2321-0850
2.47 [According Google C. Report] | SJIF : 5.263 | PIF : 4.128
| Sr. No. | Title and Author Name | Page No. | Download |
|---|---|---|---|
| 1 | Title : Meander Line EBG Based Multiband Antenna for WLAN and WiMAX application Authors : Ravindra Kumar Sharma , Mukesh Arora Click Here For Abstract Abstract :There have been many investigations in the past regarding the design of multi- band antennas. A multiband antenna is the one in which the same antenna can be operated at different frequencies. There have been many approaches towards the design of the multiband antenna like stacked patches, parasitic patches, use of slots, shaping i.e., the use of notches, reactive loading, slot loaded patches etc. The use of slots is an easier approach towards the design of multiband an- tenna as there is a well defined theoretical approach towards the design of the slot antennas. These slots can be cut either in the patch or in the ground plane as needed for the application. Higher gain is an important requirement for an antenna and use of Electromagnetic Band-Gap structures(EBG) is one of the promising technique to achieve this. The present thesis work focuses on the design of multiband antenna as well as novel Electromagnetic Band-Gap structures and their integration for enhance- ment of the gain of the antenna at desired frequencies of operation. The multi- band antenna is designed by cutting slots in the ground plane and the Uniplanar EBG is employed for the gain enhancement. The Fractalized Meander Line EBG based Microstrip Patch Slot Antenna oper- ates in the 6-7 GHz (Extended C-Band) and has a fractional bandwidth of 13% , and it maintains the radiation characteristics in the desired band with gain rang- ing from 5.5 to 7 dB. The Meander Line EBG based Multiband Antenna operates in the WLAN and WiMAX bands at frequencies 2.4, 3.6, 5.2 GHz respectively having gain 3.5 , 4.2 and 6.19 dB |
1-5 | |
| 2 | Title : Object Recognition Using Image Segmentation Authors : Sumer Singh Click Here For Abstract Abstract :Object recognition is basically an attempt to mimic the human capability to distinguish different objects in an image. This paper presents Scale-Invariant Feature Transform (SIFT) and segmentation methods such as Graph Cut, K-means, and Linde–Buzo–Gray (LBG) algorithm. In SIFT, interesting points of the object are extracted to provide a |
6-9 |
No Deadline for Paper Submission
03 to 05 Working Days after Submission
Registration Facilities are available 24 Hours
Within 5 working Days after Registration
