Predicting the Swelling Behavior of Acrylic Superabsorbent Polymers Used in Diapers by Shuxin Zhang, Yangyang Peng, Ran Jiang, Wenqiang Liu, Huanlei Yang, Na Yun, Xinsheng Chai

“…Based on a previously developed kinetic swelling model and the information from the above investigations, a semiempirical model for predicting the swelling behavior of superabsorbent polymers (SAPs) under different conditions has been developed. …”
Get full text

Learner preferences prediction with mixture embedding of knowledge and behavior graph by Xiaoguang LI, Lei GONG, Xiaoli LI, Xin ZHANG, Ge YU

“…To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences.…”
Get full text

Learner preferences prediction with mixture embedding of knowledge and behavior graph by Xiaoguang LI, Lei GONG, Xiaoli LI, Xin ZHANG, Ge YU

“…To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences.…”
Get full text

Predicting Pro-Environmental Behavior: The Leading Influence of Environmental Attitudes by Velina Hristova, Kaloyan Haralampiev, Ivo Vlaev, Sonya Karabeliova

Get full text

Application of machine learning in predicting adolescent Internet behavioral addiction by Yao Gan, Li Kuang, Xiao-Ming Xu, Ming Ai, Jing-Lan He, Wo Wang, Su Hong, Jian mei Chen, Jun Cao, Qi Zhang

Subjects: Get full text

Neural Dynamics of Strategic Early Predictive Saccade Behavior in Target Arrival Estimation by Ryo Koshizawa, Kazuma Oki, Masaki Takayose

“…<b>Background/Objectives</b>: Accurately predicting the arrival position of a moving target is essential in sports and daily life. …”
Get full text

Development and validation of a predictive model for suicidal thoughts and behaviors among freshmen by Yan Qin, Sifang Niu, Xingmeng Niu, Yangziye Guo, Yu Sun, Shuzhang Hu, Fuqin Mu, Ying Zhang, Min Liu, Jianli Wang, Yan Liu

Subjects: “…Suicidal thought and behavior…”
Get full text

Will You Become the Next Troll? A Computational Mechanics Approach to the Contagion of Trolling Behavior by Qiusi Sun, Martin Hilbert

“…We derive the unique, minimally complex, and maximally predictive model from statistical mechanics, i.e., ε-machines and transducers, and can distinguish which aspects of trolling behaviors are both self-motivated and socially induced. …”
Get full text

Protocol to study how expectations guide predictive eye movements and information sampling in humans by Annika Garlichs, Mark Lustig, Matthias Gamer, Helen Blank

Get full text

Predictive analysis of miners’ group unsafe behavior based on group dynamics and institutional environment by Shuicheng Tian, Ruirui Wang, Hongxia Li, Lei Chen, Yuan Kuang, Junrui Mao

Get full text

Predictive Modeling and Experimental Analysis of Cyclic Shear Behavior in Sand–Fly Ash Mixtures by Özgür Yıldız, Ali Fırat Çabalar

“…Furthermore, the integration of advanced machine learning techniques such as NARX models offers a powerful tool for predicting the behavior of soil mixtures, facilitating more effective and data-driven decision-making in geotechnical applications. …”
Get full text

Predict organizational citizenship behavior of the staff based on the factors of the job satisfaction by Khaidan Hatamı, Mohhammad Reza Esmaeılı, Sayed Hamid Sajadı

“…The aim of the present study was to predict organizational citizenship behavior of the staff of the Ministry of Sport and Youth in the west part of the country based on the factors of the Job Satisfaction. …”
Get full text

The utility of trauma history and current psychopathology in predicting preventive health behaviors by Sheela Raja, Emily P. Rabinowitz, Steve Gonzalez, Megan Lee, Shivali Padmani, Memoona Hasnain

Get full text

Content creators as social influencers: predicting online video posting behaviors by Jeffres Leo, Atkin David, Neuendorf Kimberly

Get full text

On the use of the stepped isostress method in the prediction of creep behavior of polyamide 6 by Tedjini Mohsein, Sedira Lakhdar, Guerira Belhi, Kamel Meftah

“…The stepped isostress method (SSM) is an advanced technique which allows the prediction of the long-term behavior and enables the construction of creep master curves of materials with short-term experimental tests. …”
Get full text

Predicting Student Behavior Using a Neutrosophic Deep Learning Model by Ahmed Mohamed Shitaya, Mohamed El Syed Wahed, Saied Helemy Abd El Khalek, Amr Ismail, Mahmoud Y. Shams, A. A. Salama

“…This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. …”
Get full text

Experimental investigation and prediction of wear behavior of cotton fiber polyester composites by Hiral H. Parikh, Piyush P. Gohil

“…A scanning electron microscope (SEM) was used to study the wear mechanism. To predict the wear behavior of the composite material, comparisons were made between the general regression technique and an artificial neural network (ANN). …”
Get full text

Possibilities of psychological methods in predicting the risk of illegal and suicidal behavior in adolescents by V.A. Mudrov, A.V. Sakharov

“… <p style="text-align: justify;"><strong>The aim </strong>of the study was to study psychological and mathematical methods in predicting the risk of unlawful and suicidal behavior in adolescents and to create computer programs based on the results obtained. …”
Get full text

Do the Theory of Planned Behavior, and Perceived Cheating predict academic dishonesty? by Felix Reskala

Get full text

Theory of Planned Behavior in predicting condom use in Latin-American Women by David Javier Enríquez-Negrete, Ricardo Sánchez-Medina, Susana Xóchitl Bárcena-Gaona, Itzel Guadalupe Chávez-Santos

“…Background: The theory of Planned Behavior (TPB) is used to predict condom use. The present study assessed the causal relationships of the TPB in a cultural context different from the one that was proposed. …”
Get full text