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  1. Artikel ; Online: Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia.

    Alboaneen, Dabiah / Pranggono, Bernardi / Alshammari, Dhahi / Alqahtani, Nourah / Alyaffer, Raja

    International journal of environmental research and public health

    2020  Band 17, Heft 12

    Abstract: The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. ...

    Abstract The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.
    Mesh-Begriff(e) Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/epidemiology ; Coronavirus Infections/virology ; Forecasting ; Health Surveys ; Humans ; Models, Biological ; Pandemics ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/virology ; SARS-CoV-2 ; Saudi Arabia/epidemiology
    Schlagwörter covid19
    Sprache Englisch
    Erscheinungsdatum 2020-06-25
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph17124568
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

    Alboaneen, Dabiah / Pranggono, Bernardi / Alshammari, Dhahi / Alqahtani, Nourah / Alyaffer, Raja

    Int. j. environ. res. public health (Online)

    Abstract: The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. ...

    Abstract The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.
    Schlagwörter covid19
    Verlag WHO
    Dokumenttyp Artikel
    Anmerkung WHO #Covidence: #614074
    Datenquelle COVID19

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  3. Artikel ; Online: Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

    Alboaneen, Dabiah / Pranggono, Bernardi / Alshammari, Dhahi / Alqahtani, Nourah / Alyaffer, Raja

    2020  

    Abstract: The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. ...

    Abstract The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.
    Schlagwörter covid19
    Sprache Englisch
    Erscheinungsdatum 2020-06-25
    Verlag MDPI AG
    Erscheinungsland uk
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Human-Computer Interaction Using Manual Hand Gestures in Real Time.

    Alsaffar, Mohammad / Alshammari, Abdullah / Alshammari, Gharbi / Almurayziq, Tariq S / Aljaloud, Saud / Alshammari, Dhahi / Belay, Assaye

    Publikation ZURÜCKGEZOGEN

    Computational intelligence and neuroscience

    2021  Band 2021, Seite(n) 6972192

    Abstract: This paper describes the construction of an electronic system that can recognise twelve manual motions made by an interlocutor with one of their hands in a situation with regulated lighting and background in real time. Hand rotations, translations, and ... ...

    Abstract This paper describes the construction of an electronic system that can recognise twelve manual motions made by an interlocutor with one of their hands in a situation with regulated lighting and background in real time. Hand rotations, translations, and scale changes in the camera plane are all supported by the implemented system. The system requires an Analog Devices ADSP BF-533 Ez-Kit Lite evaluation card. As a last stage in the development process, displaying a letter associated with a recognized gesture is advised. However, a visual representation of the suggested algorithm may be found in the visual toolbox of a personal computer. Individuals who are deaf or hard of hearing will communicate with the general population thanks to new technology that connects them to computers. This technology is being used to create new applications.
    Mesh-Begriff(e) Algorithms ; Computers ; Gestures ; Hand ; Humans ; Motion ; Upper Extremity
    Sprache Englisch
    Erscheinungsdatum 2021-11-28
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Retracted Publication
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2021/6972192
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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