Due to its stabilized and distinctive properties, the palmprint is considered a physiological biometric. Recently, palm print recognition has become one of the foremost desired identification methods. This manuscript presents a new recognition palm print scheme based on a harmony search algorithm by computing the Gaussian distribution. The first step in this scheme is preprocessing, which comprises the segmentation, according to the characteristics of the geometric shape of palmprint, the region of interest (ROI) of palmprint was cut off. After the processing of the ROI image is taken as input related to the harmony search algorithm for extracting the features of the palmprint images through using many parameters for the harmony search algorithm, Finally, Gaussian distribution has been used for computing distance between features for region palm print images, in order to recognize the palm print images for persons by training and testing a set of images, The scheme which has been proposed using palmprint databases, was provided by College of Engineering Pune (COEP), the Hong Kong Polytechnic University (HKPU), Experimental results have shown the effectiveness of the suggested recognition system for palm print with regards to the rate of recognition that reached approximately 92.60%.
Cloud <span>computing provides advantages, like flexibly of space, security, cost optimization, accessibility from any remote location. Because of this factor cloud computing is emerging as in primary data storage for individuals as well as organisations. At the same time, privacy preservation is an also a significant aspect of cloud computing. In regrades to privacy preservation, association rule mining was proposed by previous researches to protect the privacy of users. However, the algorithm involves creation of fake transaction and this algorithm also fails to maintain the privacy of data frequency. In this research an apriori algorithm is proposed to enhance the privacy of encrypted data. The proposed algorithm is integrated with elagmal cryptography and it does not require fake transactions. In this way, the proposed algorithm improves the data protection as well as query privacy and it hides data frequency. Result analysis shows that the proposed algorithm improves the privacy as compared to previously proposed association rule mining and the algorithm also shows 3% to 5% improvement in performance when compared to other existing algorithms. This performance analysis with varying number of the data and fake transactions shows that the proposed algorithm doesn’t require fake transactions, like data privacy association rule mining.</span>
Essentially use iris technique to human identification and recognition. Due enormous growth through the recent years for iris recognition techniques numerous research has emerged in the areas like; image compression, segmentation, quality assessment, Image Acquisition (IA), restoration, feature extraction (FE), normalization, noise reduction iris code matching (NRCM), evaluation, searching large database, applications, performance under changing multibiometrics and condition. Where many techniques were suggested to iris recognition (IR) using neural network because their efficient algorithm and also gives good result. In this research paper, we provide reviews a background for many techniques proposed to recognition iris image in various domains and also procedure a comparison between these techniques.
Cloud computing complexity is growing rapidly with the advancements that it is witnessing. It has created a requirement to simplify the process of configuring cloud and re-configuring it when required, it also involves tasks like auto scaling of infrastructure, elastic computing and maintaining the health of the servers. The proposed method introduces a smart cloud management using knowledge base, which models the resources of cloud; it handles service level agreement and its evaluations. The proposed knowledge base supports representational state transfer (REST/RESTful) services to store and manipulate different cloud aspects like type of application, business configuration, and metrics value and its type; it also implements the strategy for efficient resource management for smart clouds. The proposed architecture consists of smart cloud engine (which provides autonomous services, which help to exploit cloud resources for service optimization and to perform service automation), knowledge base (KB) (provide a cloud ontology which will help in the management of resources and provides intelligence to the smart cloud), server and cloud enrolment, designated monitoring tool and moderator. The resulted module is easy to integrate with any of the existing cloud management tool or orchestrator. As It is developed using REST protocol and extensible markup language (XML) language it is also easy to integrate with existing monitoring tool or application programming interface (APIs).
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