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  1. Article ; Online: A Smartphone Enabled Approach to Manage COVID-19 Lockdown and Economic Crisis.

    Maghdid, Halgurd S / Ghafoor, Kayhan Zrar

    SN computer science

    2020  Volume 1, Issue 5, Page(s) 271

    Abstract: The emergence of novel COVID-19 causes an over-load in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme ...

    Abstract The emergence of novel COVID-19 causes an over-load in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Furthermore, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact-tracing is time-consuming and labor-intensive task which tremendously over-load public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for policymakers on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses k-means algorithm as an unsupervised machine learning technique for lockdown management.
    Keywords covid19
    Language English
    Publishing date 2020-08-14
    Publishing country Singapore
    Document type Journal Article
    ISSN 2661-8907
    ISSN (online) 2661-8907
    DOI 10.1007/s42979-020-00290-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: A Smartphone Enabled Approach to Manage COVID-19 Lockdown and Economic Crisis

    Maghdid, Halgurd S. / Ghafoor, Kayhan Zrar

    SN Computer Science

    2020  Volume 1, Issue 5

    Keywords covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ISSN 2662-995X
    DOI 10.1007/s42979-020-00290-0
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Article: Prediction of global spread of COVID-19 pandemic: a review and research challenges.

    Shah, Saloni / Mulahuwaish, Aos / Ghafoor, Kayhan Zrar / Maghdid, Halgurd S

    Artificial intelligence review

    2021  Volume 55, Issue 3, Page(s) 1607–1628

    Abstract: Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by ... ...

    Abstract Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyze and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modeling tools to the latest artificial intelligence technology, the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response-whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance, including lockdowns. On the one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand, it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt to compile different research methods and comparing their accuracy in predicting the spread of COVID-19.
    Language English
    Publishing date 2021-07-16
    Publishing country England
    Document type Journal Article
    ZDB-ID 1479828-1
    ISSN 1573-7462 ; 0269-2821
    ISSN (online) 1573-7462
    ISSN 0269-2821
    DOI 10.1007/s10462-021-09988-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Order via subito

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  5. Article: A Smartphone enabled Approach to Manage COVID-19 Lockdown and Economic Crisis

    Maghdid, Halgurd S. / Ghafoor, Kayhan Zrar

    Abstract: The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme ...

    Abstract The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Further, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact tracing is time consuming and labor-intensive task which tremendously overload public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for government officials on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses K-means algorithm as an unsupervised machine learning technique for lockdown management.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  6. Book ; Online: A Smartphone enabled Approach to Manage COVID-19 Lockdown and Economic Crisis

    Maghdid, Halgurd S. / Ghafoor, Kayhan Zrar

    2020  

    Abstract: The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme ...

    Abstract The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Further, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact tracing is time consuming and labor-intensive task which tremendously overload public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for government officials on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses K-means algorithm as an unsupervised machine learning technique for lockdown management.
    Keywords Computer Science - Social and Information Networks ; Computer Science - Computers and Society ; Computer Science - Human-Computer Interaction ; covid19
    Subject code 303
    Publishing date 2020-04-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  7. Article: A Smartphone enabled Approach to Manage COVID-19 Lockdown and Economic Crisis

    Halgurd Maghdid S. / Kayhan Ghafoor Zrar

    Abstract: The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme ...

    Abstract The emergence of novel COVID-19 causing an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Further, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact tracing is time consuming and labor-intensive task which tremendously overload public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for government officials on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses K-means algorithm as an unsupervised machine learning technique for lockdown management.
    Keywords covid19
    Publisher arxiv
    Document type Article
    Database COVID19

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  8. Article: A Novel AI-enabled Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study

    Halgurd Maghdid S. / Kayhan Ghafoor Zrar / Ali Sadiq Safaa / Kevin Curran / Khaled Rabie

    Abstract: Coronaviruses are a famous family of viruses that causes illness in human or animals. The new type of corona virus COVID-19 disease was firstly discovered in Wuhan-China. However, recently, the virus has been widely spread in most of the world countries ... ...

    Abstract Coronaviruses are a famous family of viruses that causes illness in human or animals. The new type of corona virus COVID-19 disease was firstly discovered in Wuhan-China. However, recently, the virus has been widely spread in most of the world countries and is reported as a pandemic. Further, nowadays, all the world countries are striving to control the coronavirus disease COVID-19. There are many mechanisms to detect the coronavirus disease COVID-19 including clinical analysis of chest CT scan images and blood test results. The confirmed COVID-19 patient manifests as fever, tiredness, and dry cough. Particularly, several techniques can be used to detect the initial results of the virus such as medical detection Kits. However, such devices are incurring huge cost and it takes time to install them and use. Therefore, in this paper, a new framework is proposed to detect coronavirus disease COVID-19 using onboard smartphone sensors. The proposal provides a low-cost solution, since most of the radiologists have already held smartphones for different daily-purposes. People can use the framework on their smartphones for the virus detection purpose. Nowadays, smartphones are powerful with existing computation-rich processors, memory space, and large number of sensors including cameras, microphone, temperature sensor, inertial sensors, proximity, colour-sensor, humidity-sensor, and wireless chipsets/sensors. The designed Artificial Intelligence (AI) enabled framework reads the smartphone sensors signal measurements to predict the grade of severity of the pneumonia as well as predicting the result of the disease.
    Keywords covid19
    Publisher arxiv
    Document type Article
    Database COVID19

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Book ; Online: Prediction of Global Spread of Covid-19 Pandemic

    Shah, Saloni / Mulahuwaish, Aos / Ghafoor, Kayhan / Maghdid, Halgurd S.

    A Review and Research Challenges

    2020  

    Abstract: ... Since the initial reports of the Coronavirus surfacing in Wuhan, China; the novel virus currently without a cure has spread like a wildfire across the globe. The virus spread exponentially across all inhabited continent; catching local governments by ... ...

    Abstract

    Since the initial reports of the Coronavirus surfacing in Wuhan, China; the novel virus currently without a cure has spread like a wildfire across the globe. The virus spread exponentially across all inhabited continent; catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyse and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modelling tools to latest AI technology; the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response – whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance including lockdowns. On one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt in compiling different research methods and comparing their accuracy in predicting the spread of COVID-19.
    Keywords covid19
    Publisher Institute of Electrical and Electronics Engineers (IEEE)
    Publishing country us
    Document type Book ; Online
    DOI 10.36227/techrxiv.12824378
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  10. Book ; Online: Prediction of Global Spread of Covid-19 Pandemic

    Shah, Saloni / Mulahuwaish, Aos / Ghafoor, Kayhan / Maghdid, Halgurd S.

    A Review and Research Challenges

    2020  

    Abstract: ... Since the initial reports of the Coronavirus surfacing in Wuhan, China; the novel virus currently without a cure has spread like a wildfire across the globe. The virus spread exponentially across all inhabited continent; catching local governments by ... ...

    Abstract

    Since the initial reports of the Coronavirus surfacing in Wuhan, China; the novel virus currently without a cure has spread like a wildfire across the globe. The virus spread exponentially across all inhabited continent; catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyse and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modelling tools to latest AI technology; the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response – whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance including lockdowns. On one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt in compiling different research methods and comparing their accuracy in predicting the spread of COVID-19.
    Keywords covid19
    Publisher Institute of Electrical and Electronics Engineers (IEEE)
    Publishing country us
    Document type Book ; Online
    DOI 10.36227/techrxiv.12824378.v1
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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