Soil infiltration capability is the hot spot topic of soil erosion studies and soil physical and chemical properties have great influence on it. A new infiltration method point- source infiltration method was used to ...Soil infiltration capability is the hot spot topic of soil erosion studies and soil physical and chemical properties have great influence on it. A new infiltration method point- source infiltration method was used to precisely evaluate the infiltration capability in different purple soil land- use types. And correlation analysis on soil physical and chemical properties and soil infiltration capability of different land- use types was performed. Results showed that:( i) there is a large difference among soil physical and chemical properties in different land- use types,soil water content,non- capillary porosity,capillary porosity,content of > 0. 25 mm aggregates and organic matter content in the top soil are greater than those in the subsoil;( ii) soil infiltration capability showed differences among different land- use types. Land use showed great effects,in general,the order of decrease on initial infiltration rate and average infiltration rate was: woodland slope > slope farmland >grassland,the order of decrease on steady infiltration rate was: slope farmland > woodland > grassland and the time reaching stable state was:slope farmland > woodland > grassland;( iii) correlation analysis showed that there was a significantly positive correlation between initial infiltration rate and wet sieve MWD value and structural damage rate,and it had a significantly negative correlation with capillary porosity;( iv)steady infiltration rate and non- capillary porosity showed the significantly positive correlation,and it had a significantly negative correlation with the soil bulk density;( v) the average infiltration rate and non- capillary porosity and structural damage rate showed a positive correlation and the correlation coefficient was large and there was a negative correlation between average infiltration rate and soil bulk density and capillary porosity,and the absolute value of correlation coefficient was relatively large. The results of this study can provide the theoretical basis for soil infiltration study in purple soil area.展开更多
The large-scale deployment of intelligent Internet of things(IoT)devices have brought increasing needs for computation support in wireless access networks.Applying machine learning(ML)algorithms at the network edge,i....The large-scale deployment of intelligent Internet of things(IoT)devices have brought increasing needs for computation support in wireless access networks.Applying machine learning(ML)algorithms at the network edge,i.e.,edge learning,requires efficient training,in order to adapt themselves to the varying environment.However,the transmission of the training data collected by devices requires huge wireless resources.To address this issue,we exploit the fact that data samples have different importance for training,and use an influence function to represent the importance.Based on the importance metric,we propose a data pre-processing scheme combining data filtering that reduces the size of dataset and data compression that removes redundant information.As a result,the number of data samples as well as the size of every data sample to be transmitted can be substantially reduced while keeping the training accuracy.Furthermore,we propose device scheduling policies,including rate-based and Monte-Carlo-based policies,for multi-device multi-channel systems,maximizing the summation of data importance of scheduled devices.Experiments show that the proposed device scheduling policies bring more than 2%improvement in training accuracy.展开更多
基金Supported by National Science and Technology Support Program(2011BAD31B03)Fundamental Research Funds for Central Universities(XDJK2011C013)
文摘Soil infiltration capability is the hot spot topic of soil erosion studies and soil physical and chemical properties have great influence on it. A new infiltration method point- source infiltration method was used to precisely evaluate the infiltration capability in different purple soil land- use types. And correlation analysis on soil physical and chemical properties and soil infiltration capability of different land- use types was performed. Results showed that:( i) there is a large difference among soil physical and chemical properties in different land- use types,soil water content,non- capillary porosity,capillary porosity,content of > 0. 25 mm aggregates and organic matter content in the top soil are greater than those in the subsoil;( ii) soil infiltration capability showed differences among different land- use types. Land use showed great effects,in general,the order of decrease on initial infiltration rate and average infiltration rate was: woodland slope > slope farmland >grassland,the order of decrease on steady infiltration rate was: slope farmland > woodland > grassland and the time reaching stable state was:slope farmland > woodland > grassland;( iii) correlation analysis showed that there was a significantly positive correlation between initial infiltration rate and wet sieve MWD value and structural damage rate,and it had a significantly negative correlation with capillary porosity;( iv)steady infiltration rate and non- capillary porosity showed the significantly positive correlation,and it had a significantly negative correlation with the soil bulk density;( v) the average infiltration rate and non- capillary porosity and structural damage rate showed a positive correlation and the correlation coefficient was large and there was a negative correlation between average infiltration rate and soil bulk density and capillary porosity,and the absolute value of correlation coefficient was relatively large. The results of this study can provide the theoretical basis for soil infiltration study in purple soil area.
基金This work is sponsored in part by the National Natural Science Foundation of China under grants of 62022049,62111530197,and 61871254Hitachi Ltd.Part of this work has been presented in IEEE ICC 2020[1].
文摘The large-scale deployment of intelligent Internet of things(IoT)devices have brought increasing needs for computation support in wireless access networks.Applying machine learning(ML)algorithms at the network edge,i.e.,edge learning,requires efficient training,in order to adapt themselves to the varying environment.However,the transmission of the training data collected by devices requires huge wireless resources.To address this issue,we exploit the fact that data samples have different importance for training,and use an influence function to represent the importance.Based on the importance metric,we propose a data pre-processing scheme combining data filtering that reduces the size of dataset and data compression that removes redundant information.As a result,the number of data samples as well as the size of every data sample to be transmitted can be substantially reduced while keeping the training accuracy.Furthermore,we propose device scheduling policies,including rate-based and Monte-Carlo-based policies,for multi-device multi-channel systems,maximizing the summation of data importance of scheduled devices.Experiments show that the proposed device scheduling policies bring more than 2%improvement in training accuracy.
