This paper presents an investigation to evaluate the reading speed and reading comprehension of non-native English speaking students by presenting a simple analytical model. For this purpose, various readability softw...This paper presents an investigation to evaluate the reading speed and reading comprehension of non-native English speaking students by presenting a simple analytical model. For this purpose, various readability softwares were used to estimate the average grade level of the given texts. The relationship between the score obtained by the students and their reading speed under average grade level 9 and 14 using font size 12 and 14 is presented. The experimental results show that the reading speed and the score versus the students may be explained by a linear regression. Reading speed decreases as the score decreases. The students with a higher magnitude of reading speed scored better marks. More importantly, we find that the reading speed of our students is lower than the native English speakers. This approach of modeling the readability in linear form significantly simplifies the readability analysis.展开更多
In this investigation the electricity generation and the electricity capacity of energy mix for sub Saharan Africa from 2020 to 2040 including CO2 emission from (coal, oil, gas) (Total Final Consumption, transport) an...In this investigation the electricity generation and the electricity capacity of energy mix for sub Saharan Africa from 2020 to 2040 including CO2 emission from (coal, oil, gas) (Total Final Consumption, transport) and power generation were analyzed. These energy sources include conventional and renewable energy sources such as coal, oil, gas, hydro, nuclear, bioenergy, solar PV, and other renewables. We developed a linear regression equation based on the least-square method of estimation to forecast the value of energy and CO2 emission. We fit a linear trend to the energy time series including CO2 emission to show how simple linear regression analysis can be used to forecast future value. The predicted results from 2020 to 2040 show that the electricity capacity and the electricity generation from gas, hydro, solar PV and other renewables will dominate compared to nuclear and bioenergy. Some forms of energies contributions such as nuclear and bioenergy will remain insignificant. The gas will continue to emit a lot carbon dioxide compared to the emission from oil and coal. The emission of CO2 from total final consumption (TFC) of oil will be high compared to its emission from power generation (PG) and transport. The least squares estimated regression equation adequately describes the relationship between Energy or CO2 emission and time period with a high R-squared. This approach of modeling in a linear regression, the energy and CO2 emission simplifies significantly the analysis to help policy makers underlying reasons for the trends to develop appropriate strategies for the future, may be useful to assess the sustained economic development and transformation that require a definition of electricity access in those countries.展开更多
文摘This paper presents an investigation to evaluate the reading speed and reading comprehension of non-native English speaking students by presenting a simple analytical model. For this purpose, various readability softwares were used to estimate the average grade level of the given texts. The relationship between the score obtained by the students and their reading speed under average grade level 9 and 14 using font size 12 and 14 is presented. The experimental results show that the reading speed and the score versus the students may be explained by a linear regression. Reading speed decreases as the score decreases. The students with a higher magnitude of reading speed scored better marks. More importantly, we find that the reading speed of our students is lower than the native English speakers. This approach of modeling the readability in linear form significantly simplifies the readability analysis.
文摘In this investigation the electricity generation and the electricity capacity of energy mix for sub Saharan Africa from 2020 to 2040 including CO2 emission from (coal, oil, gas) (Total Final Consumption, transport) and power generation were analyzed. These energy sources include conventional and renewable energy sources such as coal, oil, gas, hydro, nuclear, bioenergy, solar PV, and other renewables. We developed a linear regression equation based on the least-square method of estimation to forecast the value of energy and CO2 emission. We fit a linear trend to the energy time series including CO2 emission to show how simple linear regression analysis can be used to forecast future value. The predicted results from 2020 to 2040 show that the electricity capacity and the electricity generation from gas, hydro, solar PV and other renewables will dominate compared to nuclear and bioenergy. Some forms of energies contributions such as nuclear and bioenergy will remain insignificant. The gas will continue to emit a lot carbon dioxide compared to the emission from oil and coal. The emission of CO2 from total final consumption (TFC) of oil will be high compared to its emission from power generation (PG) and transport. The least squares estimated regression equation adequately describes the relationship between Energy or CO2 emission and time period with a high R-squared. This approach of modeling in a linear regression, the energy and CO2 emission simplifies significantly the analysis to help policy makers underlying reasons for the trends to develop appropriate strategies for the future, may be useful to assess the sustained economic development and transformation that require a definition of electricity access in those countries.
