Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain by Ming YANG, Xuexian HU, Qihui ZHANG, Jianghong WEI, Wenfen LIU

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Insulin signaling and dietary restriction differentially influence the decline of learning and memory with age. by Amanda L Kauffman, Jasmine M Ashraf, M Ryan Corces-Zimmerman, Jessica N Landis, Coleen T Murphy

“…While conditions that increase longevity have been identified, the effects of these longevity-promoting factors on learning and memory are unknown. Here we show that the C. elegans Insulin/IGF-1 receptor mutant daf-2 improves memory performance early in adulthood and maintains learning ability better with age but, surprisingly, demonstrates no extension in long-term memory with age. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

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Retracted: Deep-Learning-Based 3D Reconstruction: A Review and Applications by Applied Bionics and Biomechanics

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Reinforcement Learning-Based Adaptive Control of a Piezo-Driven Nanopositioning System by Liheng Chen, Qingsong Xu

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Supporting complex skill learning with digital tools in tertiary education: educator’s perspective by Bernarda Letnar, André Klostermann, Mirko Schmidt

Subjects: “…complex skill learning…”
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Deep learning-assisted arrhythmia classification using 2-D ECG spectrograms by Pinjala N Malleswari, Venkata krishna Odugu, T. J. V. Subrahmanyeswara Rao, T. V. N. L. Aswini

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A Credit Card Fraud Detection Algorithm Based on SDT and Federated Learning by Yuxuan Tang, Zhanjun Liu

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THE CONCEPT OF WOMEN'S ATTIRE IN THE LEARN QUR'AN TAFSIR APPLICATION: AN EPISTEMOLOGICAL ANALYSIS OF INTERPRETATION by Nurul Istiqomah

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How and Where Did Students Learn Music in the Late Middle Ages and Renaissance? by Grantley McDonald

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Green city: An efficient task joint execution strategy for mobile micro-learning by Li Yang, Ruijuan Zheng, Junlong Zhu, Mingchuan Zhang, Ruoshui Liu, Qingtao Wu

“…Mobile micro-learning has received extensive attention in the research of smart cities because it is a novel fusion service mode of the mobile Internet, cloud computing, and micro-learning. …”
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Multi-Objective Dynamic Path Planning with Multi-Agent Deep Reinforcement Learning by Mengxue Tao, Qiang Li, Junxi Yu

Subjects: “…multi-agent reinforcement learning…”
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Cerberus: cross-site social bot detection system based on deep learning by TANG Jiawei, LIU Yushan, GAO Min, GONG Qingyuan, WANG Xin, CHEN Yang

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Machine learning and public health policy evaluation: research dynamics and prospects for challenges by Zhengyin Li, Hui Zhou, Zhen Xu, Qingyang Ma

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Edge computing smart grid resource scheduling algorithm based on reinforcement learning by Jinghang YU, Yichen ZHAO, Hu SONG

“…A smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virtual network embedding algorithms cannot dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem, edge computing and virtualization technology was combined and a virtual network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization.…”
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Assessment IS learning: developing a student‐centred approach for assessment in Higher Education by Stephen Rutherford, Connie Pritchard, Nigel Francis

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Time Effort Prediction Of Agile Software Development Using Machine Learning Techniques by Muchamad Bachram Shidiq, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…For this reason, this research aims to predict the time effort of agile software development using Machine Learning techniques, namely the Decision Tree, Random Forest, Gradient Boosting, and AdaBoost algorithms, as well as the use of feature selection in the form of RRelieff and Principal Component Analysis (PCA) to improve prediction accuracy. …”
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Contribution of cooperative learning strategies to the improvement of the quality of students' native language knowledge by Semiz Marina Ž., Antonijević Radovan M., Čutović Mirjana M.

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Design of transceivers based on sparse Bayesian learning for power line carrier communications by Xinrong LV, Youming LI, Mingchen YU

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A Machine-Learning-Based Classification Method for Meteorological Conditions of Ozone Pollution by Yang Cao, Xiaoli Zhao, Debin Su, Xiang Cheng, Hong Ren

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