iosr-JECE   Volume-12 ~ Issue-1 ~ Jan-Feb 2017

Abstract: Data Mining has great scope in the field of medicine. In this article we introduced one new fuzzy approach for prediction of hepatitis disease. Many researchers have proposed the use of K-nearest neighbor (KNN) for diabetes disease prediction. Some have proposed a different approach by using K-means clustering for reprocessing and then using KNN for classification. In our approach Naive Bayes classifier is used to clean the data. Finally, the classification is done using Fuzzy SVM algorithm. Hepatitis diseases data set is used to test our method. We are able to obtain model more precise........

Keywords: Hepatitis disease, Diabetes disease, Liver disorder, KNN algorithm,fuzzy c-means algorithm, fuzzy KNN algorithm, fuzzy SVM algorithm.

[1]. A Critical Study of Classification Algorithms Using Diabetes Diagnosis by PanigrahiSrikanth,2016 IEEE 6th International Conference on Advanced Computing (IACC).
[2]. An Efficient Rule Saba Bashir, UsmanQamar, Farhan Hassan Khan, M.YounusJaved, F2014 12th International Conference on rontiers of Information Technology (FIT),-based Classification of Diabetes Using ID3, C4.5 & CART Ensembles.
[3]. A Particle Swarm Optimization Based Classifier for Liver Disorders Classification Jyun Jie Lin and Pei-Chann Chang, 2010 International Conference on Computational Problem-Solving (ICCP).
[4]. A study on feature extraction and disease stage classification for Glioma pathology images by Kiichi Fukuma, V. B. Surya Prasath,HiroharuKawanaka, Bruce J. Aronow, Haruhiko Takase, 2015 17th International Conference on E-health Networking, Application & Services (HealthCom).
[5]. Citrus Gummosis disease severity classification using participatory sensing, remote sensing and weather data by Jayantrao Mohite, Bhushan Jagyasi, Sonali Kulkarni, Srinivasu Pappula, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

Abstract: In this paper we proposed fast and accurate interpolation and resizing of images using lifting scheme approach. 5/3 lifting scheme is an accurate and computationally inexpensive interpolation technique for image resizing. We compared the bilinear interpolation, Haar lifting scheme and 5/3 lifting scheme in this paper. The lifting scheme algorithm is applied for image interpolation to resize the image. In case of reduction in size, the image components are reduced and the reconstruction will be carried out to the original image........

Keywords: Lifting scheme, 5/3 Lifting transform , DWT , IDWT , Image Resizing , Reconstruction.

[1]. Asamwar, R.S., K.M. Bhurchandi and A.S. Gandhi, 2009. Piecewise lifting scheme based DWT to model human vision interpolation phenomenon. Proceeding of the IAENG International Conference on Signal and Image Engineering, July 1-3, IAENG, London, UK., pp: 822-827.http://www.iaeng.org/publication/WCE2009/WCE 2009_pp822-827.pdf
[2]. Asamwar, R.S., K.M. Bhurchandi and A.S. Gandhi, 2010. Successive Image Interpolation Using Lifting Scheme Approach. Journal of Computer Science 6 (9): 961-970
[3]. Asamwar, R.S., K.M. Bhurchandi and A.S. Gandhi, 2010.Interpolation of images using discrete wavelet transform to simulate image resizing as in human vision. Int. J. Autom. Comput., 7: 9-16. DOI: 10.1007/S116333-010-0009-7
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[5]. Latha, Y.M., B.C. Jinaga and V.S.K. Reddy, 2007. A precise content based image retrieval: Lifting scheme. Int. J. Comput. Sci. Network Secur. 7: 38-45.

Abstract: An novel Ultra Broad-Band Exponential Taper Transmission Line 8- Port Networkis analyzed. The parameters of this developed network is calculated and its frequency responses are computed. Comparison between the simulated and measured parameters are presented.

Keywords: Exponential Taper; 8-Port network; Nonuniform Taper

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