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  • Open Access

    ARTICLE

    Interpretable and Adaptable Early Warning Learning Analytics Model

    Shaleeza Sohail1, Atif Alvi2,*, Aasia Khanum3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3211-3225, 2022, DOI:10.32604/cmc.2022.023560 - 07 December 2021

    Abstract Major issues currently restricting the use of learning analytics are the lack of interpretability and adaptability of the machine learning models used in this domain. Interpretability makes it easy for the stakeholders to understand the working of these models and adaptability makes it easy to use the same model for multiple cohorts and courses in educational institutions. Recently, some models in learning analytics are constructed with the consideration of interpretability but their interpretability is not quantified. However, adaptability is not specifically considered in this domain. This paper presents a new framework based on hybrid statistical More >

  • Open Access

    ARTICLE

    A Rock-fall Early Warning System Based on Logistic Regression Model

    Mohammed Abaker1,*, Abdelzahir Abdelmaboud2, Magdi Osman3, Mohammed Alghobiri4, Ahmed Abdelmotlab4

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 843-856, 2021, DOI:10.32604/iasc.2021.017714 - 20 April 2021

    Abstract The rock-fall is a natural hazard that results in many economic damages and human losses annually, and thus proactive policies to prevent rock-fall hazard are needed. Such policies require predicting the rock-fall occurrence and deciding to alert the road users at the appropriate time. Thus, this study develops a rock-fall early warning system based on logistic regression model. In this system, the logistic regression model is used to predict the rock-fall occurrence. The decision-making algorithm is used to classify the hazard levels and delivers early warning action. This study adopts two criteria to evaluate the More >

  • Open Access

    ARTICLE

    An Early Warning System for Curved Road Based on OV7670 Image Acquisition and STM32

    Xiaoliang Wang1, *, Wenhua Song1, Bowei Zhang1, Brandon Mausler2, Frank Jiang1, 3

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 135-147, 2019, DOI:10.32604/cmc.2019.05687

    Abstract Nowadays, the number of vehicles in China has increased significantly. The increase of the number of vehicles has also led to the increasingly complex traffic situation and the urgent safety measures in need. However, the existing early warning devices such as geomagnetic, ultrasonic and infrared detection have some shortcomings like difficult installation and maintenance. In addition, geomagnetic detection will damage the road surface, while ultrasonic and infrared detection will be greatly affected by the environment. Considering the shortcomings of the existing solutions, this paper puts forward a solution of early warning for vehicle turning meeting More >

  • Open Access

    ARTICLE

    Predicting unplanned readmissions to a pediatric cardiac intensive care unit using predischarge Pediatric Early Warning Scores

    Ashley R. Kroeger1, Jacqueline Morrison2, Andrew H. Smith1

    Congenital Heart Disease, Vol.13, No.1, pp. 98-104, 2018, DOI:10.1111/chd.12525

    Abstract Objective: Unplanned readmission to the pediatric cardiac intensive care unit (CICU) is associated with significant morbidity and mortality. The Pediatric Early Warning Score (PEWS) predicts ward patients at risk for decompensation but has not been previously reported to identify at-risk patients with cardiac disease prior to ward transfer. This study aimed to determine whether PEWS prior to transfer may serve as a predictor of unplanned readmission to the CICU.
    Design: All patients discharged from a tertiary children’s hospital CICU from September 2012 through August 2015 were included for analysis. PEWS assessment was performed following transfer to the… More >

  • Open Access

    ABSTRACT

    Financial early warning system model for hospitals

    A.S. Koyuncugil1, N. Ozgulbas2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.3, pp. 79-80, 2009, DOI:10.3970/icces.2009.011.079

    Abstract The aim of this study is to present the Hospital Early Warning System (HEWS) that developed for determining financial performance and risk indicators of Ministry of Health Hospitals based on automation and in an objective manner with usage of data mining.
    HEWS is an automation system based on Data Mining that hospital manager, Hospital Unions Managers in case of the constitute of hospital unions, Ministry of Health and the other needing ones will use for:
    • determining financial performance of hospitals,
    • detecting financial risks of hospitals,
    • determining financial performance indicators objectively,
    • determining More >

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