Machine Learning Techniques for Classification of Stress Levels in Traffic by Amanda Trojan Fenerich, Egídio José Romanelli, Rodrigo Eduardo Catai, Maria Teresinha Arns Steiner

“… The aim of this study is to apply Machine Learning techniques for predicting and classifying the stress level of people commuting from home to work and also to evaluate the performance of prediction models using feature selection. …”
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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…The results indicate that Ensemble Learning and AdaBoost yield the highest accuracy algorithms in prediction capability as they tend to illustrate the lowest values of mean squared error and mean absolute relative error (%) and highest R-squared values. …”
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Evaluation of Mathematical Models for Teaching Precision in the Framework of Big Data by Ming Zhang

“…With the continuous development and application of data computing in the whole society in the construction of digital campus and intelligent campus of each higher education institution. In the environment of education, universities use these data well, which not only affects the orderly operation of higher education but also will become an inexhaustible power to help higher education promote the reform and innovation of education and teaching system. …”
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Hybrid energy system optimization integrated with battery storage in radial distribution networks considering reliability and a robust framework by Mohammad Javad Aliabadi, Masoud Radmehr

“…The robust optimization results show that in the 33-bus network, the system remains resilient to prediction errors under the worst-case uncertainty scenario, with a 44.53% reduction in production and a 22.18% increase in network demand for a 30% uncertainty budget. …”
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Promising Research Results and Development in the Field of Microwave Technology by A. V. Gusinsky

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Optimal channel multiplexing and maximal ratio combining: CINR comparison by V. P. Tuzlukov

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Sparse wavelet decomposition in problems of vibration-based diagnostics of rotary equipment by Y. P. Aslamov, A. P. Aslamov, I. G. Davydov, A. V. Borsuk

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IDENTIFICATION OF TRAJECTORY INFORMATION BY APPLYING FUZZY AUTOMATIC CLASSIFICATION IN THE INFORMATION ASSOCIATION PROBLEM by A. V. Khizhniak, A. A. Belous, A. S. Bely

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Comparison of tone mapping methods during images processing on liquid crystal displays by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

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Experimental and numerical investigations on the bidirectional thermal contact performance by Chen Wang, Mingjun Qiu, Huijing Liu, Jun Hong, Feiyu Gu, Lifei Chen, Tao Wang, Hao Guan, Qiyin Lin

“…Subsequently, bidirectional thermal contact performance consisting of TCR ratio and thermal rectification coefficient was analyzed under varying temperatures and pressures. Additionally, a prediction model for TCR was developed using the Levenberg-Marquardt (L-M) algorithm. …”
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Blood pressure abnormality detection and interpretation utilizing explainable artificial intelligence by Hedayetul Islam, Md. Sadiq Iqbal, Muhammad Minoar Hossain

“…We have used several ML algorithms (extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), decision tree (DT), and logistic regression (LR)) to predict blood pressure abnormality based on patient's data. …”
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Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens by Cheng Han, Shiying Lu, Pan Hu, Jiang Chang, Deying Zou, Feng Li, Yansong Li, Qiang Lu, Honglin Ren

“…Integrating these genes into an ML model based on the support vector machine (SVM) algorithm allows us to predict the zoonotic potential of various Brucella strains with high accuracy. …”
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Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation by Sheng Wang, Jincheng Liu, Xiaopan Song, Huajian Xu, Yang Gu, Junyu Fan, Bin Sun, Linwei Yu

“…The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. …”
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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

“…To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA). This modern framework employs weighted ensemble clustering and matched ensemble choice techniques, facilitating strong cluster formation and resulting in a substantial 98% development in community lifetime, an 80% enhancement in packet delivery ratio (PDR), and a 45% reduction in average power consumption while as compared to current protocols. …”
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An Approach Based on the Use of Commercial Codes and Engineering Judgement for the Battle of Water Demand Forecasting by Alfredo Iglesias-Rey, Carlos Alfonso López Hojas, F. Javier Martínez-Solano, Pedro L. Iglesias-Rey

“…Initial data filtering, input variable determination, and simultaneous application of RNN, LSTM, and GRU forecasting algorithms are conducted. Results are evaluated based on Battle of Water Demand Forecasting criteria, refining parameters iteratively for enhanced prediction accuracy. …”
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Heart failure and atrial fibrillation: updates and perspectives by V. N. Larina, I. K. Skiba, A. S. Skiba, V. G. Larin, E. A. Vartanyan

“…The article discusses modern approaches and features of management, as well as predicting the risk of complications in patients with cardiac arrhythmias, in particular, atrial fibrillation, and the potential of using conservative and interventional treatment methods for heart failure (HF), taking into account updates and achievements in clinical practice. …”
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An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children by Mengyu Duan, Zhimin Geng, Lichao Gao, Yonggen Zhao, Zheming Li, Lindong Chen, Pekka Kuosmanen, Guoqiang Qi, Fangqi Gong, Gang Yu

“…Furthermore, its interpretability enhances model transparency, facilitating clinicians’ understanding of prediction reliability.…”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…A numerical example is presented to illustrate, among other aspects, the substantial reduction in computational time achieved by the proposed algorithm, as well as its superior estimation accuracy compared to conventional quaternion processing methods.…”
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Exploring Gender Differences in Fatwa through Machine Learning by Emad Mohamed, Raheem Sarwar

“…Our methodology involves comprehensive experimental analysis, utilizing advanced Arabic text preprocessing alongside machine learning algorithms. We concentrate on two primary objectives: predicting the gender of the questioner and forecasting the popularity of answers. …”
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Idiopathic Intrahepatic Cholestasis as an Unusual Presentation of Hodgkin’s Disease by Hande Atalay, Banu Boyuk, Muhammet Ates, Aslan Celebi, Ismail Ekizoglu, Arzu A. Didik, Aysenur A. Igdem

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