بدائل البحث:
binding algorithm » finding algorithm (توسيع البحث), finding algorithms (توسيع البحث), mining algorithm (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), novel algorithm (توسيع البحث), modbo algorithm (توسيع البحث)
based binding » based funding (توسيع البحث), ace2 binding (توسيع البحث), acid binding (توسيع البحث)
data code » data model (توسيع البحث), data came (توسيع البحث)
element » elements (توسيع البحث)
binding algorithm » finding algorithm (توسيع البحث), finding algorithms (توسيع البحث), mining algorithm (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), novel algorithm (توسيع البحث), modbo algorithm (توسيع البحث)
based binding » based funding (توسيع البحث), ace2 binding (توسيع البحث), acid binding (توسيع البحث)
data code » data model (توسيع البحث), data came (توسيع البحث)
element » elements (توسيع البحث)
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881
Design methodology followed for the hardware.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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882
Block diagram for 10-bit input.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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883
Comparative graph depicting worst case delay.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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884
Comparative results with state of art design.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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885
Comparative graph depicting area used.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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886
Complete layout of the proposed architecture.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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887
GR encoding example for M = 4 [2].
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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888
Comparative graph depicting bit usage.
منشور في 2024"…The algorithm was developed and coded in Verilog and simulated using Modelsim. …"
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889
Inferring Regional Commuting Systems from Network Signaling Data
منشور في 2025"…</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>. …"
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890
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891
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892
Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025
منشور في 2025"…</li></ul><h3>Analysis Scripts</h3><p dir="ltr">Complete set of R scripts for reproducing all analyses:</p><ul><li><b>percent cost increase_line plot.R</b>: Creates visualizations of energy cost impacts under different conservation scenarios</li><li><b>Zonation curves.R</b>: Generates conservation performance curves and coverage statistics</li><li><b>NPV_bar_plot.R</b>: Produces economic analysis plots with Net Present Value breakdowns</li><li><b>domestic_export_map_iterations.R</b>: Creates spatial maps of renewable energy infrastructure for domestic and export scenarios</li></ul><h2>Technical Specifications</h2><h3>Data Formats</h3><ul><li><b>Spatial Data</b>: ESRI Geodatabase (.gdb), Shapefile (.shp), GeoTIFF (.tif)</li><li><b>Tabular Data</b>: CSV, Microsoft Excel (.xlsx, .xls)</li><li><b>Analysis Code</b>: R scripts (.R)</li></ul><h3>Software Requirements</h3><ul><li><b>R</b> (≥4.0.0) with packages: sf, dplyr, ggplot2, readr, readxl, tidyr, furrr, ozmaps, ggpattern</li><li><b>ESRI ArcGIS</b> or <b>QGIS</b> for geodatabase access and spatial analysis</li><li><b>Zonation</b> conservation planning software (for methodology understanding)</li></ul><h3>Hardware Recommendations</h3><ul><li><b>RAM</b>: 16GB minimum (32GB recommended for full spatial analysis)</li><li><b>Storage</b>: 15GB free space for data extraction and processing</li><li><b>CPU</b>: Multi-core processor recommended for parallel processing scripts</li></ul><h2>Detailed Description of the VRE Siting and Cost-Minimization Model</h2><p><br></p><p dir="ltr">This section provides an in-depth description of the Variable Renewable Energy (VRE) siting model, including the software, the core algorithm, and the optimisation process used to determine the least-cost, spatially constrained development trajectory for VRE infrastructure in Queensland, Australia.…"
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893
SPIDER (v2): Synthetic Person Information Dataset for Entity Resolution
منشور في 2025"…<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. …"
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894
MSRI
منشور في 2025"…<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>…"
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895
<b>Optimizing Task Scheduling and Containers in Cloud Data Centers</b>
منشور في 2025"…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>…"
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896
MCCN Case Study 2 - Spatial projection via modelled data
منشور في 2025"…</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. …"
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897
Raw and derived data: The quantification of downhole fractionation for laser ablation mass spectrometry
منشور في 2025"…</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.…"
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898
Mobility Analysis: Home and Work Detection from Network Signaling Data (NSD)
منشور في 2025"…</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>. …"
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899
IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems
منشور في 2025"…</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>…"
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900
Canopy Height Monitoring Data and Model of Hainan Tropical Rainforest National Park
منشور في 2025"…</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).…"