Reconstructing coastal ponds functional classification: Integration of multi-feature remote sensing by Yijun Tong, Chen Lin, Ke Song, Tingchen Jiang, Ronghua Ma, Wenzhuo Cui, Danhua Ma, Jianchun Chen, Zhenxing Wang, Xiaofen Bai

“…The functional types of PWS can be categorized as aquaculture, landscaping, water storage, and salt drying. (2) Regarding different PWS functional types, significant differences were demonstrated in terms of remote sensing features and geographical patterns. Remote sensing features revealed that LCAP, MAS, and SP differ greatly across various spectral bands, whereas NP varied substantially in shape characteristics, and LP exhibited distinct spatial distribution. …”
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AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

“…Specifically, the maximum soft pooling module improves the continuity and integrity of detected cracks. The adaptive crack feature quantization module enhances the contrast between cracks and background features and strengthens the model’s focus on critical regions through spatial feature fusion. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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SPECIFIC FEATURES OF ELECTROENCEPHALOGRAPHIC PAROXYSMAL ACTIVITY REGISTRATION IN OLD AGE GROUP PATIENTS by S. A. Gulyaev, I. V. Arkhipenko, S. E. Gulyaeva, A. A. Ovchinnikova, A. V. Ovchinnikov

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Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…A high-precision prediction framework driven by multiple features was constructed by incorporating environmental and geographical parameters into the model input to enhance the overall performance. …”
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Comprehensive study of anaplastic large cell lymphoma: clinicopathological features from Indonesia by Agnes Stephanie Harahap, Ivana Santoso, Stefanny Charles, Nadia Ayu Mulansari, Maria Francisca Ham

“…Abstract Objective Anaplastic large cell lymphoma (ALCL) is a rare and aggressive CD30-positive non-Hodgkin lymphoma with histopathological features overlapping Hodgkin and T-cell lymphomas. …”
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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…Based on acoustic feature analysis, this study systematically examines the differences in vowel pronunciation characteristics among Mandarin learners at various proficiency levels. …”
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The clinical features and 18F-FDG-PET analysis of absence status epilepsy by Jing-Wen Zuo, Xiao-Qiu Shao, Qun Wang, Rui-Juan Lv

“…Objective To summarize the clinical features and 18F-fluorodeoxy-glucose positron emission tomography (18F-FDG-PET) patterns of absence status epilepsy (ASE). …”
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Exploring the potentialities and challenges of deep learning for simulation and prediction of urban sprawl features by Ange Gabriel Belinga, Stéphane Cedric Tékouabou Koumetio, Mohamed El Haziti

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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…The method identifies linear laws that capture shared patterns within a reference class, enabling compact and verifiable representations of time series data. …”
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EEG-Based Emotion Detection Using Roberts Similarity and PSO Feature Selection by Mustafa Hussein Mohammed, Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ayman Ibaida

“…The proposed classifier addresses these challenges by segmenting EEG signals into block sizes categorized as small (1 to 10 samples), medium (20 to 100 samples), and large (200 to 1,000 samples), demonstrating particularly strong performance with medium and large block sizes to capture essential features. Integration of Particle Swarm Optimization (PSO) for feature selection, with Robert’s similarity as the fitness function, effectively refines the feature set, boosting classification accuracy and computational efficiency. …”
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Eye Tracking in Neuropsychological Research of Visual Gnosis Features in Children with Hearing Impairment by Y.K. Smirnova, Ju.E. Grigorova, L.N. Gordeeva

“…The duration of the scanning path, spatial density of fixations, scanning regularity, and scanning direction during image recognition differ. Features of the visual search strategy are observed in the number of switches, fixation time, and patterns of gaze transitions between areas of interest. …”
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Distinct clinicopathological features and treatment differences in breast cancer patients of young age by Rasmus O. C. Humlevik, Amalie A. Svanøe, Turid Aas, Anette Heie, Anna K. M. Sæle, Lars A. Akslen, Elisabeth Wik, Erling A. Hoivik

“…Young patients presented more aggressive clinico-pathologic features such as higher histological grade, more frequent lymph node metastasis involvement, and estrogen receptor negativity. …”
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Surface Electromyography and Gait Features in Patients after Anterior Cruciate Ligament Reconstruction by Xipeng Wu, Hao Zhang, Hongxing Cui, Wenbin Pei, Yixuan Zhao, Shanshan Wang, Zhijie Cao, Wei Li

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Employee Turnover Prediction Model Based on Feature Selection and Imbalanced Data Handling by Yuan Fang, Zhongqiu Zhang

“…The dataset underwent rigorous preprocessing and exploratory data analysis (EDA) to identify key patterns and relationships. Feature selection was performed using correlation matrix analysis, Chi-Square tests, and Recursive Feature Elimination (RFE) to identify the most relevant features. …”
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N6-methyladenine identification using deep learning and discriminative feature integration by Salman Khan, Islam Uddin, Sumaiya Noor, Salman A. AlQahtani, Nijad Ahmad

“…In this study, we present Deep-N6mA, a novel Deep Neural Network (DNN) model incorporating optimal hybrid features for precise 6 mA site identification. The proposed framework captures complex patterns from DNA sequences through a comprehensive feature extraction process, leveraging k-mer, Dinucleotide-based Cross Covariance (DCC), Trinucleotide-based Auto Covariance (TAC), Pseudo Single Nucleotide Composition (PseSNC), Pseudo Dinucleotide Composition (PseDNC), and Pseudo Trinucleotide Composition (PseTNC). …”
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Back pain: from pathophysiological mechanisms and clinical features to modern approaches to therapy by N. V. Titova, Yu. N. Bezdolny, A. A. Slipko

“…When inflammatory pain patterns are present in the sacroiliac joints region, it is mandatory to rule out sacroiliitis within the spectrum of seronegative spondyloarthritis (including ankylosing spondylitis and others) using a specialized diagnostic algorithm. …”
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An Agglomerative Clustering Combined with an Unsupervised Feature Selection Approach for Structural Health Monitoring by Tales Boratto, Heder Soares Bernardino, Alex Borges Vieira, Tiago Silveira Gontijo, Matteo Bodini, Dmitriy A. Martyushev, Camila Martins Saporetti, Alexandre Cury, Flávio Barbosa, Leonardo Goliatt

“…The results obtained for the four analyzed cases provide clear insights into the patterns of behavior and structural anomalies.…”
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Multiscale Feature Fusion for Salient Object Detection of Strip Steel Surface Defects by Li Zhang, Xirui Li, Yange Sun, Yan Feng, Huaping Guo

“…This paper proposes a novel multiscale feature fusion (MFF) method for salient object detection of strip steel surface defects, fusing multiscale features through the following three steps: 1) generating rough multiscale features using upsampling/downsampling or convolution operations with sampling techniques, 2) applying self-attention operations to each feature to generate a refined representation, and 3) fusing the multiscale features from the previous two steps for salient object detection. …”
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Features of the initial stage of digitalization of the executive authority of Ukraine: historical and legal overview by E. Najafli

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