An evaluation framework and comparative analysis of the widely used learning management systems. by Adnan Abid, Abdullah Hassan Tufail, Osama Mohamed Ahmed Salem, Naeem A Nawaz, Uzma Farooq, Irfan Abid, Kashif Ishaq

“…Learning Management System (LMS) is a major tool used in most universities and institutions for online/distance education purposes. …”
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A Nonlinear Deep Learning Model for Oxygen Content of Flue Gas by TANG Zhenhao, LI Yanyan, CAO Shengxian

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The Detachment of Function and the Return to Essence: Exploring the Public’s Emotional Attitudes Towards Gamified Education by Liwei Ding, Hongfeng Zhang, Tuxian Zuo

“…This study aims to explore the public’s emotional attitudes toward gamified education, particularly analyzing the phenomenon of detachment and return regarding its educational function and essence. Through sentiment analysis and LDA topic modeling, three main themes were identified: the gamification and effectiveness of language learning, programmatic learning under temporal and spatial flexibility, and interactive entertainment and social learning. …”
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Examining the Impact of Variations in Executive Functions on Students’ Problem-Solving Behaviors by Tongxi Liu

“…Students’ diverse cognitive functions play a pivotal role in shaping their problem-solving behaviors, emphasizing the need to identify and cultivate these abilities to enhance learning outcomes in STEM education. …”
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Optimizing Pretrained Autonomous Driving Models Using Deep Reinforcement Learning by Vasileios Kochliaridis, Ioannis Vlahavas

“…However, fine-tuning with DRL can lead to the Catastrophic Forgetting (CF) problem, where a policy forgets the expert behaviors learned from the demonstrations as it learns to optimize the new reward function. …”
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An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis by Syed Saad Azhar Ali, Muhammad Moinuddin, Kamran Raza, Syed Hasan Adil

“…In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. …”
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Online Learning Discriminative Dictionary with Label Information for Robust Object Tracking by Baojie Fan, Yingkui Du, Yang Cong

“…This is accomplished by adding an ideal-code regularization term and classification error term to the total objective function. By minimizing the total objective function, we learn the high quality dictionary and optimal linear multiclassifier jointly using iterative reweighed least squares algorithm. …”
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Online Attentive Kernel-Based Off-Policy Temporal Difference Learning by Shangdong Yang, Shuaiqiang Zhang, Xingguo Chen

“…Temporal difference (TD) learning is a powerful framework for value function approximation in reinforcement learning. …”
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Comparative Analysis of Time Series Prediction Algorithms on Multiple Network Function Data of NWDAF by Dasheng Chen, Qi Song, Yinbin Zhang, Ling Li, Zhiming Yang

“…In comparison to 4G technology, 5G technology brings forth a host of new features, one of which is the network data analytics function (NWDAF). This function grants network operators the flexibility to either employ their own data analytics methodologies based on machine learning (ML) and deep learning (DL) into their networks. …”
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Deep learning with Bayesian Hyperparameter Optimization for Precise Electrocardiogram Signals Delineation by Annisa Darmawahyuni, Winda Kurnia Sari, Nurul Afifah, Siti Nurmaini, Jordan Marcelino, Rendy Isdwanta

“…The used hyperparameters of BHO contain learning rate, batch size, epoch, and total of long short-term memory layers. …”
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Voltage Control Based on Multi-Agent Safe Deep Reinforcement Learning by Yi ZENG, Yi ZHOU, Jixiang LU, Liangcai ZHOU, Ningkai TANG, Hong LI

“…A safety layer is introduced in the deep policy network for agent design, while the voltage barrier function based on traditional optimization model voltage constraints is used in defining the agent reward function. …”
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Prediction and analysis of toxic and side effects of tigecycline based on deep learning by Yin Xiong, Guoxin Liu, Xin Tang, Boyang Xia, Yalian Yu, Guangjun Fan

“…The potential correlation between the toxic and side effects of tigecycline and the number of hospitalization days was preliminarily discussed, and the correlation analysis between the number of hospitalization days and continuous variables was established. Finally, the deep learning model was used to predict the hospitalization days of patients through simulated blood drug concentration and clinical laboratory indicators.ResultsThe degree of abnormal liver function was significantly correlated with AST, GGT, MCHC and hospitalization days. …”
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Evolving Stencils for Typefaces: Combining Machine Learning, User’s Preferences and Novelty by Tiago Martins, João Correia, Ernesto Costa, Penousal Machado

“…The second module, the fitness function design interface, enables the users to create fitness functions through a responsive graphical interface, by indicating the desired values and weights of a set of behavioural features, based on machine learning approaches, and morphological features. …”
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Visual Positioning Detection of EMU Brake Pad Based on Deep Learning by GUAN Chunling, XU Yingjie, SONG Yuechao

“…［Method］A visual positioning detection method for EMU brake pads based on deep learning is proposed. To address the issue of indistinct image features in real-world scenarios, based on the Faster R-CNN (region conventional neural network) algorithm, an edge detection branch is introduced, and a target edge loss function is added to the loss function, integrating edge information from an auxiliary network. …”
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Machine learning for detection of equivariant finite symmetry groups in dynamical systems by Pablo Calvo-Barlés, Sergio G Rodrigo, Luis Martín-Moreno

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Secondary Frequency Control of Islanded Microgrid Based on Deep Reinforcement Learning by Li WANG, Yuxiang JIANG, Xiangjun ZENG, Bin ZHAO, Junhao LI

“…An offline learning process is used to train the deep reinforcement learning-based secondary frequency controller. …”
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Using deep learning to capture gravel soil microstructure and hydraulic characteristics by Bin Zhu, Yu-Fei Xie, Xiang-Gang Hu, Dai-Rong Su

“…The results demonstrated a high consistency between the reconstructed model of gravel soil realizations and the original samples in terms of porosity, two-point correlation function, linear path function, specific surface, and Euler characteristics number. …”
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The Hygienic Estimation of Influence of Training Sessions Using Electronic Tablet on Functional State of Students by V. R. Kuchma, M. I. Stepanova, Z. I. Sazanyuk, M. A. Polenova, I. E. Aleksandrova, N. O. Berezina, A. Yu. Makarova

“…The purpose of the research was to study the infl uence of Tablet PC e-learning in secondary school on the functional state of the students. …”
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SUPERMAGOv2: Protein Function Prediction via Transformer Embeddings and Bitscore-Weighted Features by Gabriel Bianchin de Oliveira, Helio Pedrini, Zanoni Dias

“…To address this challenge, computational approaches based solely on amino acid sequence features have been developed to improve functional predictions. In this study, we introduce two novel approaches, one based on machine learning and another using an ensemble of machine learning with local alignment. …”
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THE THEORY OF FUNCTIONAL SYSTEMS AS A BASIS OF MEDICAL STUDENTS’ WORLD VIEW SYSTEM FORMATION by K. V. Sudakov, V. V. Andrianov

“…The article is devoted for using of the theory of functional system in teaсhing process and principle of the systemoquant organization of the normal physiology course for medical students. …”
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