Enhancing Security in DNP3 Communication for Smart Grids: A Segmented Neural Network Approach by Shahid Allah Bakhsh, Muhammad Shahbaz Khan, Oumaima Saidani, Nada Alasbali, S. Qasim Abbas, Muhammad Almas Khan, Jawad Ahmad

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Evaluating Sparse Feature Selection Methods: A Theoretical and Empirical Perspective by Monica Fira, Liviu Goras, Hariton-Nicolae Costin

“…The mathematical foundations of feature selection methods inspired by compressed detection are presented, highlighting how the principles of sparse signal recovery can be applied to identify the most relevant features. …”
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Multi-Type Change Detection and Distinction of Cultivated Land Parcels in High-Resolution Remote Sensing Images Based on Segment Anything Model by Zhongxin Huang, Xiaomei Yang, Yueming Liu, Zhihua Wang, Yonggang Ma, Haitao Jing, Xiaoliang Liu

“…By performing spatial connection analysis on cultivated land parcel units extracted by the SAM for two phases and combining multiple features such as texture features (GLCM), multi-scale structural similarity (MS-SSIM), and normalized difference vegetation index (NDVI), precise identification of cultivation type and pattern change areas was achieved. …”
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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The first stage employs an optimized increment-based detection algorithm achieving 95.0% for recall and 54.8% for precision through multidimensional analysis. …”
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A case report of fatal familial insomnia with cerebrospinal fluid leukocytosis during the COVID-19 epidemic and review of the literature by Zheng Wang, Yueqi Huang, Shuqi Wang, Jiefang Chen, Gesang Meiduo, Man Jin, Xiaoying Zhang

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A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and D... by Orhan Cicek, Yusuf Bahri Özçelik, Aytaç Altan

“…However, the nonlinear dynamics of these images pose significant challenges for reliable detection. This study presents a novel approach that integrates chaotic functional connectivity (FC) matrices and fractal dimension analysis to address these challenges. …”
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Clinical and epidemiological features of respiratory syncytial infection in children of different age by V. B. Rovniy, Yu. V. Lobzin, I. V. Babachenko, O. M. Ibragimova, E. S. Romanova

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Decreased Expression of Aquaporins as a Feature of Tubular Damage in Lupus Nephritis by Maxime Melchior, Marie Van Eycken, Charles Nicaise, Thomas Duquesne, Léa Longueville, Amandine Collin, Christine Decaestecker, Isabelle Salmon, Christine Delporte, Muhammad Soyfoo

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GAF-GradCAM: Guided dynamic weighted fusion of temporal and frequency GAF 2D matrices for ECG-based arrhythmia detection using deep learning by Zakaria Khatar, Dounia Bentaleb, Noreddine Abghour, Khalid Moussaid

“…Optimizing this fusion process fine-tunes the balance between temporal and frequency information, thus focusing the model on the most critical ECG features. As a result, training accuracy reached 99.68% and validation accuracy 98.78%, alongside a substantial reduction in loss, underscoring the efficacy of Grad-CAM-guided fusion in integrating essential ECG features and advancing arrhythmia detection accuracy. …”
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Features of the course and therapy of HIV infection in children at different stages of the disease by J. C. Hakizmana, E. B. Yastrebova, V. N. Timchenko, D. A. Gusev, O. V. Bulina

“…Purpose of the study. Analysis of clinical and laboratory features of the course of HIV infection and antiviral therapy in children at different stages of the disease.Materials and methods. …”
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Features of Diseases of the Anterior Part of the Eye in Patients after COVID-19 by E. V. Yani, E. N. Orlova, K. E. Seliverstova

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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

“…This study introduces a novel approach to brain tumor classification by exploring three pre-trained convolutional neural network (CNN) models: DenseNet201, EfficientNetB5, and InceptionResNetV2, combined with softmax activation for feature extraction. These features are then subjected to Principal Component Analysis (PCA) for dimensionality reduction. …”
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Enhanced Blade Fault Diagnosis Using Hybrid Deep Learning: A Comparative Analysis of Traditional Machine Learning and 1D Convolutional Transformer Architecture by Syed Asad Imam, Meng Hee Lim, Ahmed Mohammed Abdelrhman, Iftikhar Ahmad, Mohd Salman Leong

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Automatic model of sleep apnea detection using optimized weighted fusion process of hybrid convolution (1D/2D) efficient attention network from EEG signals by R. Nandakumar, Rajesh Arunachalam, R Pugalenthi, Karthikayen Arunachalam

“…However, PSG generates extensive data, making manual analysis labor-intensive and inefficient. Methods In this work, a hybrid deep learning framework for automated SA detection combines advanced feature extraction and efficient classification techniques. …”
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Features of management strategy for the implementation of innovations aimed at improving the competitiveness of the enterprise by V. S. Alieva

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MODERN METHODS OF AUTOMATIC RECTANGLE OBJECTS DETECTION by E. S. Matusevich, I. E. Kheidorov

“…The algorithm for object detection based on correlation analysis, as well as the algorithm containing the use of Canny edge detector, Hough and Radon transform for lines detection, and then, depending on the properties of the object lines combining in the rectangular area, were explored. …”
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Feature Fusion for Improved Skin Cancer Diagnosis Using Support Vector Machines by ali fahim

“…As such, the SVM classifier can be considered effective, for the early detection of skin cancers. The results from this investigation verify that the capacity of SVMs, in terms of skin cancer diagnosis, is greatly improved with the utilization of feature fusion techniques. …”
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Features of water extracts sample preparation of solar panels components for biotesting by M. Semenova, A. Smirnov, I. Vezhenkova, T. Kustov, A. Kovalevskaya

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Passive Diagnosis for WSNs Using Time Domain Features of Sensing Data by Lufeng Mo, Jinrong Li, Guoying Wang, Liping Chen

“…This paper presents a passive diagnosis method used for fault detection and fault classification based on the time domain features of sensing data (TDSD). …”
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Allgrove syndrome in endocrinology: Difficulties of diagnosis and treatment features. Case report by Uliana V. Buyvalenko, Anna R. Levshina, Anna K. Eremkina, Kseniya A. Komshilova, Nadezhda M. Platonova

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