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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A Dynamic and Timely Point-of-Interest Recommendation Based on Spatio-Temporal Influences, Timeliness Feature and Social Relationships by Jun Zhu, Haifeng Lin, Zhinan Gou, Yiqing Xu, Hongying Liu, Ming Tang, Li Wang, Shu Li, Bing Hu

“…The experimental results reveal that our algorithm outperforms seven state-of-the-art recommenders in terms of prediction accuracy and system timeliness.…”
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Artificial intelligence (machine learning) in the psychology of learning: Unveiling new insights and directions by Nora Darjazini, Mohammad Hossein Zarghami, Reza Ghorban Jahromi, Leila Shobeiry

“…Results: 260 features were extracted from the computer texts prepared from the speech and writing learners responses by natural language processing (NLP) algorithms. We used learning models of decision tree, nearest neighbor, support vector method, neural network and regularized linear method to predict reading comprehension using extracted linguistic features. …”
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Full-scale simulator to test a control system of an engine-propeller powerplant of a convertible aerial vehicle by D. V. Vereshchikov, I. K. Makarov, I. S. Moiseeva, S. M. Barantsev

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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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MicroRNA-1912 regulates cholesterol homeostasis by targeting PCSK9 by Chan Joo Lee, Myeongjune Go, Sae-Bom Jeon, Sun-Ho Lee, Dongkook Min, So Hee Park, Seunghyun Lee, Sahng Wook Park

“…Specific interactions of miR-1912 and miR-224 with the 3′ untranslated region (UTR) of PCSK9 mRNA were confirmed by a luciferase reporter assay and site-directed mutagenesis analysis of the predicted seed region. In transgenic mice expressing liver-specific human PCSK9 with its 3ʹ UTR, administration of miR-1912 mimics resulted in a reduction of plasma total cholesterol levels as determined by fast protein liquid chromatography following hepatic delivery. …”
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Machine learning potential predictor of idiopathic pulmonary fibrosis by Chenchun Ding, Quan Liao, Renjie Zuo, Shichao Zhang, Zhenzhen Guo, Junjie He, Ziwei Ye, Weibin Chen, Sunkui Ke

“…To construct an IPF risk prediction model, we employed LASSO-Cox regression analysis and the SVM-RFE algorithm. …”
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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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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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Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation—A Review by Seun Orenuga, Philip Jordache, Daniel Mirzai, Tyler Monteros, Ernesto Gonzalez, Ahmed Madkoor, Rahim Hirani, Raj K. Tiwari, Mill Etienne

“…This literature review explores the current and potential applications of AI in TBI management, focusing on AI’s role in diagnostic tools, neuroimaging, prognostic modeling, and rehabilitation programs. AI-driven algorithms have demonstrated high accuracy in predicting mortality, functional outcomes, and personalized rehabilitation strategies based on patient data. …”
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Data-Driven Approaches for Estimation of EV Battery SoC and SoH: A Review by Shahid Gulzar Padder, Jayesh Ambulkar, Atul Banotra, Sudhakar Modem, Sidharth Maheshwari, Kolleboyina Jayaramulu, Chinmoy Kundu

“…In this study, machine learning algorithms exhibited substantial enhancements in predicting and maintaining the lifespan of electric vehicle batteries. …”
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Model Design for Personnel Selection with Data Mining Approach (Case Study: A Commerce Bank of Iran) by Adel Azar, Parviz Ahmadi, Mohammad Vahid Sebt

“…Rules Derivation has been accomplished by the QUEST, CHAID, C5.0 and CART algorithms. The objective and the appropriate algorithms are determined based on seemingly “irrelevant” components, which the Commerce Bank Human Resources management experts described. …”
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The Spatiotemporal Evolution and Driving Forces of the Urban Heat Island in Shijiazhuang by Xia Zhang, Yue Liu, Ruohan Chen, Menglin Si, Ce Zhang, Yiran Tian, Guofei Shang

“…Autumn exhibited the greatest reduction in UHI, while predictions suggested peak temperatures in summer 2027. …”
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Simultaneous Instance and Attribute Selection for Noise Filtering by Yenny Villuendas-Rey, Claudia C. Tusell-Rey, Oscar Camacho-Nieto

“…Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. …”
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Enhancing accuracy through ensemble based machine learning for intrusion detection and privacy preservation over the network of smart cities by Mudita Uppal, Yonis Gulzar, Deepali Gupta, Jayant Uppal, Mukesh Kumar, Shilpa Saini

“…The dataset utilized for anomaly-based detection techniques is KDDCup99 dataset, on which the different algorithms have been applied. The goal is to gain knowledge about data integrity and improve the predictive power of data. …”
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Research on Road Traffic Safety Risk Assessment Based on the Data of Radar Video Integrated Sensors by Xiaoyu CAI, Zimu LI, Wufeng QIAO, Xiling CHENG, Bo PENG, Dong ZHANG

“…To accurately prevent and warn of traffic accidents, this article proposes a method for predicting urban road traffic safety risks based on vehicle driving behaviour data and information entropy theory. …”
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Spatiotemporal pattern and driving factors of atmospheric CO2 concentrations based on satellite remote sensing from 2001 to 2022 in central Yunnan plateau by Yunling He, Xiaohua Zhang, Ning Pu, Chunyan Wu, Wu Tang

“…Random Forest (RF) algorithm was used to gain insight into the nonlinear effects of these different indicators on near-formation atmospheric CO2 concentrations. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

“…<b>Methods</b>: The paper presents the application of ML algorithms, with a focus on convolutional neural networks (CNN) and recurrent neural networks (RNN), in identifying biomarkers of anxiety disorders and predicting therapy responses. …”
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Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification by Miao Yu, Zhenqi Ye, Zixin Ye, Yaping Wu, Xiang Wu

“…Then, machine learning algorithms were exploited to screen hub NRGs, and a predictive model was constructed based on these hub NRGs. …”
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