This paper focuses on prediction of change in agricultural lands by using ART2 algorithm. The existing method used ENVI and ARCGIS software to predict the changes in land, which showed less accuracy due to human error...This paper focuses on prediction of change in agricultural lands by using ART2 algorithm. The existing method used ENVI and ARCGIS software to predict the changes in land, which showed less accuracy due to human errors. To overcome this user friendly GUI based ART2 algorithm has been developed in java to obtain more accuracy in prediction of changes in land. The input is satellite temporal images of the years 1990 and 2014. By using the ART2 algorithm, the input images of the years 1990 and 2014 are classified, where the features are identified to form cluster. The clustered image is given as input and pixel to pixel comparison method in ART2 is implemented in java, for detecting the changes in agricultural lands. The comparison results of ENVI and ARCGIS and GUI based ART2 with in situ data show that the prediction of changes in agricultural land is more accurate in the case of GUI based ART2 implementation.展开更多
On page 233 and 235,volume 5 of Infectious Diseases&Immunity,in the article“Characteristics and risk factors of acquired drug resistance among people living with HIV:A retrospective study in Guangzhou,China(2018-...On page 233 and 235,volume 5 of Infectious Diseases&Immunity,in the article“Characteristics and risk factors of acquired drug resistance among people living with HIV:A retrospective study in Guangzhou,China(2018-2023)”,[1]there is an error regarding the ART regimen classification in Table 1,Table 2,and section 3.4.The regimen category labeled as“2NNRTI”should be corrected to“2NRTI”throughout.展开更多
文摘This paper focuses on prediction of change in agricultural lands by using ART2 algorithm. The existing method used ENVI and ARCGIS software to predict the changes in land, which showed less accuracy due to human errors. To overcome this user friendly GUI based ART2 algorithm has been developed in java to obtain more accuracy in prediction of changes in land. The input is satellite temporal images of the years 1990 and 2014. By using the ART2 algorithm, the input images of the years 1990 and 2014 are classified, where the features are identified to form cluster. The clustered image is given as input and pixel to pixel comparison method in ART2 is implemented in java, for detecting the changes in agricultural lands. The comparison results of ENVI and ARCGIS and GUI based ART2 with in situ data show that the prediction of changes in agricultural land is more accurate in the case of GUI based ART2 implementation.
文摘On page 233 and 235,volume 5 of Infectious Diseases&Immunity,in the article“Characteristics and risk factors of acquired drug resistance among people living with HIV:A retrospective study in Guangzhou,China(2018-2023)”,[1]there is an error regarding the ART regimen classification in Table 1,Table 2,and section 3.4.The regimen category labeled as“2NNRTI”should be corrected to“2NRTI”throughout.
