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51 to 60 of 68 Results
Mar 1, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Becher, Michael; Müller, Christoph; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Your visualisations are going places: Performance data for scientific visualisation on gaming consoles", https://doi.org/10.18419/darus-4003, DaRUS, V1
The data set contains performance data (mainly frame times) for rendering spherical glyphs and scalar fields on Xbox Series consoles, mobile game consoles and a reference PC with different GPUs.
Feb 26, 2024 - Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries
Homs Pons, Carme; Lautenschlager, Robin, 2024, "Replication Data for: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models", https://doi.org/10.18419/darus-4031, DaRUS, V1
This dataset allows to reproduce the results from the paper "Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models" submitted to GAMM Mitteilungen in September 2023. Find more information about the structure of the dataset and the st...
Feb 26, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph; Ertl, Thomas, 2024, "Performance Data for the Visualisation of Time-Dependent Particles using DirectStorage", https://doi.org/10.18419/darus-4017, DaRUS, V1
Results of a series of performance measurements (frame times) to determine the impact of using the DirectStorage API for rendering time-dependent particle data sets in contrast to using traditional POSIX-style I/O APIs.
Feb 22, 2024Projects without PN Affiliation
The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scal...
Feb 21, 2024 - Analytic Computing
Asma, Zubaria; Hernández, Daniel; Galárraga, Luis; Flouris, Giorgos; Fundulaki, Irini; Hose, Katja, 2024, "Code and benchmark for NPCS, a Native Provenance Computation for SPARQL", https://doi.org/10.18419/darus-3973, DaRUS, V1
Code for the implementation and benchmark of NPCS, a Native Provenance Computation for SPARQL. The code in this dataset includes the implementation of the NPCS system, which is a middleware for SPARQL endpoints that rewrites queries to queries that annotate answers with provenanc...
Feb 16, 2024 - Analytic Computing
Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/darus-3977, DaRUS, V1
This dataset contains the implementation code for an algorithm to infer SHACL shapes that the graph returned by an SPARQL CONSTRUCT query must satisfy if the input satisfies a given set of SHACL shapes. This dataset also includes an evaluation for the algorithm. The algorithm imp...
Feb 16, 2024 - C-X5
Kiemle, Stefanie; Schneider, Jana; Heck, Katharina, 2024, "Replication data for analyzing stable water isotopologue transport within soils using fractionation parameterizations", https://doi.org/10.18419/darus-3572, DaRUS, V1
Replication data to reproduce the results presented in J. Schneider & S. Kiemle, K. Heck, Y. Rothfuss, I. Braud, R. Helmig, J. Vanderborght (2024) Analysis of Experimental and Simulation Data of Evaporation-Driven Isotopic Fractionation in Unsaturated Porous Media. (Under review)...
Feb 13, 2024 - Analytic Computing
Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "CNVVE Dataset clean audio samples", https://doi.org/10.18419/darus-3898, DaRUS, V1
This CNVVE Dataset contains clean 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...
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...
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...
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