Sukumaran S.,Erode Arts and Science College
2013 4th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2013 | Year: 2013
Data mining is a process of inferring knowledge from such huge data. Data Mining has three major components Clustering or Classification, Association Rules and Sequence Analysis. By simple definition, in classification/clustering analyze a set of data and generate a set of grouping rules which can be used to classify future data. Data mining is the process is to extract information from a data set and transform it into an understandable structure. It is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns. Data mining involves six common classes of tasks. Anomaly detection, Association rule learning, Clustering, Classification, Regression, Summarization. Classification is a major technique in data mining and widely used in various fields. Classification is a data mining (machine learning) technique used to predict group membership for data instances. In this paper, we present the basic classification techniques. Several major kinds of classification method including decision tree induction, Bayesian networks, k-nearest neighbor classifier, the goal of this study is to provide a comprehensive review of different classification techniques in data mining © 2013 IEEE.
Sathappan S.,Erode Arts and Science College
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015 | Year: 2015
In today's life, images play a significant role in many application fields for numerous purposes. Image processing has to face the huge challenges because of images created in digital format which leads to huge data volumes. In recent days, to meet the diverse type of real time applications, the Joint Photographic Experts Group (JPEG) compression techniques are used, which are used to minimize the expenditure of possessions such as hard disk space and transmission bandwidth. Preceding paper utilized new lossless color image compression algorithm based on the hierarchical prediction and context-adaptive arithmetic coding. In this paper the specified image is transformed into YCuCv color space by RCT (Reversible Color Transform) coordination by using lossless compression technique and image compression is acquired. Preserving the sharpness of the original image is a prominent factor in image compression. New schemes are required in preserving the sharpness and reduction in bitrates in the further progress. Proposed paper recommended the approach which reduces the bitrates more than 1. The proposed scheme is named as Modified Hierarchical Prediction which removes the enormous prediction error rate near edges and preserves the sharpness of images. This paper considers the vertical, horizontal and diagonal (left up, left down and right up, right down) predictors to predict pixels. Diagonal predictor enhances the perdition accuracy of pixels in Hierarchical Prediction. The experimental result shows that the proposed Modified Hierarchical Prediction based scheme preserve the sharpness of the image. © 2015 IEEE.
Subramanian M.,Kongu Arts and Science College |
Sathappan S.,Erode Arts and Science College
International Arab Journal of Information Technology | Year: 2015
In general the users are in need to retrieve images from a collection of database images from variety of domains. In earlier phase this need was satisfied by retrieving the relevant images from different database simply. Where there is a bottleneck that the images retrieved was not relevant much to the user query because the images were not retrieved based on content where another drawback is that the manual searching time is increased. To avoid this Content-Based Image Retrieval (CBIR) is developed it is a technique for retrieving images on the basis of automatically -derived features such as colour, texture and shape of images. To provide a best result in proposed work we are implementing high level filtering where we are using the anisotropic morphological filters, hierarchical Kaman filter and particle filter proceeding with feature extraction method based on color and gray level feature and after this the results were normalized. © 2015, Zarka Private Univ. All rights reserved.
Kumaresan M.,P.A. College |
Palanisamy P.N.,Kongu Engineering College |
Kumar P.E.,Erode Arts and Science College
Indian Journal of Fibre and Textile Research | Year: 2012
The colour fastness properties of the colourant extracted from the flower of Spathodea campanulata on cotton have been studied using different combination (1:3,1:1 and 3:1) of various mordants, such as myrobolan: Nickel sulphate, myrobolan: Aluminium sulphate, myrobolan: Potassium dichromate, myrobolan: Ferrous sulphate and myrobolan: Stannous chloride. The wash, rub, light and perspiration fastness of the dyed samples have been evaluated. It is found that Spathadia campanulata dye can be successfully used for the dyeing of cotton to obtain a wide range of colours by using various combinations of mordants. With regards to colour fastness, test samples exhibit excellent fastness to washing, and rubbing, except for pre-mordanting using myrobolan: Potassium dichromate combination; and good to excellent fastness to perspiration in both acidic and alkaline media.
Raja T.,Mahendra Engg College |
Karthikeyan S.,Erode Arts and Science College |
Senthilnathan B.,Coimbatore Institute of Technology
Journal of Applied Fluid Mechanics | Year: 2013
Convective flow through porous media is a branch of research undergoing rapid growth in fluid mechanics and heat transfer. This is quite natural because of its important applications in environmental, geophysical and energy related engineering problems. Prominent applications are the utilization of geothermal energy, the control of pollutant spread in ground water, the design of nuclear reactors, solar power collectors and the heat transfer associated with the deep storage of nuclear waste. The study of heat generation in moving fluids is important in problems dealing with chemical reactions and those concerned with dissociating fluids. Heat generation effects may alter the temperature distribution and this in turn can affect the particle deposition rate in nuclear reactors, electronic chips and semi conductor wafers. Although exact modeling of internal heat generation is quite difficult, some simple mathematical models can be used to express its general behaviour for most physical situations. The objective of this work is to investigate the effects of internal heat generation on an unsteady two-dimensional magnetohydrodynamic free convection flow of a viscous, incompressible fluid free convection flow past a semi-infinite vertical porous plate embedded in a porous medium, in the presence of variable suction. The equations of continuity, linear momentum and energy, which govern the flow field, are transformed to a system of ordinary differential equations by perturbation technique. The resulting equations are solved analytically to obtain the solutions for the velocity and temperature fields. The behavior of the velocity, temperature, skin-friction and Nusselt number have been discussed for variations in the physical parameters.