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  1. 661
  2. 662

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

    Published 2025-01-01
    “…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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  5. 665

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

    Published 2013-11-01
    “…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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  6. 666

    Peer effects of health behaviors and the moderating role of Internet use among middle-aged and older adults: a nationally representative cross-sectional survey in China by Yanyin Cui, Hongrui Bao, Fang Xia, Liya Zhang, Jie Ren

    Published 2024-10-01
    “…ObjectiveThis study investigates peer effects on the health behaviors of middle-aged and older adult people in China and examines the moderating role of Internet use.MethodsA total of 16,188 respondents were selected from the China Health and Retirement Longitudinal Study (CHARLS) 2020 data set. …”
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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

    Published 2025-08-01
    “…Abstract Peptide-based data storage offers a promising solution to the escalating digital data crisis. …”
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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

    Published 2025-01-01
    “…Validation of the model is achieved using real-world Search and Rescue data to train a Gaussian Process model. …”
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  11. 671

    Factors Influencing the Use of Recommendation Systems for Elderly Research in Thailand by A-Phorn Molee, Wirapong Chansanam

    Published 2025-06-01
    “…Employing an extended the Unified Theory of Acceptance and Use of Technology 2 model, the study investigates system use behavior (SUB) based on seven core factors: Performance expectancy (PEF), effort expectancy (EFF), social influence, personal innovativeness (INN), hedonic motivation (MOT), facilitating conditions (FAC), and intention behavior (IBV), alongside three additional factors—system quality (SQU), information quality (IQU), and trust. …”
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  12. 672

    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

    Published 2022-01-01
    “…In the Internet of things, many data transfer protocols are used for various tasks. …”
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  13. 673

    Financial Technology and Financial Inclusion in Remote Areas of Algeria. Analytical Study Using Data Mining by Hassiba Hadouga

    Published 2023-12-01
    “…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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  14. 674

    Deep Convolutional Neural Network-Based Structural Damage Localization and Quantification Using Transmissibility Data by Sergio Cofre-Martel, Philip Kobrich, Enrique Lopez Droguett, Viviana Meruane

    Published 2019-01-01
    “…Damage diagnosis has become a valuable tool for asset management, enhanced by advances in sensor technologies that allows for system monitoring and providing massive amount of data for use in health state diagnosis. However, when dealing with massive data, manual feature extraction is not always a suitable approach as it is labor intensive requiring the intervention of domain experts with knowledge about the relevant variables that govern the system and their impact on its degradation process. …”
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  15. 675

    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

    Published 2025-03-01
    “…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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  16. 676

    Spatial–Temporal Reconstruction of Trajectories in Free Space Using Automatic Target Position Detection Data by Yang Chen, Xin Chen, Bin Bai, Linjiang Zheng

    Published 2024-12-01
    “…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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    Steady-State Car-Following Time Gaps: An Empirical Study Using Naturalistic Driving Data by Amara Loulizi, Youssef Bichiou, Hesham Rakha

    Published 2019-01-01
    “…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

    Published 2024-06-01
    “…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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