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Machine learning analysis of factors affecting college students' academic performance.
Front Psychol
December 2024
Department of Science and Technology, Hebei Agricultural University, Huanghua, China.
This study aims to explore various key factors influencing the academic performance of college students, including metacognitive awareness, learning motivation, participation in learning, environmental factors, time management, and mental health. By employing the chi-square test to identify features closely related to academic performance, this paper discussed the main influencing factors and utilized machine learning models (such as LOG, SVC, RFC, XGBoost) for prediction. Experimental results indicate that the XGBoost model performs the best in terms of recall and accuracy, providing a robust prediction for academic performance.
View Article and Find Full Text PDFThe environmental impact of religious beliefs in the East and West: evidence from China.
Front Psychol
December 2024
Institute for Empirical Social Science Research (IESSR), Department of Sociology, School of Humanities and Social Sciences, Xi'an Jiaotong University, Xi'an, China.
This study explores the influence of religious beliefs on environmental attitudes and behaviors in China. Using data from the 2021 Chinese General Social Survey (CGSS), two structural equation models were constructed to examine the mediating roles of natural empathy and anthropocentrism in the relationship between environmental awareness and willingness to make sacrifices for environmental protection. The results indicated that while environmental awareness positively influenced willingness to sacrifice, natural empathy did not significantly mediate this relationship.
View Article and Find Full Text PDFStrategies to prevent postoperative delirium: a comprehensive evaluation of anesthesia selection and drug intervention.
Front Psychiatry
December 2024
Department of Orthopedics, The Second Hospital of Anhui Medical University, Hefei, China.
Postoperative delirium (POD) represents a common neurological complication encountered predominantly among the elderly cohort undergoing surgical intervention for hip fractures. This phenomenon, particularly commonplace in geriatric populations with heightened preoperative risk profiles, pronounced comorbidities, and later stages of lifespan, poses complex clinical challenges. The impact of perioperative pharmacological interventions and anesthetic strategies on POD's emergence cannot be understated, as it may profoundly affect the length of hospital stays, rehabilitation milestones, and the overall mortality hazard.
View Article and Find Full Text PDFResearch on the self-efficacy and resilience of female graduate students in the era of artificial intelligence: analysis of the mechanism of mobile phone dependence, anxiety and mentoring relationship.
Arch Womens Ment Health
January 2025
Institute of Vocational Education, Tongji University, Shanghai, China.
Purpose: The purpose of this study is to investigate the impact of the employment situation on the anxiety levels and research self-efficacy of graduate students, with a particular focus on female graduate students. The study aims to understand how the use of AIGC tools, which has become more frequent among those with lower research self-efficacy, affects anxiety and research resilience. Additionally, the research explores the role of the mentoring relationship in influencing the psychological and academic experiences of female graduate students.
View Article and Find Full Text PDFNanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries.
Sci Rep
January 2025
Department of Information Systems, College of Computing and Informatics, The University of Sharjah, Sharjah, UAE.
This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels, improves fuel atomization, combustion efficiency, and emission control. Simultaneously, LSTM models are employed to analyze and predict the complex spray behavior under diverse operational and geometric conditions.
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