Nitte Meenakshi Institute of Technology

About: Nitte Meenakshi Institute of Technology is a based out in . It is known for research contribution in the topics: Computer science & Ultimate tensile strength. The organization has 846 authors who have published 644 publications receiving 2702 citations.

A Survey on Multi-resolution Methods for De-noising Medical Images

Abstract: Processing of medical images is important to improve their visibility and quality to facilitate computer-aided analysis and diagnosis in medical science. Such images are usually tainted by noise due to impediments in image capturing devices, unsupportive environment or during transmission over the network. Multi-resolution is a profound technique for decomposing the images into multiple scales and is widely used for image analysis in detail. This paper describes various multi-resolution techniques such as discrete wavelet transform, multi-wavelet transform, and Laplacian pyramid to reduce a wide variety of noise in images. Also, an image de-noising algorithm based on multi-resolution analysis for noise reduction has been described.

Influence of Various % of Carbon Nanotubes Reinforced AZ91 Magnesium Alloy Nano Composite

Abstract: Carbon Nanotube (CNT)-reinforced AZ91 metal matrix composites (MMC) is an advanced alloy used in designing lightweight vehicles and aircrafts. Powder metallurgy (ball milling), cold pressing and heat treatment prepare the composites used in this paper. It is observed, that CNTs increase mechanical properties. The addition of CNTs improves the yield strength and ultimate tensile strength. The coefficient frictions vary with the amount of CNTs added into the AZ91. The wear properties are found to decreases with an increase in CNT due to its self-lubrication property. However, the marginal increase in CNTs leads to reduce some wear aspects, which are discussed in this paper.

Numerical simulation of incompressible turbulent flows in presence of laminar to turbulent transition

Abstract: Most of the widely used popular mathematical models of turbulence use a judicious combination of intuition, empiricism and the governing equations of instantaneous and mean motion-valid strictly for fully developed turbulence without any laminar region. In reality however, any wall bounded or free shear flow may consist of some laminar flow patches which eventually undergo transition over a finite length to grow into fully turbulent flows. Most of the turbulence models used in commercial CFD codes, are unable to predict the dynamics of turbulent flows with laminar patches. However, accurate prediction of transitional flows is often essential to estimate the pressure losses and/or heat transfer in industrial applications. The present paper implements two different transition models in an existing finite volume URANS-based code RANS3D, developed in house and validated against reliable measurement data for flow past flat plates with different free stream turbulence levels and flow past SD7003 aerofoil at a chord-based Reynolds number of 60,000.

Optical Flow for Detection of Transitions in Video, Face and Facial Expression

Abstract: Optical Flow is the apparent motion of pixels that is generated when there is relative motion between an observer and a scene. Optical flow is used in many areas of research for object detection, motion estimation, navigation and tracking applications. In this paper, we have proposed two novel applications where Optical Flow has been used for Determining Shot Transitions in a video sequence and Human-Face Expression Detection in a video. For Video Shot Detection, local invariant feature points using SIFT (Scale Invariant Feature Transform) corner detectors is calculated and Optical Flow is computed with the detected feature points to determine shot changes in the video. Quality Parameters like Recall, Precision and F-measure is used to determine the quality of the algorithm. Whereas for detecting of human faces, we begin by first performing skin segmentation to obtain probable regions where human face is present. Within the probable region Optical Flow is used to eliminate the background and other objects having human skin color. From the isolated face, Optical Flow is used for identifying expressions.

Characterization of Al-17wt.%Si Using Centrifugal Casting

Abstract: Present work is focused on Horizontal centrifugal casting process, by which a wear resistant material with considerable strength can be designed. A material of heterogeneous microstructure designed in which a high volume fraction of hard particles is dispersed at the inner surface, where better wear properties are needed, and a gradually decreasing lower volume fraction of hard particles at the outer surface. By this, a better strength and ductility will be achieved at the desired surfaces. The present work is focused on the preparation of cylinder liners using centrifugal casting for Al-17wt%Si. These cylinder liners are characterized for Microstructure, Hardness, Tensile strength and Wear.