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Analysis of Covid-19 Virus Spreading Statistics by the Use of a New Modified Weibull Distribution

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Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact

Abstract

Since the World Health Organization has declared Coronavirus a pandemic, researchers have given several interpretations on how this virus is spreads. In the present work, in anticipation of substantial fatal effects on health of people following this human-to-human spread, we aim to propose a new six parameter-modified Weibull distribution to analyze the spread of Covid-19 virus. We apply this model to study the cumulative cases infected in some countries, we give a global analysis of the statistical data of the pandemic, and we prove that our new distribution efficiently generalizes some existing models and fits correctly some data registered from February to June 2020. We use these results to assess the potential for human-to-human spread to occur around the globe.

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References

  1. http://www.sehhty.com/

  2. Gondauri, D., Mikautadze, E., Batiashvili, M.: Research on COVID-19 Virus spreading statistics based on the examples of the cases from different countries. Electron. J. Gen. Med. 17, 1–4 (2020)

    Google Scholar 

  3. Li, L., Yang, Z., Dang, Z., Meng, C., Huang, J., Meng, H., Wang, D., Chen, G., Zhang, J., Peng, H., Shao, Y.: Propagation analysis and prediction of the COVID-19. Infect. Dis. Model. 5, 282–292 (2020)

    Google Scholar 

  4. Corman, V.M., Landt, O., Kaiser, M., et al.: Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill. 25(3), 2000045 (2020)

    Article  Google Scholar 

  5. Hui, D.S., Azhar, E.I., Madani, T.A., et al.: The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health-the latest 2019 novel coronavirus outbreak in Wuhan. China. Int. J. of Infect. Dis. 91, 264–266 (2020)

    Article  Google Scholar 

  6. Mizumoto, K., Chowell, G.: Transmission potential of the novel coronavirus (COVID-19) onboard the diamond Princess Cruises Ship. Infect. Dis. Model. 5, 264–270 (2020)

    Google Scholar 

  7. Riou, J., Althauss, C.L.: Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Euro Surveill. 25(4), 2000058 (2020)

    Article  Google Scholar 

  8. Shao, Y., Wu, J.: IDM editorial statement on the 2019-nCoV. Infect. Dis. Model. 5, 233–234 (2020)

    Google Scholar 

  9. Zhu, N., Zhang, D., Wang, W., et al.: A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med. 382, 727–733 (2020)

    Article  Google Scholar 

  10. Wu, J.T., Leung, G.M.: Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet 395, 689–697 (2020)

    Article  Google Scholar 

  11. He, F., Deng, Y., Li, W.: Coronavirus Disease 2019 (COVID-2019): What we know? J. Med. Virol. 92, 719–725 (2020)

    Article  Google Scholar 

  12. Lu, R., Zhao, X., Wang, Li. J, et al.: Grnomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 395, 565–574 (2020)

    Google Scholar 

  13. Zhou, P., Yang, X.L., Wang, X.G., et al.: A pneumonia outbreak associated with a new coronovirus of probable bat origin. Nature 579, 270–273 (2020)

    Article  Google Scholar 

  14. Weibull, W.A.: Statistical distribution function of wide applicability. J. App. Mech. 18, 293–296 (1951)

    Article  Google Scholar 

  15. Bailey, R.L., Dell, T.R.: Quantifying diameter distributions with the Weibul function. For. Sci. 19, 97–104 (1973)

    Google Scholar 

  16. Murthy, D.N.P., Xie, M., Jiang. R.: Weibull Models. Wiley, New York (2013)

    Google Scholar 

  17. Bebbingtom, M.S., Lai, C.D., Zitikis, R.: A flexible Weibull extension. Reliab. Eng. Sys. Safe. 92, 719–726 (2007)

    Article  Google Scholar 

  18. Zhang, T., Xie, M., Zitikis, R.: On the upper truncated Weibull distribution and its reliability implications. Reliab. Eng. Sys. Safe. 92, 194–200 (2011)

    Article  Google Scholar 

  19. Bain, L.J.: Analysis for the linear feailure-rate life-testing distribution. Technometrics. 42, 299–302 (1993)

    Google Scholar 

  20. Mudholkar, G.S., Srivastava. D.K.: Exponentiated Weibull family for analysing bathtub failure rate data. IEEE T. Reliab. 42, 299–302 (1993)

    Google Scholar 

  21. Marshall, A.W., Olkin. I.: A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families. Biometrika. 84, 641–652 (1997)

    Google Scholar 

  22. Remolls, K., Geary, D.N., Rollinson, T.J.D.: Characterizing diameter distributions by the use of the Weibull distribution. Foresty. 58, 57–66 (1985)

    Article  Google Scholar 

  23. Maltamo, M.: Comparing basal area diameter distributions estimated by tree species and for the entire growing stock in a mixed stand. Silva Fenn. 31, 53–65 (1996)

    Google Scholar 

  24. Xie, M., Tang, Y., Goh, T.N.: A modified Weibull extension with bathtub-shaped failure rate function. Reliab. Eng. Sys. Safe. 76, 279–285 (2002)

    Article  Google Scholar 

  25. Xie, M., Lai, C.D.: Reliability analysis using an additive Weibull model with bathtub-shaped failure ratefunction. Reliab. Eng. Sys. Safe. 52, 87–93 (1995)

    Article  Google Scholar 

  26. Sarhan, A.M., Zaindin, M.: Modified Weibull distribution. Appl. Sci. 11, 123–136 (2009)

    MathSciNet  MATH  Google Scholar 

  27. Famoye, F., Lee, C., Olumolade, O.: The beta-Weibull distribution. JSTA 4, 121–136 (2005)

    MathSciNet  Google Scholar 

  28. Shahbaz, M.Q., Shahbaz, S., Butt, N.S.: The Kumaraswamy-inverse weibull distribution. PAK. J. Sta. Oper. Res. 8, 479–489 (2012)

    Article  MathSciNet  Google Scholar 

  29. Ahmad, Z., Iqbal, B.: Generalized flexible Weibull extension distribution. Circ. Comput. Sci. 2, 68–75 (2017)

    Google Scholar 

  30. Ahmad, Z., Hussain, Z.: New extended weibull distribution. Circ. Comput. Sci. 2, 14–19 (2017)

    Google Scholar 

  31. Khan, M.S., King, R.: Transmuted modified Weibull distribution: a generalization of the modified Weibull probability distribution. Eur. J. Pure appl. Math. 6, 66–88 (2013)

    MathSciNet  MATH  Google Scholar 

  32. Phani, K.K.: A new modified Weibull distribution function. J. Am. Ceram. Soc. 70, 182–184 (1987)

    Google Scholar 

  33. Silva, G.O., Ortega, E.M., Cordeiro, G.M.: The beta modified Weibull distribution. Lifetime Data Anal. 16, 409–430 (2010)

    Article  MathSciNet  Google Scholar 

  34. Singla, N., Jain, K., Kumar, Sharma S.: The beta generalized Weibull distribution: properties and applications. Reliab. Eng. Sys. Safe. 102, 5–15 (2012)

    Google Scholar 

  35. Exponentiated generalized linea exponential distribution: Sarhan, A. M., Abd EL-Baset, A A., Alasbahi, I. A. Appl. Math. Model. 37, 2838–2849 (2013)

    Google Scholar 

  36. Almalki, S.J., Yuan, J.: A new modified Weibull distribution. Reliab. Eng. Sys. Safe. 111, 164–170 (2013)

    Article  Google Scholar 

  37. Abd EL-Baset, A.A., Ghazal, M.G.M.: Exponentiated additive Weibull distribution. Reliab. Eng. Sys. Safe. 193, 106663 (2020)

    Google Scholar 

  38. He, B., Cui, W., Du, X.: An additive modified Weibull distribution. Reliab. Eng. Sys. Safe. 145, 28–37 (2016)

    Article  Google Scholar 

  39. Ashour, S.K., Eltehiwy, M.A.: Transmuted exponentiated modified Weibull distribution. IJBAS 2, 258–269 (2013)

    Google Scholar 

  40. Arnold, B.C., Balakrishnan, N., Nagaraja, H.N.: A first course in order statistics. Society for Industrial and Applied Mathematics (2008)

    Google Scholar 

  41. Gradshteyn, I.S., Ryzhik, I.M.: Table of Integrals, Series, and Products, 5th edn. Academic Press, New York (1994)

    MATH  Google Scholar 

  42. Al-Fawzan, M.A.: Methods for estimating the parameters of the Weibull distribution. (2000) (Unpublish) King Abdulaziz City for Science and Technology, Saudi Arabia

    Google Scholar 

  43. Fisher, R.A.: On the mathematical foundations of theoretical statistics. Philos. Trans. R. Soc. A 222, 309–368 (1922)

    MATH  Google Scholar 

  44. Lawless, J.F.: Statistical Models and Methods for Lifetime Data, vol. 20, pp. 1108–1113. John Wiley and Sons, New York (2003)

    Google Scholar 

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Appendix

Appendix

All the second partial derivatives of the log-likelihood function are obtained in this appendix as follows

$$\begin{aligned} {{\mathcal {L}}_{\alpha \alpha }}=-\sum \limits _{i=1}^{n}{\frac{h_{\alpha }^{2}}{{{h}^{2}}}}+2\lambda \sum \limits _{i=1}^{n}{t_{i}^{2\theta }}{{h}_{S\lambda }}, \end{aligned}$$
(74)
$$\begin{aligned} {{\mathcal {L}}_{\beta \beta }}=-\sum \limits _{i=1}^{n}{\frac{h_{\beta }^{2}}{{{h}^{2}}}}+2\lambda \sum \limits _{i=1}^{n}{t_{i}^{2\gamma }{{e}^{2\chi {{t}_{i}}}}}{{h}_{S\lambda }}, \end{aligned}$$
(75)
$$\begin{aligned} {{\mathcal {L}}_{\theta \theta }}=\sum \limits _{i=1}^{n}{\frac{\left( {{h}_{\theta \theta }}h-{{\alpha }^{2}}h_{\alpha \theta }^{2} \right) }{{{h}^{2}}}}-\alpha \sum \limits _{i=1}^{n}t_{i}^{\theta }{{{\ln }^{2}}\left( {{t}_{i}} \right) }-2\alpha \lambda \sum \limits _{i=1}^{n}t_{i}^{\theta }h_{S\lambda }^{\alpha }{\ln \left( {{t}_{i}} \right) }, \end{aligned}$$
(76)
$$\begin{aligned} {{\mathcal {L}}_{\gamma \gamma }}=\sum \limits _{i=1}^{n}{\frac{\left( {{h}_{\gamma \gamma }}h-{{\beta }^{2}}h_{\beta \gamma }^{2} \right) }{{{h}^{2}}}}-\beta \sum \limits _{i=1}^{n}{t_{i}^{\gamma }}{{e}^{\chi {{t}_{i}}}}{{\ln }^{2}}({{t}_{i}})-2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}}h_{S\lambda }^{\beta \chi }{{\ln }^{2}}({{t}_{i}}), \end{aligned}$$
(77)
$$\begin{aligned} {{\mathcal {L}}_{\chi \chi }}=\sum \limits _{i=1}^{n}{\frac{\left( {{h}_{\chi \chi }}h-h_{\beta \chi }^{2} \right) }{{{h}^{2}}}}-\beta \sum \limits _{i=1}^{n}{t_{i}^{\gamma +2}}{{e}^{\chi {{t}_{i}}}}-2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma +2}{{e}^{\chi {{t}_{i}}}}}h_{S\lambda }^{\beta \chi }, \end{aligned}$$
(78)
$$\begin{aligned} {{\mathcal {L}}_{\lambda \lambda }}=-\sum \limits _{i=1}^{n}{h_{\lambda }^{2}}, \end{aligned}$$
(79)
$$\begin{aligned} {{\mathcal {L}}_{\theta \alpha }}=\sum \limits _{i=1}^{n}{\frac{\left( {{h}_{\alpha \theta }}h-\alpha {{h}_{\alpha \theta }}{{h}_{\alpha }} \right) }{{{h}^{2}}}}-\sum \limits _{i=1}^{n}{t_{i}^{\theta }\ln \left( {{t}_{i}} \right) }-2\lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta }h_{S\lambda }^{\alpha },} \end{aligned}$$
(80)
$$\begin{aligned} {{\mathcal {L}}_{\beta \alpha }}=-\sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha }}{{h}_{\beta }}}{{{h}^{2}}}+2\lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma }{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}}}, \end{aligned}$$
(81)
$$\begin{aligned} {{\mathcal {L}}_{\gamma \alpha }}=-\beta \sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha }}{{h}_{\beta \gamma }}}{{{h}^{2}}}+2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma }{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}\ln \left( {{t}_{i}} \right) }}, \end{aligned}$$
(82)
$$\begin{aligned} {{\mathcal {L}}_{\chi \alpha }}=-\sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha }}{{h}_{\beta \chi }}}{{{h}^{2}}}+2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma +1}{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}}}, \end{aligned}$$
(83)
$$\begin{aligned} {{\mathcal {L}}_{\lambda \alpha }}=-2\sum \limits _{i=1}^{n}{t_{i}^{\theta }\frac{{{e}^{S}}}{S_{\lambda }^{2}}}, \end{aligned}$$
(84)
$$\begin{aligned} {{\mathcal {L}}_{\theta \beta }}=-\alpha \sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha \theta }}{{h}_{\beta }}}{{{h}^{2}}}+2\alpha \lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma }{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}\ln \left( {{t}_{i}} \right) }}, \end{aligned}$$
(85)
$$\begin{aligned} {{\mathcal {L}}_{\gamma \theta }}=-\alpha \beta \sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha \theta }}{{h}_{\beta \gamma }}}{{{h}^{2}}}+2\alpha \beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma }{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}{{\ln }^{2}}\left( {{t}_{i}} \right) }}, \end{aligned}$$
(86)
$$\begin{aligned} {{\mathcal {L}}_{\chi \theta }}=-\alpha \sum \limits _{i=1}^{n}{\frac{{{h}_{\alpha \theta }}{{h}_{\beta \chi }}}{{{h}^{2}}}+2\alpha \beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\theta +\gamma +1}{{e}^{\chi {{t}_{i}}}}{{h}_{S\lambda }}\ln \left( {{t}_{i}} \right) }}, \end{aligned}$$
(87)
$$\begin{aligned} {{\mathcal {L}}_{\lambda \theta }}=-2\alpha \sum \limits _{i=1}^{n}{t_{i}^{\theta }\frac{{{e}^{S}}}{S_{\lambda }^{2}}\ln \left( {{t}_{i}} \right) }, \end{aligned}$$
(88)
$$\begin{aligned} {{\mathcal {L}}_{\gamma \beta }}=\sum \limits _{i=1}^{n}{{{h}_{\beta \gamma }}\frac{\left( h-\beta {{h}_{\beta }} \right) }{{{h}^{2}}}}-\sum \limits _{i=1}^{n}{t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}\ln \left( {{t}_{i}} \right) }-2\lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}h_{S\lambda }^{\beta \chi }\ln \left( {{t}_{i}} \right) }, \end{aligned}$$
(89)
$$\begin{aligned} {{\mathcal {L}}_{\chi \beta }}=\sum \limits _{i=1}^{n}{\frac{\left( {{h}_{\chi \gamma }}h-{{h}_{\beta \chi }}{{h}_{\beta }} \right) }{{{h}^{2}}}}-\sum \limits _{i=1}^{n}{t_{i}^{\gamma +1}}{{e}^{\chi {{t}_{i}}}}-2\lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma +1}{{e}^{\chi {{t}_{i}}}}}h_{S\lambda }^{\beta \chi }, \end{aligned}$$
(90)
$$\begin{aligned} {{\mathcal {L}}_{\lambda \beta }}=-2\sum \limits _{i=1}^{n}{t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}h_{S}^{\lambda }}, \end{aligned}$$
(91)
$$\begin{aligned} \begin{aligned}&{{\mathcal {L}}_{\chi \gamma }}=\beta \sum \limits _{i=1}^{n}{\frac{\left( h_{\beta \gamma }^{\chi }h-{{h}_{\beta \chi }}{{h}_{\beta \gamma }} \right) }{{{h}^{2}}}}-\beta \sum \limits _{i=1}^{n}{t_{i}^{\gamma +1}{{e}^{\chi {{t}_{i}}}}\ln \left( {{t}_{i}} \right) } \\&\,\,\,\,\,\,\,\,\,\,\,\,-2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma +1}{{e}^{\chi {{t}_{i}}}}h_{S\lambda }^{\beta \chi }\ln \left( {{t}_{i}} \right) },\\ \end{aligned} \end{aligned}$$
(92)
$$\begin{aligned} {{\mathcal {L}}_{\lambda \gamma }}=-2\beta \sum \limits _{i=1}^{n}{t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}h_{S}^{\lambda }\ln \left( {{t}_{i}} \right) }, \end{aligned}$$
(93)

and

$$\begin{aligned} {{\mathcal {L}}_{\lambda \chi }}=2\beta \lambda \sum \limits _{i=1}^{n}{t_{i}^{\gamma +1}{{e}^{\chi {{t}_{i}}}}\frac{{{e}^{S}}}{S_{\lambda }^{2}}}, \end{aligned}$$
(94)

where

$$\begin{aligned} {{h}_{\alpha }}=\theta t_{i}^{\theta -1}, \end{aligned}$$
(95)
$$\begin{aligned} {{h}_{S\lambda }}=\frac{\left( {{S}_{\lambda }}-2\lambda {{e}^{S}} \right) {{e}^{S}}}{S_{\lambda }^{2}}, \end{aligned}$$
(96)
$$\begin{aligned} {{h}_{\beta }}=\left( \gamma +\chi {{t}_{i}} \right) t_{i}^{\gamma -1}{{e}^{\chi {{t}_{i}}}}, \end{aligned}$$
(97)
$$\begin{aligned} {{h}_{\beta \gamma }}={{e}^{\chi {{t}_{i}}}}t_{i}^{\gamma -1}\left[ 1+\left( \gamma +\chi {{t}_{i}} \right) \ln \left( {{t}_{i}} \right) \right] , \end{aligned}$$
(98)
$$\begin{aligned} {{h}_{\chi \chi }}=\beta t_{i}^{\gamma +1}{{e}^{\chi {{t}_{i}}}}\left( 2+\gamma +\chi {{t}_{i}} \right) , \end{aligned}$$
(99)
$$\begin{aligned} {{h}_{\gamma \gamma }}=\beta {{e}^{\chi {{t}_{i}}}}t_{i}^{\gamma -1}\left[ 2+\left( \gamma +\chi {{t}_{i}} \right) \ln \left( {{t}_{i}} \right) \right] \ln \left( {{t}_{i}} \right) , \end{aligned}$$
(100)
$$\begin{aligned} {{h}_{\alpha \theta }}=t_{i}^{\theta -1}\left( 1+\theta \ln \left( {{t}_{i}} \right) \right) , \end{aligned}$$
(101)
$$\begin{aligned} {{h}_{\theta \theta }}=\alpha t_{i}^{\theta -1}\left( 2+\theta \ln \left( {{t}_{i}} \right) \right) \ln \left( {{t}_{i}} \right) , \end{aligned}$$
(102)
$$\begin{aligned} h_{S\lambda }^{p\chi }=\frac{\left[ {{S}_{\lambda }}-pt_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}\left( {{S}_{\lambda }}-2\lambda {{e}^{S}} \right) \right] {{e}^{S}}}{S_{\lambda }^{2}}, \end{aligned}$$
(103)
$$\begin{aligned} h_{S\lambda }^{p}=\frac{\left[ {{S}_{\lambda }}-pt_{i}^{\theta }\left( {{S}_{\lambda }}-2\lambda {{e}^{S}} \right) \right] {{e}^{S}}\ln \left( {{t}_{i}} \right) }{S_{\lambda }^{2}}, \end{aligned}$$
(104)
$$\begin{aligned} {{h}_{\beta \chi }}=\beta t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}\left( 1+\gamma +\chi {{t}_{i}} \right) , \end{aligned}$$
(105)
$$\begin{aligned} {{h}_{\chi \gamma }}=t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}\left[ 1+\left( \gamma +\chi {{t}_{i}} \right) \right] , \end{aligned}$$
(106)
$$\begin{aligned} {{h}_{\lambda }}=\frac{\left( {{S}_{\lambda }}-1 \right) }{\lambda {{S}_{\lambda }}}, \end{aligned}$$
(107)
$$\begin{aligned} {{h}_{S}}=\frac{\left( 2{{e}^{S}}-1 \right) {{e}^{S}}}{S_{\lambda }^{2}}, \end{aligned}$$
(108)
$$\begin{aligned} h_{S}^{\lambda }=\frac{\left[ {{S}_{\lambda }}-\lambda \left( 2{{e}^{S}}-1 \right) \right] {{e}^{S}}}{S_{\lambda }^{2}} \end{aligned}$$
(109)

and

$$\begin{aligned} h_{\beta \gamma }^{\chi }=t_{i}^{\gamma }{{e}^{\chi {{t}_{i}}}}\left[ 1+\ln \left( {{t}_{i}} \right) +\left( \gamma +\chi {{t}_{i}} \right) \ln \left( {{t}_{i}} \right) \right] . \end{aligned}$$
(110)

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Belafhal, A., Chib, S., Usman, T. (2021). Analysis of Covid-19 Virus Spreading Statistics by the Use of a New Modified Weibull Distribution. In: Agarwal, P., Nieto, J.J., Ruzhansky, M., Torres, D.F.M. (eds) Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact. Infosys Science Foundation Series(). Springer, Singapore. https://doi.org/10.1007/978-981-16-2450-6_8

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