Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm by Taninnuch Lamjiak, Booncharoen Sirinaovakul, Siriwan Kornthongnimit, Jumpol Polvichai, Aysha Sohail

“…Artificial neural networks (ANNs) are widely used machine learning techniques with applications in various fields. …”
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Unlocking Deep Learning: How Self-Regulated Learning Shapes Chinese Students’ Online Course Experiences by Lingli Li, Shuqing Chen, Pingping Tang, Kai Lv, Ping Li, Yunying Xu

“…Using a quantitative, cross-sectional paradigm, this study sought to analyze the link between university students perceived online course experiences and deep learning, with an emphasis on the mediating function of self-regulation through the adapted instruments of the Online Course Experience Questionnaire, Self-regulated Learning Questionnaire , and Deep Learning Scale . …”
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Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…This suggests that using Federated Learning along with MLP and LSTM as the components of this vector enhanced the function increasing its capacity and reliability in predicting the trends of stocks. …”
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Efficient optimal power flow learning: A deep reinforcement learning with physics-driven critic model by Ahmed Sayed, Khaled Al Jaafari, Xian Zhang, Hatem Zeineldin, Ahmed Al-Durra, Guibin Wang, Ehab Elsaadany

“…This approach enables accurate policy gradient computation through a differentiable loss function based on system states of realized uncertainties, simplifying both the replay buffer and the learning process. …”
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Analysing the Influence of Augmented Reality on Organization Performance via Supply and Logistics Value Chain Functions: A Hybrid ANN-PLS Model Assessment in the Gulf Cooperation C... by Ahmad Aburayya

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Investigation of brain response to acquisition and learning the second languages based on EEG signals and machine learning techniques by Talal A. Aldhaheri, Sonali B. Kulkarni, Pratibha R. Bhise, Baraq Ghaleb

“…While studies have examined brain activity during language learning, there’s a need for validated data on cognitive and functional effects of acquiring new languages, especially Arabic and Hindi. …”
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Problems in Mathematics Learning Multiple Materials Viewed From Low-Grade Students' Learning Interest Aspect by Maya Marini, Ahmad Ilham Asmaryadi, Ratnawati Ratnawati

“…The results showed that the problems in learning mathematics multiplication material can be seen from several factors, one of which is the student's interest in learning, which can be seen from the indicators of student interest in learning, namely, students' feelings of pleasure, attention in learning, lesson materials and teacher attitudes. interesting, the benefits and functions of the subjects. …”
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Unlocking the Learning Potential: ChatGPT as a Virtual Platform for Cross-Interaction in English Language Learning by Wen-Chi Hu, Radovan Škultéty

“…We explored how participants learning English as a foreign language (EFL) perceive the use of ChatGPT for English communication in combination with voice control for GPT, a Google Chrome extension, both of which are AI chatbot functionalities. …”
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Exploring Machine Learning and Deep Learning Approaches for Battery Management Systems in EVs: A Comprehensive Review by Sathish J., Ramash Kumar K., Saraswathi D.

“…This article aims to highlight the pivotal role of artificial intelligence (AI) and deep learning in improving the functionality of the BMS, ultimately contributing to the performance and longevity of EVs.…”
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An Analysis of Students’ Experience in Using English Learning Application “myON” in Helping Students’ English Learning Process by Fasya Putri Radhiyya, Nazwa Aulia, Syifa Shabrina, Hairunnisa Aulia Putri, Bambang Nur Alamsyah Lubis

“…These learning approaches are monotonous. Given the progress of technology and the internet, it is necessary for educators to utilize technology-driven online learning platforms, such as myON applications. …”
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Prediction of bladder cancer prognosis and immune microenvironment assessment using machine learning and deep learning models by Weihao Nie, Yiheng Jiang, Luhan Yao, Xinqing Zhu, Abdullah Y. AL-Danakh, Wenlong Liu, Qiwei Chen, Deyong Yang

“…In this study, we integrated 10 machine learning algorithms to develop an immune-related machine learning signature (IRMLS) and subsequently created a deep learning model to detect the IRMLS subtype based on pathological images. …”
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Combining handcrafted and learned features using deep learning to improve protein-protein interaction prediction performance by Tran Hoai Nhan, Nguyen Phuc Xuan Quynh, Le Anh Phuong

“…Understanding protein-protein interactions (PPIs) is essential because knowledge regarding PPIs helps in determining the biochemical functions of organisms. Advances made in machine learning techniques, for example, DeepFE-PPI, GcForest-PPI, and DeepPPI, have been applied to enhance PPI prediction performance. …”
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Mid-infrared spectra of dried and roasted cocoa (Theobroma cacao L.): A dataset for machine learning-based classification of cocoa varieties and prediction of theobromine and caffe... by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

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A New Paradigm in AC Drive Control: Data-Driven Control by Learning Through the High-Efficiency Data Set—Generalizations and Applications to a PMSM Drive Control System by Madalin Costin, Ion Bivol

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THE SOLUTION OF THE APPROXIMATION PROBLEM OF NONLINEAR DEPENDANCES USING ARTIFICIAL NEURAL NETWORKS by V. N. Ageyev

“…One of the problems in the development of the ANN is the choice of an appropriate activation function for neurons of the hidden layer and adjusting the parameters of the function in the learning process of the network. …”
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Interdisciplinary Distance Learning Workshop for IT Students by I. A. Andrianov, S. A. Rzheutskaya, M. V. Kharina

“…An additional useful function of the learning workshop as the means of developing English-language competence is presented.Conclusion. …”
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Learning neural operators on Riemannian manifolds by Chen Gengxiang, Liu Xu, Meng Qinglu, Chen Lu, Liu Changqing, Li Yingguang

“…Learning mappings between functions (operators) defined on complex computational domains is a common theoretical challenge in machine learning. …”
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Learning from low precision samples by Ji In Choi, Madeleine Georges, Jung Ah Shin, Olivia Wang, Tiffany Zhu, Tapan Shah

“…A simple, effective method is to learn machine learning models from quantized data stored with low arithmetic precision (1-8 bits). …”
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Learning epigenetic regulation from mycobacteria by Sanjeev Khosla, Garima Sharma, Imtiyaz Yaseen

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Learning in General Games with Nature’s Moves by Patrick L. Leoni

“…Players have a utility function over infinite histories that are continuous for the sup-norm topology. …”
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