


Paper's Title:
Existence of Compositional Square Roots of Circle Maps
Author(s):
K. Ali Akbar and T. Mubeena
Department of Mathematics,
School of Physical Sciences,
Central University of Kerala,
Periya  671320,
Kasaragod,
Kerala,
India.
Email: aliakbar.pkd@gmail.com,
aliakbar@cukerala.ac.in
Department of Mathematics,
School of Mathematics and Computational Sciences,
University of Calicut,
Thenhipalam673635,
Malappuram,
Kerala,
India.
Email: mubeenatc@gmail.com,
mubeenatc@uoc.ac.in
Abstract:
In this paper, we discuss the existence of compositional square roots of circle maps. If f and g are two maps such that g ○ g = f, we say that g is a compositional square root of f.
Paper's Title:
New Coincidence and Fixed Point Theorems for Strictly Contractive Hybrid Maps
Author(s):
S. L. Singh and Amal M. Hashim
21, Govind Nagar, Rishikesh 249201,
Ua, India
vedicmri@sancharnet.in
Dept. of Math., College of Science,
Univ. of Basarah,
Iraq.
Abstract:
The purpose of this paper is to study the (EA)property and noncompatible maps of a hybrid pair of singlevalued and multivalued maps in fixed point considerations. Such maps have the remarkable property that they need not be continuous at their common fixed points. We use this property to obtain some coincidence and fixed point theorems for strictly contractive hybrid maps without using their continuity and completeness or compactness of the space.
Paper's Title:
A Comparison Between Two Different Stochastic Epidemic Models with Respect to the Entropy
Author(s):
Farzad Fatehi and Tayebe Waezizadeh
Department of Mathematics,
University of Sussex,
Brighton BN1 9QH,
UK.
Email: f.fatehi@sussex.ac.uk
URL:
http://www.sussex.ac.uk/profiles/361251
Department of Pure Mathematics, Faculty
of Mathematics and Computer,
Shahid Bahonar University of Kerman,
Kerman 7616914111,
Iran.
Email: waezizadeh@uk.ac.ir
URL:
http://academicstaff.uk.ac.ir/en/tavaezizadeh
Abstract:
In this paper at first a brief history of mathematical models is presented with the aim to clarify the reliability of stochastic models over deterministic models. Next, the necessary background about random variables and stochastic processes, especially Markov chains and the entropy are introduced. After that, entropy of SIR stochastic models is computed and it is proven that an epidemic will disappear after a long time. Entropy of a stochastic mathematical model determines the average uncertainty about the outcome of that random experiment. At the end, we introduce a chain binomial epidemic model and compute its entropy, which is then compared with the DTMC SIR epidemic model to show which one is nearer to reality.
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