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1,216
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Dataset results
1,216 results for “real-time”
GTSRB - German Traffic Sign Recognition Benchmark by Real-Time Computer Vision at Ruhr-Universität Bochum
<div> <div>The German Traffic Sign Benchmark is a multi-class, single-image classification challenge held at the International Joint Conference on Neural Networks (IJCNN) 2011. <br>Our benchmark has the following properties: <br>- Single-image, multi-class classification problem <br>- More than 40 classes<br>- More than 50,000 images in total <br>- Large, lifelike database<br><br>Acknowledgements: [INI Benchmark Website][1]<br>[1]: http://benchmark.ini.rub.de/</div> </div>
GRM: A Novel Stochastic Model for Real-time GNSS Tropospheric Delay Estimation
<p>The dataset includes the proposed RWPN model (Cal_rwpn_new.m) and related files. The model is built based on ERA5 ZWD products from 2010 to 2019, which can be accessed at (<a>ftp://ftp.gfz-potsdam.de/pub/home/GNSS/products/gfz-vmf1/</a>). The proposed GRM model can contribute greatly by providing an efficient RWPN value to real-time GNSS ZTD estimation with an accuracy improvement of over 10% compared to fixed RWPN results. In addition, GRM also shows the superiorities of saving computation cost significantly since a large volume of the ERA5-derived RWPN values is modeled with only several parameters.</p>
Real-time monitoring of a 3D blood-brain barrier model maturation and integrity with a sensorized microfluidic device
<p><span>A significant challenge in the treatment of central nervous system (CNS) disorders is represented by the presence of the blood-brain barrier (BBB), a highly selective membrane that regulates molecular transport and restricts the passage of pathogens and therapeutic compounds. Traditional <em>in vivo</em> models are constrained by high costs, lengthy experimental timelines, ethical concerns, and interspecies variations. <em>In vitro</em> models, particularly microfluidic BBB-on-a-chip devices, have been developed to address these limitations. These advanced models aim to more accurately replicate human BBB conditions by incorporating human cells and physiological flow dynamics. In this framework, here we developed an innovative microfluidic system that integrates thin-film electrodes for non-invasive, real-time monitoring of BBB integrity using electrochemical impedance spectroscopy (EIS). EIS measurements showed frequency-dependent impedance changes, indicating BBB integrity and distinguishing well-formed from non-mature barriers. The data from EIS monitoring was confirmed by permeability assays performed with a fluorescence tracer. The model incorporates human endothelial cells in a vessel-like arrangement to mimic the vascular component and three-dimensional cell distribution of human astrocytes and microglia to simulate the parenchymal compartment. By modeling the BBB-on-a-chip with an equivalent circuit, a more accurate trans-endothelial electrical resistance (TEER) value was extracted. The device demonstrated successful BBB formation and maturation, confirmed through live/dead assays, immunofluorescence and permeability assays. Computational fluid dynamics (CFD) simulations confirmed that the device mimics <em>in vivo</em> shear stress conditions. Drug crossing assessment was performed with two chemotherapy drugs: doxorubicin, with a known poor BBB penetration, and temozolomide, conversely specific drug for CNS disorders and able to cross the BBB, to validate the model predictive capability for drug crossing behavior. The proposed sensorized microfluidic device represents a significant advancement in BBB modeling, offering a versatile platform for CNS drug development, disease modeling, and personalized medicine.</span></p>
Real-time tilt undersampling optimization during electron tomography of beam sensitive samples using golden ratio scanning and RECAST3D
<p>This dataset contains experimental data related: "Real-time tilt undersampling optimization during electron tomography of beam sensitive samples using golden ratio scanning and RECAST3D", T.Craig, A. Kadu, K.J. Batenburg and S. Bals, <em><strong>Nanoscale</strong></em>, 2023,<strong>15</strong>, 5391-5402 (2023).</p>
Mp4-Version of the supplementary Movies for the manuscript: "Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation"
<p>Videos in 'mp4'-format of the 8 supplementary movies for the manuscript: "Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation"</p>
Real-time Automatic Temperature Regulation During In Vivo MRI-guided Laser Induced Thermotherapy (MR-LITT)
<p>This dataset is associated with the article.</p> <p>For each example (in vitro/in vivo), two matrices are provided, each containing :</p> <p>- coefficients estimation curves ;</p> <p>- automatic regulation curves and recontructed data (thermometry, phase, module) of the MRI sequence.</p>
NOBEL-BOX: A Ship-Based Low-Cost Instrument for Real-Time Ocean Monitoring and Analysis
<p>This data is the measurement result obtained from the NOBEL-BOX instrument. The principle of NOBEL-BOX is to attach sensors in a container connected to a microcontroller and then measure directly. This data results from measurements using fresh water and sea water mixed to see the response from NOBEL BOX. Furthermore, data was also obtained from sea measurements in Pangandaran, West Java, Indonesia. These measurements include pH, water and water temperature, dissolved oxygen, TDS, and salinity. The use of this parameter is to see the condition of the sea so that it becomes a reference in mitigating and managing the ocean.</p>
Data for "ChickenSense: A low-cost deep learning-based solution for real-time poultry feed intake monitoring using sound technology"
<p>The dataset includes two types of data: scale and audio. The scale data is recorded using a hanging scale and measures the feeders' weight with a 5 Hz frequency. The audio data contains 1824 hours of recorded audio using a piezo-electric sensor attached to a bucket feeder to capture vibrations as audio signals with a sampling rate of 48 kHz. Each .wav file contains 15 minutes of audio recording.<br> Along with the raw data, a part of the dataset containing 36 30-second audio recordings was sampled and labeled in four classes, including pecking, singing, anomaly, and silence, resulting in 3319 labeled events. </p>
Interpretation results used in the paper "Real-Time Dual-Para FWI-Inv of GPR Data Based on Robust Deep Learning"
<p>We provide the updated synthetic data and inversion results used for all interpretations presented in the paper "Real-Time Dual-Parameter FWI Inversion of GPR Data Based on Robust Deep Learning."</p>
Now or Never? Global Review of Reactive and Near Real-Time Conservation Actions For Cetaceans
<p><span>Table S1: Information on resulting publications (<em>n</em> = 64) reviewed in this study.</span></p>
Mobile Technology and Data Analytics to Identify Real-time Predictors of Caregiver Well-Being
ClinicalTrials.gov study NCT04556591. IPD Sharing: YES. Countries: 1. Publications: 4.
Log2Lose: Incenting Weight Loss and Dietary Self-monitoring in Real-time to Improve Weight Management Among Adults With Obesity
ClinicalTrials.gov study NCT04770909. IPD Sharing: YES. Countries: 1. Publications: 2.
Validation of an indoor real-time location system for tracking sheep
Open the record for dataset details and reuse information.
Inducing representational change in the hippocampus through real-time neurofeedback
Open the record for dataset details and reuse information.
Using a real-time location system to detect behavioral changes in ewes with subclinical mastitis and their lambs
Open the record for dataset details and reuse information.
Rapid and real-time identification of fungi up to the species level with long amplicon Nanopore sequencing from clinical samples
<p>Samples collected from fungal cultures, skin of dogs and ZymoBIOMICS<sup>TM </sup>mock community (which includes <em>Saccharomyces cerevisiae</em> and <em>Cryptococcus neoformans</em>). The amplicons length of the fungal cultures and ZymoBIOMICS<sup>TM </sup>mock community is 3,5 Kb and 6 Kb, while the <em>Malassezia spp</em> samples used as control is 3,5 Kb. The amplicons length of the four samples from the skin is 3,5 Kb.</p>
Research data for dissertation 'Real-time Tomographic Reconstruction'
<p><br> This repository contains research data and software used for the research presented in the dissertation "Real-time tomographic reconstruction" by Jan-Willem Buurlage. Made permanently available as required by the research data policy of Leiden University.</p> <p><br> *<strong>Chapter 2</strong>*: A modern interface for BSP programs</p> <p>This chapter outlines the design and use of a new interface for bulk-synchronous parallel programs called Bulk. The 'chapter2/' directory programs contain source code for the three numerical experiments used to verify Bulk: a benchmarking program 'benchmark.cpp' that measures the BSP parameters, source code for the fast-fourier transform 'fft.cpp' and a comparison to a BSPlib implementation 'fft_bspedupack.cpp'. The Bulk library itself is also included.</p> <p><br> *<strong>Chapter 3</strong>*: Geometric partitioning for tomography</p> <p>This chapter describes a partitioning method that is based on the acquisition geometry underlying the tomographic system matrix, rather than the nonzero pattern. The main results are presented in four large tables, which can be generated using the programs implemented in 'chapter3/src/tableX.cpp'. The main dependency is the "TPT" which was developed alongside this research, and is also included in the directory. The tasks have high computational cost. The runtime measurements were performed on the Lisa supercomputer of SURFsara.</p> <p>The acquisition geometries used are represented in TOML files in 'data/geometries'.</p> <p><br> *<strong>Chapter 4</strong>*: A projection-based partitioning method</p> <p>This chapter describes a refinement of the previous method, that is based on a continuous model of the projections that make up the acquisition geometry. The programs used to generate the numerical results as well as most of the illustrations are contained in the directory 'chapter4/'. In particular (files relative to this directory):</p> <p>- Figure 4.3 and 4.4: generated by 'src/overlap.cpp'<br> - Figure 4.5: generaed by 'python/plot_partitioning_blender.py'<br> - Table 4.1 and 4.2: generated by 'src/grcb.cpp' and 'TPT/tools/generate_comvol_table.cpp'<br> - Figure 4.6: Generated by running 'Pleiades/src/reconstruct.cpp' on a GPU<br> cluster of 8 nodes with a 40 Gbit Mellanox Infiniband connection. Each node<br> has four NVIDIA GeForce GTX TITAN X GPUs, two Intel Xeon E5-2630 v3 CPUs<br> running at 2.40GHz, and 128GB RAM</p> <p>The acquisition geometries used are represented in TOML files in 'data/geometries', and were used as input to the programs above.</p> <p><br> *<strong>Chapter 5</strong>*: Real-time quasi-3D tomographic reconstruction</p> <p>This chapter describes a new reconstruction framework and software package based around the idea of reconstructing arbitrarily oriented slices that can be adjusted on the fly.</p> <p>- All results in the paper were generated directly using the RECAST3D software, and the code snippets are directly given as examples in the corresponding software folder.<br> - The benchmark results in Table 5.1 were produced on a node with two Intel Xeon E5-2623v3 processors, 128 GB RAM, and two dual-GPU NVIDIA GTX TITAN Z cards for a total of 4 GPUs with 6GB RAM each. To obtain these numbers, 'RECAST3D/slicerecon/src/slicerecon_server.cpp' should be run with a '--bench' flag.<br> - The data used for the experimental verification, presented in Figure 5.8, can be found at <https://doi.org/10.5281/zenodo.1154166>.</p> <p><br> *<strong>Chapter 6</strong>*: Application of quasi-3D reconstruction to synchrotron tomography</p> <p>This chapter describes an application of the RECAST3D software to synchrotron tomography. The results were generated using the RECAST3D software, as explained above. Adapters to make it work together with the GigaFRoST camera were written in Python, and a slightly modified version of RECAST3D was used for generating some of the results presented in the paper. Later, these changes were merged back into RECAST3D. The original code, which was used to generated some of the results shown in the chapter, is given in the Zipfile 'chapter6/tomcat-live-master.zip'.<br> </p>
Real-time benchmark dynamics of the Ohmic Spin-Boson Model computed with Time-Dependent Variational Matrix Product States. (TDVMPS) coupling strength and temperature parameter space
<p>Data describing the complete propagators (maps) for the evolution of the Ohmic Spin-Boson Model are made available, here. Using a time-dependent variotnal matrix product states (TDVMPS) respresentation of the complete spin-environment wave function, non -perturbative results are presented over a wide range of coupling strengths, temperatures and initial conditions. The results in this repository are associated with the article: </p> <p>https://www.preprints.org/manuscript/202012.0016/v1 </p> <p>A mathematica notebook that allows the data to be visualised and manipulated is also provided. </p>
Deep Reinforcement Learning for END-To-END Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments
<p> </p> <p>Videos for the real flight tests and the simulation experiments </p>
Dataset for Anomaly Detection Using Inter-Arrival Curves for Real-time Systems
<p>The dataset shows the input files and detailed results for the experiments discussed in the paper. A README file provide more details on the data.</p>
ScienceDex guides
Understand access before you commit
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.