Isomorphism and Anti Isomorphism in (Q,L)-Fuzzy Translation of (Q,L)--Fuzzy Subhemirings of A Hemiring

2015 ◽  
Vol 2 (2) ◽  
pp. 51-54
Author(s):  
Anitha.N ◽  
Latha.M
Keyword(s):  
Subject Classification ◽  
Ams Subject Classification

In this paper, we made an attempt to study the algebraic nature of a (Q,L)--fuzzy subhemiring of a hemiring. 2000 AMS Subject Classification: 03F55, 06D72, 08A72.

Designs Robust Against Aberrations

1993 ◽  
Vol 43 (1-2) ◽  
pp. 95-108 ◽  
Author(s):  
N. K. Mandal ◽  
K. R. Shah
Keyword(s):  
Sufficient Conditions ◽  
Subject Classification ◽  
Alternative Formulation ◽  
Block Designs ◽  
Ams Subject Classification ◽  
Secondary 62K05

In this paper, we obtain sufficient conditions for a design to be robust against aberrations in the sense of Box and Draper. Block designs, row-column designs and fractional designs are considered here. An alternative formulation of robustness is also presented. AMS Subject Classification: Primary 62K99; Secondary 62K05.

scholarly journals Two Higher Order Iterative Methods for Solving Nonlinear Equations

2018 ◽  
Vol 14 (1) ◽  
pp. 179-187
Author(s):  
Jivandhar Jnawali ◽  
Chet Raj Bhatta
Keyword(s):  
Iterative Methods ◽  
Nonlinear Equations ◽  
Order Of Convergence ◽  
Higher Order ◽  
Secant Method ◽  
Subject Classification ◽  
Numerical Examples ◽  
Ams Subject Classification

 The main purpose of this paper is to derive two higher order iterative methods for solving nonlinear equations as variants of Mir, Ayub and Rafiq method. These methods are free from higher order derivatives. We obtain these methods by amalgamating Mir, Ayub and Rafiq method with standard secant method and modified secant method given by Amat and Busquier. The order of convergence of new variants are four and six. Also, numerical examples are given to compare the performance of newly introduced methods with the similar existing methods. 2010 AMS Subject Classification: 65H05 Journal of the Institute of Engineering, 2018, 14(1): 179-187

scholarly journals Reinforcement Number of a Graph with respect to Half-Domination

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
G. Muhiuddin ◽  
N. Sridharan ◽  
D. Al-Kadi ◽  
S. Amutha ◽  
M. E. Elnair
Keyword(s):  
Upper Bounds ◽  
Subject Classification ◽  
Ams Subject Classification

In this paper, we introduce the concept of reinforcement number with respect to half-domination and initiate a study on this parameter. Furthermore, we obtain various upper bounds for this parameter. AMS subject classification: 05C38, 05C40, 05C69.

scholarly journals AMS subject classification:30C45 Meromorphically p-valent functions defined by integral operator involving ȴ-Function in new subclasses

2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Ahmed Khalaf Radhi ◽  
Thamer Khalil Al-Khafaji
Keyword(s):  
Integral Operator ◽  
Convex Set ◽  
Subject Classification ◽  
Partial Sums ◽  
Coefficient Inequality ◽  
Ams Subject Classification ◽  
Distortion Bounds

Some relations in this paper we using  in  new subclass of meromorphically p-valent functions TK( ) defined by integral operator involving  -function  We derived some properties, like, coefficient inequality  , growth and distortion bounds by theorems (2) and (3), Partial sums, convex set, radii of starlikeness and radii  convexity.

Inverse Sampling for Bivariate Nonparametric Two-Sample Problems Against Restricted Alternatives

1992 ◽  
Vol 42 (3-4) ◽  
pp. 221-236 ◽  
Author(s):  
Uttam Bandyopadhyay ◽  
Gopaldeb Chattopadhyay
Keyword(s):  
Nonparametric Tests ◽  
Bivariate Distribution ◽  
Distribution Functions ◽  
Subject Classification ◽  
Fixed Size ◽  
Inverse Sampling ◽  
Large Sample ◽  
Ams Subject Classification

The object of the present investigation is to provide suitable nonparametric tests for testing the identity of two bivariate distribution functions F1 and F2 against a class of restricted alternatives when there is sample of fixed size m from F1 and the observations from F2 are drawn sequentially. Various large sample results of the proposed tests are formulated and examined. AMS Subject Classification: Primary 62010, Secondary 62020.

Detailed Statistical Inference—An Alternative Non-Bayesian Approach : Two-Decision Problem

1992 ◽  
Vol 42 (1-2) ◽  
pp. 41-74
Author(s):  
Shoutir Kishore Chatterjee ◽  
Gaurangadeb Chattopadhyay
Keyword(s):  
Statistical Inference ◽  
Bayesian Approach ◽  
Decision Problem ◽  
Utility Functions ◽  
Subject Classification ◽  
New Approach ◽  
Ams Subject Classification ◽  
Actual Application ◽  
Betting Odds

In this paper we propose a new approach to detailed inference for any two-decision problem under the frequentist framework, based on a somewhat different interpretation of the confidence coefficients in terms of betting odds. We first elaborate this interpretation with reference to summary inference and enlarge the interpretation to the needs of detailed inference. The actual application of the proposed technique requires the choice of some suitable utility functions. We illustrate our ideas through some examples. AMS Subject Classification: 62 A 99.

Incomplete Split-Plot Designs Generatd By GDPBIBD(2)

1996 ◽  
Vol 46 (1-2) ◽  
pp. 117-128 ◽  
Author(s):  
Iwona Mejza ◽  
Stanislaw Mejza
Keyword(s):  
Block Design ◽  
Subject Classification ◽  
Incomplete Block ◽  
Balanced Incomplete Block Design ◽  
Ams Subject Classification ◽  
Incomplete Block Design ◽  
Split Plot ◽  
Balanced Incomplete Block ◽  
Plot Design

The paper deals with split-plot types of experiment in which some kind of incompleteness can be accepted. In particular, the considered designs can be incomplete with regard to the wboleplot treatments or with regard to the subplot treatments. In such a case the incomplete treatments are arranged in a Gtoup Divisible Partially Balanced Incomplete Block Design with Two Associate Classes (GDPBIBD{2)). Hence, the resulting desian is called incomplete split-plot design generated by GDPBIBD(2). AMS Subject Classification: 62K10, 62K15.

scholarly journals Certain Features of Fuzzy Contra-continuous functions

1970 ◽  
Vol 32 (1) ◽  
pp. 71-77
Author(s):  
MH Rashid ◽  
DM Ali
Keyword(s):  
Compact Space ◽  
Continuous Functions ◽  
Subject Classification ◽  
Topological Spaces ◽  
Fuzzy Graph ◽  
Closed Space ◽  
Ams Subject Classification ◽  
Fuzzy Topological Spaces ◽  
Academy Of Sciences

We deal with fuzzy topological spaces, fuzzy compact space, fuzzy S-closed space, fuzzy graph, fuzzy continuous functions and fuzzy LC-continuous functions. In this paper, we introduce the concepts of fuzzy contra-continuities and explore properties and relationships of such types of functions. Keywords: fuzzy contra-continuity, fuzzy S-closed space, fuzzy graph. AMS Subject Classification: 54A40. doi: 10.3329/jbas.v32i1.2444 Journal of Bangladesh Academy of Sciences, Vol. 32, No. 1, 71-77, 2008

scholarly journals Inverse Sum Status Energy of a Graph

2021 ◽  
Vol 9 (VI) ◽  
pp. 86-92
Author(s):  
K. N. Prakasha
Keyword(s):  
Subject Classification ◽  
Ams Subject Classification ◽  
Status Index

Motivated by the inverse sum status index, we introduce the inverse sum status matrix ISS={■((σ_u σ_v)/((σ_u+σ_v ) ) if u_i~v_j,@0 otherwise)┤ Thus we also obtained the results for well known graphs. Keywords: Inverse sum status energy, Inverse Sum Indeg matrix. 2010 AMS Subject Classification: 05C50.

scholarly journals Interval valued Fuzzy n-normed linear space

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
S. Vijayabalajia ◽  
S.Anita Shanthib ◽  
N. Thillaigovindanb
Keyword(s):  
Tensor Product ◽  
Linear Space ◽  
Normed Linear Space ◽  
Subject Classification ◽  
Ams Subject Classification ◽  
Interval Valued

The aim of this paper is to introduce the notion of interval-valued fuzzy subspace with its flags and interval-valued fuzzy n-normed linear space. We define the operations intersection, sum, directsum and tensor product of intervalvalued fuzzy subspaces and obtain their corresponding flags. Further we provide some results on interval-valued fuzzy n-normed linear space. AMS Subject Classification : 46S40, 03E72.

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