The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economic...The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.展开更多
One of the primary forestry research interests lies in estimating forest stand parameters by applying empirical or semi-empirical model to establish the relationship between the forest stand parameters and remote sens...One of the primary forestry research interests lies in estimating forest stand parameters by applying empirical or semi-empirical model to establish the relationship between the forest stand parameters and remote sensing data. Using remote sensing image and the inventory data from 2 compartments in northeast Florida, U.S.A., this paper explored the correlation between forest stand parameters and Landsat TM spectral digital number （DN） value. Results showed that less than 50% of the total variance could be explained by linear regression models with only either a single band or such vegetation indices as vegetation index （VI） or normalized difference vegetation index （NDVI） as predicators. In consequence, multi-linear regression models which synthesized more predicators were introduced to estimate forest parameters. Regression results were tested in terms of the other group of data, and verification showed a better capability of explaining over 75% variance except for forest density. The weakness and further improvement of prediction models were also discussed in the article. This paper is expected to provide a better understanding of the relationship between TM spectral and forest characteristics展开更多
OBJECTIVE:To optimize the vinegar-steaming process of Wuweizi(Fructus Schisandrae Chinensis)using the response surface method(RSM)based on the Box-Behnken design.METHODS:A regression model was constructed with the res...OBJECTIVE:To optimize the vinegar-steaming process of Wuweizi(Fructus Schisandrae Chinensis)using the response surface method(RSM)based on the Box-Behnken design.METHODS:A regression model was constructed with the response variables,the content of Deoxyschizandrin,and the three explanatory factors:length of steaming time,the quantity of vinegar and length of moistening time to evaluate the effects on the processing of Wuweizi(Fructus SchisandraeChinensis).RESULTS:There was a linear relationship between the content of Deoxyschizandrin and the three explanatory factors.When the steaming time was5.49 h,with 2.365 g of vinegar added and a moistening time of 4.13 h,the content of Deoxyschizandrin reached the maximum predicted value of0.1076%,and under the conditions the average content of Deoxyschizandrin was 0.1058%.CONCLUSION:The correlation coefficient of thenonlinear mathematical model was relatively high and the model matched the data well,potentially providing a method for the study of the steaming process.展开更多
Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential health signs for earlier disease diagnosis...Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and prediction.Among the various disease,skin cancer was the wide variety of cancer,as well as enhances the endurance rate.In recent years,many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors,including malignant melanoma(MM)and other skin cancers.However,accurate cancer detection was not performed with minimum time consumption.In order to address these existing problems,a novel Multidimensional Bregman Divergencive Feature Scaling Based Cophenetic Piecewise Regression Recurrent Deep Learning Classification(MBDFS-CPRRDLC)technique is introduced for detecting cancer at an earlier stage.The MBDFS-CPRRDLC performs skin cancer detection using different layers such as input,hidden,and output for feature selection and classification.The patient information is composed of IoT.The patient information was stored in mobile clouds server for performing predictive analytics.The collected data are sent to the recurrent deep learning classifier.In the first hidden layer,the feature selection process is carried out using the Multidimensional Bregman Divergencive Feature Scaling technique to find the significant features for disease identification resulting in decreases time consumption.Followed by,the disease classification is carried out in the second hidden layer using cophenetic correlative piecewise regression for analyzing the testing and training data.This process is repeatedly performed until the error gets minimized.In this way,disease classification is accurately performed with higher accuracy.Experimental evaluation is carried out for factors namely Accuracy,precision,recall,F-measure,as well as cancer detection time,by the amount of patient data.The observed result confirms that the proposed MBDFS-CPRRDLC technique increases accuracy as well as lesser cancer detection time compared to the conventional approaches.展开更多
The research work was carried out to compare and evaluate the extractability of cationic micronutrients(Zn,Cu,Fe and Mn)using widely employed diethylene triamine pentaacetic acid(DTPA)-triethanolamine(TEA)-CaCl2 metho...The research work was carried out to compare and evaluate the extractability of cationic micronutrients(Zn,Cu,Fe and Mn)using widely employed diethylene triamine pentaacetic acid(DTPA)-triethanolamine(TEA)-CaCl2 method with that of multinutrient extractant(ammonium bicarbonate(AB)-DTPA)in Inceptisols,Alfisols and Entisols in the erstwhile united Andhra Pradesh.The percent variation of extraction of Zn was higher in soils with DTPA-TEA-CaCl2 over AB-DTPA method in all the soil orders(types)in the range of 35.3% to 46.2%.AB-DTPA extracted high amounts of Cu to an extent of 10%-21% in Entisols and Alfisls,respectively.In Inceptisols both extracatants extracted equal amounts of Cu.AB-DTPA extracted high amounts of Fe 13% and 18% in Alfisols and Entisols compared to that of DTPA-TEA-CaCl2 method and DTPA-TEA-CaCl2 method was good extract for Fe in Inceptisols and even for Mn in Alfisols.The amounts of micronutrient contents extracted were found to be highly and significantly correlated with soil properties like electrical conductivity(EC)and organic carbon(OC).The individual micronutrient contents of Zn,Cu and Fe extracted by DTPA-TEA-CaCl2 methods were found to be highly correlated with that of AB-DTPA extractant.However,such correlation was not observed for Mn extraction when all soils were grouped.展开更多
Aim of this study is to discuss matters with HR and finn performance. Therefore, we used HR and firm performance questionnaire from Delaney and Huselid （1996）. HR variables include recruitment, training, compensatio...Aim of this study is to discuss matters with HR and finn performance. Therefore, we used HR and firm performance questionnaire from Delaney and Huselid （1996）. HR variables include recruitment, training, compensation and promotion. Firm performance divided into organizational and market performance. Therefore, correlation analysis demonstrates that HR has positive and significant relationship with organizational performance, and HR has positive but weak relationship with market performance. Therefore, we can propose that HR is partly correlated with firm performance for those companies in sample. Therefore, since we didn＇t realize demography of companies in study, it is arguable, findings of this study can be generalized to other companies in Turkey.展开更多
The effects of three factors （i.e., drop height h, hopper outlet diameter do, and material temperature T] on the dust generation rate derived from a free falling particle stream were investigated via filll factorial ...The effects of three factors （i.e., drop height h, hopper outlet diameter do, and material temperature T] on the dust generation rate derived from a free falling particle stream were investigated via filll factorial experiments. The correlation between the three factors and dust generation rate was also analysed. Results show that Tand h affect the first fugitive dust rate largely, whereas the second fugitive dust rate is mainly dominated by h and do. Through analysing the first fugitive dust percentage data, it is found that h and T should be considered first for higher temperatures and lower flow rates, whereas h and do can be considered under contrasting conditions, and h should be controlled in the remaining two sets of conditions. Relationships between the influencing factors and total and first fugitive dust rates were developed via multiple regression to quantify the dust emission rates for different contact surfaces （rigid or water）.展开更多
基金CDC/NIOSH for their partial funding of this work
文摘The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.
文摘One of the primary forestry research interests lies in estimating forest stand parameters by applying empirical or semi-empirical model to establish the relationship between the forest stand parameters and remote sensing data. Using remote sensing image and the inventory data from 2 compartments in northeast Florida, U.S.A., this paper explored the correlation between forest stand parameters and Landsat TM spectral digital number （DN） value. Results showed that less than 50% of the total variance could be explained by linear regression models with only either a single band or such vegetation indices as vegetation index （VI） or normalized difference vegetation index （NDVI） as predicators. In consequence, multi-linear regression models which synthesized more predicators were introduced to estimate forest parameters. Regression results were tested in terms of the other group of data, and verification showed a better capability of explaining over 75% variance except for forest density. The weakness and further improvement of prediction models were also discussed in the article. This paper is expected to provide a better understanding of the relationship between TM spectral and forest characteristics
基金Supported by Scientific Research Foundation of Health Department of Shaanxi Province(2012D14),China
文摘OBJECTIVE:To optimize the vinegar-steaming process of Wuweizi(Fructus Schisandrae Chinensis)using the response surface method(RSM)based on the Box-Behnken design.METHODS:A regression model was constructed with the response variables,the content of Deoxyschizandrin,and the three explanatory factors:length of steaming time,the quantity of vinegar and length of moistening time to evaluate the effects on the processing of Wuweizi(Fructus SchisandraeChinensis).RESULTS:There was a linear relationship between the content of Deoxyschizandrin and the three explanatory factors.When the steaming time was5.49 h,with 2.365 g of vinegar added and a moistening time of 4.13 h,the content of Deoxyschizandrin reached the maximum predicted value of0.1076%,and under the conditions the average content of Deoxyschizandrin was 0.1058%.CONCLUSION:The correlation coefficient of thenonlinear mathematical model was relatively high and the model matched the data well,potentially providing a method for the study of the steaming process.
基金This research is funded by Princess Nourah Bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R194)Princess Nourah Bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and prediction.Among the various disease,skin cancer was the wide variety of cancer,as well as enhances the endurance rate.In recent years,many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors,including malignant melanoma(MM)and other skin cancers.However,accurate cancer detection was not performed with minimum time consumption.In order to address these existing problems,a novel Multidimensional Bregman Divergencive Feature Scaling Based Cophenetic Piecewise Regression Recurrent Deep Learning Classification(MBDFS-CPRRDLC)technique is introduced for detecting cancer at an earlier stage.The MBDFS-CPRRDLC performs skin cancer detection using different layers such as input,hidden,and output for feature selection and classification.The patient information is composed of IoT.The patient information was stored in mobile clouds server for performing predictive analytics.The collected data are sent to the recurrent deep learning classifier.In the first hidden layer,the feature selection process is carried out using the Multidimensional Bregman Divergencive Feature Scaling technique to find the significant features for disease identification resulting in decreases time consumption.Followed by,the disease classification is carried out in the second hidden layer using cophenetic correlative piecewise regression for analyzing the testing and training data.This process is repeatedly performed until the error gets minimized.In this way,disease classification is accurately performed with higher accuracy.Experimental evaluation is carried out for factors namely Accuracy,precision,recall,F-measure,as well as cancer detection time,by the amount of patient data.The observed result confirms that the proposed MBDFS-CPRRDLC technique increases accuracy as well as lesser cancer detection time compared to the conventional approaches.
文摘The research work was carried out to compare and evaluate the extractability of cationic micronutrients(Zn,Cu,Fe and Mn)using widely employed diethylene triamine pentaacetic acid(DTPA)-triethanolamine(TEA)-CaCl2 method with that of multinutrient extractant(ammonium bicarbonate(AB)-DTPA)in Inceptisols,Alfisols and Entisols in the erstwhile united Andhra Pradesh.The percent variation of extraction of Zn was higher in soils with DTPA-TEA-CaCl2 over AB-DTPA method in all the soil orders(types)in the range of 35.3% to 46.2%.AB-DTPA extracted high amounts of Cu to an extent of 10%-21% in Entisols and Alfisls,respectively.In Inceptisols both extracatants extracted equal amounts of Cu.AB-DTPA extracted high amounts of Fe 13% and 18% in Alfisols and Entisols compared to that of DTPA-TEA-CaCl2 method and DTPA-TEA-CaCl2 method was good extract for Fe in Inceptisols and even for Mn in Alfisols.The amounts of micronutrient contents extracted were found to be highly and significantly correlated with soil properties like electrical conductivity(EC)and organic carbon(OC).The individual micronutrient contents of Zn,Cu and Fe extracted by DTPA-TEA-CaCl2 methods were found to be highly correlated with that of AB-DTPA extractant.However,such correlation was not observed for Mn extraction when all soils were grouped.
文摘Aim of this study is to discuss matters with HR and finn performance. Therefore, we used HR and firm performance questionnaire from Delaney and Huselid （1996）. HR variables include recruitment, training, compensation and promotion. Firm performance divided into organizational and market performance. Therefore, correlation analysis demonstrates that HR has positive and significant relationship with organizational performance, and HR has positive but weak relationship with market performance. Therefore, we can propose that HR is partly correlated with firm performance for those companies in sample. Therefore, since we didn＇t realize demography of companies in study, it is arguable, findings of this study can be generalized to other companies in Turkey.
文摘The effects of three factors （i.e., drop height h, hopper outlet diameter do, and material temperature T] on the dust generation rate derived from a free falling particle stream were investigated via filll factorial experiments. The correlation between the three factors and dust generation rate was also analysed. Results show that Tand h affect the first fugitive dust rate largely, whereas the second fugitive dust rate is mainly dominated by h and do. Through analysing the first fugitive dust percentage data, it is found that h and T should be considered first for higher temperatures and lower flow rates, whereas h and do can be considered under contrasting conditions, and h should be controlled in the remaining two sets of conditions. Relationships between the influencing factors and total and first fugitive dust rates were developed via multiple regression to quantify the dust emission rates for different contact surfaces （rigid or water）.
