iosr-JVSP   Volume-8 ~ Issue-1 ~ Jan-Feb 2018

ABSTRACT: In Wireless Sensor Nodes due to the resource constraintsthe fast multipliers are preferred for data processing. In this paper, the RSA processor using Vedic multiplication technique is proposed which is capable of achieving considerable speed and with minimum area utilization. The multiplication of two prime numbers is implemented using Nikhilam and UrdvaTriyagbagam multipliers.The results shows that there is good improvement in delay and device utilization usingUrdvaTriyagbagam method. UrdvaTriyagbagamis utilized in Point addition and Point doubling, which are finite field arithmetic of ECC in both prime and binary field. Multipliers are implemented on RSA and ECC over NIST/SECG GF(p) and GF(2m) curves and estimates the algorithms with respect to performance in speed and memory usage.

 

Keywords: Ellptic Curve Cryptography, FPGA,NikhilamMultiplier, RSA algorithm, Urdva-tiryagbhyam Multiplier, Wireless Sensor Networks

[1]. Antonio de la Piedra, An Braeken, and AbdellahTouhafi. 2012. Sensor Systems Based on FPGAs and Their Applications: A Survey. Sensors (2012), 12, 12235-12264; DOI:10.3390/s 120912235.
[2]. Shaila K, S H Manjula, Thriveni J, Venugopal K R and L MPatnaik,"Resilience Against Node Capture Attack using Asymmetric Matrices in Key Predistribution Scheme in Wireless Sensor Networks ," in International Journal on Computer Science and Engineering, ISSN:0975-3397, vol. 11, no. 3, pp. 31-41, 2011.
[3]. Lata B T, VidyaRao, Sivasankari H, Tejaswi V, Shaila K, Venugopal K R, L M Patnaik, "SEAD: Source Encrypted Authentic Data for WirelessSensor Networks," in International Journal of Engineering Research andDevelopment, e-ISSN: 2278-067X, p-ISSN: 2278-800X, vol. 11, no. 3,pp. 01-16, 2015.
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ABSTRACT: Breast cancer is the most commonly diagnosed life threatening cancer in women worldwide. Breast cancer is the leading cause of cancer death among women. Early detection is of great significance and essential to the treatment of breast cancer. Ultrasonography is one of the most widespread imaging modality used to detect and classify abnormalities of the breast. This paper proposes the use of wavelet transform and its coefficients as texture features for the detection of abnormalities in the breast. Gray level co-occurrence matrix is computed from wavelet coefficients at two levels. Principal component analysis and genetic algorithms are used for feature reduction and selection. Support vector machine (SVM) and Naïve Bayes (NB) are used to differentiate benign and malignant lesions. Their performances are evaluated using diagnostic accuracy, sensitivity, specificity, positive predictive value.......

 

Keywords: Breast lesion, Genetic algorithm, Principal component analysis, Ultrasonography, Wavelet transform.

[1] R. L. Siegel, K. D. Miller, A. Jemal, Cancer statistics, 2017, Cancer J. Clin., 67(1), 2017, 7–30 .

[2] Malvia, S., Bagadi, S. A., Dubey, U. S. and Saxena, S, Epidemiology of Breast Cancer in Indian Women, Asia-Pac J Clin Oncol, 13(4), 2017, 289–295.

[3] C.M.Sehgal, S.P. Weinstein, P.H. Arger, E.F. Conant, A Review of Breast Ultrasound, Journal of Mammary Gland Biology and Neoplasia, 11(2), 2006, 113-123.

[4] H.D.Cheng, J.Shan, W. Ju, y. Guo, L. Zhang, Automated breast cancer detection and classification using ultrasound images: A Survey, Pattern Recognition, 43(1), 2010, 299—317.

[5] D.R. Chen, R.F. Chang, Y.L. Huang, Breast Cancer Diagnosis using Self Organizing Map for Sonography, Ultrasound Med. Biol. 26( 3) , 2000, 405–411.

ABSTRACT: Optical Character Recognition (OCR) is a technology that extracts all the text from the images, .pdf documents or scanned files. So OCR converts normal scanned documents text-searchable so to allow content search on the same. Hindi being the national language of India, with such huge population makes document managing and preservation difficult in government sector. Hence, this paper presents an efficient algorithm Fuzzy KNN for recognition of Hindi script characters from printed documents. Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate due to shirorekha as well as joint characters. This paper proposes an OCR.......

 

Keywords: Optical Character Recognition, Fuzz-KNN, Wavelet Transform.

[1]. Gonzalez R.C and Woods, R.E "Digital Image Processing", Second Edition, Pearson Education, Singapore.
[2]. "Character Recognition System" by Mohammed Cheriet, Nawwwaf Kharma, Chen-Lin Liu, Ching Y.Suen.
[3]. "Design Implementation of OCR to recognize Gujarati script using Template Matching" by Prof. K S Shah, A. Verma.
[4]. "Optical Character Recognition" by Jesse Hansen.
[5]. "Otsu.N, 1979" A threshold selection method from grey level histogram. IEEE. Trans. Sys. Man. And Cyber, 9:62-66.