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641
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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642
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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Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections
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646
Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading
Published 2021-08-01“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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647
LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning
Published 2024-01-01“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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648
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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649
Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring
Published 2022-11-01“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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650
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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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability
Published 2025-05-01“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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653
DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection
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654
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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655
Deception mechanisms of FDA‒AWACS against passive monopulse angle measurements
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Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection
Published 2025-02-01“…Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. …”
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Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium
Published 2025-07-01“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells
Published 2025-01-01“…The objective function of the optimization problem is defined as the sum of squared errors of the actual and predicted voltage data. …”
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