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Computation, Volume 9, Issue 5 (May 2021) – 12 articles

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21 pages, 490 KiB  
Article
Optimization Algorithm to Sequence the Management Processes in Information Technology Departments
by Juan Luis Rubio Sánchez
Computation 2021, 9(5), 60; https://doi.org/10.3390/computation9050060 - 19 May 2021
Cited by 2 | Viewed by 2687
Abstract
The most important standard in technology services management is the Information Technology Infrastructure Library (ITIL). The literature review developed shows that one of the most important questions to answer is finding the sequence of processes to be implemented, mainly in small companies with [...] Read more.
The most important standard in technology services management is the Information Technology Infrastructure Library (ITIL). The literature review developed shows that one of the most important questions to answer is finding the sequence of processes to be implemented, mainly in small companies with few resources. The purpose of this paper is to show a methodology that defines an optimal specific sequence of processes for each small company depending on internal and external parameters. The main contribution of this paper is a proven methodology to obtain a particular sequence of ITIL processes specifically adapted to each company, based on a mathematical and statistical model that uses data from a web survey. Its application generates an optimal sequence of ITIL processes. The methodology has been applied with successful results in a real case, and it shows specific benefits over the previous approaches. The main learning objective of this research is a proven method to obtain an optimal sequence of processes for the implementation of ITIL in small companies. Finally, some future works are presented. Full article
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15 pages, 524 KiB  
Article
Multi-Model Approach and Fuzzy Clustering for Mammogram Tumor to Improve Accuracy
by Sarada Ghosh, Guruprasad Samanta and Manuel De la Sen
Computation 2021, 9(5), 59; https://doi.org/10.3390/computation9050059 - 18 May 2021
Cited by 3 | Viewed by 2761
Abstract
Breast Cancer is one of the most common diseases among women which seriously affect health and threat to life. Presently, mammography is an uttermost important criterion for diagnosing breast cancer. In this work, image of breast cancer mass detection in mammograms with [...] Read more.
Breast Cancer is one of the most common diseases among women which seriously affect health and threat to life. Presently, mammography is an uttermost important criterion for diagnosing breast cancer. In this work, image of breast cancer mass detection in mammograms with 1024×1024 pixels is used as dataset. This work investigates the performance of various approaches on classification techniques. Overall support vector machine (SVM) performs better in terms of log-loss and classification accuracy rate than other underlying models. Therefore, further extensions (i.e., multi-model ensembles method, Fuzzy c-means (FCM) clustering and SVM combination method, and FCM clustering based SVM model) and comparison with SVM have been performed in this work. The segmentation by FCM clustering technique allows one piece of data to belong in two or more clusters. The additional parts are due to the segmented image to enhance the tumor-shape. Simulation provides the accuracy and the area under the ROC curve for mini-MIAS are 91.39% and 0.964 respectively which give the confirmation of the effectiveness of the proposed algorithm (FCM-based SVM). This method increases the classification accuracy in the case of a malignant tumor. The simulation is based on R-software. Full article
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12 pages, 3302 KiB  
Article
Synthesis, Mass Spectroscopy Detection, and Density Functional Theory Investigations of the Gd Endohedral Complexes of C82 Fullerenols
by Anastasia A. Shakirova, Felix N. Tomilin, Vladimir A. Pomogaev, Natalia G. Vnukova, Grigory N. Churilov, Nadezhda S. Kudryasheva, Olga N. Tchaikovskaya, Sergey G. Ovchinnikov and Pavel V. Avramov
Computation 2021, 9(5), 58; https://doi.org/10.3390/computation9050058 - 17 May 2021
Cited by 9 | Viewed by 3437
Abstract
Gd endohedral complexes of C82 fullerenols were synthesized and mass spectrometry analysis of their composition was carried out. It was established that the synthesis yields a series of fullerenols Gd@C82Ox(OH)y (x = 0, 3; y = [...] Read more.
Gd endohedral complexes of C82 fullerenols were synthesized and mass spectrometry analysis of their composition was carried out. It was established that the synthesis yields a series of fullerenols Gd@C82Ox(OH)y (x = 0, 3; y = 8, 16, 24, 36, 44). The atomic and electronic structure and properties of the synthesized fullerenols were investigated using the density functional theory calculations. It was shown that the presence of endohedral gadolinium increases the reactivity of fullerenols. It is proposed that the high-spin endohedral fullerenols are promising candidates for application in magnetic resonance imaging. Full article
(This article belongs to the Section Computational Chemistry)
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24 pages, 3995 KiB  
Article
RuSseL: A Self-Consistent Field Theory Code for Inhomogeneous Polymer Interphases
by Constantinos J. Revelas, Aristotelis P. Sgouros, Apostolos T. Lakkas and Doros N. Theodorou
Computation 2021, 9(5), 57; https://doi.org/10.3390/computation9050057 - 10 May 2021
Cited by 3 | Viewed by 3348
Abstract
In this article, we publish the one-dimensional version of our in-house code, RuSseL, which has been developed to address polymeric interfaces through Self-Consistent Field calculations. RuSseL can be used for a wide variety of systems in planar and spherical geometries, such as free [...] Read more.
In this article, we publish the one-dimensional version of our in-house code, RuSseL, which has been developed to address polymeric interfaces through Self-Consistent Field calculations. RuSseL can be used for a wide variety of systems in planar and spherical geometries, such as free films, cavities, adsorbed polymer films, polymer-grafted surfaces, and nanoparticles in melt and vacuum phases. The code includes a wide variety of functional potentials for the description of solid–polymer interactions, allowing the user to tune the density profiles and the degree of wetting by the polymer melt. Based on the solution of the Edwards diffusion equation, the equilibrium structural properties and thermodynamics of polymer melts in contact with solid or gas surfaces can be described. We have extended the formulation of Schmid to investigate systems comprising polymer chains, which are chemically grafted on the solid surfaces. We present important details concerning the iterative scheme required to equilibrate the self-consistent field and provide a thorough description of the code. This article will serve as a technical reference for our works addressing one-dimensional polymer interphases with Self-Consistent Field theory. It has been prepared as a guide to anyone who wishes to reproduce our calculations. To this end, we discuss the current possibilities of the code, its performance, and some thoughts for future extensions. Full article
(This article belongs to the Section Computational Chemistry)
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11 pages, 692 KiB  
Article
Application of a Deep Neural Network to Phase Retrieval in Inverse Medium Scattering Problems
by Soojong Lim and Jaemin Shin
Computation 2021, 9(5), 56; https://doi.org/10.3390/computation9050056 - 28 Apr 2021
Cited by 2 | Viewed by 2765
Abstract
We address the inverse medium scattering problem with phaseless data motivated by nondestructive testing for optical fibers. As the phase information of the data is unknown, this problem may be regarded as a standard phase retrieval problem that consists of identifying the phase [...] Read more.
We address the inverse medium scattering problem with phaseless data motivated by nondestructive testing for optical fibers. As the phase information of the data is unknown, this problem may be regarded as a standard phase retrieval problem that consists of identifying the phase from the amplitude of data and the structure of the related operator. This problem has been studied intensively due to its wide applications in physics and engineering. However, the uniqueness of the inverse problem with phaseless data is still open and the problem itself is severely ill-posed. In this work, we construct a model to approximate the solution operator in finite-dimensional spaces by a deep neural network assuming that the refractive index is radially symmetric. We are then able to recover the refractive index from the phaseless data. Numerical experiments are presented to illustrate the effectiveness of the proposed model. Full article
(This article belongs to the Section Computational Engineering)
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25 pages, 1420 KiB  
Article
Stabilization of the Computation of Stability Constants and Species Distributions from Titration Curves
by Stephan Daniel Schwoebel, Dominik Höhlich, Thomas Mehner and Thomas Lampke
Computation 2021, 9(5), 55; https://doi.org/10.3390/computation9050055 - 27 Apr 2021
Cited by 3 | Viewed by 3252
Abstract
Thermodynamic equilibria and concentrations in thermodynamic equilibria are of major importance in chemistry, chemical engineering, physical chemistry, medicine etc. due to a vast spectrum of applications. E.g., concentrations in thermodynamic equilibria play a central role for the estimation of drug delivery, the estimation [...] Read more.
Thermodynamic equilibria and concentrations in thermodynamic equilibria are of major importance in chemistry, chemical engineering, physical chemistry, medicine etc. due to a vast spectrum of applications. E.g., concentrations in thermodynamic equilibria play a central role for the estimation of drug delivery, the estimation of produced mass of products of chemical reactions, the estimation of deposited metal during electro plating and many more. Species concentrations in thermodynamic equilibrium are determined by the system of reactions and to the reactions’ associated stability constants. In many applications the stability constants and the system of reactions need to be determined. The usual way to determine the stability constants is to evaluate titration curves. In this context, many numerical methods exist. One major task in this context is that the corresponding inverse problems tend to be unstable, i.e., the output is strongly affected by measurement errors, and can output negative stability constants or negative species concentrations. In this work an alternative model for the species distributions in thermodynamic equilibrium, based on the models used for HySS or Hyperquad, and titration curves is presented, which includes the positivity of species concentrations and stability constants intrinsically. Additionally, in this paper a stabilized numerical methodology is presented to treat the corresponding model guaranteeing the convergence of the algorithm. The numerical scheme is validated with clinical numerical examples and the model is validated with a Citric acid–Nickel electrolyte. This paper finds a stable, convergent and efficient methodology to compute stability constants from potentiometric titration curves. Full article
(This article belongs to the Section Computational Chemistry)
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21 pages, 4854 KiB  
Article
Integrated Multi-Model Face Shape and Eye Attributes Identification for Hair Style and Eyelashes Recommendation
by Theiab Alzahrani, Waleed Al-Nuaimy and Baidaa Al-Bander
Computation 2021, 9(5), 54; https://doi.org/10.3390/computation9050054 - 27 Apr 2021
Cited by 10 | Viewed by 11355
Abstract
Identifying human face shape and eye attributes is the first and most vital process before applying for the right hairstyle and eyelashes extension. The aim of this research work includes the development of a decision support program to constitute an aid system that [...] Read more.
Identifying human face shape and eye attributes is the first and most vital process before applying for the right hairstyle and eyelashes extension. The aim of this research work includes the development of a decision support program to constitute an aid system that analyses eye and face features automatically based on the image taken from a user. The system suggests a suitable recommendation of eyelashes type and hairstyle based on the automatic reported users’ eye and face features. To achieve the aim, we develop a multi-model system comprising three separate models; each model targeted a different task, including; face shape classification, eye attribute identification and gender detection model. Face shape classification system has been designed based on the development of a hybrid framework of handcrafting and learned feature. Eye attributes have been identified by exploiting the geometrical eye measurements using the detected eye landmarks. Gender identification system has been realised and designed by implementing a deep learning-based approach. The outputs of three developed models are merged to design a decision support system for haircut and eyelash extension recommendation. The obtained detection results demonstrate that the proposed method effectively identifies the face shape and eye attributes. Developing such computer-aided systems is suitable and beneficial for the user and would be beneficial to the beauty industrial. Full article
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11 pages, 460 KiB  
Article
Potential Water Recovery from Biomass Boilers: Parametric Analysis
by Daniele Dondi, Cristina D. López Robles, Anna Magrini and Marco Cartesegna
Computation 2021, 9(5), 53; https://doi.org/10.3390/computation9050053 - 27 Apr 2021
Cited by 2 | Viewed by 2464
Abstract
A fundamental component of the losses of convection boilers is localized in the warm fumes that are expelled. In the warm fumes, not only energy is lost, but water is also formed from the combustion reaction in the form of steam which is [...] Read more.
A fundamental component of the losses of convection boilers is localized in the warm fumes that are expelled. In the warm fumes, not only energy is lost, but water is also formed from the combustion reaction in the form of steam which is expelled through the exhaust. Modern fuel boilers recover both the heat from the fumes and the latent heat of condensation from water vapor. Depending on the chemical composition of the fuel, different amounts of steam are produced together with heat and different combustion conditions, such as air in excess. In this article, a computational tool was established to simulate a combustion system mainly (but not only) focusing on the prediction of the amount of water produced. In fact, while steam in fossil fuel boilers is commonly condensed, this is not so when the fuel is a biomass. Furthermore, biomasses could contain moisture in different amounts, thus affecting the production of water and the heat of combustion. The study shows that a ten-fold amount of water is formed from biomass combustion with respect to fossil fuels (when the same energy output is produced). As a result, the recovery of water is amenable in biomasses, both from the energetic point of view and for liquid water production. In fact, the water recovered from the fumes might be also reused in other processes such as the cleaning of fumes or agriculture (after treatment). Full article
(This article belongs to the Special Issue Computational Insights into Industrial Chemistry)
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19 pages, 2129 KiB  
Article
Application of the Exp-Function and Generalized Kudryashov Methods for Obtaining New Exact Solutions of Certain Nonlinear Conformable Time Partial Integro-Differential Equations
by Supaporn Kaewta, Sekson Sirisubtawee and Surattana Sungnul
Computation 2021, 9(5), 52; https://doi.org/10.3390/computation9050052 - 26 Apr 2021
Cited by 18 | Viewed by 3336
Abstract
The key objective of this paper is to construct exact traveling wave solutions of the conformable time second integro-differential Kadomtsev–Petviashvili (KP) hierarchy equation using the Exp-function method and the (2 + 1)-dimensional conformable time partial integro-differential Jaulent–Miodek (JM) evolution equation utilizing the generalized [...] Read more.
The key objective of this paper is to construct exact traveling wave solutions of the conformable time second integro-differential Kadomtsev–Petviashvili (KP) hierarchy equation using the Exp-function method and the (2 + 1)-dimensional conformable time partial integro-differential Jaulent–Miodek (JM) evolution equation utilizing the generalized Kudryashov method. These two problems involve the conformable partial derivative with respect to time. Initially, the conformable time partial integro-differential equations can be converted into nonlinear ordinary differential equations via a fractional complex transformation. The resulting equations are then analytically solved via the corresponding methods. As a result, the explicit exact solutions for these two equations can be expressed in terms of exponential functions. Setting some specific parameter values and varying values of the fractional order in the equations, their 3D, 2D, and contour solutions are graphically shown and physically characterized as, for instance, a bell-shaped solitary wave solution, a kink-type solution, and a singular multiple-soliton solution. To the best of the authors’ knowledge, the results of the equations obtained using the proposed methods are novel and reported here for the first time. The methods are simple, very powerful, and reliable for solving other nonlinear conformable time partial integro-differential equations arising in many applications. Full article
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14 pages, 3565 KiB  
Article
DrainCAN—A MATLAB Function for Generation of a HEC-RAS-Compatible Drainage Canal Network Model
by Gordon Gilja, Antonija Harasti and Robert Fliszar
Computation 2021, 9(5), 51; https://doi.org/10.3390/computation9050051 - 23 Apr 2021
Viewed by 3462
Abstract
The dimensioning of canal geometry in a surface drainage network influences the size and functionality of canal structures, reduces flood hazard, and consequently imposes restrictions on land use. Reliable free-surface flow calculation for optimization of the canal network can be challenging because numerous [...] Read more.
The dimensioning of canal geometry in a surface drainage network influences the size and functionality of canal structures, reduces flood hazard, and consequently imposes restrictions on land use. Reliable free-surface flow calculation for optimization of the canal network can be challenging because numerous hydraulic structures and canal interactions influence the flow regime. The HEC-RAS software of the US Army Corps of Engineers’ Hydrologic Engineering Center is often used for this purpose as it allows the user to simulate the effect of numerous hydraulic structures on flow regime. This paper presents a MATLAB function, DrainCAN, for generating a HEC-RAS model from standard runoff input data, i.e., topographic data and canal design geometry (profile and slope). The DrainCAN function allows for fast optimization of the network geometry—it generates normal flow depth estimation and observed water levels in critical locations that need to be optimized. Advantages of the DrainCAN function are fast generation of the HEC-RAS hydraulic model files from simple input files, introduction of optimization variables in the model, and automatic adjustment of model geometry for computational junctions. This allows fast iteration of the canal design parameters, namely cross-sectional geometry, invert elevation, and longitudinal slope, and the evaluation of introduced changes on the flow regime. Full article
(This article belongs to the Section Computational Engineering)
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12 pages, 3041 KiB  
Article
Numerical Investigation of a Thermal Ablation Porous Media-Based Model for Tumoral Tissue with Variable Porosity
by Assunta Andreozzi, Luca Brunese, Marcello Iasiello, Claudio Tucci and Giuseppe Peter Vanoli
Computation 2021, 9(5), 50; https://doi.org/10.3390/computation9050050 - 23 Apr 2021
Cited by 6 | Viewed by 2377
Abstract
Thermal ablation is a minimally or noninvasive cancer therapy technique that involves fewer complications, shorter hospital stays, and fewer costs. In this paper, a thermal-ablation bioheat model for cancer treatment is numerically investigated, using a porous media-based model. The main objective is to [...] Read more.
Thermal ablation is a minimally or noninvasive cancer therapy technique that involves fewer complications, shorter hospital stays, and fewer costs. In this paper, a thermal-ablation bioheat model for cancer treatment is numerically investigated, using a porous media-based model. The main objective is to evaluate the effects of a variable blood volume fraction in the tumoral tissue (i.e., the porosity), in order to develop a more realistic model. A modified local thermal nonequilibrium model (LTNE) is implemented including the water content vaporization in the two phases separately and introducing the variable porosity in the domain, described by a quadratic function changing from the core to the rim of the tumoral sphere. The equations are numerically solved employing the finite-element commercial code COMSOL Multiphysics. Results are compared with the results obtained employing two uniform porosity values (ε = 0.07 and ε = 0.23) in terms of coagulation zones at the end of the heating period, maximum temperatures reached in the domain, and temperature fields and they are presented for different blood vessels. The outcomes highlight how important is to predict coagulation zones achieved in thermal ablation accurately. In this way, indeed, incomplete ablation, tumor recurrence, or healthy tissue necrosis can be avoided, and medical protocols and devices can be improved. Full article
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15 pages, 491 KiB  
Article
Exact Reduction of the Generalized Lotka–Volterra Equations via Integral and Algebraic Substitutions
by Rebecca E. Morrison
Computation 2021, 9(5), 49; https://doi.org/10.3390/computation9050049 - 22 Apr 2021
Cited by 1 | Viewed by 2650
Abstract
Systems of interacting species, such as biological environments or chemical reactions, are often described mathematically by sets of coupled ordinary differential equations. While a large number β of species may be involved in the coupled dynamics, often only α<β species are [...] Read more.
Systems of interacting species, such as biological environments or chemical reactions, are often described mathematically by sets of coupled ordinary differential equations. While a large number β of species may be involved in the coupled dynamics, often only α<β species are of interest or of consequence. In this paper, we explored how to construct models that include only those given α species, but still recreate the dynamics of the original β-species model. Under some conditions detailed here, this reduction can be completed exactly, such that the information in the reduced model is exactly the same as the original one, but over fewer equations. Moreover, this reduction process suggests a promising type of approximate model—no longer exact, but computationally quite simple. Full article
(This article belongs to the Section Computational Biology)
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