Xia Zhou¹, Zijian Wang², Tianyu Wang², Jin Han^2,*, Zhiling Wang², Yannan Qian³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 473-481, 2022, DOI:10.32604/iasc.2022.022493

Abstract User identity recognition is the key shield to protect users’ privacy data from disclosure and embezzlement. The user identity of mobile devices such as mobile phones mainly includes fingerprint recognition, nine-grid password, face recognition, digital password, etc. Due to the requirements of computing resources and convenience of mobile devices, these verification methods have their own shortcomings. In this paper, a user identity recognition technology based on finger trajectory is proposed. Based on the analysis of the users’ finger trajectory data, the feature of the user's finger movement trajectory is extracted to realize the identification of the user. Also, in this… More >

Salman A. Cheema¹, Tanveer Kifayat², Abdu R. Rahman², Umair Khan³, A. Zaib⁴, Ilyas Khan^5,*, Kottakkaran Sooppy Nisar⁶

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1977-1985, 2021, DOI:10.32604/cmc.2020.012096

Abstract The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might… More >