The mathematic theory of Brownian passage-time model and its difference from other recurrence models such as Poisson, lognormal, gamma and Weibull, were introduced. We assessed and analyzed the earthquake probabiliti...The mathematic theory of Brownian passage-time model and its difference from other recurrence models such as Poisson, lognormal, gamma and Weibull, were introduced. We assessed and analyzed the earthquake probabilities of the major faults with the elapsed time much greater than the recurrence interval in the northwest region of Bei- jing (China) in 100-year by using both Brownian passage-time model and Poisson model, and concluded that the calculated results obtained from Brownian passage-time model is more reasonable.展开更多
In this paper, we identify a set of factors that may be used to forecast software productivity and software development time. Software productivity was measured in function points per person hours, and software develo...In this paper, we identify a set of factors that may be used to forecast software productivity and software development time. Software productivity was measured in function points per person hours, and software development time was measured in number of elapsed days. Using field data on over 130 field software projects from various industries, we empirically test the impact of team size, integrated computer aided software engineering (ICASE) tools, software development type, software development platform, and programming language type on the software development productivity and development time. Our results indicate that team size, software development type, software development platform, and programming language type significantly impact software development productivity. However, only team size significantly impacts software development time. Our results indicate that effective management of software development teams, and using different management strategies for different software development type environments may improve software development productivity.展开更多
Floods are the most common type of natural disaster in the world and one of the most damaging.Changes in weather conditions such as precipitation and temperature result in changes in discharge.To better understand the...Floods are the most common type of natural disaster in the world and one of the most damaging.Changes in weather conditions such as precipitation and temperature result in changes in discharge.To better understand the floods and eventually develop a system to predict them,we must analyze in more detail the flow of rivers.The purpose of this article is to analyze the discharges in the upper Senegal River Basin by focusing on determining the limits of the climatic classification according to past discharges.The daily discharges from May 1,1950 to April 30,2018 were chosen as the study period.These flow data have been grouped into annual discharges and classified as very wet,moist,medium,dry and very dry each year.Then,the flow data were divided into two seasons or periods each year:high water and low water.The statistical variables used in this study are the average,the standard deviation,the coefficient of variation and the skewness.The results of the climate classification that corresponds to a log-normal distribution indicate a total of 17 years classified as averages(25%of the series),14 classified as wet(20.6%),29 classified as dry(42.6%)and 8 classified as very wet(11.8%),very dry classifications being nil.Seasonal analysis showed that the months of the high water period,such as September,had the highest flow,and the period of low water,such as May,had the lowest flow.The results of the flow analysis were then compared with changes in rainfall.The results obtained show similar climatic classifications between rainfall and flow in the basin.展开更多
基金Joint Seismological Science Foundation of China (103034) and Key Project ″Assessment of Seismic Safety″ from China Earthquake Administration during the tenth Five-year Plan.
文摘The mathematic theory of Brownian passage-time model and its difference from other recurrence models such as Poisson, lognormal, gamma and Weibull, were introduced. We assessed and analyzed the earthquake probabilities of the major faults with the elapsed time much greater than the recurrence interval in the northwest region of Bei- jing (China) in 100-year by using both Brownian passage-time model and Poisson model, and concluded that the calculated results obtained from Brownian passage-time model is more reasonable.
文摘In this paper, we identify a set of factors that may be used to forecast software productivity and software development time. Software productivity was measured in function points per person hours, and software development time was measured in number of elapsed days. Using field data on over 130 field software projects from various industries, we empirically test the impact of team size, integrated computer aided software engineering (ICASE) tools, software development type, software development platform, and programming language type on the software development productivity and development time. Our results indicate that team size, software development type, software development platform, and programming language type significantly impact software development productivity. However, only team size significantly impacts software development time. Our results indicate that effective management of software development teams, and using different management strategies for different software development type environments may improve software development productivity.
文摘Floods are the most common type of natural disaster in the world and one of the most damaging.Changes in weather conditions such as precipitation and temperature result in changes in discharge.To better understand the floods and eventually develop a system to predict them,we must analyze in more detail the flow of rivers.The purpose of this article is to analyze the discharges in the upper Senegal River Basin by focusing on determining the limits of the climatic classification according to past discharges.The daily discharges from May 1,1950 to April 30,2018 were chosen as the study period.These flow data have been grouped into annual discharges and classified as very wet,moist,medium,dry and very dry each year.Then,the flow data were divided into two seasons or periods each year:high water and low water.The statistical variables used in this study are the average,the standard deviation,the coefficient of variation and the skewness.The results of the climate classification that corresponds to a log-normal distribution indicate a total of 17 years classified as averages(25%of the series),14 classified as wet(20.6%),29 classified as dry(42.6%)and 8 classified as very wet(11.8%),very dry classifications being nil.Seasonal analysis showed that the months of the high water period,such as September,had the highest flow,and the period of low water,such as May,had the lowest flow.The results of the flow analysis were then compared with changes in rainfall.The results obtained show similar climatic classifications between rainfall and flow in the basin.
