Generalization challenges in video deepfake detection: methods, obstacles, and technological advances by LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang

“…Regarding the challenges of cross-dataset detection, the paper analyzes how differences in feature distributions between datasets lead to the performance degradation of traditional deep learning models in cross-domain applications. …”
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ANALYTICAL FEATURES OF SYNTHETIC MDMB(N)-073F CANNABIMIMETICS AND ITS MARKERS IN BIOLOGICAL MATERIAL by S. S. Kataev, O. N. Dvorskaya, M. A. Gofenberg, A. V. Labutin, A. B. Melentyev

“…The aim of the research is to study both analytical features of synthetic MDMB(N)-073F cannabimimetics of indazole carboxamides group by gas chromatography methods combined with tandem mass spectrometry (GC-MS) and high performance liquid chromatography with high-resolution mass spectrometry (HPLC-HRMS) as well as characteristics of the major MDMB(N)-073F metabolite, its glucuronide and derivatives, using gas chromatography with mass-spectrometric (GC-MS) detection and high-performance liquid chromatography (HPLC) with MS/MS mass spectrometry (HPLC-MS/MS) in urine samples to be applied in expert practice, chemical-toxicological and forensic and chemical analyses.Materials and methods. …”
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EEG alpha/beta features as a biomarker for quantifying pain in patients with lumbar disk herniation by Rumei Li, Rumei Li, Wanqi Shao, Shumei Zhao, Lingli Wang, Chao Yu, Chao Yu, Lanying Liu, Kuiying Yin

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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…Keypoint detection is achieved through pose estimation, and full-body feature extraction includes using OpenPose for movable body parts, the Lucas-Kanade method for a 3D Cartesian view, and Texton Map techniques. …”
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Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Objectives: This study aims to develop a deep learning-based method to detect anomalies in high-dimensional energy metering data, overcoming the limitations of existing techniques that struggle with data complexity and lack effective contextual analysis. …”
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Fusion feature-based hybrid methods for diagnosing oral squamous cell carcinoma in histopathological images by Jiaxing Li

“…ObjectiveThis study is experimental in nature and assesses the effectiveness of the Cross-Attention Vision Transformer (CrossViT) in the early detection of Oral Squamous Cell Carcinoma (OSCC) and proposes a hybrid model that combines CrossViT features with manually extracted features to improve the accuracy and robustness of OSCC diagnosis.MethodsWe employed the CrossViT architecture, which utilizes a dual attention mechanism to process multi-scale features, in combination with Convolutional Neural Networks (CNN) technology for the effective analysis of image patches. …”
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Methodology for Feature Selection of Time Domain Vibration Signals for Assessing the Failure Severity Levels in Gearboxes by Antonio Pérez-Torres, René-Vinicio Sánchez, Susana Barceló-Cerdá

“…Early failure detection in gear systems reduces unplanned downtime and associated maintenance costs in rotating machinery. …”
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Status and serological features of occult hepatitis B virus infection among blood donors in Xuzhou by LIU Jiahui, WANG Bei, ZHOU Liling

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Clinical Epidemiology Features and Risk Factors for Acute Diarrhea Caused by Rotavirus A in Vietnamese Children by Dang Van Chuc, Dang Phuong Linh, Dang Viet Linh, Pham Van Linh

“…Among the 321 children included in our analysis, 221 (68.8%) children were positive for RVA. …”
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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…AE signals, capturing the dynamic responses of machine components, are transformed into continuous wavelet transform (CWT) scalograms for further analysis. Gaussian filtering is applied to enhance the clarity of these scalograms, effectively reducing noise while maintaining essential features. …”
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Features of the epidemic situation on tuberculosis in the conditions of climate change in the Far North of the Republic of Sakha (Yakutia) by Svetlana Zorina, Egor Prokopyev, Maria Vinokurova, Olga Kondrateva, Mr Ruslan Khachetlov, Irina Lizinfeld, Liubov Parolina

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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…In addition to fine-tuning input dimensionality, F-test feature selection increases learning efficiency.ResultsThrough the integration of feature importance analysis and conventional performance measures, this study presents valuable insights into the discriminative neurophysiological patterns associated with Schizophrenia, advancing both diagnostic and neuroscientific expertise. …”
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Clinical and psychopathological features of course and correction of depressive disorders in patients with brain tumors, prevention and rehabilitation by V.V. Ogorenko, A.G. Kyrychenko, O.M. Hnenna

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Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features by Rajkumar Govindarajan, K. Thirunadanasikamani, Komal Kumar Napa, S. Sathya, J. Senthil Murugan, K. G. Chandi Priya

“…This method offers a practical tool for clinicians and researchers to support early diagnosis and personalized risk assessment of AD, thus aiding in timely and informed clinical decision-making.Accurate Prediction: Gradient Boosting model achieved 93.9 % accuracy for early Alzheimer’s detection.Explainability: SHAP values provided interpretable insights into key clinical features.Clinical Tool: A Streamlit-based web app enabled real-time, explainable predictions for users.…”
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Clinical features of rhinovirus infection in hospitalized adult patients during the epidemic season 2017–2018 by M. A. Bichurina, L. V. Voloshchuk, A. Go, M. M. Pisareva, D. A. Guzhov

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A Hybrid Brain Stroke Prediction Framework: Integrating Feature Selection, Classification, and Hyperparameter Optimization by Mohammad Amin, Khalid M. O. Nahar, Hasan Gharaibeh, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Nesrine Atitallah, Ali Gharaibeh, Raneem Hamad, Raed Abu Zitar, Aseel Smerat, Laith Abualigah

“…We used a publicly available Harvard Stroke Prediction Data Warehouse dataset, applying multiple feature selection methods: ANOVA, chi‐square, mutual information classification, and analysis of variance to identify relevant features. …”
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EXAMINING THE IMPACT OF FEATURE SELECTION TECHNIQUES ON MACHINE AND DEEP LEARNING MODELS FOR THE PREDICTION OF COVID-19 by Hafiza Zoya Mojahid, Jasni Mohamad Zain, Marina Yusoff, Abdul Basit, Abdul Kadir Jumaat, Mushtaq Ali

“…This study delves into key variable selection methods—specifically Recursive Feature Elimination (RFE), Principal Component Analysis (PCA) and Least Absolute Shrinkage and Selection Operator (LASSO). …”

Study on infrasonic leakage monitoring and signal processing for product oil pipeline by Yuanbo YIN, Yuxing LI, Wen YANG, Shu LU, Chen ZHANG, Cuiwei LIU, Kai YANG, Wuchang WANG

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Research on Pantograph Defect Classification Based on Vibration Signals by Vytautas Gargasas, Kęstas Rimkus, Mindaugas Alekna, Andrius Knyš, Mindaugas Žilys, Algimantas Valinevičius

“…However, in these publications, mechanical vibration analysis is limited to signal shape and spectral analysis. …”
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Bone marrow composition features and possibilities of tumor involvement diagnosing in patients with classic Hodgkin’s lymphoma by F. M. Abbasbeyli, P. A. Zeynalova, M. A. Vernyuk, A. A. Fedenko, T. Yu. Mushkarina, A. A. Melnikova, V. Yu. Kovalskaya, L. Yu. Grivtsova

“…Detection of CD20+/±- and cd15+/±-Berezovsky–Reed–Sternberg cells according to primary tumor IHC analysis indicates a low probability of bone marrow tumor infiltration, but further analysis is required on a large clinical and laboratory material.…”
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