يعرض 881 - 900 نتائج من 1,078 نتيجة بحث عن '(( element method algorithm ) OR ((( data code algorithm ) OR ( based magic algorithm ))))', وقت الاستعلام: 0.41s تنقيح النتائج
  1. 881

    Measuring diaphragmatic excursion using 4-Dimensional Ultrasound: a feasibility study حسب Adam Handley (21524120)

    منشور في 2025
    "…</p><p dir="ltr">This dataset contains Voluson ultrasound data files of diaphragm motion from 12 participants, the raw python code to process this data and the compiled executable of the python scripts. …"
  2. 882

    <b>From street view imagery to the countryside: large-scale perception of rural China using deep learning</b> حسب Yao Yao (7903457)

    منشور في 2025
    "…The project includes both the data and code that support the Pair-CNN model.</p><h3>1. …"
  3. 883

    CSPP instance حسب peixiang wang (19499344)

    منشور في 2025
    "…<p dir="ltr">This Python script (<code>instance_generator.py</code>) is a tool designed to <b>programmatically generate synthetic instance data for container stowage and logistics problems.…"
  4. 884

    Stress and frequency optimization of prismatic sandwich beams with structural joints: Improvements through accelerated topology optimization حسب Shengyu Yan (21450735)

    منشور في 2025
    "…To address computational demands, accelerated linear finite element (FE) solvers and eigensolvers are employed, specifically adapted for density-based TO to enhance efficiency and maintain accuracy. …"
  5. 885

    Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014 حسب Karin L. Riley (19657882)

    منشور في 2025
    "…Forest Service’s Forest and Inventory Analysis program (FIA) version 1.7.1 and 2) the landscape target data, which consisted of raster data at 30x30 meter (m) resolution provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE; https://landfire.gov/) FIA plots were imputed to the raster data by the random forests algorithm, providing a tree-level model of all forested areas in the conterminous U.S. …"
  6. 886

    Overtuning in Hyperparameter Optimization - Artifacts حسب Lennart Schneider (20131899)

    منشور في 2025
    "…<br></p><p dir="ltr">This data contains the following columns (and some additional ones not explained here which are self-explanatory) where the validation and test performance of each proposed hyperparameter configuration are tracked over time in the form of trajectories</p><ul><li>iteration (iteration of an HPO run)</li><li>valid (validation performance)</li><li>test_retrained (test performance after retraining)</li><li>seed (replication id)</li><li>classifier (learning algorithm)</li><li>data_id (data set id)</li><li>train_valid_size (size of the set used for training and validation)</li><li>resampling (resampling method)</li><li>metric (performance metric)</li><li>method (post selection method and resampling method)</li><li>optimizer (HPO algorithm)</li></ul><p><br></p>…"
  7. 887

    Replication Package of "Battling Phish" حسب Anonymous Author (7372229)

    منشور في 2025
    "…</li><li><code>Phishing_Site_URLs_32_Features_Extracted_Data.csv</code> (PSU dataset):<br>Includes phishing and legitimate URLs with 32 extracted lexical features.…"
  8. 888

    Aluminum alloy industrial materials defect حسب Ying Han (20349093)

    منشور في 2024
    "…<p dir="ltr">The dataset used in this study experiment was from the preliminary competition dataset of the 2018 Guangdong Industrial Intelligent Manufacturing Big Data Intelligent Algorithm Competition organized by Tianchi Feiyue Cloud (https://tianchi.aliyun.com/competition/entrance/231682/introduction). …"
  9. 889

    Catalogue of compact radio sources in Messier-82 from e-MERLIN observations حسب Sibongumusa Shungube (21197363)

    منشور في 2025
    "…</p><p dir="ltr">The data were processed using the e-MERLIN CASA pipeline for initial calibration. …"
  10. 890

    Alphabet (United States): What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…Fields of Research with greater than 50% of their output not represented in the network include: Education (65.0%), and Law and Legal Studies (66.67%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"
  11. 891

    Technical University of Munich: What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"
  12. 892

    <b>A virtual tracer experiment to assess the temporal origin of root water uptake, evaporation, and </b><b>drainage</b> حسب Paolo Nasta (19710883)

    منشور في 2024
    "…</p><p dir="ltr"><a href="" target="_blank">Two open-source Matlab scripts are available in the zip-files. The PT.m Matlab code determines the drainage transit time based on the particle tracking algorithm, while the VTE.m Matlab code determines the drainage and RWU transit times and relative rainfall contributions to actual evaporation, actual transpiration, and drainage using isotope transport simulations in HYDRUS-1D</a>. …"
  13. 893

    iNCog-EEG (ideal vs. Noisy Cognitive EEG for Workload Assessment) Dataset حسب Fariya Bintay Shafi (21692408)

    منشور في 2025
    "…Inside each folder, four <b>.EDF</b> files represent the workload conditions:</p><pre><pre>subxx_nw.EDF → No Workload (resting state) <br>subxx_lw.EDF → Low Workload (easy multitasking) <br>subxx_mw.EDF → Moderate Workload (medium multitasking) <br>subxx_hw.EDF → High Workload (hard multitasking) <br></pre></pre><ul><li><b>Subjects 01–30:</b> Clean EEG recordings</li><li><b>Subjects 31–40:</b> Noisy EEG recordings with real-world artifacts</li></ul><p dir="ltr">This structure ensures straightforward differentiation between clean vs. noisy data and across workload levels.</p><h3>Applications</h3><p dir="ltr">This dataset can be applied to a wide range of research areas, including:</p><ul><li>EEG signal denoising and artifact rejection</li><li>Binary and hierarchical <b>cognitive workload classification</b></li><li>Development of <b>robust Brain–Computer Interfaces (BCIs)</b></li><li>Benchmarking algorithms under <b>ideal and noisy conditions</b></li><li>Multitasking and mental workload assessment in <b>real-world scenarios</b></li></ul><p dir="ltr">By combining controlled multitasking protocols with deliberately introduced environmental noise, <b>iNCog-EEG provides a comprehensive benchmark</b> for advancing EEG-based workload recognition systems in both clean and challenging conditions.…"
  14. 894

    gridded_livestock_mongolian_plateau_2000_2020 حسب Yaping Liu (20964836)

    منشور في 2025
    "…</p><p dir="ltr">The repository has four folders containing sample code and data for total livestock, sheep & goats, large livestock, and 2020 total livestock density spatial distribution simulations. …"
  15. 895

    The dataset of main grain land changes in China over 1985–2020 حسب Shidong Liu (11590769)

    منشور في 2025
    "…</p> <p>Data viewing and download links:</p> <p>https://code.earthengine.google.com/d371ab6f6c1bd274c85af270e4ad09c5 </p> <p><br></p> <p>Directly call ID of dataset in GEE:</p> <p>var MGL = ee.ImageCollection(“projects/ee-linshi-428901/assets/MrainlandType”)</p> <p><br></p> <p>Data usage code:</p> <p>var year = 2020 // Any year between 1985 and 2020</p> <p>var mglyear = MGL.filterMetadata('time', "equals", year).max()</p> <p>var visParams = {</p> <p>  min: 1,</p> <p>  max: 7,</p> <p>  palette: ['cyan', 'blue','green', 'yellow', 'red','purple','white']</p> <p>};</p> <p>Map.addLayer(mglyear.selfMask(),visParams,"MGL"+year)</p> <p><br></p>…"
  16. 896

    Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients حسب Chongwen Zuo (21546541)

    منشور في 2025
    "…Chronic knee pain alters cortical plasticity, yet our data demonstrate preserved MI capability in patients—a finding with direct implications for rehabilitation BCI development. …"
  17. 897

    Stanford University: What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…Fields of Research with greater than 50% of their output not represented in the network include: Economics (50.23%), Commerce, Management, Tourism and Services (51.57%), Creative Arts and Writing (56.37%), Language, Communication and Culture (56.59%), Philosophy and Religious Studies (60.57%), and History, Heritage and Archaeology (73.53%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"
  18. 898

    Stellenbosch University: What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…Fields of Research with greater than 50% of their output not represented in the network include: Physical Sciences (59.03%), Law and Legal Studies (68.66%), Mathematical Sciences (70.97%), Creative Arts and Writing (71.92%), Philosophy and Religious Studies (73.4%), History, Heritage and Archaeology (74.21%), and Language, Communication and Culture (77.64%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"
  19. 899

    Indian Institute of Science Bangalore: What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…Fields of Research with greater than 50% of their output not represented in the network include: Law and Legal Studies (58.06%), Mathematical Sciences (59.19%), and Philosophy and Religious Studies (67.86%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"
  20. 900

    Georgia Institute of Technology: What does a university look like? حسب Simon Porter (1364613)

    منشور في 2025
    "…Fields of Research with greater than 50% of their output not represented in the network include: Language, Communication and Culture (51.05%), Economics (51.16%), Philosophy and Religious Studies (54.95%), and History, Heritage and Archaeology (67.09%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…"