Mathematical and Computational Applications

Special Issue Information

Dear Colleagues,

Please visit this site http://physicsmathcomputing.com/ for a detailed description of this Special Issue. The Special Issue will mainly consist of selected papers presented at the "2nd Global Conference on Applied Physics, Mathematics and Computing (APMC-18)". Papers considered to fit the scope of the journal and of sufficient quality, after evaluation by the reviewers, will be published free of charge. The main topics of this Special Issue are:

Applied Mathematics

Mathematical modelling, simulation and optimization
Applied partial differential equations
Numerical analysis and mathematical methods
Mathematical modeling in materials science and biology
Nonlinear problems in mechanics
Homogenisation and multiscale analysis
Inverse problems
Algebra and its application
Differential equations, dynamical systems and their applications
Fuzzy mathematics and its applications
Geometry and its application
Statistical methods in technical and economic sciences and practice
Probability and decision theory
Design of experiments
Game theory

Applied Computing

Computer Applications in Science and Engineering
Modeling and Simulation
Computational chemistry and physics. Computational materials
Computational fluid dynamics
Computation and data enabled social science. Business and Social Issues
Computer Science
Bioinformatics and computational biology
Information Technology
Web Technology
Measurement Technologies
Software Design and Development
Simulation Tools
Formal Methods
Networking and Internet of Things
Artificial Intelligence
Trends and Applications in Accessibility

Prof. Dr. Israel González Carrasco
Guest Editor

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Published Papers (3 papers)

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Research

13 pages, 5179 KiB

Open AccessArticle

A Novel Air Quality Monitoring Unit Using Cloudino and FIWARE Technologies

by Yolanda Raquel Baca Gómez, Hugo Estrada Esquivel, Alicia Martínez Rebollar and Daniel Villanueva Vásquez

Math. Comput. Appl. 2019, 24(1), 15; https://doi.org/10.3390/mca24010015 - 24 Jan 2019

Cited by 5 | Viewed by 3820

Abstract

Smart City applications aim to improve the quality of life of citizens. Applying technologies of the Internet of Things (IoT) to urban environments is considered as a key of the development of smart cities. In this context, air pollution is one of the most important factors affecting the quality of life and the health of the increasing urban population of industrial societies. For this reason, it is essential to develop applications that allow citizens monitoring the concentration of pollutants and avoid places with high levels of pollution. Due to the increasing use of IoT in different areas, there are arising platforms which deal with the challenges IoT implies, such as FIWARE, which provides technologies to facilitate the development of IoT applications. In this paper, an Air Quality Monitoring Unit using Cloudino and Arduino devices and FIWARE technologies is presented. Through Cloudino and Arduino, the monitoring unit gather data from various sensors and transforms the data in a FIWARE data model. Then, the measurements are sent to the Orion Context Broker (OCB), which is a software component provided by FIWARE. The Orion Context Broker allows to manage and publish the data to be consumed by users and applications. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd Global Conference on Applied Physics, Mathematics and Computing (APMC-18))

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8 pages, 800 KiB

Open AccessArticle

Iterated Petrov–Galerkin Method with Regular Pairs for Solving Fredholm Integral Equations of the Second Kind

by Silvia Alejandra Seminara and María Inés Troparevsky

Math. Comput. Appl. 2018, 23(4), 73; https://doi.org/10.3390/mca23040073 - 13 Nov 2018

Viewed by 2365

Abstract

In this work we obtain approximate solutions for Fredholm integral equations of the second kind by means of Petrov–Galerkin method, choosing “regular pairs” of subspaces,

{X_{n}, Y_{n}},

which are simply characterized by the positive definitiveness of a [...] Read more.

In this work we obtain approximate solutions for Fredholm integral equations of the second kind by means of Petrov–Galerkin method, choosing “regular pairs” of subspaces,

{X_{n}, Y_{n}},

which are simply characterized by the positive definitiveness of a correlation matrix. This choice guarantees the solvability and numerical stability of the approximation scheme in an easy way, and the selection of orthogonal basis for the subspaces make the calculations quite simple. Afterwards, we explore an interesting phenomenon called “superconvergence”, observed in the 1970s by Sloan: once the approximations

u_{n} \in X_{n}

to the solution of the operator equation

u - K u = g

are obtained, the convergence can be notably improved by means of an iteration of the method,

u_{n}^{*} = g + K u_{n}

. We illustrate both procedures of approximation by means of two numerical examples: one for a continuous kernel, and the other for a weakly singular one. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd Global Conference on Applied Physics, Mathematics and Computing (APMC-18))

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Figure 1

12 pages, 317 KiB

Open AccessFeature PaperArticle

Green’s Function of the Linearized Logarithmic Keller–Segel–Fisher/KPP System

by Jean Rugamba and Yanni Zeng

Math. Comput. Appl. 2018, 23(4), 56; https://doi.org/10.3390/mca23040056 - 03 Oct 2018

Cited by 3 | Viewed by 2639

Abstract

We consider a Keller–Segel type chemotaxis model with logarithmic sensitivity and logistic growth. The logarithmic singularity in the system is removed via the inverse Hopf–Cole transformation. We then linearize the system around a constant equilibrium state, and obtain a detailed, pointwise description of the Green’s function. The result provides a complete solution picture for the linear problem. It also helps to shed light on small solutions of the nonlinear system. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd Global Conference on Applied Physics, Mathematics and Computing (APMC-18))

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