Classification of overweight/obesity among Saudi adolescents relative to lifestyle behaviors using the IOTF or WHO reference standards by Hazzaa M. Al-Hazzaa, Hazzaa M. Al-Hazzaa, Amal Alhakami, Ahlam M. Alotaibi, Ahlam M. Alotaibi

“…PurposeTo compare two BMI classifications (the IOTF and WHO references) in assessing overweight/obesity prevalence among Saudi adolescents and to evaluate the ability of the two standards to detect risks of unhealthy lifestyle behaviors.MethodsHealthy Saudi adolescents (15–19 years) were drawn from two data sets (n = 2,263) collected previously in 2009 and 2019, using a random multistage stratified cluster sampling technique. …”
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Discovering action insights from large-scale assessment log data using machine learning by Minyoung Yun, Minjeong Jeon, Heyoung Yang

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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

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Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning by Naadiya Mirbahar, Kamlesh Kumar, Asif Ali Laghari

“…The objective of this study is to recommend apps to university students by category based on app usage patterns. Data was used to evaluate these 806 university students to train the Collaborative Filtering (CF) and Contemporary Deep Learning (DL) models. …”
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APLIKASI MODEL PENERIMAAN TEKNOLOGI DALAM PENGGUNAAN SOFTWARE AUDIT OLEH AUDITOR by Dhini Suryandini

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Analysis of kidney patients and pump failure data using a new unit interval distribution by Tariq S. Alshammari, Khudhayr A. Rashedi

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PARAMETRIC DISTRIBUTION FAMILIES USEFUL FOR MODELLING NON - LIFE INSURANCE PAYMENTS DATA. TAIL BEHAVIOUR by Sandra Teodorescu

“…The present paper describes a series of parametric distributions used for modeling non-life insurance payments data.Of those listed, special attention is paid to the transformed Beta distribution family.This distribution as well as those which are obtained from it(special cases of four-parameter transformed Beta distribution) are used in the modeling of high costs, or even extreme ones.In the literature it follows the tail behaviour of distributions depending on the parameters, because the insurance payments data are tipically highly positively skewed and distributed with large upper tails.In the paper is described the tail behavior of the distribution in the left and right side respectively, and deduced from it, a general case.There are also some graphs of probability density function for one of the transformed Beta family members, which comes to reinforce the comments made.…”
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Evaluating the completeness of electronic health records in dental education: a big data study by Tamanna Tiwari, Maxim Kondratenko, Nihmath Nasiha, Toan Ong, Sangeetha Chandrasekaran, Gary Kostbade, Zachary Giano

“…To better understand how this database can be used for further research, the repository must be analyzed for data quality, such as accuracy, consistency, and completeness. …”
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The impact of the outsourcing ban in Mexico on labor market outcomes. An analysis using worker level data by Fernando Moreno-Contreras, Edwin van Gameren

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High-capacity information storage using peptide-encapsulated hydrogels for long-term data preservation by Benxiang Luo, Songyan Gao, Minghao Wu, Xin Dong, Xiaoyong Deng, Honggang Hu

“…Abstract Peptide-based data storage offers a promising solution to the escalating digital data crisis. …”
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Characterization of Fractured Reservoirs Using a Combination of Downhole Pressure and Self-Potential Transient Data by Yuji Nishi, Tsuneo Ishido

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Predictive Probability Density Mapping for Search and Rescue Using an Agent-Based Approach With Sparse Data by Jan-Hendrik Ewers, David Anderson, Douglas Thomson

“…Validation of the model is achieved using real-world Search and Rescue data to train a Gaussian Process model. …”
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Using IoT Protocols in Real-Time Systems: Protocol Analysis and Evaluation of Data Transmission Characteristics by Andrei Gavrilov, Marlen Bergaliyev, Sergey Tinyakov, Kirill Krinkin, Pavel Popov

“…In the Internet of things, many data transfer protocols are used for various tasks. …”
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Financial Technology and Financial Inclusion in Remote Areas of Algeria. Analytical Study Using Data Mining by Hassiba Hadouga

“…A data mining tool was used to analyze the study data, and the survey participants' K algorithm was later used to predict the behavior patterns of people from a similarly contextualized community regarding financial activities. …”
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Deep Convolutional Neural Network-Based Structural Damage Localization and Quantification Using Transmissibility Data by Sergio Cofre-Martel, Philip Kobrich, Enrique Lopez Droguett, Viviana Meruane

“…For each case study, the models are also validated using experimental data, where results indicate that the proposed approach delivers satisfactory performance and thus being an appropriate tool for damage diagnosis.…”
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Modeling the Dynamics of a Passenger Car Using Experimental Data on Nonlinear Passive Shock Absorbers by Avicenna An-Nizhami, Yusuf Dewantoro Herlambang, Nanang Apriandi, Bono Bono, Friska Ayu Fitrianti Sugiono, Ali Sai'in, Ignatius Gunawan Widodo, Padang Yanuar

“…To capture the nonlinear damping behavior, experimental data from a shock absorber testing apparatus was utilized to derive an empirical formula. …”
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Spatial–Temporal Reconstruction of Trajectories in Free Space Using Automatic Target Position Detection Data by Yang Chen, Xin Chen, Bin Bai, Linjiang Zheng

“…The reconstructed trajectory data can be used for critical applications such as the intent and behavior analysis of key targets in national airspace and ground areas, providing valuable insights into security and safety.…”
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Predicting Missing Values in Survey Data Using Prompt Engineering for Addressing Item Non-Response by Junyung Ji, Jiwoo Kim, Younghoon Kim

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Steady-State Car-Following Time Gaps: An Empirical Study Using Naturalistic Driving Data by Amara Loulizi, Youssef Bichiou, Hesham Rakha

“…Several statistical distributions were used to fit the data of the seven drivers as well as the data for all drivers combined for each speed interval. …”
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Efficient Method of Road Outlier Recognition Using Deep Learning Coupled with Data Augmentation Approach by Sarfaraz Natha, Fareed Ahmed Jokhio, Muhammad Shafique, Naeem Ahmed, Danish Munir Arain

“…Furthermore, we introduced a benchmark real-world Road Outlier Dataset (ROD) containing roads, streets, and highways videos and images that presented different road anomalies performed by vehicles and humans. Experimentation using different pre-trained CNN models i.e., VGG19, InceptionV3, ResNet50, and DenseNet201 with a data augmentation approach has been performed on the ROD dataset. …”
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