Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

“…Empirical methods lack universal applicability due to their reliance on specific project conditions, while statistical models struggle with inconsistent patterns across different datasets. Furthermore, traditional AI models, including single machine learning algorithms, often overlook the multifaceted nature of overbreak, and hybrid models lack comprehensive evaluation standards. …”
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Metabolomics and nutrient intake reveal metabolite–nutrient interactions in metabolic syndrome: insights from the Korean Genome and Epidemiology Study by Minyeong Kim, Suyeon Lee, Junguk Hur, Dayeon Shin

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Automatic detection of sleep spindles by neural networks algorithms by Jan Rychlík, Roman Mouček

“…Consequently, comprehending and accurately analyzing sleep patterns is of paramount importance. This research aims to introduce, formulate, execute, and assess diverse machine/deep learning methodologies tailored for the processing of EEG signals geared explicitly towards identifying sleep spindles. …”
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Improvement of signal detection based on using machine learning by Bassam Abd

“…The proposed system depends on the support vector machine (SVM). The SVM is one of the most popular learning algorithms in different fields, such as signal processing, image processing, communication, and pattern recognition. …”
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RACH Traffic Prediction in Massive Machine Type Communications by Hossein Mehri, Hani Mehrpouyan, Hao Chen

“…Traffic pattern prediction has emerged as a promising approach for efficiently managing and mitigating the impacts of event-driven bursty traffic in massive machine-type communication (mMTC) networks. …”
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Application of Machine Learning Techniques for Bearing Fault Diagnosis by Sarra Eddai, Nabih Feki, Ahmed Ghorbel, Abdelkhalak El Hami, Mohamed Haddar

“…Machine learning enhances machine diagnostics through advanced data analysis, pattern recognition, and fault prediction. …”
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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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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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Intelligent Technologies and Robotic Machines for Garden Crops Cultivation by I. G. Smirnov, D. O. Khort, A. I. Kutyrev

“…It is noted that there is a need for developing special actuators, grippers and new control algorithms for harvesting horticulture products. (Research purpose) The research aimed to develop an intelligent control system for horticulture industrial technologies and robotic techniques for yield monitoring and fruit harvesting. …”
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Traffic congestion forecasting using machine learning methods by Ramil R. Zagidullin, Almaz N. Khaybullin

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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…The CNN model is adjusted for different convolutional layers and fully connected layers to identify patterns and features in brain tumor pictures using an enhanced salp swarm algorithm (SSA) with kernel extreme learning machine (KELM). …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“… Human intervention cannot halt natural disasters like earthquakes, but machine learning application expertise can be utilized to detect patterns in data and increase understanding and predictive power. …”
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Machine Learning‐Assisted Simulations and Predictions for Battery Interfaces by Zhaojun Sun, Xin Li, Yiming Wu, Qilin Gu, Shiyou Zheng

“…This review highlights recent progress in ML‐assisted simulations and predictions at battery interfaces, illustrating how ML accelerates the research and development trajectory. By employing ML algorithms and machine vision, simulations of lithium dendrite growth, SEI formation, and interfacial dynamics can be performed. …”
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Research on Classification of Rail Defects Based on Image Processing Algorithm by Mengying HUANG, Jiangping LUO, Wenxing WANG, Jingwei CAO

“…Therefore, a classification for rail defects based on image processing algorithm was proposed. Firstly, the Tamura texture feature algorithm was combined with the local binary pattern algorithm to extract the feature values of the defect images, and form feature vectors. …”
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Angle Modulated Artificial Bee Colony Algorithms for Feature Selection by Gürcan Yavuz, Doğan Aydin

“…Optimal feature subset selection is an important and a difficult task for pattern classification, data mining, and machine intelligence applications. …”
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Novel Multimodal Fusion Algorithm for Non-Intrusive Anxiety Detection by Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, M. Jamshed Alam Patwary

“…The study utilizes six advanced machine learning algorithms (Gaussian Naive Bayes, XGB Classifier, K-Neighbors, SVM, Decision-Tree, and RandomForest) for data classification, pattern recognition, and predictive accuracy. …”
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Modeling an Image Clustering Algorithm For Detecting Overheated Railway Axle by Oleksandr Gertsiy, Serhii Karnatov, Vitaliy Gladish, Valentyna Tkachenko

“…The principles of the proposed algorithm are described in the context of image segmentation and compression, as well as pattern recognition in the transportation domain. …”
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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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ICBoost: An XGBoost-Based Unbiased Transformed Algorithm for Survival Regression by Jingyi Zhang, Shishun Zhao, Yang Xu, Tao Hu

“…This study aims to develop a reliable and efficient prediction algorithm that utilizes unbiased transformation to improve machine learning model performance on interval-censored data. …”
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