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Shashikumar, D. R.
- Design of Finfet
Abstract Views :146 |
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Authors
Affiliations
1 Department of ECE, Cambridge institute of Technology, Bangalore, Karnataka, IN
2 Cambridge Institute of Technology, Bangalore, Karnataka, IN
1 Department of ECE, Cambridge institute of Technology, Bangalore, Karnataka, IN
2 Cambridge Institute of Technology, Bangalore, Karnataka, IN
Source
International Journal of Engineering Research, Vol 5, No SP 5 (2016), Pagination: 1052-1057Abstract
Since the fabrication of MOSFET, the minimum channel length has been shrinking continuously. As devices shrink further and further, the problems with conventional (planar) MOSFETs are increasing. Industry is currently at the 90nm node (i.e., DRAM half metal pitch, which corresponds to gate lengths of about 70nm). As we go down to the 65nm, 45nm, 32NM, 22nm, 14nm etc., nodes, there seem to be no viable options of continuing forth with the conventional MOSFET. The motivation behind this decrease has been an increasing interest in high speed devices and in very large scale integrated circuits. The sustained scaling of conventional bulk device requires innovations to circumvent the barriers of fundamental physics constraining the conventional MOSFET device structure.Full Text
- Image Processing System for Fertilization Management of Crops
Abstract Views :114 |
PDF Views:0
Authors
Affiliations
1 Dept. of CSE, Cambridge Institute of Technology, Bangalore, IN
1 Dept. of CSE, Cambridge Institute of Technology, Bangalore, IN
Source
International Journal of Engineering Research, Vol 5, No SP 4 (2016), Pagination: 910-913Abstract
The paper focuses on providing the information regarding the pesticide and the amount of pesticide to be used for an unhealthy crop. The user who is the farmer clicks a picture of the crop and uploads it to the server via the android application. After uploading the image, the farmer gets a unique ID displayed on his application screen. The uploaded image is then processed using image processing techniques, the features are extracted based on clustering and SVM Classification is applied, accordingly the disease is detected. The disease and the corresponding pesticide and other information about it are updated into server. The farmer using this unique ID can retrieve the complete information about the Disease name, affected area, pesticide name and its optimal amount to be used.Keywords
Image Processing, Feature Extraction, Clustering, SVM Classification.Full Text