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Mohamed Jafar O.A.,Jamal Mohamed College Autonomous | Sivakumar R.,AVVM Sri Pushpam College Autonomous
International Review on Computers and Software | Year: 2014

Data Clustering means the act of partitioning a data set into group of similar objects. It is an important activity of data mining. Fuzzy c-means (FCM) is one of the most widely used data clustering methods. However, it suffers from some limitations like easily struck in local minima and sensitive to noise and outlier. Fuzzy possibilistic c-means (FPCM) algorithm is one of the good methods for noisy environment. Partition Index Maximization (PIM) is one of the extensions of FCM algorithm by adding partition coefficient (PC) into FCM objective function. Nature-inspired algorithm such as particle swarm optimization (PSO) is a global optimization technique. It overcomes the problem of local optima. The performance of PSO algorithm can be further improved with the help of fuzzy clustering algorithms. Most of the traditional clustering algorithms are based on Euclidean distance measure. In this paper, two hybrid algorithms namely fuzzy possibilistic c-means based particle swarm optimization algorithm (FPCM-PSO) and fuzzy c-means based particle swarm optimization algorithm with PIM (FUZZY-PSO-PIM) are proposed using different measures including Euclidean, Manhattan and Chessboard distance. Experimental results on well-known real world benchmark UCI repository biomedical data sets and an artificial data set show that Fuzzy-PSO-PIM hybrid algorithm is efficient and report encouraging results than other clustering techniques for all the distance measures. The clustering results are evaluated with respect to many cluster validity measures. It is also observed that hybrid algorithms based on chessboard distance measure produce better results than the other distance measures. © 2014 Praise Worthy Prize S.r.l.-All rights reserved. Source

Abul Hasan M.J.,AVVM Sri Pushpam College Autonomous | Ramakrishnan S.,AVVM Sri Pushpam College Autonomous
Artificial Intelligence Review | Year: 2011

Clustering is a popular data analysis and data mining technique. It is the unsupervised classification of patterns into groups. Many algorithms for large data sets have been proposed in the literature using different techniques. However, conventional algorithms have some shortcomings such as slowness of the convergence, sensitive to initial value and preset classed in large scale data set etc. and they still require much investigation to improve performance and efficiency. Over the last decade, clustering with ant-based and swarm-based algorithms are emerging as an alternative to more traditional clustering techniques. Many complex optimization problems still exist, and it is often very difficult to obtain the desired result with one of these algorithms alone. Thus, robust and flexible techniques of optimization are needed to generate good results for clustering data. Some algorithms that imitate certain natural principles, known as evolutionary algorithms have been used in a wide variety of real-world applications. Recently, much research has been proposed using hybrid evolutionary algorithms to solve the clustering problem. This paper provides a survey of hybrid evolutionary algorithms for cluster analysis. © 2011 Springer Science+Business Media B.V. Source

Madhumathi V.,AVVM Sri Pushpam College Autonomous | Vijayakumar S.,AVVM Sri Pushpam College Autonomous
Biomedicine and Aging Pathology | Year: 2014

In this research, we have conducted docking study to screen bioactive compounds from Microcystis aeruginosa and Phormidium corium. Among the two blue-green algal species were analyzed for chemical nature of bioactive substances using TLC and GC-MS methods. The antimicrobial compounds identified were phenolics, alkaloids, steroids. In the present study as reported that M. aeruginosa curde extract contained the bioactive compound Microginins, while Cyalobolide B was detected from P. corium. The phytochemical analysis of M. aeruginosa (Microginins), provided ethaneloic acid, Octanal, 3,7,11-Trimethyl-1,6,10-dodecatrien-3-ol (nerolidal), Monomethyl hydrazine and formic acid. The cumulative effect of these phytochemical provided more effective antimicrobial compound in inhibiting microbial growth. The phytochemical analysis of P. corium (Cyalobolide B) exhibited Ethaneloic acid, Dihydrodiplodialide, 3, 7, 11-Trimethyl-1, 6, 10-dodecatrien-3-ol (nerolidal), 1-Dodecanol, 1-Hexadecanol (CAS) and nanonic acid. These compounds together exhibited more effective antimicrobial substance in inhibiting microbial growth. Which members of a community interact with themselves as well as with different host structures and components of Candida albicans and Streptococcus mutans. The pathogenesis of this dental infection is a multi factorial process that results in a serious degenerative disease of the Oral candidiasis. In the present study SAP (secreted aspartyl proteinases in virulence and pathogenesis) is taken as a case study molecule to understand high reactive responses of various drugs administered for the oral candidiasis. The drugs are being compared with the SAP from C. albicans and SpaP (cell surface antigen SpaP gene) from S. mutans. The SAP and SpaP interacted with formic acid, nerolidal, octanol and nonanoic acid using docking methods. The exponentially increasing speed of computational methods makes a more extensive use in the early stages of drug discovery attractive if sufficient accuracy can be achieved. © 2014 Elsevier Masson SAS. All rights reserved. Source

Murugesan S.,AVVM Sri Pushpam College Autonomous | Pannerselvam A.,AVVM Sri Pushpam College Autonomous | Tangavelou A.C.,Bio Science Research Foundation
Journal of Applied Pharmaceutical Science | Year: 2011

An ethnomedicinal plant, Memecylon umbellatum Burm. f., was investigated for preliminary phytochemical screening and antimicrobial activity. Preliminary phytochemical screening of various extracts of the leaves revealed the presence of various classes of compounds such as amino acids, carbohydrates, flavonoids, gum, oil & resins, proteins, phenolic groups, saponins, steroids, tannins and terpenoids. Bioassay of antimicrobial activity of leaves of petroleum ether, chloroform and ethanol extracts showed significant activity against the human pathogens such as Streptococcus pneumoniae causing brain abscesses, pneumonia and septic arthritis, Proteus vulgaris, Pseudomonas aeruginosa causing urinary tract infections and septicaemia, Salmonella typhi causing typhoid fever, Vibrio species causing diarrheal infections and the fungus Candida albicans. The antimicrobial activity of the petroleum ether, chloroform and ethanolic leaf extract showed concentration-dependent activity against all the tested bacteria with the zone of inhibition at various concentrations. Thus the findings revealed the medicinal potential of Memecylon umbellatum against various infectious diseases to develop a drug. © 2010 Medipoeia. Source

Karthika K.,AVVM Sri Pushpam College Autonomous | Ravichandran K.,AVVM Sri Pushpam College Autonomous
Ceramics International | Year: 2015

Undoped and doubly (Mn+Co) doped ZnO nanopowders were synthesized with different doping levels of Co (1, 2, 3, 4 and 5 at%) and constant Mn doping level (10 at%) using a simple soft chemical route. XRD profiles confirmed that the synthesized material is nanocrystalline ZnO with hexagonal wurtzite structure. No peaks other than the characteristic ZnO peaks were observed in the XRD pattern confirming the absence of any secondary phase. Antibacterial activities of synthesized ZnO nanopowders were tested against Staphylococcus aureus bacteria using agar well diffusion method. It was found that the antibacterial efficiency of the doubly doped ZnO nanopowders was remarkably high when the Co doping level was 5 at%. The obtained PL, SEM and TEM results are corroborated well with the antibacterial activity. Magnetic measurements showed that undoped ZnO sample exhibits diamagnetic behavior and as the Co doping level increases, the nanopowder behaves as a ferromagnetic material. © 2015 Elsevier Ltd. and Techna Group S.r.l. All rights reserved. Source

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