AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…Concurrently, the DQN optimizes design parameters through scaling and rotation operations, enhancing structural performance based on predicted stress metrics. Our approach resulted in a 4.3% improvement in average stress uniformity and a 23.1% reduction in maximum stress concentration. …”
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Efficient Data Collection Method in Sensor Networks by Keyan Cao, Haoli Liu, Yefan Liu, Gongjie Meng, Si Ji, Gui Li

“…An efficient data collection algorithm based on the position prediction of extreme learning machines is proposed. …”
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Simulating high-speed solar wind streams from coronal holes using an L5-L1 configuration of Lagrangian points by Tatiana Podladchikova, Astrid M. Veronig, Manuela Temmer, Stefan J. Hofmeister

“…We use these insights to develop a predictive algorithm for HSSs, beginning with an analysis of the separation angle and distances between L5 and L1. …”
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Bridging Behavioral Insights and Automated Trading: An Internet of Behaviors Approach for Enhanced Financial Decision-Making by Imane Moustati, Noreddine Gherabi

“…Effective investment decision-making in today’s volatile financial market demands the integration of advanced predictive analytics, alternative data sources, and behavioral insights. …”
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Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

“…The optimized mND705 was selected as the most critical spectral indices for PNC prediction. Incorporating RGB-based texture features and MS-based spectral indices into the VHGPR model achieved the highest prediction accuracy (RMSE = 0.29%). …”
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Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study by Zhong-Kai Ni, Tian-Han Zhou, Shu-Chao Kang, Ye-Hong Han, Hai-Min Jin, Shi-Fei Huang, Hai Huang

“…A predictive model for internal abdominal hernias was constructed based on a machine learning algorithm incorporating 7 different features. …”
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Collaborative governance model for spoil disposal and gully infill land creation near open-pit coal mines by Shaogang LEI, Jianying ZHANG, Chang LIU, Liang WANG, Zhenwang JIA

“…The results show that the total area of natural gullies around the open-pit mine treated by this model is 2.588 × 105 m2, reducing the amount of earthwork discharge in the mining area by about 1.536 × 107 m3; By combining the CLiDE geomorphic evolution and soil erosion assessment model, we simulated and evaluated a 66.53% reduction in regional soil erosion after collaborative treatment of surrounding gullies over a 30-year period. …”
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Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

“…Time series and state estimation are the Supervised Learning techniques executed for charge diagnostics and State of Charge (SOC) predictions. The results show remarkable performance metrics of the Transformer models, achieving over 94% accuracy in Model evaluation compared to traditional Deep Learning algorithms.…”
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Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed‐Cohort Study Based on 16,189 Participants by Cong Lai, Zhensheng Hu, Jintao Hu, Zhuohang Li, Lin Li, Mimi Liu, Zhikai Wu, Yi Zhou, Cheng Liu, Kewei Xu

“…Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. …”
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A Novel Model with GA Evolving FWNN for Effluent Quality and Biogas Production Forecast in a Full-Scale Anaerobic Wastewater Treatment Process by Zehua Huang, Renren Wu, XiaoHui Yi, Hongbin Liu, Jiannan Cai, Guoqiang Niu, Mingzhi Huang, Guangguo Ying

“…In this work, a novel model fuzzy wavelet neural network based on the genetic algorithm (GA-FWNN) that combines the advantages of the genetic algorithm, fuzzy logic, neural network, and wavelet transform was established for prediction of effluent quality and biogas production rates in a full-scale anaerobic wastewater treatment process. …”
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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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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…Results All model types demonstrated predictive performance on the test set with AUCPR that exceeded the current positivity rate. …”
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Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study by Haoyue Cao, Jianqiang Han, Weiming Hou, Juxiang Yuan

“…Second, four statistical methods were used to assess the correlation and lag effects across different age groups and epidemic periods. Deep learning algorithms were employed to evaluate the predictive effect of environmental factors on the incidence of scrub typhus. …”
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Detection of Water Content of Watermelon Seeds Based on Hyperspectral Reflection Combined with Transmission Imaging by Siyi Ouyang, Siwei Lv, Bin Li

“…The intermediate data fusion of the feature spectral data of reflectance and transmittance selected by the CARS algorithm improves the prediction effect of the model more obviously, in which the model with the best prediction accuracy is Raw-CRAS-LSSVR, whose <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msubsup><mi>R</mi><mi>P</mi><mn>2</mn></msubsup></semantics></math></inline-formula> and RMSEP are 0.9149 and 0.0144, respectively, which improves the prediction effect of the model built by a single full-spectrum datum by 5.72%. …”
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Machine-Learning-Driven Analysis of Wear Loss and Frictional Behavior in Magnesium Hybrid Composites by Barun Haldar, Hillol Joardar, Arpan Kumar Mondal, Nashmi H. Alrasheedi, Rashid Khan, Murugesan P. Papathi

“…Data-driven machine learning (ML) algorithms were utilized to identify complex patterns and predict relationships between input variables and output responses. …”
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A review on artificial intelligence-enabled mechanical analysis of 3D printed and FEM-modelled auxetic metamaterials by Aman Garg, Anshu Sharma, Weiguang Zheng, Li Li

“…This review provides a comprehensive analysis of the use of ML algorithms in predicting the properties and performance of auxetic metamaterials. …”
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Improved Hierarchical Convolutional Features for Robust Visual Object Tracking by Jinping Sun

“…The target and background will change continuously in the long-term tracking process, which brings great challenges to the accurate prediction of targets. The correlation filter algorithm based on manual features is difficult to meet the actual needs due to its limited feature representation ability. …”
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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…In the oracle case with known transferable source datasets, a transfer learning algorithm based on penalized maximum likelihood and expectation-maximization algorithm is established. …”
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