Qom University of TechnologyMathematics and Computational Sciences2717-27084120230301Numerical solution to Volterra integro-differential equations using collocation approximation1870330610.30511/mcs.2023.1978083.1099ENGaniyuAjileyeDepartment of Mathematics and Statistics, Federal University Wukari, Taraba State, NigeriaSikiru AAmooDepartment of Mathematics and Statistics, Federal University Wukari, Taraba StateJournal Article20221204This paper considers the collocation method for the numerical solution of the Volterra integro- differential equation using polynomial basis functions. The modeled equation was converted into a linear algebraic system of equations and matrix inversion was employed to solve the algebraic equation. We substitute the result of algebraic into the approximate solution to obtain the numerical result. Some numerical problems are solved to show the method's efficiency and consistency.https://mcs.qut.ac.ir/article_703306_902e36cd9368322687846123d4dad4e1.pdfQom University of TechnologyMathematics and Computational Sciences2717-27084120230301On a fractional differential equation with fractional boundary conditions91770330710.30511/mcs.2023.1987591.1106ENYasserKhaliliDepartment of Basic Sciences, Sari Agricultural Sciences and Natural Resources University, 578 Sari, Iran,MiladYadollahzadehDepartment of Mathematics, Faculty of Mathematical Sciences, University of Mazandaran, Babolsar 47416-
95447, IranJournal Article20230116In this article, we study a new nonlinear Langevin equation of two fractional orders with fractional boundary value conditions which is a generalization of previous Langevin equations. Based on Banach and Schauder fixed point theorems, the existence and uniqueness of solutions of this equation are investigated. Moreover, our hypotheses are simpler than similar works.https://mcs.qut.ac.ir/article_703307_542cf67a044ea0d396efa264e3b32ec3.pdfQom University of TechnologyMathematics and Computational Sciences2717-27084120230301Numerical solution of eight order boundary value problems using Chebyshev polynomials182870330910.30511/mcs.2023.1988829.1108ENMusiliu TayoRajiDepartment of Mathematics, Federal University of Agriculture, Abeokuta, Ogun State, NigeriaChristie YemisiIsholaDepartment of Mathematics, National Open University of Nigeria Jabi, Abuja, NigeriaOlayemi OlutolaBabalolaDepartment of Mathematics and Statistics, Osun State College of Technology Esa Oke, Osun State, NigeriaTawakalt AbosedeAyoolaDepartment of Mathematics, Osun State University, Osogbo, NigeriaNasiru MuhammedMomohDepartment of Mathematics, Federal University of Technology Minna, Niger State, Nigeria.Olumuyiwa JamesPeterDepartment of Mathematical and Computer Sciences, University of Medical Sciences,
Ondo City, Ondo State0000-0001-9448-1164Journal Article20230130First-kind Chebyshev polynomials are used as the basis functions in this study to present the approximations to the eighth-order boundary-value problems. The problem is reduced using the suggested approach into a set of linear algebraic equations, which are then solved to determine the unknown constants. To demonstrate the application and effectiveness of the strategy, analytical results are provided using tables and graphs for three examples. The results obtained using the proposed method reveal that it is simple and outperforms comparable solutions in the literature.https://mcs.qut.ac.ir/article_703309_1ba6efe1fb096ae97b9033d5aa0c5642.pdfQom University of TechnologyMathematics and Computational Sciences2717-27084120230301Facial recognition system using eigenfaces and PCA293570330510.30511/mcs.2023.562662.1085ENHamid RezaYazdaniIran University of Science and Technology, School of Mathematics, Tehran, Iran.0000-0002-3556-4864Ali RezaShojaeifardDepartment of Mathematics and Statistics, Imam Hossein Comprehensive University, Tehran, Iran.Journal Article20220926Face recognition is an essential field of image processing and computer vision. In this paper, we have developed a facial recognition system that can detect and recognize the face of a person by comparing the characteristics, and features of the face to those of known faces. Our approach considers the face recognition problem as an intrinsically two-dimensional recognition problem rather than requiring recovery of three-dimensional geometry, considering that eigenvectors generally describe human faces in the face space. The system works by projecting face images onto a feature space that spans the significant variations among known face images that are called eigenvectors (or principal components of the face set). Our technique can learn and recognize new faces in an unsupervised style—this approach is based on eigenfaces and principal component analysis (PCA).https://mcs.qut.ac.ir/article_703305_7e75d542da4fecc5c1c0dabc92143cea.pdfQom University of TechnologyMathematics and Computational Sciences2717-27084120230301Linear programming for instant complimentary food formulations among Tanzanian infants aged 6 to 23 months364470330410.30511/mcs.2023.561478.1080ENHalidi AllyLyemeDepartment of Mathematics, Faculty of Science, Muslim University of Morogoro, Morogoro, Tanzania0000-0002-6139-3739LeonardKatalambulabDepartment of Public Health and Community Nursing, University of DodomaJournal Article20220904It is challenging to follow all nutritional requirements simultaneously. A good mathematical tool for converting nutrient-based suggestions into realistically nutritionally ideal food combinations integrating locally accessible foods is the diet optimization model. The objective of this study is to design a linear programming model that figures out how many grams of each food type need to be mixed to produce an instant meal complement for infants between the ages of 6 and 23 months. The mathematical model developed computes the grams of each food type – Quelea mixed with either Green Banana or White Rice or Irish Potato and Onions, Tomatoes, Carrots and Green bell Pepper. When those foods were combined, an instant food complement will be created and entirely satisfy the preset needs of malnourished infants. Thus, Tanzanian public health technologists and nutritionists may apply the linear programming approach explored in this study to create new ready-to-use food formulations.https://mcs.qut.ac.ir/article_703304_8761d102a88c6195b0975132af94dc8f.pdfQom University of TechnologyMathematics and Computational Sciences2717-27084120230301Approximation of inverse source problem for time fractional pseudo-parabolic equation in $L^p$455770389310.30511/mcs.2023.1990393.1111ENPhong ThanhTranDivision of Applied Mathematics, Thu Dau Mot University, Binh Duong Province, VietnamLong DinhLeDivision of Applied Mathematics, Science and Technology Advanced Institute Van Lang University, Ho Chi Minh City, Viet NamFaculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, Vietnam0000-0001-8805-4588Journal Article20230224In this work, we focus on the final value problem of an inverse problem for the pseudo-parabolic equation. This study aims to provide a regularization method for this equation, once the measurement data are obtained at the final time in $L^{r}(0,\pi)$. We obtain an approximated solution using the Fourier method and the final input data $L^{r}(0,\pi)$ for $r \neq 2$. Using embedding between $L^{r}(0,\pi)$ and Hilbert scales $\mathcal{H}^{\rho}(0,\pi)$, this study is the error between the exact and regularized solutions to be estimated in $L^{r}(0,\pi)$.https://mcs.qut.ac.ir/article_703893_d21afa1d1e996a0c865b31213980d906.pdf