International Journal of Modern Mathematical Sciences
ISSN: 2166-286X (online)Search Article(s) by:
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Current Issue: Vol. 17 No. 2or Keyword in Title:
Editorial Email: ijmms@modernscientificpress.comor Keyword in Abstract:

Table of Content for Vol. 17 No. 2, 2019

On Some Characterizations of Generalized Log Pearson Type-VII Distribution
Fiaz Ahmad Bhatti, Azeem Ali and Munir Ahmad
 PP. 78 - 84
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ABSTRACT: In this article, generalized log Pearson type VII (GLPT-VII) distribution is characterized via (i) doubly truncated moments and (ii) ratio of truncated moments. The applications and utility of characterizations of GLPT-VII distribution will be constructive for researchers in different disciplines of science.

Semi-analytical Solution for Surface Coverage Model in an Electrochemical Arsenic Sensor Using a New Approach to Homotopy Perturbation Method
V. Ananthaswamy, S. Narmatha
 PP. 85 - 110
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ABSTRACT: The theoretical model for the surface coverage parameter of an electrochemical sensor is considered and discussed. Semi-analytical solution has been derived for arsenic concentration in the steady state and the non-steady state using a new approach to Homotopy perturbation method. Upon comparison, we found that the analytical results of this work are in excellent agreement with the numerical results. Further, the sensitivity of the parameters in the diffusion of the arsenic ions was also analyzed due to its importance in predicting the relationship between the parameters and the model results.

Fractional Calculus and Its Applications for Scientific Professionals: A Literature Review
Rajesh Kumar Shukla and Puneet Sapra
 PP. 111 - 137
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ABSTRACT: In this paper our aim is to explore about the Fractional Calculus and its possible applications in the field of science and engineering. The objective is to expose the reader to the concepts, notations, operators, fractional order differential equations and execution of fractional calculus as well as to show how these may be used to solve the different kinds of modern problems.

Precision Estimation of Assay Data in Mine Exploration Using Robust Regression
Joseph Acquah, Kofi Agyarko and Peter Ofori-Amanfo
 PP. 138 - 150
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ABSTRACT: The paper examined the use of robust regression techniques in solving prob¬lems associated with outliers or extreme observations. Thus, the study seeks for a parameter estimation method which is robust in nature such that a small change in the data set have no effect on the value of the estimation. The robust regression methods considered to determine an acceptable re¬gression model to use are the M-estimate, the MM-estimate, the S-estimate, Ordinary Least Squares (OLS), and the Least Absolute Value (LAV) method. The algorithms of these methods are presented and applied to an assay data in mine exploration to determine the precision estimates in assessing the repeatability of the data. The results show that the use of robust regression techniques in estimating precision of assay data in mine exploration is fea¬sible and reliable.