Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…Furthermore, decision tree, random forest, support vector machine (SVM), logistic regression, XGBoost, blending ensemble, and convolutional neural network (CNN) algorithms with corresponding optimized hyperparameters and synthetic minority oversampling technique (SMOTE) have been applied for learning behavior classification. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…In summary, the YOLOv11x algorithm demonstrates excellent performance and broad application potential in forest fire smoke recognition, providing robust technical support for early fire warning systems and offering valuable insights for the design of intelligent monitoring systems in related fields.…”
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Advanced Ignition and Combustion Analysis of Second‐Generation Biodiesels in Turbocharged Diesel Engines by Balamurugan Mani, Ratchagaraja Dhairiyasamy, Deepika Gabiriel, C. Ahamed Saleel, Nasim Hasan, Fayaz Hussain

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Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…Gene-expression analysis can be an alternative, where the different machine learning and artificial intelligence techniques can be developed to learn microarray RNA details for breast cancer detection. …”
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Research on rock fracture evolution prediction model based on Adam-ConvLSTM and transfer learning by Runze Liu, Ziwei Wang, Yanbo Zhang, Xulong Yao, Shaohong Yan, Zhiyuan Chen, Shuai Wang, Hua Li, Qi Wang

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On McEliece-Type Cryptosystems Using Self-Dual Codes With Large Minimum Weight by Luca Mariot, Stjepan Picek, Radinka Yorgova

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A Beyond 5G OTFS Waveform Radio for Smart Hospital: PAPR Reduction in OTFS Using the Cuckoo Search–Based PTS Method by Arun Kumar, Aziz Nanthaamornphong

“…The results revealed that the proposed PTS + CS obtained significant PAPR and PSD performance while retaining the BER of the framework. The optimal PAPR, BER, PSD, and power-saving performance of the advanced radio enhance the quality of the B5G-based intelligent healthcare system.…”
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Exploring the Current Status of Risk Stratification in Hypertrophic Cardiomyopathy: From Risk Models to Promising Techniques by Alexandros Kasiakogias, Christos Kaskoutis, Christos-Konstantinos Antoniou, Stavros Georgopoulos, Dimitrios Tsiachris, Petros Arsenos, Alexandrina Kouroutzoglou, Dimitrios Klettas, Charalambos Vlachopoulos, Konstantinos Tsioufis, Konstantinos Gatzoulis

“…Novel cardiac imaging techniques, better understanding of the genetic substrate and artificial intelligence-based algorithms may prove promising for risk refinement. …”
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NOMA Performance Improvement with Downlink Sectorization by Hurianti Vidyaningtyas, . Iskandar, . Hendrawan, Aloysius A. Pramudita

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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. …”
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A mineral-strength conversion model based on LIBS technology and rapid batch testing and application of uniaxial compressive strength by Qinghe ZHANG, Xiaorui WANG, Chuanbing WANG, Weiguo LI, Fengqiang GONG, Xinsheng ZHANG, Jingguo LI

“…Due to the complexity and abruptness of deep engineering disasters, the mechanical parameters of rocks, particularly uniaxial compressive strength (UCS), play a critical role in stability analysis, risk assessment, support parameter optimization, and intelligent construction. Achieving rapid quantitative characterization of rock strength is therefore essential. …”
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Cattle identification based on multiple feature decision layer fusion by Dongxu Li, Baoshan Li, Qi Li, Yueming Wang, Mei Yang, Mingshuo Han

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Estimation of phytoplankton community composition from satellite data using a fuzzy and probabilistic combination model in mountainous reservoirs: A case of Huating Lake in spring... by Yixuan Qiu, Zhongya Fan, Huiyun Feng, Yutao Wang, Dan Li, Wencai Wang, Ruting Huang, Jingang Jiang

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Mixed reality infrastructure based on deep learning medical image segmentation and 3D visualization for bone tumors using DCU-Net by Kun Wang, Yong Han, Yuguang Ye, Yusi Chen, Daxin Zhu, Yifeng Huang, Ying Huang, Yijie Chen, Jianshe Shi, Bijiao Ding, Jianlong Huang

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Meshless Numerical Simulation on Dry Shrinkage Cracking of Concrete Piles for Offshore Wind Power Turbine by Cong Hu, Jianfeng Xue, Taicheng Li, Haiying Mao, Haotian Chang, Wenbing Zhang

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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…This study introduces Pympute, a comprehensive Python package designed for efficient and robust missing value imputation for EHRs. Pympute’s core algorithm, Flexible, intelligently selects the optimal imputation method for each variable based on its characteristics. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

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Speech Signal Enhancement Techniques by Chouki Zegar, Abdelhakim Dahimene

“…The comparison study results based on subjective and objective tests showed that the Optimally Modified Log-Spectral Amplitude Estimator (OM-LSA) method outperforms all the implemented DFTbased single-channel speech enhancement algorithms …”
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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

“…In terms of model selection, we employed a pre-trained ResNet34 network and fine-tuned its architecture to suit our specific task. For the optimization algorithm, we opted for the Adam optimizer and utilized the cross-entropy loss function. …”
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