期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
A novel,green 1-glycyl-3-methyl imidazolium chloride-copper(Ⅱ) complex catalyzed C-H oxidation of alkyl benzene and cyclohexane 被引量:3
1
作者 Parasuraman Karthikeyan Pundlik Rambhau Bhagat s.senthil kumar 《Chinese Chemical Letters》 SCIE CAS CSCD 2012年第6期681-684,共4页
A variety of alkyl-arenes and cyclohexane were converted to the corresponding ketones with NaC10 as the oxidant in the presence of 1-glycyl-3-methyl imidazolium chloride--copper(II) complex. This method contains sim... A variety of alkyl-arenes and cyclohexane were converted to the corresponding ketones with NaC10 as the oxidant in the presence of 1-glycyl-3-methyl imidazolium chloride--copper(II) complex. This method contains simplified product isolation and catalyst recycling, affording benzylic C-H oxidation of alkyl-arenes imparting high yield of ketones. Furthermore, complex could be reused seven times without a significant loss of its catalytic activity. 展开更多
关键词 COPPER ALKANE Ionic liquid Room temperature
原文传递
Deep Optimal VGG16 Based COVID-19 Diagnosis Model
2
作者 M.Buvana K.Muthumayil +3 位作者 s.senthil kumar Jamel Nebhen Sultan S.Alshamrani Ihsan Ali 《Computers, Materials & Continua》 SCIE EI 2022年第1期43-58,共16页
Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December 2019.It was tagged as a pandemic soon by the WHO being a serious public medical conditionworldwide.In spite of the fact that the virus can ... Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December 2019.It was tagged as a pandemic soon by the WHO being a serious public medical conditionworldwide.In spite of the fact that the virus can be diagnosed by qRT-PCR,COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray(CXR)and Computed Tomography(CT)images.In this paper,the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various features.Impressive features like Speeded-Up Robust Features(SURF),Features from Accelerated Segment Test(FAST)and Scale-Invariant Feature Transform(SIFT)are used in the test images to detect the presence of virus.The optimal features are extracted from the images utilizing DeVGGCovNet(Deep optimal VGG16)model through optimal learning rate.This task is accomplished by exceptional mating conduct of Black Widow spiders.In this strategy,cannibalism is incorporated.During this phase,fitness outcomes are rejected and are not satisfied by the proposed model.The results acquired from real case analysis demonstrate the viability of DeVGGCovNet technique in settling true issues using obscure and testing spaces.VGG16 model identifies the imagewhich has a place with which it is dependent on the distinctions in images.The impact of the distinctions on labels during training stage is studied and predicted for test images.The proposed model was compared with existing state-of-the-art models and the results from the proposed model for disarray grid estimates like Sen,Spec,Accuracy and F1 score were promising. 展开更多
关键词 COVID 19 multi-feature extraction vgg16 optimal learning rate
暂未订购
上一页 1 下一页 到第
使用帮助 返回顶部