Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Experimental results demonstrate a substantial reduction in electricity costs for consumers by an average of 25% and a decrease in carbon dioxide (CO2) emissions by 40 tons annually. …”
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Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks by Hanjin Kim, Young-Jin Kim, Won-Tae Kim

“…The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. …”
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Machine learning assisted estimation of total solids content of drilling fluids by B.T. Gunel, Y.D. Pak, A.Ö. Herekeli, S. Gül, B. Kulga, E. Artun

“…In the final stage, different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models. Among all algorithms tested, random forests algorithm was found to be the best predictive model resulting in consistently high accuracy. …”
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Creation of a collection of different biological sample types from elderly patients to study the relationship of clinical, systemic, tissue and cellular biomarkers of accumulation... by A. G. Sorokina, Ya. A. Orlova, O. A. Grigorieva, E. S. Novoseletskaya, N. A. Basalova, N. A. Alexandrushkina, M. A. Vigovsky, K. I. Kirillova, A. V. Balatsky, L. M. Samokhodskaya, N. V. Danilova, U. D. Dyachkova, D. А. Fedotov, A. A. Akopyan, V. V. Kakotkin, D. A. Asratyan, Zh. A. Akopyan, A. Yu. Efimenko

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An introduction to causal discovery by Martin Huber

“…This survey provides an introduction to key concepts, algorithms, and applications of causal discovery from the perspectives of economics and social sciences. …”
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Region-wise landmarks-based feature extraction employing SIFT, SURF, and ORB feature descriptors to recognize Monozygotic twins from 2D/3D Facial Images [version 2; peer review: 2... by Srikanth Prabhu, Vinod Nayak, Aparna Jayakala, Krishna Prakasha K, Gangothri Sanil

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Parallel Implicit Runge-Kutta Methods for Stiff ODEs by Bashir Khalaf, Abdulhabib Murshid

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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…The thematic analysis revealed five major categories: 1. Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…The STL, the turbulent self-noise reduction or a weighting function of the STL and turbulent self-noise reduction of FGM acoustic windows is chosen as the optimization objective. …”
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Identification and validation of parthanatos-related genes in end-stage renal disease by Xuan Dai, Lianfang Yuan

“…Two machine learning algorithms identified candidate genes, refined through ROC analysis. …”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…For estimating SoH, prevalent data-driven techniques include support vector regression (SVR) and Gaussian process regression (GPR), alongside hybrid models merging machine learning with conventional estimation techniques to heighten predictive accuracy. RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). …”
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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Results demonstrate strong predictive performance for both CNN-TLBO and CNN-SPBO, with area under the curve values of 0.926 and 0.920, respectively. …”
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Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints by Xiumin Liu, Xinyue Zhang, Ye Sheng, Zihe Zhang, Pan Xiong, Xuehai Ju, Junwu Zhu, Caichao Ye

“…The random forest (RF) algorithm exhibited the best predictive performance for material design and screening. …”
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A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

“…These algorithms were tested on a diabetes risk dataset divided into training, validation, and testing subsets. …”
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Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling by Pimolkan Piankitrungreang, Kantawatchr Chaiprabha, Worathris Chungsangsatiporn, Chanat Ratanasumawong, Peemdej Chancharoen, Ratchatin Chancharoen

“…By integrating big data concepts and intelligent algorithms, the system supports continuous monitoring, anomaly detection, and process optimization. …”
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Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities by Gift Echefu, Rushabh Shah, Zanele Sanchez, John Rickards, Sherry-Ann Brown

“…Additional application opportunities for AI in cardio-oncology involve multimodal cardiovascular imaging, where algorithms can also utilize imaging input to generate predictive risk profiles for cancer patients. …”
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Hyperspectral Reconstruction Method Based on Global Gradient Information and Local Low-Rank Priors by Chipeng Cao, Jie Li, Pan Wang, Weiqiang Jin, Runrun Zou, Chun Qi

“…It combines reconstruction algorithms to recover hyperspectral data from low-dimensional measurement images. …”
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Artificial intelligence - finite element method - hybrids for efficient nonlinear analysis of concrete structures by Michael A. Kraus, Rafael Bischof, Walter Kaufmann, Karel Thoma

“…We successfully calibrated and evaluated k-nearest-neighbour, LGBM and ResNet algorithms and report their predictive capabilities. …”
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Predictors of Acute Myocardial Infarction: A Machine Learning Analysis After a 7-Year Follow-Up by Marco Casciaro, Pierpaolo Di Micco, Alessandro Tonacci, Marco Vatrano, Vincenzo Russo, Carmine Siniscalchi, Sebastiano Gangemi, Egidio Imbalzano

“…We found that the potential of machine learning to predict life-threatening events is significant. <b>Conclusions:</b> Machine learning algorithms can be used to create models to identify patients at risk for acute myocardial infarction. …”
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Performance evaluation of geopolymer masonry units: A hybrid approach combining laboratory testing and AI modeling by Md. Zia Ul Haq, Sandeep Singh, Tarak Vora, A.K. Dasarathy, Kaushik Bharti, Vanitha S, Priyadarshi Das, Laura Ricciotti

“…The study also employs nine machine learning algorithms on a dataset comprising 612 prism and 63 wallette data points, assessing performance based on six predictive metrics. …”
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