A secured cloud storage auditing with empirical outsourcing of key updates

Vijayakumar, K.; Suchitra, S.; Shri, Prince

doi:10.1504/ijris.2019.10021320

Cited by 12 publications

(11 citation statements)

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“…An efficient Sort-based Incomplete Data Skyline (SIDS) algorithm for evaluating the skyline query over incomplete data discussed in [7]. [12] This algorithm is an improvement of an existing bucket algorithm. Sorting based Cluster Skyline Algorithm(SCSA) for retrieving skyline from incomplete data proposed in [9][10].…”

Section: Properties Of Skyline Querymentioning

confidence: 99%

Comparative Analysis of Skyline Query Execution using Imputation Techniques on Partially Complete Data

Kanmani¹,

Kirubakaran²,

Rajsingh³

2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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In this era, the Database community depends on preference queries to satisfy user needs according to their given preferences. Skyline query is one of the preference-based queries. The skyline proceeds with contradictory preferences given by the user. Skyline query derived from the maximum vector problem which deals with Pareto dominance. Skyline query always leads to promising results in the complete data environment. Due to the dynamic data setup, this leads to unknown values or noisy data in the database. This type of data leads partially complete data environment and this affects the performance of skyline queries. This paper gives an analysis of complete and partially complete data using skyline queries with imputation techniques. Two different imputation techniques are used namely Random forest and Amelia to execute the Skyline query on partially complete data. The experimental study gives the solemnity of partially complete data using the skyline query and its influence on the result of the query.

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Section: Properties Of Skyline Querymentioning

confidence: 99%

Comparative Analysis of Skyline Query Execution using Imputation Techniques on Partially Complete Data

Kanmani¹,

Kirubakaran²,

Rajsingh³

2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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“…The EWT output is composed on filtering with scaling function and wavelets. The careful selection of wavelet [7][8] [9] and decomposed level in order to obtained in good time frequency resolution. A similar approach is recorded with color image processing by authors in [6] [10].…”

Section: Empirical Wavelet Transformmentioning

confidence: 99%

Diagnosing the level of Glaucoma from Fundus Image Using Empirical Wavelet Transform

Swamy¹,

Ahmed²,

Thanuja³

et al. 2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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An increased pressure of fluid in optic nerve can subsequently leads to permanent blindness are known as Glaucoma. The normal pressure of eye is 15mmHg or even lower, once it is higher than 30mmHg then there is risk in vision loss. There are many existing technique that require experienced clinicians and cost effective. These systems use higher order spectra and discrete wavelet transform features for extracting the values and fed to classifier for normalization and ranking the feature. In this paper presenting a new methodology for diagnosis of glaucoma based on EWT. Empirical wavelet transform is applied on image to format the sub band which is also called as decomposed image. These features are sustained into neural network system that produces ne value from n iteration and classify images into mild, intermediate and heavily affected eye using Fundus images.

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“…More than 50 million smart speakers have been installed in American households [2]. Sensors senses the data from the home apparatus such as AC, DC Light and water tank sensor data [3] [8].Sensors accurately sense the real-time data disaster management data such as fire detection alarm with high accuracy [4] [7]. Cloud computing provide a variety of computing services in various levels and provide minimal interaction [5][6] to manage smart home data.…”

Section: Significance Of Home Automation In the Modern Eramentioning

confidence: 99%

Scalable Cloud Platform for Smart Home Devices Automation

Arun¹

2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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Empathize the user needs for home device automation is a creative design thinking to facilate man kind. The prevalence of home automation has been increased due to inter-linking and shadowing of human activities by controled machine activities. Use of machines and its control by using information technologies to improve automation is a next step beyond mechanization. Control home machinaries , electronic devices ,fire alarm systems, water tank management systems, and security surveillance camera can be automate to reduce manual labour, elecrticty and ease of accesing from remote systems to make human living style as easy and secure.This paper, cloud based support for home devices automation bolster the elders, pet animal care takers and disabled persons activity by remote automation though Smartphone and tablet connectivity. Focus of this project is to develop a system which makes integration of the different home automation components seamlessly irrespective of manufacturer or where the components are coming from and accessing by remote by storing in cloud.

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A secured cloud storage auditing with empirical outsourcing of key updates

Cited by 12 publications

References 0 publications

Comparative Analysis of Skyline Query Execution using Imputation Techniques on Partially Complete Data

Comparative Analysis of Skyline Query Execution using Imputation Techniques on Partially Complete Data

Diagnosing the level of Glaucoma from Fundus Image Using Empirical Wavelet Transform

Scalable Cloud Platform for Smart Home Devices Automation

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