Simulation and Experimental Demonstration of Novel In-service Correlation OTDR using Single-period Signal Extension

Author(s):  
Xintao Fan ◽  
Jinhao Du ◽  
Tao Yang ◽  
Sheping Shi ◽  
Yangguang Shangguan
2008 ◽  
Vol 128 (4) ◽  
pp. 677-682 ◽  
Author(s):  
Taku Takaku ◽  
Noriyuki Iwamuro ◽  
Yoshiyuki Uchida ◽  
Ryuichi Shimada

Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


GIS Business ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. 39-45
Author(s):  
J. P. Singh

This article sets up a single period value maximization model for the firm based on stochastic end-of-period cash inflows, stochastic bankruptcy costs and taxes based on income rather than wealth. The risk-return trade-off is captured in the Capital Asset Pricing Model. Thus, the model also assumes a perfect capital market and market equilibrium. The model establishes the existence of a unique optimal financial leverage at which the firm value is maximized, this leverage being less than the maximum debt capacity of the firm.


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