The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sa...The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.展开更多
The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower...The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower and upper quartiles. For efficient monitoring of process dispersion, we have proposed auxiliary information based Shewhart-type IQR control charts (namely IQRr and IQRp charts) based on ratio and product estimators of lower and upper quartiles under bivariate normally distributed process. We have developed the control structures of proposed charts and compared their performances with the usual IQR chart in terms of detection ability of shift in process dispersion. For the said purpose power curves are constructed to demonstrate the performance of the three IQR charts under discussion in this article. We have also provided an illustrative example to justify theory and finally closed with concluding remarks.展开更多
Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabi...Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.展开更多
The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups o...The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups of coal density composition data and their jigging stratification data derived from the pilot jig, the regression analysis has been done for the relationship between the characteristic values of the density curve and the characteristic values of the distribution curve.The results show as follow: (1) The bigger the skewness of the density curve, the bigger the probable error (Ep) and imperfection (I ) are. (2) The bigger the median of density curve, the smaller the probable error or imperfection is. (3) The characteristic values of density curve have no influence on the kurtosis K of the distribution curve.展开更多
Based on the understanding that the seismic fault system is a nonlinear complex system,Rundle(1995)introduced the nonlinear threshold system used in meteorology to analyze the ocean-atmosphere interface and the El Ni?...Based on the understanding that the seismic fault system is a nonlinear complex system,Rundle(1995)introduced the nonlinear threshold system used in meteorology to analyze the ocean-atmosphere interface and the El Ni?o Southern Oscillation into the study of seismic activity changes,and then proposed the PI method(Rundle et al.,2000a,b).Wu et al.(2011)modified the Pattern Informatics Method named MPI to extract the ionospheric anomaly by using data from DEMETER satellites which is suitable for 1–3 months short-term prediction.展开更多
The density seasonal dynamics of Bemisia tabaci MED were evaluated over two years in a cotton-growing area in Langfang, Hebei Province, northern China on cotton （Gossypium hirsutum L.） and six other co-occurring com...The density seasonal dynamics of Bemisia tabaci MED were evaluated over two years in a cotton-growing area in Langfang, Hebei Province, northern China on cotton （Gossypium hirsutum L.） and six other co-occurring common plants, common ragweed （Ambrosia artemisiifolia L.）, piemarker （Abutilon theophrasti Medicus）, sunflower （Helianthus annuus L.）, sweet potato （Ipomoea batatas L.）, soybean （Glycine max L.）, and maize （Zea mays L.）. The whitefly species identity was repeatedly tested and confirmed; seasonal dynamics on the various host plants were standardized by the quartile method. B. tabaci MED appeared on weeds （the common ragweed and piemarker） about 10 days earlier than on cotton, or the other cultivated plants. The peak population densities were observed over a span of 2 to 3 weeks on cotton, starting in early （2010） or mid-August （2011）. The common ragweed growing adjacent to cotton supported the highest B. tabaci densities （no. on 100 cm2 leaf surface）, 12-22 fold higher than on cotton itself. Sunflower supported more B. tabaci than the other plants, and about 1.5-2 fold higher than cotton did, Our results indicate that weeds （esp. the common ragweed） around cotton fields could increase the population density of B. tabaci MED on cotton, while sunflower could act as a trap crop for decreasing pest pressure on cotton.展开更多
Contamination analysis of the unsaturated zone requires information on the spatial variability of hydraulic conductivity. Two types of hydraulic tests (variable and constant charge) were identified to estimate the spa...Contamination analysis of the unsaturated zone requires information on the spatial variability of hydraulic conductivity. Two types of hydraulic tests (variable and constant charge) were identified to estimate the spatial variability of the hydraulic conductivity of the surface portion of the unsaturated zone in the Olezoa watershed. These tests were performed on 100 holes at depths ranging between 50 and 90 cm, spread throughout the watershed. The hydraulic conductivity values obtained at 50 and 90 cm are close to the absolute value for each method. However, they show a difference of 10<sup>-1</sup> m/s between the two types of test regardless of the depth of investigation. The representation of data in the graph indicates a staircase quartile distribution for the variable charge test. The test at constant charge, rather presents a log normal distribution which is also supported by the Kolmogorov-Smirnov test. Hydraulic conductivities have a random component and a spatial organization which results from soil and/or morphological factors. This organization thus permits the distinction of zones which could show high pollution risk.展开更多
文摘The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.
文摘The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower and upper quartiles. For efficient monitoring of process dispersion, we have proposed auxiliary information based Shewhart-type IQR control charts (namely IQRr and IQRp charts) based on ratio and product estimators of lower and upper quartiles under bivariate normally distributed process. We have developed the control structures of proposed charts and compared their performances with the usual IQR chart in terms of detection ability of shift in process dispersion. For the said purpose power curves are constructed to demonstrate the performance of the three IQR charts under discussion in this article. We have also provided an illustrative example to justify theory and finally closed with concluding remarks.
文摘Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.
文摘The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups of coal density composition data and their jigging stratification data derived from the pilot jig, the regression analysis has been done for the relationship between the characteristic values of the density curve and the characteristic values of the distribution curve.The results show as follow: (1) The bigger the skewness of the density curve, the bigger the probable error (Ep) and imperfection (I ) are. (2) The bigger the median of density curve, the smaller the probable error or imperfection is. (3) The characteristic values of density curve have no influence on the kurtosis K of the distribution curve.
基金supported by the Joint Funds of the National Natural Science Foundation of China(Grant No.U2039207)。
文摘Based on the understanding that the seismic fault system is a nonlinear complex system,Rundle(1995)introduced the nonlinear threshold system used in meteorology to analyze the ocean-atmosphere interface and the El Ni?o Southern Oscillation into the study of seismic activity changes,and then proposed the PI method(Rundle et al.,2000a,b).Wu et al.(2011)modified the Pattern Informatics Method named MPI to extract the ionospheric anomaly by using data from DEMETER satellites which is suitable for 1–3 months short-term prediction.
基金funded by grants from the National Natural Science Foundation of China(30930062)the National Basic Research Program of China(2013CB127605)the CABI Special Fund for the Agricultural Industry(20130302404,201303019-02)
文摘The density seasonal dynamics of Bemisia tabaci MED were evaluated over two years in a cotton-growing area in Langfang, Hebei Province, northern China on cotton （Gossypium hirsutum L.） and six other co-occurring common plants, common ragweed （Ambrosia artemisiifolia L.）, piemarker （Abutilon theophrasti Medicus）, sunflower （Helianthus annuus L.）, sweet potato （Ipomoea batatas L.）, soybean （Glycine max L.）, and maize （Zea mays L.）. The whitefly species identity was repeatedly tested and confirmed; seasonal dynamics on the various host plants were standardized by the quartile method. B. tabaci MED appeared on weeds （the common ragweed and piemarker） about 10 days earlier than on cotton, or the other cultivated plants. The peak population densities were observed over a span of 2 to 3 weeks on cotton, starting in early （2010） or mid-August （2011）. The common ragweed growing adjacent to cotton supported the highest B. tabaci densities （no. on 100 cm2 leaf surface）, 12-22 fold higher than on cotton itself. Sunflower supported more B. tabaci than the other plants, and about 1.5-2 fold higher than cotton did, Our results indicate that weeds （esp. the common ragweed） around cotton fields could increase the population density of B. tabaci MED on cotton, while sunflower could act as a trap crop for decreasing pest pressure on cotton.
文摘Contamination analysis of the unsaturated zone requires information on the spatial variability of hydraulic conductivity. Two types of hydraulic tests (variable and constant charge) were identified to estimate the spatial variability of the hydraulic conductivity of the surface portion of the unsaturated zone in the Olezoa watershed. These tests were performed on 100 holes at depths ranging between 50 and 90 cm, spread throughout the watershed. The hydraulic conductivity values obtained at 50 and 90 cm are close to the absolute value for each method. However, they show a difference of 10<sup>-1</sup> m/s between the two types of test regardless of the depth of investigation. The representation of data in the graph indicates a staircase quartile distribution for the variable charge test. The test at constant charge, rather presents a log normal distribution which is also supported by the Kolmogorov-Smirnov test. Hydraulic conductivities have a random component and a spatial organization which results from soil and/or morphological factors. This organization thus permits the distinction of zones which could show high pollution risk.
