Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of the validation techniques (covariate shift). While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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Emergent behaviors in multiagent pursuit evasion games within a bounded 2D grid world by Sihan Xu, Zhaohui Dang

“…These findings provide significant insights into the mechanisms of behavioral emergence and the optimization of cooperative strategies in multi-agent games.…”
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Efficient topology control for time-varying spacecraft networks with unreliable links by Wei Zhang, Hong Ma, Tao Wu, Xueshu Shi, Yiwen Jiao

“…We prove that such an optimization problem is NP-hard. Then, we provide five heuristic algorithms, which can significantly maintain low topology cost efficiency ratio while achieving high reliable connectivity. …”
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Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method by Jingdan Liu, Xujie Bao, Liji Chen

“…Abstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learning through voice assistants and essay evaluation. …”
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Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Abstract As the global population is expected to reach 10.3 billion by the mid-2080s, optimizing agricultural production and resource management is crucial. …”
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Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation by Marco Negozio, Lorenzo Donati, Adrian H. A. Lutey

“…Abstract Optimization of the mechanical and crash properties of extruded AA6XXX automotive profiles requires detailed understanding of grain size evolution and formation of the peripheral coarse grain (PCG) defect. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. Regression models predicted vault height as a continuous variable, while classification models categorized vault heights into binary and multi-class tasks. …”
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AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…Our performance evaluation across various configurations highlights performance–resource trade-offs and demonstrates that ANN and BPNN achieve significant parallelism, while AES optimization increases resource utilization the most. …”
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Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review by Hesameddin Akbarein, Mohammad Hussein Taaghi, Mahyar Mohebbi, Parham Soufizadeh

“…Consequently, healthcare systems stand to gain notable advantages, such as enhanced accessibility, treatment efficacy, and optimized resource allocation, owing to the seamless integration of AI. …”
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Design Methodology and Performance Evaluation of New Generation Sounding Rockets by Marco Pallone, Mauro Pontani, Paolo Teofilatto, Angelo Minotti

“…A general configuration composed of a rocket with four canards and four tail wings is sized and optimized, assuming different payload masses and microgravity durations. …”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making by Lei Li, Li Li, Mantian Li, Ke Liang

“…In summary, AI contributes to robotics through design optimization, environmental perception, and intelligent decision-making. …”
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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…Abstract Background Hands-and-knees crawling is a promising rehabilitation intervention for infants with motor impairments, while research on assistive crawling devices for rehabilitation training was still in its early stages. …”
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Modern fixation techniques versus traditional tension band wiring for olecranon fractures: a systematic review and meta-analysis of functional outcomes, healing time, and complicat... by Chengjing Wang, Changqing Li

“…Cable-pin System appears optimal for simple fractures, while Eyelet K-wire System shows advantages for comminuted fractures. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…Finally, the introduction of the Wise-ShapeIoU loss function further accelerates the model’s convergence and optimization process. Experimental results demonstrate that, compared to the original model, the number of parameters and FLOPs are reduced by 36.7% and 28.4%, respectively, while the Precision is increased by 5.1%. …”
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Prediction and Screening of Lead-Free Double Perovskite Photovoltaic Materials Based on Machine Learning by Juan Wang, Yizhe Wang, Xiaoqin Liu, Xinzhong Wang

“…The SHAP (Shapley Additive Explanations) analysis revealed that the X-site electron affinity positively influences the bandgap, while the B″-site first and third ionization energies exhibit strong negative effects. …”
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Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes by Shoupeng Ding, Chunxiao Huang, Jinghua Gao, Chun Bi, Yuyang Zhou, Zihan Cai

“…The developed diagnostic model and molecular subtyping strategy enable precise TB–LTBI differentiation and inform immunotherapy optimization.…”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…While the framework incorporates established components, its core contributions lie in the optimized skip connection strategy and supporting techniques like RSS and DWD. …”
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Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

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Using machine learning to predict anesthetic dose in fish: a case study using nutmeg oil by Mert Minaz, Cem Alparslan, Akif Er

“…Each model was trained using different activation functions (purelin, tansig, logsig) and optimization algorithms (traingda, trainrp, trains), and the optimal network architecture was selected based on prediction performance for each output variable. …”
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