Comprehensive assessment on estimating the thermodynamic and mechanical properties of multicomponent Fe–Cr-based alloys using machine learning techniques by Ahed Habib, Bashar Alibrahim, Mahdi Z. Alnunu, Hussein Moussa, Maan Habib

“…This study investigates the performance of 11 different machine learning algorithms to predict the mixing enthalpy, Young’s modulus, and the shear-to-bulk modulus ratio of Fe–Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. …”
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A model for classifying information objects using neural networks and fuzzy logic by Vadym Mukhin, Valerii Zavgorodnii, Viacheslav Liskin, Sergiy Syrota, Aleksandra Czupryna-Nowak, Bohdan Rusyn, Arkadiusz Banasik, Jacek Woloszyn, Wojciech Kempa

“…Improve the efficiency of classification algorithms by fine-tuning neural network parameters and fuzzy logic rules, ensuring high accuracy and computational efficiency when processing large-scale educational datasets. …”
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Cognitive Apprenticeship Strategies for the Media Literacy Classroom by Nate Floyd, Jaclyn Spraetz

“…., misinformation, climate change, algorithms, right-to-repair, blockchain, artificial intelligence, etc.), and create engagement-driven course content. …”
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Ensemble machine learning model for forecasting wind farm generation by A. G. Rusina, Osgonbaatar Tuvshin, P. V. Matrenin, N. N. Sergeev

“…This study is carried out by ensemble algorithms, such as Random Forest, AdaBoost and XGBoost, which are one of the machine learning approaches. …”
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Urban sentinel: advancing structural health monitoring for building damage measurement in districts through IoT integration and self-optimizing machine learning by Parsa Parsafar

“…These sensors transmit data using LoRaWAN wireless technology to a centralized management system, where a regression AI model harnesses the power of machine learning algorithms to analyze the data and predict the health status of the buildings. …”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…Multiple machine learning algorithms were used to generate the LUSC classification. …”
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Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis by Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos, Elpiniki Papageorgiou

“…These results highlight a potential synergistic relationship between human expertise and advanced algorithmic predictions, suggesting a hybrid approach as a promising direction for enhancing CAD diagnostics.…”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…Deep learning techniques, including hybrid and ensemble methods, were developed to predict these properties with high accuracy. This paper focuses on forecasting models using T-SFIS, GBMBoost, and Decision Tree, combined with metaheuristic algorithms (GWO, QPSO) in hybrid and ensemble frameworks. …”
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Dataset on the long-term monitoring of foundation vertical deformations on medium-expansive soilMendeley Data by Hawkar Hashim Ibrahim, Rizgar Ali Hummadi

“…It is particularly useful in developing machine learning algorithms that can be used to predict foundation behavior in response to different environmental conditions, optimize foundation designs on expansive soils, and specifically predict foundation heave. …”
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Genetic analysis of a serologically weak D phenotype caused by the p. R191G variant of the RHAG gene by ZHANG Xu, LI Xiaofeng, LI Jianping

“…R191Q) mutation was predicted to be “probably damaging”, “deleterious” and “affected” by PolyPhen2, PROVEAN and Mutation Taster algorithms, respectively. …”
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Application of machine learning in forensic geochemistry using presalt oil samples from the Santos basin by Gil Marcio Avelino Silva, Fernando Pellon de Miranda, Jarbas Vicente Poley Guzzo, Wagner Leonel Bastos, Ygor Rocha, Igor Viegas Alves Fernandes de Souza, Italo Oliveira Matias, Sarah Barron Torres, Francisco Fabio de Araujo Ponte

“…A dataset comprising 2200 presalt oil samples and 75 attributes from the Santos Basin underwent preprocessing and exploratory analysis, resulting in 2137 samples and 62 predictive attributes. Seven machine learning algorithms were evaluated, with the random forest model achieving the highest classification accuracy of 91%. …”
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The influence of pH and temperature on benthic chlorophyll-a: Insights from SHAP-XGBoost and random forest models by Sangar Khan, Noël P.D. Juvigny-Khenafou, Tatenda Dalu, Paul J. Milham, Yasir Hamid, Kamel Mohamed Eltohamy, Habib Ullah, Bahman Jabbarian Amiri, Hao Chen, Naicheng Wu

“…There is little information on machine learning predictive models of benthic chl–a and input parameters in lotic ecosystems, and to fill this gap, we predict benthic chl–a levels in China's Thousand Islands Lake (TIL) watershed using machine learning algorithms. …”
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Determination of Colles fracture risk index by X-ray images with the computer vision application by Wisam A. Hussein, Hussain J. AlKhatteib, Jawad K. Abbas

“…Background. Modelling a predictive risk index for Colles fractures using X-ray image analysis is a crucial application in orthopaedics since these fractures have essential health and economic burdens, particularly among the elderly. …”
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Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

“…The integration of machine learning techniques, particularly the Random Survival Forest (RSF) model, offers potential enhancements to predictive modeling and decision-making. This study aims to provide an introduction to the application of the RSF model in survival analysis in kidney transplantation alongside a practical guide to develop and evaluate predictive algorithms. …”
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Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study by Erkan Boğa

“…Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of leukocytosis in predicting surgical needs were calculated. …”
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PRINCIPLES OF PHASE-LOCKED LOOPS MATHEMATICAL MODELS CONSTRUCTION by M. P. Batura, A. P. Kuznetsov, L. Yu. Shilin, D. P. Kukin

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Generation and processing of chaotic signals BASED ON simple functions in three dimensional space by V. A. Cherdyntsev, S. I. Polovenya, V. V. Dubrovsky

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On constraint qualifications in mathematical programming by L. I. Minchenko, S. I. Sirotko

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Classical special functions of matrix arguments by Dmytro Shutiak, Gleb Podkolzin, Victor Bondarenko, Yury Chapovsky

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Are minimum indoor air quality requirements combined with passive retrofit solutions enough to guarantee thermal comfort in southern Spain High Schools? by Calama-González Carmen María, Escandón Rocío, Suárez Rafael

“…A representative educational building is selected as case study to simulate the performance of the existing high school stock in southern Spain. …”
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