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Dharwad, India

Bommanahal B.,Karnatak University | Mirajkar K.G.,Karnatak Arts College
Mathematics in Computer Science | Year: 2011

The coarseness ξ(G) of a graph G is the maximum number of mutually line-disjoint nonplanar subgraphs of G. Clearly, ξ(G) = 1 if and only if G is nonplanar and G has no two line-disjoint subgraphs homeomorphic to K 3,3 or K 5. In this paper, we obtain a necessary and sufficient condition for plick graph P n(G); n ≥ 1 to have coarseness number one. © 2011 Springer Basel AG. Source


Mathad K.M.,Karnatak Arts College | Shetty I.D.,Karnatak University
International Journal of Agricultural and Statistical Sciences | Year: 2014

A simple sequential non-parametric test for the two-sample problem is proposed. A method of deriving its OC function is given and the adequacy confirmed by simulation. We consider the normal approximation to the U-statistic and later on test for small sample sensitivity. We first consider the Lehmann alternative. The test is found to be performing well even for small sample size. Source


Kadi A.S.,Karnatak University | Gani S.R.,Karnatak Arts College
International Journal of Agricultural and Statistical Sciences | Year: 2011

We are interested in how the introduction of preventive measures affects the long time behaviour of endemic diseases. The quasi-stationary distribution or conditional limiting distribution has proved to be a potential tool in describing the time to extinction of an epidemic. However, the conditional expectation of susceptible given an infective of quasi-stationary distribution is unknown, thus, we have given theoretical framework for comparison of SVIR model with SIR model and it reveals that the expected time to extinction of an epidemic is less in the presence of immunization programs. Source


Kengnal P.,Karnatak Arts College | Megeri M.N.,Karnatak Arts College | Giriyappanavar B.S.,Karnatak Science College | Patil R.R.,Karnatak Arts College | Patil R.R.,Karnatak Science College
Asian Journal of Water, Environment and Pollution | Year: 2015

Water quality has degraded dramatically in the Krishna River (India) due to point and non-point sources. Present investigation aims to assess temporal variations of physical and chemical parameters of the river. Environmental data from rural and urban areas for the period 2007-2012 were compared. A statistical analysis was carried out with six environmental variables considering a multivariate system, analysis of variance and principal component analysis. Statistical analysis divided the river into two zones with different degrees of contamination. The most polluted zone is due to pollution inputs of municipal and industrial origin; this region showed a remarkable deterioration in water quality, mainly due to wastewater discharges. Source

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