Human Behavior Analysis Using Radar Data: A Survey by Patrycja Miazek, Alicja Zmudzinska, Pawel karczmarek, Adam Kiersztyn

“…In this study, we focus not only on the analysis of human behavior using radar but also on video observations. …”
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Using Big Data in Consumer Behavior Analysis: A Case Study by Adrian Ionuț MOȘESCU, Denisa-Roxana BOTEA-MUNTEAN, Daniela MARINICĂ, Brîndușa BÎRSAN, Daniela Maria STANCIU (FRĂȚILĂ), Paul COSMOVICI, Ștefan-Claudiu CĂESCU

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Heterogeneity in the Driver Behavior: An Exploratory Study Using Real-Time Driving Data by Jahnavi Yarlagadda, Digvijay S. Pawar

“…The driving maneuver data are analyzed using the unsupervised techniques (PCA and K-means clustering) and three patterns of acceleration and braking are identified, which are further associated with two patterns of speed behavior. …”
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Early detection of mental health disorders using machine learning models using behavioral and voice data analysis by Sunil Kumar Sharma, Ahmed Ibrahim Alutaibi, Ahmad Raza Khan, Ghanshyam G. Tejani, Fuzail Ahmad, Seyed Jalaleddin Mousavirad

“…For this reason, this study presents a novel framework for the early detection of mental illness disorders using a multi-modal approach combining speech and behavioral data. …”
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Identifying Cyclical Patterns of Behavior Using a Moving-Average, Data-Smoothing Manipulation by Billie J. Retzlaff, Andrew R. Craig, Todd M. Owen, Brian D. Greer, Alex O’Donnell, Wayne W. Fisher

“…We describe two cases for which we identified cyclical patterns in daily occurrences of destructive behavior, and we demonstrate the importance of analyzing smoothed data across various windows when using this approach. …”
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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

“…Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. …”
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On the Asymptotic Behavior of the Maximum and Record Values of Multivariate Data Using the R-ordering principle by Mahmoud H. Harpy, Haroon M. Barakat

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Association between different types of smoking and first sexual behavior in adolescents: Survey data from South Korea by Yunyun Wu, Wenbin Du

“…Furthermore, data from the KYRBS 2018–2021 were used to analyze the time-related patterns in the connection between tobacco use and the first occurrence of sexual behavior among adolescents, with a focus on the moderating role of gender. …”
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Personal Information Sharing Behavior Using Social Media by Ashraf Sharif, Shafiq Ur Rehman, Khalid Mahmood

“…We used Scopus database for data extraction, and 1020 pertinent records were chosen. …”
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Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin by M. D. Gladyshev, A. V. Rybakov

“…Existing approaches to modeling and predicting URS behavior are known for their weak or absent integration of data from real sensors in real time. …”
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Understanding the Shortest Route Selection Behavior for Private Cars Using Trajectory Data and Navigation Information by Shiguang Wang, Heng Ding, Zeyang Cheng

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A dynamical systems analysis of criminal behavior using national longitudinal survey of youth data. by David McMillon, Jeffrey Morenoff, Carl Simon, Erin Lane

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Simultaneous Speech and Eating Behavior Recognition Using Data Augmentation and Two-Stage Fine-Tuning by Toshihiro Tsukagoshi, Masafumi Nishida, Masafumi Nishimura

“…By concatenating speech and eating sounds of varying lengths and sequences, we generated training data that mimic real-world environments where speech and eating behaviors co-exist. …”
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Bus driver deceleration behavior modeling at intersections using multi-source on-board sensor data by Yancheng Ling, Zhenliang Ma, Yuchen Song, Qi Zhang, Xiaoxiong Weng, Xiaolei Ma

“…We explored the factors impact on bus deceleration behavior at intersections using data from a typical bus route in China. …”
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The goldilocks days represent optimal time-use to prevent obesity, low physical performance, risk and fear of falling in older adults by Jan Vindiš, Jana Pelclová, Paulína Jašková, Karel Hron

“…Data were collected from 309 older adults (65 + years) in Czechia, using accelerometers worn on the non-dominant wrist to assess intensity-specific behaviors (sedentary behavior - SB, light physical activity - LPA, moderate-to-vigorous physical activity - MVPA, and sleep) and on the right thigh and waist to assess posture-specific behaviors (lying, sitting, standing, moving, and walking). …”
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Consumer behavior at sale point and consumption according to strawberry quality: How to use those data to evaluate food waste?entrepot.recherche.data.gouv.fr by Emma Pignères, Marine Masson, Steven Duret, David Blumenthal, Maëlle-Ahou Gouton, Nathalie Gontard, Hélène Angellier-Coussy, Valérie Guillard, Fanny Coffigniez, Sébastien Gaucel

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Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…Unlike traditional Rex architectures, this unified framework allows fine tuning of RexNet hyperparameters, simplifying their application. By combining data quality analysis with RexNet, this methodology explores multi-model behaviors and deeper interactions between dependent (e.g., health and condition indicators) and independent variables (e.g., Remaining Useful Life (RUL)), offering richer insights than conventional methods. …”
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Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone by Daniel Alves da Silva, José Alberto Sousa Torres, Alexandre Pinheiro, Francisco L. de Caldas Filho, Fabio L. L. Mendonça, Bruno J. G Praciano, Guilherme Oliveira Kfouri, Rafael T. de Sousa Jr

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Finite element analysis of RC beams using static experimental data to predict static and dynamic behaviors by Arvindan Sivasuriyan, D. S. Vijayan, Naveen Sankaran, D. Parthiban

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Machine learning to predict killer whale (Orcinus orca) behaviors using partially labeled vocalization data by Sophia Sandholm

“…In a call, an orca typically varies the frequencies, varies the length, varies the temporal patterns, varies their volumes, and can use multiple frequencies simultaneously. Behavior data is hard to obtain because orcas live under water and travel quickly. …”
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