Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem by Yi Chang, Ming Dong, Lihong Fan, Bochao Kang, Weikai Sun, Xiaofeng Li, Zhang Yang, Ming Ren

“…In cardiac potential reconstruction, long short-term memory network has significant advantages over other algorithms. Clinical trial number Not applicable.…”
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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…To address this challenge, our study presents the “Optimized Random Forest (Opt-Forest),” an innovative ensemble model that combines decision forest approaches with genetic algorithms (GAs) for enhanced intrusion detection. The genetic algorithms based decision forest construction offers notable benefits by traversing a wider exploration space and mitigating the risk of becoming stuck in local optima, resulting in the discovery of more accurate and compact decision trees. …”
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Automated Detection of Working Area of Peripheral Blood Smears Using Mathematical Morphology by Jesús Angulo, Georges Flandrin

“…Second, the number of connected components from the three kinds of particles is counted and the coefficient of spreading ρs and the coefficient of overlapping ρo are calculated. …”
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Processing Water‐Medium Spinal Endoscopic Images Based on Dual Transmittance by Ning Hu, Qing Zhang

“…Experiments comparing classical image enhancement algorithms demonstrate that the proposed algorithm could effectively improve the quality of spinal endoscopic images.…”
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ADAPTABLE DYNAMIC ROUTING SYSTEM IN URBAN TRANSPORT LOGISTICS PROBLEMS USING GIS DATA by Viktor DANCHUK, Oleksandr HUTAREVYCH

“…Route optimization is performed on a weighted bidirectional graph for an asymmetric dynamic traveling salesman problem using a modified ant colony optimization algorithm. The system allows automatically updating the weights of the graph depending on the current changes in the characteristics traffic in the URN sections, obtained from GIS data, and fixing the optimal configuration of a partially completed route before updating the graph. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The research utilizes stepwise linear regression (SLR), random forest (RF), gradient boosting (GB), extreme gradient boosting (XGB), and Gaussian process regression (GPR) algorithms, developed based on 357 experimental results sourced from recent studies. …”
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Multiobjective Optimal Control of Longitudinal Seismic Response of a Multitower Cable-Stayed Bridge by Geng Fangfang, Ding Youliang

“…The dynamic behavior of a multitower cable-stayed bridge with the application of partially longitudinal constraint system using viscous fluid dampers under real earthquake ground motions is presented. …”
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Model experimental study of filling property of ring-type geotextile tube by LAI Zhiqiang, XU Shuling, ZHAO Lianjun, Chen Lin, ZHANG Ming

“…The results were relatively accurate, with <italic>M</italic>_SE values of 5×10^-5, 3×10^-4, and2×10^-5, respectively.The counterclockwise filling mechanism operates as followsConclusionsUnder 12 different working conditions, when the tube bag is filled counterclockwise at a speed of 2.77 m/s, its average height after filling reaches its peak at 0.09 m, with a relatively uniform distribution of sediment particles inside the bag. Leveraging machine learning principles, the heights of the filled tube bags under three different filling methods—counterclockwise, radial, and vertical—were simulated and predicted using the random forest algorithm, based on experimentally measured heights. …”
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Icosahedral metallic nanoclusters: low-temperature structures or pre-melting ones? by I.V. Karakeyan, V.V. Puitov, I.V. Talyzin, V.M. Samsonov

“…The heating process was simulated in the NVT ensemble using the well-known open LAMMPS program, the Verlet velocity algorithm and the Nosé-Hoover thermostat. The interatomic interactions in metal nanoparticles were reproduced by employing the embedded atom method. …”
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An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors by Atcharawan Rattanasak, Talit Jumphoo, Wongsathon Pathonsuwan, Kasidit Kokkhunthod, Khwanjit Orkweha, Khomdet Phapatanaburi, Pattama Tongdee, Porntip Nimkuntod, Monthippa Uthansakul, Peerapong Uthansakul

“…This study evaluated ten signal extraction methods, six machine learning algorithms, and four feature selection techniques to enhance classification performance. …”
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Resonance Attenuation of Ultrasonic Waves in a High Viscosity Magnetic Liquid by Karolina CHARAZIAK, Marcin MARECKI, Tomasz HORNOWSKI, Arkadiusz JÓZEFCZAK, Andrzej SKUMIEL

“… Ultrasonic waves attenuation as a function of frequency in a magnetic fluid APG-832 containing magnetite particles dispersed in a synthetic hydrocarbon was investigated. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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A novel hexagonal PtPS monolayer for high anisotropic carrier mobility and potential for photocatalytic water splitting with pronounced optical absorption by Chunying Pu, Pan Zhang, Linxuan Chen, Xindong Pan, Dawei Zhou

“…Motivated by the attractive properties and potential applications of MPX materials, we identified a novel stable hexagonal structure of PtPS monolayer with the space group $$P\bar {3}m1$$ using particle swarm optimization algorithms in conjunction with first-principles calculations. …”
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Soot Mass Concentration Prediction at the GPF Inlet of GDI Engine Based on Machine Learning Methods by Zhiyuan Hu, Zeyu Liu, Jiayi Shen, Shimao Wang, Piqiang Tan

“…The results of the study can serve as a reference for the development of accurate prediction algorithms to estimate soot loads in GPFs, which in turn can provide some basis for the control of the particulate mass and particle number (PN) emitted from GDI engines.…”
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Modern strategies of alternative insulin delivery systems by І. О. Vlasenko, L. L. Davtian, V. V. Hladyshev

“…Innovations in alternative insulin delivery systems include algorithms for continuous glucose monitoring systems, glucose-sensitive polymer matrices and biological structures with insulin. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…Optimization is performed using Multi-Objective Particle Swarm Optimization (MOPSO), enabling efficient exploration of Pareto-optimal solutions that balance deformation and material usage. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…The proposed methodology combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for hybrid feature selection, ensuring the selection of the most relevant features for detecting FDIAs. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Drone Navigation and Target Interception Using Deep Reinforcement Learning: A Cascade Reward Approach by Ali A. Darwish, Arie Nakhmani

“…First, we tackle the challenge of partial observability when employing nonlinear function approximators for learning stochastic policies. …”
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