Effects of Transcranial Alternating Current Stimulation on Cognitive Functions in Healthy Young and Older Adults by Daria Antonenko, Miriam Faxel, Ulrike Grittner, Michal Lavidor, Agnes Flöel

“…Linear mixed models revealed significantly increased retrieval accuracy following tACS-accompanied associative learning, after controlling for session order and learning success. …”
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JC Polyomavirus-Associated Nephropathy Case Report: Clinical and Laboratory Learning by Rachael M. Tomb, Siobhan K. McManus, David Kipgen, Sawsan Yaqub, Sally Taylor, Rory N. Gunson

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Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

“…Based on the recognition outcomes of mineral rock block size images, the “S” shaped cumulative distribution pattern of block size was discovered, and the Pearson curve function was fitted. And a segmented function R-R block size distribution correction model was proposed, which can better characterize the characteristics of blasting block size distribution and serves as a guide for accurate prediction of block size distribution. …”
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Determination of cervical vertebral maturation using machine learning in lateral cephalograms by Shahab Kavousinejad, Asghar Ebadifar, Azita Tehranchi, Farzan Zakermashhadi, Kazem Dalaie

“…This study aimed to develop a semi-automated approach using machine learning based on cervical vertebral dimensions (CVD) for determining skeletal maturation status. …”
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A new method for reconstructing building model using machine learning by Shengjie Wu, Haibo Ye, Antao Li, Huawei Tu, Shenxin Xu, Dong Liang

“…Therefore, this study attempts to train a neural network to fit a five-dimensional (5D) function. The input to this function is a 5D vector, including the position (x, y, z) and viewing direction (θ, φ), and the output is the color and density of this point when viewed from this direction. …”
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Functions of Teacher and Student Code-Switching in an EFL Classroom and Pedagogical Focus: Observations and Implications by Stefan Rathert

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Application of Deep Learning Techniques in Uranium Microparticle Fission Track Detection by ZHAO Xiong, REN Fangda, SHEN Yan

“…It is found that the integrated network alters the performance of the loss functions, with the DIOU loss function being most compatible with the YOLOv5-ST network. …”
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Le projet européen Romtels (Roma translanguaging enquiry learning spaces) by Nathalie Auger, Brahim Azaoui, Christel Houée, Frédéric Miquel

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Identity-based fully homomorphic encryption from learning with error problem by Yan GUANG, Yue-fei ZHU, Jin-long FEI, Chun-xiang GU, Yong-hui ZHENG

“…The security of the proposed scheme reduces to the hard-ness of learning with errors problem and the one-wayness of trapdoor function in the random oracle model.…”
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Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression by Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou

“…This loss function is motivated by the ϵ-insensitive loss for support vector regression and the pinball loss for quantile regression. …”
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Truth, beauty, and goodness in grand unification: A machine learning approach by Shinsuke Kawai, Nobuchika Okada

“…We compare these two approaches by numerically optimising a loss function, defined as the ratio of determinants of mass matrices. …”
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Adaptive Iterative Learning Control of Hybrid Drive Cable Parallel Manipulator by Jianbin Cao, Mingsheng Wei, Haixiao Zhao

“…By means of Lyapunvo function， the stability of the controller is proved. …”
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DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…Cardiac MRI allows medical practitioners to assess cardiac function accurately by providing comprehensive and quantitative information about the structure and function, hence making it an indispensable tool for monitoring the disease and treatment response. …”
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Performance Analysis of a Wind Turbine Pitch Neurocontroller with Unsupervised Learning by J. Enrique Sierra-García, Matilde Santos

“…The controller is based on a radial basis function (RBF) network with unsupervised learning algorithm. …”
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Design and implementation of an ERP platform as practice environment for learning in Operations Management by Juan Manuel Maqueira Marín, José Moyano Fuentes, Sebastián Bruque Cámara, Pedro Nuñez-Cacho Utrilla

“…Given the increasing business use of Enterprise Resource Planning (ERP) software, it is necessary to have such platforms for application in the teaching-learning process in Operations Management. However, the implementation of commercial solutions is not adequate due to its high cost and to exceed the conceptual learning function, which is the main objective of this software tool with the students of Operations Management. …”
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Classification algorithm of loin swarm optimization kernel extreme learning machine by Liu Xinjian, Sun Zhonghua

“…The test accuracy is taken as the fitness function of LSO to optimize KELM, and the evaluation standard for data classification test is obtained according to the mobile position to obtain the optimal fitness value. …”
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A Kernel Based Neighborhood Discriminant Submanifold Learning for Pattern Classification by Xu Zhao

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Smart Sampling: Self-Attention and Bootstrapping for Improved Ensembled Q-Learning by Muhammad Junaid Khan, Syed Hammad Ahmed, Gita Sukthankar

“…We present a novel method aimed at enhancing the sample efficiency of ensemble Q learning. Our proposed approach integrates multi-head self-attention into the ensembled Q networks while bootstrapping the state-action pairs ingested by the ensemble. …”
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End-to-End Learning of Constellation Shaping for Optical Fiber Communication Systems by Wenshan Jiang, Xue Zhao, Fangfang Huang, Xiatao Huang, Taowei Jin, Hong Lin, Jing Zhang, Kun Qiu

“…End-to-end learning based on autoencoder can realize robust constellation shaping for optical fiber communications. …”
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Visual didactic regulators as instruments of learning activity: Development and applied aspects by V. E. Steinberg, N. N. Manko, L. V. Vakhidova, D. R. Fatkhulova

“…The hypothesis assumes the expediency of the development of conceptual and graphic means of visualisation in the form of visual didactic regulations, which are the subject of research.The present research aims: to discuss the problem of the creation of didactic regulations for educational activities; to study the development of conceptual-graphic means of visibility and factors for improving their functionality; to forecast the development of this type of means based on the visualisation of the logical-semantic modelling of knowledge; to clarify terminology and applied aspects; and to conduct experimental approbation in the conditions of distance learning.Methodology and research methods. …”
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