Comparative graph depicting area used. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Complete layout of the proposed architecture. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

GR encoding example for M = 4 [2]. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Comparative graph depicting bit usage. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Inferring Regional Commuting Systems from Network Signaling Data by Alexe Vlad (20556224)

“…</li></ul><p dir="ltr">The repository does not contain raw data due to <b>privacy constraints</b>. The methods and scripts are designed to process anonymized mobility datasets while ensuring compliance with <b>data protection standards</b>. …”

Overview of mouse ovary analysis using Vizgen MERFISH data. by Ian K. Gingerich (22822222)

Result of feature importance sorting. by Jinlin Teng (17972595)

“…</p><p>This study employs data mining concepts and machine learning techniques to provide an accurate and objective assessment of urban noise levels. …”

Study area and noise monitoring points. by Jinlin Teng (17972595)

“…</p><p>This study employs data mining concepts and machine learning techniques to provide an accurate and objective assessment of urban noise levels. …”

SHAP dependency graph. by Jinlin Teng (17972595)

“…</p><p>This study employs data mining concepts and machine learning techniques to provide an accurate and objective assessment of urban noise levels. …”

SPIDER (v2): Synthetic Person Information Dataset for Entity Resolution by Praveen Chinnappa (20835779)

“…<p dir="ltr">SPIDER (v2) – Synthetic Person Information Dataset for Entity Resolution provides researchers with ready-to-use data for benchmarking Duplicate or Entity Resolution algorithms. …”

MSRI by Anonymous Readmore (20472299)

“…<p dir="ltr">This repository contains the reproducible code and sample data for the paper:</p><p dir="ltr">MSRI: Minimum Spatial Residual Iterative Algorithm</p>…”

<b>Optimizing Task Scheduling and Containers in Cloud Data Centers</b> by Arash GhorbanniaDelavar (22563696)

“…Overall, TPMCD provides a scalable and cost-efficient framework that enhances both <b>performance and sustainability</b> in cloud data centers.</p><p dir="ltr"><code>Original article DOI: https://doi.org/10.1016/j.jnca.2025.104132</code></p>…”

MCCN Case Study 2 - Spatial projection via modelled data by Donald Hobern (21435904)

“…</p><p dir="ltr">The dataset contains input files for the case study (source_data), RO-Crate metadata (ro-crate-metadata.json), results from the case study (results), and Jupyter Notebook (MCCN-CASE 2.ipynb)</p><h4><b>Research Activity Identifier (RAiD)</b></h4><p dir="ltr">RAiD: https://doi.org/10.26292/8679d473</p><h4><b>Case Studies</b></h4><p dir="ltr">This repository contains code and sample data for the following case studies. …”

Raw and derived data: The quantification of downhole fractionation for laser ablation mass spectrometry by Jarred Lloyd (4825671)

“…</p><p dir="ltr">The zip file "DerivedData" contains two CSV files generated by the accompanying Julia code that processes data in preparation for fitting orthogonal polynomials that quantify the dowhnhole fractionation of these analyses and generates the figures for the publication.…”

Mobility Analysis: Home and Work Detection from Network Signaling Data (NSD) by Alexe Vlad (20556224)

“…</li></ul><p dir="ltr">The repository does not contain raw data due to <b>privacy constraints</b>. The methods and scripts are designed to process anonymized mobility datasets while ensuring compliance with <b>data protection standards</b>. …”

IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems by Xuhui Lin (19505503)

“…</p><p dir="ltr"><b>Quality Assurance</b>: Comprehensive technical validation demonstrates the dataset's integrity, sensitivity to rainfall impacts, and capability to reveal complex traffic-weather interaction patterns.</p><h2>Data Structure</h2><p dir="ltr">The dataset is organized into four primary components:</p><ol><li><b>Road Network Data</b>: Topological representations including spatial geometry, functional classification, and connectivity information</li><li><b>Traffic Sensor Data</b>: Sensor metadata, locations, and measurements at both 5-minute and hourly resolutions</li><li><b>Precipitation Data</b>: Hourly meteorological information with spatial grid cell metadata</li><li><b>Derived Analytical Matrices</b>: Pre-computed structures for advanced spatial-temporal modelling and network analyses</li></ol><h2>File Formats</h2><ul><li><b>Tabular Data</b>: Apache Parquet format for optimal compression and fast query performance</li><li><b>Numerical Matrices</b>: NumPy NPZ format for efficient scientific computing</li><li><b>Total Size</b>: Approximately 2 GB uncompressed</li></ul><h2>Applications</h2><p dir="ltr">The IUTF dataset enables diverse analytical applications including:</p><ul><li><b>Traffic Flow Prediction</b>: Developing weather-aware traffic forecasting models</li><li><b>Infrastructure Planning</b>: Identifying vulnerable network components and prioritizing investments</li><li><b>Resilience Assessment</b>: Quantifying system recovery curves, robustness metrics, and adaptive capacity</li><li><b>Climate Adaptation</b>: Supporting evidence-based transportation planning under changing precipitation patterns</li><li><b>Emergency Management</b>: Improving response strategies for weather-related traffic disruptions</li></ul><h2>Methodology</h2><p dir="ltr">The dataset creation involved three main stages:</p><ol><li><b>Data Collection</b>: Sourcing traffic data from UTD19, road networks from OpenStreetMap, and precipitation data from ERA5 reanalysis</li><li><b>Spatio-Temporal Harmonization</b>: Comprehensive integration using novel algorithms for spatial alignment and temporal synchronization</li><li><b>Quality Assurance</b>: Rigorous validation and technical verification across all cities and data components</li></ol><h2>Code Availability</h2><p dir="ltr">Processing code is available at: https://github.com/viviRG2024/IUTDF_processing</p>…”

Canopy Height Monitoring Data and Model of Hainan Tropical Rainforest National Park by Zixuan Qiu (14013837)

“…</p><p dir="ltr">The data in the folder (Code) includes the training code and prediction code for four machine learning algorithms (BP, CNN, GBDT, RF).…”

Data associated with "Functional specialisation of multisensory temporal integration in the mouse superior colliculus" by Gaia Bianchini (7570553)

“…</p><p><br></p><p dir="ltr"><b>2.decoder_datasets</b><br>Contains outputs of classification algorithms trained on the <code>delay_tuning_dataset</code>.…”

Supporting Data for “All-temperature barocaloric effects at pressure-induced phase transitions” by Zhao Xueting (21796316)

“…The structure search for the low-temperature phase was conducted using the generic evolutionary algorithm implemented in the USPEX code^42–44. …”

MEE2025-Integrated movement models for individual tracking and species distribution data-Supplement by Frances Buderman (17775255)

“…</i><i>Integrated movement models for individual tracking and species distribution data. Methods in Ecology and Evolution.</i></p><p dir="ltr">supplement.data.rdata is an R workspace containing simulated data<br>supplement.code.R is an R script to fit the model<br>mcmc.jmm.ou.R is the MCMC sampler for the model, called by supplement.code.R</p><p dir="ltr">out.sim.rdata contains samples from fitting the MCMC algorithm to the simulated data</p><p dir="ltr"><br></p>…”