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Optimization of a Method for Detecting Single copies of Hepatitis B Virus DNA using CRISPR/Cas systems
Published 2025-01-01“…We maintained the sensitivity of the optimized method at the level of the original one (detection of single copies of hepatitis B virus DNA), when optimizing the method for detecting hepatitis B virus DNA. …”
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An islanding detection method for grid-connect inverter based on parameter optimized variational mode decomposition and deep learning
Published 2025-04-01“…To address the drawbacks of active methods and passive methods, an intelligent islanding detection strategy based on parameter-optimized variational mode decomposition (VMD) and deep learning was developed. …”
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Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards
Published 2025-07-01“…This study proposes an AI-powered drone-based pollination method for complex durian orchards, integrating improved object detection and optimized path planning. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine
Published 2023-04-01“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Image optimization method for ablation defects in high-voltage cable buffer layers based on X-ray detection technique
Published 2025-05-01“…This paper proposes an optimization method based on image enhancement and feature detection to address the challenges of low-quality X-ray images,significant noise interference, and difficulty in defect identification during the detection of ablation defects in high-voltage cable buffer layers. …”
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RLita: A Region-Level Image–Text Alignment Method for Remote Sensing Foundation Model
Published 2025-05-01“…The foundation model fine-tuning optimization method has gradually become a research hotspot due to the development of generative pretrained transformer. …”
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Online Traffic Crash Risk Inference Method Using Detection Transformer and Support Vector Machine Optimized by Biomimetic Algorithm
Published 2024-11-01“…In light of the above, an online inference method for traffic crash risk based on the self-developed TAR-DETR and WOA-SA-SVM methods is proposed. …”
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A Detection and Cover Integrated Waveform Design Method with Good Correlation Characteristics and Doppler Tolerance
Published 2025-05-01“…Aiming at the above problems, this paper proposes a waveform optimization method for a detection and cover integrated signal with high Doppler tolerance. …”
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Credit card fraud Detection using Feature select method and improved machine learning algorithm
Published 2025-06-01“…Experimental results on the Credit Card Fraud Detection dataset demonstrate the effectiveness of this method, achieving an impressive accuracy of 99.99%. …”
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Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling
Published 2024-11-01“…Based on this model, an ABD method was established using action data based on spatio-temporal block detection and motion foreground effect map features. …”
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Optimal Convolutional Networks for Staging and Detecting of Diabetic Retinopathy
Published 2025-03-01“…Fundus photography and optical coherence tomography (OCT) are used by ophthalmologists to assess retinal thickness and structure, as well as detect edema, hemorrhage, and scarring. The effectiveness of ConvNet no longer needs to be demonstrated, and its use in the field of imaging has made it possible to overcome many barriers, which were until now insurmountable with old methods. …”
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Low-complexity optimal MPSK detection for spatial modulation
Published 2015-08-01“…The low-complexity optimal SM detection algorithm for MQAM signal detection had been proposed,but no similar method was found for MPSK signal.The problem of low-complexity detection for MPSK signal was considered in SM systems.Utilizing 2-D vector quantization of ML demodulation and the property of MPSK constellation,a low-complexity optimal detection which is independent to modulation order was developed.Since the approach avoids the exhaustive searching on signal constellation space,the computational complexity can be significantly reduced.The proposed detection algorithm can provide the identical performance with ML-optimum detector and has lower computational complexity.Therefore,it has both theoretical and practical significance.The proposed algorithm is of great significance in the large antenna and green communication technology.…”
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