311 to 320 of 550 Results
Ritter, Simon; Leberecht, Kerstin; Eschenröder, Julian; Scholz, Christian, 2021, "Hells Bells project - results of sampling campaign in February 2020", https://doi.org/10.11588/data/GYLDH5, heiDATA, V2, UNF:6:1Ua7KESTWxO3lRrcac/mWQ== [fileUNF]
This data set compiles the results of water chemical analyses as well as bulk chemical analyses of the particles suspended in the water columns of cenotes (sinkholes) obtained during a sampling campaign in Mexico in February 2020. Three stratified cenotes from North-Eastern Yucat... |
May 22, 2017 - 3D Spatial Data Processing
Hämmerle, Martin; Lukač, Niko; Chen, Kuei-Chia; Koma, Zsófia; Wang, Chi-Kuei; Anders, Katharina; Höfle, Bernhard, 2017, "HELIOS full-waveform laser scanning simulation framework. Source code, precompiled version, example files for study of understory tree height scanning and respective output.", https://doi.org/10.11588/data/10101, heiDATA, V1
This data collection enables any user to reproduce the study Hämmerle et al. (2017). It provides the source code to compile the applied simulation framework. Furthermore, a precompiled version of the software including the necessary files are provided so that a direct start of th... |
Dec 6, 2021 - Carbon Cycle Group
Maier, Fabian; Gerbig, Christoph; Levin, Ingeborg; Super, Ingrid; Marshall, Julia; Hammer, Samuel, 2021, "Heidelberg integrated samples 2018-2020 and pseudo power plant experiment results [Data]", https://doi.org/10.11588/data/CK3ZTX, heiDATA, V1
These data files show the measurement and model ffCO2 results (surface source influence vs. volume source influence approach) for the two-week integrated afternoon and nighttime samples from Heidelberg (July 2018 - June 2020). Moreover, the results of the pseudo power plant exper... |
Harnisch, Sebastian; Zettl, Kerstin; Steiger, Stefan, 2021, "Heidelberg Cyber Conflict Dataset (HD-CY.CON)", https://doi.org/10.11588/data/KDSFRB, heiDATA, V1
The Heidelberg Cyber Conflict Dataset (HD-CY.CON) has been developed at the Institute for Political Science, Heidelberg University, under the guidance of Prof. Dr. Sebastian Harnisch. HD-CY.CON is a comprehensive dataset on malicious cyber operations, integrating categories of of... |
Mara, Hubert, 2019, "HeiCuBeDa Hilprecht - Heidelberg Cuneiform Benchmark Dataset for the Hilprecht Collection", https://doi.org/10.11588/data/IE8CCN, heiDATA, V2
The number of known cuneiform tablets is assumed to be in the hundreds of thousands. A fraction has been published by printing photographs and manual tracings in books, which is collected by the online Cuneiform Digital Library Initiative (CDLI) catalog including some of these im... |
Sep 2, 2019 - AWI Experimental Economics
Oechssler, Jörg; Rau, Hannes; Roomets, Alex, 2019, "Hedging, ambiguity, and the reversal of order axiom [Dataset]", https://doi.org/10.11588/data/1XDKHZ, heiDATA, V1, UNF:6:c8rHrHnmCxS3BC4O6euGVQ== [fileUNF]
We ran experiments that gave subjects a straight-forward and simple opportunity to hedge away ambiguity in an Ellsberg-style experiment. Subjects had to make bets on the combined outcomes of a fair coin and a draw from an ambiguous urn. By modifying the timing of the draw, coin f... |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines; Frank, Anette, 2023, "Head Selection Parsers and LSTM Labelers", https://doi.org/10.11588/data/BPWWJL, heiDATA, V1
This resource contains code, data and pre-trained models for various types of neural dependency parsers and LSTM labelers used in the papers: Do et al. (2017). "What Do We Need to Know About an Unknown Word When Parsing German" Do and Rehbein (2017). "Evaluating LSTM Models for G... |
Oct 28, 2016 - Multiple Myeloma Research Laboratory
Rème, Thierry; Emde, Martina; Seckinger, Anja; Hose, Dirk, 2016, "HDAMM-predictor: prediction of progression in asymptomatic myeloma patients", https://doi.org/10.11588/data/10092, heiDATA, V1
The HDAMM-predictor is based on microarray gene expression and predicts the risk of progression from asymptomatic to symptomatic myeloma. It divides the patients in three groups, from low to high risk to progress. It was generated according to the method published by Rème et al.... |
Zong, Wansheng; Hippchen, Nikolai; Dittmar, Benedikt; Elter, Maximilian; Ludwig, Philipp; Rominger, Frank; Freudenberg, Jan; Bunz, Uwe H. F., 2024, "Halogenated Phenazinothiadiazoles: Electron Transporting Materials [data]", https://doi.org/10.11588/data/PKX5CI, heiDATA, V1, UNF:6:M6UVaar224tmBy3Sj1o9jg== [fileUNF]
Triisopropylsilyl-(TIPS)-alkynylated phenazinothiadiazoles were prepared by the condensation of halogenated ortho-quinones and TIPS-alkynylated 5,6-diamino-2,1,3-benzothiadiazole with different combinations of halogen substituents. The compounds pack in brickwall motif of head-to... |
Dec 13, 2023 - 3D Spatial Data Processing
Vallejo Orti, Miguel; Negussie, Kaleb; Corral, Eva; Höfle, Bernhard; Bubenzer, Olaf, 2023, "Gully detection with Inverse Morphological Reconstruction Algorithm [data]", https://doi.org/10.11588/data/PXDR4M, heiDATA, V1
Characterization of micro-terrain features has been explored to detect gully objects in the terrain. An adaptation to the morphological reconstruction operator is implemented to detect gullies instead of buildings or other man-made structures. This operator can be configured to d... |
