Purpose： The purpose of this study was to develop and validate a method that would facilitate immediate feedback on linear hammer speed during training. Methods： Three-dimensional hammer head positional data were me...Purpose： The purpose of this study was to develop and validate a method that would facilitate immediate feedback on linear hammer speed during training. Methods： Three-dimensional hammer head positional data were measured and used to calculate linear speed （calculated speed） and cable force. These data were used to develop two linear regression models （shifted and non-shifted） that would allow prediction of hammer speed from measured cable force data （predicted speed）. The accuracy of the two models was assessed by comparing the predicted and calculated speeds. Averages of the coefficient of multiple correlation （CMC） and the root mean square （RMS） of the difference between the predicted and calculated speeds for each throw of each participant were used to assess the level of accuracy of the predicted speeds. Results： Both regression models had high CMC values （0.96 and 0.97） and relatively low RMS values （1.27 m/s and 1.05 m/s） for the non-shifted and shifted models, respectively. In addition, the average percentage differences between the predicted and calculated speeds were 6.6% and 4.7% for the non-shifted and shifted models, respectively. The RMS differences between release speeds attained via the two regression models and those attained via three-dimensional positional data were also computed. The RMS differences between the predicted and calculated release speeds were 0.69 m/s and 0.46 m/s for the non-shifted and shifted models, respectively. Conclusion： This study successfully derived and validated a method that allows prediction of linear hammer speed from directly measured cable force data. Two linear regression models were developed and it was found that either model would be capable of predicting accurate speeds. However, data predicted using the shifted regression model were more accurate.展开更多
The aim of this research was to value, using a multiple regression model, the role of knowledge to guarantee the development in rural areas of European Union countries over 10 years. The main question was to find out ...The aim of this research was to value, using a multiple regression model, the role of knowledge to guarantee the development in rural areas of European Union countries over 10 years. The main question was to find out relationships among some variable, as the percentage of national Gross Domestic Product （GDP） used to improve the high training, and rural development in terms of agricultural labour units. The results underlined in 2001 as an high value of rural development, in terms of working force in agriculture, was identified in some countries of European Union characterised by a low value both in high training investments and also by a low value of Human Development Index, according to the definition of The Economist. The results in 2010 pointed out an inverse correlation among the dependent variable development in rural areas and the independent variables per capita GDP and national expenditure in advanced training, in percentage of national GDP. The learning by doing and by using, the introduction of advanced training in agriculture, using Long Life Learning measures of European Union, are important to improve the development of European rural areas but, sometimes, these actions are not perceived as something of useful.展开更多
文摘Purpose： The purpose of this study was to develop and validate a method that would facilitate immediate feedback on linear hammer speed during training. Methods： Three-dimensional hammer head positional data were measured and used to calculate linear speed （calculated speed） and cable force. These data were used to develop two linear regression models （shifted and non-shifted） that would allow prediction of hammer speed from measured cable force data （predicted speed）. The accuracy of the two models was assessed by comparing the predicted and calculated speeds. Averages of the coefficient of multiple correlation （CMC） and the root mean square （RMS） of the difference between the predicted and calculated speeds for each throw of each participant were used to assess the level of accuracy of the predicted speeds. Results： Both regression models had high CMC values （0.96 and 0.97） and relatively low RMS values （1.27 m/s and 1.05 m/s） for the non-shifted and shifted models, respectively. In addition, the average percentage differences between the predicted and calculated speeds were 6.6% and 4.7% for the non-shifted and shifted models, respectively. The RMS differences between release speeds attained via the two regression models and those attained via three-dimensional positional data were also computed. The RMS differences between the predicted and calculated release speeds were 0.69 m/s and 0.46 m/s for the non-shifted and shifted models, respectively. Conclusion： This study successfully derived and validated a method that allows prediction of linear hammer speed from directly measured cable force data. Two linear regression models were developed and it was found that either model would be capable of predicting accurate speeds. However, data predicted using the shifted regression model were more accurate.
文摘The aim of this research was to value, using a multiple regression model, the role of knowledge to guarantee the development in rural areas of European Union countries over 10 years. The main question was to find out relationships among some variable, as the percentage of national Gross Domestic Product （GDP） used to improve the high training, and rural development in terms of agricultural labour units. The results underlined in 2001 as an high value of rural development, in terms of working force in agriculture, was identified in some countries of European Union characterised by a low value both in high training investments and also by a low value of Human Development Index, according to the definition of The Economist. The results in 2010 pointed out an inverse correlation among the dependent variable development in rural areas and the independent variables per capita GDP and national expenditure in advanced training, in percentage of national GDP. The learning by doing and by using, the introduction of advanced training in agriculture, using Long Life Learning measures of European Union, are important to improve the development of European rural areas but, sometimes, these actions are not perceived as something of useful.
