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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
3,080 datasets
Ulster University and OpenDataNI provide historical shoreline data for the Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery dating back to the early 1800s. The dataset includes rate-of-change statistics calculated at 25-meter intervals using the Digital Shoreline Analysis System (DSAS). It was last updated on 2026-03-18.
Historical shoreline analysis for the entire Northern Ireland coastline, with rate-of-change statistics calculated at 25-meter intervals. The dataset was created by Ulster University using Ordnance Survey maps and aerial imagery, processed with the Digital Shoreline Analysis System (DSAS) in ArcGIS. It provides a dynamic picture of coastal change from the early 1800s onward.
Historical shoreline information for the entire Northern Ireland coastline, analyzed at 25-meter intervals. Ulster University produced this dataset using Ordnance Survey maps and aerial imagery to calculate rates of change since the early 1800s. The data includes statistics like Net Shoreline Movement and Linear Regression Rate, processed with the Digital Shoreline Analysis System (DSAS).
Historical shoreline positions for the Northern Ireland coastline, with analysis covering annual to decadal periods from the early 1800s. The dataset was created by Ulster University using Ordnance Survey maps and aerial imagery, processed with the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics. The end product is a digital asset for visualizing and assessing historical shoreline change.
Historical shoreline positions for the Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset was last updated on March 18, 2026, and is provided by OpenDataNI.
Ulster University and OpenDataNI provide historical shoreline change data for the Northern Ireland coastline. The dataset was created by analyzing Ordnance Survey maps and aerial imagery from the early 1800s onward, using the Digital Shoreline Analysis System (DSAS) to calculate rates of change. The data includes statistics like Net Shoreline Movement and Linear Regression Rate, measured at 25-meter intervals.
Historical shoreline positions for the entire Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset includes metrics like Net Shoreline Movement and Linear Regression Rate to visualize coastal retreat and accretion.
Ulster University and OpenDataNI provide a historical shoreline analysis for the Northern Ireland coastline. The dataset visualizes shoreline change and calculates rates of change using statistics like Net Shoreline Movement and Linear Regression Rate, derived from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Data was processed using the Digital Shoreline Analysis System (DSAS) in ArcGIS, with rates calculated at 25-meter intervals.
Historical shoreline positions for the Northern Ireland coastline, analyzed from the early 1800s to recent decades. The data was derived from Ordnance Survey maps and aerial imagery, processed using the Digital Shoreline Analysis System (DSAS) to calculate rates of change. The end product was provided by Ulster University and published by OpenDataNI.
A summary of Bayesian posterior inference results from 100 simulation replicates for three bacterial transmission scenarios: hospital-driven, equal, and community-driven. The dataset, created by Sanni Översti and last updated in March 2026, includes metrics on effective sample size, relative error, relative bias, and 95% highest posterior density accuracy. It is a small 5.5 KB Excel file.
A summary of Bayesian posterior inference results from 100 simulation replicates for different pathogen transmission scenarios. The dataset, created by Sanni Översti and last updated in March 2026, includes metrics like effective sample size, relative error, relative bias, and 95% highest posterior density accuracy for parameters in hospital-driven, equal, and community-driven transmission models. It is a small dataset of 9.5 KB, stored in an XLS file format.
A summary of Bayesian posterior inference results from 100 simulation replicates for three transmission scenarios: hospital-driven, equal, and community-driven. The dataset includes metrics on effective sample size, relative error, relative bias, and 95% highest posterior density interval accuracy for epidemiological parameters. It was authored by Sanni Översti and uploaded to figshare on March 17, 2026.
Sanni Översti's summary of Bayesian posterior inference results from 100 simulation replicates for hospital and community-driven transmission scenarios. The dataset, last updated on March 17, 2026, includes metrics like effective sample size, relative error, bias, and 95% highest posterior density interval accuracy for epidemiological parameters. It is a 9.5 KB Excel file shared under a CC-BY-4.0 license on figshare.
G-13-Andivalent created this archive on Hugging Face, last updated May 14, 2026. It presents a fundamental break from traditional probabilistic cloud inference models. The description positions it as resurrecting principles of absolute determinism and physically grounded logic for artificial general intelligence research.
A 3.4-fold increase in investment-specific productivity for synthesizing 5 nm gold nanoparticles was achieved via machine learning-optimized laser ablation in liquid. The dataset, created by Runpeng Miao and published on figshare in April 2026, details the experimental parameters and outcomes of this green synthesis method. It compares the results to conventional chemical synthesis, showing the optimized process is four times cheaper for gram-scale production.
Statistical results summarizing the performance of 18 algorithms on 30 benchmark functions. The data includes mean and standard deviation values, with lower mean values indicating better solution quality. The dataset was authored by Mohammad Salehi, shared on figshare under a CC-BY-4.0 license, and last updated on April 15, 2026.
Model estimates for the effect of water year percentile on the proportional difference in streamflow impairment occurrence. The dataset was authored by Christopher Dillis and last updated on April 22, 2026. It is a small 5.5 KB Excel file containing statistically reliable estimates.
Replication data for the OptChain research project on enhancing quantum circuit optimization. The dataset is hosted by Harvard Dataverse and authored by Laura Baird, with a last update timestamp of 2026-05-29. Its companion source code is available under an MIT license from a public GitHub repository.
Graph-theoretical finite-difference modelling of steady and transient flow in arbitrary open channel networks. The dataset accompanies a study applying graph theory to reformulate the Preissmann implicit scheme, tested across four network configurations with varied topologies and boundary conditions. Author weixin qiu published the dataset on figshare in April 2026.
A synthetic dataset designed for training models on column addition and subtraction. It includes a dedicated split for hard cases with long carries and borrows, such as 9999+1 and 100000-1. The dataset was created by author foxycuter and last updated on 2026-05-11.