An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…The proposed motion cueing algorithm (MCA), based on a reinforcement learning algorithm using gradient information to directly update the control policy, introduces three significant enhancements. …”
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Multimodal Fusion Framework for Urban functional zone change detection using Remote Sensing and Social Sensing Data by B. Fang, B. Fang, B. Fang, B. Fang, X. Chen, X. Chen, X. Chen, X. Chen, H. Chen, H. Chen, Z. Xiang, Z. Xiang, B. Hu, B. Hu, Z. Hu, Z. Hu, Z. Hu, Z. Hu, W. Tu, W. Tu, W. Tu, W. Tu

“…Previous studies have focused primarily on single-modal data like high-resolution remote sensing (RS) imagery, overlooking the role of social sensing characteristics in determining urban functional zones (UFZs). In this study, we propose a novel multimodal dual-branch change detection (MDB-CD) deep learning framework, for detecting UFZ changes by combining RS imagery and social sensing data. …”
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Moderate regular physical exercise can help in alleviating the systemic impact of schistosomiasis infection on brain cognitive function by Inssaf Berkiks, Inssaf Berkiks, Nada Abdel Aziz, Nada Abdel Aziz, Nada Abdel Aziz, Blessing Moses, Blessing Moses, Tiroyaone Brombacher, Tiroyaone Brombacher, Frank Brombacher, Frank Brombacher

“…Our findings unveiled that while acute infection did not disrupt simple and complex learning or spatial reference memory, it did induce significant deficits in recall memory—a critical aspect of cognitive function. …”
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Result aggregation algorithm based on differential evolution and Top-k ranking in learning Worker’s weight by Yuping XING, Yongzhao ZHAN

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Explainable AI and deep learning models for recommender systems: State of the art and challenges by Maroua Benleulmi, Ibtissem Gasmi, Nabiha Azizi, Nilanjan Dey

“…Recommender systems have a pivotal function in delivering customized and pertinent suggestions to clients on the basis of their preferences and activities. …”
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Aprender haciendo: paideia y phronesis en Aristóteles = Learning by doing: paideia and phronesis in Aristóteles by Marcos, Alfredo

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Design of English Mobile Learning Platform Based on GSM-R Wireless Network Communication System by Xiaowei Liu, Hongjin Liu

“…Because the traditional English mobile learning platform has low student satisfaction and a long learning time, an English mobile learning platform based on the GSM-R wireless network communication system is designed. …”
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Explicit Form of Solutions of Second-Order Delayed Difference Equations: Application to Iterative Learning Control by Nazim I. Mahmudov, Muath Awadalla, Meraa Arab

“…The closed form of its solution is derived by means of a newly defined delayed matrix sine/cosine using the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="script">Z</mi></semantics></math></inline-formula> transform and determining function. This representation helps with analyzing iterative learning control by applying appropriate updating laws and ensuring sufficient conditions for achieving asymptotic convergence in tracking.…”
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Modeling Analysis of the Relationship between Adolescent Aerobic Exercise and Obesity Reduction Based on Deep Learning by Peng Mu

“…In order to explore the modeling analysis of the relationship between adolescent aerobic exercise and obesity reduction, the relationship modeling method of deep learning algorithm is proposed. This study integrates deep learning algorithms and first uses the changes in body shape, weight, BMI index, body fat, body circumference, and other indicators of adolescent obese before and after aerobic exercise as the initial pheromone distribution matrix and introduces random evolution factor and evolutionary drift threshold to establish the objective function of aerobic exercise to reduce adolescent obesity. …”
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Mammalian piRNA target prediction using a hierarchical attention model by Tianjiao Zhang, Liang Chen, Haibin Zhu, Garry Wong

“…Despite their significant role in regulating cellular RNA levels, the piRNA targeting rules are not well defined, especially in mammals, which poses obstacles to the elucidation of piRNA function. Results Given the complexity and current limitation in understanding the mammalian piRNA targeting rules, we designed a deep learning model by selecting appropriate deep learning sub-networks based on the targeting patterns of piRNA inferred from previous experiments. …”
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Research on gut microbiota characteristics of PBC patients at different ALBI grades based on machine learning by Han Shi, Qi Wang, Qi Wang, Qi Wang, Bin Xu, Yanmin Liu, Juan Zhao, Xue Yang, Chunyang Huang, Ronghua Jin, Ronghua Jin, Ronghua Jin, Ronghua Jin

“…We analyzed alpha diversity, beta diversity, LEfSe analysis and pathway function prediction. Additionally, various machine learning methods—including random forest (RF), lasso, gradient boosting machine (GBM) and support vector machine (SVM)—were employed to identify key features and to build and validate predictive models using bootstrap techniques.ResultsClinical characteristics of ALBI grade 1 patients were comparatively better than those of ALBI grade 2 and 3 patients, including multiple laboratory indices. …”
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A Deep Reinforcement Learning-Based Cooperative Guidance Strategy Under Uncontrollable Velocity Conditions by Hao Cui, Ke Zhang, Minghu Tan, Jingyu Wang

“…A heuristically reshaped reward function is designed to enhance cooperative guidance among agents, enabling effective target engagement while mitigating the low learning efficiency caused by sparse reward signals in the guidance environment. …”
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Digital teachers and parallel education: A paradigm shift in teaching and learning after ChatGPT by WANG Fei-Yue

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Harnessing Machine Learning for Diabetes Prediction: Optimizing Classifiers to Tackle Canada's Growing Health Challenge by Mark Gerald Anastacio, Alam Md Twariqul

“…Therefore, based on tree-based, function-based techniques, and rule-based models, the study seeks to establish the best and most understandable model for early diabetes prediction. …”
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Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization. by Honghua Liu, Mingwei Zhao, Chang She, Han Peng, Mailan Liu, Bo Li

“…Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. …”
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Classification of heart diseases using time-frequency representations of electrocardiogram signals by transfer learning networks by Amir Hossein Jalalzadeh, Hamid Ebrahimi, Maryam Jahangiri Moghadam

“… It is crucial to monitor and diagnose cardiac function early to prevent the development of future, more severe issues. …”
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Full-dimensional dynamic convolution and progressive learning strategy for strawberry recognition based on YOLOv8 by Liping Bai, Chenglei Xia, Fei Liu, Xing Yang, Tai Zhang

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Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome by Jia-Wei Tang, Alfred Chin Yen Tay, Liang Wang

“…In this study, 16S rRNA sequencing data from stool samples of 233 patients were thoroughly collected. Machine learning (ML) and Shapley Additive exPlanations (SHAP) interpretability algorithms were applied to identify core taxa and predict the metabolic functions. …”
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Application of Immunological and Swarm Intelligence Learning-Based Algorithm for Industrial Grade Computer Sales Prediction by Zhen-Yao Chen

“…This paper strives to raise the imitating effectiveness of radial basis function-based neural network (RNNet) through biological learning (BL) and swarm intelligence (SI) optimization algorithms. …”
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Classification and Detection of Rumors Related to COVID-19 Using Machine Learning-Based Smart Techniques by Yancheng Yang, Junqiao Zhai, Shah Nazir

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