Development of an autonomous chess robot system using computer vision and deep learning by Truong Duc Phuc, Bui Cao Son

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Positional embeddings and zero-shot learning using BERT for molecular-property prediction by Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, Kyuri Jo, Young-Seob Jeong

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The learning curve for laparoscopic-assisted single-port mediastinoscopic esophagectomy: an analysis of proficiency by Wenhao Li, Xiangfeng Gan, Liangzhan Lv, Yingmeng Wu, Weizhao Huang, Yi Liang, Qingdong Cao

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Personalising Learning: Do Teachers Use Student Voice and Choice at Secondary School? by Mikhail N. Shchevliagin, Diana O. Koroleva

Subjects: “…personalised learning…”
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Evaluating the Transformative Impact of Online Education on Medical Student Learning Outcomes [Letter] by Benhissoune A, Abdulqadir A, Shah H

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Predicting Course Grade through Comprehensive Modelling of Students’ Learning Behavioral Pattern by Danial Hooshyar, Yeongwook Yang

“…This study aims to model students’ online learning behavior and accordingly predict their course achievement. …”
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Bearing Fault Classification Using Improved Antlion Optimizer and Extreme Learning Machine by Zhuanzhe Zhao, Yu Zhang, Qiang Ma, Yujian Rui, Guowen Ye, Mengxian Wang, Yongming Liu, Zhen Zhang, Neng Wei, Zhijian Tu

“…Secondly, in order to solve the disadvantage that extreme learning machine (ELM) network is easy to fall into local optimization, this ELALO algorithm is used to initialize the weights and thresholds of its network and to form the new pattern recognition model, ELALO-ELM. …”
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Motor Learning Deficits in a Neonatal Mouse Model of Hypoxic-Ischemic Injury by Maria Marlicz, Weronika Matysik, Emily Zucker, Sarah Lee, Hannah Mulhern, Jennifer Burnsed

“…At p30, we assessed complex motor performance and learning using the accelerating rotarod and complex running wheel tasks. …”
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On learning molecular biology in François Gros’ lab in the late 1970s and early 1980s by Minty, Adrian

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UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification by Zeyu Ren, Xiangyu Kong, Yudong Zhang, Shuihua Wang

Subjects: “…Deep learning…”
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A survey of MRI-based brain tissue segmentation using deep learning by Liang Wu, Shirui Wang, Jun Liu, Lixia Hou, Na Li, Fei Su, Xi Yang, Weizhao Lu, Jianfeng Qiu, Ming Zhang, Li Song

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Development and experimental validation of a machine learning model for the prediction of new antimalarials by Mukul Kore, Dimple Acharya, Lakshya Sharma, Shruthi Sridhar Vembar, Sandeep Sundriyal

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Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks by Thomas Nowotny, James P Turner, James C Knight

“…Event-based machine learning promises more energy-efficient AI on future neuromorphic hardware. …”
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Innovative Arabic Language Learning: Redefining Language Archetypes Using Artificial Intelligence by Hadid Asfar, Ilya Husna, Yasmadi Yasmadi, Ashabul Khairi, Karmila Suryani, Al Ikhlas, Ade Sri Madona

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Retracted: Machine Learning and Artificial Intelligence in the Food Industry: A Sustainable Approach by Journal of Food Quality

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Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning by Hsuan-Ta Lin, Po-Ming Lee, Tzu-Chien Hsiao

“…Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students’ learning gains. …”
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Method of Evaluating and Predicting Traffic State of Highway Network Based on Deep Learning by Jiayu Liu, Xingju Wang, Yanting Li, Xuejian Kang, Lu Gao

“…The accurate evaluation and prediction of highway network traffic state can provide effective information for travelers and traffic managers. Based on the deep learning theory, this paper proposes an evaluation and prediction model of highway network traffic state, which consists of a Fuzzy C-means (FCM) algorithm-based traffic state partition model, a Long Short-Term Memory (LSTM) algorithm-based traffic state prediction model, and a K-Means algorithm-based traffic state discriminant model. …”
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The Elite Paradigm Driving Australian Aid Policy: Learning to Live With the ‘Cautious Consensus’ by Benjamin Day, Tamas Wells

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Exploring the relationship between learning emotion and cognitive behaviors in a digital game by Li Chen, Zehui Zhan, Han Chen, Linlin Zheng

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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…<h4>Results</h4>The logistic regression model emerged as the optimal model for predicting recurrence of NPM with machine learning, primarily utilizing three variables: FIB, bacterial infection, and CD4+ T cell count. …”
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