Series-1 (Jul. - Aug. 2021)Jul. - Aug. 2021 Issue Statistics
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| Paper Type | : | Research Paper |
| Title | : | VHDL-AMS Macro models of MOSFET. Consideration of Gate Length Variability And Single-Electron-Transistors |
| Country | : | Greece |
| Authors | : | George P. Patsis |
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: | 10.9790/4200-11040105  |
ABSTRACT: The integrated circuit/system designers are faced with problems that involves nano-scale devices with far less than ideal characteristics, very high integration densities (i.e. giga-scale complexity), very high operation speeds and data transmission rates, and system-level integration of analog and digital functions. The single-electron tunnelling (SET) devices might be scaled down almost to the molecular level. Gate length variability due to intra or inter die variations can lead to considerable mismatch between devices even inside the same chip. This variability has to be considered in detail and new device models should be developed, aiming in modelling its effects.......
Key Words: mosfet, line-width-roughness, vhdl-ams, digital-gates, single-electron-transistor, coulombblockage, compact-device-modelling
[1]. Y. S. Yu, H. S. Lee, and S. W. Hwang, SPICE Macro-Modelling for the Compact Simulation of Single Electron Circuits, J.
Korean Phys. Soc. 33, 1998, 269.
[2]. G. P. Patsis, Modelling MOSFET gate length variability for future technology node, Phys. Stat. Sol. (a) 205 (11), 2008, 2541-2543.
Ansys site: http://www.ansys.com/
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| Paper Type | : | Research Paper |
| Title | : | Hindi Optical Character Recognition For Printed Documents Using Fuzzy K-Nearest Neighbor Algorithm: A Problem Approach In Character Segmentation |
| Country | : | India |
| Authors | : | Prof. Amit Choksi || Kajal Kumari || Shivani Kanojiya || Pragya Sahu || Nishtha Rindani |
|
: | 10.9790/4200-11040615 |
ABSTRACT: Optical Character Recognition (OCR) is a technology that extracts all the text from the images, .pdf documents or scanned files. So OCR converts normal scanned documents text-searchable so to allow content search on the same. Hindi being the national language of India, with such huge population makes document managing and preservation difficult in government sector. Hence, this paper presents an efficient algorithm Fuzzy KNN for recognition of Hindi script characters from printed documents. Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate due to shirorekha as well as joint characters. This paper proposes an OCR for printed Hindi text in Devanagari script, using Fuzzy KNN which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation also. The presence of touching......
Keywords – Optical Character Recognition, Fuzz-KNN, Wavelet Transform
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