Fast evaluation on the fatigue level of copper contact wire based on laser induced breakdown spectroscopy and supervised machine learning for high speed railway by Wenfu Wei, Langyu Xia, Zefeng Yang, Huan Zhang, Like Pan, Jian Wu, Guangning Wu

“…Results have shown that the standard normal variable transform–principal component analysis–genetic algorithm improve support vector machine (SNV‐PCA‐GASVM) model have presented a most satisfactory performance than the others. …”
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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…This enables attackers to manipulate the output of the state estimation model according to their intentions, which represents an improvement over previous work. …”
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Minimising the impact of stable 208Pb on recovery of 212Pb from a generator by Rachel Roberts, Tim Carthy, Jennifer Young, Temi Awogboro, Howard Greenwood, Jane Sosabowski, Scott Heath, Francis Livens

“…This model was used to calculate the optimal elution times for each generator with respect to ESA and Am. …”
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Enhancing the reliability and accuracy of wireless sensor networks using a deep learning and blockchain approach with DV-HOP algorithm for DDoS mitigation and node localization by Bhupinder Kaur, Deepak Prashar, Leo Mrsic, Ahmad Almogren, Ateeq Ur Rehman, Ayman Altameem, Seada Hussen

“…The remedy to these challenges in this work is a solution based on deep learning integrated with a blockchain-aided distance-vector hop (DV-HOP) localization algorithm for reliable and secure node localization. …”
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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

“…Microarray data are high dimensional, which can degrade the performance of the ML-based models. For this, feature selection becomes essential.MethodsSwarm Optimization Algorithm (SSA), Improved Maximum Relevance and Minimum Redundancy (IMRMR), and Boruta form the basis of this work’s ML-based model BIMSSA. …”
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Toward AI-Driven Cough Sound Analysis for Respiratory Disease Diagnosis by Houda Benaliouche, Houda Hafi, Hakim Bendjenna, Zeyad Alshaikh

“…Our study involves the application of three distinct models: a Convolutional Neural Network (CNN) model, a CNN-Support Vector Machine (CNN-SVM) hybrid model, and a transfer learning-based model. …”
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Data-Driven Fault Detection and Diagnosis in Cooling Units Using Sensor-Based Machine Learning Classification by Amilcar Quispe-Astorga, Roger Jesus Coaquira-Castillo, L. Walter Utrilla Mego, Julio Cesar Herrera-Levano, Yesenia Concha-Ramos, Erwin J. Sacoto-Cabrera, Edison Moreno-Cardenas

“…The Support Vector Machine (SVM) model achieved 93%, Decision Tree (DT) 93%, Gradient Boosting (GB) 91%, K-Nearest Neighbors (KNN) 83%, and Naive Bayes (NB) 77%, while the Random Forest (RF) model stood out, having an accuracy of 96% in deferred tests and 95.28% in real-time. …”
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Characteristics and Associated Factors of Insomnia Among the General Population in the Post-Pandemic Era of COVID-19 in Zhejiang, China: A Cross-Sectional Study by Da M, Mou S, Hou G, Shen Z

“…Six machine learning models were employed to develop a predictive model for insomnia, namely logistic regression, random forest, neural network, support vector machine, CatBoost, and gradient boosting decision tree.Results: The study obtained 2769 and 1161 valid responses in T1 and T2, respectively. …”
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Adaptive neuro-fuzzy inference system for accurate power forecasting for on-grid photovoltaic systems: A case study in Sharjah, UAE by Tareq Salameh, Mena Maurice Farag, Abdul-Kadir Hamid, Mousa Hussein

“…The study compares the ANFIS model with other established machine learning models, including Linear Regression, Decision Tree, Support Vector Machine (SVM), and Random Forest. …”
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Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

“…Various ML models—including Lasso Regression, Gradient Boosting, Random Forest, Extreme Gradient Boosting, Support Vector Regression, and Adaptive Boosting were rigorously evaluated to determine their predictive capabilities. …”
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Machine learning-based risk of fall estimation using insole with force sensors while performing a sequence of activities in the TUG test by Clinton Enow Tabi, Johannes C. Ayena, Martin J.-D. Otis

“…For the sit-to-start of the walk sequence identification phase, the best accuracy was achieved using the support vector machine model.…”
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Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…A Support Vector Regression-based model was trained on CFD-generated data to guide design modifications and reduce reliance on trial-and-error experimentation. …”
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Thermodynamic Analysis of Catalytic Urea Steam Reforming for Decentralized Hydrogen Production by Leticia M. S. Barros, Bruna G. Floriam, Jean Felipe Leal Silva, Verena S. Bombonatti, Aulus R. R. Bineli, Chayene G. Anchieta, Rubens Maciel Filho

“…Bearing this in mind, this work investigated urea steam reforming through a simulation study, using Aspen Plus software. …”
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Design and Analysis of a Flexible, Elastic, and Rope-Driven Parallel Mechanism for Wrist Rehabilitation by Zaixiang Pang, Tongyu Wang, Junzhi Yu, Shuai Liu, Xiyu Zhang, Dawei Jiang

“…To address this problem, the external force acting on the moving platform is firstly equivalent to the vector force and torque at the center of the moving platform. …”
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

“…Convolutional neural network based pretrained deep learning models can be used successfully to detect lung cancer. …”
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AdaGram in Python: An AI Framework for Multi-Sense Embedding in Text and Scientific Formulas by Arun Josephraj Arokiaraj, Samah Ibrahim, André Then, Bashar Ibrahim, Stephan Peter

“…The Adaptive Skip-gram (AdaGram) algorithm extends traditional word embeddings by learning multiple vector representations per word, enabling the capture of contextual meanings and polysemy. …”
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LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification by Nimisha Ghosh, Sankar Kumar Mridha, Rourab Paul

“…To identify such biomarkers, initially LASSO in association with four machine learning models such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Naive Bayes (NB) are applied on the dataset to find the initial reduced set of genes as well as the best learning model based on classification accuracy; SVM in this case. …”
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Learning from low precision samples by Ji In Choi, Madeleine Georges, Jung Ah Shin, Olivia Wang, Tiffany Zhu, Tapan Shah

“…The key contributions of the paper are as follows: • For 3 standard machine learning models, Support Vector Machines, Decision Trees and Linear (Logistic) Regression, we compare the performance loss for a standard static quantization and stochastic quantization for 55 classification and 30 regression datasets with 1-8 bits quantization…”
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Vocational guidance and career development in cultural institutions of the secondary vocational education in china by Sergey Sergeevich Zengin

“…At present, vocational guidance and career development are the most important aspects of training qualified personnel ready to work in modern conditions. In this regard, the issue of studying the best world practices becomes relevant. …”
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Artificial Sensing: AI-Driven Electronic Nose for Real-Time Gas Leak Detection and Food Spoilage Monitoring by Lubna Aziz, Hassan Adil, Raheel Sarwar

“…Additionally, the system provides continuous real-time freshness tracking, ensuring reliable food monitoring. Future work will focus on enhancing sensor diversity, improving model generalization, and extending applications to industrial safety, environmental monitoring, and smart home automation. …”
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