Interculture-Based Language Learning Model to Improve Prospective English Teachers’ Speaking Skills Viewed From Linguistic Awareness by Haerazi, Lalu Ari Irawan, Rimajon Sotlikova

“…This study aimed to know the use of the interculture-based language learning (IBLL) model to improve learners’ speaking skills integrated with linguistic awareness and their responses to learning experiences. …”
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SED-NET: Real-Time Suspicious Event Detection via Deep Learning-Based Di-Stream Neural Network by D. Siva Senthil, T. S. Sivarani

“…This research introduces a novel deep learning-based SED-NET model for detecting suspicious events in public places. …”
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Validity of problem-based learning biodiversity e-book integrating Ruwat Petirtaan Jolotundo's local wisdom for science literacy by Yusnita Ivaningtias, Sifak Indana, Novita Kartika Indah

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Integrating user demographic parameters for mouse behavioral biometric-based assessment fraud detection in online education platforms by Aditya Subash, Insu Song, Ickjai Lee, Kyungmi Lee

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Damage Identification of Railway Bridge KW51 Conditions Using Deep-Learning-Based 1D CNN Model by Ali Al-Ghalib, Sawsan Mahmoud

“…The 1D CNN classification algorithm is compared with a statistical-based ML model and another CNN model. The alternative classification model uses human-derived damage-sensitive features extracted from Principal Components Analysis (PCA) in the supervised Linear Discriminant Analysis (LDA) method. …”
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Deep Learning-Based Multi-Floor Indoor Localization Using Smartphone IMU Sensors With 3D Location Initialization by Jin-Woo Kim, Yoan Shin

“…This study proposes a deep learning-based multi-floor indoor localization method that estimates a three-dimensional position using only smartphone sensors without relying on external infrastructure. …”
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Inverse Kinematics of a 7-Degree-of-Freedom Robotic Arm Based on Deep Reinforcement Learning and Damped Least Squares by Shusheng Yu, Gongquan Tan

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Categorizing high-grade serous ovarian carcinoma into clinically relevant subgroups using deep learning–based histomic clusters by Byungsoo Ahn, Eunhyang Park

“…Conclusions Deep learning-based histologic analysis effectively stratifies HGSC into clinically relevant prognostic groups, highlighting the role of mitochondrial dynamics and energy metabolism in disease progression. …”
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Meta-learning based softmax average of convolutional neural networks using multi-layer perceptron for brain tumour classification by Irwan Budi Santoso, Shoffin Nahwa Utama, Supriyono

“…The variability in tumour shape, size, and position poses challenges to classification methods. …”
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The effects of e-learning vs. gamification-based training on ICU nurses’ knowledge and attitudes toward organ donation candidates: a study based on the psychological security and e... by Meysam Pour Hossein, Mojgan Ansari, Nazanin Fekri, Hamideh Yazdimoghaddam

“…Given the positive effects of both educational approaches, educational and medical center administrators should be familiarized with innovative approaches like gamification to enhance nurses’ learning by utilizing more engaging and practical methods.…”
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Protocol-Agnostic and Packet-Based Intrusion Detection Using a Multi-Layer Deep-Learning Architecture at the Network Edge by Rodolphe Picot, Felipe Gohring de Magalhaes, Ahmad Shahnejat Bushehri, Maroua Ben Atti, Gabriela Nicolescu, Alejandro Quintero

“…Unlike existing approaches that transform packets into alternative representations such as images or NLP-based techniques, which introduce additional overhead, our method processes packets directly, eliminating the need for complex components like Recurrent Neural Networks (RNNs) or convolutional layers. …”
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Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning by Li Xie, Han Xiao, Maoyu Zhao, Li Xu, Si Tang, Youzhu Qiu

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Deep learning-based risk stratification of ductal carcinoma in situ using mammography and abbreviated breast magnetic resonance imaging by Tingfeng Zhang, Tingting Cui, Zhenjie Cao, Jintao Hu, Jintao Hu, Jie Ma

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Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

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An e-Learning Intervention for Professionals to Promote Family-Centered Cancer Care When a Significant Caregiver for Children Is at End of Life: Mixed Methods Evaluation Study by Cherith Jane Semple, Carla O'Neill, Sarah Sheehan, Tanya McCance, Amanda Drury, Jeffrey R Hanna

“…MethodsGuided by the “person-based approach,” a mixed methods outcome evaluation was used. …”
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A Multi-Layer Attention Knowledge Tracking Method with Self-Supervised Noise Tolerance by Haifeng Wang, Hao Liu, Yanling Ge, Zhihao Yu

“…The knowledge tracing method based on deep learning is used to assess learners’ cognitive states, laying the foundation for personalized education. …”
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A condition diagnosis method for subway track structures employing distributed optical fiber sensing by Hong Han, Xiaopei Cai, Liang Gao

“…First, a method for constructing a correlation model for strain monitoring data based on the optimal space window is proposed to realize the division of measuring points to reduce the computational complexity, and then, the deep generative adversarial network model with residual learning is constructed. …”
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Fast Spectral Correlation Based on Sparse Representation Self-Learning Dictionary and Its Application in Fault Diagnosis of Rotating Machinery by Hongchao Wang, Wenliao Du

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GLOPS: A Hybrid Approach for Enhanced Scheduling in Cloud Computing Environments via Machine Learning-Based Process Prediction by Syed Abu Ammar Muhammad Zarif, Layla Kader Suma, Md. Sadat Rahman, Md. Motaharul Islam, Phuoc Hung Pham, Phong Dung Thi Nguyen, Nguyen Thanh Binh

“…In order to mitigate these challenges, this research proposes a comprehensive strategy that incorporates machine learning based process prediction and metaheuristic optimization techniques in the process scheduling. …”
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