Evaluation of the elastic modulus of pavement layers using different types of neural networks models by M. M.M. Elshamy, A. N. Tiraturyan, E. V. Uglova

“…This paper studies the capability of different types of artificial neural networks (ANN) to predict the modulus of elasticity of pavement layers for flexible asphalt pavement under operating conditions. …”
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Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition by Ahmad S. Lateef, Mohammed Y. Kamil

“…Result: The system demonstrated accuracy of up to 100%, with deep learning algorithms outperforming machine learning methods. Conclusion: These promising results suggest that face recognition technology can effectively streamline and automate attendance tracking, offering a viable solution for educational institutions seeking to improve operational efficiency and accuracy…”
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Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…We evaluated the efficiency and performance of the ML algorithms using a set of metrics to measure their ability to accurately predict the HFF slope within the data set. …”
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Pedotransfer functions for estimating the van Genuchten model parameters in the Cerrado biome by Mariana F. Veloso, Lineu N. Rodrigues, Elpídio I. Fernandes Filho, Carolina F. Veloso, Bruna N. Rezende

“…Multiple Linear Regression (MLR) and four machine learning (ML) algorithms were used to develop the PTFs. The ML algorithms were the Multivariate Adaptive Regression Splines (MARS), Random Forest (RF), Support Vector Regression (SVR), and K Nearest Neighbors (KNN). …”
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A Review of Numerical Techniques for Frictional Contact Analysis by Govind Vashishtha, Sumika Chauhan, Riya Singh, Manpreet Singh, Ghanshyam G. Tejani

“…These advancements will ultimately improve the predictive power of simulations in diverse fields.…”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…We explore how ML can optimize the geometric and structural design of WPT coils, predict the optimal parameters for inductive couplers, and enhance coupling efficiency under varying conditions. …”
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Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…However, advanced biostatistical analysis is required to properly combine microbiome taxonomic abundance data with phenotypical metadata and reliably predict disease states. While differential abundance analysis and machine-learning techniques are widely used to perform such analyses, selecting the best method is not trivial due to the complexity and specific characteristics of both the data and the algorithms. …”
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Mathematical Modelling and Optimisation of Operating Parameters for Enhanced Energy Generation in Gas Turbine Power Plant with Intercooler by Anthony O. Onokwai, Udochukwu B. Akuru, Dawood A. Desai

“…The study demonstrated the potential of extending metaheuristic algorithms to provide sustainable solutions to energy system problems and reduced emissions through gas turbine power plant (GTPP) optimisation.…”
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Two General Data Protection Regulation (GDPR) Compliant Approaches to Scoring Firm Financial Frailty in Business Litigation by A. E Rodriguez, Gazi Murat Duman, Ron Kuntze

“…We then map the scores onto bivariate classes using Fisher-Jenks clustering. Each algorithm’s accuracy is obtained by comparing its predictions of either failure of viability to those of the labeled data in O'Haver (1993). …”
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Sensor-Based Rock Hardness Characterization in a Gold Mine Using Hyperspectral Imaging and Portable X-Ray Fluorescence Technologies by Saleh Ghadernejad, Kamran Esmaeili, Mariano P. Consens

“…Three ML algorithms, including Random Forest Regressor (RFR), Adaptive Boosting (AdaBoost), and Multivariate Linear Regression (MLR), were applied to develop predictive hardness models considering three scenarios: using chemical features, using refined spectral features, and their combination. …”
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Web Application for Mathematical Modeling of Unsteady Oil Flow in Porous Medium by A. A. Mazitov

“…The analysis and interpretation of hydrodynamic research data are based on theoretical models and computational algorithms. Despite the demand for this topic, numerous issues related to unsteady fluid flows in oil reservoirs still require solutions. …”
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Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…However, the performance of previous automated approaches has often been hindered by suboptimal feature selection and algorithms’ “black-box” nature, which adversely affect their interpretability and clinical applicability. …”
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Tuning of PID Controller for Speed Control of DC-Motor by using Generalized Regression Neural Network and Invasive Weed Optimization by Muhammad Hilal, Haider TH. Salim ALRikabi, Ibtisam A. Aljazaery

“…To optimize motor drive speed using GRNN and IWO algorithms, data on motor performance over time must be collected and used to train a GRNN model that can predict future motor performance based on past performance. …”
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Investigation of the impact of service parameters on the degree of passenger satisfaction based on the application of the apparatus of neural networks by S. S. Pastukhov, K. V. Stel’Mashenko

“…The approbation results of the apparatus of neural networks on sets of marketing data concerning various aspects of passenger service at stations and in trains are presented, as well as an estimation of the efficiency of using neural networks in comparison with the algorithms of ordinal logistic and linear regression. …”
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Teaching a neural network modeling socio-economic development of the region by S. V. Romanchukov, O. G. Berestneva, L. A. Petrova

“…Under these conditions, the expansion of the mathematical apparatus and the more active introduction of information technologies (including in the area of Big Data analysis and the construction of predictive models based on artificial neural networks) can be viable. …”
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Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

“…This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. …”
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Achieving precision assessment of functional clinical scores for upper extremity using IMU-Based wearable devices and deep learning methods by Weinan Zhou, Diyang Fu, Zhiyu Duan, Jiping Wang, Linfu Zhou, Liquan Guo

“…Simultaneously, on the basis of the internal correlation between the Fugl–Meyer assessment and the Brunnstrom scale, Brunnstrom stage prediction models of the arm and hand were established via the random forest and extremely randomized trees algorithm. …”
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Quantum Vulnerability Analysis to Guide Robust Quantum Computing System Design by Fang Qi, Kaitlin N. Smith, Travis LeCompte, Nian-feng Tzeng, Xu Yuan, Frederic T. Chong, Lu Peng

“…The QVA determines the cumulative quantum vulnerability (CQV) of the target quantum computation, which quantifies the quantum error impact based on the entire algorithm applied to the target quantum machine. By evaluating the CQV with well-known benchmarks on three 27-qubit quantum computers, the CQV success estimation outperforms the estimated probability of success state-of-the-art prediction technique by achieving on average six times less relative prediction error, with best cases at 30 times, for benchmarks with a real SR rate above 0.1%. …”
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Advancing the deployment and information management of direct air capture: A solution enabled by integrating consortium blockchain system by Zihan Chen, Yiyu Liu, Eryu Wang, Huajie You, Qi Gao, Fan David Yeung, Jia Li

“…(Source: Investopedia) ECDSA encryption,22 Elliptic Curve Digital Signature Algorithm (ECDSA): In cryptography, the Elliptic Curve Digital Signature Algorithm (ECDSA) offers a variant of the Digital Signature Algorithm (DSA) which uses elliptic-curve cryptography. …”
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Enhancing placental pathology detection with GAMatrix-YOLOv8 model by Weirui Wu, Zhifa Jiang, Jingwen Liu, Jiahui Ji, Xiaoyan Wei, Xiangyun Ye, Zhen Zhang

“…Conclusions: GAMatrix-YOLOv8 achieves unprecedented prediction accuracy in detecting delayed villous maturation in placental pathological tissues through algorithmic innovation. …”
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