Inverse Identification of Constituent Elastic Parameters of Ceramic Matrix Composites Based on Macro–Micro Combined Finite Element Model by Sheng Huang, Le Rong, Zhuoqun Jiang, Yuriy V. Tokovyy

“…The inversion process of the constituent elastic parameters was established using the trust-region algorithm combined with an improved error function. …”
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Enhancement of joint quality for laser welded dissimilar material cell-to-busbar joints using meta model-based multi-objective optimization by Andreas Andersson Lassila, Tobias Andersson, Rohollah Ghasemi, Dan Lönn

“…In an meta model-based multi-objective optimization approach, the non-dominated sorting genetic algorithm II (NSGA-II) is used to efficiently search for trade-off solutions and the meta models are used for objective approximation. …”
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A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…Abstract Reservoir oil-bearing recognition is the process of predicting reservoir types based on well logging data, which determines the accuracy of recognition. …”
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Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter by Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman

“…Background: Understanding the dynamics of infectious disease spread and predicting clinical outcomes are critical for managing large-scale epidemics and pandemics, such as COVID-19. …”
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Identification of Road Black Spots Based on the Sliding Window Optimization and Safety Performance Function Development by Shahin Shabani, Jalal Ayoubinejad, Nassir Baradaran Rahmanian

“…The optimization methodology employed in this study is as follows: Firstly, the road is segmented, and for each segment, different scenarios of window lengths are chosen using the Density-Based Spatial Clustering of Applications with Noise algorithm. Next, a Safety Performance Function is developed to calculate the predicted and expected number of crashes, as well as the Potential Safety Improvement, for each window movement across all selected scenarios within the segment. …”
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NMPC-Based 3D Path Tracking of a Bioinspired Foot-Wing Amphibious Robot by Heqiang Cao, Hailong Wang, Zhiqiang Hu

“…To this end, a nonlinear model predictive control (NMPC) algorithm is employed to compute optimal control inputs, as it effectively addresses the challenges of strong nonlinearity, coupling effects, and multi-objective optimization. …”
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Trajectory-Based Optimal Area Forwarding for Infrastructure-to-Vehicle Data Delivery with Partial Deployment of Stationary Nodes by Liang-Yin Chen, Song-Tao Fu, Jing-Yu Zhang, Xun Zou, Yan Liu, Feng Yin

“…This paper proposes a trajectory-based optimal area forwarding (TOAF) algorithm tailored for multihop data delivery from infrastructure nodes (e.g., Internet access points) to moving vehicles (infrastructure-to-vehicle) in vehicular ad hoc networks (VANETs) with partial deployment of stationary nodes. …”
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Integrated Technologies for Smart Building Energy Systems Refurbishment: A Case Study in Italy by Lorenzo Villani, Martina Casciola, Davide Astiaso Garcia

“…This model enabled energy simulations using the Carrier–Pizzetti method and supported the design of a hybrid HVAC system—integrating VRF and hydronic circuits—further enhanced by a custom ML algorithm for adaptive, predictive energy management through BIM and IoT data fusion. …”
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In silico exploration of novel EGFR-targeting compounds: integrative molecular modeling, docking, pharmacokinetics, and MD simulations for advancing anti-cervical cancer therapeuti... by Auwal Salisu Isa, Adamu Uzairu, Umar Meleh Umar, Muhammad Tukur Ibrahim, Abdullahi Bello Umar, Kamal Tabti, Abdussamad Mukhtar Mohammed

“…This study investigates the potential of 2,4-diphenyl indenol [1,2-b] pyridinol derivatives as inhibitors targeting the epidermal growth factor receptor (EGFR) through computational drug discovery methods. A genetic algorithm-multiple linear regression (GA-MLR) model was created, achieving strong predictive accuracy with R² = 0.9243, Q² = 0.8957, CCC = 0.9021, and MAE = 0.034. …”
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U-net based approach for pectoralis muscle segmentation in digital mammography by Francesca Angelone, Alfonso Maria Ponsiglione, Roberto Grassi, Francesco Amato, Mario Sansone

“…This study aims to propose an automatic breast segmentation algorithm that combines traditional methods with Deep Learning methods limited only to the border region between the muscle and the breast. …”
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Driving Factors and Future Trends of Wildfires in Alberta, Canada by Maowei Bai, Qichao Yao, Zhou Wang, Di Wang, Hao Zhang, Keyan Fang, Futao Guo

“…This study analyzed the relationship between climate and wildfire and used a random forest algorithm to predict future wildfire frequencies in Alberta, Canada. …”
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Exploring the Potential Imaging Biomarkers for Parkinson’s Disease Using Machine Learning Approach by Illia Mushta, Sulev Koks, Anton Popov, Oleksandr Lysenko

“…To ensure interpretability, we applied the local interpretable model-agnostic explainer (LIME), identifying contralateral putamen SBR as the most predictive feature for distinguishing PD from healthy controls. …”
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Outdoor Dataset for Flying a UAV at an Appropriate Altitude by Theyab Alotaibi, Kamal Jambi, Maher Khemakhem, Fathy Eassa, Farid Bourennani

“…Therefore, this study presents an image dataset for training drones for 3D navigation. We developed an algorithm to capture these data from multiple worlds on the Gazebo simulator using a quadcopter. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…Deep learning-based models assist radiologists by detecting patterns, generating probability maps, and predicting outcomes like heart failure. However, AI is still supplementary to clinical expertise due to challenges such as data limitations, algorithmic biases, and the need for extensive validation. …”
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Artificial intelligence-assisted nursing interventions in psychiatry for oral cancer patients: A concise narrative review by Abdulmalik Fareeq Saber, Sirwan Khalid Ahmed, Safin Hussein, Karzan Qurbani

“…Challenges and ethical considerations in integrating AI into healthcare include data privacy, algorithm validation, and the need for professional training.…”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

“…An empirical investigation using real driving trajectory data from Kunming, China, confirms the ability of our approach to predict potential driving decisions with high accuracy while providing the rationale implicit AV decisions. …”
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Experimental study on mechanical properties of triaxial geogrid reinforced marine coral sand-clay mixture based on 3D printing technology by Danda Shi, Kaiwei Xu, Zhiming Chao, Zhiming Chao, Peng Cui, Peng Cui

“…Based on the experimental results, a dataset was established, while a novel machine learning model named GP-BPNN was proposed, integrating genetic algorithm (GA), particle swarm optimization (PSO), and backpropagation neural network (BPNN). …”
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Development of an MRI based artificial intelligence model for the identification of underlying atrial fibrillation after ischemic stroke: a multicenter proof-of-concept analysisRes... by Zijie Zhang, Yang Ding, Kaibin Lin, Wenli Ban, Luyue Ding, Yudong Sun, Chuanliang Fu, Yihang Ren, Can Han, Xue Zhang, Xiaoer Wei, Shundong Hu, Yuwu Zhao, Li Cao, Jun Wang, Saman Nazarian, Ying Cao, Lan Zheng, Min Zhang, Jianliang Fu, Jingbo Li, Xiang Han, Dahong Qian, Dong Huang

“…Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were calculated for model evaluation. …”
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Dual Control of the Extremal Multidimensional Regression Object by V. S. Mukha, N. F. Kako

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Optimal Histogram Filter by A. V. Ausiannikau, V. M. Kozel

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