Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan by Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk

“…Overall, this study demonstrates the potential of machine learning algorithms for predicting tunnel abrasion in SBTs.Paper highlightsThis study introduces a validated 2D model for tunnel abrasion based on field data, contributing to improved sediment management in SBTs.ASM Model efficiently predicts abrasion mapping in SBT, achieving 86.4% overall accuracy.High sensitivity and specificity in distinguishing abraded and non-abraded areas.Captures four complex abrasion patterns in straight and curved sections but is limited to relatively small wave-like patterns.Geometric and hydraulic parameters, particularly the elongated distance and flow velocity, exhibit significant impacts in the ASM model.…”
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Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics by Zhenze Zhang, Zhenze Zhang, Caiqing Zhao, Caiqing Zhao, Yijun Zhou, Ling Yao, Peng Liu, Ziling Fang, Nian Fang, Nian Fang

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Assessing the spatial-temporal performance of machine learning in predicting grapevine water status from Landsat 8 imagery via block-out and date-out cross-validation by Eve Laroche-Pinel, Vincenzo Cianciola, Khushwinder Singh, Gaetano A. Vivaldi, Luca Brillante

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Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm by Hongtao Chen, Zhengbai Lin, Quan Xu

“…This paper compared and analyzed football players’ technical action behavior recognition based on the PCA–LBP algorithm and the traditional LBP recognition. The data comparing the two algorithms are based on data from 200 football players at a football match in 2020. …”
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Machine Learning Algorithms Performance Evaluation for Intrusion Detection by Shyla ., Kapil Kumar, Vishal Bhatnagar

“…The detection of Intrusion is the major research problem faced in the area of information security, the objective is to scrutinize threats or intrusions to secure information in the network Intrusion detection system (IDS) is one of the key to conquer against unfamiliar intrusions where intruders continuously modify their pattern and methodologies. In this paper authors introduces Intrusion detection system (IDS) framework that is deployed over KDD Cup99 dataset by using machine learning algorithms as Support Vector Machine (SVM), Naïve Bayes and Random Forest for the purpose of improving the precision, accuracy and recall value to compute the best suited algorithm.…”
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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

“…Some areas of applications of ML algorithms include cluster analysis, pattern recognition, image processing, natural language processing, and medical diagnostics. …”
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Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals by Gulay Tasci, Prabal Datta Barua, Dahiru Tanko, Tugce Keles, Suat Tas, Ilknur Sercek, Suheda Kaya, Kubra Yildirim, Yunus Talu, Burak Tasci, Filiz Ozsoy, Nida Gonen, Irem Tasci, Sengul Dogan, Turker Tuncer

“…<b>Background:</b> Electroencephalography (EEG) signal-based machine learning models are among the most cost-effective methods for information retrieval. …”
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Histopathological Image Analysis Using Machine Learning to Evaluate Cisplatin and Exosome Effects on Ovarian Tissue in Cancer Patients by Tuğba Şentürk, Fatma Latifoğlu, Çiğdem Gülüzar Altıntop, Arzu Yay, Zeynep Burçin Gönen, Gözde Özge Önder, Özge Cengiz Mat, Yusuf Özkul

“…Classification was performed using ML algorithms, including decision tree (DT), k-nearest neighbors (KNN), support vector machine (SVM), and Artificial Neural Network (ANN). …”
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Iterative Shaping of Error Patterns For Normal Syndrome Decoding of Iterative Codes by X. H. Ren, V. K. Kanapelka, V. Yu. Tsviatkou

“…In the decoder, the error position of the twodimensional can be obtained by the operations that first calculate the syndromes and norms, then match with the error patterns in the existing library. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…In addition, the unsupervised K-means algorithm was implemented to analyze vehicle gear changes, identify driving patterns, and segment the data into meaningful groups. …”
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Weighted Content Similarity Feature for Software Architecture Anti-Patterns Prediction by Somayeh Kalhor, Mohammad Reza Keyvanpour

“…So, it is more effective than these two features in predicting dependencies between components using machine learning algorithms.…”
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MPFM-VC: A Voice Conversion Algorithm Based on Multi-Dimensional Perception Flow Matching by Yanze Wang, Xuming Han, Shuai Lv, Ting Zhou, Yali Chu

“…Voice conversion (VC) is an advanced technology that enables the transformation of raw speech into high-quality audio resembling the target speaker’s voice while preserving the original linguistic content and prosodic patterns. In this study, we propose a voice conversion algorithm, Multi-Dimensional Perception Flow Matching (MPFM-VC). …”
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Review of Automatic Estimation of Emotions in Speech by Douglas O’Shaughnessy

“…Many methods of emotion recognition have been found in research on pattern recognition in other areas, e.g., image and text recognition, especially in recent methods for machine learning. …”
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The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China by Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Gu

“…Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

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Exploring the Influencing Factors of Surface Ozone Variability by Explainable Machine Learning: A Case Study in the Basilicata Region (Southern Italy) by Roberta Valentina Gagliardi, Claudio Andenna

“…In this study, a methodological approach combining both supervised and unsupervised machine learning algorithms (MLAs) with the Shapley additive explanations (SHAP) method was used to understand the key factors behind O₃ variability and to explore the nonlinear relationships linking O₃ to these factors. …”
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Residual-based approach for authenticating pattern of multi-style diacritical Arabic texts. by Saqib Hakak, Saqib Hakak, Amirrudin Kamsin, Shivakumara Palaiahnakote, Omar Tayan, Mohd Yamani Idna Idris, Khir Zuhaili Abukhir

“…Furthermore, we propose to use the Tuned BM algorithm (BMT) exact pattern matching algorithm to verify the substituted Uthmani verse with a given database of plain Qur'anic style. …”
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Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods by Chu Zhang, Chang Wang, Fei Liu, Yong He

“…The potential of using mid-infrared transmittance spectroscopy combined with pattern recognition algorithm to identify coffee variety was investigated. …”
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Generate vector graphics of fine-grained pattern based on the Xception edge detection. by Anqi Chen, Yicui Peng, Meng Li, Hao Chen, Chang Liu, Jinrong Hu, Xiang Wen, Guo Huang

“…With higher autonomy, the machine learning algorithms are able to accurately extract the image information, understand and convey the concept contained in it. …”
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Bioinformatics Analysis of Oxidative Stress-Related Genes and Immune Infiltration Patterns in Vitiligo by Yang M, Wang H, Zhang R

“…Immune cell infiltration between vitiligo and normal control groups was assessed using the CIBERSORT algorithm. Additionally, two machine learning algorithms were employed to identify hub genes, perform enrichment analyses, and evaluate their correlation with immune infiltration.Results: A total of 415 Oxidative Stress-DEGs were identified in vitiligo, including 317 up-regulated and 98 down-regulated genes. …”
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