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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: In this article, the authors used a three-dimensional finite element model of the acetabular component to analyze the dynamic stumbling activity using ANSYS® and concluded that the Alumina femoral head paired with ultra-high molecular weight polyethylene (UHMWPE) cup reduced the maximum von Mises stress and maximum contact pressure developed between the interface regions when compared with other combinations.
Abstract: The estimation of the hip joint contact stresses and contact pressure distribution during stumbling activities is a critical task for selecting the best material pair in the hip prosthesis design. This paper utilizes a three-dimensional finite element model of acetabular component to analyze the dynamic stumbling activity using ANSYS®. The present study investigates the maximum von Mises stress, contact pressure and deformation developed for different combinations of materials under the stumbling load condition. The different combination of bearing couplings considered for the analysis are metal in contact with plastic, metal on metal, metal on ceramic, ceramic on plastic, ceramic on metal and ceramic on ceramic combinations. The results concluded that the Alumina femoral head paired with ultra-high molecular weight polyethylene (UHMWPE) cup reduces the maximum von Mises stress and maximum contact pressure developed between the interface regions when compared with other combinations. The obtained results are compared with the result of Hai-bo-Jiang et al., for available combinations, and higher correlation of 92% was found between the two results.

10 citations

Journal ArticleDOI
01 Oct 2017
TL;DR: This paper proposes a new k-modes clustering algorithm that is combined with Cuckoo Search algorithm to obtain the global optimum solution for categorical clustering and shows the efficiency of the proposed algorithm.
Abstract: Cluster analysis is the unsupervised learning technique that finds the interesting patterns in the data objects without knowing class labels. Most of the real world dataset consists of categorical data. For example, social media analysis may have the categorical data like the gender as male or female. The k-modes clustering algorithm is the most widely used to group the categorical data, because it is easy to implement and efficient to handle the large amount of data. However, due to its random selection of initial centroids, it provides the local optimum solution. There are number of optimization algorithms are developed to obtain global optimum solution. Cuckoo Search algorithm is the population based metaheuristic optimization algorithms to provide the global optimum solution. Methods: In this paper, k-modes clustering algorithm is combined with Cuckoo Search algorithm to obtain the global optimum solution. Results: Experiments are conducted with benchmark datasets and the results are compared with k-modes and Particle Swarm Optimization with k-modes to prove the efficiency of the proposed algorithm.

10 citations

Journal ArticleDOI
TL;DR: This paper proposes the robust segmentation algorithm that can reliably separate touching cells and is compared with several images which aids in applications such as locating the tumours and other pathologies.
Abstract: The cancer cells are multiplicative in nature. Doctors face difficulties in counting the white blood cells (WBCs) at a particular stage due to crowding of cells. This paper proposes the robust segmentation algorithm that can reliably separate touching cells. Segmentation is the main important step in medical image processing. Precisely locating the area of interest in an image, in the presence of inherent uncertainty and ambiguity, is a challenging problem in medical imaging. Hence, one is often faced with a situation that demands proper segmentation. The algorithm is composed of two steps. It begins with a detecting and finding the cells in the region that utilizes level set algorithm. Next, the contour of big cell is obtained using modified level set active contour based on a piecewise smooth function. Finally, the proposed algorithm is compared with several images which aids in applications such as locating the tumours and other pathologies.

10 citations

Proceedings ArticleDOI
01 Mar 2018
TL;DR: A robust authentication scheme is proposed that utilises only lightweight XOR, one way and perceptual hash operations for authorisation, and multiple factors such as User's Identity, Password and Biometrics are used for better scalability and security.
Abstract: With the advancements in the Information and communication Technologies, people's living are becoming more sophisticated and easier. Information and communication Technologies is the core of modern computing. Among its several applications, smart cities playa major role in the upliftment of the society's well-being. E-governance in the smart cities bridges the gap between the public and the government and hence plays a major role in the modern era. There arises some security concerned issues with the rapid growth of e-governance applications. To ensure its security, authentication must be more secure and must allow only the legitimate users to access the services. In this paper, a robust authentication scheme is proposed to overcome the drawbacks of the existing schemes. It utilises only lightweight XOR, one way and perceptual hash operations for authorisation. Also multiple factors such as User's Identity, Password and Biometrics are used for better scalability and security. The proposed scheme is validated with well known Automated Validation of Internet Security Protocols and Applications tool. The security analysis concludes that the scheme is resistant to various attacks.

10 citations

Journal ArticleDOI
TL;DR: In this article, the machining performance of as-prepared aluminum zirconium diboride AA2024-ZrB2 was investigated for phase identification using X-ray diffraction technique; microstructure analysis using both optical microscope and field emission scanning electron microscope; and analysis of mechanical properties using tensile strength and micro-hardness tests.
Abstract: In recent years, application of aluminum materials in aircraft structures with output responses like maximum material removal rate and minimal surface roughness is at great necessity. This performance is attained during the wire cut electrical discharge machining and is influenced by the extent of ceramic inclusions in the aluminum matrix. The current research focuses on improving the machining performance of as-prepared aluminum zirconium diboride AA2024–ZrB2 prepared at different weight ratios of ZrB2 particles as 0, 2.5, 5, 7.5 and 10 wt%. The as-prepared samples are investigated for different characterizations like phase identification using X-ray diffraction technique; microstructure analysis using both optical microscope and field emission scanning electron microscope; and analysis of mechanical properties using tensile strength and micro-hardness tests. During the machining process, four input parameters like pulse on time Ton (μs), pulse off time Toff (μs), gap voltage GV (V) and ZrB2 wt% are considered for optimization and obtains 23 μs, 41 μs and GV 100 V at 2.5 wt% ZrB2. During machining, multi-response optimization, using response surface methodology with desirability function is performed. The output responses as of maximum material removal rate (MRR) of 0.0765 g/min and minimum surface roughness (SR) of 3.618 μm are obtained. The addition of different wt% ZrB2 in the base matrix has greatly influenced the output response like MRR and SR in the aluminum matrix.

10 citations


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