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• A Comparative Analysis of Working Capital Management Among Top 5 NSE Listed Indian Steel Companies
  R. Sivaranjani ; Mrs. B. Kishori
  MBA
  Year: 2016, Volume:2, Issue : 11
  Pages: 821 - 828

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  A proper management of working capital is essential to a company’s fundamental financial health and operational success as a business. A hallmark of good business management is the ability to utilize working capital management to maintain a solid balance between growth, profitability and liquidity. In this study investigate the relationship between the firm’s working capital operating cycle and profitability of the firm. This study is done on five steel company namely, Steel Authority of India Ltd., Tata Steel Ltd., JSW Steel Ltd., Steel authority of India Ltd. & Jindal Steel & Power Ltd. The study was done to know the comparative position of steel companies in working capital management and applying various analyses such as correlation, regression, chi- square by taking data from year 2011 to 2015.The study reveals that operating cycle are increasing the profitability of the company. Operating cycle and profitability are having the linear relationship between both, JSW, placing the first place to handling operating cycle. TATA is also having good operating cycle; JINDAL are gives the importance to maintain the operating cycle and getting more profit, SAIL are maintain the best profitability for handling effective operating cycle, SEIL are given importance to increasing profitability for minimize the cycle period.

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  IJIRST R. Sivaranjani and Mrs. B. Kishori. "A Comparative Analysis of Working Capital Management Among Top 5 NSE Listed Indian Steel Companies" International Journal for Innovative Research in Science & Technology Volume 2 Issue 11 2016 Page 821-828 MLA R. Sivaranjani and Mrs. B. Kishori. "A Comparative Analysis of Working Capital Management Among Top 5 NSE Listed Indian Steel Companies." International Journal for Innovative Research in Science & Technology 2.11 (2016) : 821-828. APA R. Sivaranjani and Mrs. B. Kishori. (2016). A Comparative Analysis of Working Capital Management Among Top 5 NSE Listed Indian Steel Companies. International Journal for Innovative Research in Science & Technology, 2(11), 821-828. Chicago R. Sivaranjani and Mrs. B. Kishori. "A Comparative Analysis of Working Capital Management Among Top 5 NSE Listed Indian Steel Companies." International Journal for Innovative Research in Science & Technology 2, no. 11 (2016) : 821-828.

  

• Privacy Preservation of Data in Data mining using K-anonymity and Randomization Method
  Mr. Kartik Patel ; Mr. Trushar Patel ; Mr. Dharmesh Patel
  Computer Science and Engineering
  Year: 2016, Volume:2, Issue : 11
  Pages: 829 - 836

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  Increasing the business prospective the sharing of data is the most important. But when Sensitive data are share between two parties at that time the privacy of data is the major problem. In day to day life the Sharing, transferring, mining and publishing data are the major factor in privacy preservation. When sensitive data are share between two parties then the privacy of data is the major problem. The main aim of the privacy preservation is protecting the sensitive information in data while extracting knowledge from large amount of data. There are many techniques are use in privacy preservation like k-anonymity, l-diversity, t-closeness, blocking based method and cryptography techniques. Privacy preserving techniques available but still they have shortcomings. Like Anonymity technique gives privacy protection and usability of data but it suffers from homogeneity and background attack. Blocking method suffers from information loss and random perturbation technique does not provide usability of data. Cryptography technique gives privacy protection but does not provide usability of data and it requires more computational overhead. So in this work we use the k-anonymity method to prevent our data and we can get better accuracy as compare to previously used methods.

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  IJIRST Mr. Kartik Patel , Mr. Trushar Patel and Mr. Dharmesh Patel. "Privacy Preservation of Data in Data mining using K-anonymity and Randomization Method" International Journal for Innovative Research in Science & Technology Volume 2 Issue 11 2016 Page 829-836 MLA Mr. Kartik Patel , Mr. Trushar Patel and Mr. Dharmesh Patel. "Privacy Preservation of Data in Data mining using K-anonymity and Randomization Method." International Journal for Innovative Research in Science & Technology 2.11 (2016) : 829-836. APA Mr. Kartik Patel , Mr. Trushar Patel and Mr. Dharmesh Patel. (2016). Privacy Preservation of Data in Data mining using K-anonymity and Randomization Method. International Journal for Innovative Research in Science & Technology, 2(11), 829-836. Chicago Mr. Kartik Patel , Mr. Trushar Patel and Mr. Dharmesh Patel. "Privacy Preservation of Data in Data mining using K-anonymity and Randomization Method." International Journal for Innovative Research in Science & Technology 2, no. 11 (2016) : 829-836.

  

• Estimation of Breast Density and Feature Extraction of Mammographic Images
  Anusree Mohan ; Dr. Devesh. D. Nawgaje
  Electronics and Telecommunication
  Year: 2016, Volume:2, Issue : 11
  Pages: 837 - 841

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  Breast cancer is one of the leading causes of fatality in women. Mammogram is the effectual modality for early detection of breast cancer. Increased mammographic breast density is a moderate independent risk factor for breast cancer, Radiologists have estimated breast density using four broad categories (BI-RADS) swearing on visual assessment of mammograms. But if we can measure breast density quantitatively, we can provide most accurate and a reliable density measures. Breast density and Lesion feature extraction plays important role in determining cancer risk. Breast contour helps to find the position of the nipple, as its position is important for registration of left and right breasts, to detect bilateral asymmetry. The shape of the mass border helps radiologists to judge whether mass is malignant or benign. Novel algorithms are designed for 1) Breast Density Estimation 4) Extraction of features[15] from the mass. These features help to further investigate in a clinical evaluation for classification to detect the cancer in early stages.

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  IJIRST Anusree Mohan and Dr. Devesh. D. Nawgaje. "Estimation of Breast Density and Feature Extraction of Mammographic Images" International Journal for Innovative Research in Science & Technology Volume 2 Issue 11 2016 Page 837-841 MLA Anusree Mohan and Dr. Devesh. D. Nawgaje. "Estimation of Breast Density and Feature Extraction of Mammographic Images." International Journal for Innovative Research in Science & Technology 2.11 (2016) : 837-841. APA Anusree Mohan and Dr. Devesh. D. Nawgaje. (2016). Estimation of Breast Density and Feature Extraction of Mammographic Images. International Journal for Innovative Research in Science & Technology, 2(11), 837-841. Chicago Anusree Mohan and Dr. Devesh. D. Nawgaje. "Estimation of Breast Density and Feature Extraction of Mammographic Images." International Journal for Innovative Research in Science & Technology 2, no. 11 (2016) : 837-841.

  

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