Improvement of Surgical Technologist Students' Learning by Development of a Customized e-portfolio: A Mixed-method Study by Leila Sadati, Sahar Karami, Rana Abjar, Fatemeh Edalat, Pourya Kanani, Zahra Nouri Khaneghah

“…Background: Electronic portfolios provide opportunities for students to reflect on their performance and develop their competencies.Objectives: The present study was done to improve surgical technologist students' learning through the development of a customized e-portfolio.Methods: This interventional study was conducted using a sequential mixed method in two phases. …”
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Delay Prediction Through Multi-Channel Traffic and Weather Scene Image: A Deep Learning-Based Method by Ligang Yuan, Linghua Kong, Haiyan Chen

“…Using real operational data from Guangzhou Baiyun Airport, this paper shows that ADLCNN achieves significantly higher prediction accuracy compared to traditional machine learning methods. The results confirm that MTWSI provides a more accurate representation of real traffic conditions under convective weather.…”
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Underwater DVL Optimization Network (UDON): A Learning-Based DVL Velocity Optimizing Method for Underwater Navigation by Feihu Zhang, Shaoping Zhao, Lu Li, Chun Cao

“…To evaluate the proposed method, we conducted lake experiments using SINS and DVL equipment, from which the collected data were organized into a dataset for training and assessing the model. …”
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A physical state prediction method based on reduce order model and deep learning applied in virtual reality by Pengbo Yu, Qiyu Liu, Qiyu Liu, Qiyu Liu, Qiyu Liu, Siyun Yi, Ming Zhu, Yangheng Hu, Gexiang Zhang, Gexiang Zhang

“…To enhance the application of VR, a real-time VR visualization method is introduced, which adopts a pre-trained deep learning model to construct high-fidelity physical dynamic changes. …”
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Research on cloud detection method based on voting ensemble learning using FY-4B satellite data by Jianhua Qu, Lingmeng Ye, Junjie Yan, Jinjing Sun, Ziyu Huyan

“…We propose a Voting Ensemble Learning method to enhance generalization and adaptability for stable cloud detection. …”
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LETSmix: a spatially informed and learning-based domain adaptation method for cell-type deconvolution in spatial transcriptomics by Yangen Zhan, Yongbing Zhang, Zheqi Hu, Yifeng Wang, Zirui Zhu, Sijing Du, Xiangming Yan, Xiu Li

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A Real-Time Human–Machine–Logistics Collaborative Scheduling Method Considering Workers’ Learning and Forgetting Effects by Wenchao Yang, Sen Li, Guofu Luo, Hao Li, Xiaoyu Wen

“…Third, a task slack-based matching method is developed to facilitate real-time, adaptive allocation of tasks to resource groups. …”
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A Deep Learning Inversion Method for 3D Temperature Structures in the South China Sea with Physical Constraints by Dongcan Xu, Yahao Liu, Yuan Kong

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Prediction of 1p/19q state in glioma by integrated deep learning method based on MRI radiomics by Fengda Li, Zeyi Li, Hong Xu, Gang Kong, Ze Zhang, Kaiyuan Cheng, Longyuan Gu, Lei Hua

“…Conclusion The deep learning model based on conventional MRI radiomic integrates VAE and IG methods. …”
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Rice Phenology Classification Model Based on Sentinel-1 Using Machine Learning Method on Google Earth Engine by Hengki Muradi, Dede Dirgahayu Domiri, I Made Parsa, I Kadek Yoga, Alhadi Bustamam, Anisa Rarasati, Sri Harini, R. Johannes Manalu, Mokhamad Subehi

“…In this study, the performance of two machine learning methods for classification was compared: classification and regression trees (CART) and RF. …”
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A Deep Learning Inversion Method for Airborne Time-Domain Electromagnetic Data Using Convolutional Neural Network by Xiaodong Yu, Peng Zhang, Xi Yu

“…In this paper, we present a deep learning inversion method that can be used to solve the fast inversion problem of airborne time-domain electromagnetic data; the method uses a one-dimensional convolutional neural network. …”
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Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method by Pooria Iranian, Thomas Lapauw, Thomas Van den Dries, Sevada Sahakian, Joris Wuts, Valéry Ann Jacobs, Jef Vandemeulebroucke, Maarten Kuijk, Hans Ingelberts

“…In this work, the capabilities of an endoscopic lifetime imaging system are demonstrated using a rigid endoscope involving various phantoms and an IRF-free deep learning-based method with only 6-time points. The results show that this application’s fluorescence lifetime image has better lifetime uniformity and precision with 6-time points than the conventional methods.…”
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The Clinical Learning Environment Experience of the Student Nurse of the Generation Z: a Convergent Parallel Mixed Method Study by Marzia Lommi, Giuliana Covelli, Dhurata Ivziku, Giorgia Barretta, Gianluca Pozzuoli, Barbara Porcelli, Luca Guarente, Simona Ricci

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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

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Student Center Learning Design : Development of Human Rights Textbooks Based on Case Method and Team Based Project by Alfiandra Alfiandra, Emil El Faisal, Mariyani Mariyani, Rilda Sonada, Hanifah Qonita, Salsa Agustin

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Efficient Solving of Boundary Value Problems Using Radial Basis Function Networks Learned by Trust Region Method by Mohie Mortadha Alqezweeni, Vladimir Ivanovich Gorbachenko, Maxim Valerievich Zhukov, Mustafa Sadeq Jaafar

“…The main advantages of mesh-free methods based on RBFN are explained here. To learn RBFNs, the Trust Region Method (TRM) is proposed, which simplifies the process of network structure selection and reduces time expenses to adjust their parameters. …”
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A Proposed Method for Deep Learning-Based Automatic Tracking with Minimal Training Data for Sports Biomechanics Research by Daichi Yamashita, Minoru Matsumoto, Takeo Matsubayashi

“…<b>Methods:</b> The present method facilitates the arbitrary definition of key points on athletes’ bodies or sports equipment. …”
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A Long-Time Series Forecast Method for Wind Turbine Blade Strain with Incremental Bi-LSTM Learning by Bingkai Wang, Wenlei Sun, Hongwei Wang

“…Based on the Bi-directional Long Short-Term Memory (Bi-LSTM) framework, the proposed method incorporates incremental learning via an error-supervised feedback mechanism, enabling the dynamic self-updating of the model parameters. …”
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Hypervolume-Based Multi-Objective Optimization Method Applying Deep Reinforcement Learning to the Optimization of Turbine Blade Shape by Kazuo Yonekura, Ryusei Yamada, Shun Ogawa, Katsuyuki Suzuki

“…A multi-objective turbine shape optimization method based on deep reinforcement learning (DRL) is proposed. …”
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Proposing a Novel Method for Optimal Location Finding Based on Machine Learning Algorithms and Gray Wolf Optimization by Fatemeh Heydari Pirbasti, Mahmoud Modiri, Kiamars Fathi-Hafshejani, Alireza Rashidi-Komijan

“…In this paper, a new method based on machine learning for finding the optimal location of hazardous waste disposal is presented. …”
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