Kamala Institute of Technology and Science

andhra Pradesh, India

Kamala Institute of Technology and Science

andhra Pradesh, India

Time filter

Source Type

Sharmila K.,Kamala Institute of Technology and Science | Krishna E.H.,Kakatiya University | Komalla N.R.,Government MGM Hospitals | Reddy K.A.,Kakatiya Institute of Technology and Science
MeMeA 2012 - 2012 IEEE Symposium on Medical Measurements and Applications, Proceedings | Year: 2012

Sudden cardiac death (SCD) is a major health concern. In time domain, detection of such condition involving monitoring the 24-h ambulatory ECG is a big issue. Here, the presented work describes higher order spectral analysis carried out on the normal portion of SCD-ECG and the analyzed parameters are compared with that of healthy person ECG. The developed algorithm detects the chances of myocardial infarction in prior, on the basis of higher order spectral analysis of an SCD-ECG. Specifically, quadratic phase coupling techniques are applied on QRS complex to extract information from the SCD-ECG signal providing the basis with which a signal suggesting predisposition of the patient to suffer a cardiac arrest can be differentiated from a normal ECG signal. The algorithm requires short segments of ECG to detect the possibility of SCD. The proposed algorithm is tested on MIT-BIH database signals and the results obtained established that it is possible to analyze and predict whether an individual is susceptible to cardiac arrest or not. Certain parameters like energy are evaluated and analyzed from the normal portion of QRS complex of SCD-ECG and are compared with that of the healthy person ECG. This primitive idea can extend the research aspect in view of analyzing the ECG signal to identify the predisposition to other cardiac diseases. © 2012 IEEE.


Sharmila K.,Kamala Institute of Technology and Science | Krishna E.H.,Kakatiya University | Reddy K.N.,Government MGM Hospitals | Reddy K.A.,Kakatiya University
Conference Record - IEEE Instrumentation and Measurement Technology Conference | Year: 2011

The electrocardiogram (ECG) is an electrical manifestation of contractile activity of the heart. The presence of parasite interference signals, like power line interference (PLI), Electromyogram (EMG) or myopotential signals and baseline drift interferences, could cause serious problems in the registration of ECG signals. Many a time, they pose problem in modern control and signal processing applications by being a narrow in-band interference near the frequencies carrying crucial information. The wavelet transform is a powerful time-frequency analysis tool analysis of complex non stationary signals. Principle Component Analysis (PCA) is a standard tool in modern data analysis because it is simple non-parametric method for extracting relevant information from complex data sets. In multi scale Principal Component Analysis (MSPCA), the PCA's ability to decorrelate the variables by extracting a linear relationship and wavelet analysis are utilised. This paper presents MSPCA method proposed for the enhancement of ECG signals, so that the enhanced signal can be used for clear identification of arrhythmias. In MSPCA, the principal components of the wavelet coefficients of the ECG data at each scale are computed forst and are then combined at relevant scales. In this application for ECG enhancement, the MSPCA served as a powerful tool when addressing problems related to noise reduction. Results revealed that Daubenchies based MSPCA out performed the basic wavelet based processing for ECG signal enhancement. © 2011 IEEE.


Gurram M.,Kamala Institute of Technology and Science | Adepu K.,National Institute of Technology Warangal | Pinninti R.R.,Chaitanya Bharathi Institute of Technology | Gankidi M.R.,Indian Defence Research And Development Laboratory
Journal of Materials Research and Technology | Year: 2013

The influence of grain refining elements such as copper (Cu) and aluminium (Al) on mechanical properties of AISI 430 ferritic stainless steel welds through gas tungsten arc welding process was studied. Cu (foil form) and Al powder of -100 μm mesh was added in the range from 1 to 3 g between the butt joint of ferritic stainless steel. In order to investigate the influence of post-weld heat treatment on the microstructure and mechanical properties of welds, post-weld annealing was adopted at 830 C, 30 min holding followed by water quenching. Corrosion behaviour of ferritic stainless steel welds was also studied. From this investigation, it is observed that the joints made by the addition of 2 g Al (2.4 wt.%) in post-weld annealed condition led to improved strength. There is a marginal improvement in the ductility and pitting corrosion resistance of ferritic stainless steel welds by the addition of 2 g Cu (0.18 wt.%) in post-weld annealed condition. The observed mechanical properties have been correlated with microstructure, fracture features and corrosion behaviour of ferritic stainless steel weldments. © 2013 Brazilian Metallurgical, Materials and Mining Association.


Pundlik Y.Y.,Kamala Institute of Technology and Science | Nirgude P.M.,Indian Central Power Research Institute
Proceedings - 2014 4th International Conference on Communication Systems and Network Technologies, CSNT 2014 | Year: 2014

Power Transformers are significant links between HVAC/HVDC transmission systems for changing the life of such aged transformers. Sometimes failure of power transformers may lead to failure of entire power grid. At present, there is large number of transformers being operated towards end of their working life. The main challenge for the High voltage substation maintenance engineers and asset managers is to extend useful life of transformers to avoid major catastrophic failure in them & resulting grid failures. A prorated model of transformer is prepared and tests were carried out. The model was subjected to accelerated aging with high voltage stress. This accelerated aging was followed by PDC test was carried out in frequency domain known as frequency domain spectroscopy (FDS). In this paper Polarization and Depolarization Current measurement (PDC) technique is applied to determine moisture content of a HV coil Model. © 2014 IEEE.


Sharmila V.,Kamala Institute of Technology and Science | Hari Krishna E.,Kakatiya University | Ashoka Reddy K.,Kakatiya Institute of Technology and Science
Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 | Year: 2013

In this paper a cumulant based Teager energy operator (TEO) method is proposed to enhance the morphological features of noisy stress ECG signals which are corrupted with Gaussian noise, and other artifacts like baseline wander. It uses higher order statistical (HOS) cumulants in combination with nonlinear TEO required for the analysis of nonlinear and non stationary signals. Higher order cumulants suppress the Gaussian noise and TEO derives an energy from nonlinear components in time and frequency domains. It exhibits an attractive feature of retrieving a clean ECG from noisy recordings with extremely poor SNR of up to 10dB. The mean of Teager energy (TE) in time as well as frequency domains and improvement in signal to noise ratio (SNRI) are the statistical measures used for classification. Results reveal the efficacy of the proposed method in improving the signal to noise ratio and computing the energy in time and frequency domains. © 2013 IEEE.


Nagaraju A.,Kamala Institute of Technology and Science | Ramachandram S.,Osmania University | Eswar B.,Kamala Institute of Technology and Science
Journal of Emerging Technologies in Web Intelligence | Year: 2010

A mobile ad hoc network (MANET) is a wireless network that does not rely on any fixed infrastructure (i.e., routing facilities, such as wired networks and access points), and whose nodes must coordinate among themselves to determine connectivity and routing. The broadcast can target a portion of the network (e.g. gathering neighborhood information), or the entire network (e.g., discovering routes on demand). Broadcasting of signaling and data in MANETs raise redundant transmission of control packets to overcome these problems we applied dominating set and Adaptive partial Dominating (APDP) approach to existing routing protocols such as Ad-hoc On-demand Distance Vector (AODV). The focus of this paper is to apply the concept of DS and APDP to AODV and evaluate the performance of dominating sets in AODV that improve broadcasting, End-to-End Delay, Network load, Packet Latency, and also maintains secure packet transmission. © 2010 ACADEMY PUBLISHER.


Sharmila V.,Kamala Institute of Technology and Science | Harikrishna E.,KU CE and T | Reddy K.N.,Government Maternity Hospital | Reddy K.A.,Kakatiya Institute of Technology and Science
2013 IEEE Conference on Information and Communication Technologies, ICT 2013 | Year: 2013

Electrocardiogram (ECG) signal gets corrupted with artifacts, such as 50/60 Hz power line interference (PLI), electromyogram (EMG) and baseline wander, making it difficult to diagnose the cardiac abnormalities. This paper presents autoregressive (AR) modelling of cumulants for enhancement of ECG signals. Higher order spectral (HOS) cumulants possess many properties that make it an effective tool for the analysis of nonlinear and non stationary signals like ECG. Novelty of the proposed algorithm is that it combines the higher order spectral cumulant properties in conjunction with AR modelling. Results on the records of MIT-BIH data base revealed that the proposed algorithm is effective in reducing the noise and enhancing the ECG data with low root mean square error (RMSE), root mean square variance (RMSV), root mean square deviation (RMSD) and improved signal to Noise Ratio (SNRI). © 2013 IEEE.


Archana T.,Kakatiya University | Venugopal T.,JNTUH College of Engineering | Kumar M.P.,Kamala Institute of Technology and Science
International Conference on Signal Processing and Communication Engineering Systems - Proceedings of SPACES 2015, in Association with IEEE | Year: 2015

Face is the primary index for imparting the identity. Automated face detection is one of the interesting field of research. Face detection of digital image has acquired much importance and interest in last two decades, which has applications in different fields. Computerizing the process needs many image processing methods. In this paper, a new face detection approach using color base segmentation and morphological operations is presented. The algorithm uses color plane extraction, background subtraction, thresholding, morphological operations(such as erosion and dilation ), filtering (to avoid false detection). Then particle analysis is done to detect only the face area in the image and not the other parts of the body. The color planes are extracted using vision module the RGB color space is converted into suitable color space such as HSV and YCbCr. The algorithm can be used to detect both single as well as multiple persons in a image. Experimental results of the algorithm show that, it is good enough to detect the human faces with an accuracy of 93% i.e., the efficiency of the detection is up to 93%. © 2015 IEEE.

Loading Kamala Institute of Technology and Science collaborators
Loading Kamala Institute of Technology and Science collaborators