PREDICTING THE LEARNING PATH TO LEARNER’S OPTIMUM COMPREHENSION by Ifeanyi Isaiah Achi, Chukwuemeka Odi Agwu, Christopher Chizoba Nnamene, Sylvester C. Aniobi, Ifebude Barnabas C., Kelechi Christian Oketa, Godson Kenechukwu Ezeh, John Otozi Ugah

Subjects: “…Machine Learning…”
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Transfer learning for linear regression with differential privacy by Yiming Hou, Yunquan Song, Zhijian Wang

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Wind and Trees: Lessons Learned from Hurricanes by Mary L. Duryea, Eliana Kampf

“…FOR118/FR173: Wind and Trees: Lessons Learned from Hurricanes (ufl.edu) …”
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Temperature and Humidity Prediction Based on Machine Learning by Xiong Yanqi

“…This paper employs various machine learning models, including Linear Regression(LR). Support Vector Machine(SVM), Neural Network(NN), and Random Forest(RF). to analyze their accuracy in predicting temperature and humidity. …”
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Blended learning in physical education of distance students by Akhmatgatin, Anvar Amirovich, Struganov, Sergey M., Balashov, Alexander V.

Subjects: “…blended learning…”
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Causal inference and machine learning in endocrine epidemiology by Kosuke Inoue

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Involvement of Adult Hippocampal Neurogenesis in Learning and Forgetting by Suk-yu Yau, Ang Li, Kwok-Fai So

“…Mounting evidence has suggested that hippocampal neurogenesis contributes to some forms of hippocampus-dependent learning and memory; however, the detailed mechanism concerning how this small number of newborn neurons could affect learning and memory remains unclear. …”
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Vascular Anomalies in Pancreaticoduodenectomy: A Lesson Learned by Joana E. Ochoa, David T. Pointer, John B. Hamner

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Folk Text in the Process of Foreign Language Learning by E. R. Kornienko

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Deep Learning for Plastic Waste Classification System by Janusz Bobulski, Mariusz Kubanek

“…One of the opportunities is the use of deep learning and convolutional neural network. In household waste, the most problematic are plastic components, and the main types are polyethylene, polypropylene, and polystyrene. …”
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Engaging Learners via Live Online Learning by Taylor Nash, Megan S. Cantrell

Subjects: “…Online Learning…”
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Evaluation of Learning Management Systems for Success Factors. by Muhaise, Hussein, Adeyemi, A. L., Muteb,I.J.

Subjects: “…eLearning…”
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Exploring Medical Students’ Readiness for E-Learning and Knowledge Sharing Behaviors in Emergency Remote Learning Environments during Covid-19 by Gunes Korkmaz, Cetin Toraman

Subjects: “…Emergency remote learning…”
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Analyzing the influence of principals' instructional leadership, teachers' attitudes toward change, and schools' collaborative learning cultures on educational reform in learning by Ying Hu, Ibrahim Duyar

Subjects: “…collaborative learning culture…”
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Exploring peer learning module vs. conventional tutorials: effects on engagement and learning outcomes among first-year medical students by Vinay Arasappa Vishwanath, Sindhu Raghuramaiah, Kavita Rasalkar

Subjects: “…Peer-learning…”
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Bayesian reinforcement learning models reveal how great-tailed grackles improve their behavioral flexibility in serial reversal learning experiments by Lukas, Dieter, McCune, Kelsey, Blaisdell, Aaron, Johnson-Ulrich, Zoe, MacPherson, Maggie, Seitz, Benjamin, Sevchik, August, Logan, Corina

Subjects: “…Behavioral flexibility, comparative cognition, grackle, innovativeness, multi-access box, problem solving, reversal learning…”
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DIGIEDU: Learning Project with Digital Based to Overcome Learning Lost Post Covid-19 Pandemic in Social Science Education Department by Rosmiati Rosmiati, Ahmad Nasori, Nurmala Sari, Iwan Putra, Novia Sri Dwijayanti

Subjects: “…learning lost…”
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Social Learning in Bumblebees (Bombus impatiens): Worker Bumblebees Learn to Manipulate and Forage at Artificial Flowers by Observation and Communication within the Colony by Hamida B. Mirwan, Peter G. Kevan

“…Social learning occurs when one individual learns from another, mainly conspecific, often by observation, imitation, or communication. …”
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Prediction of case types from non-searchable pdf documents in arabic: Comparison of machine learning and deep learning with image processing by El Arrasse Mouad, Khourdifi Youness, Mounir Soufyane, El Alami Alae

Subjects: “…machine learning…”
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Lessons Learned Developing and Using a Machine Learning Model to Automatically Transcribe 2.3 Million Handwritten Occupation Codes by Bjørn-Richard Pedersen, Einar Holsbø, Trygve Andersen, Nikita Shvetsov, Johan Ravn, Hilde Leikny Sommerseth, Lars Ailo Bongo

Subjects: “…Machine learning…”
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