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Institution

Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.


Papers
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Journal ArticleDOI
TL;DR: The present study investigates the effect of independent variables such as extraction temperature, time, and solid-liquid ratio over the extraction yield of polysaccharide from Gossypium arboreum L. seeds and develops a second order polynomial mathematical model.

20 citations

Journal ArticleDOI
TL;DR: The proposed TP Scheduling (Transpotation Problem based) responded for various tasks assigned by clients in poisson arrival pattern and achieved the improved reliability in dynamic decentralized cloud environment.
Abstract: Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a scheduling algorithm that can improve the availability and reliability in cloud environment. Approach: We propose a new algorithm using modified linear programming problem transportation based task scheduling and resource allocation for decentralized dynamic cloud computing. The Main objective is to improve the reliability of cloud computing environment by considering the resources available and it’s working status of each Cluster periodically and maximizes the profit for the cloud providers by minimizing the total cost for scheduling, allocation and execution cost and minimizing total turn-around, total waiting time and total execution time. Our proposed algorithm also utilizes task historical values such as past success rate, failure rate of task in each Cluster and previous execution time and total cost for various Clusters for each task from Task Info Container (TFC) for tasks scheduling resource allocation for near future. Results: Our approach TP Scheduling (Transpotation Problem based) responded for various tasks assigned by clients in poisson arrival pattern and achieved the improved reliability in dynamic decentralized cloud environment. Conclusion: With our proposed TP Scheduling algorithn we improve the Reliability of the decentralized dynamic cloud computing.

20 citations

Journal ArticleDOI
TL;DR: In this article, the authors present the design of the test station, which is accessible for the testing of electric bicycles and can be used for either a low-power Brushless Dc traction vehicle or a high-powered motor scooter.
Abstract: This article presents the design of the test station, which is accessible for the testing of electric bicycles. In this process, a low-power Brushless Dc traction vehicle or a high-powered motor sc...

20 citations

Journal ArticleDOI
TL;DR: In this article, a modified iterative grouping median filter (IMF) was proposed to remove the noise in the MRI image and a maximum likelihood estimation-based kernel principal component analysis (KPCA) was used for feature extraction.
Abstract: The most vital challenge for a radiologist is locating the brain tumors in the earlier stage. As the brain tumor grows rapidly, doubling its actual size in about twenty-five days. If not dealt properly, the affected person’s survival rate usually does no longer exceed half a year. This can rapidly cause dying. For this reason, an automatic system is desirable for locating brain tumors at the early stage. In general, when compared to computed tomography (CT), magnetic resonance image (MRI) scans are used for detecting the diagnosis of cancerous and noncancerous tumors. However, while MRI scans acquisition, there is a chance of appearing noise such as speckle noise, salt & pepper noise and Gaussian noise. It may degrade classification performance. Hence, a new noise removal algorithm is proposed, namely the modified iterative grouping median filter. Further, Maximum likelihood estimation-based kernel principal component analysis is proposed for feature extraction. A deep learning-based VGG16 architecture has been utilized for segmentation purposes. Experimental results have shown that the proposed algorithm outperforms the well-known techniques in terms of both qualitative and quantitative evaluation.

20 citations

Journal ArticleDOI
TL;DR: In recent years, Aluminium Alloy 7075 plays a vital role in the manufacturing of aircraft wing and fuselage skin due to its light weight and specific strength characteristic behavior.
Abstract: In recent years, Aluminium Alloy 7075 plays a vital role in the manufacturing of aircraft wing and fuselage skin due to its light weight and specific strength characteristic behavior. The component...

20 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202221
2021572
2020234
2019121
2018143
2017136