Predicting Financial Well-Being in Millennial Workers: A Test of the Theory of Planned Behavior and the Role of Financial Literacy by Ignatius Jonathan, Eka Bertuah

“…In addition, while both TPB and financial literacy have been used to predict financial behavior, their combined application to specifically predict the financial well-being of millennial workers offers a nuanced and potentially more comprehensive understanding. …”
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Investigation on fracture behavior and prediction model of AA2219-T6 under the coupled effects of temperature and stress state by Cong Liu, Ji Qiu, Buyun Su, Zhiqiang Li, Xiaohu Yao, Xuefeng Shu

“…This study systematically investigates the coupled effects of temperature and stress state on the ductile fracture behavior of AA2219-T6. Tensile tests were conducted on specimens with various geometries (TR5, TR10, TD10, and SH) at room temperature, 150 °C, and 200 °C. …”
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A prediction model of massive 5G network users’ revisit behavior based on telecom big data by Yudi SUN

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Association of artificial intelligence–predicted milk yield residuals to behavioral patterns and transition success in multiparous dairy cows by C. Kemel, M. Salamone, B. Aernouts, I. Adriaens, G. Opsomer, P. Hut, M. Hostens

“…Three milk residual categories (low, medium, high) were subsequently defined, and behavioral differences between the categories were studied. …”
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Finite Element Analysis and Machine Learning‐Based Prediction of Oil Tank Behavior Under Diverse Operating Conditions by Themba Mashiyane, Lagouge Tartibu, Smith Salifu

“…This study integrates Finite Element Analysis (FEA) and Machine Learning (ML) to predict the behavior (structural) and useful life of oil tanks under diverse operating conditions. …”
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Prediction Analysis of College Students’ Physical Activity Behavior by Improving Gray Wolf Algorithm and Support Vector Machine by Minjian Wang

“…By constructing a campus behavior data set of college students and conducting experiments, the algorithm achieves 90.45% behavior prediction accuracy, which is better than that of typical prediction models. …”
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CD4+ T-cell transcription factors predict phenoconversion in idiopathic rapid eye movement sleep behavior disorder by Monica Pinoli, Michele Terzaghi, Franca Marino, Cristoforo Comi, Maurizio Versino, Marco Cosentino

“…In patients with idiopathic REM sleep behavior disorder (iRBD), the strongest risk factor for neurodegeneration, CD4+ T cells exhibit a peculiar transcription factor pattern.Objective: To assess transcription factor mRNA levels in CD4+ T cells as predictive biomarkers of phenoconversion in iRBD patients.Methods: iRBD patients were followed prospectively. …”
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A Hybrid Internet of Behavior Algorithm for Predicting IoT Data of Plant Growing using LSTM and NB Models by Khansaa Yaseen Ahmad, Omar Muayad Abdullah

“…This research proposes a hybrid Internet of Behaviors (IoB) technique that linking between time-series predicting and the classification models to estimate the plant growing behaviors using real environmental data. …”
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Ship behavior prediction and anomaly detection using LSTM-DCross model based on AIS and remote sensing data by Wanrong Wu, Dongmei Yan, Jun Yan, Xiaowei Wang

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Predicting learners' engagement and help-seeking behaviors in an e-learning environment by using facial and head pose features by Guan-Yun Wang, Yasuhiro Hatori, Yoshiyuki Sato, Chia-Huei Tseng, Satoshi Shioiri

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TCB: A feature transformation method based central behavior for user interest prediction on mobile big data by Chen Zhou, Hao Jiang, Yanqiu Chen, Jing Wu, Jianguo Zhou, Yuanshan Wu

“…Moreover, these typical features ignore the fact that human behaviors are highly predictable and centralized. Specifically, human mobility is constrained in a small area depicted by several hotspots, and users tend to access mobile Internet intensively on several particular timeslots, which are defined as hot-times in this article. …”
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Predicting the relationship between consumer buying behavior (CBB) and consumption metaphor (CM) through machine learning (ML) by Koyluoglu Alaaddin Selcuk, Esme Engin

“…The study aims to predict the relationship between consumer buying behavior (CBB) and consumption metaphor (CM) through ML. …”
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A prediction model of massive 5G network users’ revisit behavior based on telecom big data by Yudi SUN

Subjects: “…telecom big data;prediction of users’ revisit behavior;multi order weighted Markov chain model;one step transition probability matrix;autocorrelation coefficient…”
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Spatial-Temporal Distribution Prediction of Electric Vehicle Charging Load Considering Charging Behavior and Real-Time SOC by ZHANG Linjuan, LI Wenfeng, XU Changqing, GUO Jianyu, ZHANG Xiawei, YUAN Jia, WANG Yaoqiang

“…[Conclusions] The proposed method can fully consider the interaction of the road network，EV，and user charging behavior and accurately predict the spatial-temporal distribution characteristics of EV charging loads.…”
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Prediction of thermomechanical behavior of acrylonitrile butadiene styrene using a newly developed nonlinear damage-reliability model by A. En-naji, N. Mouhib, H. Farid, M. El Ghorba

“…The results demonstrate that the behavior of the polymers is strongly dependent on the temperature. …”
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One factor to bind them all: visual foraging organization to predict patch leaving behavior with ROC curves by Marcos Bella-Fernández, Manuel Suero Suñé, Alicia Ferrer-Mendieta, Beatriz Gil-Gómez de Liaño

“…Using ROC curves, all results consistently show that organization measures outperform classic intake rates commonly used in animal models to predict optimal human quitting behavior. Importantly, a combination of organization and traditional intake rates within a unitary factor is the best predictor. …”
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Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery by Benoit Schmauch, Sarah S. Elsoukkary, Amika Moro, Roma Raj, Chase J. Wehrle, Kazunari Sasaki, Julien Calderaro, Patrick Sin-Chan, Federico Aucejo, Daniel E. Roberts

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Prediction of stress-strain behavior of rock materials under biaxial compression using a deep learning approach. by Changsheng Li, Xinsong Zhang

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Prediction of thermomechanical behavior of acrylonitrile butadiene styrene using a newly developed nonlinear damage-reliability model by Abderrazak En-naji, N. Mouhib, H. Farid, M. El Ghorba

“…The results demonstrate that the behavior of the polymers is strongly dependent on the temperature. …”
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Fatigue behavior and prediction model assessment of laser powder-bed fusion additively manufactured Nickel-based alloys by Mosa Almutahhar, Mohammed Yousif, Ali Alhajeri, Aremu Habib, Khaled Al-Athel, Jafar Albinmousa, Usman Ali

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