Machine learning message-passing for the scalable decoding of QLDPC codes by Arshpreet Singh Maan, Alexandru Paler

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Sociolinguistic Epistemology and Its Implications in Learning Indonesian Language at School by Novita Asmi Sihombing, Sofyan Sauri

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Application of the Method of Problem Learning in the Study of the Discipline “Information Security” by V. A. Sizov, D. M. Malinichev, Kh. K. Kuchmezov, V. V. Mochalov

“…The paper considers the practical task of creating and resolving a problem situation for the protection of information in state information systems with terminal access devices, which can be used in the educational process to solve similar tasks by the method of problem learning.The creation of a problematic situation is based on the existing contradictions in the regulations governing the functioning and protection of information of this type of systems in which the protected information is processed in order to comply with legislation and ensure the functioning of authorities. …”
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Controlling nonergodicity in quantum many-body systems by reinforcement learning by Li-Li Ye, Ying-Cheng Lai

“…We develop a model-free and deep reinforcement-learning (DRL) framework for quantum nonergodicity control. …”
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Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

“…In this work, we optimise a transfer learning approach for predicting the Remaining Useful Life (RUL) of ball bearings, particularly in scenarios with limited data availability. …”
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Multi-wavelength optical information processing with deep reinforcement learning by Qiuquan Yan, Hao Ouyang, Zilong Tao, Meili Shen, Shiyin Du, Jun Zhang, Hengzhu Liu, Hao Hao, Tian Jiang

“…To mitigate these issues, this study introduces a deep reinforcement learning calibration (DRC) method inspired by the deep deterministic policy gradient training strategy. …”
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The dengue-specific immune response and antibody identification with machine learning by Eriberto Noel Natali, Alexander Horst, Patrick Meier, Victor Greiff, Mario Nuvolone, Lmar Marie Babrak, Katja Fink, Enkelejda Miho

“…Antibody expression and functional assays have validated the obtained results.…”
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Mobile EEG in Education & Language Learning: A Scoping Review by Jincai Yang, Craig Neville, Máire Ní Riordáin

“…The review explores trends in mEEG technology, its use across disciplines, and its potential for understanding cognitive functions such as attention, memory, and cognitive load. …”
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Hybrid solver with deep learning for transport problem in porous media by Vladislav Trifonov, Egor Illarionov, Anton Voskresenskii, Musheg Petrosyants, Klemens Katterbauer

“…Abstract In this work, a hybrid solver with deep learning is proposed for numerical modeling of fluid flow in porous media. …”
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Melting simulations of high-entropy carbonitrides by deep learning potentials by Viktor S. Baidyshev, Christian Tantardini, Alexander G. Kvashnin

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Constructing multicomponent cluster expansions with machine-learning and chemical embedding by Yann L. Müller, Anirudh Raju Natarajan

“…The eCE model simultaneously learns a low dimensional embedding of site basis functions along with the weights of an energy model. …”
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Proper Nouns in Context of Arabic as a Foreign Language Learning by Yu. S. Chernykh, O. V. Makarova

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Implementation of the Drill Method in Learning Arabic with a Communicative Approach by Muhammad Zikran Adam, Laily Fitriani

“…The study identifies four supporting factors for the method's application: student participation, cognitive abilities, clarity of instruction, and availability of learning facilities. This study provides valuable insights and knowledge to improve Arabic language teaching for teachers and researchers to develop additional learning on more functional skills.…”
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Machine Learning in E-Commerce: Trends, Applications, and Future Challenges by Elias Dritsas, Maria Trigka

“…The rapid evolution of e-commerce has been significantly influenced by the integration of machine learning (ML) and data science techniques. The present survey provides a comprehensive overview of how ML methods are applied across various functional domains in e-commerce, including personalized recommendations, dynamic pricing, fraud detection, customer segmentation, and behavioral analysis. …”
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Improving Data Cleaning by Learning From Unstructured Textual Data by Rihem Nasfi, Guy de Tre, Antoon Bronselaer

“…The study involves training a machine learning model with instances that satisfy the dataset constraints (such as functional dependencies), and examining its impact on efficiency in repairing dirty data. …”
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Benchmarking machine learning models for predicting lithium ion migration by Artem D. Dembitskiy, Innokentiy S. Humonen, Roman A. Eremin, Dmitry A. Aksyonov, Stanislav S. Fedotov, Semen A. Budennyy

“…Abstract The development of fast ionic conductors to improve the performance of electrochemical devices relies on expensive high-throughput (HT) density functional theory (DFT) calculations of transport properties. …”
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Changes caused by fatherhood as a source of the need for lifelong learning by Zorica B. Milošević, Petar D. Živojinović

“…The beginning and development of parenting education and educational programs for parents are primarily associated with mothers, their role in the functioning of the family and the upbringing of children. …”
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FORMATION OF THE AXIOLOGICAL SPACE OF PERSONALITY IN THE PROCESS OF LEARNING THE UKRAINIAN LANGUAGE by Oleksandra Glazova, Natalia Dyka

“…The article highlights the peculiarities of the formation of the axiological space of the individual in the process of learning the Ukrainian language. Scientific works on the coverage of the outlined problem in them are analyzed. …”

Bidirectional information flow in cooperative learning reflects emergent leadership by Yuanyuan Li, Ya-jie Wang, Chang Su, Fang Deng, Yafeng Pan

“…However, the directionality of this synchronization, and the role of emergent leadership (i.e., a group leader emerges naturally), in cooperative learning remain unclear. Here, we investigated the directionality and dynamics of information flow by leveraging functional near-infrared spectroscopy (fNIRS) hyperscanning and Granger causality analysis (GCA). …”
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The ubiquity of selective attention in the processing of feedback during category learning. by Katerina Dolguikh, Tyrus Tracey, Mark R Blair

“…At the broadest level, these three findings reveal that selective attention is ubiquitous throughout the entire category learning task, functioning to emphasize the importance of certain stimulus features, the helpfulness of extra stimulus encoding during times of uncertainty, and the superfluousness of feedback once one has learned the task. …”
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