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

Machine Learning Heuristic for Solving Multi-Mode Resource-Constrained Project Scheduling Problems

The non-preemptive resource-constrained project scheduling problem is considered in this work. It is assumed that each activity has many ways of execution and the objective is to find a schedule that minimizes the project’s completion time (multi-mode RCPSP). Methods that are based on priority rules do not always give the needed very good results when used to solve multi-mode RCPSP. In solving large real-life problems quickly though, these methods are absolutely necessary. Hence good methods based on priority rules to get the primary results for metaheuristic algorithms are needed. This work presents a novel method based on priority rules to calculate the primary solutions for metaheuristic algorithms. It is a machine learning approach. This algorithm first of all uses Preprocessing to reduce the project data in order to speed up the process. It then employs a mode assignment procedure to obtain the mode of each job. After which the algorithm uses machine learning priority rule to get the precedence feasible activity list of the project’s tasks. Finally, it then uses the Serial Schedule Generation Scheme to get the total completion time of the project. In our experiments, we use our algorithm to solve some problems in the literature that was solved with metaheuristic procedures. We compared our results with the initial solutions the authors started with, and our results competes favorably with the initial solutions, making our algorithm a good entry point for metaheuristic procedures

Minimization of Failed Roads - A Hybrid Resource-Constrained Project Scheduling Problem

Causes of failed roads and the reasons why most roads stay consistently failed in some nations of the world, like Nigeria, may be attributed to many factors, salient among them may be corruption and recession ultimately. Corruption in the award of road construction contracts make roads not to be properly done, to meet set standards thereby failing almost immediately they are completed. So, if corruption is minimized in awarding road construction contracts, the number of failed roads maybe minimized. This paper introduces some solution methods to minimize corruption in road construction projects so that good and sustainable roads are constructed even if there is also recession. In our experiment, we formulated the construction of real life 5km asphalt road as a hybrid resource constrained project scheduling problem (HRCPSP). Using priority based project scheduling technique, our results show the number of skilled workers needed in each period which gives the idea of the amount of fund needed in each of the periods. We constructed two Gantt diagrams: when resources are unconstrained and when resources are constrained to the minimal demand of jobs in the eligible set in each period. The unconstrained Gantt diagram helps to know the maximum amount of fund that should be released to the engineers in each period. This helps to curb corruption. The constrained Gantt diagram helps to know the minimum amount that should be released to the engineers for work to go on and the project to get to completion stage even there is recession. This helps project to be completed even if there is recession

Data in support of high rate of pregnancy related deaths in Maiduguri,Borno State,Northeast Nigeria

Pregnancy relateddeaths(PRD)arepublichealthconcerninmost developing countriesandNigeriainparticular.Despitetheefforts put inbytheconcernedauthorities,PRDremainsanintegralpart of maternalmortalityormaternaldeathsinNigeriaingeneraland Borno stateinparticular,asevidencedfromtherecordsobtained from UmaruShehuHospital,Maiduguri(astatehospitalinthe state capital.ThedatacontainsfrequencyofPRDinmonthsand grouped intogynaecology,ante-natalandpost-natal,andlabour obtained frommid-2009tomid-2017.Thestatisticalanalysisof the datamayrevealtheextentofincidenceorepidemiologyof PRD isinthestat

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

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

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

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