h) 2018 - 49 Documents

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Start date: 2018End date: 2018

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    PSIDIUM GUAJAVA: A NOVEL PLANT IN THE SYNTHESIS OF SILVER NANOPARTICLES FOR BIOMEDICAL APPLICATIONS
    (Innovare Academic Sciences, 2018) Sharmila, C; Ranjith Kumar, R; Chandar Shekar, B
    Synthesis of silver nanoparticles (AgNPs) using a simple, cost-effective and environmentally friendly green route approach and to study the antibacterial activity of AgNPs against human pathogens.
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    VIRTUAL SCREENING OF TREATED PISTACHIO VERA SHELL POWDER AS A POTENTIAL SORBENT IN SEQUESTERING UBIQUITOUS DIVALENT METAL IONS FROM AQUEOUS MATRICES
    (Oriental Journal of Chemistry, 2018) Shyamala Devi, N; Muthulakshmi Andal, N; Vivithabharathi, K
    Water pollution due to noxious heavy metals such as Hg(II), Cr(VI), Cd(II) and Pb(II) ions etc., has been tremendously focused gaining attention towards social benefit. Increasing concentrations of these metals into the ecosystem constitute a severe health hazard due to their toxicity, accumulation and bio-magnification throughout the food chain. Lead contamination of drinking water is a great threat through varied sources viz., lead pipes, plating units etc. Pistachio vera shell (PVS) is a hard layer that surrounds the delicious kernel of the nut. The current work evaluates the feasibility of powdered Pistachio vera shell (PVSP) - a biowaste for sequestering Pb (II) ions is treated with 0.1N HCl and 0.1N NaOH to enhance its sorption efficacy (TPVSP). SEM, FTIR and microscopic analyses are recorded for characterising the chosen sorbent. Batch experimental studies are performed to assess the equilibration between the sorbate and the sorbent. The competence of the sorbent material is experimentally verified through various operating factors viz., particle size and dosage of TPVSP, agitation time interval between TPVSP and Pb(II) ions, initial concentrations of Pb(II) ions, pH of the adsorption medium, effects of cations, anions, co-ions and influence of temperatures on Pb(II) – TPVSP system. The residual concentrations of Pb (II) ions from aqueous solutions are analysed using Atomic Absorption Spectrophotometer (Shimadzu-AA-6200). Langmuir and Freundlich models are applied to describe the adsorption capacity. Column studies are conducted to ensure the quantitative estimation of TPVSP in trapping 99% of sorbate species at a dose of 40 mg the flow rate being, 100 ml/10 min. assuring the bulkiness of the materia
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    A HYBRID LINEAR KERNEL WITH PCA IN SVM PREDICTION MODEL OF TAMIL WRITING PATTERN
    (International Journal of Simulation: Systems, Science and Technology, 2018) Thendral, Tharmalingam; Vijaya, Vijayakumar
    Principal Component Regression (PCR) is a regression analysis technique based on Principal Component Analysis (PCA) which enables the identification of the principal components that can be used in a linear kernel and Support Vector Machine (SVM) as a classifier. In PCR, instead of regressing the dependent variable on the explanatory variables directly, the principal components of the explanatory variables are used as regresseors. Only a subset of all the principal components is made use of for regression, thus making PCR a kind of regularized procedure. The principal components with higher variances are selected as regressors and used in SVM linear kernel to estimate the coefficients of the kernel and the linear kernel is specified as Principal Component Kernel–Support Vector Machine (PCK-SVM). Writer Identification in Tamil handwriting is implemented by employing PCK-SVM and the results of the PCK-SVM are compared with our Weighted Least Square regression Kernel based Support Vector Machine (WLK-SVM) and Bayesian linear regression Kernel based Support Vector Machine (BLK-SVM)models. These methods are evaluated on several text images of handwriting at character, word and paragraph levels. The results show that modified linear kernel performs very well with minimum time taken to classify the writer. Performance comparison results of three kernels achieved highest performance of 94.9% accuracy in PCK-SVM than in WLK of 90.8% and BLK of 92.3% accuracy.
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    EFFECT OF ROTATION ON THERMAL STABILITY OF SUPERPOSED FLUID AND POROUS LAYER
    (International Journal of Engineering Research and Technology, 2018) Aiswarya, S; Arunachalam, T; Sumathi, K
    In this paper linear stability of a viscous incompressible fluid saturated porous medium under the influence of rotation is investigated. Closed form solutions of velocity, temperature and fluid vorticity in terms of wave number as perturbation parameter have been obtained. The influence of various non-dimensional parameters such as Taylor number, Grashof number, Prandtl number, Darcy number, porosity and wave number on stability characteristics of flow field are discussed numerically.
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    ASSESSMENT OF LOW CARBON STEEL CORROSION INHIBITION BY ECO-FRIENDLY GREEN CHAENOMELES SINENSIS EXTRACT IN ACID MEDIUM
    (The Korean Electrochemical Society, 2018-07-16) Ill-Min, Chung; Venkatesan, Hemapriya; Kanchana, Ponnusamy; Natarajan, Arunadevi; Subramanian, Chitra; Chi-Hee, Youn; Seung-Hyun, Kim; Mayakrishnan, Prabakaran
    The impact of methanol extract of Chaenomeles sinensis (C. sinensis) leaves on acid corrosion of low carbon steel was assessed by gravimetric and electrochemical methods. Phytochemical characterization by total phenolic content (TPC), and total flavonoids content (TFC) of the extract was performed. The TPC and TFC concentrations were identified as 193.50 and 40.55 mg/g. Efficiency increased remarkably in the presence of inhibitor and found as concentration dependent. A maximum inhibition efficiency of 93.19% was achieved using 2000 ppm of the C. sinensis inhibitor. Impedance and surface morphology analysis by SEM and AFM revealed that the anticorrosive activity results from the protective film of phytochemical components of C. sinensis extract adsorbed on the metal surface.
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    MACROCYCLIC COMPOUNDS AS GREEN CORROSION INHIBITORS FOR ALUMINIUM: ELECTROCHEMICAL, SURFACE AND QUANTUM CHEMICAL STUDIES
    (International Journal of Corrosion and Scale Inhibition, 2018-09-28) Ansari, K R; Ramkumar, S; Chauhan, D S; Salman, Md; Nalini, D; Srivastava, V; Quraishi, M A
    In the present work, two macrocyclic compounds namely 5,6,11,12-tetramethyl1,2,4,7,8,10 hexaazacyclododeca-4,6,10,12-tetraene-3,9-dithione (TMCD) and 5,6,11,12- tetraphenyl-1,2,4,7,8,10-hexaazacyclododeca-4,6,10,12-tetraene-3,9-dithione (TMPD) have been synthesized and for the first time reported as inhibitors against the corrosion of aluminium in 1 M hydrochloric acid. The synthesized compounds were characterized using 1H NMR and 13C NMR. The corrosion inhibition behaviour of TMCD and TMPD was studied using gravimetric measurements, electrochemical impedance spectroscopy and potentiodynamic polarization studies. The surface analysis was carried out using AFM and SEM. Theoretical studies on the adsorption behaviour of inhibitor were carried out using the Density Functional Theory method. A detailed study of the effect of temperature and the influence of immersion time is presented using weight loss technique. Potentiodynamic polarization study proves that the corrosion inhibition efficiencies of TMCD and TMPD at 400 mg L –1 concentration are 97.30% and 89.71% respectively. Both the inhibitors behaved as mixed type but exhibit cathodic predominance. The results of EIS-Nyquist plots show inductive behavior at low frequency characteristic of the electrochemical behaviour of aluminium. The increase in polarization resistance with concentration suggests the adsorption and corrosion inhibition behaviour for both TMCD and TMPD. The AFM studies reveal a considerable decrease in surface roughness in the presence of inhibitors compared to blank sample and the SEM images show a highly smooth surface of the metal sample in the presence of inhibitors. The Fukui functions, global softness and Mulliken charges reveal that the sites for electrophilic attack are the hetero atoms. The frontier molecular orbital energies, the molecular orbital energy gap and the other quantum chemical parameters corroborated the experimental observations and suggested a better performance of TMCD compared to TMPD molecule.
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    AN EFFICIENT CONVOLUTIONAL NEURAL NETWORK BASED CLASSIFIER TO PREDICT TAMIL WRITER
    (Periodicals of Engineering and Natural Sciences, 2018-06) Thendral, Tharmalingam; Vijaya, Vijayakumar
    Identification of Tamil handwritten calligraphies at different levels such as character, word and paragraph is complicated when compared to other western language scripts. None of the existing methods provides efficient Tamil handwriting writer identification (THWI). Also offline Tamil handwritten identification at different levels still offers many motivating challenges to researchers. This paper employs a deep learning algorithm for handwriting image classification. Deep learning has its own dimensions to generate new features from a limited set of training dataset. Convolutional Neural Networks (CNNs) is one of deep, feed-forward artificial neural network is applied to THWI. The dataset collection and classification phase of CNN enables data access and automatic feature generation. Since the number of parameters is significantly reduced, training time to THWI is proportionally reduced. Understandably, the CNNs produced much higher identification rate compared with traditional ANN at different levels of handwriting.
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    A STUDY ON ASSESSMENT OF THE LIFE-STYLE FEATURES OF CUSTOMERS’ TOWARDS VARIOUS LEADING TEXTILE SHOWROOMS IN COIMBATORE CITY
    (Blue Eyes Intelligence Engineering & Sciences Publication, 2018-12) Judithpriya, R; Maheshwari, M; Lakshmi, G
    The clothing retail industry in Coimbatore city of Tamilnadu is one such industry which is characterized by intensifying competition from both local and national companies leading to rise in more sophisticated and demanding customers. Consequently, retailers today aims to differentiate themselves by outperforming their competitors. Clothing has identities and images, and consumers seek those apparels that match their selfimage or the image they would like to project to others. The clothing retail industry in Coimbatore city of Tamilnadu is one such industry which is characterized by intensifying competition from both local and national companies leading to rise in more sophisticated and demanding customers. This research paper analysis assess the life style features of the customers’ towards various leading textile showrooms in Coimbatore City
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    ANTIPYRETIC POTENTIAL OF AQUEOUS LEAF EXTRACT OF ANNONA MURICATA.L AND SPERMACOCE ARTICULARIS. L.F.ON YEAST-INDUCED PYREXIA IN RATS
    (Innovare Academic Sciences, 2018) Maruvoor Arasi, K; Krishnaveni, C
    The objective of this study is to evaluate the potential of in vivo antipyretic activity of the aqueous leaf extracts of Annona muricata L. and Spermacoce articularis. L.f.
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    LINEAR POLYESTERS AS EFFECTIVE CORROSION INHIBITORS FOR STEEL REBARS IN CHLORIDE INDUCED ALKALINE MEDIUM – AN ELECTROCHEMICAL APPROACH
    (Elsevier, 2018-03-20) Chan Basha, Nusrath Unnisa; Gowraraju, Nirmala Devi; Venkatesan, Hemapriya; Subramanian, Chitra; Ill-Min, Chung; Seung-Hyun, Kim; Mayakrishnan, Prabakaran
    As a motto of framing the strategies to minimise the deterioration in steel reinforced concrete structures as well as the fact that the work carried out with polymers are rare and scanty, polyesters namely Poly (Glycerol azealate) (PGAZ) and 4-(1-(4-methoxy phenyl) cyclo hexyl)phenyl 9-oxodecanoate (MPOD) were synthesised and evaluated for rebar corrosion in simulated concrete pore solution (SCP) for the first time at selected concentrations of 10, 100, 1000 ppm levels with an aid of electrochemical impedance and potentiodynamic polarisation techniques. Nyquist plots favoured increased Rct values suggesting the formation of barrier. Tafel plots represented cathodic inhibition. The experimental datas were best fitted with Langmuir adsorption isotherm facilitating monolayer adsorption. Both the methods employed were in good agreement with each other favouring maximum inhibition efficiency of 71.81% for MPOD and minimum of 57.64% for PGAZ primarily due the difference in aromatic sites as revealed in mechanism.