Analyzing and explaining the reflective teacher approach and its role in improving curriculum knowledge: Developing an educational discourse at Farhangian University by Reza Masouminejad

“…In fact, reflective activity allows teachers to take a moment to examine their past teaching experiences and through the tools of self-observation, self-analysis and self-evaluation, identify individual experiences and discover the truth about themselves and improve their professional life (Suphasri & Chinokul, 2021). …”
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Discrete Wavelet Transform Sampling for Image Super Resolution by Chieh-Li Chen, Heng-Lin Yao, Bo-Lin Jian

“…We evaluate our model on a super-resolution dataset and compare its performance against other networks, highlighting the importance of minimizing trainable parameters for real-time deployment on resource-constrained drone platforms. …”
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A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation by Ronald Kfouri, Harag Margossian

“…We then subject the neural network to multiple test scenarios featuring noisier measurements and bad data to evaluate the robustness of our algorithm. …”
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Bibliometric analysis of laryngeal cancer treatment literature (2003–2023) by Yan Zhao, Jiancheng Xue

“…This study explores the evolution of key topics and trends in laryngeal cancer research. …”
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CFAR-DP-FW: A CFAR-Guided Dual-Polarization Fusion Framework for Large-Scene SAR Ship Detection by Tianjiao Zeng, Tianwen Zhang, Zikang Shao, Xiaowo Xu, Wensi Zhang, Jun Shi, Shunjun Wei, Xiaoling Zhang

“…The proposed CFAR-DP-FW consists of three core components: the CFAR dual-polarization detector provides initial target indication; the CFAR field generator constructs a probabilistic ship presence map, reducing reliance on CFAR's hard thresholds; and the CFAR guidance dual-polarization network incorporates a novel feature extractor and enhancement module, tailored to amplify relevant features, and suppress noise. …”
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GAN-Based Super-Resolution in Linear R-SAM Imaging for Enhanced Non-Destructive Semiconductor Measurement by Thi Thu Ha Vu, Tan Hung Vo, Trong Nhan Nguyen, Jaeyeop Choi, Le Hai Tran, Vu Hoang Minh Doan, Van Bang Nguyen, Wonjo Lee, Sudip Mondal, Junghwan Oh

“…The precise identification and non-destructive measurement of structural features and defects in semiconductor wafers are essential for ensuring process integrity and sustaining high yield in advanced manufacturing environments. …”
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Dynamical System Modeling for Disruption in Supply Chain and Its Detection Using a Data-Driven Deep Learning-Based Architecture by Víctor Hugo de la Cruz Madrigal, Liliana Avelar Sosa, Jose-Manuel Mejía-Muñoz, Jorge Luis García Alcaraz, Emilio Jiménez Macías

“…The network architecture integrates convolutional layers for feature extraction and dense layers for classification, thereby enhancing its ability to identify disruption-related patterns. …”
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High Precision Detection Pipe Bursts Based on Small Sample Diagnostic Method by Guoxin Shi, Xianpeng Wang, Jingjing Zhang, Xinlei Gao

“…The performance of the model was evaluated in both simulated and real scenarios. The results indicate that the leaked features can be improved by 350% by the HLR. …”
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Deep learning based on multiparametric MRI predicts early recurrence in hepatocellular carcinoma patients with solitary tumors ≤5 cm by Tingting Mu, Xinde Zheng, Danjun Song, Jiejun Chen, Xuewang Yue, Wentao Wang, Shengxiang Rao

“…Purpose: To evaluate the effectiveness of a constructed deep learning model in predicting early recurrence after surgery in hepatocellular carcinoma (HCC) patients with solitary tumors ≤5 cm. …”
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Integrated bioinformatics and functional studies identify CDK9 as a potential prognostic biomarker and therapeutic target in AML by Zhibin Xie, Yang Xia, Zhongyu Li, Mengmeng Zhang, Yuanyuan Tan, Yuqing Han, Meng Wang, Pingping Zhang, Jiajia Li

“…Furthermore, the relationship between CDK9 expression and tumor immune infiltration was evaluated, and a protein–protein interaction (PPI) network was constructed. …”
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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…The augmented fundus images are subsequently processed through four convolutional neural network (CNN) models—ResNet50, InceptionV3, VGG16, and Xception—to extract deep features, which are then combined into a final feature matrix. …”
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Development and Clinical Interpretation of an Explainable AI Model for Predicting Patient Pathways in the Emergency Department: A Retrospective Study by Émilien Arnaud, Pedro Antonio Moreno-Sanchez, Mahmoud Elbattah, Christine Ammirati, Mark van Gils, Gilles Dequen, Daniel Aiham Ghazali

“…Various models (including a cross-validation artificial neural network (ANN), a k-nearest neighbors (KNN) model, a logistic regression (LR) model, and a random forest (RF) model) were trained and assessed for performance with regard to the area under the receiver operating characteristic curve (AUROC). …”
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A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO by Yu Wang, Haifu Sun, Tiankai Jiang, JunFeng Shi, JunFeng Shi, Qin Wang, Qin Wang, Hongwei Yang, Hongwei Yang, Yusen Qiao

“…Secondly, we develop the C2f-Faster-EMA module that preserves fine-grained spatial details through optimized information pathways and statistical feature aggregation. Third, our Feature-Driven Pyramid Network facilitates multi-resolution feature fusion across scales for improved detection. …”
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Dermoscopic Patterns of Facial Melanoses in Adult Patients: A Cross-sectional Study by Manjari Annapurna Malladi, Rameez Raja Mullan Abdul, Divya Sri Vaka, Abhilash Bhavani Satya Venkata Subrahmanya Pampana, Susmitha Kattamsetty

“…Different pigmentary conditions exhibit specific pigment patterns, networks and special features on dermoscopy, which aid in their diagnosis. …”
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Functional characteristics of sleep monitoring devices in China: A real-world cross-sectional study by Le Yang, Bingtao Weng, Xingyan Xu, Zhi Huang, Run Ding, Miaomiao Si, Yingxin Fu, Yurui Zhu, Yu Jiang, Beibei Rao, Xinyi Zhang, Qingwei Zhou, Shenglan Lin, Yansong Guo, XiaoXu Xie

“…A two-level variance model was employed to analyzed the link between device features and sales. Additionally, a structured questionnaire assessed public usage and attitudes towards these devices, with 167 responses collected via social networks. …”
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SBML Level 3: an extensible format for the exchange and reuse of biological models by Sarah M Keating, Dagmar Waltemath, Matthias König, Fengkai Zhang, Andreas Dräger, Claudine Chaouiya, Frank T Bergmann, Andrew Finney, Colin S Gillespie, Tomáš Helikar, Stefan Hoops, Rahuman S Malik‐Sheriff, Stuart L Moodie, Ion I Moraru, Chris J Myers, Aurélien Naldi, Brett G Olivier, Sven Sahle, James C Schaff, Lucian P Smith, Maciej J Swat, Denis Thieffry, Leandro Watanabe, Darren J Wilkinson, Michael L Blinov, Kimberly Begley, James R Faeder, Harold F Gómez, Thomas M Hamm, Yuichiro Inagaki, Wolfram Liebermeister, Allyson L Lister, Daniel Lucio, Eric Mjolsness, Carole J Proctor, Karthik Raman, Nicolas Rodriguez, Clifford A Shaffer, Bruce E Shapiro, Joerg Stelling, Neil Swainston, Naoki Tanimura, John Wagner, Martin Meier‐Schellersheim, Herbert M Sauro, Bernhard Palsson, Hamid Bolouri, Hiroaki Kitano, Akira Funahashi, Henning Hermjakob, John C Doyle, Michael Hucka, SBML Level 3 Community members, Richard R Adams, Nicholas A Allen, Bastian R Angermann, Marco Antoniotti, Gary D Bader, Jan Červený, Mélanie Courtot, Chris D Cox, Piero Dalle Pezze, Emek Demir, William S Denney, Harish Dharuri, Julien Dorier, Dirk Drasdo, Ali Ebrahim, Johannes Eichner, Johan Elf, Lukas Endler, Chris T Evelo, Christoph Flamm, Ronan MT Fleming, Martina Fröhlich, Mihai Glont, Emanuel Gonçalves, Martin Golebiewski, Hovakim Grabski, Alex Gutteridge, Damon Hachmeister, Leonard A Harris, Benjamin D Heavner, Ron Henkel, William S Hlavacek, Bin Hu, Daniel R Hyduke, Hidde de Jong, Nick Juty, Peter D Karp, Jonathan R Karr, Douglas B Kell, Roland Keller, Ilya Kiselev, Steffen Klamt, Edda Klipp, Christian Knüpfer, Fedor Kolpakov, Falko Krause, Martina Kutmon, Camille Laibe, Conor Lawless, Lu Li, Leslie M Loew, Rainer Machne, Yukiko Matsuoka, Pedro Mendes, Huaiyu Mi, Florian Mittag, Pedro T Monteiro, Kedar Nath Natarajan, Poul MF Nielsen, Tramy Nguyen, Alida Palmisano, Jean‐Baptiste Pettit, Thomas Pfau, Robert D Phair, Tomas Radivoyevitch, Johann M Rohwer, Oliver A Ruebenacker, Julio Saez‐Rodriguez, Martin Scharm, Henning Schmidt, Falk Schreiber, Michael Schubert, Roman Schulte, Stuart C Sealfon, Kieran Smallbone, Sylvain Soliman, Melanie I Stefan, Devin P Sullivan, Koichi Takahashi, Bas Teusink, David Tolnay, Ibrahim Vazirabad, Axel von Kamp, Ulrike Wittig, Clemens Wrzodek, Finja Wrzodek, Ioannis Xenarios, Anna Zhukova, Jeremy Zucker

“…Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. …”
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Structural, optical and biological characterization of a new cobalt-based mixed halide hybrid compound: insights from DFT and vibrational analysis by Iteb Ben Mahmoud, Naoufel Ben Hamadi, Sandra Walha, Nourhene Zammel, Ali Ben Ahmed, Ahlem Guesmi, Wesam Abd El-Fattah, Ferdinando Costantino, Houcine Naïli

“…These units are interconnected via an extensive network of N–H···Br/Cl and C–H···Br/Cl hydrogen bonds, stabilizing the crystal lattice. …”
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Data-Enabled Intelligence in Complex Industrial Systems Cross-Model Transformer Method for Medical Image Synthesis by Zebin Hu, Hao Liu, Zhendong Li, Zekuan Yu

“…Recently, generative adversarial network (GAN) models are applied to many medical image synthesis tasks and show prior performance, since they enable to capture structural details clearly. …”
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A novel Arthrobotrys species: Taxonomic characterization, nematicidal activity, and multi-omics insights into nematode predation by Mengting Gao, Zhaoqi Yan, Zexin Liu, Yunxia Jiang, Tengteng Liu, Xingjun Miao, Meixue Dai, Tanay Bose, Runlei Chang

“…The integrated in vitro nematicidal activity, physiological adaptability, and multi-omics data suggest A. byssisimilis warrants further evaluation as a potential biocontrol agent against PWN, while its unique genomic features provide new molecular targets for investigating fungal-nematode interactions.…”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…Decision trees offer the advantage of handling high-dimensional and complexly correlated data through feature combination and selection. Extreme Gradient Boosting (XGBoost) overcomes the issue of overfitting in decision trees by integrating multiple tree models. …”
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