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Dataset results
57 results for “time window”
More social species live longer, have longer generation times, and longer reproductive windows
<p>Data and scripts required to reproduce the results of the manuscript "More social species live longer, have longer generation times, and longer reproductive windows"</p>
Dataset: Time-dependent source apportionment of submicron organic aerosol for a rural site in an alpine valley using a rolling positive matrix factorisation (PMF) window
<p>Uploaded igor pxp files are the data to generate all figures of the results from our publication in Atmospheric Chemistry and Physics with the name of <em>"Time dependent source apportionment of submicron organic aerosol for a rural site in an alpine valley using a rolling PMF window"</em> by Chen et al. (2021).</p> <p>This study deployed a novel and advanced source apportionment technique on a dataset measured in Magadino. Rolling PMF allows retrieving more realistic, time-dependent and detailed information of the organic aerosol sources. This work highlights the strength of the rolling PMF mechanism by comparing it with the results derived from conventional seasonal PMF. Overall, this comprehensive interpretation of chemical speciation monitor (ACSM) data could be a role model for similar analyses.</p>
Data from: Evaluating Window Size Effects on Univariate Time Series Forecasting with Machine Learning
<p>In the realm of time series prediction modeling, the window size (w) is a critical hyperparameter that determines the number of time units included in each example provided to a learning model. This hyperparameter is crucial because it allows the learning model to recognize both long-term and short-term trends, as well as seasonal patterns, while reducing sensitivity to random noise. This study aims to elucidate the impact of window size on the performance of machine learning algorithms in univariate time series forecasting tasks. To achieve this, we employed 40 time series from two different domains, conducting experiments with varying window sizes using four types of machine learning algorithms: Bagging, Boosting, Stacking, and a Recurrent Neural Network (RNN) architecture. The results reveal that increasing the window size generally enhances the evaluation metric values up to a stabilization point, beyond which further increases do not significantly improve predictive accuracy. This stabilization effect was observed in both domains when w values exceeded 100 time steps. Moreover, the study found that RNN architectures do not consistently outperform ensemble models in various univariate time series forecasting scenarios.</p>
Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions
<p>Instances for Multi-Commodity Supply Vessel Planning Problem With Order Selection and Time Window Decisions</p>
Usable observations over Europe: Evaluation of compositing windows for landsat and sentinel-2 time series
<p>Landsat and Sentinel-2 data archives provide ever-increasing amounts of satellite data. However, the availability of usable observations greatly varies spatially and temporally. Pixel-based compositing that generates temporally equidistant cloud-free synthetic images can mitigate temporal variability, by constructing uninterrupted time series using different compositing windows. Here, we evaluated the feasibility of using compositing windows ranging from five days to one year for 1984-2021 Landsat and 2015-2021 Sentinel 2 time series to derive uninterrupted time series across Europe. We considered separate and joint use of both data archives and analyzed the spatio-temporal availability of composites during each calendar year and pixel-specific growing season across a variety of time windows and hypothesizing data interpolation. Our results demonstrated opportunities and limitations in the available data records to support medium- and long-term analyses requiring uninterrupted time series of composites with sub-annual temporal resolution. Spatial disparities across different compositing windows provide guidance on the feasibility of workflows relying on different data densities and on the challenges in wall-to-wall analyses. The feasibility of consistent time series based on composites with sub-monthly aggregation periods was mostly limited to the combined Landsat and Sentinel-2 archives after 2015, yet in some geographies requires interpolation of up to 50% of data.</p>
Dataset and code for the variants of the traveling salesman problem with time windows using multifactorial evolutionary algorithm
<p>Dataset and code for the variants of the traveling salesman problem with time windows using multifactorial evolutionary algorithm</p>
Usable observations over Europe: Evaluation of compositing windows for landsat and sentinel-2 time series
Open the record for dataset details and reuse information.
Data from: Identifying the critical climatic time window that affects trait expression
Identifying the critical time window during which climatic drivers affect the expression of phenological, behavioral, and demographic traits is crucial for predicting the impact of climate change on trait and population dynamics. Two widely used associative methods exist to identify critical climatic periods: sliding-window models and recursive operators in which the memory of past weather fades over time. Both approaches have different strong points, which we combine here into a single method. Our method uses flexible functions to differentially weight past weather, which can reflect competing hypotheses about time lags and the relative importance of recent and past weather for trait expression. Using a 22-year data set, we illustrate that the climatic window identified by our new method explains more of the phenological variation in a sexually selected trait than existing approaches. Our new method thus helps to better identify the critical time window and the causes of trait response to environmental variability.
The postseismic GPS displacements at different time windows following the 2024 M7.5 Noto Peninsula, Japan Earthquake
<p>The postseismic GPS displacements at different time windows following the 2024 M7.5 Noto Peninsula, Japan Earthquake.</p> <p>This data is based on the GPS time series from Nevada Geodetic Laboratory (NGL <span>http://geodesy.unr.edu/ )</span>.</p> <p>The format of data is:</p> <p>Time, lon, lat, dn, de, du, sign, sige, sigu</p>
Supplementary dataset for the paper "A time window averaging method to mitigate the impact of shell growth trends on Tridacna d18O records".
<p>Data and code for the paper "A time window averaging method to mitigate the impact of shell growth trends on Tridacna δ18O records". We have included an example in the pseudo-Tridacna package v2.1 to demonstrate how users can generate pseudo-Tridacna series.</p>
BRAIN CT PERFUSION IN ACUTE ISCHEMIC STROKE PATIENTS IN THE EARLY TIME WINDOW
Open the record for dataset details and reuse information.
Time Window for Ischemic Stroke First Mobilization Effectiveness
ClinicalTrials.gov study NCT03938311. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Extending the Time Window for Intravenous Tenecteplase in Patients With Distal Medium Vessel Occlusions Stroke
ClinicalTrials.gov study NCT06559436. IPD Sharing: NO. Countries: 1. Publications: 0.
EXtending the Time Window for Thrombolysis in Posterior Circulation Stroke Without Early CT Signs
ClinicalTrials.gov study NCT05429476. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Randomization of Endovascular Treatment in Acute Ischemic Stroke in the Extended Time Window
ClinicalTrials.gov study NCT04256096. IPD Sharing: YES. Countries: 1. Publications: 1.
The Effect of Time Window for Umbilical Cord Clamping During Cesareans on Offspring Hemoglobin and Maternal Blood Loss
ClinicalTrials.gov study NCT05492214. IPD Sharing: YES. Countries: 1. Publications: 1.
Intravenous Thrombolysis With rhTNK-tPA for Acute Non-large Vessel Occlusion in Extended Time Window
ClinicalTrials.gov study NCT05752916. IPD Sharing: NO. Countries: 1. Publications: 1.
Efficacy and Safety of Endovascular Recanalization for Acute Basilar Artery Occlusion With Extended Time Window (ANGEL-BAO)
ClinicalTrials.gov study NCT06101667. IPD Sharing: NO. Countries: 1. Publications: 0.
MRI-guided thrOmbolysis for Stroke bEyond Time Window by TNK
ClinicalTrials.gov study NCT04752631. IPD Sharing: NO. Countries: 1. Publications: 1.
Efficacy and Safety of Thrombectomy in Stroke With Extended Lesion and Extended Time Window
ClinicalTrials.gov study NCT03094715. IPD Sharing: YES. Countries: 10. Publications: 7.
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.