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662 results for “method comparison”
Dataset Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T
<p>Scientific Reports - Nature - DOI : 10.1038/s41598-018-37825-8</p> <p>##################################<br> "Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T"<br> ##################################</p> <p>E. Najdenovska*, C. Tuleasca*, J. Jorge, P. Maeder, J.P. Marques, T. Roine, D. Gallichan, J.-P. Thiran, M. Levivier, and M. Bach Cuadra</p> <p>*Equally contributed authors</p> <p><br> Copyright (c) - All rights reserved. University of Lausanne. 2018.</p> <p><br> To reproduce the analyses presented in the referred study, in this repository you could find the MR images acquired from nine young healthy subjects (YS1-YS5), four elderly healthy subject (ES1-ES4) and two drug-resistant tremor patients treated treated with Vim radiosurgery by Gamma Knife (P1 and P2).</p> <p>The provided dataset includes the following NifTI files:</p> <p>- MPRRAGE @3T<br> - DWI @3T (together with the corresponding bvals and bvecs)<br> - MP2RAGE @7T<br> - SWI @7T<br> - binary masks of the manual delineation of both left and right Vim respectively that were done on the SWI (as NifTI files as well).</p> <p>Additionally, for the young cohort (YS1-YS5) we include as well the images used for building the quadrilateral of Guiot:<br> - T2-w @3T<br> - T2 CISS @3T</p> <p>For the patients (P1 and P2), a follow-up MPRAGE (acquired at 3T) with Gadolinium enhancement is also provided.</p> <p>——————————————<br> Notes:<br> 1. For YS3 MP2RAGE at 7T is missing, instead MPRAGE at 3T was used</p> <p>2. The code performing the thalamic nuclei clustering could be found in Zenodo (DOI: 10.5281/zenodo.123768)</p>
Dataset of "Comparison of Localization Methods for Internet of Things in 5G Cellular Networks: A Wide-scale Assessment"
<p>As the 3rd generation partnership project (3GPP) organization pushes out new releases,<br>positioning in heterogeneous mobile networks enables the achievement of the accuracy required<br>in the majority of industrial applications without dependence on global navigation<br>satellite systems (GNSS). This study presents the results gathered during an extensive measurement<br>campaign related to the practical applicability of localization in next-generation<br>heterogeneous networks. We present an accuracy comparison of basic timing advance (TA)<br>localization with the k-nearest neighbor (KNN), decision tree-based random forest (RF),<br>extreme gradient boosting (XGBoost), and long short-term memory (LSTM) recurrent neural<br>network. Our results demonstrate that TA cannot be considered an optimal solution<br>from the perspective of localization accuracy because the error roughly corresponds to the<br>average separation distance from the base station (BS) to the end device (ED). In addition,<br>we found that the LSTM approach is not optimal for the outdoor localization of moving<br>ED because of the combination of multiple factors, with sparse deployment being the most<br>important. The median value of the location error of the LSTM was more than 200m higher<br>than that of the TA for the self-validation dataset. However, a simple KNN regression shows<br>solid results for 5G New Radio (NR) operating in the non-standalone (NSA) mode. KNN<br>provided the most accurate results of all methods, with median error values of approximately<br>12 (k=3) and 82 (k=5) m for the self-validated and cross-validated datasets, respectively.</p>
A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN (datasets)
<p>The train/validation/test sets used in the study "<strong>A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN</strong>".</p> <p>Preprint: <a href="https://arxiv.org/abs/1908.05085">https://arxiv.org/abs/1908.05085</a></p> <p>Published paper: <a href="https://ieeexplore.ieee.org/document/8970177">https://ieeexplore.ieee.org/document/8970177</a></p> <p> </p> <p>The dataset used to create these sets was published in:</p> <p><a href="http://www.mdpi.com/2306-5729/3/2/13">http://www.mdpi.com/2306-5729/3/2/13</a></p> <p>The full dataset is available here:</p> <pre><a href="https://doi.org/10.5281/zenodo.1212478">https://doi.org/10.5281/zenodo.1212478</a> </pre> <p>The credit for the creation of the dataset goes to Aernouts, Michiel; Berkvens, Rafael; Van Vlaenderen, Koen and Weyn, Maarten.</p>
Fast Method for Calibrated Self-Discharge Measurement of Lithium-Ion Batteries including Temperature Effects and Comparison to Modelling
<p>Self-discharge data related to the manuscript entitled: 'Fast Method for Calibrated Self-Discharge Measurement of Lithium-Ion Batteries including Temperature Effects and Comparison to Modelling', submitted to Energy Reports on 26 April 2023.</p>
Dataset for comparison of QuantumPower method to the differential PJVS method.
<p>Dataset for comparison of QuantumPower method to the differential PJVS method.</p> <p> </p> <p>Two methods for calibration of low frequency AC voltage using quantum voltage standard were compared: 1, classic differential method where digitizer measures difference between device under test and a step sine like signal generated by programmable josephson voltage standard. 2, quantum power method, where digitiser is first calibrated using programmable josephson voltage standard, and after a switch of multiplexer digitiser directly measures voltage of a device under test.</p> <p> </p> <p>To obtain the data, QPSW software was used:</p> <p>https://github.com/KaeroDot/QPsw</p> <p> </p> <p>Author: Martin Šíra</p> <p> </p> <p>Contact: Czech Metrology Institute, Okružní 31, 638 00 Brno, msira@cmi.cz</p> <p> </p> <p>Part of project Quantum traceability for AC power standards, QuantumPower, Project Number: 19RPT01. This project (19RPT01) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.</p> <p> </p> <p>https://www.euramet.org/research-innovation/search-research-projects/details/project/quantum-traceability-for-ac-power-standards/</p>
Dataset for comparison of QuantumPower method to the reference power standard
<p>Dataset for comparison of QuantumPower method to the power standard Radian RD-22.</p> <p>The QuantumPower method was compared to a power standard Radian RD-22. As a device under test, a Fluke 6100 power calibrator was used.</p> <p>To obtain the data, QPSW software was used:</p> <p>https://github.com/KaeroDot/QPsw</p> <p>Author: Martin Šíra</p> <p>Contact: Czech Metrology Institute, Okružní 31, 638 00 Brno, msira@cmi.cz</p> <p>Part of project Quantum traceability for AC power standards, QuantumPower, Project Number: 19RPT01.<em> </em>This project (19RPT01) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.</p> <p>https://www.euramet.org/research-innovation/search-research-projects/details/project/quantum-traceability-for-ac-power-standards/</p>
Evaluation of Spatiotemporal Fusion Methods Using Sentinel-2 And Sentinel-3: A New Benchmark Dataset And Comparison
<p>In Earth observation, data fusion is important to generate high temporal and spatial resolution images. Nevertheless, existing research on data fusion primarily concentrates on merging two sources of data (mostly MODIS and Landsat). Therefore, we offer the community a new benchmark dataset for evaluating data fusion using new European sensors (Sentinel-2 and Sentinel-3).</p> <p>The dataset is composed of three different sites located in different parts of the world to ensure the diversity of the ecosystem. The two components of the dataset are collected from operating missions ( Sentinel-2 and Sentinel-3). We also provide 10 bands for Sentinel-2 ranging from blue to SWIR, 4 bands at 10m resolution and 6 at 20m resolution. For Sentinel-3 16 bands are provided with a spatial resolution of 300m. The multiple bands allow for different applications for this dataset such as testing data fusion methods, etc.</p>
Dataset for: An experimental comparison of anomaly detection methods for collaborative robot manipulators
<p>The dataset contains data recordings from a UR5e robot during normal and anomalous operation and is recorded to support the authors Master thesis project and the associated Paper: <em>"An Experimental Comparison of Anomaly Detection Methods for Collaborative Robot Manipulators" </em>(inProceeding).</p> <p>An in-depth description of the dataset can be found in the pdf uploaded with the dataset and an example of a data loader is also provided.</p>
Application of multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables to Interaboratory Comparison Study on Pesticide Residues in Food (ILC)
<p>The suitability of multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables and related products, developed within activities of task (Multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables (including tea) and fruit juices), was evaluated by the Interaboratory Comparison Study on Pesticide Residues in Food (ILC). Test material (“Pesticide Residues in green tea”), prepared from the batch used for another proficiency test (PT), was provided by Fapas (Fera Science Ltd, York, UK).</p> <p>Data set obtains (i) information about performance characteristics of the analytical method and (ii) compilation of results of interlaboratory study.</p>
A comparison of density estimation methods for monitoring marked and unmarked animal populations
<p>These data were generated to compare different methods of estimating population density from marked and unmarked animal populations. We compare conventional live trapping with two more modern, non-invasive field methods of population estimation: genetic fingerprinting from hair-tube sampling and camera trapping for the European pine marten (Martes martes). We used arrays of camera traps, live traps, and hair tubes to collect the relevant data in the Ring of Gullion in Northern Ireland. We apply marked spatial capture-recapture models to the genetic and live trapping data where individuals were identifiable, and unmarked spatial capture-recapture (uSCR), distance sampling (CT-DS), and random encounter models (REM) to the camera trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.41 – 0.99 animals per km<sup>2</sup>), despite differences in precision, cost, and effort being apparent.</p> <p>In addition to the data, we provide novel code for running unmarked spatial capture-recapture (uSCR) and random encounter models (REM) to the camera trap data where individual ID was not possible. </p>
Comparison of methods to identify and monitor mold damages in buildings
<p>Molds thrive in indoor environments challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in microbiology of buildings with specific benefits and drawbacks. We evaluated the use of two methods, microscopy of visible mold growth (tape lifts) and DNA metabarcoding of mold and dust samples (swabs), for mapping mold-damage indicator fungi in buildings in Oslo. Overall, both methods provided consistent results for mold samples, where nearly 80% of the microscopy-identified taxa were confirmed by DNA analysis. <em>Aspergillus </em>was the most abundant genus colonizing all materials, while some taxa were associated with different substrates: <em>Acremonium </em>with gypsum board, <em>Chaetomium</em><em> </em>with chipboard, <em>Stachybotrys </em>with gypsum board and wood, and <em>Trichoderma</em> with wood. Based on DNA data, community composition was clearly different between mold and dust with a much higher alpha diversity in dust. Most genera identified in mold were also detected with a low abundance in dust from the same apartments. Their spatial distribution indicated some local spread from the mold growth to other areas, but there was no clear correlation between relative abundances and the distance to the damages. To study mold damages, different microbiological analyses (microscopy, cultivation, DNA and chemistry) should be combined with a thorough inspection of buildings. The interpretation of such datasets requires the collaboration of skilled mycologists and building consultants.</p>
A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13: Climate Action
<p>This data set pertains to the following research article: Purnell, P.J. (2022) <em>A comparison of different methods of identifying publications related to the United Nations Sustainable Development Goals: Case Study of SDG 13 – Climate Action</em>. arXiv:2201.02006</p>
DATA: Comparison between optical tissue clearing methods for detecting administered mesenchymal stromal cells in mouse lungs
<p>This data set includes all the raw data collected for the following article: "Comparison between optical tissue clearing methods for detecting administered mesenchymal stromal cells in mouse lungs".</p>
reference data for "A Critical Comparison of Annual Glare Simulation Methods"
<p><strong>CORRECTION (20.05.2025): This repository contains a preliminary material assignment for the NMT option (in scene.tar.gz scene/options/north_metal.rad) that was not used in the final simulations. The material used in all simulations was actually:</strong></p> <p><strong>void plastic facade</strong><br><strong>0</strong><br><strong>0</strong><br><strong>5 .15 .15 .15 0.075 0.02 </strong></p> <p> </p> <p>Scene and reference results files for:</p> <p>"A Critical Comparison of Annual Glare Simulation Methods"<br>Stephen Wasilewski, Jan Wienold, Marilyne Andersen<br>2022 Buildsim Nordic, Copenhagen</p> <p>Contents:</p> <p>01-06*.tar.gz:</p> <p>reference simulation image archives, one for each of 6 scene options and view directions.<br>Simulated using Radiance rpict with the following settings:</p> <p>rpict -t 60 -vu 0 0 1 -vf VIEWFILE -x 3000 -y 3000 -dp 4096 -ar 392 -ms 0.025 -ds .2 -dt .05 -dc .75 -dr 3 -ss 16 -st .01 -ab 1 -af AMBFILE -aa .075 -ad 4096 -as 2048 -av 0.5 0.5 0.5 -lr 12 -lw 1e-5 -ab 6 -av 0 0 0 -ar 600 -ad 1500 -as 750 -dt .01 -dc 1 -ps 3 -pt .04 | pfilt -1 -e 1 -m .25 -x /3 -y /3</p> <p><br>scene.tar.gz:</p> <p>scene files including geometry, weather, materials, views and sensor points. See README.rst for details.</p> <p>reference_values.tar.gz:</p> <p>result metrics calculated on reference images in 4 ways:</p> <p>ref: using evalglare 3.02 with default values<br>refBS: using evalglare 3.02 with default values on images processed with humanblur.sh (in archive)<br>refrt: calculated numerically on pixel by pixel basis (no glare source grouping) with 2000 cd/m2 threshold<br>refrtBS: same as refRT, but solar source size is corrected accounting for point spread of typical human eye</p>
FIGURE 5 in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
FIGURE 5. Pyrgopolon (Septenaria) cf. tricostata (Goldfuss, 1841), longitudinal section of a tube from Kaňk "Na Vrších", no. NM O8728. A. SEM image of the resulting cast providing a three-dimensional view of three bi-camerate specimens of Entobia isp. and numerous shafts of Trypanites isp. cut by the longitudinal boring Maeandropolydora isp.; galleries are duplicated, more or less parallel, partially touching each other. B. The same view to the specimen by using micro-CT. C. detail of the resin cast showing a pair of bi-camerate Entobia isp. D. micro-CT scan from the same view, details of Entobia chambers are below the lower limit of micro-CT resolution.
ANIMATION 1 in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
ANIMATION 1. Three-dimensional animation of specimen Cementula sp., a coiled tube, no. CZ2, from Velim locality, the Czech Republic.
FIGURE 3 in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
FIGURE 3. Cementula sp., a coiled tube, no. CZ2, from Velim. A–C. Scanning electron microscope images of resin cast, B–C insets in A showing microbioerosion beneath D–F. Micro-CT images. A, D and E. Identical views using different methods. B. SEM image of resin cast shows branching stolons of Iramena isp., below lower limit of micro-CT resolution. C. Detail showing microbioerosion beneath tube surface and shaft incompletely filled with epoxy resin. D. 2D section through both tubes. E. Semi-transparent rendering of 2D section. F. Volume reproduction image, 3D view to smooth inner surfaces of the tubes.
FIGURE 1. A in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
FIGURE 1. A. Simplified geographic map of Bohemian Cretaceous Basin indicating locations of the studied sites (in rectangle). B. Geographic position of nearshore deposits at Velim, Kaňk "Na Vrších" and Kamajka, where samples were taken (black pentangles).
FIGURE 4 in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
FIGURE 4. Placostegus zbyslavus (Ziegler, 1984), longitudinal section of a tube from Kamajka near Chotusice, no. NM O8727. A. SEM image of the resin cast showing a high degree of silicification that led to incomplete dissolution of the tube wall in HCl; image shows only indeterminate non-branching shafts. B. The same view of the specimen using micro-CT clearly shows relatively frequent Maeandropolydora isp. and shallow shafts of Trypanites isp.
FIGURE 2 in Comparison of methods: Micro-CT visualization method and epoxy cast-embedding reveal hidden details of bioerosion in the tube walls of Cretaceous polychaete worms
FIGURE 2. Stratigraphic provenance of serpulid tubes from Velim, Kamajka, and Kaňk. 1 - crystalline basement; 2 - basal Cenomanian conglomerate; 3 - redeposited Turonian conglomerate; 4 - bioclastic limestone with calcitic-clayey matrix; 5 - organodetritic clayey limestone; 6 - marly siltstone with intercalations of phosphatized horizon; 7 - sponge 'meadows'; 8 - limestone layer with nodule-like bodies; 9 - calcareous claystone (modified from Košťák et al., 2010; Kočí, 2012). Full filled circles indicate position of serpulid fauna.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.