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Funding Information Agency: BMBF Subject: Engineering

1 to 10 of 797 Results

Code for Training and Testing CNVVE Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/darus-3896, DaRUS, V1 This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for...
Raw audio samples of the CNVVE dataset Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/darus-3897, DaRUS, V1 This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective fo...
SynDAB Dataset Jan 23, 2024 - SynDAB Müller, Manuel; Hagmanns, Raphael; Petereit, Janko; Egloffstein, Thomas; Weyrich, Lucas; Ebert, Christof; Weyrich, Michael, 2024, "SynDAB Dataset", https://doi.org/10.18419/darus-3758, DaRUS, V1 The dataset comprises a collection of images captured from the perspective of an excavator. The images depict a landfill with various environmental contexts. Specifically, various type of barrels are contained. Moreover, the dataset contains the simulated LiDAR data of these scen...
Self-diffusion coefficients of simulated aqueous glycerol mixtures Oct 28, 2022 - ThermoML Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous glycerol mixtures", https://doi.org/10.18419/darus-3115, DaRUS, V1 In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi...
Densities of simulated aqueous methanol mixtures Oct 28, 2022 - ThermoML Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3112, DaRUS, V1 In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi...
Self-diffusion coefficients of simulated aqueous methanol mixtures Oct 28, 2022 - ThermoML Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3114, DaRUS, V1 In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi...
Densities of simulated aqueous glycerol mixtures Oct 28, 2022 - ThermoML Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous glycerol mixtures", https://doi.org/10.18419/darus-3113, DaRUS, V1 In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi...
User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus" Sep 28, 2022 - Institute for Modelling and Simulation of Biomechanical Systems Saini, Harnoor, 2022, "User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"", https://doi.org/10.18419/darus-2229, DaRUS, V1 Background and Objective: Many biomedical, clinical, and industrial applications may benefit from musculoskeletal simulations. Three-dimensional macroscopic muscle models (3D models) can more accurately represent muscle architecture than their 1D (line-segment) counterparts. Neve...
3D CT-Data for KK17/5-09 Jul 29, 2022 - KK17/5-09 Kurskreisel-Komponente Mammadov, Gasim; Schweizer, Timo; Niklaus, Maria, 2021, "3D CT-Data for KK17/5-09", https://doi.org/10.18419/darus-1841, DaRUS, V2 Research data (mostly *.hdf5 format) which was obtained by scanning the object via Computed Tomography and generating a 3D inside view of the object with non-invasive means. This dataset is part of the digital gyroscope collection. For more information about the collection and it...
Information about KH22-10 Jul 29, 2022 - KH22-10 Künstlicher Horizont Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Wagner, Jörg F.; Zhan, Kun, 2021, "Information about KH22-10", https://doi.org/10.18419/darus-1486, DaRUS, V2 Pdf list containing all information collected about this object. For more information see entry in Goobi. This dataset is part of the digital gyroscope collection. For more information about the collection and its creation, please see the documentation dataset: Niklaus, Maria, 20...

Code for Training and Testing CNVVE

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/darus-3896, DaRUS, V1

This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for...

Raw audio samples of the CNVVE dataset

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/darus-3897, DaRUS, V1

This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective fo...

SynDAB Dataset

Jan 23, 2024 - SynDAB

Müller, Manuel; Hagmanns, Raphael; Petereit, Janko; Egloffstein, Thomas; Weyrich, Lucas; Ebert, Christof; Weyrich, Michael, 2024, "SynDAB Dataset", https://doi.org/10.18419/darus-3758, DaRUS, V1

The dataset comprises a collection of images captured from the perspective of an excavator. The images depict a landfill with various environmental contexts. Specifically, various type of barrels are contained. Moreover, the dataset contains the simulated LiDAR data of these scen...

Self-diffusion coefficients of simulated aqueous glycerol mixtures

Oct 28, 2022 - ThermoML

Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous glycerol mixtures", https://doi.org/10.18419/darus-3115, DaRUS, V1

In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experi...

Densities of simulated aqueous methanol mixtures

Oct 28, 2022 - ThermoML

Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3112, DaRUS, V1

Self-diffusion coefficients of simulated aqueous methanol mixtures

Oct 28, 2022 - ThermoML

Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Self-diffusion coefficients of simulated aqueous methanol mixtures", https://doi.org/10.18419/darus-3114, DaRUS, V1

Densities of simulated aqueous glycerol mixtures

Oct 28, 2022 - ThermoML

Gültig, Matthias; Range, Jan Peter; Schmitz, Benjamin; Pleiss, Jürgen, 2022, "Densities of simulated aqueous glycerol mixtures", https://doi.org/10.18419/darus-3113, DaRUS, V1

User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"

Sep 28, 2022 - Institute for Modelling and Simulation of Biomechanical Systems

Saini, Harnoor, 2022, "User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"", https://doi.org/10.18419/darus-2229, DaRUS, V1

Background and Objective: Many biomedical, clinical, and industrial applications may benefit from musculoskeletal simulations. Three-dimensional macroscopic muscle models (3D models) can more accurately represent muscle architecture than their 1D (line-segment) counterparts. Neve...

3D CT-Data for KK17/5-09

Jul 29, 2022 - KK17/5-09 Kurskreisel-Komponente

Mammadov, Gasim; Schweizer, Timo; Niklaus, Maria, 2021, "3D CT-Data for KK17/5-09", https://doi.org/10.18419/darus-1841, DaRUS, V2

Research data (mostly *.hdf5 format) which was obtained by scanning the object via Computed Tomography and generating a 3D inside view of the object with non-invasive means. This dataset is part of the digital gyroscope collection. For more information about the collection and it...

Information about KH22-10

Jul 29, 2022 - KH22-10 Künstlicher Horizont

Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Wagner, Jörg F.; Zhan, Kun, 2021, "Information about KH22-10", https://doi.org/10.18419/darus-1486, DaRUS, V2

Pdf list containing all information collected about this object. For more information see entry in Goobi. This dataset is part of the digital gyroscope collection. For more information about the collection and its creation, please see the documentation dataset: Niklaus, Maria, 20...

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