Showing 81 - 89 results of 89 for search 'code complex classification', query time: 0.31s Refine Results
  1. 81

    Image 2_De novo assembly and comparative analysis of the first complete mitogenome in Distylium (Distylium racemosum).jpeg by Yaling Wang (800597)

    Published 2025
    “…The mitogenome comprises a longer circular chromosome and a shorter linear chromosome (904,264 bp in total length), revealing a structurally complex conformation. We annotated 67 genes, including 43 protein-coding genes (PCGs), 21 tRNA genes, and three rRNA genes. …”
  2. 82

    Image 1_De novo assembly and comparative analysis of the first complete mitogenome in Distylium (Distylium racemosum).jpeg by Yaling Wang (800597)

    Published 2025
    “…The mitogenome comprises a longer circular chromosome and a shorter linear chromosome (904,264 bp in total length), revealing a structurally complex conformation. We annotated 67 genes, including 43 protein-coding genes (PCGs), 21 tRNA genes, and three rRNA genes. …”
  3. 83

    Yellow River Basin Industrial Base Spatio-temporal Monitoring and Impact Assessment Dataset by Libing Wang (21723566)

    Published 2025
    “…</li><li><b>Fine-grained Feature Extraction and Classification Phase:</b> Contains sample data, intermediate processing results (e.g., representative slices of classification probability maps), and corresponding algorithm implementation codes used to illustrate how the "feature decoupling" strategy was applied to identify and classify various key features from high-resolution imagery.…”
  4. 84

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

    Published 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>…”
  5. 85

    Supplementary file 1_Neuron synchronization analyzed through spatial-temporal attention.pdf by Haoming Yang (8506971)

    Published 2025
    “…Previous studies of synchronization have predominantly emphasized rate coding and pairwise interactions between neurons, which have provided valuable insights into emergent network phenomena but remain insufficient for capturing the full complexity of temporal dynamics in spike trains, particularly the interspike interval. …”
  6. 86

    Table 1_Socioeconomic differences in discharge against medical advice and hospital admission among emergency department visits associated with substance use in the United States.do... by Zahra Mojtahedi (17359606)

    Published 2025
    “…The International Classification of Diseases 10th Revision (ICD-10) codes were used to identify opioid, cannabis, and alcohol use, and smoking.…”
  7. 87

    Nocturnal vocalization behavior and related behavioral data of wild tibetan macaques by Gaoxin Gao (22818563)

    Published 2025
    “…</p><p dir="ltr">behavior: This column contains codes or labels that represent different types of behavior. …”
  8. 88

    Data Sheet 1_The first complete mitochondrial genome of Biotodoma cupido (Cichiliformes: Cichlidae) and its phylogeny.pdf by Xiaoli Zhang (135098)

    Published 2025
    “…<p>Traditional classifications of New World cichlids have been subject to persistent controversy. …”
  9. 89

    Correlation of 4 Greenhouse Gas Emissions datasets using the Family Food Module of the UK’s Living Costs and Food Survey for food eaten at home. LEAP 2025 conference, Oxford by Christian Reynolds (9048647)

    Published 2025
    “…We mapped each dataset to the food and drink codes in the Family Food Module of the UK’s Living Costs and Food Survey. …”