iosr-JCE   Volume-20 ~ Issue-3 ~ May-June 2018

Abstract: This research paper presents a natural language processing based automated system for generating UML diagrams after analyzing the given Use case diagram in the current scenario. This model represent to analyzing natural language processing and extract the relative information from the given UML diagram which are given by the user . User defines the all requirement in simple input language of machine language which are context free language and grammar language. After combining all the information we prepare a relative model in the grammar language. Natural language...........

Keywords– Natural language processing, UML diagram, Use case diagram, Data flow diagram, Software Requirement Specification

[1]. Thomas C. Rindflesch (1999) Natural language processing.
[2]. Ruth Malan and Dana Bredemeyer, (2001) ―Functional Requirements and Use Cases‖, Bredemeyer Consulting, ruth_malan@bredemeyer.com
[3]. L. R. Tang and R. J. Mooney, (2001), ―Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing‖, Proceedings of the 12th European Conference on Machine Learning (ECML- 2001), Freiburg, Germany, pages 466–477.
[4]. Woo, H., & Robinson, W. (2002). ―A light-weight approach to the reuse of use-cases specifications‖, In Proceedings of the 5th annual conference of the Southern Association for Information Systems (pp. 330- 336) Savannah: SAIS
[5]. Imran Sarwar Bajwa, M. Abbas Choudhary, (2006) ―A Rule Based System for Speech Language Context Understanding‖ Journal of Donghua University, (English Edition) 23 (6), pp. 39-42.

Abstract: Rainfall is considered to be an important ingredient in agricultural cultivation. Conventional rain fall predictors use ANN to predict the future rainfall. We introduce a simple machine learning based predictive model using SVM regression. Here the Average Mean Square Error (AMSE) for each kernel is evaluated and the kernel having minimum MSE is selected for prediction. The proposed technique is applied to predict the month wise prediction of rainfall in Khurda District of Orissa. After successful training and validation, the result derive from SVM model is Polynomial kernel is low MSE among all. But after changing the parameter value for each kernel with specified run it is found the Linear kernel produce minimum average MSE 15.04% on test data set while other kernels like Polynomial, RBF, Sigmoid produce 18.81%, 16.15% & 18.32% respectively..

Keywords– Support Vector Machine, Kernel function, RBF kernel, Polynomial Kernel, Accuracy.

[1]. http://en.wikipedia.org/wiki/Artificial_neural_network the details of Artificial Neural Network.
[2]. http://disi.unitn.it/~segata/FaLKM-lib/papers/ FaLKNR_ICCBR09_slides.pdf
[3]. Nello Cristianini and John Shawe-Taylor. An Introduction to Support Vector Machines and Other Kernel-based Learning MethodsCambridge University Press, March 2000.
[4]. Vautard, R., Yiou, P., and Ghil, M., 1992: Singular-spectrum analysis: A toolkit for short, noisy chaotic signals, Physica D, 58, 95-126.
[5]. Lisi, F., Nicolis, O., Sandri, M., 1995. Combining Singular-spectrum analysis and neural networks for time series forecasting. Neural Processing Letter 2 (4), 6-10.

Abstract: Prediction of various diseases can be done by the close examination of Human nail. The proposed system – Nail Image Processing System using KNN (NIPS-K) helps us to create a model which can perform the analysis of human nail and thereby help us in predicting various diseases. The input to the proposed system is the Human Palm Image. The nail portion is segmented and nail color, shape and texture features are extracted and combined to form 13 features and then analysis of nail is done which will then be used for the diagnosis of various diseases. This proposed system will surely help the medical practitioners in the early diagnosis of diseases.

Keywords– Nail Analysis, Feature analysis, disease prediction, Supervised Learning, KNN classifier

[1]. Fawcett RS, Linford S, Stulberg DL. Nail Abnormalities: Clues to Systemic Disease. Am Fam Physician March 15, 2004; 69(6):p 1417-24
[2]. Motswaledi MH, Mayayise MC. Nail changes in systemic diseases, SA Fam Pract 2010; 52 (5): p 409-413.
[3]. http://www.aocd.org/?page=GreenNailSyndrome.
[4]. http://www.wikipedia.org/wiki/
[5]. http://www.healthline.com/health/dermatoses.

Abstract: Dimensionality Reduction is the transformation of high-dimensional data into a meaningful representation of reduced dimensionality. Dimensionality reduction techniques offer solutions that both significantly improve the computation time, and yield reasonably accurate clustering results in high dimensional data. The Reduction techniques are struggled to project the features for variant of discriminant information. The LDA is the best supervised reduction method for linear discriminate information based on the mean values. LDA required more features to project the classification errors. The proposed semi supervised reduction techniques the classification stage...........

[1]. MM Steffi, JJR Jose -Comparative Analysis of Facial Recognition involving Feature Extraction Techniques ,2018.
[2]. K Wang, D Zhang, Y Li, R Zhang, "Cost-Effective Active Learning for Deep Image Classification," IEEETransactions on Circuits...Volume: 27 Issue: 12 Dec-2017.
[3]. L Shao, Z Cai, L Liu, K Lu "Performance evaluation of deep feature learning for RGB-D image/video classification," Volumes 385–386, April 2017- Elsevier, Pages 266-283 .
[4]. L. Liu, L. Shao, X. Zhen, and X. Li, "Learning discriminative key poses for action recognition." IEEE Transactions on Cybernetics, 2013.
[5]. Q Ding, J Han, X Zhao, Y Chen - IEEE Transactions on …, "Missing-data classification with the extended full-dimensional Gaussian mixture model: Applications to EMG-based motion recognition," - ieeexplore.ieee.org. Volume: 62 Issue: 8. 2015.

Abstract: This research paper attempts to identify the climate changes based on rainfall data and to cross validate the changes of climate using various machine learning method. In recent and past years, climate changes due to various parameters like, pollution, real estate business, and shortages of lake and pond waters. The climate of Tamilnadu is generally tropical and features of fairly hot temperature over the year except monsoon seasons. Tamilnadu seasons and climate are classified into three categories viz, summer, winter and monsoon seasons. This research paper aims at analyzing rainfall model evaluation and cross validation to evaluate the district wise data of Tamilnadu and make possible the result in various seasons to understand the climate changes. The secondary...........

Keywords: Rainfall, Machine Learning Methods, Logistic Regression, Random Forest Method, Support Vector Machine, Euclidean distance and Silhouette plot

[1]. Olaiya, Folorunsho, and Adesesan Barnabas Adeyemo. "Application of data mining techniques in weather prediction and climate change studies."International Journal of Information Engineering and Electronic Business (IJIEEB) 4.1 (2012): 51.
[2]. Sharma RH, Shakya NM. 2006. Hydrological changes and its impact on water resources of Bagmati watershed, Nepal. Journal of Hydrology 327 (3-4): 315-322.
[3]. Nikhil Sethi, Dr.Kanwal Garg "Exploiting Data Mining Technique for Rainfall prediction" , International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 3982-3984.
[4]. Pasanen, A-L., et al. "Laboratory studies on the relationship between fungal growth and atmospheric temperature and humidity." Environment International17.4 (1991): 225-228. Swinbank, W. CQJR. "Long‐wave radiation from clear skies." Quarterly Journal of the Royal Meteorological Society 89.381 (1963): 339-348.
[5]. Manimannan G. and Lakshmi Priya R (2001), Rainfall Fluctuation and Classification over Tamilnadu Region: Using Data Mining Techniques, IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728, p-ISSN: 2319-765X. Volume 10, Issue 5 Ver. IV (Sep-Oct. 2014), PP 05-12.

Abstract: The general public's demand of Bangladesh for safe health is rising promptly with the improvement of the living standard. However, the allocation of limited and unbalanced medical resources is deteriorating the assurance of safe health of the people. Therefore, the new hospital construction with rational allocation of resources is imminent and significant. The site selection for establishing a hospital is one of the crucial policy-related decisions taken by planners and policy makers. The process of hospital site selection is inherently complicated because of this involves many factors to be measured and evaluated. These factors are expressed both in objective and subjective ways where as a hierarchical relationship exists among the factors. In addition, it is difficult to measure qualitative factors in.........

Keywords: Multiple criteria decision analysis (MCDA), uncertainty, evidential reasoning (ER) and Knowledge-based Decision Support System (KDSS)

[1]. M Sonmez, G. Graham and J. B. Yang and G D Holt, "Applying evidential reasoning to pre-qualifying construction contractors", Journal of Management in Engineering, Vol.18, No.3, pp.111-119, 2002.
[2]. J. B. Yang, "Rule and utility based evidential reasoning approach for multiple attribute decision analysis under uncertainty", European Journal of Operational Research, Vol. 131, No.1, pp.31-61, 2001.
[3]. Y. M. Wang, J. B. Yang and D. L. Xu, "Environmental Impact Assessment Using the Evidential Reasoning Approach", European Journal of Operational Research, Vol.174, No.3, pp.1885-1913, 2006.
[4]. Lisa M. (2008). The Sage encyclopedia of qualitative research methods. Los Angeles, Calif.: Sage Publications. ISBN 1-4129-4163-6.
[5]. http://www.pearson.ch/1449/9780273722595/An-Introduction-to-Geographical.aspx.

Abstract: In a business organization, management has to make decisions on how to allocate their resources to achieve its organization's goal. Each organization wants to achieve some objective with constrained resources. To be able to find the best uses of an organization's resources using spreadsheet model, a mathematical technique called Linear Programming can be used. Linear Programming (LP) is a mathematical optimization technique. By optimization technique, it refers to a method which attempts to maximize or minimize some objective, for example, maximize profits or minimize costs. The adjective linear is used to describe a relationship between two or more variables.......

Keywords: Linear Programming (LP), Spreadsheet Methodology and Optimization.

[1]. Andersen, D.R., D.J. Sweeney, & T.A. Williams, An Introduction to Management Science: Quantitative Approaches to Decision
Making
[2]. Andersen, D. R., Dennis J. Sweeny, and Thomas A. Williams. 2001. QuantitativeMethods for Business.Eighth edition. Cincinnati,
Ohio: South-Western College Publishing.
[3]. Anderson, Michael Q. 1982. Quantitative Management Decision Making, Belmont,California: Brooks/ Cole Publishing Co.,
[4]. Dunn, Robert A. and K. D. Ramsing. 1981. Management Science: A Practical Approach to Decision Making. New York, New
York: MacMillan Publishing Co.
[5]. Krajewski, Lee C. and H. E. Thompson. 1981. Management Science: Quantitative Methods in Context, New York: John Wiley &
Sons..

Abstract: This research paper attempts to identify the climate changes based on rainfall data and to cross validate the changes of climate using various machine learning method. In recent and past years, climate changes due to various parameters like, pollution, real estate business, and shortages of lake and pond waters. The climate of Tamilnadu is generally tropical and features of fairly hot temperature over the year except monsoon seasons. Tamilnadu seasons and climate are classified into three categories viz, summer, winter and monsoon seasons. This research paper aims at analyzing rainfall model evaluation and cross validation to evaluate the district wise data of Tamilnadu and make possible the result in various seasons to understand the climate changes. The secondary database was collected from Indian Meteorological department during the year 2008 to 2012 and it is monthly rainfall........

Keywords: Rainfall, Machine Learning Methods, Logistic Regression, Random Forest Method, Support Vector Machine, Euclidean distance and Silhouette plot

[1]. Olaiya, Folorunsho, and Adesesan Barnabas Adeyemo. "Application of data mining techniques in weather prediction and climate change studies."International Journal of Information Engineering and Electronic Business (IJIEEB) 4.1 (2012): 51.
[2]. Sharma RH, Shakya NM. 2006. Hydrological changes and its impact on water resources of Bagmati watershed, Nepal. Journal of Hydrology 327 (3-4): 315-322.
[3]. Nikhil Sethi, Dr.Kanwal Garg "Exploiting Data Mining Technique for Rainfall prediction" , International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 3982-3984.
[4]. Pasanen, A-L., et al. "Laboratory studies on the relationship between fungal growth and atmospheric temperature and humidity." Environment International17.4 (1991): 225-228. Swinbank, W. CQJR. "Long‐wave radiation from clear skies." Quarterly Journal of the Royal Meteorological Society 89.381 (1963): 339-348.
[5]. Manimannan G. and Lakshmi Priya R (2001), Rainfall Fluctuation and Classification over Tamilnadu Region: Using Data Mining Techniques, IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728, p-ISSN: 2319-765X. Volume 10, Issue 5 Ver. IV (Sep-Oct. 2014), PP 05-12..

Abstract: Conductive composites in which they associate the electrical properties of metallic particles with the mechanical properties and processability of conventional polymers has been intensively investigated for many years precisely because of the versatility and potential of technological applications that they can present. In this work composites were easily obtained by physically mixing the PVDF thermoplastic and the nickel particles and homogeneous films were obtained by hot pressing at a temperature of 180 ° C and 30 MPa. The electrical conductivity of PVDF / Ni of the composites studied as a function of the content of Nickel particles presented percolation threshold between 15 and 20% with a jump of 7 and 5 orders of magnitude, respectively..

Keywords: PVDF, Nickel, Physical Mixture Electrical Properties

[1]. Mazumdar, S. K. Composites manufacturing: materials, product, and process. New York: CRC Press LLC, 2002.
[2]. Harper, C. A. Modern plastics handbook. New York: McGraw-Hill Professional, 2000.
[3]. Strümpler, R.; Glatz-reichenbach, J. Conducting polymer composites. Journal of electroceramics, New York, v. 3(4), 1999. p. 329-346.
[4]. Martins, N. Physical mixtures of polypropylene with conductive additives: obtaining, characterization and application for electromagnetic shielding. Universidade Federal, Florianópolis-SC, 2012.
[5]. Móczó, J.; Pukánszky, B. Polymer micro and nanocomposites: structure, interactions, properties. Journal of Industrial and Engineering Chemistry, Washington, n. 14, 2008, p. 535-563.

Abstract:The purpose of this article is to demonstrate the Birch and Swinnerton-Dyer Conjecture : If L is the function associated to an elliptic curve, then the order of the zero of L at s = 1 is exactly the order of the curve. In particular, the curve admits an infinity of rational points if and only if L(1)= 0 . Résumé : Le but de cet article est de démontrer la Conjecture de Birch et Swinnerton-Dyer : Si L est la fonction associée à une courbe elliptique, alors l'ordre d'annulation de la fonction L en s=1 est exactement l'ordre de la courbe. En particulier, la courbe admet une infinité de points rationnels si et seulement si L(1)= 0.

Keywords: Birch, Swinnerton-Dyer, L-function, courbe elliptique, zêta de Riemann,

[1] B. Birch and H. Swinnerton-Dyer, Notes on elliptic curves II, Journ. reine u. angewandte Math. 218 (1965), 79–108.
[2] C. Breuil, B. Conrad, F. Diamond, and R. Taylor, On the modularity of elliptic curves over Q: wild 3-adic exercises, J. Amer. Math. S
oc. 14 (2001), 843–939.
[3] J. Coates and A. Wiles, On the conjecture of Birch and Swinnerton-Dyer, Invent. Math. 39 (1977), 223–251.
[4] L. Mordell, On the rational solutions of the indeterminate equations of the third and fourth degrees, Proc. Cambridge Phil. Soc. 21
(1922-23), 179–192.
[5] M. Sghiar (Décembre 2015) , Des applications génératrices des nombres premiers et cinq preuves de l'hypothèse de riemann,
Pioneer Journal of Algebra, Number Theory and its Applications , Volume 10, Numbers 1-2, 2015, Pages 1-31..

Abstract: CRT method is an example of embedding method for fragile watermarking which closely related to document image protection. This study compares the use of watermarking schemes using the DWT-CRT and TLDCT-CRT methods. The DWT method is capable of providing good compression results to support the quality of watermark extraction, while the CRT method can produce a low level of distortion. This scheme is capable of producing watermark results with PSNR range of 45 dB and in the extraction process yields an average of 25 dB PSNR. While the TLDCT-CRT scheme has PSNR in the range of 45 dB and an average PSNR of 24 dB in the extraction process.

Keywords: Digital Watermarking, Discrete Wavelet Transform, Chinese Remainder Theorem

[1]. Chen, P.Y. & Chang, J.Y. 2013. An Adaptive Quantization Scheme for 2-D DWT Coefficients. International Journal of Applied Science and Engineering. 1: 85-100.
[2]. Haribabu, M., Bindu, C.H. & Swamy, K.V. 2016. A Secure & Invisible Image Watermarking Scheme Based on Wavelet Transform in HSI Color Space. 6th International Conference on Advances in Computing &Communications. ICACC. Cochin, 6-8 September 2016.
[3]. Katharotiya, A., Patel, S. & Goyani, M. 2011. Comparative Analysis between DCT & DWT Techniques of Image Compression. Journal of Information Engineering and Applications. Vol 1, No.2.
[4]. Nguyen, T.S., Chang, C.C. & Yang, X.Q. 2016. A Reversible Image Authentication Scheme Based on Fragile Watermarking in DWT Domain. International Journal of Electronics and Communications. 70: 1055-1061.
[5]. Nugraha, D.A., Rahmadwati & Muslim, M.A. 2017. Skema Digital Watermarking Citra dengan Metode TLDCT dan Chinese Remainder Theorem. Jurnal Nasional Teknik Elektro dan Teknologi Informasi. Vol 6, No 2..