Asymptotic Behaviors of the Lorenz Curve for Left Truncated and Dependent Data by M. Bolbolian Ghalibaf

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Investigating Therapeutic Targets for Alcohol Use Disorder: Pharmacological View of ClinicalTrials.gov Data by Alorfi NM

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Four‐year follow‐up of weight loss maintenance using electronic medical record data: The PROPEL trial by Peter T. Katzmarzyk, Emily F. Mire, Ronald Horswell, San T. Chu, Dachuan Zhang, Corby K. Martin, Robert L. Newton, John W. Apolzan, Eboni G. Price‐Haywood, Dan Fort, Thomas W. Carton, Kara D. Denstel, the PROPEL Research Group

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Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model by Shanshan Wang, Jingwu Liu

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Survey of video behavior recognition by Huilan LUO, Chanjuan WANG, Fei LU

“…Behavior recognition is developing rapidly,and a number of behavior recognition algorithms based on deep network automatic learning features have been proposed.The deep learning method requires a large number of data to train,and requires higher computer storage and computing power.After a brief review of the current popular behavior recognition method based on deep network,it focused on the traditional behavior recognition methods.Traditional behavior recognition methods usually followed the processes of video feature extraction,modeling of features and classification.Following the basic process,the recognition process was overviewed according to the following steps,feature sampling,feature descriptors,feature processing,descriptor aggregation and vector coding.At the same time,the benchmark data set commonly used for evaluating the algorithm performance was also summarized.…”
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Analyzing the Strelitzia Juncea Cellulosic Fibers Mechanical Properties’ Experimental Data Using Various Statistical Methods by Soumia Teyar, Hassina Gheribi, Messaouda Boumaaza, Ahmed Belaadi, Boon Xian Chai, Mahmood M.S. Abdullah, Ibrahim M.H. Alshaikh, Amar Al-Khawlani, Djamel Ghernaout

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Identifying student help-seeking behavior patterns and help-seeking tendencies from student problem-solving and help-seeking behavior data: An educational data mining approach by Chih-Yueh Chou, Wei-Han Chen

“…This study applied an educational data mining approach, including clustering and classification, to analyze students’ problem-solving and help-seeking data in a computer assisted learning system to identify student help-seeking behavior patterns and tendencies. …”
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Urban Environmental Predictors of Group Size in Cliff Swallows (<i>Petrochelidon pyrrhonota</i>): A Test Using Community-Science Data by Cassie Rueda, Kevin J. McGraw

“…The urban heat island effect and shifts in resource availability (e.g., food, water) may also affect colonial birds. Here, we used five years of community-science data available in eBird to investigate urban impacts on group size in Cliff Swallows (<i>Petrochelidon pyrrhonota</i>), an abundant colonial bird species that now breeds readily under bridges and other built structures over or near water in Phoenix, Arizona, USA. …”
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Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data. by Ali Golestani, Nazila Rezaei, Mohammad-Reza Malekpour, Naser Ahmadi, Seyed Mohammad-Navid Ataei, Sepehr Khosravi, Ayyoob Jafari, Saeid Shahraz, Farshad Farzadfar

“…This study aimed to utilize interpretable ML models to predict the occurrence of errors in road accident hotspots using telematics data in Iran and interpret the most influential predictors.…”
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Ensemble-based customer churn prediction in banking: a voting classifier approach for improved client retention using demographic and behavioral data by Ruchika Bhuria, Sheifali Gupta, Upinder Kaur, Salil Bharany, Ateeq Ur Rehman, Seada Hussen, Ghanshyam G. Tejani, Pradeep Jangir

“…Using a comprehensive dataset including demographic, financial, and behavioral data—such as credit score, account balance, tenure, and activity levels—the study employs the goal variable revealing if a customer has left the bank. …”
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Evaluating drivers’ braking behavior at mid-block pedestrian crosswalks using video data and a mixed logit model with heterogeneity in the means by Md Jamil Ahsan, Mohamed Abdel-Aty, Nafis Anwari, Natalia Barbour

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Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data by Ali Golestani, Nazila Rezaei, Mohammad-Reza Malekpour, Naser Ahmadi, Seyed Mohammad-Navid Ataei, Sepehr Khosravi, Ayyoob Jafari, Saeid Shahraz, Farshad Farzadfar

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Quad-Tree-Based Driver Classification Using Deep Learning for Mild Cognitive Impairment Detection by Seyedeh Gol Ara Ghoreishi, Charles Boateng, Sonia Moshfeghi, Muhammad Tanveer Jan, Joshua Conniff, Kwangsoo Yang, Jinwoo Jang, Borko Furht, David Newman, Ruth Tappen, Monica Rosselli, Kelley L. Jackson

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Analyzing customer churn behavior using datamining approach: hybrid support vector machine and logistic regression in retail chain by Mohammad Barzegar, Aliakbar Hasani

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Behavior recognition technology based on deep learning used in pediatric behavioral audiometry by Wen Xie, Chunhua Li, Haisen Peng, Yuehui Liu, Zhilin Zhang, Xiaogang Cheng, Jiali Liu

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AI-Generated Questions in Context: A Contextualized Investigation Using Platform Data, Student Feedback, and Faculty Observations by Rachel Van Campenhout, Benny G. Johnson, Michelle Clark, Melissa Deininger, Shannon Harper, Kelly Odenweller, Erin Wilgenbusch

“…Previous research studies used aggregated data from all questions answered by all students to complete the largest evaluation of the performance metrics for automatically generated questions. …”
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A novel behavioral health care dataset creation from multiple drug review datasets and drugs prescription using EDA by Gantela Prabhakar, George Merlin Linda, Bandi Sudheer Reddy, Samineni Nagamani, Chary Sonkoju Nagarjuna

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ADOPTION OF IOT AND BIG DATA IN SHAPING AND ENHANCING ORGANIZATIONAL CITIZENSHIP BEHAVIOR by Pooja Kanojia, Rupa Khanna Malhotra, Amit Kumar Uniyal, Tannupriya Chaudhary

“…SPSS was used to analyze the data. The relationship between Big data and OCB also, demographic factors, and OCB is not significant. …”
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Air pollution and defensive behavior: Evidence from transaction data in China. by Qingqing Yang, Xinping Dong

“…Using transaction-level data from a large insurance company, covering more than half a million insurance contracts from nineteen cities in China from 2014 to 2018, we empirically imply that an increase of 10% in AQI leads to a 0.37% uptick in the number of daily sales of health insurance contracts by the company within the city. …”
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Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses by İsmail Baydili, Burak Tasci, Gülay Tasci

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