Mathematical Theory, Methods, and Its Applications for Industry

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 10430

Special Issue Editors


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Guest Editor
National Institute for Mathematical Science, Daejeon, Korea
Interests: drug discovery; computational fluid dynamics such as numerical analysis of the Poisson equation and Navier–Stokes equation; image processing based on mathematics such as image restoration, object recognition, retrieval, tracking, and clustering

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Guest Editor
Department of Mathematics, Pusan National University, Busan 609-735, Korea
Interests: bio/medical mathematics; mathematical modeling; optimal control theory; epidemiology; mathematical analysis

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Guest Editor
Department of Mathematics and Informatics, TU Cluj-Napoca, North University Center, 430122 Baia Mare, Romania
Interests: applied mathematics; soft computing; artificial intelligence; metaheuristics
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Special Issue Information

Dear Colleagues,

Substantial progress made in machine learning and artificial intelligence has led to their extensive applications to various problems in industry, medical science, engineering, and many other areas of research. The bases of these advancements lie in the strength of mathematical and scientific analyses of given phenomena, as well as the capability of mathematics to motivate effective optimal solutions. Industrial mathematics enables such advancements by developing and applying mathematical insights to promote discoveries in science and technology. Establishments of new mathematical theories and flexible applications of mathematical ideas in accordance with real-world problems distinguish industrial mathematics from pure or applied mathematics, which focuses on theoretical pursuits of such insights. The aforementioned remarks demonstrate why industrial mathematics, as a crucial driving force behind the Fourth industrial revolution, has been experiencing its ever-growing importance and effectiveness.

With an increase in successful cases of applications of industrial mathematics, many areas of research have experienced not only the birth of new techniques and novel advances in research but also an increased demand in using industrial mathematics to motivate key insights and establish optimal methods in solving real-world problems.

In light of these achievements, we would like to propose an MDPI Special Issue to promote both advances and extensive applications of mathematics by sharing successful instances where industrial mathematics contributed to solving problems in industry, and by discussing potential problems and technological issues that require further research.

Please note that all submitted papers must be within the general scope of the Symmetry journal.

Prof. Dr. Gangjoon Yoon
Prof. Il Hyo Jung
Dr. Camelia M. Pintea
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Artificial intelligence and manufacturing
  • Mathematical modelling
  • Numerical analysis for industrial mathematics
  • Optimization
  • ODE and PDE for Industrial Mathematics
  • Applied and industrial mathematics
  • Prediction modeling
  • Medical data analysis
  • Machine learning and deep learning
  • Data analytics
  • Infectious disease
  • Pharmacokinetic/pharmacodynamic modeling

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Published Papers (3 papers)

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Research

19 pages, 4435 KiB  
Article
Various Approaches to the Quantitative Evaluation of Biological and Medical Data Using Mathematical Models
by Mária Ždímalová, Anuprava Chatterjee, Helena Kosnáčová, Mridul Ghosh, Sk Md Obaidullah, Martin Kopáni and Daniel Kosnáč
Symmetry 2022, 14(1), 7; https://doi.org/10.3390/sym14010007 - 22 Dec 2021
Cited by 4 | Viewed by 2984
Abstract
Biomedical data (structured and unstructured) has grown dramatically in strength and volume over the last few years. Innovative, intelligent, and autonomous scientific approaches are needed to examine the large data sets that are gradually becoming widely available. In order to predict unique symmetric [...] Read more.
Biomedical data (structured and unstructured) has grown dramatically in strength and volume over the last few years. Innovative, intelligent, and autonomous scientific approaches are needed to examine the large data sets that are gradually becoming widely available. In order to predict unique symmetric and asymmetric patterns, there is also an increasing demand for designing, analyzing, and understanding such complicated data sets. In this paper, we focused on a different way of processing biological and medical data. We provide an overview of known methods as well as a look at optimized mathematical approaches in the field of biological data analysis. We deal with the RGB threshold algorithm, new filtering based on the histogram and on the RGB model, the Image J program, and the structural similarity index method (SSIM) approaches. Finally, we compared the results with the open-source software. We can confirm that our own software based on new mathematical models is an extremely suitable tool for processing biological images and is important in research areas such as the detection of iron in biological samples. We study even symmetric and asymmetric properties of the iron existence as a design analysis of the biological real data. Unique approaches for clinical information gathering, organizing, analysis, information retrieval, and inventive implementation of contemporary computing approaches are all part of this research project, which has much potential in biomedical research. These cutting-edge multidisciplinary techniques will enable the detection and retrieval of important symmetric and asymmetric patterns, as well as the faster finding of pertinent data and the opening of novel learning pathways. Full article
(This article belongs to the Special Issue Mathematical Theory, Methods, and Its Applications for Industry)
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16 pages, 2937 KiB  
Article
A Topology Optimization Method Based on Non-Uniform Rational Basis Spline Hyper-Surfaces for Heat Conduction Problems
by Marco Montemurro and Khalil Refai
Symmetry 2021, 13(5), 888; https://doi.org/10.3390/sym13050888 - 17 May 2021
Cited by 19 | Viewed by 3680
Abstract
This work deals with heat conduction problems formulation in the framework of a CAD-compatible topology optimization method based on a pseudo-density field as a topology descriptor. In particular, the proposed strategy relies, on the one hand, on the use of CAD-compatible Non-Uniform Rational [...] Read more.
This work deals with heat conduction problems formulation in the framework of a CAD-compatible topology optimization method based on a pseudo-density field as a topology descriptor. In particular, the proposed strategy relies, on the one hand, on the use of CAD-compatible Non-Uniform Rational Basis Spline (NURBS) hyper-surfaces to represent the pseudo-density field and, on the other hand, on the well-known Solid Isotropic Material with Penalization (SIMP) approach. The resulting method is then referred to as NURBS-based SIMP method. In this background, heat conduction problems have been reformulated by taking advantage of the properties of the NURBS entities. The influence of the integer parameters, involved in the definition of the NURBS hyper-surface, on the optimized topology is investigated. Furthermore, symmetry constraints, as well as a manufacturing requirement related to the minimum allowable size, are also integrated into the problem formulation without introducing explicit constraint functions, thanks to the NURBS blending functions properties. Finally, since the topological variable is represented by means of a NURBS entity, the geometrical representation of the boundary of the topology is available at each iteration of the optimization process and its reconstruction becomes a straightforward task. The effectiveness of the NURBS-based SIMP method is shown on 2D and 3D benchmark problems taken from the literature. Full article
(This article belongs to the Special Issue Mathematical Theory, Methods, and Its Applications for Industry)
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19 pages, 2804 KiB  
Article
The Inclined Factors of Magnetic Field and Shrinking Sheet in Casson Fluid Flow, Heat and Mass Transfer
by Shahanaz Parvin, Siti Suzilliana Putri Mohamed Isa, Norihan Md Arifin and Fadzilah Md Ali
Symmetry 2021, 13(3), 373; https://doi.org/10.3390/sym13030373 - 25 Feb 2021
Cited by 21 | Viewed by 2368
Abstract
The development of the mathematical modeling of Casson fluid flow and heat and mass transfer is presented in this paper. The model is subjected to the following physical parameters: shrinking parameter, mixed convection, concentration buoyancy ratio parameter, Soret number, and Dufour number. This [...] Read more.
The development of the mathematical modeling of Casson fluid flow and heat and mass transfer is presented in this paper. The model is subjected to the following physical parameters: shrinking parameter, mixed convection, concentration buoyancy ratio parameter, Soret number, and Dufour number. This model is also subjected to the inclined magnetic field and shrinking sheet at a certain angle projected from the y- and x-axes, respectively. The MATLAB bvp4c program is the main mathematical program that was used to obtain the final numerical solutions for the reduced ordinary differential equations (ODEs). These ODEs originate from the governing partial differential equations (PDEs), where the transformation can be achieved by applying similarity transformations. The MATLAB bvp4c program was also implemented to develop stability analysis, where this calculation was executed to recognize the most stable numerical solution. Numerical graphics were made for the skin friction coefficient, local Nusselt number, local Sherwood number, velocity profile, temperature profile, and concentration profile for certain values of the physical parameters. It is found that all the governed parameters affected the variations of the Casson fluid flow, heat transfer, mass transfer, and the profiles of velocity, temperature, and concentration. In addition, a stable solution can be applied to predict the impact of physical parameters on the actual fluid model by using a mathematical fluid model. Full article
(This article belongs to the Special Issue Mathematical Theory, Methods, and Its Applications for Industry)
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