Time Series Analysis of Mining-Induced Subsidence Using Small Baseline Subset Interferometric Synthetic Aperture Radar (Wanli Mining Area, Inner Mongolia, China) by Xinlei Xue, Jinzhu Ji, Guoping Li, Huaibin Li, Qi Cao, Kai Wang

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An Automated Method Inspired by Taxonomic Classification for Distinguishing Chilean Pelagic Fish Species by Vincenzo Caro Fuentes, Danny Luarte, Ariel Torres, Jorge E. Pezoa, Sebastian E. Godoy, Sergio N. Torres, Mauricio A. Urbina

“…Our method includes taxonomic analysis, exploiting geometric characteristics such as distances and angles between key body parts, segmenting patterned areas, and extracting texture features. Furthermore, we developed hierarchical classification models that employ a dichotomous key based on these key morphological traits to assess specific fish features such as size, shape, mouth orientation, and color patterns, simulating taxonomic classification. …”
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Grammatical Deviations in the Lesson Plans Among Bachelor of Secondary Education (BSED) English Students by Deo J. Galvez, Marie L. Celesio

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Multiscale Spatiotemporal Variation Analysis of Regional Water Use Efficiency Based on Multifractals by Tong Zhao, Yanan Wang, Yulu Zhang, Qingyun Wang, Penghai Wu, Hui Yang, Zongyi He, Junli Li

“…Temporally, the variation in fractal features between years was not prominent, while inter-seasonal variation was most complex in August during summer. …”
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Research on seismic activity and seismic structural characteristics of the Shandong region by Linhai Lu, Zhenghao Liu, Hanwen Zhang, Chaojun Wu, Jiecheng Sun, Xianfeng Ma, Dingyi Zhou, Han Han, Haojin Zhang, Rui Li

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Monthly precipitation prediction based on quadratic decomposition and improved parrot algorithm by Weijie Zhang, Yuming Zeng, Shubo Zhou, Libin Zhang, Haiquan Li, Zhongsheng Yao, Rusheng Zhou

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Clinicopathological analysis of biphenotypic sinonasal sarcoma： a case report by GONG Jingqing, CAO Duanrong, ZHUANG Yixin, QIU Li, LI Xiaoming

“…This study reported a rare case of biphenotypic sinonasal sarcoma (BSNS) and analyzed its clinicopathological features. The patient was a 35-year-old male admitted due to "recurrent right-sided nasal discharge mixed with blood for over three months". …”
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Clostridioides difficile ribotypes 001 and 126 were predominant in Tehran healthcare settings from 2004 to 2018: a 14-year-long cross-sectional study by Masoumeh Azimirad, Marcela Krutova, Abbas Yadegar, Shabnam Shahrokh, Meysam Olfatifar, Hamid Asadzadeh Aghdaei, Warren N. Fawley, Mark H. Wilcox, Mohammad Reza Zali

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K-Means Clustering and Classification of Breast Cancer Images Using Histogram of Oriented Gradients Features and Convolutional Neural Network Models: Diagnostic Image Analysis Stud... by Said Salloum

“…The proposed hybrid method included three stages: (1) unsupervised clustering using K-means to group visually similar features; (2) feature extraction using Histogram of Oriented Gradients (HOG) to capture texture and shape patterns; and (3) classification using a CNN trained on the extracted features. …”
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Research and implementation of network transmission situation awareness by ZHUO Ying, GONG Chun-ye, GONG Zheng-hu

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Big Data Deep Learning: Challenges and Perspectives by Xue-Wen Chen, Xiaotong Lin

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TFDGiniXML: A Novel Explainable Machine Learning Framework for Early Detection of Cardiac Abnormalities Based on Nonlinear Time-Frequency Distribution Gini Index Features by Mohamed Aashiq, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani, Marsyita Hanafi, Ahmed Faeq Hussein

“…These interpretable features provide clear insights into normal and abnormal ECG patterns. …”
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Research onconvolutional neural network for reservoir parameter prediction by You-xiang DUAN, Gen-tian LI, Qi-feng SUN

“…As the branch of artificial intelligence,artificial neural network solved many difficult practical problems in pattern recognition and classification prediction field successfully.However,they cannot learn the feature from networks.In recent years,deep learning becomes more and more advanced,but the research on the field of geological reservoir pa-rameter prediction is still rare.A method to predict reservoir parameters by convolutional neural network was presented,which can not only predict reservoir parameters accurately,but also get features of the geological reservoir.The study es-tablished the convolutional neural network model.Results show that the convolutional neural network can be used for reservoir parameter prediction,and get high prediction precision.Moreover,convolutional features from convolutional neural network provided important support for geological modeling and logging interpretation.…”
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Research on Detection Technology of Wind Turbine Blade AnomalyBased on Audio Data by HU Kaikai, CHEN Yanan, CHEN Gang, SHU Hui, LI Ziyuan

“…By installing a pickup on the wind turbine, analyzing and mining the collected wind turbine audio data, and based on the multi classification machine learning model, it explores a set of audio data feature analysis and pattern recognition methods. …”
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Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization by Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan

“…Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. …”
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Improvement of signal detection based on using machine learning by Bassam Abd

“…The paper strongly emphasized extracting the dataset's most essential features, which improved Support Vector Machines’ capacity to detect signals in noisy and complicated situations. …”
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A Study on CNN-Based and Handcrafted Extraction Methods with Machine Learning for Automated Classification of Breast Tumors from Ultrasound Images by Mohamed Benaouali, Mohamed Bentoumi, Mansour Abed, Malika Mimi, Abdelmalik Taleb-Ahmed

“…We evaluated our approach using four openly available datasets and investigated two categories of feature extraction methods: handcrafted methods (Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG)) and methods based on convolutional neural network (CNN) models. …”
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Integrating CEUS Imaging Features and LI-RADS Classification for Postoperative Early Recurrence Prediction in Solitary Hepatocellular Carcinoma: A Machine Learning-Based Prognostic... by Liang L, Pang J, Zhang B, Que Q, Gao R, Wu Y, Peng J, Zhang W, Bai X, Wen R, He Y, Yang H

“…Model performance was evaluated using the concordance index (C-index), area under the curve (AUC), calibration curves, decision curve analysis (DCA), and Kaplan–Meier (KM) survival analysis.Results: Five significant features identified by univariate Cox regression were included in model development: microvascular invasion (MVI), tumor size, LI-RADS classification, tumor necrosis, and arterial enhancement patterns. …”
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KRAS Mutation Status in Relation to Clinicopathological Characteristics of Romanian Colorectal Cancer Patients by Elena-Roxana Avădănei, Irina-Draga Căruntu, Irina Nucă, Raluca Anca Balan, Ludmila Lozneanu, Simona-Eliza Giusca, Diana Lavinia Pricope, Cristina Gena Dascalu, Cornelia Amalinei

“…Our results demonstrate the relationship between <i>KRAS</i> mutation and clinicopathological features, with possible impact in clinical tumour stratification and therapeutic management.…”
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Enhanced Skin Lesion Classification Using Deep Learning, Integrating with Sequential Data Analysis: A Multiclass Approach by Azmath Mubeen, Uma N. Dulhare

“…Additionally, Markov random fields (MRFs) enhance pattern recognition. The integrated system classifies lesions and evaluates whether they are responding to treatment or worsening, achieving 93% accuracy in distinguishing nodules, melanoma, and basal cell carcinoma. …”
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