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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour
Published 2025-12-01“…Compared to regression models built with competitive adaptive reweighted sampling and genetic algorithm for feature wavelength selection, the performance improved significantly, enhancing generalization capability. …”
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743
"Non-destructive and rapid determination of bound styrene content of styrene-butadiene rubber latex using near-infrared spectroscopy"
Published 2024-12-01“…A non-destructive and rapid determination of bound styrene content in styrene-butadiene rubber latex was studied using near-infrared spectroscopy diffuse transmission method combined with chemometrics, bound styrene content in styrene-butadiene rubber latex was determined by refractive index method, near-infrared spectral data of styrene-butadiene rubber latex were collected using Fourier transform near-infrared spectrometer, Kennard-Stone algorithm was used to divide the calibration set and validation set, partial least squares regression quantitative analysis model was established by combining the spectral preprocessing methods, such as multiple scattering correction method, second-order derivatives and Norris smoothing, etc, and the influence of screening spectral feature variables by interval partial least squares algorithm on the quantitative ana-lysis model was finally investigated. …”
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744
An efficient hybrid Hopfield convolutional neural network for detecting spam bots in Twitter platform
Published 2025-12-01“…The extracted features are then subjected to feature selection, where a meta-heuristic-based optimization algorithm called the Binary Golden Search Optimization algorithm (BGSO) is used. …”
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State-of-the-Art Review on the Application of Unmanned Aerial Vehicles (UAVs) in Power Line Inspections: Current Innovations, Trends, and Future Prospects
Published 2025-03-01“…Unmanned aerial vehicles (UAVs) make power line inspections more safe, efficient, and cost-effective, replacing risky manual checks and expensive helicopter surveys while overcoming challenges like stability and regulations. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing
Published 2025-07-01“…The dual-variable selection strategy integrates SHAP with the Pearson correlation coefficient (PC), RF, EN, and Lasso to enhance feature screening robustness and interpretability. The results of the study showed that Lasso-SHAP dual-variate screening was more stable than SHAP univariate screening. …”
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Identification and Validation of Circadian Rhythm‐Related Genes Involved in Intervertebral Disc Degeneration and Analysis of Immune Cell Infiltration via Machine Learning
Published 2025-06-01“…Results Six hub genes related to CRs (CCND1, FOXO1, FRMD8, NTRK2, PRRT1, and TFPI) were screened out. Immune infiltration analysis revealed that the IVDD group had significantly more M0 macrophages and significantly fewer follicular helper T cells than those of the control group. …”
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749
Exploring patterns in pediatric type 1 diabetes care and the impact of socioeconomic status
Published 2025-04-01“…Higher socioeconomic status is associated with care that more closely adheres to clinical guidelines.…”
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750
AI-driven innovation in antibody-drug conjugate design
Published 2025-06-01“…This review is organized into six sections: (1) the progression from traditional modeling approaches to AI-driven design of individual ADC components; (2) the application of deep learning (DL) to antibody structure prediction and identification of optimal conjugation sites; (3) the use of AI/ML models for forecasting pharmacokinetic properties and toxicity profiles; (4) emerging generative algorithms for antibody sequence diversification and affinity optimization; (5) case studies demonstrating the integration of computational tools with experimental pipelines, including systems that link in silico predictions to high-throughput validation; and (6) persistent challenges, including data sparsity, model interpretability, validation complexity, and regulatory considerations. …”
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ARTS AND MACHINE CIVILIZATION INTERNATIONAL SCIENTIFIC CONFERENCE / МЕЖДУНАРОДНАЯ НАУЧНАЯ КОНФЕРЕНЦИЯ «ИСКУССТВО И МАШИННАЯ ЦИВИЛИЗАЦИЯ»...
Published 2021-06-01“…Along with the study of new challenges, old issues were raised, which became in demand in the machine civilization: originals and copies of artworks, the boundaries of conventionality and overcoming distrust in new media, narratives and poetics in serious and entertaining screen genres. The conference reports were divided into six blocks: Theoretical Models, Screen Arts—Cinema, Fine Arts, Music, PC Games, and Digitalization. …”
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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures
Published 2025-02-01“…Early screening for coronary heart disease (CHD) remains insufficiently addressed, underscoring the need for a more effective screening tool. …”
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753
Play, watch, share: the dissemination of the cultural presence of games on video-based social media
Published 2025-07-01“…Finally, text proctyessing is performed via manual coding, screening, classification and summarization. We obtain the IR dissemination model of digital cultural presence. 1. …”
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Fecal occult blood affects intestinal microbial community structure in colorectal cancer
Published 2025-01-01“…Characteristic gut bacteria were screened, and various machine learning algorithms were applied to construct CRC risk prediction models. …”
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Explainable machine learning for predicting lung metastasis of colorectal cancer
Published 2025-04-01“…We selected the best algorithm and visualized it using SHAP. We conducted a validation of the model utilizing data from a Chinese hospital to assess its practicality. …”
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756
Cost-effectiveness analysis of best management practices for non-point source pollution in watersheds: A review
Published 2017-03-01“…According to the accounting results, two optimization criteria, namely cost minimization and benefit maximization, were employed to screen for the most cost effective measures. Application of cost-effectiveness analysis method included three categories, coupling NPS model with empirical calculation methods, coupling NPS model with economic model and cost-effectiveness analysis based on optimization algorithm. …”
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Multi-Class Classification Using Improved Mahalanobis-Taguchi System Based on Binary Tree and Its Application
Published 2025-06-01“…Aiming at the inadequacy of Mahalanobis-Taguchi System(MTS), an improved MTS optimization model(MTSO) is proposed. The core idea is that a number of optimization objectives are proposed based on the purpose and characteristics of the data classification problem and optimization model is used for screening important variables instead of orthogonal arrays and signal-noise-ratio. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis
Published 2024-09-01“…We performed a claims data analysis using a machine learning algorithm. To build our model, the study population was randomly divided into an 80% training subset and a 20% testing subset and tested and trained using a cross-validation technique. …”
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Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities
Published 2022-01-01“…The algorithm extracts mixed feature information of local long path and local short path based on the information retention module, and decomposes the information by combining wavelet transform, inputs the different components obtained from the decomposition into the network for training, and removes the noise by subsequent feature screening of the network structure. …”
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Comparative performance of deep learning architectures for diabetic peripheral neuropathy detection using corneal confocal microscopy: a retrospective single-centre study
Published 2025-08-01“…For single-image predictions in the three-class classification task of CCM images, the InceptionV3 model achieved a precision of 0.8385, a recall of 0.9083, an F1 score of 0.8720 and an AUC of 0.8769 for predicting DPN+.Conclusions The InceptionV3-based DLA model achieved superior performance compared with traditional convolutional neural network architectures like ResNet and DenseNet, and the Swin transformer model, highlighting its potential for effective DPN screening.…”
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