Development of science subject-specific pedagogy to support disaster risk reduction in education: Its feasibility and influence by Nukhbatul Bidayati Haka, Luckyta Mauliana, Supriyadi Supriyadi, Abdul Hamid

“…This development research aims to provide innovations to learning media in Biology learning. The model used in developing this media adopts the Borg & Gall development theory which is cut into 9 steps with a population of students in class XI MIPA. …”
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Threat Modeling AI/ML With the Attack Tree by Seied Veria Hoseini, Jaakko Suutala, Juha Partala, Kimmo Halunen

“…This article aims to bridge this gap by proposing a simple, efficient, and time-saving approach to evaluate potential attacks and their security risks by utilizing the attack tree and a risk analysis method in the Adversarial Machine Learning (AML) field. One of the most important steps in determining the overall risk of the attack is evaluating the risk attached to each node in an attack tree. …”
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OncoMet: a deep learning framework for the prediction of oncogenic signaling pathways and metastasis in esophageal cancer patients using histopathology images from primary tumors by Syed Wajid Aalam, Abdul Basit Ahanger, Tabasum Majeed, Ab Naffi Ahanger, Tariq Masoodi, Ajaz A. Bhat, Assif Assad, Muzafar Ahmad Macha, Muzafar Rasool Bhat

“…The WSIs underwent several pre-processing steps, including patching, color normalization and augmentation. …”
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Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach by Lukas Zbinden, Samuel Erb, Damiano Catucci, Lars Doorenbos, Leona Hulbert, Annalisa Berzigotti, Michael Brönimann, Lukas Ebner, Andreas Christe, Verena Carola Obmann, Raphael Sznitman, Adrian Thomas Huber

“…The two-step approach of segmentation and co-registration allowed to assess arbitrary sequences. …”
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A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections by Yemeng Yang, Kun Han, Jiatao Li, Tao Zhang, Zhijing Zhu, Ling Su, Zhaoyong Han, Chunyan Xu, Yi Lu, Likun Pan, Tao Yang

“…This work represents a step forward in using machine learning to support antimicrobial stewardship and personalized antibiotic therapy.…”
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Improving the capture and reporting of adverse events in clinical trials of non-pharmacological interventions: learnings from the PaCCSC/CST membership by Rayan Saleh Moussa, Jack Power, Vanessa Yenson, Belinda Fazekas, Celia Marston, Annmarie Hosie, Layla Edwards, Domenica Disalvo, Linda Brown, Imelda Gilmore, John Stubbs, Andrea Cross, Sally Fielding, Meera R. Agar

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A siamese neural network model for phase identification in distribution networks by Dong Liu, Juan S. Giraldo, Peter Palensky, Pedro P. Vergara

“…The existing load profiles-based approaches rely on stepwise subtraction of the identified customers in a step-by-step identification procedure, while the accuracy of each step is not guaranteed. …”
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A bio-inspired framework for apple leaf disease detection: Integrating lesion localization, ant colony optimization, and machine learning by Xiaolong Li, Feifan Huang, Haotian Sun, Jiayu He, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang

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Investigating The Role Of Algerian Middle School Teachers In Enhancing Academic Self-regulation: A Key Towards Teaching How To Learn. by Houda Zouar, Hanane Sarnou

“… Academic self-regulation or self-regulated learning is the field that underlines the autonomy of learners and self-directed steps to learn. …”
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Development of a Team-Project-Based Flip Classroom Learning Model to Enhance Creativity in Teacher Training High School Students by Sri Sumarni, Riska Nurhayati, Ida Nugroho Saputro

“…The results showed that the team project-based flip classroom learning model is reliable and efficient. This model has three main steps: independent learning, face-to-face learning, and guided learning for self-reflection. …”
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Botany Teaching–Learning Proposal Using the Phytosociological Method for University Students’ Study of the Diversity and Conservation of Forest Ecosystems for University Students... by Ana Cano-Ortiz, José Carlos Piñar Fuentes, Carmelo Maria Musarella, Eusebio Cano

“…We propose a method consisting of four steps for phytosociological research and education on flora and vegetation diversity. …”
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Artificial-intelligence-guided design of ordered gas diffusion layers for high-performing fuel cells via Bayesian machine learning by Jing Sun, Pengzhu Lin, Lin Zeng, Zixiao Guo, Yuting Jiang, Cailin Xiao, Qinping Jian, Jiayou Ren, Lyuming Pan, Xiaosa Xu, Zheng Li, Lei Wei, Tianshou Zhao

“…Here, we propose a closed-loop workflow of Bayesian machine learning approach to guide the design of GDL structures. …”
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Analysis of pre-course learning situation of postgraduates in the selection of evidence-based medicine course at Peking University Health Science Center by ZHANG Meng, LIU Fengqi, WU Shanshan, WU Tao, SUN Feng

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Returning social context to seismic risk knowledge & management. Lessons learned from an interdisciplinary research in the city of Esmeraldas, Ecuador by Julien Rebotier, Patrick Pigeon, Pascale Metzger

“…Such a level of reflexivity within the discourse of research programming and risk management is consistent with the Risk Society thesis and the primary challenges that it posits. Lessons learned from REMAKE offer some insights to nurture the very first steps towards interdisciplinary research programmes and integrative disaster prevention policies, so that a significant difference might be made in disaster risk reduction.…”
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A deep learning based intrusion detection system for CAN vehicle based on combination of triple attention mechanism and GGO algorithm by Hongwei Yang, Mehdi Effatparvar

“…The purpose of TAN here is to identify intrusion within 3 steps. Within the initial phase, the major features have been extracted, and TAN functions as a descriptor of feature. …”
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Assessment of first-year medical student perceptions in the development of self-directed learning skills in a single medical school course by Amanda P. Beck

“…Critical Reasoning Exercises (CREs), a student-driven, problem-based learning course, was introduced for first year medical students at New York Medical College School of Medicine to ensure all steps of the SDL cycle were covered in a comprehensive and standardized way. …”
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Understanding the Early Impacts of School Mentors’ Ethics of Care on Filipino Gen Z Novice Science Educators’ Informal Professional Learning by Marwin Obmerga, Francis Michael Yambao

“…The field texts were analysed using Colaizzi’s procedural steps to distil the phenomenon’s essence. The findings were validated through the member checking procedure and the critical friend technique. …”
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Machine learning modeling based on informer for predicting complex unsteady flow fields to reduce consumption of computational fluid dynamics simulation by Mingkun Fang, Fangfang Zhang, Di Zhu, Ruofu Xiao, Ran Tao

“…Simultaneously, the predicted cloud maps at 24-time steps are compared with the CFD-calculated cloud maps to validate the feasibility of using machine learning models for predicting unsteady flow fields. …”
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Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom by Kehinde Sunmboye, Hannah Strafford, Samina Noorestani, Malena Wilison-Pirie

“…Personalized learning, supported by AI tools, can adapt to individual learning styles and needs, thus transforming how medical students approach their studies. …”
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Understanding the Early Impacts of School Mentors’ Ethics of Care on Filipino Gen Z Novice Science Educators’ Informal Professional Learning by Marwin Obmerga, Francis Michael Yambao

“…The field texts were analysed using Colaizzi’s procedural steps to distil the phenomenon’s essence. The findings were validated through the member checking procedure and the critical friend technique. …”
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