Time filter

Source Type

Hyderabad, India

Kumar G.N.,VNRVJIET | Kalavathi M.S.,Andhra University
ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology | Year: 2011

Voltage stability is of major concern in power systems stability. Main reason for the cause of voltage instability is the sag in reactive power at various locations in an interconnected power system. Improving the systems reactive power handling capacity via FACTS devices during large disturbance voltage instability is the idea behind this paper. The FACTS devices used to improve the reactive power profile are SVC and TCSC. Power system Analysis toolbox (PSAT) is used to effect of these controllers on 9-bus and 6-bus test systems. © 2011 IEEE.

Naveen Kumar G.,VNRVJIET | Surya Kalavathi M.,JNTUH College of Engineering
International Journal of Electrical Power and Energy Systems | Year: 2014

Voltage stability categorized under various classifications of power system stability is considered one of the important subjects in power systems stability studies. A power system, experiencing disturbances, is at risks of voltage instability. Main reason for the cause of voltage instability is the sag in reactive power at various locations due to circuit contingencies classified under large disturbance voltage stability. The aim of this paper is to identify the optimal location of Unified Power Flow Controller in an interconnected power system under N-1 contingency. As the size and the cost of the FACTS devices are high, an optimal location and size has to be identified before they are actually installed. We are trying to improve the voltage profile and Maximum Loading Parameter using Unified Power Flow Controller while determining their optimal location based upon Cat Swarm Optimization. © 2013 Elsevier Ltd. All rights reserved.

Reddy G.S.,VNRVJIET | Rajinikanth T.V.,SNIST | Rao A.A.,JNTUA
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014 | Year: 2014

Text clustering is an unsupervised process forming its basis solely on finding the similarity relationship between documents with the output as a set of clusters [14]. In this research, a commonality measure is defined to find commonality between two text files which is used as a similarity measure. The main idea is to apply any existing frequent item finding algorithm such as apriori or fp-tree to the initial set of text files to reduce the dimension of the input text files. A document feature vector is formed for all the documents. Then a vector is formed for all the static text input files. The algorithm outputs a set of clusters from the initial input of text files considered. © 2014 IEEE.

Chandra K.V.,VNRVJIET | Rashmi K.,VNRVJIET
2015 International Conference on Control Instrumentation Communication and Computational Technologies, ICCICCT 2015 | Year: 2015

The Cornea is the most important layer in human eye which consists of 12 sub layers in it, Each one is very unique to its own identity and forming some diseases in it cause vigorous vision problems, This paper deals with the corneal diseases using NI VISION Assistant in LabVIEW. NI Vision for LabVIEW is apart ofthe NI VDM is a Iibrary of LabVIEW used to develop machine vision and scientific imaging applications. The diseases and disorders affecting the cornea are many but only few ofthem are discussed in this paper. They are: Corneal Infections, Dry Eye, Keratoconus, and Allergies. © 2015 IEEE.

2015 International Conference on Control Instrumentation Communication and Computational Technologies, ICCICCT 2015 | Year: 2015

Diabetic Retinopathy is the frequent cause of blindness. Diabetic retinopathy is a complication of diabetes mellitus. The longer one is suffering with diabetes the more is the probability of diabetic retinopathy(DR). DR leads to several abnormalities like Micro aneurisms(MA); hard exudates (HE), hemorrhages (Hem) and Cotton wool spots(CWS). MA is first symptom of DR. The detection of MA is important for the early detection of DR. We have proposed MA detection based on Eigen value analysis using hessian matrix in retinal images. The objective of the proposed work is, to develop an algorithm for improved MA detection. The algorithm employed Eigen value analysis from Hessian matrix to detect MAs. MA particle analysis is employed to measure the area of MA in retinal image. When the method was evaluated on visible MAs using 89 images from the diaretDB0 database, the true positive rate was 91% with eight false positive images. Lab VIEW software is used to implement the algorithm. © 2015 IEEE.

Discover hidden collaborations