Data mining system contain large amount of private and sensitive data such as healthcare, financial and criminal records. These private and sensitive data can not be share to every one, so privacy protection of data is required in data mining system for avoiding privacy leakage of data. Data perturbation is one of the best methods for privacy preserving. We used data perturbation method for preserving privacy as well as accuracy. In this method individual data value are distorted before data mining application. In this paper we present min max normalization transformation based data perturbation. The privacy parameters are used for measurement of privacy protection and the utility measure shows the performance of data mining technique after data distortion. We performed experiment on real life dataset and the result show that min max normalization transformation based data perturbation method is effective to protect confidential information and also maintain the performance of data mining technique after data distortion.
Fusarium wilt (Fusarium udum Butler) is an important biotic constraint to pigeonpea (Cajanus cajan L.) production worldwide. Breeding for fusarium wilt resistance continues to be an integral part of genetic improvement of pigeonpea. Therefore, the study was aimed at identifying and validating resistant genotypes to fusarium wilt and determining the magnitude of genotype × environment (G × E) interactions through multi-environment and multi-year screening. A total of 976 genotypes including germplasm and breeding lines were screened against wilt using wilt sick plot at Patancheru, India. Ninety two genotypes resistant to wilt were tested for a further two years using wilt sick plot at Patancheru. A Pigeonpea Wilt Nursery (PWN) comprising of 29 genotypes was then established. PWN was evaluated at nine locations representing different agro-climatic zones of India for wilt resistance during two crop seasons 2007/08 and 2008/09. Genotypes (G), environment (E), and G × E interactions were examined by biplot which partitioned the main effect into G, E, and G × E interactions with significant levels (p ≤ 0.001) being obtained for wilt incidence. The genotype contributed 36.51% of resistance variation followed by the environment (29.32%). A GGE biplot integrated with a boxplot and multiple comparison tests enabled us to identify seven stable genotypes (ICPL 20109, ICPL 20096, ICPL 20115, ICPL 20116, ICPL 20102, ICPL 20106, and ICPL 20094) based on their performance across diverse environments. These genotypes have broad based resistance and can be exploited in pigeonpea breeding programs.
A poly(3,4-ethylenedioxythiophene) (PEDOT) modified glassy carbon electrode (GCE) was used to determine uric acid in the presence of ascorbic acid at physiological pH facilitating a peak potential separation of ascorbic acid and uric acid oxidation (ca. 365 mV), which is the largest value reported so far in the literature. Also, an analytical protocol involving differential pulse voltammetry has been developed using a microchip electrode for the determination of uric acid in the concentration range of 1 to 20 mM in presence of excess of ascorbic acid.
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