cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4769101
title: Pressure Sensors towards Pipeline Leakage Detection Dataset

description: <strong>Abstract:</strong> Pipe leakage is one of the problems became reasonable high cost for the company. Water, Oil, and Gas are natural resources using pipe for media distribution. Leaky pipe occurs caused by many factors such as environment, pipe resistance, illegal tapping and etc. This research aimed to detect leakage of pipes by illegal tapping. Illegal tapping is a theft method to get stabbing or tapping pipeline. Illegal tapping impact of changing in pressure value between the upstream and downstream pipes. Pressure will be changes if sensor detected any irregularly mount on upstream and downstream value in experimental pipe. The result value will processes and analyze using continue wavelet transformation to finding the differences time and frequency. Although the results became measure experiment, that pipeline leaked could be detected. Citing<br> Citation data : "Using Pressure Sensors towards Pipeline Leakage Detection" - https://ieeexplore.ieee.org/document/8605251/ <pre><code>@INPROCEEDINGS{8605251, author={Exaudi, Kemahyanto and Passarella, Rossi and Rendyansyah and Zulfahmi, Rido}, booktitle={2018 International Conference on Electrical Engineering and Computer Science (ICECOS)}, title={Using Pressure Sensors towards Pipeline Leakage Detection}, year={2018}, volume={}, number={}, pages={89-92}, doi={10.1109/ICECOS.2018.8605251}}</code></pre>
description: For further more information, kindly to contacted at kemahyanto[at]ilkom.unsri.ac.id
DOI: 10.1594/pangaea.771645
title: (Table 2) Asphalt samples taken in the surveyed area at Chapopote Knoll, Southern Gulf of Mexico

description: Following the discovery of asphalt volcanism in the Campeche Knolls a research cruise was carried out in 2006 to unravel the nature of the asphalt deposits at Chapopote. The novel results support the concept that the asphalt deposits at the seafloor in 3000 m of water depth originate from the seepage of heavy petroleum with a density slightly greater than water. The released petroleum forms characteristic flow structures at the seafloor with surfaces that are 'ropy' or 'rough' similar to magmatic lava flows. The surface structures indicate that the viscosity of the heavy petroleum rapidly increases after extrusion due to loss of volatiles. Consequently, the heavy petroleum forms the observed asphalt deposit and solidifies. Detailed survey with a remotely operated vehicle revealed that the asphalts are subject to sequential alterations: e.g. volume reduction leading to the formation of visible cracks in the asphalt surface, followed by fragmentation of the entire deposit. While relatively fresh asphalt samples were gooey and sticky, older, fragmented pieces were found to be brittle without residual stickiness. Furthermore, there is evidence for petroleum seepage from below the asphalt deposits, leading to local up-doming and, sometimes, to whip-shaped extrusions. Extensive mapping by TV-guided tools of Chapopote Asphalt Volcano indicates that the main asphalt deposits occur at the south-western rim that borders a central, crater-like depression. The most recent asphalt deposit at Chapopote is the main asphalt field covering an area of ~2000 m**2. Asphalt volcanism is distinct from oil and gas seepage previously described in the Gulf of Mexico and elsewhere because it is characterized by episodic intrusions of semi-solid hydrocarbons that spread laterally over a substantial area and produce structures with significant vertical relief. As Chapopote occurs at the crest of a salt structure it is inferred that asphalt volcanism is a secondary result of salt tectonism.
description: GC - gravity core, ROV - suction is a suction sampler, PC - push core. Corrected position provides sample location in Fig. 7, cf. navigation error in Methods chapter.
description: Supplement to: Brüning, Markus; Sahling, Heiko; MacDonald, Ian R; Ding, Feng; Bohrmann, Gerhard (2010): Origin, distribution, and alteration of asphalts at the Chapopote Knoll, Southern Gulf of Mexico. Marine and Petroleum Geology, 27(5), 1093-1106
DOI: 10.5281/zenodo.3638165
title: IoT device identification dataset

description: This is the main record in the IoT device measurements connected to the paper "Identification of IoT Devices using Experimental Radio Spectrum Dataset and Deep Learning". This is a connecting dataset that references all the actual data. The records are split because of the large size of the dataset. The records containing the data are found at the following DOIs: Raw data Other room: 10.5281/zenodo.3646427 Upstairs: 10.5281/zenodo.3641580 Same room: 10.5281/zenodo.3638163 Background measurement: 10.5281/zenodo.3638139 Multi user data (No fading): 10.5281/zenodo.3754210 Multi user data: 10.5281/zenodo.3753003 Cut and dimensionality reduced measurements: 10.5281/zenodo.3752981 Common parameters for all the measurements: Frequency: 863-870 MHz (center 866,5 MHz) Sample Frequency: 10 MSPS Date of measurement: 15 November 2018 Location: Connectivity Lab, Fredrik Bajers Vej 7C, Aalborg University, Denmark
DOI: 10.5281/zenodo.3958325
title: ds-uct-007: Asphalt Concrete: X-Ray micro-CT of an asphalt concrete sample.

description: <strong>Summary</strong>:<br> .X-Ray micro-computed tomography (micro-CT) of an asphalt concrete sample, including both raw projection data and the final reconstructions, for one single resolution (voxel size of 7 μm).<br> .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility.<br> .Image data segmented with four different segmentation techniques: DL (Deep Learning), ML (Machine Learning), TH (Thresholding) and WS (Watershed).<br> .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers.<br> <strong>Details</strong>:<br> .Tomo - Voxel size: 7 μm; Sample-source: 31 mm; Sample-detector: 274.25 mm; Optical magnification: 0.4X; Filter: LE#6; Beam energy: 100 kV; Power: 9 W; Exposure time: 4.0 sec; Projections: 1600. <strong>Contents</strong>:<br> ._info_ds-uct-007.txt<br> .ds-uct-007_asphalt_concrete_07um_16bits.zip<br> .ds-uct-007_asphalt_concrete_07um_1600p.txrm<br> .ds-uct-007_asphalt_concrete_07um_1600p_Drift.txrm<br> .ds-uct-007_asphalt_concrete_07um_1600p_recon.txm<br> .ds-uct-007_asphalt_concrete_07um_DL.zip<br> .ds-uct-007_asphalt_concrete_07um_ML.zip<br> .ds-uct-007_asphalt_concrete_07um_TH32.zip<br> .ds-uct-007_asphalt_concrete_07um_WS.zip
DOI: 10.5281/zenodo.4659750
title: An Excel spreadsheet including eddy covariance-based daily and monthly greenhouse gas (carbon dioxide and methane) fluxes at Yunxiao mangrove flux tower

description: An Excel spreadsheet including eddy covariance-based daily and monthly greenhouse gas (carbon dioxide and methane) fluxes at Yunxiao mangrove flux tower.
DOI: 10.5281/zenodo.6532796
title: The station-based error information of monthly snow depth, precipitation and air temperature for CMIP6 models in mainland China

description: This dataset contains the data of monthly snow depth in terms of RMSD (cm), spatial correlation (R<sub>s</sub>), temporal correlation (R<sub>t</sub>), consistency index (CI), and Hotspot score (H-score) of the 1415 weather stations (only 342 stations with longterm observations were available for R<sub>t</sub>, CI and H-score) in China used for evaluating the snow depth simulated or estimated from 31 CMIP6 models, MERRA2 reanalysis and a remote sensing snow depth dataset (Che). It also includes the data of errors and accumulated errors of monthly precipitation (mm) and air temperature (℃) from the 342 stations of all the 31 CMIP6 models, which can be used for constructing the regression models for analyzing error sources of snow depth simulations. The NA values of monthly precipitation and temperature indicate that the effects of accumulated errors were ignored for the corresponding month and station.
DOI: 10.5281/zenodo.4896170
title: Urban Green Spaces of Shanghai province without ChongMing district

description: Polygons of Urban Green Spaces in Shanghai Province. Polygons have been collected using 静态地图API The projection is New Beijing / Gauss-Kruger zone 21 - EPSG:4576 The dataset contains all 1467626 polygons
DOI: 10.5281/zenodo.4264445
title: PEMS-BAY

description: PEMS-BAY dataset <pre><code>@inproceedings{li2018dcrnn_traffic, title={Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting}, author={Li, Yaguang and Yu, Rose and Shahabi, Cyrus and Liu, Yan}, booktitle={International Conference on Learning Representations (ICLR '18)}, year={2018} }</code></pre>
DOI: 10.5281/zenodo.6782601
title: TripAdvisor Restaurant Details and Reviews

description: Dataset of restaurant details and reviews from TripAdvisor that includes all details that a restaurant has and a review (binary) from a user to that restaurant.
DOI: 10.5281/zenodo.1484667
title: Two Multi-Temporal Datasets To Track The Enhanced Landsliding After The 2008 Wenchuan Earthquake

description: We release two datasets that track the enhanced landsliding induced by the 2008 M<sub>w</sub> 7.9 Wenchuan earthquake over a portion of the Longmen mountains, at the eastern margin of the Tibetan plateau (Sichuan, China). The first dataset is a geo-referenced multi-temporal polygon-based inventory of pre- and coseismic landslides, post-seismic remobilisations of coseismic landslide debris, and post-seismic landslides (new failures). It covers 471 km<sup>2</sup> in the earthquake’s epicentral area, from 2005 to 2018. The second dataset records the debris flows that occurred from 2008 to 2017 in a larger area (~17,000 km<sup>2</sup>), together with information on their triggering rainfall as recorded by a network of rain gauges. For some well-monitored events, we provide more detailed data on rainfall, discharge, flow depth and density. The datasets can be used to analyse, at various scales, the patterns of landsliding caused by the earthquake. They can be compared to inventories relative to past or new earthquakes or other triggers to reveal common or distinctive controlling factors. To our knowledge, no other inventories that track the temporal evolution of earthquake-induced mass wasting have been made freely available thus far. Our datasets can be accessed from https://doi.org/10.5281/zenodo.1405490. We also encourage other researchers to share their datasets to facilitate research on post-seismic geological hazards.
DOI: 10.5281/zenodo.3609064
title: NBA players

description: Data for nba players.
DOI: 10.5281/zenodo.4663137
title: UVic ESCM simulations of historical period, SSP1-2.6, SSP5-3.4-OS, and SSP5-8.5

description: These datasets contain the UVic-ESCM model output for simulations of the historical period and the shared socio-economic pathway (SSP) scenarios SSP1-2.6, SSP5-3.4-OS, and SSP5-8.5. All values are provided as annual global mean values. Provided variables are, e.g., surface air temperature, CO2 concentrations, diagnosed CO2 emissions, total land carbon, total ocean carbon, and total atmospheric carbon.
DOI: 10.5281/zenodo.3479859
title: VLF phase and amplitude data recorded at Scott Base Antarctica

description: This dataset contains the phase and amplitude data from VLF radio transmitter NPM (Hawaii, 21.4 kHz, 21.4⁰N, 158.2⁰E) recorded at the field-site for New Zealand's Scott Base, Arrival Heights, in Antarctica (77.8⁰S, 166.8⁰E). The propagation path is ~11 Mm long, oriented nearly north-south, with the mid-point at 28.9⁰S, 164.4⁰W. The data files are formatted as ASCII text files with columns of time (s), amplitude (dB) & phase (degrees) data. The MATLAB script plotUltraMSK.m can be used to plot the data files and an example data plot has been included in the dataset.
DOI: 10.5281/zenodo.5674405
title: Supporting data for the submission to the WRR journal

description: It is supporting data for the submission entitled "Uncertainty Quantification of Transient-based Leakage Identification: A Frequency Domain Approach" to the WRR journal. 1. All figures in fig format. 2. Experimental data of the Perugia Test [Keramat et al. (2019)]. Keramat, A., Louati, M., Wang, X., Meniconi, S., Brunone, B., Ghidaoui, M.S. (2019). Objective Functions for Transient-Based Pipeline Leakage Detection in a Noisy Environment: Least Square and Matched-Filter. Journal of Water Resources Planning and Management, ASCE, 145(10), 04019042.
DOI: 10.5281/zenodo.4153216
title: A Benchmark Dataset for Semi-Automatic Seismic Interpretation Based on a New Zealand's Seismic Survey

description: Open access to curated datasets positively impacts on scientific research of machine learning and deep learning techniques. It is a fact that benchmarks and public datasets prepared for data science assist researchers interested in evaluating, testing, and building new data-driven methodologies for specific domain areas. In geosciences, there has been a remarkable growth of public datasets arranged to address machine learning challenges related to the oil and gas industry, particularly for reserves exploration and data interpretation. For these reasons, we present the Taranaki dataset, which is a collection of seismic horizons interpreted for a seismic stratigraphic interpretation study in the Taranaki Basin, offshore New Zealand. This data comprises fourteen seismic horizons that mark stratigraphic discordances in the Tui-3D seismic dataset. We annotated five seismic horizons on 33 inline sections and nine horizons on 19 crossline sections. Besides, we present the results of a series of experiments that compare a method of interpolation and a method of deep learning for seismic segmentation. The deep learning experiments evaluated the result of different image tile sizes to train the model, which is presented separately in this dataset. Finally, we evaluated both methodologies to interpret the horizons of this dataset in selected seismic sections. Also, we assessed the absolute error of each method with the ground truth interpretations proposed in this dataset.
DOI: 10.5281/zenodo.6403870
title: DataSet La Habra Earthquake

description: This dataset contains input, configuration, results for the simulations of the 2014 La Habra Earthquakes, which is used and cited by journal papers "Calibration of the Near-surface Seismic Structure in the SCEC Community Velocity Model Version 4" and "0-5 Hz Deterministic 3D Ground Motion Simulations for the 2014 La Habra, CA, Earthquake" published on Geophysical Journal International.
DOI: 10.5281/zenodo.3250672
title: LIBS-wallscanner dataset related to "Scanning laser-induced breakdown spectrometer for mine walls" thesis

description: This is a LIBS dataset published alongside the thesis in related identifiers. For better description see the thesis publication.
DOI: 10.5281/zenodo.1344314
title: Assessing the sustainability performance of sustainability management software - replication package

description: This is the replication package for the article "Assessing the sustainability performance of sustainability management software", published in Technologies – SI „Advanced Green Information and Communication Technology“

<strong>Contents</strong><br>
The repository contains the following files:


	<em>Data_-_Scenario_Hardware_Measurement.csv:</em><br>
	measurement data acquired during the measurement of the standard usage scenario
	<em>Data_-_Scenario_Log.txt:</em><br>
	timestamp log file for the measurements of the standard usage scenario
	<em>Data_-_Baseline_Hardware_Measurement.csv:</em><br>
	baseline meaurements
	<em>Data_-_Baseline_Log.txt:</em><br>
	baseline timestamp log file
	<em>R_image.Rdata:</em><br>
	data is also available in an R image dump
	<em>R_Analysis_Script.R:</em><br>
	analysis script, written in R
	<em>Results_SCSS_WeSustain_ESM.pdf:</em><br>
	results of the analysis
	<em>Results_and_calculation_for_Indicators_1.2.b_and_1.2.c.ods:</em><br>
	calculation for indicators 1.1.4.d) 1.2.b) and 1.2.c)
	<em>Usage-scenario_WeSustain_ESM.pdf:</em><br>
	description of the standard usage scenario


<strong>Usage</strong><br>
To recreate the analysis, run the R script and, if necessary, modify <em>lines 103 to 115</em> to fit the filenames where to find the data.<br>
<em>Lines 193 to 217</em> need to be executed manually, to generate the desired plots and calculations.

It is also possible to load the <em>R_image.RData</em> data dump into an R session, import the library `psych` (<em>line 2</em> in the script) and manually execute <em>lines 193 to 217</em> to generate the desired plots and calculations.
description: The replication package is also available on our GitLab at https://gitlab.umwelt-campus.de/a.guldner/sustainability_performance_of_sustainability_management_software/tree/master
DOI: 10.5281/zenodo.4769100
title: Pressure Sensors towards Pipeline Leakage Detection Dataset

description: <strong>Abstract:</strong> Pipe leakage is one of the problems became reasonable high cost for the company. Water, Oil, and Gas are natural resources using pipe for media distribution. Leaky pipe occurs caused by many factors such as environment, pipe resistance, illegal tapping and etc. This research aimed to detect leakage of pipes by illegal tapping. Illegal tapping is a theft method to get stabbing or tapping pipeline. Illegal tapping impact of changing in pressure value between the upstream and downstream pipes. Pressure will be changes if sensor detected any irregularly mount on upstream and downstream value in experimental pipe. The result value will processes and analyze using continue wavelet transformation to finding the differences time and frequency. Although the results became measure experiment, that pipeline leaked could be detected. Citing<br> Citation data : "Using Pressure Sensors towards Pipeline Leakage Detection" - https://ieeexplore.ieee.org/document/8605251/ <pre><code>@INPROCEEDINGS{8605251, author={Exaudi, Kemahyanto and Passarella, Rossi and Rendyansyah and Zulfahmi, Rido}, booktitle={2018 International Conference on Electrical Engineering and Computer Science (ICECOS)}, title={Using Pressure Sensors towards Pipeline Leakage Detection}, year={2018}, volume={}, number={}, pages={89-92}, doi={10.1109/ICECOS.2018.8605251}}</code></pre>
description: For further more information, kindly to contacted at kemahyanto[at]ilkom.unsri.ac.id
DOI: 10.5281/zenodo.4040636
title: xinjiang

description: These data was used to drive and validate the model
DOI: 10.5281/zenodo.6403869
title: DataSet La Habra Earthquake

description: This dataset contains input, configuration, results for the simulations of the 2014 La Habra Earthquakes, which is used and cited by journal papers "Calibration of the Near-surface Seismic Structure in the SCEC Community Velocity Model Version 4" and "0-5 Hz Deterministic 3D Ground Motion Simulations for the 2014 La Habra, CA, Earthquake" published on Geophysical Journal International.
DOI: 10.5281/zenodo.6675452
title: PRJNA363032 gVCFs

description: Sequencing reads were aligned to the Amel_HAv3.1 reference genome using BWA-MEM v0.7.17. Reads were sorted with SAMtools v1.9 and duplicates marked (MarkDuplicates) with GATK v4.0.11.0. Variants for each sample were called using GATK’s HaplotypeCaller with the following non-default parameters --ERC GVCF, --sample-ploidy 1 and -A AlleleFraction. This dataset comprises the gVCF files for samples belonging to project accession: PRJNA363032.
DOI: 10.5281/zenodo.5567687
title: Marine Heatwave Tracking with Ocetrac and OISST

description: These netCDF files contain the preprocessed NOAA OISST v2.1 data and corresponding Ocetrac labels. The preprocessed data (<strong>preprocessed_oisst_mhw_stats.nc</strong>) contains global maps of monthly sea surface temperature decomposed into the mean, trend, seasonal cycle, and remaining variability. Summary statistics of marine heatwave events are provided and include the mean event duration, total count, and mean event intensity. These statistics are computed with the monthly OISST anomalies between 09-1981 and 06-2021. The resulting labeled marine heatwaves identified using Ocetrac and are contained in <strong>ocetrac_labels.nc</strong>.
DOI: 10.5281/zenodo.6354977
title: Using VLF Transmitter Signals at LEO for Plasmasphere Model Validation

description: <strong>VPM_survey_data_2020-03-12.xml </strong>survey electric field data collected between 2020-03-12 00:13:35UT and 2020-03-12 23:59:15 UT <strong>vpm_map.cdf.zip</strong> processed VPM survey mode data containing longitude, latitude and power spectral density across the entire mission
DOI: 10.1594/pangaea.898513
title: Water level and storage changes of Har lake during 2000‒2017

description: Following information is included:1) Date of the data acquisition time in the form of yyyy-mm-dd.2) Lake water levels are orthometric heights with respect to EGM08, WGS84, in the unit of meter.3) Uncertainty of the lake water level in the unit of meter, if it is altimetry water level. The uncertainty of optical water levels was not calculated and set to 0.4) Lake water storage changes with respect to the baseline (lake water storage of the water level baseline H0, which is a value we do not exactly know; see https://doi.pangaea.de/10.1594/PANGAEA.898409) in the unit of km^3.5) The source of the data, 0 - Landsat, 1 - Envisat, 2 - ICESat, 3 - CryoSat, 4 - Jason-1/2/3.
DOI: 10.5281/zenodo.4715772
title: An Excel spreadsheet including eddy covariance-based greenhouse gas (carbon dioxide and methane) fluxes at Yunxiao mangrove flux tower

description: An Excel spreadsheet including eddy covariance-based greenhouse gas (carbon dioxide and methane) fluxes at Yunxiao mangrove flux tower.
DOI: 10.5281/zenodo.4636121
title: Raw Data for the article: Veno-Arterial Extracorporeal Life Support in Heart Transplant and Ventricle Assist Device Centres. Meta-analysis

description: <strong>Aims: </strong>Because reported mortality on veno-arterial (V-A) extracorporeal life support (ECLS) substantially varies between centres, the aim of the current analysis was to assess the outcomes between units performing heart transplantation and/or implanting ventricular assist device (HTx/VAD) vs. non-HTx/VAD units in patients undergoing V-A ECLS for cardiogenic shock. <strong>Methods and results: </strong>Systematic search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was performed using PubMed/MEDLINE databases until 30 November 2019. Articles reporting in-hospital/30-day mortality and centre's HTx/VAD status were included. In-hospital outcomes and long-term survival were analysed in subgroup meta-analysis. A total of 174 studies enrolling n = 13 308 patients were included with 20 series performed in non-HTx/VAD centres (1016 patients, 7.8%). Majority of patients underwent V-A ECLS for post-cardiotomy shock (44.2%) and acute myocardial infarction (20.7%). Estimated overall in-hospital mortality was 57.2% (54.9-59.4%). Mortality rates were higher in non-HTx/VAD [65.5% (59.8-70.8%)] as compared with HTx/VAD centres [55.8% (53.3-58.2%)], P &lt; 0.001. Estimated late survival was 61.8% (55.7-67.9%) without differences between non-HTx/VAD and HTx/VAD centres: 66.5% (30.3-1.02%) vs. 61.7% (55.5-67.8%), respectively (P = 0.797). No differences were seen with respect to ECLS duration, limb complications, and reoperations for bleeding, kidney injury, and sepsis. Yet, weaning rates were higher in HTx/VAD vs. non-HTx/VAD centres: 58.7% (56.2-61.1%) vs. 48.9% (42.0-55.9%), P = 0.010. Estimated rate of bridge to heart transplant was 6.6% (5.2-8.3%) with numerical, yet not statistically significant, difference between non-HTx/VAD [2.7% (0.8-8.3%)] as compared with HTx/VAD [6.7% (5.3-8.6%)] (P = 0.131). <strong>Conclusions: </strong>Survival after V-A ECLS differed according to centre's HTx/VAD status. Potentially different risk profiles of patients must be taken account for before definite conclusions are drawn.
DOI: 10.5281/zenodo.5372016
title: The PM2.5 concentration data

description: The PM<sub>2.5</sub> concentration data