iosr-JCE   Volume-15 ~ Issue-3

Abstract: In current days, Digital Imaging and Communication in Medicine (DICOM) is widely used for viewing medical images from different modalities, distribution and storage. Image processing can be processed by photographic, optical and electronic means, because digital methods are precise, fast and flexible, image processing using digital computers are the most common method. Image Processing can extract information, modify pictures to improves and change their structure (image editing, composition and image compression etc.). Image compression is the major entities of storage system and communication which is capable of crippling disadvantages of data transmission and image storage and also capable of reducing the data redundancy. Medical images are require to stored for future reference of the patients and their hospital findings hence, the medical image need to undergo the process of compression before storing it. Medical images are much important in the field of medicine, all these Medical image compression is necessary for huge database storage in Medical Centre and medical data transfer for the purpose of diagnosis

Keywords: JPEG, DCT, DWT, SPIHT, DICOM, VQ, Lossless Compression, Wavelet Transform, image Compression, PSNR, RMSE.

[1] Bairagi, V. K. and Sampkal, A. M., (2012-13), "ROI - based DICOM Image Compression for Telemedicine", IEEE, Vol 38, pp.123-131. [2] Dubey, V. G. (2012), "3D Medical Image Compression Using Huffman Encoding Technique", IJSRC, Vol 2, Issue no 9, pp.1-3. [3] Morales, Y. and Diaz, F. V, (2012), "Fingerprint verification by correlation using wavelet compression of preprocessing digital images", IEEE, Vol 2, no 12, pp.1517-1520.

[4] Kumar, V., Kumar, A. and Bhardwaj, A., (2012), "Performance Evaluation od Image Compression Techniques, IEEE, pp.447-450.

[5] Kaur, P. and Singh, S., (2012), "Image Compression Using Multithresholding Technique to Enhance Huffman Technique", Vol 3, Issue 8, pp.1-5

[6] Ramola, E. and Manoharan, J.S., (2011), "An Area Efficient VLSI Realization of Discrete Wavelet Transform for Multiresolution Analysis", IEEE, Vol 2, no 11, pp.377-381.
[7] Dhawan, S., (2011), "A review of image compression and comparison of its algorithms," International Journal of electronics & Communication, Vol 2, Issue 1, pp.22-26.

[8] Talukder, KH. And Harada, K., (2009), "A Scheme of Model Verification of the Concurrent Discrete Wavelet Transform (DWT) for Image Compression", International Journal of Signal Processing, pp.1-10.
[9] S. S. Devi and K. Vidhya, "Development of Medical Image Compression Techniques," Conference on Computational Intelligence and Multimedia Applications, IEEE vol. 3, pp. 97–101, 2007.

[10] Graham, R.N.J., Perriss, R.W. and Scarsbrook, A.F, (2005), "DICOM demystified: A review of digital file formats and their use in radiological practice", ELSEVIEER, pp.1133-1140.

Abstract: Web Mining is specialized field of Data Mining which deals with the methods and techniques of data mining to extract useful patterns from the web data that is available in web server logs/databases. Web content mining is one of the classifications of web mining which extracts information from the web documents containing texts, links, videos and multimedia data available in World Wide Web databases. Further, web structure mining is a kind of web content mining which extracts patterns and meaningful information from the structure of hyperlinks contained in web documents having the same domain. The hyperlinks which are not related to content or the invalid ones are called web structure outliers. In this paper the basic aim is to find out these web structure outliers.

Keywords- Outliers, web outlier mining, web structure mining, Web mining, web structure documents.

[1]. Signed approach for mining web content outliers by G.Poonkuzhali, K. Thaiagrajan, K. Sarukesi and G.V.Uma, World Academy of Science Engineering & Technology, 32, 2009.
[2]. Bing Liu, Kevin chen-chuan chang, Editorial special issue on web content mining, SIGKDD Explorations Volume 6, issue 2.
[3]. Hongqili, Zhuang Wu, Xia.ogang Ji research on the techniques for effectively searching and retrieving information from Internet Symposium on Electronic Commerce & Security, IEEE 2008.
[4]. G.Poonkuzhali, K.Thaigarajan, K.Sarukesi, set theoretical approach for mining web content through outlier detection, International Journal on Research & Industrial Applications, Volume 2, January 2009.
[5]. "Chinese web text outlier mining Based on domain knowledge ", by Xia Huosang , Fan Xhaoyan, Pang Liuyan in 2010 Second WRI Global Congress on Intelligent Systems.

Abstract: The evaluation of physically challenged is always a challenging task as any evaluation of them is compared with that of normal candidates. The case of visually challenged is still more difficult as vision is a nunerouno sensor in the field of study and knowledge enhancement and evaluation of them on par with other candidate is very difficult. The aim of this paper is to present an approach for E-evaluation model for the visually challenged students/candidates for the screening tests conducted by the different examination authorities. The major attempt is made to use the personal computer and avoid the use of a scriber by the candidate so that candidate can take the exam independently. A portion of the PC keyboard is slightly modified in its software functionality to help them in undergoing the test. Also described is the functioning of this model of E-Evaluation and its relative advantages.

Keywords: E-evaluation, PC keyboard, visually challenged candidate

[1]. Census of India-2001.

[2]. Application details for the post of probationary officer in State bank of India.

[3]. News paper clippings:- Times of India-18may 2009, Expess News service 15 may 2009, IANS 8 march 2008.

[4]. Proceedings of International seminar on empowering Visually Impaired through ICT, April 15-16-2009.

[5]. Lorentz J ntschi, Sorana D. Bolboac, Monica M. Marta, and Alexandru Laszlo, ' E-Learning and E- Evaluation: A Case Study', HIS 2008, Krakow, Poland, May 25-27, 2008.

[6]. Daniel Fallman, Oskar Fjellström & Kent Lindbergh, 'AudioIndex: Library Access for the Visually Challenged Using an RFID-based Point and Listen Interface'.