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Search Results: 1 - 10 of 119625 matches for " T.;Raj "
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Cloudpress 2.0: A MapReduce Approach for News Retrieval on the Cloud
Arockia Anand Raj,T. Mala
Computer Science , 2012,
Abstract: In this era of the Internet, the amount of news articles added every minute of everyday is humongous. As a result of this explosive amount of news articles, news retrieval systems are required to process the news articles frequently and intensively. The news retrieval systems that are in-use today are not capable of coping up with these data-intensive computations. Cloudpress 2.0 presented here, is designed and implemented to be scalable, robust and fault tolerant. It is designed in such a way that, all the processes involved in news retrieval such as fetching, pre-processing, indexing, storing and summarizing, exploit MapReduce paradigm and use the power of the Cloud computing. It uses novel approaches for parallel processing, for storing the news articles in a distributed database and for visualizing them as a 3D visual. It uses Lucene-based indexing for efficient and faster retrieval. It also includes a novel query expansion feature for searching the news articles. Cloudpress 2.0 also allows on-the-fly, extractive summarization of news articles based on the input query.
Excellent Techniques of Manufacturing Systems: RMS and FMS
V. Malhotra,,T. Raj,,A. Arora
International Journal of Engineering Science and Technology , 2010,
Abstract: Meeting customer demands requires a high degree of flexibility as well as abilities to reconfigure operations for new demands. Based on literature review, various types of flexibilities are presented with aview to clarify their correspondence. This paper highlighted the merits, demerits and applications of RMS and FMS. Different technique of RMS and FMS are overviewed. The recent researches in reconfigurabledesign also viewed in the research paper. The paper is concluded with a future research of flexible and reconfigurable manufacturing system.
Reconfigurable manufacturing system: an overview
Malhotra V.,Raj T.,Arora A.
International Journal of Machine Intelligence , 2009,
Abstract: This paper presents the review of Reconfigurable manufacturing system. That aims at achievingcost effective and rapid system changes needed, by incorporating principle of modularity, integrability andscalability as this new manufacturing system. Reconfigurable manufacturing system promises customizedflexibility in a short time, while the other manufacturing system provides generalized flexibility designed foranticipation variations.This paper shows the definition and background of reconfigurable manufacturing system. In this researchpaper an overview of components of reconfigurable manufacturing system and comparisons of differentmanufacturing system with their merits and demerits are presented. The capabilities of reconfigurablemanufacturing system, challenges of reconfigurable manufacturing system and key role in reconfigurablemanufacturing system are explained. The characteristic of reconfigurable manufacturing system are alsopresented in this research paper.
Denoising of Magnetic Resonance and X-Ray Images Using Variance Stabilization and Patch Based Algorithms
V N Prudhvi Raj,T Venkateswarlu
International Journal of Multimedia & Its Applications , 2013,
Abstract: Developments in Medical imaging systems which are providing the anatomical and physiological details ofthe patients made the diagnosis simple day by day. But every medical imaging modality suffers from somesort of noise. Noise in medical images will decrease the contrast in the image, due to this effect lowcontrast lesions may not be detected in the diagnostic phase. So the removal of noise from medical imagesis very important task. In this paper we are presenting the Denoising techniques developed for removingthe poison noise from X-ray images due to low photon count and Rician noise from the MRI (magneticresonance images). The Poisson and Rician noise are data dependent so they won’t follow the Gaussiandistribution most of the times. In our algorithm we are converting the Poisson and Rician noise distributioninto Gaussian distribution using variance stabilization technique and then we used the patch basedalgorithms for denoising the images. The performance of the algorithms was evaluated using various imagequality metrics such as PSNR (Peak signal to noise ratio), UQI (Universal Quality Index), SSIM (Structuralsimilarity index) etc. The results proved that the Anscombe transform, Freeman & Tukey transform withblock matching 3D algorithm is giving a better result.
VLSI based Design of Multiresolution Median Transform for Digital Image Restoration
Latha T,Raj A,Kumar M
IETE Technical Review , 2007,
Abstract: Multiresolution processing of an image has become increasingly important in the present application areas like image restoration, filtering, enhancement, compression, etc. Although the Fourier Transform has been the mainstay of transform-based image processing, a more recent transformation, called the Wavelet Transform, now makes it easier to compress, transmit, and analyze many images. Another multiscale approach which is an alternative to Wavelet Transform, is the multiresolution median transform. It is a non-linear transform and offers advantages for robust smoothing. This paper presents the VLSI implementation of multiresolution median transform for digital image restoration using Active-VHDL. This transform has many advantages in comparison with Wavelet Transform, such as fast computation, error-free reconstruction, etc. Synthesis is performed with Xilinx FPGA from Virtex-II Pro family which yields users high performance, unlimited reprogrammability, very low cost and provides system clocks upto 200 MHz.
Implementation of ML Using Na ve Bayes Algorithm for Identifying Disease-Treatment Relation in Bio-Science Text
T.F. Michael Raj,S. Prasanna
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: In recent years many successful machine learning applications have been developed, ranging from datamining programs to information-filtering systems that learn users' reading preferences. At the same time, there have been important advances in the theory and algorithms that can be used identify the diseases and treatment relations in a Bio-Science text. Imagine a computer learns from medical records which treatments are most effective for new diseases. Having the machine learning concept behind we have proposed a Machine Learning (ML) approach based on Na ve Bayes (NB) algorithm to improve the automatic disease identification in the medical field. And also we have improved text classification by using an integrated model.
Denoising of Medical Ultrasound Images Using Spatial Filtering and Multiscale Transforms
V N Prudhvi Raj,T Venkateswarlu
International Journal of Computer Science & Information Technology , 2013,
Abstract: Medical imaging became the integral part in health care where all the critical diagnosis such as blocks inthe veins, plaques in the carotid arteries, minute fractures in the bones, blood flow in the brain etc arecarried out without opening the patient’s body. There are various imaging modalities for differentapplications to observe the anatomical and physiological conditions of the patient. These modalities willintroduce noise and artifacts during medical image acquisition. If the noise and artifacts are not minimiseddiagnosis will become difficult. One of the non-invasive modality widely used is ultrasound Imaging whereno question of radiation but suffers from speckle noise produced by the small particles in the tissues who’ssize is less than the wavelength of the ultrasound. The presence of the speckle noise will cause the lowcontrast images because of this the low contrast lesions and tumours can’t be detected in the diagnosticphase. So there is a strong need in developing the despeckling techniques to improve the quality ofultrasound images. Here in this paper we are presenting the denoising techniques for speckle reduction inultrasound imaging. First we presented the various spatial filters and their suitability for reducing thespeckle. Then we developed the denoising methods using multiscale transforms such as Discrete WaveletTransform (DWT), Undecimated Discrete Wavelet Transform (UDWT), dual tree complex wavelettransform (DTCDWT) and Double density dual tree complex wavelet transform (DDDTCDWT). Theperformance of the filters was evaluated using various metrics based on pixel based, correlation based,edge based and Human visual system (HVS) based and we found that denoising using double density dualtree complex discrete wavelet transform is outperformed with best edge preserving feature.
Denoising of Medical Images Using Image Fusion Techniques
V N Prudhvi Raj,T Venkateswarlu
Signal & Image Processing , 2012,
Abstract: Medical Imaging is playing the key role in diagnosing and treatment of diseases such as locating the tumours in brain, thin fractures in bones, detection of cancer cells in early stages etc. For making accurate decisions the images acquired by various medical imaging modalities must be free from noise. So Image denoising became an important pre-processing step in Medical image analysis. Developing the denoising algorithms is a difficult task because diagnostic information must be preserved while removing the noise. Earlier the denoising algorithms were designed in the spatial domain such as median filtering, harmonic filtering, and weiner filtering etc. by directly working on the pixel values, these methods will remove noise while introducing the blur in the denoised images. At present advanced mathematical models such as Partial differential equations which are useful for edge preservation and multiresolution analysis useful for preserving directional oriented information and texture became very popular in developing the denoising techniques. In this paper we are using Total Variational approach (PDE method) and Complex Dual Tree wavelet transform (Multiresolution analysis)method to denoise the medical images and we perform the fusion of the two denoised images resulting from the above denoising techniques. The performance of the proposed algorithm is compared with the existing methods using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index.). The performance of the fusion process is measured using MI (Mutual Information), Edge Association and Spatial Frequency (SF) measures. The results showed that the proposed method is having better PSNR values diagnostically acceptable and very much useful for the diagnosis& treatment phases.
Denoising of Medical Images Using Total Variational Method
V N Prudhvi Raj,T Venkateswarlu
Signal & Image Processing , 2012,
Abstract: Feature extraction and object recognition from images acquired by various imaging modalities are playingthe key role in diagnosing the various diseases. These operations will become difficult if the images arecorrupted with noise. So the need for developing the efficient algorithms for noise removal became animportant research area today. Developing Image denoising algorithms is a difficult operation because finedetails in a medical image embedding diagnostic information should not be destroyed during noiseremoval. In this paper the total variational method which had success in computational fluid dynamics isadopted to denoise the medical images. We are using split Bregman method from optimisation theory tofind the solution to this non-linear convex optimisation problem. The present approach will outperform indenoising the medical images while compared with the traditional spatial domain filtering methods. Theperformance metrics we used to measure the quality of the denoised images is PSNR (Peak signal to noiseratio).The results showed that these methods are removing the noise effectively while preserving the edgeinformation in the images.
Synthesis, Growth and Characterization of 4-Benzeneazoaniline Single Crystal  [PDF]
T. Kishore Kumar, S. Janarthanan, S. Pandi, M. Victor Antony Raj, Kanagalakshmi ?, D. Prem Anand
Journal of Minerals and Materials Characterization and Engineering (JMMCE) , 2010, DOI: 10.4236/jmmce.2010.911069
Abstract: A new organic nonlinear optical material 4-Benzeneazoaniline (C12H11N3) was synthesized by diazotization and diazocoupling mechanisms. Single crystal of 4-Benzeneazoaniline was grown by slow evaporation of methanol solution at room temperature. Transparent crystals with size up_to 13x4x4 mm3 were obtained. Single crystal X-ray diffractometer was utilized to measure the unit cell parameters and to confirm the crystal structure. The structure of compound was further confirmed by FTIR, 1H & 13C NMR and mass spectral analyses. The UV-Vis-NIR result shows that the crystal has a sharp cut off at 220 nm and is nearly 75% transparent over a wide wavelength range enabling it for application in the UV region. The optical energy gap of 4- Benzeneazoaniline was found to be 3.4 eV. Thermal properties of crystals were investigated using thermogravimetric and differential scanning calorimetric analyses, which indicated that the material does not decompose before melting. The NLO test confirms the second harmonic signal generation in the sample.
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