On iterative techniques for numerical solutions of linear and nonlinear differential equations

This paper presents Differential Transformation Method (DTM) and Picard’s Iterative Method (PIM) as computational techniques in solving linear and nonlinear differential equations. For numerical analysis of the methods, three examples are considered. The results obtained are compared with their corresponding exact solutions. A link between successive terms of the solutions using the two methods is noted. The DTM is very effective and reliable in obtaining approximate solutions. The PIM requires the satisfaction of Lipschitz continuity condition; though, its results also converge rapidly to the exact solutions

Breast cancer patients in Nigeria:Data exploration approach

Breast cancer is the type of cancer that develops from breast tissue;it is mostly common in women and it is one of the most studied diseases, largely because of its high mortality(second to lung cancer). However,it occursinmales also.This article presents a statistical study of the distribution of age,gender,length of stay, mode of diagnosis,status(dead or alive)after treatment and the location of breast cancer among 300 patients admitted in the University of Ilorin teaching hospital,Ilorin, Nigeria. The study covers a period of five (5)years;from 2011 to 2016 and logistic regression was used to perform the basic analysis int his study. It was discovered that the age of patient sand the location of the breast cancer(right or left)contributes significantly to the survival of the patients.However,early detection and treatment of the disease is highly encouraged.This study also recommends that awareness should be taken to the grassroots and males should not be excluded from this discussio

A Monte Carlo Simulation Approach in Assessing Risk and Uncertainty Involved in Estimating the Expected Earnings of an Organization: A Case Study in Nigeria

This work provides a simulation-based approach of assessing the risk and uncertainty involved in estimating the expected earnings of an organization. The procedure involves using Monte Carlo Simulation (MCS) in creating various possible outcomes and scenarios. The MCS is found to be more effective than single point estimates or guesswork. Hence, it is an efficient and useful tool in risk management analysis. The analysis of the output of the simulation reveals that the expected earnings is a little bit lower than the most likely forecasted value of N30m but there is 37% chance that the expected earnings might drop below or rise above the estimated value by margin of N10.9m and the wide range of possible outcomes make the venture to be very risky as uncertainties in unit sales, unit price or variable cost can push the earnings to assume any value within the wide range. It is also observed that a large increase in the unit sales and a moderate increase in the unit price will increase the expected revenue which will in turn increase the earnings. The regression analysis gives almost the same result as MCS

Approximate Solution of Multipoint Boundary Value Problems

This study applies the Differential Transform Method (DIM) to obtain the approximate solution of multipoint bmmdary value problems. Two examples are solved to illustrate the efficiency of the method. Comparison with the solution obtained by Adomian Decomposition Method revealed that the DIM is an excellent method for this type of problem

Application of Semi-Analytical Technique for Solving Thirteenth Order Boundary Value Problem

This work considers the numerical solution of thirteenth order boundary value problems using the modified Adomian decomposition method (MADM). Some examples are considered to illustrate the efficiency of the method. It is demonstrated that MADM converges more rapidly to the exact solution than the existing methods in literature and it reduces the computational involvemen

Comparison Homotopy Perturbation and Adomian Decomposition Techniques for Parabolic Equations

This paper compares homotopy perturbation and Adomian decomposition techniques for the solution of parabolic equations. Some examples are considered to illustrate the techniques. The results reveal that the two techniques gave closed form of solution and as such considered most suitable for solving heat flow problems

Irreversibility Analysis of a Radiative MHD Poiseuille Flow through Porous Medium with Slip Condition

In this article, irreversibility analysis of thermal radiation with slip condition on MHD Poiseuille flow through porous medium is investigated. The upper and lower walls are kept constant with the same temperature. The radiative heat flux in the energy equation is assumed to follow Roseland approximation. Semi-analytical solutions of the non-linear boundary value problems obtained from the governing equations is constructed using Adomian decomposition method, and the effects of some fluid parameters on fluid motion, temperature, entropy generation and Bejan number are presented

The Kumaraswamy-Power Distribution: A Generalization of the Power Distribution

We introduce a generalization referred to as the Kumaraswamy Power distribution. The proposed model serves as a generalization of the two-parameter Power distribution using the Kumaraswamy Generalized family of distributions. We investigate some of its statistical properties; the Generalized Power distribution, Exponentiated Power distribution and the Power distribution are found to be sub-models of the proposed distribution. The method of maximum likelihood estimation is proposed in estimating the parameters of the model

Correspondence Analysis for the Trend of Human African Trypanosomiasis

The aim of this research work is to give a graphical picture of the declining trend of the Human African Trypanosomiasis (T.b. gambiense) in 12 selected endemic countries (based on 10 years data) via the application of correspondence analysis. Grouping the countries into three regions affects the model but reveals that the disease is most endemic in Central Africa but least in West Africa. Hence, we therefore recommend that efforts must be intensified by the countries in the Central Africa to reduce the menace of the disease since graphically; there have been reported cases mostly in this region for the past 10 year

Quantile Approximation of the Chi–square Distribution using the Quantile Mechanics

In the field of probability and statistics, the quantile function and the quantile density function which is the derivative of the quantile function are one of the important ways of characterizing probability distributions and as well, can serve as a viable alternative to the probability mass function or probability density function. The quantile function (QF) and the cumulative distribution function (CDF) of the chi-square distribution do not have closed form representations except at degrees of freedom equals to two and as such researchers devise some methods for their approximations. One of the available methods is the quantile mechanics approach. The paper is focused on using the quantile mechanics approach to obtain the quantile density function and their corresponding quartiles or percentage points. The outcome of the method is second order nonlinear ordinary differential equation (ODE) which was solved using the traditional power series method. The quantile density function was transformed to obtain the respective percentage points (quartiles) which were represented on a table. The results compared favorably with known results at high quartiles. A very clear application of this method will help in modeling and simulation of physical processes