Drone Video Anomaly Detection by Future Segmentation Prediction and Spatio- Temporal Relational Modeling by Ahmed Fakhry, Janghoon Lee, Jong Taek Lee

Subjects: “…Deep learning…”
Get full text

INTERACTION IN AN EDUCATIONAL ENVIRONMENT WITH VIRTUAL AND AUGMENTED REALITY by Svitlana H. Lytvynova, Natalia V. Soroko

Subjects: Get full text

Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHANES 2015–2018 by Jiayi Chen

Subjects: “…Machine learning…”
Get full text

The usability and technology acceptance of immersive virtual reality simulation for critical infrastructure workers by Andrzej Grabowski

Subjects: Get full text

Comprehensive Analysis of Word Embedding Models and Design of Effective Feature Vector for Classification of Amazon Product Reviews by B. Priya Kamath, M. Geetha, U. Dinesh Acharya, Dipesh Singh, Ayush Rao, Shwetha Rai, Roopashri Shetty

Subjects: Get full text

Fatigue State Evaluation of Urban Railway Transit Drivers Using Psychological, Biological, and Physical Response Signals by Hao Wu, Yubo Jiao, Chaozhe Jiang, Tong Wang, Jiangbo Yu

Subjects: Get full text

Synthetic CT generation from CBCT and MRI using StarGAN in the Pelvic Region by Paritt Wongtrakool, Chanon Puttanawarut, Pimolpun Changkaew, Supakiet Piasanthia, Pareena Earwong, Nauljun Stansook, Suphalak Khachonkham

Subjects: Get full text

Alternatives to Traditional Physical Science Laboratory Experiences: A Review by Mercy Ogunsola-bandele, Dietmar Kennepohl

Subjects: “…online learning…”
Get full text

Investigation of multi-input convolutional neural networks for the prediction of particleboard mechanical properties by Shuoye Chen, Shunsuke Sakai, Miyuki Matsuo-Ueda, Kenji Umemura

Subjects: Get full text

Adaptive Cut Selection in Mixed-Integer Linear Programming by Turner, Mark, Koch, Thorsten, Serrano, Felipe, Winkler, Michael

Subjects: Get full text

Real-Time Quality Monitoring and Anomaly Detection for Vision Sensors in Connected and Autonomous Vehicles by Elena Politi, Charalampos Davalas, Christos Chronis, George Dimitrakopoulos, Dimitrios Michail, Iraklis Varlamis

Subjects: Get full text

Exploring gender differences in vocational education and training through the lens of neuroscience by Jinjiao Zhou, Shuo Chen, yuzhuo Gong

Subjects: Get full text

A computational role of blood nanofluid induced by a stenosed artery with porous medium and thermophoretic particle deposition effects by Shivalila Hangaragi, N. Neelima, N. Beemkumar, Ankur Kulshreshta, Umair Khan, Noreen Sher Akbar, Mohammad Kanan, Mona Mahmoud

Subjects: Get full text

Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

Subjects: “…Machine learning…”
Get full text

Distinctive blood and salivary proteomics signatures in Qatari individuals at high risk for cardiovascular disease by Ghada Yousif, Selvasankar Murugesan, Mohamed Nadhir Djekidel, Annalisa Terranegra, Giusy Gentilcore, Jean Charles Grivel, Souhaila Al Khodor

Subjects: Get full text

GTAT: empowering graph neural networks with cross attention by Jiahao Shen, Qura Tul Ain, Yaohua Liu, Banqing Liang, Xiaoli Qiang, Zheng Kou

Subjects: “…Graph learning…”
Get full text

Early-stage investigators’ experiences with an National Institutes of Health Pilot Award Program by Cyleste C. Collins, Jacqueline Dolata, Elodie Nonguierma, Mona Shediac-Rizkallah, Ashwini R. Sehgal, J. Daryl Thornton

Subjects: Get full text

Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

Subjects: Get full text

Real-Time Pose Prediction and Dynamic Anchor Selection for Ultra-Wideband Tagless Gate by Junyoung Choi, Joohyun Lee, Sagnik Bhattacharya

Subjects: Get full text

Association between the use of daily injury risk estimation feedback (I-REF) based on machine learning techniques and injuries in athletics (track and field): results of a prospective cohort study over an athletics season by Karsten Hollander, David Blanco, Pascal Edouard, Laurent Navarro, Antoine Bruneau, Alexis Ruffault, Joris Chapon, Pierre-Eddy Dandrieux, Christophe Ley, Spyridon (Spyros) Iatropoulos

“…However, when considering athletes’ daily response rate in secondary analysis, for a response rate of at least 9%, we observed a significant association between the self-reported level of I-REF use and the injury burden (n=76, eβ: 0.981, 95% CI: 0.965 to 0.998; p=0.027).Conclusions Daily injury risk estimation feedback using machine learning was not associated with reducing injury burden.…”
Get full text