Jülich DATA

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Jülich DATA is the central institutional repository for research data of Forschungszentrum Jülich.

It serves as a platform for all research data generated at Forschungszentrum Jülich or created in this context. Please feel welcome to index your research data here.

This service is managed by the Central Library. Please see our guide about how to use this service or feel free to reach out via email to forschungsdaten@fz-juelich.de.

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16,541 to 16,550 of 17,318 Results

ParticlePhase_AerosolLiquidWater_ConcentrationData_timeseries.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 154.9 KB - SHA-256: 8b41fc7b28e428dbac5e2d2a523868582fbf583ba7518b7a1c338d12f3d44e1b Time-series of aerosol liquid water in micrograms per cubic meter (ugm3). The value -9999 is given to non-existing data. File delimiter is the tabstop.
ParticlePhase_AMS_ConcentrationData_timeseries.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 398.4 KB - SHA-256: 9dd6ca94a422f5b36ae847285c6f1c345d4eb84b45b8f94d85af64e0b1d07826 Time-series of aerosol organics, nitrate, ammonium, sulfate, and chloride in micrograms per cubic meter (ugm3) as derived by an Aerosol Mass Spectrometer. The value -9999 is given to non-existing data. File delimiter is the tabstop.
PositiveMatrixFactorization_GasPhase_Profiles.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 9.8 KB - SHA-256: ec01f533a753dcd5eb94419a459d707cd7d9e8f97a1c95b991bd63d8d67b2967 Profiles of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.
PositiveMatrixFactorization_GasPhase_Timeseries.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 409.5 KB - SHA-256: 1c6f5dfe7162cee14e48b6774e38d6d6d7ec1bcac4f499cf8fdc75bedbde8d36 Time-series of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.
PositiveMatrixFactorization_ParticlePhase_Profiles.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 53.5 KB - SHA-256: 92f62d627219d8612a516446e96e3ca0363d969e236b233907141346619979dc Profiles of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.
PositiveMatrixFactorization_ParticlePhase_Timeseries.csv Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) Plain Text - 375.8 KB - SHA-256: 04c1af1388f28d4c534155be6c3d685120a5638862450b3a9345a04170125da1 Time-series of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.
ELPVPower: A dataset for large scale PV power prediction using EL images of cells Aug 28, 2020 - EL images Dataverse Hoffmann, Mathis; Buerhop-Lutz, Claudia; Reeb, Luca; Pickel, Tobias; Winkler, Thilo; Doll, Bernd; Würfl, Tobias; Peters, Ian Marius; Brabec, Christoph J.; Maier, Andreas; Christlein, Vincent, 2020, "ELPVPower: A dataset for large scale PV power prediction using EL images of cells", https://doi.org/10.26165/JUELICH-DATA/TVWUUP, Jülich DATA, V1 Measurements are provided in the folder `data` as PNG-Images. The original measurements have been rescaled to the range [0, 255] globally, such that intensities between measurements are comparable. The dataset comes with a file `data.csv` that provides additional meta data associ...
000.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 496.9 KB - SHA-256: d837586cda00ba70a3ed49c4a535bc733dde111a3602ba42143ef879d54246ca
001.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 498.1 KB - SHA-256: a5cf5cc388feda09438db6932a60e6eab10974eb02246797c3b29ec6e3f6640c
002.png Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells PNG Image - 498.2 KB - SHA-256: d7053a268e34a7b395e63bca9d889f876efbba54f32d18efc0d7c1ed23427311

ParticlePhase_AerosolLiquidWater_ConcentrationData_timeseries.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 154.9 KB - SHA-256: 8b41fc7b28e428dbac5e2d2a523868582fbf583ba7518b7a1c338d12f3d44e1b

Time-series of aerosol liquid water in micrograms per cubic meter (ugm3). The value -9999 is given to non-existing data. File delimiter is the tabstop.

ParticlePhase_AMS_ConcentrationData_timeseries.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 398.4 KB - SHA-256: 9dd6ca94a422f5b36ae847285c6f1c345d4eb84b45b8f94d85af64e0b1d07826

Time-series of aerosol organics, nitrate, ammonium, sulfate, and chloride in micrograms per cubic meter (ugm3) as derived by an Aerosol Mass Spectrometer. The value -9999 is given to non-existing data. File delimiter is the tabstop.

PositiveMatrixFactorization_GasPhase_Profiles.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 9.8 KB - SHA-256: ec01f533a753dcd5eb94419a459d707cd7d9e8f97a1c95b991bd63d8d67b2967

Profiles of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.

PositiveMatrixFactorization_GasPhase_Timeseries.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 409.5 KB - SHA-256: 1c6f5dfe7162cee14e48b6774e38d6d6d7ec1bcac4f499cf8fdc75bedbde8d36

Time-series of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.

PositiveMatrixFactorization_ParticlePhase_Profiles.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 53.5 KB - SHA-256: 92f62d627219d8612a516446e96e3ca0363d969e236b233907141346619979dc

Profiles of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.

PositiveMatrixFactorization_ParticlePhase_Timeseries.csv

Nov 3, 2020 - 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Plain Text - 375.8 KB - SHA-256: 04c1af1388f28d4c534155be6c3d685120a5638862450b3a9345a04170125da1

Time-series of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.

ELPVPower: A dataset for large scale PV power prediction using EL images of cells

Aug 28, 2020 - EL images Dataverse

Hoffmann, Mathis; Buerhop-Lutz, Claudia; Reeb, Luca; Pickel, Tobias; Winkler, Thilo; Doll, Bernd; Würfl, Tobias; Peters, Ian Marius; Brabec, Christoph J.; Maier, Andreas; Christlein, Vincent, 2020, "ELPVPower: A dataset for large scale PV power prediction using EL images of cells", https://doi.org/10.26165/JUELICH-DATA/TVWUUP, Jülich DATA, V1

Measurements are provided in the folder `data` as PNG-Images. The original measurements have been rescaled to the range [0, 255] globally, such that intensities between measurements are comparable. The dataset comes with a file `data.csv` that provides additional meta data associ...

000.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 496.9 KB - SHA-256: d837586cda00ba70a3ed49c4a535bc733dde111a3602ba42143ef879d54246ca

001.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 498.1 KB - SHA-256: a5cf5cc388feda09438db6932a60e6eab10974eb02246797c3b29ec6e3f6640c

002.png

Aug 28, 2020 - ELPVPower: A dataset for large scale PV power prediction using EL images of cells

PNG Image - 498.2 KB - SHA-256: d7053a268e34a7b395e63bca9d889f876efbba54f32d18efc0d7c1ed23427311

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