As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a loo...As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.展开更多
With observations and reflections on a series of phenomena,such as the ＂independent situation＂of China＇s FDI during the recent global financial risis and the increase of round tripped investment after the ＂tax rat...With observations and reflections on a series of phenomena,such as the ＂independent situation＂of China＇s FDI during the recent global financial risis and the increase of round tripped investment after the ＂tax rate unification,＂this paper examines a unique phenomenon in China＇s FDI-round tripped investment.It reveals its determinants from a micro-perspectiv ,and establishes a vector error correction mode（VECM）for emprirical testing.The results is that the determinants of China＇s round tripped investment are institutional factors such as ＂achievable differential treatment＂ and cpaital control.Tax ,exchange rate,housing price and capital control intensity all have an impact on the scale of round tripped FDI.However,judging from the extent of influence,the most important factor should be exchange rate ,followed by capital control intensity and housing price,and tax has a limited impact.展开更多
Delay to large scale projects, which is as a result of actions or inactions of some project stakeholders, is becoming a global phenomena and Ghana is no exception. The objective of the research is to identify, rate an...Delay to large scale projects, which is as a result of actions or inactions of some project stakeholders, is becoming a global phenomena and Ghana is no exception. The objective of the research is to identify, rate and rank the most significant risk factors that causes delay on projects and examine the social impact of these delays to recommend modalities to help mitigate these risk factors. The study adopted quantitative methods with the distribution of 144 questionnaires to built environment professionals receiving a response rate of 75.7%. The instrument listed 58 common factors under eight categories that contribute to the causes of delay for respondents to rate. Analysis of data non-parametric test revealed that client, contractor, material and finance category factors significantly resulted in the schedule delay of large infrastructural projects. The survey analysis revealed that micro-factors that result in delays to large construction projects are time constraint, cost overrun, payment problems, dispute and litigation. The research recommended the following modalities to minimize such delays： availability of resources, improved communication and coordination, proper scope definition and feasibilities, utilization of modern technology, appropriate application of technologically based systems and competent project management＇s structures.展开更多
基金Project(531107040300) supported by the Fundamental Research Funds for the Central Universities in ChinaProject(2006BAJ04B04) supported by the National Science and Technology Pillar Program during the Eleventh Five-year Plan Period of China
文摘As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.
文摘With observations and reflections on a series of phenomena,such as the ＂independent situation＂of China＇s FDI during the recent global financial risis and the increase of round tripped investment after the ＂tax rate unification,＂this paper examines a unique phenomenon in China＇s FDI-round tripped investment.It reveals its determinants from a micro-perspectiv ,and establishes a vector error correction mode（VECM）for emprirical testing.The results is that the determinants of China＇s round tripped investment are institutional factors such as ＂achievable differential treatment＂ and cpaital control.Tax ,exchange rate,housing price and capital control intensity all have an impact on the scale of round tripped FDI.However,judging from the extent of influence,the most important factor should be exchange rate ,followed by capital control intensity and housing price,and tax has a limited impact.
文摘Delay to large scale projects, which is as a result of actions or inactions of some project stakeholders, is becoming a global phenomena and Ghana is no exception. The objective of the research is to identify, rate and rank the most significant risk factors that causes delay on projects and examine the social impact of these delays to recommend modalities to help mitigate these risk factors. The study adopted quantitative methods with the distribution of 144 questionnaires to built environment professionals receiving a response rate of 75.7%. The instrument listed 58 common factors under eight categories that contribute to the causes of delay for respondents to rate. Analysis of data non-parametric test revealed that client, contractor, material and finance category factors significantly resulted in the schedule delay of large infrastructural projects. The survey analysis revealed that micro-factors that result in delays to large construction projects are time constraint, cost overrun, payment problems, dispute and litigation. The research recommended the following modalities to minimize such delays： availability of resources, improved communication and coordination, proper scope definition and feasibilities, utilization of modern technology, appropriate application of technologically based systems and competent project management＇s structures.
