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421
Forecasting springtime rainfall in southeastern Australia using empirical orthogonal functions and neural networks
Published 2025-08-01“…In addition to standard ocean climate indicators such as El Niño or the Indian Ocean Dipole, other typical patterns of variation are captured in terms of the temperatures of selected ocean areas. When characteristic patterns of correlation are discovered, they are included in the predictor selection in the form of expansion in terms of the empirical orthogonal functions (EOFs). …”
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422
Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections
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423
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Statistically Optimized Near-Field Acoustic Holography Using Prolate Spheroidal Wave Functions
Published 2023-01-01“…Near-field acoustic holography (NAH) is an effective tool for realizing accurate sound field reconstruction in three-dimensional space on the prerequisite that appropriate elementary wave functions are selected or constructed to match the characteristics of the sound sources. …”
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425
Beach volleyball athlete training trends of Russian-language scientific resources: a systematic review
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426
Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning
Published 2024-01-01“…To address this problem, machine learning (ML) based intrusion detection systems (IDSs) have been proposed. However, existing IDSs suffer from low detection accuracy, limited real-time response, and high resource requirements. …”
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427
Energy-Efficiency using Critical Nodes Detection Problem in Industrial Wireless Sensor Networks (IWSNs)
Published 2025-03-01“…Experiments simulation validates our proposed approach, approving its efficiency in reducing significant energy consumption while preserving connectivity and functionality for industrial systems. Furthermore, the results highlight the potential of using critical node analysis to support sustainable and efficient operations in resource-constrained industrial environments. …”
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428
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK
Published 2025-06-01“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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430
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
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431
TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5
Published 2025-05-01“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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432
YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes
Published 2025-04-01“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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433
Advancements in Nanostructured Functional Constituent Materials for Gas Sensing Applications: A Comprehensive Review
Published 2025-02-01“…High-end detection values may reach around a few ppb for most gases. …”
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434
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Securing Wireless Communications with Energy Harvesting and Multi-antenna Diversity
Published 2025-04-01“…Analytical expressions for the Signal-to-Noise Ratios (SNRs) at both the destination D and the eavesdropper E are derived, along with the Probability Density Function (PDF) and Cumulative Distribution Function (CDF) of these SNRs under block Rayleigh fading conditions. …”
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436
Uncovering functional deterioration in the rhizosphere microbiome associated with post-green revolution wheat cultivars
Published 2025-06-01“…Of the 113 functional genes that were differentially abundant between heritage and modern cultivars, 95% were depleted in modern cultivars and 65% of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). …”
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437
IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT
Published 2024-04-01“…The system goes beyond traditional LMS functionalities by providing suggestions to enhance and diversify lessons. …”
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438
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction
Published 2016-01-01“…Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. …”
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Antimicrobial Activity of Chitosan from Different Sources Against Non-<i>Saccharomyces</i> Wine Yeasts as a Tool for Producing Low-Sulphite Wine
Published 2024-10-01“…Finally, the efficiency of different antimicrobial treatments was evaluated during laboratory-scale fermentations inoculated with a selected <i>S. cerevisiae</i> strain. The tested strains exhibited medium/high resistance to the chitosan; in some cases, the behaviour varied in the function of species/strain, and only four strains exhibited different resistance levels, depending on the chitosan source. …”
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