Machine learning models and methods for solving optimization and forecasting problems of the work of seaports by M. N. Lukashevich, M. Y. Kovalyov

Subjects: “…machine learning…”
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Forecasting Foreign Exchange Volatility Using Deep Learning Autoencoder-LSTM Techniques by Gunho Jung, Sun-Yong Choi

“…Additionally, the ability to learn the magnitude of data spread and singularities determines the accuracy of predictions made using deep learning models. …”
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SEMdag: Fast learning of Directed Acyclic Graphs via node or layer ordering by Mario Grassi, Barbara Tarantino

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Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus by Dariusz Świetlik

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Prediction of Proton Pressure in the Outer Part of the Inner Magnetosphere Using Machine Learning by S. Y. Li, E. A. Kronberg, C. G. Mouikis, H. Luo, Y. S. Ge, A. M. Du

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Investigation on the thermal characteristics of electronic system and prediction of chip temperature by machine learning by Fanyu Wang, Dongwei Wang, Qiang Deng, Hao Yan, Qi Chen, Yang Zhao

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Learning Discrete-Time Uncertain Nonlinear Systems With Probabilistic Safety and Stability Constraints by Iman Salehi, Tyler Taplin, Ashwin P. Dani

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Parents’ Role in Supporting, Brokering or Impeding Their Children’s Connected Learning and Media Literacy by Livingstone Sonia, Blum-Ross Alicia

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Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients by Cheng Qu, Lin Gao, Xian-qiang Yu, Mei Wei, Guo-quan Fang, Jianing He, Long-xiang Cao, Lu Ke, Zhi-hui Tong, Wei-qin Li

“…In the study, machine learning (ML) techniques were used to establish predictive models for AKI in AP patients during hospitalization. …”
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PROJECT DESIGN OF LEARNING ACTIVITY CYCLE FROM THE PERSPECTIVE OF ACTIVITY AND COMPETENCE APPROACH by E. O. Pokhomchikova

Subjects: “…: learning activity cycle…”
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Exploring the Potential Imaging Biomarkers for Parkinson’s Disease Using Machine Learning Approach by Illia Mushta, Sulev Koks, Anton Popov, Oleksandr Lysenko

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Profiles of technology-rich learning activities for early literacy and teachers’ roles in Korea by Boram No

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Chemical Diversity of UK-Grown Tea Explored Using Metabolomics and Machine Learning by Amanda J. Lloyd, Alina Warren-Walker, Jasen Finch, Jo Harper, Kathryn Bennet, Alison Watson, Laura Lyons, Pilar Martinez Martin, Thomas Wilson, Manfred Beckmann

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Balancing Privacy and Utility in Split Learning: An Adversarial Channel Pruning-Based Approach by Afnan Alhindi, Saad Al-Ahmadi, Mohamed Maher Ben Ismail

Subjects: “…Adversarial learning…”
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Unlocking Potential Score Insights of Sentimental Analysis with a Deep Learning Revolutionizes by Ibrahim R. Alzahrani

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Personalized client-edge-cloud hierarchical federated learning in mobile edge computing by Chunmei Ma, Xiangqian Li, Baogui Huang, Guangshun Li, Fengyin Li

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Multi-channel learning for integrating structural hierarchies into context-dependent molecular representation by Yue Wan, Jialu Wu, Tingjun Hou, Chang-Yu Hsieh, Xiaowei Jia

“…They also struggle to learn the subtle variations in structure-activity relationship. …”
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Freedom of Expression: what lessons should we learn from US experience? by Ronaldo Porto Macedo Junior

“…This article advocates that Brazilian interpretation of freedom expression has a lot to learn from the US model and doctrine. The US more strict and conceptual jurisprudence on this issue offers a powerful and democratic alternative to the balancing model and represents a rich conceptual analysis still unknown by Brazilian courts.…”
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A novel explainable deep learning framework for reconstructing South Asian palaeomonsoons by K. M. R. Hunt, K. M. R. Hunt, S. P. Harrison

“…Our findings offer insights into the historical variability of the Indian summer monsoon and highlight the potential of deep learning techniques in palaeoclimate reconstruction.…”
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Applying Data Analysis and Machine Learning Methods to Predict Permafrost Coast Erosion by Daria Bogatova, Stanislav Ogorodov

“…This study aims to establish a scientific and methodological basis for predicting shoreline positions using modern data analysis and machine learning techniques. The focus area is a 5 km section of the Ural coast along Baydaratskaya Bay in the Kara Sea. …”
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