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Characteristics of vocal cues, facial action units, and emotions that distinguish high from low self-protection participants engaged in self-protective response to self-criticizing.
Front Psychol
January 2025
Faculty of Social and Economic Sciences, Institute of Applied Psychology, Comenius University in Bratislava, Bratislava, Slovakia.
Introduction: Self-protection, also called protective anger or assertive anger, is a key factor in mental health. Thus, far, researchers have focused mainly on the qualitative analysis of self-protection.
Methods: Therefore, we investigated facial action units, emotions, and vocal cues in low and high self-protective groups of participants in order to detect any differences.
Distributed acoustic sensing (DAS) is a technology that uses optical fiber as a sensing unit to detect external vibration signals. Due to the high resolution and high sensitivity of DAS, it has great application potential in the detection of vibration events. However, high detection performance will bring limitations to DAS in multi-source detection.
View Article and Find Full Text PDFGreen building development utilising modified fired clay bricks and eggshell waste.
Sci Rep
January 2025
PV Unit, Solar and Space Research Department, National Research Institute of Astronomy and Geophysics (NRIAG), Helwan, Cairo, Egypt.
The inadequate thermal insulation of the building envelope contributes significantly to the high power consumption of air conditioners in houses. A crucial factor in raising a building's energy efficiency involves utilizing bricks with high thermal resistance. This issue is accompanied by another critical challenge: recycling and disposing of waste in a way that is both economically and environmentally beneficial, including using it to fuel industrial growth, in order to reduce the harmful effects of waste on the environment as waste generation in our societies grows.
View Article and Find Full Text PDFA multi-dimensional student performance prediction model (MSPP): An advanced framework for accurate academic classification and analysis.
MethodsX
June 2025
Department of Networking & Communications, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
Forecasting student performance with precision in the educational space is paramount for creating tailor-made interventions capable to boost learning effectiveness. It means most of the traditional student performance prediction models have difficulty in dealing with multi-dimensional academic data, can cause sub-optimal classification and generate a simple generalized insight. To address these challenges of the existing system, in this research we propose a new model Multi-dimensional Student Performance Prediction Model (MSPP) that is inspired by advanced data preprocessing and feature engineering techniques using deep learning.
View Article and Find Full Text PDFA machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.
Sci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
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