iosr-Jm   Volume-11 ~ Issue-4 ~ July-Aug 2015

Abstract: Normal body temperature varies by person, age, activity, and time of day. The average normal body temperature is generally accepted as 98.6°F (37°C). Some studies have shown that the "normal" body temperature can have a wide range, from 97°F (36.1°C) to 99°F (37.2°C). A temperature over 100.4°F (38°C) is usually an indication of a fever caused by an infection or illness. A temperature over 100.4°F (38°C) is usually an indication of a fever caused by an infection or illness, hyperthermia and hyperpyrexia. Hyperthermia occurs when the body produces or absorbs more heat than it can dissipate. It is usually caused by prolonged exposure to high temperatures, Axelrodand Diringer (2008), and Laupland (2009).The Easy Fit 5.5 Standard version was used to obtain the parameter estimates and also in determining the distribution that best fits the data on maximum temperature recorded in Adamawa state, Nigeria.

[1]. Abramowitz, M. and Stegun, I. A. (Eds.). Handbook of Mathematical Functions with Formulas, Graphs,and Mathematical Tables,
9th printing. New York: Dover.
[2]. Axelrod Y. K. and Diringer M. N. (2008). "Temperature management in acute neurologic disorders". Neurol. Clin.26(2).
[3]. Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer.
[4]. Cordeiro, G. M. and Castro, M. de (2009). A New family of Generalized Distributions. Journal of StatisticalComputation and
Simulation.
[5]. Dargahi-Noubary, G. R. (1989). "On tail estimation: An improved method". Mathematical Geology 21.Davison, A. C. (1984).
"Modelling Excesses over High Thresholds, with an Application". In de Oliveira,J. Tiago.Statistical Extremes and Applications.
Kluwer.
[6]. Denissen, J.J.A.; Butalid, Ligaya; Penke, Lars; van Aken, Marcel A. G. (2008). The effects of weather ondaily mood: A multilevel
approach. Emotion, 8, 662-667.

Abstract: The health of an individual is the biggest wealth that he can achieve. Rightly said "Health is Wealth", the researcher wants to know why the educated youth even when knowing about the importance of health and fitness, don't try to take care of their physical bodies and mental health and waste their time in activities and not only do not promote growth but instead create hindrances in the normal functioning of the body.Thus it is important to analyse the need for the fitness among the people in our society. Thus researcher has made an attempt to anayse the reasons for the decline of health and fitness in teenagers and children and their consequences by quantitative approach which is the field of applied Mathematical Satistics

[1]. Hiyaguha Cohen, 1999-2015, The Baseline of Health FoundationPHYSICAL ACTIVITY
[2]. Lisa Franchi on November 21, 2013
[3]. Fiona McPherson on Tue, 02/03/2015 - 10:43 Physical fitness crucial for fighting age-related cognitive decline
[4]. Fiona McPherson on Mon, 02/02/2015 - 21:00 http://www.memory-key.com/research/news/physical-fitness-helps-children-think-read-learn [5]. Res Militaris, vol.1, n°3, Summer/Été 2011 3 Temporal Trends in Health and Fitness Levels Overweight and Obesity [6]. Temporal Trends in Health and Fitness of Military Personnel By Kerry A. Sudom& Krystal K. Hachey.

Abstract: The finite difference method is a direct interpretation of the differential equation into a discrete domain so that it can be solved using a numerical method. It is a direct representation of the governing equation (𝜕𝑓𝜕𝑥) = (𝑓𝑖+1−𝑓𝑖)/(𝑥𝑖+1−𝑥𝑖). Using the discontinuous but connected regions, the governing equation is defined within the interval.In this paper, an initial-Boundary value problem of the parabolic type is investigated. The explicit and implicit schemes were established. The numerical solution obtained using Crank-Nicolson's finite difference equations is found to agree with existing analyzing results at discretized nodes of uniform interval.

[1]. Abramowitz.M, and Stegun, I.A. Handbook of mathematics functions (New York Dover, 1965).
[2]. Lapidus L. and G.F. Pinder. Numerical solution of partial differential equations in science and engineering. John Wiley & sons.New York, 1982.
[3]. Richard L. Burden and J.Dogulas Faires. Numerical Analysis. 7th Edition. Brooks/cole USA. 2001.
[4]. William E. Boyce and Richard. C. Diprima Elementary Differential Equations and Boudary value problems Fifth edition. John Wiley & Sons Inc.

Abstract: Motivated by some results on orthogonal (𝜎,𝜏) derivations in semiprime gamma rings, in [6], the authors defined the notion of (𝜎,𝜏) derivations and generalized (𝜎,𝜏) derivations in semiprime gamma rings. In this paper, we also introduce the notion of orthogonal generalized (𝜎,𝜏) derivations in semiprime semiring and derived some interesting results.

keywords: Semirings, (𝜎,𝜏) derivation, generalized(𝜎,𝜏) derivation, orthogonal generalized (𝜎,𝜏) derivation

[1]. N. Argac, A. Nakajima and E. Albas, On orthogonal generalized derivations of semiprime rings, Turkish J. Math., 28(2) (2004), 185 – 194.
[2]. M. Ashraf and M.R. Jamal, Orthogonal derivations in gamma rings, Advances in Algebra, 3(1) (2010), 1 – 6
[3]. M. Ashraf and M.R. Jamal, Orthogonal generalized derivations in gamma rings, Aligarth Bull. Math., 29(1) (2010), 41 - 46
[4]. Bresar.M and Vukman.J, Orthogonal derivation and extension of a theorem of Posner, Radovi Matematicki 5(1989), 237-246.
[5]. E.Posner, Derivations in primerings, Proc.Amer Math.Soc.8(1957), 1093-1100

Abstract: This study investigates the effect of the nano particle effect on magnetohydrodynamic boundary layer flow over a stretching surface with the effect of viscous dissipation. The governing partial differential equations are transformed to a system of ordinary differential equations and solved numerically using fifth order Runge-Kutta method integration scheme and Matlab bvp4c solver. The effects of the Non-Newtonian Williamson parameter, Prandtl number, Lewis number, the diffusivity ratio parameter, heat capacities ratio parameter, Eckert number, Schmidt number on the fluid properties as well as on the skin friction and Nusselt number coefficients are determined and shown graphically.

[1]. Choi, S.U.S., (1995), Enhancing thermal conductivity of fluid with nanoparticles, developments and applications of non-Newtonian
flow. ASME FED, Vol.231, pp.99-105.
[2]. Masuda, H., Ebata, A., Teramae, K., and Hishinuma, N., (1993), Alteration of thermal conductivity and viscosity of liquid by
dispersing ultra-fine particles, Netsu Bussei, Vol.7, pp.227-233.
[3]. Buongiorno, J., Hu, W., (2005), Nanofluid coolants for advanced nuclear power plants, Proceedings of ICAPP 05: May 2005 Seoul .
Sydney: Curran Associates, Inc; pp.15-19.
[4]. Buongiorno, J., (2006), Convective transport in nanofluids, ASME J Heat Transf, Vol.128, pp.240-250.

Abstract: Let G = (V (G),E(G)) and G1= (V (G1),E(G1)) be graphs. In this paper werepresent a homomorphism f :G → G1as a pair f = ( f * , ) where f * : V (G) → V (G1)and : E(G) → E(G1) are maps such that (x,y) = ( f * (x), f * (y)) for all edges(x,y) in G. With this representation we characterize some specialmorphisms likemonomorphism, epimorphism, coretraction, retraction etc in terms of set
functions.Finally we show that the Category of Graphs is not balanced.
Keywords: monomorphism, epimorphism, coretraction, injective, surjective, retraction

[1]. B. Mitchell, Theory of categories (Academic Press, New York and London, 1965).
[2]. Harold Simmons, An Introduction to Category theory, Cambridge University Press, Newyork(2011) pp(226).
[3]. Horst Schubert Categories , Springer-Verlag Berlin Heidelberg-Newyork (1972).
[4]. S. Awodey, Category Theory (Clarendon Press; Oxford University Press Inc., New York, 2006).
[5]. C. Godsil and G. Royle, Algebraic Graph Theory University of Waterloo, Ontario Canada.
[6]. V. K. Balakrishnan, Schaum's Outline of Graph Theory: Including Hundreds of Solved Problems (Schaum's Outline Series, 1997)

Abstract: In this paper, we present the solution of one dimensional advection diffusion equation for initial condition in infinite space analytically by transform to heat equation via coordinate transformation. A comparison among explicit upwind difference scheme, explicit centered difference scheme and explicit downwind difference scheme is projected herein with a variety of numerical results and relative errors. Our goal is to investigate the efficient numerical schemes for advection diffusion equation.
Keywords: Advection Diffusion Equation, Explicit Scheme, Relative Errors.

[1]. Scott A. Socoloofsky Gerhard H. Jirka, "Advection Diffusion Equation", 2004.
[2]. MATH3203 Lecture 2, "Derivation of the Fundamental Conservation Law", Dion Weatherly Earth System Science Computational Centre, University of Queensland, Feb. 27, 2006.
[3]. F. B. Agusto and O. M. Bamigbola, "Numerical Treatment of the Mathematical Models for Water Pollution", Research Journal of Applied Sciences 2(5): 548-556, 2007.
[4]. L.F. Leon, P.M. Austria, "Stability Criterion for Explicit Scheme on the solution of Advection Diffusion Equation", Maxican Institute of Water Technology.
[5]. A. Kumar, D. Kumar, Jaiswal and N. Kumar, "Analytical solution of one dimensional advection diffusion equation with variable coefficients in a finite domain", J. Earth Syst. Sci. Vol. 118, No.5, pp. 539-549, 2009.

Abstract:The Cellular Neural Network (CNN) is an artificial neural network of the nearest neighbour interaction type. It has been used for image processing, pattern recognition, moving object detection, signal processing, augmented reality and etc. The cellular neural network CMOS array was implemented by Anguita et al [1 - 5] and Dalla Betta et al [6]. The design of a cellular neural network template is an important problem, and has received wide attention [7 - 9]. Based on the dynamic analysis of a cellular neural network, this paper presents, a design method for the template of the hole-filler used to improve the performance of the handwritten character recognition using Leapfrog method.

[1] M. Anguita, F. J. Pelayo, E. Ros, D. Palomar and A. Prieto, ―VLSI implementations of CNNs for image processing and vision tasks: single and multiple chip approaches‖, IEEE International Workshop on Cellular Neural Networks and their Applications, 1996, pp. 479 - 484.
[2] M. Anguita, F. J. Pelayo, F. J. Fernandez and A. Prieto, ―A low-power CMOS implementation of programmable CNN's with embedded photosensors‖, IEEE Transactions on Circuits Systems I: Fundamental Theory and Applications, Vol. 44, No.2, 1997, pp. 149 - 153.
[3] M. Anguita, F. J. Pelayo, E. Ros, D. Palomar and A. Prieto, ―Focal-plane and multiple chip VLSI approaches to CNNs‖, Analog Integrated Circuits and Signal Processing, Vol. 15, No. 3, 1998, pp. 263 - 275.
[4] M. Anguita, F. J. Pelayo, I. Rojas and A. Prieto, ―Area efficient implementations of fixed template CNN's‖, IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, Vol. 45, No. 9, 1997, pp. 968 - 973.
[5] M. Anguita, F. J. Fernandez, A. F. Diaz, A. Canas and F. J. Pelayo, ―Parameter configurations for hole extraction in cellular neural networks‖, Analog Integrated Circuits and Signal Processing, Vol. 32, No. 2, 2002, pp.149 - 155.

Abstract: Let G = (σ,μ) be a fuzzy graph. Let u be an element of V. Let N(u) = {v ∈ V : μ (uv) = σ (u) ∧ σ (v)}. The fuzzy support of u is defined as the sum of the neighborhood degrees of the elements in N(u). In this research work we introduce the concept of support strong domination in fuzzy graphs. The fuzzy support of a vertex is defined and domination based on the fuzzy support is considered. Several results involving this new fuzzy domination parameter are established. We also obtain the fuzzy support strong domination number γf(supp) for several classes of fuzzy graphs.

[1]. Zadeh, L.A. 1971, Similarity relations and fuzzy ordering, Information sciences, 3(2), pp. 177-200.
[2]. kaufmann. A., 1976, Introduction a latheorie des sous-ensembles, Io elements thoriques de base.Paris: Masson et cie.
[3]. Bhutani, K.R., 1989 Onautomophism of fuzzy graphs, pattern recognition Letters, 9, pp.159-162..
[4]. J.N. Mordeson ans P.S Nair, Fuzzy graphs and Fuzzy Hyper graphs, Physica Cerlag, Heidelberg,
1998: Second edition 2001..
[5]. A. Rosenfeld, Fuzzy graphs, in L.A. Zadeh, K.S. Fu, M. Shimura(Eds), Fuzzy sets and theirApplications to cognitive and Decision Processes. Academic Press. New York, 1975, 77-95.

Abstract: Recently the present author introduced the notion of generalized quasi-conformal curvature tensor which bridges Conformal curvature tensor, Concircular curvature tensor, Projective curvature tensor and Conharmonic curvature tensor. This article attempts to charectrize Sasakian manifolds with (X,Y) W = 0. Based on this curvature conditions, we obtained and tabled the expression for the Ricci tensor for the respective semi-symmetry type Sasakian manifolds.

[1]. B. J.Papantoniou, Contact Riemannian manifolds satisfying R( ,X) R = 0 and  (k,) -nullity distribution,
Yokohama Math. J., 40(1993), 149-161.
[2]. D. E. Blair, Contact manifolds in Riemannian geometry, Lecture Notes in Mathematics, 509, Springer-Verlag, Berlin, 1976.
[3]. D. Perrone, Contact Riemannian manifolds satisfying R( ,X) R = 0 , Yokohama Math. J., 39 (1992), no. 2, 141-149.

Abstract: Thyroid disorders are common disorders of the thyroid gland. Thyroid disorders include such diseases and conditions as graves disease, thyroid nodules, Hashimoto's thyroiditis, trauma to the thyroid, thyroid cancer and birth defects. These include being born with a defective thyroid gland or without a thyroid gland. Thyroid disorder can be caused by hyperthyroidism, thyroid cancer, goiter, hyperparathyroidism and postpartum thyroiditis. Thyroid disorder are usually characterized by life threatening symptoms such as insomnia, irritability, nervousness, unexplained weight loss, heat sensitivity, increased perspiration, thinning of skin, warm skin, fine hair, brittle hair and thinning hair.

[1]. Shoenfeld Y, Meroni P and Gershwin ME. Autoantibodies. Elsevier. Amsterdam; Boston. 838, 2007.
[2]. HealthLine, 2011, "Thyroid Disorder", retrieved from http://healthline.com.
[3]. Johnson R.C. (1993), "Making the Neural-Fuzzy Connection", Electronic Engineering Times, Cmp Publications, Manhasset, New York.
[4]. Rumelhert D.E.,Windrow B., and Lehr M.A (1994), "Neural Networks:Application in Industry, Business and Science", Communication of ACM,37(1994), 93-105.
[5]. L. A. Zadeh, "Fuzzy sets versus probability," Proc. IEEE, vol. 68, pp. 421-421, (1980).