Flipbook and e-learning for teaching English to elementary school teacher education students by Herlina Usman, Ika Lestari, Yulia Elfrida Yanty Siregar, Syarifa Rafiqa Rafiqa, Izlan Sentryo

Subjects: “…e-learning…”
Get full text

Deployment method for vEPC virtualized network function via Q-learning by Quan YUAN, Hong-bo TANG, Kai-zhi HUANG, Xiao-lei WANG, Yu ZHAO

Get full text

A feature selection method based on instance learning and cooperative subset search by Xiaoyuan XU, Li HUANG

Get full text

Immersive Haptic Technology to Support English Language Learning Based on Metacognitive Strategies by Adriana Guanuche, Wilman Paucar, William Oñate, Gustavo Caiza

Subjects: “…English learning…”
Get full text

Digital twins as global learning health and disease models for preventive and personalized medicine by Xinxiu Li, Joseph Loscalzo, A. K. M. Firoj Mahmud, Dina Mansour Aly, Andrey Rzhetsky, Marinka Zitnik, Mikael Benson

“…However, widespread implementation faces several challenges: (1) characterizing dynamic molecular changes across multiple biological scales; (2) developing computational methods to integrate data into DTs; (3) prioritizing disease mechanisms and therapeutic targets; (4) creating interoperable DT systems that can learn from each other; (5) designing user-friendly interfaces for patients and clinicians; (6) scaling DT technology globally for equitable healthcare access; (7) addressing ethical, regulatory, and financial considerations. …”
Get full text

Selective learning for sensing using shift-invariant spectrally stable undersampled networks by Ankur Verma, Ayush Goyal, Sanjay Sarma, Soundar Kumara

“…To address this, we introduce a selective learning approach, where the amount of data collected is problem dependent. …”
Get full text

The Short‐Time Prediction of Thermospheric Mass Density Based on Ensemble‐Transfer Learning by Peian Wang, Zhou Chen, Xiaohua Deng, Jing‐Song Wang, Rongxing Tang, Haimeng Li, Sheng Hong, Zhiping Wu

Subjects: Get full text

Experiential Learning in Vehicle Dynamics Education via Motion Simulation and Interactive Gaming by Kevin Hulme, Edward Kasprzak, Ken English, Deborah Moore-Russo, Kemper Lewis

“…Creating active, student-centered learning situations in postsecondary education is an ongoing challenge for engineering educators. …”
Get full text

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy by Min Guo, Yicong Wu, Chad M. Hobson, Yijun Su, Shuhao Qian, Eric Krueger, Ryan Christensen, Grant Kroeschell, Johnny Bui, Matthew Chaw, Lixia Zhang, Jiamin Liu, Xuekai Hou, Xiaofei Han, Zhiye Lu, Xuefei Ma, Alexander Zhovmer, Christian Combs, Mark Moyle, Eviatar Yemini, Huafeng Liu, Zhiyi Liu, Alexandre Benedetto, Patrick La Riviere, Daniel Colón-Ramos, Hari Shroff

“…Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. …”
Get full text

Efficient and accurate identification of maize rust disease using deep learning model by Pei Wang, Pei Wang, Jiajia Tan, Yuheng Yang, Yuheng Yang, Tong Zhang, Pengxin Wu, Xinglong Tang, Hui Li, Xiongkui He, Xinping Chen

Get full text

Padlet: a tool for fostering collaborative learning and feedback literacy in dental education by Avita Rath

Subjects: Get full text

Community Participation Process for the Sustainable Business Development of Local Wisdom Learning Centers by Thussaneeya Boripis, Shubham Pathak, Wachiraporn Poungjinda, Josephine Chen Yii Ling

“…The findings included that the policies must consist of a community participation process to develop local wisdom learning centers to jointly formulate wisdom tourism policies by the local government in Koh Yao District, Phang Nga Province. …”
Get full text

Access control relationship prediction method based on GNN dual source learning by Dibin SHAN, Xuehui DU, Wenjuan WANG, Aodi LIU, Na WANG

“…With the rapid development and wide application of big data technology, users’ unauthorized access to resources becomes one of the main problems that restrict the secure sharing and controlled access to big data resources.The ReBAC (Relationship-Based Access Control) model uses the relationship between entities to formulate access control rules, which enhances the logical expression of policies and realizes dynamic access control.However, It still faces the problems of missing entity relationship data and complex relationship paths of rules.To overcome these problems, a link prediction model LPMDLG based on GNN dual-source learning was proposed to transform the big data entity-relationship prediction problem into a link prediction problem with directed multiple graphs.A topology learning method based on directed enclosing subgraphs was designed in this modeled.And a directed dual-radius node labeling algorithm was proposed to learn the topological structure features of nodes and subgraphs from entity relationship graphs through three segments, including directed enclosing subgraph extraction, subgraph node labeling calculation and topological structure feature learning.A node embedding feature learning method based on directed neighbor subgraph was proposed, which incorporated elements such as attention coefficients and relationship types, and learned its node embedding features through the sessions of directed neighbor subgraph extraction and node embedding feature learning.A two-source fusion scoring network was designed to jointly calculate the edge scores by topology and node embedding to obtain the link prediction results of entity-relationship graphs.The experiment results of link prediction show that the proposed model obtains better prediction results under the evaluation metrics of AUC-PR, MRR and Hits@N compared with the baseline models such as R-GCN, SEAL, GraIL and TACT.The ablation experiment results illustrate that the model’s dual-source learning scheme outperforms the link prediction effect of a single scheme.The rule matching experiment results verify that the model achieves automatic authorization of some entities and compression of the relational path of rules.The model effectively improves the effect of link prediction and it can meet the demand of big data access control relationship prediction.…”
Get full text

Non-line-of-sight Visible Light Positioning System based on Deep Learning by HUANG Weijie, LIN Bangjiang, DING Yongqi, LUO Jiabin, HUANG Tianming

Subjects: Get full text

Phase retrieval for block sparsity based on adaptive coupled variational Bayesian learning by Di Zhang, Yimao Sun, Siqi Bai, Qun Wan

Subjects: “…variational Bayesian learning (VBL)…”
Get full text

Evaluation of an Interdisciplinary Educational Program to Foster Learning Health Systems: Education Evaluation by Sathana Dushyanthen, Nadia Izzati Zamri, Wendy Chapman, Daniel Capurro, Kayley Lyons

“…In a flipped classroom model, participants (n=400) undertook 2 hours of preclass learning online and then attended 2.5 hours of live synchronous learning in interactive weekly Zoom workshops for 13 weeks. …”
Get full text

Milk Composition Is Predictive of Low Milk Supply Using Machine Learning Approaches by Xuehua Jin, Ching Tat Lai, Sharon L. Perrella, Xiaojie Zhou, Ghulam Mubashar Hassan, Jacki L. McEachran, Zoya Gridneva, Nicolas L. Taylor, Mary E. Wlodek, Donna T. Geddes

“…<b>Results:</b> Among the six machine learning algorithms tested, deep learning and gradient boosting machines methods had the best performance metrics. …”
Get full text

About the morphological characteristics of speeches of Plemetina: Contribution to learning of lower sitnica speeches by Jovanović Jovana S.

“…According to system of declension of nouns, the learning local speech is inclined to North and North East conditions on the area of Kosovo dialect nevertheless it has not been exempted from mediocrity. …”
Get full text

Experiencing information seeking and learning: a study of the interaction between two phenomena by Louise Limberg

Subjects: “…Experiencing information seeking and learning: a study of the interaction between two phenomena…”
Get full text

Recent advances on federated learning systems and the design for computing power Internet of things by LU Jianfeng, QI Pan, PAN Linyu, LI Bing, CAO Shuqin, JIN Yan'an

“…Within the context of privacy protection requirements for CPIoT, federated learning (FL) that is a distributed learning technique upholds data privacy, and offers a novel approach to addressing data silos for executing complex training tasks, and training large models. …”
Get full text