ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani

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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…This approach is considered a hybrid of optimization algorithms and classifiers in machine learning. Binary Whale Optimization (BWO) and Binary Grey Wolf Optimization (BGWO) algorithms are used for feature selection and K-Nearest Neighbor (KNN) and Fuzzy K-Nearest Neighbor (FKNN) algorithms are applied as the classifiers in this research. …”
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PredβTM: A Novel β-Transmembrane Region Prediction Algorithm. by Amrita Roy Choudhury, Marjana Novič

“…Here, we describe PredβTM, a transmembrane region prediction algorithm for β-barrel proteins. Using amino acid pair frequency information in known β-transmembrane protein sequences, we have trained a support vector machine classifier to predict β-transmembrane segments. …”
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A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine by Yanping Cai, Guanghua Xu, Aihua Li, Xu Wang

“…To effectively make use of the component spatial information in time-frequency images, local binary pattern (LBP) algorithm is applied. Also, in view of the problems that traditional LBP coding is easily interfered by singular pixel points and the relative spatial information is not prominent, an improved coding rule of the LBP operator is put forward in this paper. …”
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Stock Index Prices Prediction via Temporal Pattern Attention and Long-Short-Term Memory by Xiaolu Wei, Binbin Lei, Hongbing Ouyang, Qiufeng Wu

“…The study’s motivation is based on the notion that datasets of stock index prices involve weak periodic patterns, long-term and short-term information, for which traditional approaches and current neural networks such as Autoregressive models and Support Vector Machine (SVM) may fail. …”
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Adaptive algorithm for reducing pulse noise level in images from CCTV cameras by Andrey Sadchenko, Oleg Kushnirenko, Alexander Troyanskiy, Yurii Savchuk

“…The proposed algorithm can be used for pre-preprocessing images intended for recognition by machine vision systems, scanning text, and improving subjective image characteristics, such as sharpness and contrast.…”
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Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns by Hua‐jing Yuan, Hui Yu, Yi‐ding Yu, Xiu‐juan Liu, Wen‐wen Liu, Yi‐tao Xue, Yan Li

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Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. …”
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Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection by Rani Kurnia Putri, Muhammad Athoillah*

“…Both algorithms have proven to be powerful tools for any classification problem specially to classify or identify image patterns. …”
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Integration of Deep Learning and Machine Learning Techniques for Advancing the Detection of Plant Diseases by Abdul Karim, Touqeer Ahmed Jumani, Muhammad Amir Raza, Shadi Khan Baloch, Nouman Qadeer Soomro, Muhammad Masud, Muhammad Salman Saeed, Mouaaz Nahas, Aamir Ali Patoli

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Sonographic machine-assisted recognition and tracking of B-lines in dogs: the SMARTDOG study by Aurélie Jourdan, Aurélie Jourdan, Caroline Dania, Caroline Dania, Maxime Cambournac, Maxime Cambournac

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Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

“…Structural health monitoring (SHM) systems used sensors to detect damage indicators such as vibrations and cracks, which were crucial for predicting service life and planning maintenance. Machine learning (ML) enhanced SHM by analyzing sensor data to identify damage patterns often missed by human analysts. …”
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Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning by Chengping Chai, Omar Marcillo, Monica Maceira, Junghyun Park, Stephen Arrowsmith, James O. Thomas, Joshua Cunningham

“…Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. …”
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Exoskeleton-guided passive movement elicits standardized EEG patterns for generalizable BCIs in stroke rehabilitation by Xinyi Zhang, Lanfang Xie, Wanting Liu, Shaoying Liang, Liyao Huang, Mingjun Wang, Lingling Tian, Li Zhang, Zhen Liang, Hai Li, Gan Huang

“…Time and time-frequency domain analyses were performed to examine the event-related potential (ERP), event-related desynchronization (ERD), and synchronization (ERS) patterns. The performance of two BCI algorithms, Common Spatial Patterns (CSP) and EEGNet, was evaluated in both within-subject and cross-subject decoding tasks. …”
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A Multi-Area Software-Defined Vehicular Network Control Plane Deployment Mechanism Oriented to Traffic Prediction by Hao Li, Hongming Li, Yuqing Ji, Ziwei Wang

“…A comprehensive comparison of various machine learning and deep learning algorithms is then conducted to evaluate their efficacy in forecasting SDVN traffic patterns, which is crucial for system efficiency. …”
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Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques by Mohamed Ali Kazi

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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

“…A speech corpus containing samples from advanced, intermediate, and elementary learners (N = 50) and standard speakers (N = 10) was constructed, with a total of 5880 samples. Support Vector Machine (SVM) and ID3 decision tree algorithms were employed to classify vowel formant parameters (F1-F2) patterns. …”
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The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data by Sudarmaji Saroji*, Ekrar Winata, Putra Pratama Wahyu Hidayat, Suryo Prakoso, Firman Herdiansyah

“…The support vector machine (SVM) algorithm has been applied successfully to the Damar field, Indonesia. …”
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Time Evolution of Bacterial Resistance Observed with Principal Component Analysis by Claudia P. Barrera Patiño, Mitchell Bonner, Andrew Ramos Borsatto, Jennifer M. Soares, Kate C. Blanco, Vanderlei S. Bagnato

“…<b>Results</b>: The processing and data analysis with machine learning algorithms performed on this FTIR spectral database allowed for the identification of patterns across minimum inhibitory concentration (MIC) values associated with different exposure times and both clusters from hierarchical classification and PCA. …”
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Machine learning approach for Studying the multifunctionality of soil against global climate changes by Xiangng Hu, Yingying Xie, Qixing Zhou, Li Mu

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