Rajiv Gandhi Institute of Technology, named after the late Prime Minister Sri. Rajiv Gandhi, run by the Government of Kerala, started functioning in 1991. Government started this institution with a view of making it a center for post graduation and research studies. The college is affiliated to the Mahatma Gandhi University Kottayam, Kerala. Wikipedia.
Arif M.A.,Rajiv Gandhi Institute of Technology
Proceedings of IEEE International Conference on Emerging Technological Trends in Computing, Communications and Electrical Engineering, ICETT 2016 | Year: 2017
Citation Recommendation is very interesting research area. Many algorithms and methods are proposed for better citation recommendation. Recently, the growth of information technology is high. So the digital libraries are there such as IEEE Xplore and ACM Digital library. The online publications of research papers and conferences are increasing day by day. This makes citation recommendation is a very challenging one. In this paper, propose a citation recommendation method that uses citation relations and similarity between many other papers. The basic method consists of recommend citations by cross references. If one paper is co-occurred in two or more citing papers, then they are similar to some extent. After that, these citing papers are pairwise compared with their contents to get similarities between them. Here, evaluate the proposed method in real word datasets such as IEEE journals. © 2016 IEEE.
Bandary B.,Andhra University |
Hussain Z.,Rajiv Gandhi Institute of Technology |
Kumar R.,Rajiv Gandhi Institute of Technology
Materials Today: Proceedings | Year: 2016
Increasing the demand for clothing and simultaneous increase in production activities, largely responsible for the textile dye waste. To lower the pollution of colouring compounds in the textile industries, a robust and sustainable treatment process called biodegradation is useful. In the present study the parametric effect namely the effect of carbon and nitrogen sources on Escherichia coli in removing methylene blue and methyl orange dyes is discussed. Analysing the results shows that the Glucose and ammonium sulphate are proven to be the best carbon and nitrogen sources respectively, with some usage pause on the maintenance of experimental conditions. © 2016 Elsevier Ltd. All rights reserved.
Krishnapriya K.S.,Rajiv Gandhi Institute of Technology
International Conference on Computer, Communication, and Signal Processing: Special Focus on IoT, ICCCSP 2017 | Year: 2017
Fingerprint is an important measure used to detect an unknown victim, suspect or witness. It has a major role in verifying records to explore links and matches between a suspect and a crime. Fingerprints are also used for security reasons, such as an entrance control at important buildings. But the quality of fingerprint images can easily get degraded by skin dryness, wet, wound and other types of noises. Hence denoising of fingerprint images is a necessary step in systems for automatic fingerprint recognition. This paper suggests a 3-stage process for the removal of noise from fingerprint images, through exploring external correlations and internal correlations, with the help of a set of correlated images. Internal and external data cubes are built for each noisy patch by discovering identical patches from the corresponding noisy and internet based images. External denoising in the first stage is done by a graph based optimization method and internal denoising is done by means of a frequency truncation process. Internal denoising results and external denoising results are combined to obtain the preliminary denoising result. The second stage performs filtering of external and internal cubes and the fused result is in turn passed to the third stage. In the third stage, an image enhancement technique is carried out to obtain the final denoised result. This method is compared with the existing algorithms and the experimental results, in terms of its PSNR (Peak Signal to Noise Ratio) values and SSIM (Structural Similarity Measure) values proved that the method is efficient than all of them. © 2017 IEEE.
Kale R.V.,Rajiv Gandhi Institute of Technology |
Pohekar S.D.,Tolani Maritime Institute
Renewable and Sustainable Energy Reviews | Year: 2012
The growth potential of any state is linked with infrastructure and electricity infrastructure is the most important parameter for economic growth. Maharashtra, a prominent state in India consumes 12 per cent of India's electricity. Maharashtra's power sector is facing the electricity deficit and shortage since early 2005. On the other hand, industrial and service sectors are rising in the state. The present paper discusses electricity situational analysis of the state. Electricity demand analysis has been presented and comparison of state electricity demand vis-à-vis Mumbai's demand (state capital) has been carried out for two years. Variation for monthly average demand for two years and load shedding have also been analyzed. Power supply situation analysis and analysis of major power suppliers have been carried out. The State Load Distribution Center data is used to depict the load variation for a typical day. Interventions needed to sustainably meet the growing demands are also discussed. © 2012 Elsevier Ltd. All right reserved.
Shukla A.,Rajiv Gandhi Institute of Technology |
Aberg S.,Lund University
Physical Review C - Nuclear Physics | Year: 2014
Nuclei with a central region of low nucleonic density, "bubble" nuclei, are studied. In particular, the possibility of bubbles in deformed nuclei is discussed, concentrating on experimentally accessible light nuclei. Utilizing the relativistic mean field (RMF) model we find favorable candidates in the prolately deformed 24Ne nucleus and the mirror nuclei 32Si and 32Ar with oblate shapes. © 2014 American Physical Society.
Rajpoot M.K.,Rajiv Gandhi Institute of Technology
Computers and Fluids | Year: 2016
The present paper deals with the dispersion relation preserving (DRP) analysis of the Robert-Asselin type filters coupled with leapfrog time integration method for time dependent non-dispersive and dispersive model systems. As, leapfrog time advancement method is widely used in the numerical modeling of atmosphere and ocean dynamics, despite the fact that in addition to physical mode it also admits a spurious mode. This is the major disadvantage of leapfrog time integration scheme in discrete computing. To suppress the spurious mode associated with leapfrog time integration method, Robert-Asselin type filters are extensively used in the literature. Here, the dispersion analysis is based on the spectral analysis by considering filtered/unfiltered leapfrog time integration method along with spatial discretization schemes. Spatial discretization is performed using second order centered difference and optimized compact schemes. Furthermore, to assess the efficacy of these methods one dimensional convection equation is used as a model equation for the non-dispersive case, while linearized rotating shallow water equations (LRSWE), as a model test problem for the dispersive case. © 2016 Elsevier Ltd.
Sharma A.,Rajiv Gandhi Institute of Technology
Renewable and Sustainable Energy Reviews | Year: 2011
Energy is considered a prime agent in the generation of wealth and a significant factor in economic development. Energy is also essential for improving the quality of life. Development of conventional forms of energy for meeting the growing energy needs of society at a reasonable cost is the responsibility of the Government. Limited fossil resources and environmental problems associated with them have emphasized the need for new sustainable energy supply options that use renewable energies. Development and promotion of non-conventional/alternate/new and renewable sources of energy such as solar, wind and bio-energy, etc., are also getting sustained attention. Alternative energy news source has long asserted that there are fortunes to be made from smart investments in renewable energy. Solar power is one of the hottest areas in energy investment right now, but there is much debate about the future of solar technology and solar energy markets. This report examines various ways in which solar power is precisely such an opportunity. © 2010 Elsevier Ltd. All rights reserved.
Hemanth J.,Rajiv Gandhi Institute of Technology
Composites Part B: Engineering | Year: 2011
This paper describes the fabrication and testing of aluminum alloy MMCs reinforced with fused silica particles cast in sand moulds containing metallic and nonmetallic chills. Fused silica particles of size 50-100 μm were dispersed (3-12 wt.%) into the matrix. The resulting composites cast were tested for their microstructure, strength, hardness, and wear behavior. Microstructural studies indicate good bonding along with uniform distribution of the dispersoid. Strength, hardness and wear resistance increase up to 9 wt.% additions of dispersoid and copper chill was found to be the best because of its high volumetric heat capacity. © 2011 Elsevier Ltd. All rights reserved.
Mandal I.,Rajiv Gandhi Institute of Technology
Knowledge-Based Systems | Year: 2014
This research work adduces new hybrid machine learning ensembles for improving the performance of a computer aided diagnosis system integrated with multimethod assessment process and statistical process control, used for the spine diagnosis based on noninvasive panoramic radiographs. Novel methods are proposed for enhanced accurate classification. All the computations are performed considering steep error tolerance rate with statistical significance level of 5% as well as 1% and established the results with corrected t-tests. The kernel density estimator has been implemented to distinguish the affected patients against healthy ones. A new ensemble consisting of Bayesian network optimized by Tabu search algorithm as a classifier and Haar wavelets as the projection filter is used for relevant feature selection and attribute's ranking. The performance analysis of each method along with major findings is discussed using various evaluation metrics and concludes with propitious results. The results are compared to the existing SINPATCO platform that uses MLP, GRNN, and SVM. The optimization of machine learning algorithms is obtained using Design of Experiments scheme to achieve superior prediction accuracy. The highest classification accuracy obtained is 96.55% with sensitivity, specificity of 0.966 and 0.987 respectively. The objective is to enhance the software reliability and quality of spine disorder diagnosis using medical diagnostic system and reinforce the viability of precise treatment. © 2014 Elsevier B.V. All rights reserved.
Sharma A.,Rajiv Gandhi Institute of Technology |
Shukla A.,Rajiv Gandhi Institute of Technology
Energy and Buildings | Year: 2015
This paper deals with the thermal cycle tests of the binary mixtures based on fatty acids, i.e. capric acid (CA), lauric acid (LA), myristic acid (MA), palmitic acid (PA) and stearic acid (SA). Overall, 13 binary mixtures, i.e. CA-LA (40/60 wt.%, 50/50 wt.%, 60/40 wt.%, 70/30 wt.% and 80/20 wt.%), CA-MA (70/30 wt.%, 80/20 wt.% and 90/10 wt.%), CA-PA (70/30 wt.%, 80/20 wt.% and 90/10 wt.%) and CA-SA (60/40 wt.% and 90/10 wt.%) were developed as latent heat energy storage materials for the building applications. The Differential Scanning Calorimetry (DSC) technique was applied to the binary mixtures after 0, 50, 100, 150, 200, 250, 300, 600, 900, 1200 melt/freeze cycles to measure the melting temperatures and the latent heats of fusion. The DSC results showed that the changes in melting temperature were in between -1.69°C to 4.33°C, and the changes in the latent heat fusion was -35% to +25%. These results show that the melting temperatures and latent heat values of the PCMs are in the range of about 21-30°C and 100-170 J/g which showed that these materials have good thermal stability up to 1200 thermal cycles and can be potentially applied for building applications. © 2015 Elsevier B.V. All rights reserved.