The COVID-19 disease has already spread to more than 213 countries and territories with infected(confirmed)cases of more than 27 million people throughout the world so far,while the numbers keep increasing.In India,th...The COVID-19 disease has already spread to more than 213 countries and territories with infected(confirmed)cases of more than 27 million people throughout the world so far,while the numbers keep increasing.In India,this deadly disease was first detected on January 30,2020,in a student of Kerala who returned from Wuhan.Because of India’s high population density,different cultures,and diversity,it is a good idea to have a separate analysis of each state.Hence,this paper focuses on the comprehensive analysis of the effect of COVID-19 on Indian states and Union Territories and the development of a regression model to predict the number of discharge patients and deaths in each state.The performance of the proposed prediction framework is determined by using three machine learning regression algorithms,namely Polynomial Regression(PR),Decision Tree Regression,and Random Forest(RF)Regression.The results show a comparative analysis of the states and union territories having more than 1000 cases,and the trained model is validated by testing it on further dates.The performance is evaluated using the RMSE metrics.The results show that the Polynomial Regression with an RMSE value of 0.08,shows the best performance in the prediction of the discharged patients.In contrast,in the case of prediction of deaths,Random Forest with a value of 0.14,shows a better performance than other techniques.展开更多
In this paper, the new organization for unit testing embedding pair-wise mode is proposed with the core thought focused on the cooperation of programmer and tester by “cross-testing”. The typical content of unit tes...In this paper, the new organization for unit testing embedding pair-wise mode is proposed with the core thought focused on the cooperation of programmer and tester by “cross-testing”. The typical content of unit testing for the new organizing mode should have three aspects, including self-checking, cross-testing and independent-testing. For cross-testing, executing “pair-wise” mode, mainly tackles data testing, function testing and state testing, which function testing must be done by details and state testing must be considered for completeness. With the specializing of independent-testing, it should be taken as more rigid testing without arbitrariness. Consequently, strategy and measure are addressed for data testing focusing on boundary testing and function/state testing. And organizing method of procedure and key points of tackling unit testing are investigated for the new organizing mode. In order to assess the validity of our study and approach, a series of actual examples are demonstrated for GUI software. The result indicates that the execution of unit testing for the new organizing mode is effective and applicable.展开更多
文摘The COVID-19 disease has already spread to more than 213 countries and territories with infected(confirmed)cases of more than 27 million people throughout the world so far,while the numbers keep increasing.In India,this deadly disease was first detected on January 30,2020,in a student of Kerala who returned from Wuhan.Because of India’s high population density,different cultures,and diversity,it is a good idea to have a separate analysis of each state.Hence,this paper focuses on the comprehensive analysis of the effect of COVID-19 on Indian states and Union Territories and the development of a regression model to predict the number of discharge patients and deaths in each state.The performance of the proposed prediction framework is determined by using three machine learning regression algorithms,namely Polynomial Regression(PR),Decision Tree Regression,and Random Forest(RF)Regression.The results show a comparative analysis of the states and union territories having more than 1000 cases,and the trained model is validated by testing it on further dates.The performance is evaluated using the RMSE metrics.The results show that the Polynomial Regression with an RMSE value of 0.08,shows the best performance in the prediction of the discharged patients.In contrast,in the case of prediction of deaths,Random Forest with a value of 0.14,shows a better performance than other techniques.
文摘In this paper, the new organization for unit testing embedding pair-wise mode is proposed with the core thought focused on the cooperation of programmer and tester by “cross-testing”. The typical content of unit testing for the new organizing mode should have three aspects, including self-checking, cross-testing and independent-testing. For cross-testing, executing “pair-wise” mode, mainly tackles data testing, function testing and state testing, which function testing must be done by details and state testing must be considered for completeness. With the specializing of independent-testing, it should be taken as more rigid testing without arbitrariness. Consequently, strategy and measure are addressed for data testing focusing on boundary testing and function/state testing. And organizing method of procedure and key points of tackling unit testing are investigated for the new organizing mode. In order to assess the validity of our study and approach, a series of actual examples are demonstrated for GUI software. The result indicates that the execution of unit testing for the new organizing mode is effective and applicable.
