Behavioral Dynamics Analysis in Language Education: Generative State Transitions and Attention Mechanisms by Qi Zhang, Yiming Qian, Shumiao Gao, Yufei Liu, Xinyu Shen, Qing Jiang

“…Furthermore, this approach attains a learning satisfaction score of 89.2 with a 94.3% positive feedback rate, significantly outperforming benchmark models such as BERT, GPT-3, and T5. …”
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IL-6-Inducing Peptide Prediction Based on 3D Structure and Graph Neural Network by Ruifen Cao, Qiangsheng Li, Pijing Wei, Yun Ding, Yannan Bin, Chunhou Zheng

“…IL-6-inducing peptides are critical for the development of immunotherapy and diagnostic biomarkers for some diseases. Most existing methods for predicting IL-6-induced peptides use traditional machine learning methods, whose feature selection is based on prior knowledge. …”
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Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space by Shuai Li, Shufang He, Yuanrui Dong, Caihong Dai, Jinyuan Liu, Yanfei Wang, Hiroaki Shigemasu

“…In the future, it is necessary to explore methods for easier manipulating of depth cue signals in stereoscopic images and adopting deep learning-related methods to construct models and predict depths, to meet the increasing demand of human–computer interaction in complex 3D scenarios.…”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

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Infrared Small Target Detection Algorithm Based on Improved Dense Nested U-Net Network by Xinyue Du, Ke Cheng, Jin Zhang, Yuanyu Wang, Fan Yang, Wei Zhou, Yu Lin

“…Infrared weak and small target detection technology has attracted much attention in recent years and is crucial in the application fields of early warning, monitoring, medical diagnostics, and anti-UAV detection.With the advancement of deep learning, CNN-based methods have achieved promising results in general-purpose target detection due to their powerful modeling capabilities; however, CNN-based methods cannot be directly applied to infrared small targets due to the disappearance of deep targets caused by multiple downsampling operations. …”
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User experiences of a mobile hospital clowning application: User-based evaluation with hospitalized children by Eira Erola, Johanna Viitanen, Kaisa Savolainen, Pekka Lahdenne

“…However, technical difficulties and improvement requests, particularly regarding the child-clown messaging and communication features, were also identified. Based on the reported study, our key learnings and recommendations for conducting user-based evaluations with hospitalized pediatric patients include: careful planning of ethical approval and a research permit for a non-medical study, employing multiple approaches for recruiting participants, adjusting research methods to suit for children, pilot testing the methods, and involving parents to help and assist the child participants. …”
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Establishment of a wastewater-based surveillance network to support infectious disease surveillance in South Africa by Ms Sibonginkosi Maposa, Dr Mukhlid Yousif, Ms Chenoa Sankar, Mr Victor Vusi Mabasa, Ms Nosihle Msomi, Mr Emmanuel Phalane, Mr Sipho Gwala, Ms Mokgaetji Macheke, Ms Natasha Singh, Ms Kathleen Subramoney, Ms Phindile Ntuli, Mr Nkosenhle Ndlovu, Mr Thabo Mangena, Ms Mantshali Motloung, Mr Lethabo Monametsi, Ms Lebohang Rabotapi, Ms Fiona Els, Dr Said Rachida, Ms Sibonginkosi Maposa, Dr Kerrigan McCarthy

“…Challenges have provided learning and development opportunities. Research efforts are now focusing on exploring and interpreting the relationship between the clinical and wastewater based epidemiology of the pathogens, and development of models to support public health decision making. …”
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Integrative habitat analysis and multi-instance deep learning for predictive model of PD-1/PD-L1 immunotherapy efficacy in NSCLC patients: a dual-center retrospective study by Xiaoxiao Huang, Xiaoxin Huang, Yurun Xie, Kui Wang, Housheng Bai, Ruiling Ning, Xiqi Zhu, Deyou Huang, Guanqiao Jin

“…We implemented a DenseNet121-based architecture extracting radiomics features from triplanar (axial/coronal/sagittal) tumor sequences to construct a 2.5D deep-learning dataset. …”
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GAN-Based Driver’s Head Motion Using Millimeter-Wave Radar Sensor by Hong Nhung Nguyen, Yong-Hwa Kim

“…The recognition of driver behavior is critical for enhancing road safety, with a particular focus on monitoring driver attention. Radar-based recognition systems offer distinct advantages over traditional computer vision methods, including enhanced user privacy, reduced power consumption, and greater flexibility in sensor deployment. …”
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A Novel Global Energy and Local Energy-Based Legendre Polynomial Approximation for Image Segmentation by Feng Hu, Mengyun Zhang, Bo Chen

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Perception of Light Environment in University Classrooms Based on Parametric Optical Simulation and Virtual Reality Technology by Zhenhua Xu, Jiaying Chang, Cong Han, Hao Wu

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Optimalisasi Perencanaan Strategik Pembelajaran Dalam Meningkatkan Mutu Lulusan Era Digital by Suharyanto H. Soro, Enden Hayati, Dewi Tejawati, Asti Susanti

“…This research aims to identify strategic steps implemented in digital-based learning planning to improve the quality of education. era of globalization. …”
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Robust Feature Matching of Multi-Illumination Lunar Orbiter Images Based on Crater Neighborhood Structure by Bin Xie, Bin Liu, Kaichang Di, Wai-Chung Liu, Yuke Kou, Yutong Jia, Yifan Zhang

“…The method integrates deep-learning based crater detection, Crater Neighborhood Structure features (CNSFs) construction, CNSF similarity-based matching, and outlier removal. …”
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Adoption of evidence-based medicine: A comparative study of hospital and community pharmacists in Saudi Arabia. by Fahad Alzahrani, Nawaf Almutairi, Abdullah Aloufi, Abdulmalik Kattan, Abdulaziz Hakeem, Mohammed Alharbi, Naif Alarawi, Haifa A Fadil, Ehsan Habeeb

“…<h4>Objectives</h4>Evidence-based medicine (EBM) combines clinical expertise, patient values, and the best available evidence to guide healthcare decision-making. …”
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Underwater Sound Speed Profile Inversion Based on Res-SACNN from Different Spatiotemporal Dimensions by Jiru Wang, Fangze Xu, Yuyao Liu, Yu Chen, Shu Liu

“…It combines the spatiotemporal characteristics of sea level anomaly (SLA) and sea surface temperature anomaly (SSTA) data and establishes a nonlinear relationship between satellite remote sensing data and sound speed field by deep learning. The single empirical orthogonal function regression (sEOF-r) method is used in a comparative experiment to confirm the model’s performance in both the time domain and the region. …”
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Development of a Collision-Free Path Planning Method for a 6-DoF Orchard Harvesting Manipulator Using RGB-D Camera and Bi-RRT Algorithm by Zifu Liu, Rizky Mulya Sampurno, R. M. Rasika D. Abeyrathna, Victor Massaki Nakaguchi, Tofael Ahamed

“…Therefore, in this study, we introduced a collision-free path planning method for a 6-DoF orchard harvesting manipulator using an RGB-D camera and the Bi-RRT algorithm. …”
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Adapted Swin Transformer-based real-time plasma shape detection and control in HL-3 by Qianyun Dong, Zhengwei Chen, Rongpeng Li, Zongyu Yang, Feng Gao, Yihang Chen, Fan Xia, Wulyu Zhong, Zhifeng Zhao

“…In the field of magnetic confinement plasma control, the accurate feedback of plasma position and shape primarily relies on calculations derived from magnetic measurements through equilibrium reconstruction or matrix mapping method. …”
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Applying state-of-the-art artificial intelligence to grading in simulation-based education: assessment, feedback, and ROI by Krystle K. Campbell, Michael J. Holcomb, Sol Vedovato, Lenora Young, Gaudenz Danuser, Thomas O. Dalton, Andrew R. Jamieson, Daniel J. Scott

“…Abstract Objective Accreditation bodies are driving competency-based education in healthcare, prompting curriculum reform. …”
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Data-driven soil salinization mapping: risk prediction and uncertainty quantification based on Bayesian inference by Yujian Yang, Ying Zhao, Rongjiang Yao, Xueqin Tong

“…KDE of 100 groups of predicted values showed a good fit based on data-driven soil EC, higher levels of uncertainty associated with soil EC correspond to areas where the gaussian distributions overlap using Theano, as PyMC3 core component based on deep learning principles.…”
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The Effect of Realistic Mathematics Education Approach on Students' Conceptual Understanding by Ahmad Nizar Rangkuti, Mariam Nasution, Almira Amir, Irwan Saleh Dalimunthe, Samsuddin Samsuddin, Muhammad Amin, Dame Siregar, Mhd. Rafi'i Ma'arif Tarigan

“…The research findings indicate that students' understanding of mathematical concepts was better when using the Realistic Mathematics Approach compared to conventional learning methods. Based on the hypothesis testing results, it was found that t-count > t-table (2.23 > 1.98) and the Sig. value = 0.018, indicating that there is a positive effect of the Realistic Mathematics Education Approach (RME) on students' conceptual understanding. …”
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