with Ce0.8Pr0.1Sm0.1O2-s layer
Open Research DataThe dataset includes The electrical properties mesurements of SOFC with Ce0.8Pr0.1Sm0.1O2-s layer. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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The electrical properties mesurements of SOFC with Ce0.8Pr0.05Sm0.15O2-s layer
Open Research DataThe dataset includes The electrical properties mesurements of SOFC with Ce0.8Pr0.05Sm0.15O2-s layer. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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Impact of binary mixtures of diclofenac and buthylparaben of the model organism Saccharomyces Cerevisiae (using XenoScreen YES/YAS test)
Open Research DataData shown in data set illustrate the results of the edorin processes of miture of diclofenac and buthylparaben on S cerevisiae is used as a model organism in the monitoring of endocrine disruptors in environmental and reference samples in Xenometrix® systems - XenoScreen®. Tested substances have bakeriosis and fungicide properties and are used in...
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Impact of binary mixtures of Irgasan (triclosan) and two parabens on endocrine processes of the model organism Saccharomyces Cerevisiae (using XenoScreen YES/YAS test)
Open Research DataData shown in data set illustrate the results of the edorin processes of the Irgasan (triclosan) mixture with two parabens e.i. methylparaben and buthylparaben. S cerevisiae is used as a model organism in the monitoring of endocrine disruptors in environmental and reference samples in Xenometrix® systems - XenoScreen®. Tested substances have bakeriosis...
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Impact of binary mixtures of Irgasan (triclosan) and Diclofenac on endocrine processes of the model organism Saccharomyces Cerevisiae (using XenoScreen YES/YAS test)
Open Research DataThe XenoScreen YES/YAS reagents and methodology is given in Kudłak et al. (2019) and in details in electronic supplementary material.
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Impact of binary mixtures of diclofenac and on endocrine processes of the model organism Saccharomyces Cerevisiae (using XenoScreen YES/YAS test)
Open Research DataData shown in data set highlighte the results of the edorin processes of the diclofenac sodium salt mixture with Methylparaben. S cerevisiae is used as a model organism in the monitoring of endocrine disruptors in environmental and reference samples in Xenometrix® systems - XenoScreen®. Methylparaben have fungicide properties used in food preservative,...
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Gdańsk district - scale 1:10000. Data from OSM
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Kartuzy district - scale 1:10000. Data from OSM.
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The changes of outlet gases concentrations from SOFC with Ce(Pr,Sm)O2-s layers
Open Research DataThe dataset includes The changes of outlet gases concentrations from SOFC with Ce(Pr,Sm)O2-s layers. Samples were produced using aqueous soft chemistry methods (microemulsion method) and applied in form of a layer onto the anode of the commercial SOFC. The SOFC was working under biogas feeding.
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Kartuzy district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Gdańsk district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Katowice district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Katowice district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Gdańsk district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Kartuzy district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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AVHRR Level1CD covering Baltic Sea area year 2006
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2010
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2007
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2011
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2012
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2008
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2009
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2001
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2005
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2004
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2003
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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AVHRR Level1CD covering Baltic Sea area year 2002
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...