Mepco Schlenk Engineering College

About: Mepco Schlenk Engineering College is a based out in . It is known for research contribution in the topics: Wavelet & Wavelet transform. The organization has 1307 authors who have published 1665 publications receiving 18690 citations.

Available Transfer Capability Determination in the Restructured Electricity Market

Abstract: Deregulation of the electricity industry throughout the world aims at creating a competitive market to trade electricity, which generates a host of new technical challenges to market participants and power system researchers. For transmission systems, it requires non-discriminatory open access to transmission resources. Therefore, for better transmission services support and full utilization of transmission assets, one of the major challenges is to accurately gauge the transfer capability remaining in the system for further transactions, which is termed the available transfer capability (ATC). It is crucial to develop an appropriate ATC determination methodology that enables one to evaluate the realistic transmission transfer capability by accounting for all related important requirements. This article describes the evaluation of single-area ATC using power transfer distribution factors in a combined economic emission dispatch environment. In addition, multi-area ATC is calculated with the inclus...

Flame‐retardant fabric systems based on electrospun polyamide/boric acid nanocomposite fibers

Abstract: To examine the feasibility of developing flame-retardant-textile coated fabric systems with electrospun polyamide/boric acid nanocomposites, fiber webs coated on cotton substrates were developed to impart-fire retardant properties. The morphology of the polyamide/boric acid nanocomposite fibers was examined with scanning electron microscopy. The flame-retardant properties of coated fabric systems with different nanoparticle contents were assessed. The flame retardancy of the boric acid coated fabric systems was evaluated quantitatively with a flammability test apparatus fabricated on the basis of Consumer Product Safety Commission 16 Code of Federal Regulations part 1610 standard and also by thermogravimetric analysis. The 0.05 wt % boric acid nanocomposite fiber web coated on pure cotton fabric exhibited an increment in flame-spreading time of greater than 80%, and this indicated excellent fire protection. Also, the coated fabric systems with 0.05% boric acid nanocomposite fiber webs exhibited a distinct shift in the peak value in the thermal degradation profile and a 75% increase in char formation in the thermooxidative degradation profile, as indicated by the results of thermogravimetric analysis. The results show the feasibility of successfully imparting flame-retardant properties to cotton fabrics through the electrospinning of the polymer material with boric acid nanoparticles. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Bio-active mixed ligand Cu(II) and Zn(II) complexes of pyrimidine derivative Schiff base: DFT calculation, antimicrobial, antioxidant, DNA binding, anticancer and molecular docking studies

Abstract: A new series of bio active Cu(II) and Zn(II) complexes [CuL(phen)](OOCCH3) (1), [ZnL(phen)](OOCCH3) (2), [CuL(bpy)](OOCCH3) (3), [ZnL(bpy)](OOCCH3) (4) have been synthesized using the pyrimidine de...

Image de-noising using double density wavelet transform based adaptive thresholding technique

Abstract: This paper describes an efficient and adaptive method of threshold estimation for removing impulse noise from images, based on Double Density Wavelet Transform (DDWT). The performance of image de-noising algorithms using wavelet transforms can be improved significantly by fixing an optimum threshold value, based on the analysis of the statistical parameters of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. Here the noisy image is first decomposed into many levels to obtain different frequency bands using DDWT. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum threshold value by the proposed method. Experimental results on several test images by using the proposed method show that, the proposed method yields significantly superior image quality and better Peak Signal-to-Noise Ratio (PSNR). Some comparisons with the best available results will be given in order to illustrate the effectiveness of the proposed algorithm.