Kumar B.M.V.,Vidya Vikas Institute of Engineering and Technology |
Ananthan H.,Vidya Vikas Institute of Engineering and Technology
Journal of Building Engineering | Year: 2017
This experimental work deals with the assessment of strength and water absorption characteristics of cement stabilized masonry block (CSMB) units made with brick powder (BP) and fine recycled concrete aggregate (FRCA) along with pozzolanic materials such as silica fume (SF), fly ash (FA) and ground granulated blast furnace slag (GGBS) as partial replacement for cement. The basic tests such as, dry density, 28 days wet compressive strength, water absorption and rate of moisture absorption are performed on CSMB units of size 190×90×90 mm. The correction factors that are available in the literature, with respect to fired clay bricks and compressed earth blocks, so as to account for the confinement of specimens by platen restraints at the ends are used to assess the uniaxial strength of CSMB units. The corrected average values of wet compressive strength of CSMB units at 28 days are found to meet the minimum requirement of 3.5 MPa. The percentage of water absorption is found to be higher, but, still within permissible limit of 18% by weight. The average dry density is also found to meet the minimum requirement of 1750 kg/m3. The rate of moisture absorption with time is found to follow an exponential trend. © 2017 Elsevier Ltd
Suma,Vidya Vikas Institute of Engineering and Technology
2015 International Conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2015 | Year: 2015
Performing an effective, reliable, and faster compression is one of the important processes in managing the radiological images that relates to either storage or transmission purpose. Ensuring no loss of significant clinical information during transmission along with faster computational capabilities are quite less to find in literature pertaining to medical image compression techniques. Therefore, this paper introduces a technique called as VCAR or Vedic Compression Algorithm over Region of interest that uses the potential vertical and cross over multiple characteristics of Urdhava Tiryakbhyam sutra in Vedic mathematics. VCAR takes the input image as region of interest extracted by author's prior technique and then subjects it to compression. The outcome of the study was found to be superior compared to frequently used DCT-based compression techniques with respect to computational speed, Peak Signal to Noise Ratio (PSNR), visual quality in the forms of bits per pixels over multiple standard medical image databases. © 2015 IEEE.
Suma,Vidya Vikas Institute of Engineering and Technology
International Journal of Electrical and Computer Engineering | Year: 2016
Compressing the medical images is one of the challenging areas in healthcare industry which calls for an effective design of the compression algorithms. The conventional compression algorithms used on medical images doesn't offer enhanced computational capabilities with respect to faster processing speed and is more dependent on hardware resources. The present paper has identified the potential usage of Vedic mathematics in the form of Urdhava Tiryakbhyam sutra, which can be used for designing an efficient multiplier that can be used for enhancing the capabilities of the existing processor to generate enhance compression experience. The design of the proposed system is discussed with respect to 5 significant algorithms and the outcome of the proposed study was testified with heterogeneous samples of medical image to find that proposed system offers approximately 57% of the reduction in size without any significant loss of data. Copyright © 2016 Institute of Advanced Engineering and Science. All rights reserved.
Vijay G.S.,Manipal University India |
Kumar H.S.,NMAM Institute of Technology |
Srinivasa P.P.,NMAM Institute of Technology |
Sriram N.S.,Vidya Vikas Institute of Engineering and Technology |
Rao R.B.K.N.,COMADEM International
Computational Intelligence and Neuroscience | Year: 2012
The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR) and reducing the root-mean-square error (RMSE). In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN) and the Support Vector Machine (SVM), for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB) test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher's Criterion (FC). Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal. © 2012 Vijay G. S. et al.
Sannappa J.,University of Mysore |
Ningappa C.,Vidya Vikas Institute of Engineering and Technology |
Indian Journal of Pure and Applied Physics | Year: 2010
The activities of 226Ra, 232Th and 40K and natural radiation levels have been measured at granite regions of Karnataka State, India using HPGe detector and scintillometer. In granite region 232Th activity is high compared to 226Ra. The data shows that the activities of 226Ra, 232Th and 40K and ambient y-radiation level were found to be high in comparison to global and Indian average1.
Kumar H.S.,NITTE University |
Srinivasa Pai P.,NITTE University |
Sriram N.S.,Vidya Vikas Institute of Engineering and Technology |
Vijay G.S.,Manipal University India
Procedia Engineering | Year: 2013
Bearings are one of the critical components in rotating machines and the majority of the failure arises from the defective bearings. Bearing failure leads to failure of a machine and unpredicted productivity loss for production facilities. Hence, bearing fault detection and diagnosis is an integral part of the preventive maintenance procedures. In this paper vibration signals for three conditions of a deep groove ball bearing Normal (N), defect on inner race (IR) and defect on outer race (OR) were acquired from a customized bearing test rig, under one load and two speed conditions. Discrete Wavelet Transform (DWT) has been used for vibration signal analysis. The statistical features extracted from the dominant wavelet coefficients are used as inputs to ANN classifier to evaluate its performance. The vibration signals have also been denoised using a new thresholding scheme. A comparison of ANN performance is made based on raw vibration data and denoised data. The ANN performance has been found to be comparatively higher when denoised signals were used as inputs to the classifier. Also various mother wavelet functions (Db8, Db4, Db44 and Sym10) were used to analyze the denoised vibration signals and their performance has been evaluated using the ANN classifiers. © 2013 The Authors. Published by Elsevier Ltd.
Padyana M.,Vidya Vikas Institute of Engineering and Technology |
Thomas B.A.,Vidya Vikas Institute of Engineering and Technology
2nd International Conference on Electronics and Communication Systems, ICECS 2015 | Year: 2015
Raaga in carnatic classical music is one of the melodic modes of the music. It is not only characterized by set of five or more musical notes called swaras, but also associated with special ornamentations called gamaka, pauses, frequency changes and many more information. Auto generation of carnatic classical is challenging because of ornamentations. Raaga is the basic foundation for auto generation of carnatic classical. Hence modeling raaga will help to build a lowest level platform. © 2015 IEEE.
Banu M.,Vidya Vikas Institute of Engineering and Technology |
Prasad N.,Vidya Vikas Institute of Engineering and Technology
Kasetsart Journal - Natural Science | Year: 2013
The efficiency of TBHQ (tertiary butyl hydroquinone) as an antioxidant in peanut (Arachis hypogaea) oil was evaluated by ultrasonic studies. The effect of TBHQ on the oxidation stability of peanut oil was examined. The antioxidant-peanut oil system, in parallel with a control experiment, was subjected to heating at 180 ± 5 °C continuously for a daily period of 4 h for four consecutive days. The parameters used to assess the thermal degradation and oxidation properties of the antioxidant in oils were: ultrasonic velocity, viscosity, density and peroxide value. The adiabatic compressibility, intermolecular free length, relaxation time and acoustic impedance were calculated from the experimental data. Changes in the viscosity, density and ultrasonic velocity in the control were from 0.26553 × 10-1 to 1.28729 × 10-1 10kg.m-1.s-1, 912.59 to 938.31 kg.m-3 and 1422 to 1480 m.s-1, respectively, and in peanut oil with 200 ppm TBHQ were from 0.29129 × 10-1 to 0.573459 × 10-1 kg.m-1.s-1, 913.58 to 922.45 kg.m-3 and 1426 to 1446 m.s-1, respectively, with the 16 h of heating. The results obtained showed an improvement in the thermal degradation and oxidation stability of the formulation compared with the base oil, while ultrasonic studies helped to determine the stability of the edible oil. Hence, it is recommended that peanut oil with TBHQ can be used for frying without any adverse effect and ultrasonic properties can be used for the assessment of the stability of frying oil.
Varalatchoumy M.,Dayananda Sagar College of Engineering |
Ravishankar M.,Vidya Vikas Institute of Engineering and Technology
Smart Innovation, Systems and Technologies | Year: 2016
A robust and efficient CAD system to detect and classify breast cancer at its early stages is an essential requirement of radiologists. This paper proposes a system that detects, classifies and also recognizes the stage of the detected tumor which helps radiologists in reducing false positive predictions. A MRM image is preprocessed using histogram equalization and dynamic thresholding approach. Segmentation of the preprocessed image is carried out using a novel hybrid approach, which is a hybridization of PSO and K-Means clustering. Fourteen textural features are extracted from the segmented region in order to classify the tumor using Artificial Neural Network. If the tumor is classified as malignant then the stage of the tumor is identified using size as a key parameter. © Springer India 2016.
Manoj S.,Vidya Vikas Institute of Engineering and Technology |
Puttaswamy P.S.,P.A. College
Lecture Notes in Electrical Engineering | Year: 2014
Worldwide fast depletion of conventional energy resources necessitates the implementation of renewable energy sources for generation to satisfy the growing demand. Since last decade, technological innovations and a changing economic and regulatory environment have resulted considerable revival of interest in connecting wind generation to the grid. Utilities are seeking to understand possible impacts on system operations when a large amount of wind power is introduced into the electric power system. Producers of renewable energy must condition the power produced in order to interconnect with the power grid and not interface with the grid's overall performance. In these aspects, flexible AC transmission systems (FACTS) technology plays a vital role in enhancing the power system performance and improving the power quality of the system. This paper concentrates on power quality issues when wind power integrates with grid and the solution with the usage of STATCOM. An attempt is made with IEEE 16 Bus, 3 feeder test system, and modeled for simulation study using MATLAB/SIMULINK simulation. Scopes obtained from the simulation results are proven for the improvement of voltage profile which in turn improves the overall power quality issues. © 2014 Springer India.