What do Parents Learn by Reading a DPT Vaccine Information Form? by Ronald Gold, Gordean L Bjornson

Get full text

Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning by Wei Hao, Donglei Rong, Kefu Yi, Qiang Zeng, Zhibo Gao, Wenguang Wu, Chongfeng Wei, Biljana Scepanovic

“…With the exponential growth of traffic data and the complexity of traffic conditions, in order to effectively store and analyse data to feed back valid information, this paper proposed an urban road traffic status prediction model based on the optimized deep recurrent Q-Learning method. The model is based on the optimized Long Short-Term Memory (LSTM) algorithm to handle the explosive growth of Q-table data, which not only avoids the gradient explosion and disappearance but also has the efficient storage and analysis. …”
Get full text

Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

Subjects: Get full text

Cross-domain entity identity association analysis and prediction based on representation learning by Mingcheng Gao, Ruiheng Wang, Lu Wang, Yang Xin, Hongliang Zhu

“…Moreover, we creatively designed a network representation learning method. We proposed a supervised learning identity association model combined with a representation learning method. …”
Get full text

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

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

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

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

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

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

The potential for productive use of the digital service LearningApps in teaching foreign languages by Natalia A. Katalkina, Nadezhda V. Bogdanova

“…The purpose of the study is to test the method of productive use by students of higher educational institutions of the LearningApps service in the process of teaching foreign languages. …”
Get full text

Tropospheric Ducting: A Comprehensive Review and Machine Learning-Based Classification Advancements by Mohammed Banafaa, Ali Hussein Muqaibel

“…Our findings demonstrate that machine learning models, particularly support vector machines, can effectively classify ducting conditions, offering superior predictive performance compared to other models. …”
Get full text

Research on intrusion detection method for edge networks based on federated reinforcement learning by DING Kai, HUANG Yidu, TAO Ming, XIE Renping

Subjects: “…federated reinforcement learning…”
Get full text

A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy by Chetan Shetty, S. Seema, B. J. Sowmya, Rajesh Nandalike, S. Supreeth, Dayananda P., Rohith S., Vishwanath Y., Rajeev Ranjan, Venugopal Goud

“…In this work, density-based spatial clustering of applications with noise (DBSCAN) is used which is among the widely used clustering algorithms in machine learning. It is not only capable of finding clusters of various sizes and shapes but can also detect outliers. …”
Get full text

Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…This study aimed to identify potential therapeutic targets for the treatment of AD using comprehensive bioinformatics methods and machine learning algorithms. By integrating differential gene expression analysis, weighted gene co-expression network analysis, Mfuzz clustering, single-cell RNA sequencing, and machine learning algorithms including LASSO regression, SVM-RFE, and random forest, five hub genes related to AD, including PLCB1, NDUFAB1, KRAS, ATP2A2, and CALM3 were identified. …”
Get full text