i-manager's Journal on Mathematics (JMAT)


Volume 3 Issue 1 January - March 2014

Article

Some New Generalized Difference Sequence Spaces with Modular Sequence Space

Gülcan Atici* , Cigdem A. BEKTAS**
* Department of Mathematics, Mus Alparslan University, Mus, Turkey.
** Department of Mathematics, Firat University, Elazig, Turkey.
Atici, G., and Bektas, C.A. (2014). Some New Generalized Difference Sequence Spaces With Modular Sequence Space. i-manager’s Journal on Mathematics, 3(1), 1-6. https://doi.org/10.26634/jmat.3.1.2937

Abstract

In this paper, the authors define the sequence space used in a sequence of Orlicz functions , generalized difference sequence and seminorm q. They examine some topological properties of this space.

Article

Collections of Statements Related to Domination Parameters in Graphs

D. R. Robert Joan* , Y. Sheeja**
* Assistant Professor of Mathematics in Christian College of Education, Marthandam, Tamilnadu, India.
** Assistant Professor, Department of mathematics, M.E.T. College of Education, Chenbagaramanputhoor, Tamilnadu, India.
Joan, D. R. R., and Sheeja, Y. (2014). Collections Of Statements Related To Domination Parameters In Graphs. i-manager’s Journal on Mathematics, 3(1), 7-13. https://doi.org/10.26634/jmat.3.1.2938

Abstract

A dominating set D ⊆ V is said to be a nilprivate neighbour dominating set if, for every vertex u in D has no private neighbour in V-D. The nilprivate neighbour domination number γnpn(G) is the minimum cardinality of a nilprivate npn neighbour dominating set. A dominating set D⊆ V of a graph G is a non-split dominating set if the induced sub-graph is connected. The non-split domination number γns(G) is the minimum cardinality of a non-split dominating set of G. A dominating set D ⊆ V of a graph G is a strong non-split dominating set if the induced sub-graph is complete. The strong non-split domination number sns(G) is the minimum cardinality of a strong non-split dominating set of G. The dominating set D ⊆ V of a graph G is a vertex set dominating set if for any set S ⊆V-D, there exists a vertex vD such that the induced sub-graph is connected.The vertex set domination number γvs(G) is the minimum cardinality of a vs vertex set dominating set of G. A dominating set D of a graph G = (V, E) is a strong non-split dominating set if the induced sub-graph is complete. The strong non-split domination number γsns(G) of G is the minimum cardinality of a strong sns non-split dominating set of G. Here, the authors state some definitions and statements related to the Nilprivate neighbour domination and strong non-split domination number in graphs. In conclusion, the authors state the domination of strong non-split domination graphs.

Research Paper

Calculating Tri–Symmetrical Analytics: A Guide Into The In–Depth Processes Associated With The Post Hoc Advanced Statistical Metrics Used To Determine The Value Of Significant Tri–Squared Tests

James Edward Osler II*
North Carolina Central University, Durham, North Carolina.
Osler, J. E., II. (2014). Calculating Tri–Symmetrical Analytics: A Guide into the In–Depth Processes Associated with the Post Hoc Advanced Statistical Metrics used to Determine the Value of Significant Tri–Squared Tests. i-manager’s Journal on Mathematics, 3(1), 14-26. https://doi.org/10.26634/jmat.3.1.2939

Abstract

This monograph provides an epistemological guide for the Post Hoc Tri–Symmetrical Omnibus Test for the Tri–Squared Test. In this guide, Advanced Tri–Symmetrical Tests are explained in great detail and are calculated using sample data. Tri–Symmetrical Omnibus Tests use Tri–Squared correlation metrics and Tri–Squared association analytics to further discern information regarding the outcomes of a statistically significant Tri–Squared Test. In this narrative, multiple sequential Tri–Symmetrical mathematical models are illustrated in a tabular format to demonstrate the entire process of advanced Tri–Symmetrical inquiry.

Research Paper

Synchronization Of Three Dimensional Cancer Model With Lorenz System Using A Robust Adaptive Sliding Mode Controller

Mohammad *
Department of General Requirements, College of Applied Sciences, Nizwa, Oman.
Shahzad, M. (2014). Synchronization of Three Dimensional Cancer Model with Lorenz System using A Robust Adaptive Sliding Mode Controller. i-manager’s Journal on Mathematics, 3(1), 27-34. https://doi.org/10.26634/jmat.3.1.2940

Abstract

This paper investigates the synchronization of chaotic Three Dimensional Cancer Model (TDCM) with Lorenz System (LS) using a Robust Adaptive Sliding Mode Controller (RASMC) together with uncertainties, external disturbances and fully unknown parameters. The technique used for synchronization is based on simple suitable sliding surface, which includes synchronization errors and appropriate update laws to tackle the uncertainties, external disturbances and unknown parameters. All simulations to achieve the synchronization for the proposed technique for the two non-identical systems under consideration are being done using Mathematica.

Research Paper

Mass Transfer Effects On Nonlinear MHD Boundary Layer Flow Of Liquid Metal Over A Porous Nonlinearly Stretching Surface Through Porous Medium With Nonlinear Radiation

s mohammed ibrahim*
Department of Mathematics, Priyadarshini College of Engineering & Technology, Nellore, Andhra Pradesh, India
Ibrahim, S.M. (2014). Mass Transfer Effects On Nonlinear MHD Boundary Layer Flow Of Liquid Metal Over A Porous Nonlinearly Stretching Surface Through Porous Medium With Nonlinear Radiation. i-manager’s Journal on Mathematics, 3(1), 35-45. https://doi.org/10.26634/jmat.3.1.2941

Abstract

The paper investigates the nonlinear radiation effects on two-dimensional, steady MHD laminar boundary layer flow with heat and mass transfer characteristic of an incompressible, viscous, electrically conducting fluid over a nonlinearly stretching surface through a porous medium. The liquid metal is assumed to be gray, emitting, and absorbing, but nonscattering medium. The basic equations governing the flow are in the form of partial differential equations and have been reduced to a set of non-linear ordinary differential equations by applying suitable similarity transformations. The problem is tackled numerically using shooting techniques with fourth order Runge-Kutta integration scheme. Pertinent results with respect to embedded parameters are displayed graphically for the velocity, temperature, concentration, skin-friction coefficient, rate of heat transfer and rate of mass transfer profiles and were discussed quantitatively.