Forecasting Stock Returns Using Long Short-Term Memory (LSTM) Model Based on Inflation Data and Historical Stock Price Movements by Nur Faid Prasetyo, Wina Witanti, Asep Id Hadiana

“…However, its inherent volatility necessitates the inclusion of macroeconomic indicators like inflation, which can affect stock valuation and investor behavior. This study explores predicting stock returns using a Long Short-Term Memory (LSTM) model by incorporating inflation data, historical stock price movements, and calculated returns as input features. …”
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A Modified Latent Dirichlet Allocation Topic Approach for Driving Style Exploration Using Large-Scale Ride-Hailing GPS Data by Ye Li, Yiqi Chen, Jie Bao, Lu Xing, Jinjun Tang, Changyin Dong, Ruifeng Gu

“…The large-scale GPS data are collected and preprocessed, and then, the k-means clustering is implemented to acquire driving behavior. …”
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Fatigue crack behaviour: comparing three-point bend test and wedge splitting test data on vibrated concrete using Paris' law by S. Seitl, T. Thienpont, W. De Corte De Corte

“…In a final step, the Paris-Erdogan law parameters C and m were obtained through linear curve fitting on the data points from the obtained graphs. The parameters C and m are then used to compare and evaluate the fatigue crack behavior in vibrated concrete, and the differences between the results from the three-point bend tests and wedge splitting tests.…”
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Moderated Mediating Effect of Behavioral Psychology on Generation Z’s Selfie-Posting Behavior: A Two-Stage Analytical Approach by Sanjoy Kumar Roy, Shamsun Arefin, Md. Rahat Khan

“…The research comprised 414 samples through convenience sampling. The empirical data were analyzed using a hybrid SEM-artificial neural network (SEM-ANN) approach. …”
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The Dual Effects of Work Connectivity Behavior After-Hours on Employee Behaviors: Balancing Psychological Job Control and ICT Anxiety by Lijun Chen, Shimin Zhang

“…The dual effects of work connectivity behavior after-hours (WCBA) on employees’ in-role and extra-role behaviors were investigated using the framework of the Job Demands–Resources (JD-R) model. …”
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Influencing factors and mechanisms promoting proactive health behavior intention: an integration of the health belief model and the theory of planned behavior by Lidong Fang, Qiaoqiao Zhang, Ning Zhou, Jin Chen, Hu Lou

“…Participants were approached on-site during routine check-ups and voluntarily completed the survey after providing informed consent. Data were analyzed using SPSS 26.0 and AMOS 26.0. …”
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Exploring purchasing behavior of Ethiopian consumers towards locally produced apparel products: an extended model of the theory of planned behavior by Eyob Minbale, Berihun Bizuneh, Wendosen Seife, Shalemu Sharew, Kumlachew Bitew

“…With this concern, this paper explores the determinants of Ethiopian consumers’ purchasing behavior towards locally-produced apparel products by using the extended theory of planned behavior (TPB) model. …”
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The relationship between academic stress, anxiety, and cognitive behavioral outcomes among young adults: The moderating role of prosocial behavior by Iftikhar Ahmed Charan, Wang Chongjin, Shazia Soomro

“…Data were analyzed using SPSS version 26. Results revealed that academic stress was significantly and positively correlated with cognitive behavioral outcomes, while it showed a significant negative correlation with academic emotions, civic engagement, and prosocial behavior. …”
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Assessing Crash Reduction at Stop-Controlled Intersections: A Before-After Study of LED-Backlit Signs Using Crash and Conflict Data by Maziyar Layegh, Ciprian Alecsandru, Matin Giahi Foomani

“…It provides a framework for assessing safety treatments in contexts where crash data are limited. Findings offer insights for improving SCIs and enhancing transportation safety using LED stop signs.…”
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The use of a matched controls design and publicly available outcome data to evaluate a multiyear urban school-based SEL intervention by Angela W. Wang, Simon Daniel, Maurice J. Elias

“…Our findings indicate mixed results across academic and behavioral indicators, such as significant improvement in Math scores but smaller effects for behavioral metrics, such as substance use. …”
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Predicting consumers' intention and behavior towards industrial dairy products: A study based on an extended theory of planned behavior by Mohammad Hojjati, Abbas Mirzaei, Nastaran Hemmati, Bahareh Goodarzi Shamsabadi

“…Using stratified random sampling, 377 household heads in Izeh County, Khuzestan Province, Iran, were selected, and data were collected through face-to-face interviews. …”
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Predicting poor self-management behaviors in adults with newly diagnosed COPD: based on the information-motivation-behavioral skills model by Xiaomei Chen, Jia Liu, Yuxuan He, Li Wei, Menghui Deng, Rui Zhang, Huiqin Song, Yanni Yang

“…Multivariate logistic regression was used to develop a risk prediction model to predict poor self-management behaviors. …”
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A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…To overcome these limitations, we propose a probabilistic methodology for turbine-level active power prediction and uncertainty estimation using high-frequency SCADA data and farm-wide autoregressive information. …”
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Validation of the Mild Behavioral Impairment Scale (MBI-S) for brief self-assessment of Mild Behavioral Impairment in people without dementia by Paula Hinkl, Elmar Graessel, Nicolas Rohleder, Peter Landendoerfer, Thomas Kuehlein, Natascha Lauer, Anna Pendergrass

“…Abstract Background Mild Cognitive Impairment (MCI) and Mild Behavioral Impairment (MBI) are important constructs in the context of cognitive decline. …”
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Artificial Intelligence Teaching System and Data Processing Method Based on Big Data by Bo Xu

“…Based on relevant researches on domestic and foreign related learning analysis and common big data analysis methods, combined with actual learning evaluation goals, this paper proposes an artificial intelligence teaching system using big data analysis methods and a modeling process framework for online learning evaluation and uses student data to carry out predictive evaluation modeling to evaluate student learning outcomes. …”
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Using Active and Passive Smartphone Data to Enhance Adolescents’ Emotional Awareness in Forensic Outpatient Setting: A Qualitative Feasibility and Usability Study by Merel M L Leijse, Levi van Dam, Tijs Jambroes, Amber Timmerman, Arne Popma

“…The low-threshold use of smartphone data can be useful in addressing these treatment challenges. …”
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Investigating Synoptic Influences on Tropospheric Volcanic Ash Dispersion from the 2015 Calbuco Eruption Using WRF-Chem Simulations and Satellite Data by Douglas Lima de Bem, Vagner Anabor, Franciano Scremin Puhales, Damaris Kirsch Pinheiro, Fabio Grasso, Luiz Angelo Steffenel, Leonardo Brenner, Umberto Rizza

“…We used WRF-Chem to simulate ash transport from eruptions of Chile’s Calbuco volcano on 22–23 April 2015. …”
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Analyzing Online Search Trends for Kidney, Prostate, and Bladder Cancers in China: Infodemiology Study Using Baidu Search Data (2011-2023) by Shuangquan Lin, Lingxing Duan, Xiangda Xu, Haichao Cao, Xiongbing Lu, Xi Wen, Shanzun Wei

“…User demand was assessed by categorizing the top 10 related terms weekly into 13 predefined topics, including diagnosis, treatment, and traditional Chinese medicine. Data visualization and statistical analyses were performed using Prism 9. …”
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EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation by Ch Anwar Ul Hassan, Muhammad Ehatisham-ul-Haq, Fiza Murtaza, Aman Ullah Yasin, Syed Sajid Ullah

“…This paper proposes the EmoTrans model, which uses the DEAP dataset to analyze physiological signals and facial video recordings. …”
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Analyzing the use of fact-checking tools in disaster-risk reduction in Europe through the lens of the heuristic-systematic model by Nadejda Komendantova, Tahereh Zobeidi, Masoud Yazdanpanah

“…Identifying false information can curb its spread and reduce its impact on people’s attitudes and behaviors. Understanding how and why people in a disaster situation use fact-checking tools is crucial, as disaster-risk messages containing false content can usually be detected using systematic or heuristic processing. …”
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