Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection by Mohammad Abrar, Abdu Salam, Ahmed Albugmi, Fahad Al-otaibi, Farhan Amin, Isabel de la Torre, Thania Candelaria Chio Montero, Perla Araceli Arroyo Gala

“…In addition, classification is performed using a Support Vector Machine (SVM) based on features extracted through Multivariate Empirical Mode Function (MEMF) and entropy measures. …”
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A novel fault location method for multi-terminal transmission lines based on composite analysis of time-frequency fault traveling waves by Jupeng Zeng, Xiangjun Zeng, Hao Bai, Kun Yu, Min Xu, Xiaolong She, Feng Liu

“…According to the characteristic that the FTW natural frequency (NF) is inversely proportional to the transmission distance, the fault branch determination vector is defined, and the corresponding principle is proposed to determine the fault branch. …”
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Channel equalization in ultraviolet communication based on LSTM-DNN hybrid model by Liwei Zhang

“…The model leverages LSTM to process temporal dependencies and combines it with DNN for nonlinear feature extraction, thereby improving its adaptability to single-scattering channels. …”
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Intertextuality of the Personosphere as a Factor of Meta-Genre (Clifford Simak “Shakespeare’s Planet”) by Dan Paranyuk, Alyona Tychinina

“…Particular emphasis has been placed on the fact that the evolution of science fiction into a meta-genre format is due to a number of factors, such as the simulative nature of the chronotope of possible and parallel worlds, the change in the anthropological vector of texts, and the involvement of samples of other art forms (intermedial components). …”
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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

“…A hybrid information extraction process combining rule-based parsing and a fine-tuned Universal Information Extraction (UIE) model was employed to extract knowledge from unstructured texts. …”
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Accurate Indoor Home Location Classification through Sound Analysis: The 1D-ILQP Approach by Umut Erman, Türker Tuncer, Nura Abdullahi, Sengul Dogan, Erhan Akbal

“…This novel 1D-ILQP plays a central role in the feature extraction process, generating textural features from the acoustic signals. …”
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Machine learning-enhanced fully coupled fluid–solid interaction models for proppant dynamics in hydraulic fractures by Dennis Delali Kwesi Wayo, Sonny Irawan, Lei Wang, Leonardo Goliatt

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Leukocyte index of intoxication according to V. K. Ostrovskii as a criterion for assessing bacterial infection by M. I. Gromov, A. V. Rysev, Yu. F. Zhuravlev, L. P. Pivovarova, O. B. Ariskina, E. V. Markelova

“…The calculation of LII according to Ostrovsky or its simplified version without taking into account plasma cells (neutrophils + immature granulocytes)/(lymphocytes + monocytes + eosinophils + basophils) is appropriate and easily applicable in wide clinical practice for assessing a bacterial infection and the development vector of an infectious process.…”
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À la croisée du développement de la compétence numérique et de la compétence en langue étrangère : étude préliminaire pour le développement d'un outil ludopédagogique pour les 4-7... by Laurence Schmoll, Joséphine Rémon, Pascale Manoïlov, Anissa Hamza, Élodie Oursel

“…Our research question at this stage deals with the data needed to inform the development of a digital English learning tool for playschool pupils in an iterative improvement process. From a theoretical perspective, we approach this problem through the lens of digital literacy, at the interconnection of three dimensions, namely technological literacy, meaning-making literacy, and interaction literacy. …”
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Precision Inverse Modeling of Highway Pavements Based on Standardized Alignment by Ruifeng Ma, Qing Zhu, Xuming Ge, Xin Jia, Han Hu, Tao Liu

“…This approach involves extracting vector lines from point clouds and applying constraints at pivotal points on highway pavement cross-sections. …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…This paper proposes a railway worker detection method based on improved support vector machines (ISVM), while using non-local mean noise reduction and histogram equalisation pre-processing techniques to optimise image quality to improve detection efficiency and accuracy. …”
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SOX3 protein is associated with epithelial-mesenchymal transition (EMT) changes in human melanoma cell by Ana Paula Gomes dos Santos Miranda, Bruna Mendes Lima, Bárbara Andrade de Carvalho, Emanuele Tadeu Pozzolini, Diego Crimi de Castro, Fábio Eduardo dos Santos, Luciana de Oliveira Andrade, Jeremy W. Prokop, Adam Underwood, Helen Lima Del Puerto, Enio Ferreira

“…Human melanoma cell line SK-MEL-28 was transfected with a SOX3 expression vector to evaluate the impact of SOX3-induced expression on EMT markers, cellular viability, and wound healing. …”
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Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants by Mohamed Farag Taha, Hanping Mao, Samar Mousa, Lei Zhou, Yafei Wang, Gamal Elmasry, Salim Al-Rejaie, Abdallah Elshawadfy Elwakeel, Yazhou Wei, Zhengjun Qiu

“…The suggested methodology presents a pathway to automating the process of nutrient status diagnosis throughout the entire plant life cycle, with the LSTM technique poised to assume a pivotal role in forthcoming time-series analyses for precision agriculture.…”
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Preclinical Evaluation of ⁶⁸Ga-labeled RGD Peptide for Detection of Malignant Angiogenesis by O. E. Klementyeva, A. B. Bruskin, A. S. Lunev, M. G. Rakhimov, K. A. Luneva, G E. Codina

“…The molecular participants in the process are gallium-68 labeled vector to the delivery of radionuclides and positron-emission tomography (PET) imaging.Aim. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied within a five-fold cross-validation framework, ensuring a balanced training set while maintaining an unbiased validation process. Six machine learning models, including Support Vector Machine, Logistic Regression, Random Forest, XGBoost, Artificial Neural Network, and AdaBoost, were trained using extensive hyperparameter tuning. …”
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A clinical case of thrombocytopenic purpura in a 13-year-old child by A. Yu. Babko, O. B. Gordeeva, A. V. Dobrotok

“…Immune thrombocytopenic purpura is an immune-mediated disease that develops as a result of impaired immune tolerance to platelet antigens and the formation of antibodies to them, followed by a decrease in platelet levels per unit volume of blood, which can lead to the development of hemorrhagic syndrome. The pathological process in immune thrombocytopenic purpura is based on the breakdown of immunological tolerance to its own antigen. …”
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Production and optimization of affordable artificial geopolymer aggregates containing crumb rubber, plastic waste, and granulated cork based on machine learning algorithms by Mohamed Abdellatief, Abedulgader Baktheer, Mohamed Shahin, Aref A. Abadel, Ashraf M. Heniegal

“…The properties of AGAs were evaluated, and the optimal utilization of waste materials was determined using response surface methodology (RSM) and machine learning models, including linear regression (LR), support vector regression (SVR), and Gaussian process regression (GPR). …”
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Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing by Changchun Hei, Xiaowen Li, Ruochen Wang, Jiahui Peng, Ping Liu, Xialan Dong, P. Andy Li, Weifan Zheng, Jianguo Niu, Xiao Yang

“…The primary objective was to develop classification models to identify crucial PRDEGs integral to the ischemic stroke process. Leveraging three distinct machine learning algorithms (LASSO, Random Forest, and Support Vector Machine), models were developed to differentiate between the Control and the IS patient samples. …”
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Anderson impurity solver integrating tensor network methods with quantum computing by François Jamet, Lachlan P. Lindoy, Yannic Rath, Connor Lenihan, Abhishek Agarwal, Enrico Fontana, Fedor Simkovic IV, Baptiste Anselme Martin, Ivan Rungger

“…Solving the Anderson impurity model typically involves a two-step process, where one first calculates the ground state of the Hamiltonian and then computes its dynamical properties to obtain Green’s function. …”
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Research on Tongue Image Segmentation and Classification Methods Based on Deep Learning and Machine Learning by Bin Liu, Zeya Wang, Kang Yu, Yunfeng Wang, Haiying Zhang, Tingting Song, Hao Yang

“…In this study, we propose a tongue image segmentation method based on deep learning and a pixel-level tongue color classification method utilizing machine learning techniques such as support vector machine (SVM) and ridge regression. These two approaches together form a comprehensive framework that spans from tongue image acquisition to segmentation and analysis. …”
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