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Anuratha M.,Thamirabharani Engineering College | Jawahar A.,Nmssvn College | Umadevi M.,Mother Teresa Womens University | Sathe V.G.,University Campus | And 5 more authors.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2015

Silver nanoparticles (Ag NPs) were prepared by solution combustion method with urea as fuel. Silver nanoparticles were characterized by UV-visible spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. Surface-enhanced Raman scattering (SERS) of 2-bromo-3-methyl-1,4-dimethoxy-9,10-anthraquinone (BMDMAQ) adsorbed on silver nanoparticles was investigated. The orientation of BMDMAQ on silver nanoparticles was inferred from nRs and SERS spectral features. Density functional theory (DFT) calculation was also performed to study the theoretical performance. The observed spectral features such as the high intensity of C-H out-of-plane bending mode and ring C-C stretching mode revealed that BMDMAQ adsorbed on silver surface through 'stand-on' orientation. Anthraquinone (AQ) derivatives have wide biomedical application which includes laxatives, antimalarials and antineoplastics used in the treatment of cancer. This present study would help to identify the interaction of drug molecules with DNA. © 2015 Elsevier B.V. All rights reserved. Source


Anuratha M.,Thamirabharani Engineering College | Jawahar A.,Nmssvn College | Umadevi M.,Mother Teresa Womens University | Sathe V.G.,University Campus | And 5 more authors.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2015

(Graph Presented) SERS provides essential data regarding the interaction of molecules in drugs with DNA. In the present study silver nanoparticles were synthesized using a solution combustion method with urea as fuel. The prepared silver nanoparticles are rod like structure. Surface-enhanced Raman scattering (SERS) of N-(1-2-bromophenyl)-2-(2-nitrophenyl)ethyl)-4-methylbenzenesulfonamide (BrS) adsorbed on the silver nanoparticle was studied. The nRs and Raman spectral analysis reveal that the BrS adsorbed tilted orientation on the silver surface. Vibrational modes of nRs along with HF calculations are also performed to study the HOMO and LUMO behavior and vibrational features of BrS. © 2014 Elsevier B.V. All rights reserved. Source


Anuratha M.,Thamirabharani Engineering College | Jawahar A.,Nmssvn College | Umadevi M.,Mother Teresa Womens University | Sathe V.G.,UGC-DAE Consortium for Scientific Research | And 4 more authors.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2014

In the present study, the silver nanoparticles were synthesized using a solution combustion method with urea as fuel. The prepared silver nanoparticles show an FCC crystalline structure with particle size of 59 nm. FESEM image shows the prepared silver is a rod like structure. The surface-enhanced Raman scattering (SERS) spectrum indicates that the N-(1-(2-chlorophenyl)-2-(2- nitrophenyl)ethyl)-4-methylbenzenesulfonamide (CS) molecule adsorbed on the silver nanoparticles. The spectral analysis reveals that the sulfonamide is adsorbed by tilted orientation on the silver surface. The Hatree Fock calculations were also performed to predict the vibrational motions of CS. This present investigation has been a model system to deduce the interaction of drugs with DNA. © 2014 Elsevier B.V. All rights reserved. Source


Rajarajeswari S.,Thamirabharani Engineering College | Sutha J.,Sethu Institute of Technology
ARPN Journal of Engineering and Applied Sciences | Year: 2015

With the growth of different networking technology and multimedia technology the real time delivery of multimedia content becomes an imperative field. Most of the applications such as video conferencing need multimedia transmission techniques that send multimedia data from one end to another with enhanced efficiency in quality and minimized delay. Conventional packet fragmentation schemes shed a packet if all its fragments are not received correctly. But video data is loss tolerant and delay-sensitive. In this paper we propose a new family of delay based fragmentation algorithm which reduces the packet loss and delay thereby attain Quality of service in Multimedia applications. © 2006-2015 Asian Research Publishing Network (ARPN). Source


Nelson kennedy babu C.,Thamirabharani Engineering College
Journal of Theoretical and Applied Information Technology | Year: 2014

Manual segmentation by individual specialists on medical image dataset is time-consuming, expensive, and suffers from considerable inter and intra rater inconsistency. In addition segmentation is hard for the individual expert to combine the information from numerous portions and various channels when multi spectral data has to be examined. Unsupervised segmentation images as occlusions of textures, designed based on local histogram is well-suited to a broader class of images. The model proved that the local histograms were approximately the convex combinations of the value distributions of its component textures but did not provide with a richer characterization of textures and the pixel wise labeling consumed more time. Texture classification of images with multinomial latent model used a mixture density to obtain spatially smooth class segment. But better segmentation was not achieved for speckle noisy biomedical images and the texture classification of images increased the computational cost. To overcome the poor categorization of texture on medical images, the incorporation of neighborhood-based segmentation and binomial classifier tree-based sorting (NS-BCTS) is applied to demonstrate its utility in detecting the noisy speckle biomedical images in medical imagery. To start with, the neighborhood-based segmentation displays the features of rich set in terms of shape, position, color and neighborhood relations. The features extracted are then given as input to the binomial classifier tree-based sorting, with the data label obtained from the experts to minimize the time consuming process. The binomial classifier tree-based sorting examines each collective feature and labels it across the range to determine the computational cost. The experiment is conducted on biomedical image (i.e.,) lung cancer dataset with the factors such as time consumption, computational cost, running time, accuracy and feature categorization efficiency. © 2005 - 2014 JATIT & LLS. All rights reserved. Source

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