Computation

15 pages, 10966 KiB

Open AccessArticle

Multimodal Biometrics Recognition Using a Deep Convolutional Neural Network with Transfer Learning in Surveillance Videos

by Hsu Mon Lei Aung, Charnchai Pluempitiwiriyawej, Kazuhiko Hamamoto and Somkiat Wangsiripitak

Computation 2022, 10(7), 127; https://doi.org/10.3390/computation10070127 - 21 Jul 2022

Cited by 7 | Viewed by 2463

Abstract

Biometric recognition is a critical task in security control systems. Although the face has long been widely accepted as a practical biometric for human recognition, it can be easily stolen and imitated. Moreover, in video surveillance, it is a challenge to obtain reliable [...] Read more.

Biometric recognition is a critical task in security control systems. Although the face has long been widely accepted as a practical biometric for human recognition, it can be easily stolen and imitated. Moreover, in video surveillance, it is a challenge to obtain reliable facial information from an image taken at a long distance with a low-resolution camera. Gait, on the other hand, has been recently used for human recognition because gait is not easy to replicate, and reliable information can be obtained from a low-resolution camera at a long distance. However, the gait biometric alone still has constraints due to its intrinsic factors. In this paper, we propose a multimodal biometrics system by combining information from both the face and gait. Our proposed system uses a deep convolutional neural network with transfer learning. Our proposed network model learns discriminative spatiotemporal features from gait and facial features from face images. The two extracted features are fused into a common feature space at the feature level. This study conducted experiments on the publicly available CASIA-B gait and Extended Yale-B databases and a dataset of walking videos of 25 users. The proposed model achieves a 97.3 percent classification accuracy with an F1 score of 0.97and an equal error rate (EER) of 0.004. Full article

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32 pages, 4051 KiB

Open AccessArticle

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

by Rapeepan Pitakaso, Natthapong Nanthasamroeng, Thanatkij Srichok, Surajet Khonjun, Nantawatana Weerayuth, Thachada Kotmongkol, Peema Pornprasert and Kiatisak Pranet

Computation 2022, 10(7), 126; https://doi.org/10.3390/computation10070126 - 20 Jul 2022

Cited by 16 | Viewed by 3101

Abstract

In recent years, agriculture products have contributed to 28.75% of Thailand’s GDP. China, Vietnam, Myanmar, Cambodia, Laos and Vietnam are the main markets for agricultural products. The annual export volume exceeds 119,222 million THB. The majority of them are shipped over Thailand’s land [...] Read more.

In recent years, agriculture products have contributed to 28.75% of Thailand’s GDP. China, Vietnam, Myanmar, Cambodia, Laos and Vietnam are the main markets for agricultural products. The annual export volume exceeds 119,222 million THB. The majority of them are shipped over Thailand’s land borders to its neighbors. Small and medium-sized farmers make up more than 85% of those who produce agricultural items. Numerous scholars have studied the transportation methods used by the Greater Mekong Subregion (GMS) nations along the economic corridor, but the majority of them have concentrated on import–export operations involving sizable firms, which are not applicable to the transportation of agricultural products, particularly when attention is paid to small and medium-sized farmers. In this study, mixed-integer programming (MIP) is presented to design an agricultural product logistics network. In order to prolong the lifespan of the container used, the MIP’s primary goal is to maximize the total chain profit while maintaining the lowest container usage possible. The approach was developed to increase small and medium-sized farmers’ ability to compete. Small and medium-sized farmers bring their products to an agricultural product collecting center, also known as a container loading facility. After that, skilled logistics companies distribute the goods. In order to convey the goods to the final clients in neighboring nations, the proper locations of the containing loading centers, the correct transportation option and the borders must be decided. The issue was identified as multi-echelon location–allocation sizing (MELLS), an NP-hard problem that cannot be handled in an efficient manner. To solve a real-world problem, however, efficient techniques must be supplied. AMIS, an artificial multiple intelligence system, was created to address the suggested issue. AMIS was developed with the goal of leveraging a variety of methods for local search and development. There are several well-known heuristics techniques employed in the literature, including the genetic algorithm (GA) and the differential evolution algorithm (DE). With respect to the improved solutions obtained, the computational results show that AMIS exceeds the present heuristics, outperforming DE and GA by 9.34% and 10.95%, respectively. Additionally, the system’s farmers made a total of 15,236,832 THB in profit, with an average profit per container of 317,434 THB and an average profit per farmer of 92,344.44 THB per crop. The container loading center uses 48 containers, with a 5.33 container average per container loading center (CLC). The farmers’ annual revenues were previously less than 88,402 THB per family per year, so we can predict that the new network may increase customers’ annual income by 4.459% for each crop. Full article

(This article belongs to the Special Issue Transport and Logistics Optimization Solution)

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20 pages, 647 KiB

Open AccessArticle

Sliding-Mode Control of Bidirectional Flyback Converters with Bus Voltage Regulation for Battery Interface

by Carlos Andres Ramos-Paja, Juan David Bastidas-Rodriguez and Luz Adriana Trejos-Grisales

Computation 2022, 10(7), 125; https://doi.org/10.3390/computation10070125 - 20 Jul 2022

Cited by 2 | Viewed by 1584

Abstract

Energy storage systems are essential for multiple applications like renewable energy systems, electric vehicles, microgrids, among others. Those systems are responsible of regulating the dc bus voltage using charging-discharging systems which are mainly formed by a power converter and a control system. This [...] Read more.

Energy storage systems are essential for multiple applications like renewable energy systems, electric vehicles, microgrids, among others. Those systems are responsible of regulating the dc bus voltage using charging-discharging systems which are mainly formed by a power converter and a control system. This work focuses on the control system of a flyback converter. A detailed design procedure of an adaptive sliding-mode controller (SMC) and its parameters is presented. The proposed procedure was validated through simulations which allow to confirm its good performance in terms of global stability providing the desired dynamic of the dc bus voltage regulation. Full article

(This article belongs to the Special Issue Intelligent Computing, Modeling and its Applications)

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17 pages, 582 KiB

Open AccessArticle

Snake Graphs Arising from Groves with an Application in Coding Theory

by Agustín Moreno Cañadas, Gabriel Bravo Rios and Robinson-Julian Serna

Computation 2022, 10(7), 124; https://doi.org/10.3390/computation10070124 - 19 Jul 2022

Cited by 4 | Viewed by 1614

Abstract

Snake graphs are connected planar graphs consisting of a finite sequence of adjacent tiles (squares)

T_{1}, T_{2}, \dots, T_{n}

. In this case, for

1 \leq j \leq n - 1

, two consecutive tiles

T_{j}

[...] Read more.

Snake graphs are connected planar graphs consisting of a finite sequence of adjacent tiles (squares)

T_{1}, T_{2}, \dots, T_{n}

. In this case, for

1 \leq j \leq n - 1

, two consecutive tiles

T_{j}

and

T_{j + 1}

share exactly one edge, either the edge at the east (west) of

T_{j}

(

T_{j + 1}

) or the edge at the north (south) of

T_{j}

(

T_{j + 1}

). Finding the number of perfect matchings associated with a given snake graph is one of the most remarkable problems regarding these graphs. It is worth noting that such a number of perfect matchings allows a bijection between the set of snake graphs and the positive continued fractions. Furthermore, perfect matchings of snake graphs have also been used to find closed formulas for cluster variables of some cluster algebras and solutions of the Markov equation, which is a well-known Diophantine equation. Recent results prove that snake graphs give rise to some string modules over some path algebras, connecting snake graph research with the theory of representation of algebras. This paper uses this interaction to define Brauer configuration algebras induced by schemes associated with some multisets called polygons. Such schemes are named Brauer configurations. In this work, polygons are given by some admissible words, which, after appropriate transformations, permit us to define sets of binary trees called groves. Admissible words generate codes whose energy values are given by snake graphs. Such energy values can be estimated by using Catalan numbers. We include in this paper Python routines to compute admissible words (i.e., codewords), energy values of the generated codes, Catalan numbers and dimensions of the obtained Brauer configuration algebras. Full article

(This article belongs to the Special Issue Graph Theory and Its Applications in Computing)

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17 pages, 3616 KiB

Open AccessArticle

Complete Integrated Automation of the Electrochemical Corrosion Protection System of Pipelines Based on IoT and Big Data Analytics

by Oleksandr Prokhorov, Valeriy Prokhorov, Alisher Khussanov, Zhakhongir Khussanov, Botagoz Kaldybayeva and Dilfuza Turdybekova

Computation 2022, 10(7), 123; https://doi.org/10.3390/computation10070123 - 18 Jul 2022

Cited by 3 | Viewed by 1859

Abstract

This article is devoted to the issues of creating an adaptive intelligent system, for monitoring and controlling the technological process for electrochemical corrosion protection of main pipelines (MP), which has been designed for remote control of electrochemical protection (EChP) parameters and their optimization [...] Read more.

This article is devoted to the issues of creating an adaptive intelligent system, for monitoring and controlling the technological process for electrochemical corrosion protection of main pipelines (MP), which has been designed for remote control of electrochemical protection (EChP) parameters and their optimization as well as adaptive control of the parameters of cathodic protection stations while taking into account changes in external conditions. The multi-objective problem of optimizing the operating modes of cathodic protection stations (CPS) is considered because optimization is carried out according to both the criterion of optimal distribution of the protective potential (uniform distribution of the protective total (pipe-to-soil) potential along the length of the pipeline) and to the criterion of the minimum total protective current of stations. The structure of the distributed electrochemical protection system is described in the article. A more complete picture of the protection of the pipeline and solving the problems of optimizing the electrochemical protection modes in real time is possible due to remote monitoring of control and measuring points (CMP) in the middle of the pipeline between neighboring cathodic protection stations, as well as in all corrosion and hazardous zones where they are also installed. In addition to the often-used GSM/GPRS networks in electrochemical protection systems, an energy-efficient LPWAN (Low-Power Wide-Area Network) data transmission network is also used and data collection is carried out using a cloud IoT platform. The functionality of the system is described, web application screens are shown in various operating modes for remote monitoring and control of the protective parameters of cathodic protection stations is reported. Analytical data processing for the tasks assessing the protection of objects in the pipeline system against corrosion are also shown. The system ensures that the electrochemical protection process is maintained at an optimal level between the destructive zones of “underprotection” and “overprotection”, taking into account monitoring data, geological conditions at the pipeline site, climatic or seasonal changes and other factors. In general, this system provides an increase in the reliability of the electrochemical protection system as a whole and, accordingly, it prevents possible emergency situations on the pipeline system while also reducing the cost of pipeline maintenance due to the reliability and continuity of protection. Full article

(This article belongs to the Section Computational Engineering)

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12 pages, 1444 KiB

Open AccessProject Report

Analysis of Liquid Quantity Measurement in Loading/Unloading Processes in Cylindrical Tanks

by Asta Meškuotienė, Paulius Kaškonas, Benas Gabrielis Urbonavičius, Gintautas Balčiūnas and Justina Dobilienė

Computation 2022, 10(7), 122; https://doi.org/10.3390/computation10070122 - 15 Jul 2022

Cited by 1 | Viewed by 1450

Abstract

Tanks, as instruments in oil and its product’s amount measurement system chain, must be regularly maintained and metrologically inspected, as they significantly contribute to measurement uncertainty. However, when measuring a change in the amount of stored material (i.e., transfer), the measurement uncertainty becomes [...] Read more.

Tanks, as instruments in oil and its product’s amount measurement system chain, must be regularly maintained and metrologically inspected, as they significantly contribute to measurement uncertainty. However, when measuring a change in the amount of stored material (i.e., transfer), the measurement uncertainty becomes highly dependent not only on the mass of the transaction but also on the initial liquid level in the tank. This paper provides modeling of the uncertainties of the measuring system, which involves tanks, oil, and its product loading/unloading processes. It is shown that the accuracy of volume/mass measurement depends not only on the tank calibration table but also on the accuracy of other measuring instruments used and on the level of the liquid at the moment of measurement. The relative uncertainty of the measurement of the change in product mass depends linearly on the tank fill level present at the time of the transaction but nonlinearly on the transaction mass quantity. Full article

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17 pages, 4692 KiB

Open AccessArticle

Contactless Material Tensile Testing Using a High-Resolution Camera

by Jaroslav Bulava, Libor Hargaš and Dušan Koniar

Computation 2022, 10(7), 121; https://doi.org/10.3390/computation10070121 - 15 Jul 2022

Viewed by 2002

Abstract

This article deals with the use of contactless measurement with a high-resolution imaging device during tensile testing of materials in a universal tearing machine (UTM). Setting the material parameters in tensile testing is based on changes in the geometrical properties of the sample [...] Read more.

This article deals with the use of contactless measurement with a high-resolution imaging device during tensile testing of materials in a universal tearing machine (UTM). Setting the material parameters in tensile testing is based on changes in the geometrical properties of the sample being tested. In this article, authors propose the method and system for automated measuring the height, width, and crack occurrence during tensile testing. The system is also able to predict the location of crack occurrence. The proposed method is based on selected algorithms of image analysis, feature extraction, and template matching. Our video extensometry, working with common inspection cameras operating in visible range, can be an alternative method to expensive laser extensometry machines. The motivation of our work was to develop an automated measurement system for use in a UTM. Full article

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15 pages, 2209 KiB

Open AccessArticle

Mathematical Modeling: Global Stability Analysis of Super Spreading Transmission of Respiratory Syncytial Virus (RSV) Disease

by Rattiya Sungchasit, I-Ming Tang and Puntani Pongsumpun

Computation 2022, 10(7), 120; https://doi.org/10.3390/computation10070120 - 12 Jul 2022

Cited by 2 | Viewed by 1618

Abstract

In this paper, a model for the transmission of respiratory syncytial virus (RSV) in a constant human population in which there exist super spreading infected individuals (who infect many people during a single encounter) is considered. It has been observed in the epidemiological [...] Read more.

In this paper, a model for the transmission of respiratory syncytial virus (RSV) in a constant human population in which there exist super spreading infected individuals (who infect many people during a single encounter) is considered. It has been observed in the epidemiological data for the diseases caused by this virus that there are cases where some individuals are super-spreaders of the virus. We formulate a simply SEI_rI_sR (susceptible–exposed–regular infected–super-spreading infected–recovered) mathematical model to describe the dynamics of the transmission of this disease. The proposed model is analyzed using the standard stability method by using Routh-Hurwitz criteria. We obtain the basic reproductive number (

R_{0}

) using the next generation method. We establish that when

R_{0} < 1

, the disease-free state is locally asymptotically stable and the disease endemic state is unstable. The reverse is true when

R_{0} > 1

, the disease endemic state becomes the locally asymptotically stable state and the disease-free state becomes unstable. It is also established that the two equilibrium states are globally asymptotically stable. The numerical simulations show how the dynamics of the disease change as values of the parameters in the SEI_rI_sR are varied. Full article

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15 pages, 2857 KiB

Open AccessArticle

Mathematical Models and Nonlinear Optimization in Continuous Maximum Coverage Location Problem

by Sergiy Yakovlev, Oleksii Kartashov and Dmytro Podzeha

Computation 2022, 10(7), 119; https://doi.org/10.3390/computation10070119 - 11 Jul 2022

Cited by 5 | Viewed by 1814

Abstract

This paper considers the maximum coverage location problem (MCLP) in a continuous formulation. It is assumed that the coverage domain and the family of geometric objects of arbitrary shape are specified. It is necessary to find such a location of geometric objects to [...] Read more.

This paper considers the maximum coverage location problem (MCLP) in a continuous formulation. It is assumed that the coverage domain and the family of geometric objects of arbitrary shape are specified. It is necessary to find such a location of geometric objects to cover the greatest possible amount of the domain. A mathematical model of MCLP is proposed in the form of an unconstrained nonlinear optimization problem. Python computational geometry packages were used to calculate the area of partial coverage domain. Many experiments were carried out which made it possible to describe the statistical dependence of the area calculation time of coverage domain on the number of covering objects. To obtain a local solution, the BFGS method with first-order differences was used. An approach to the numerical estimation of the objective function gradient is proposed, which significantly reduces computational costs, which is confirmed experimentally. The proposed approach is shown to solve the maximum coverage problem of a rectangular area by a family of ellipses. Full article

(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)

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19 pages, 1561 KiB

Open AccessArticle

Concept of High-Tech Enterprise Development Management in the Context of Digital Transformation

by Yurii Pronchakov, Oleksandr Prokhorov and Oleg Fedorovich

Computation 2022, 10(7), 118; https://doi.org/10.3390/computation10070118 - 10 Jul 2022

Cited by 4 | Viewed by 3064

Abstract

The purpose of this article is to check and identify management gaps that lead to the formation of digitalization problems in enterprises in the context of Industry 4.0 and to offer a conceptual approach to managing the development of high-tech enterprises in digital [...] Read more.

The purpose of this article is to check and identify management gaps that lead to the formation of digitalization problems in enterprises in the context of Industry 4.0 and to offer a conceptual approach to managing the development of high-tech enterprises in digital transformation. The paper substantiates the concept of digital transformation management in a high-tech enterprise based on interdependent adaptive systems for planning digital transformation processes, monitoring, and change management. The paper considers the idea of the Industry 4.0 concept and presents principal technologies and tools that contribute to the gradual transition to digital transformation. It is determined that digital transformation is a process of transition to digital business, which involves the use of digital technologies to change business processes in the company and provision of new opportunities for additional income and development prospects. A conceptual model of enterprise competitiveness formation in the process of digital transformation has been developed, which includes organizational and economical digital tools for sustainable development of high-tech enterprises and synergies from the organization of new forms of digital interaction. The proposed methodology for managing the development of high-tech enterprises in the context of digital transformation is based on the formation of an ecosystem model of decentralization in a single distributed digital space, based on interconnected adaptive systems of planning, monitoring, and change management, and, on the basis of modeling and forecasting of complex manufacturing and logistics processes of high-tech industries, it allows effective implementation of the innovative order portfolio in the short term and with limited opportunities while coordinating the priorities of the business strategy and strategy of digital transformation of high-tech enterprises. Full article

(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)

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32 pages, 10458 KiB

Open AccessArticle

Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates

by Olugbenga Oluseun Oluwagbemi, Elijah K. Oladipo, Olatunji M. Kolawole, Julius K. Oloke, Temitope I. Adelusi, Boluwatife A. Irewolede, Emmanuel O. Dairo, Ayodele E. Ayeni, Kehinde T. Kolapo, Olawumi E. Akindiya, Jerry A. Oluwasegun, Bamigboye F. Oluwadara and Segun Fatumo

Computation 2022, 10(7), 117; https://doi.org/10.3390/computation10070117 - 08 Jul 2022

Cited by 10 | Viewed by 4477 | Correction

Abstract

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome [...] Read more.

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response. Full article

(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))

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12 pages, 829 KiB

Open AccessArticle

Chebfun Solutions to a Class of 1D Singular and Nonlinear Boundary Value Problems

by Călin-Ioan Gheorghiu

Computation 2022, 10(7), 116; https://doi.org/10.3390/computation10070116 - 08 Jul 2022

Cited by 2 | Viewed by 1590

Abstract

The Chebyshev collocation method implemented in Chebfun is used in order to solve a class of second order one-dimensional singular and genuinely nonlinear boundary value problems. Efforts to solve these problems with conventional ChC have generally failed, and the outcomes obtained by finite [...] Read more.

The Chebyshev collocation method implemented in Chebfun is used in order to solve a class of second order one-dimensional singular and genuinely nonlinear boundary value problems. Efforts to solve these problems with conventional ChC have generally failed, and the outcomes obtained by finite differences or finite elements are seldom satisfactory. We try to fix this situation using the new Chebfun programming environment. However, for tough problems, we have to loosen the default Chebfun tolerance in Newton’s solver as the ChC runs into trouble with ill-conditioning of the spectral differentiation matrices. Although in such cases the convergence is not quadratic, the Newton updates decrease monotonically. This fact, along with the decreasing behaviour of Chebyshev coefficients of solutions, suggests that the outcomes are trustworthy, i.e., the collocation method has exponential (geometric) rate of convergence or at least an algebraic rate. We consider first a set of problems that have exact solutions or prime integrals and then another set of benchmark problems that do not possess these properties. Actually, for each test problem carried out we have determined how the Chebfun solution converges, its length, the accuracy of the Newton method and especially how well the numerical results overlap with the analytical ones (existence and uniqueness). Full article

(This article belongs to the Special Issue Mathematical Modeling and Study of Nonlinear Dynamic Processes)

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19 pages, 4873 KiB

Open AccessArticle

Capacitive Water-Cut Meter with Robust Near-Linear Transfer Function

by Oleksandr Zabolotnyi, Vitalii Zabolotnyi and Nikolay Koshevoy

Computation 2022, 10(7), 115; https://doi.org/10.3390/computation10070115 - 07 Jul 2022

Cited by 3 | Viewed by 1409

Abstract

The water content in fuel–water emulsions can vary from 10% to 30%, and is under control during the process of emulsification. The main task of this study was to obtain near-linear static function for a water-cut meter with capacitive sensors, and to provide [...] Read more.

The water content in fuel–water emulsions can vary from 10% to 30%, and is under control during the process of emulsification. The main task of this study was to obtain near-linear static function for a water-cut meter with capacitive sensors, and to provide it with effective type-uncertainty compensation during the process of water–fuel emulsion moisture control. To fulfill the capacitive measurements, two capacitive sensors in the measuring channel and two capacitive sensors in the reference channel were used. The method of least squares and general linear regression instruments were used to obtain robust and near-linear transfer function of the capacitive water-cut meter. The prototype product of the water-cut meter was developed with the purpose of fulfilling multiple moisture measurements and checking the workability of the new transfer function. Values of moisture content for the new transfer function and the closest analog were compared with the help of dispersion analysis. The new transfer function provided minimal dispersions of repeatability and adequacy, and minimal F-test values, proving its better capability for type-uncertainty compensation and better adequacy for the nominal linear transfer function of the water-cut meter. Full article

(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)

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19 pages, 3763 KiB

Open AccessArticle

Modeling the Meshing Procedure of the External Gear Fuel Pump Using a CFD Tool

by Ihor Romanenko, Yevhen Martseniuk and Oleksandr Bilohub

Computation 2022, 10(7), 114; https://doi.org/10.3390/computation10070114 - 06 Jul 2022

Cited by 2 | Viewed by 1771

Abstract

In modern aircraft engine technology, there is a tendency to replace the mechanical drive of external gear fuel pumps with an electric one. This significantly reduces the integral energy consumption for pumping fuel (kerosene). On the other hand, in order to reduce the [...] Read more.

In modern aircraft engine technology, there is a tendency to replace the mechanical drive of external gear fuel pumps with an electric one. This significantly reduces the integral energy consumption for pumping fuel (kerosene). On the other hand, in order to reduce the dimensions of the structure, it is reasonable to increase the rotation speed of the pumping unit gears. The above considerations make it advisable to study the problems that may arise in the design of pumping units. Analysis of the existing designs of external gear fuel pumps shows that the flow processes in the meshing zone have a significant impact on the pump performance and lifetime. Incorrect truss plate geometry and the compensation system lead to an increase in the velocities when opening and closing the cavity in the meshing zone, which causes intense cavitation. To understand the causes and factors which influence this phenomenon, it is necessary to study the fluid flow behavior in the meshing zone gaps. High-speed cameras are used to experimentally study the flow behavior. However, this approach gives only a qualitative result but does not allow for determining the absolute values of pressure and load in terms of the angle of rotation. Nevertheless, high-speed surveying can be used as a basis for fluid flow model verification. In this paper, the model of the fluid flow in a high-pressure external gear pump was proposed. The verification of the simulation results for HDZ 46 HLP 68 oil operation was carried out according to the results of experimental data visualization. The influence of rotation speed on the position of cavitation zones was revealed and confirmed by operational data. The analysis of the flow process in meshing for kerosene as a working fluid was carried out. Full article

(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)

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15 pages, 1763 KiB

Open AccessArticle

Balanced Circular Packing Problems with Distance Constraints

by Tetyana Romanova, Olexandr Pankratov, Igor Litvinchev, Petro Stetsyuk, Oleksii Lykhovyd, Jose Antonio Marmolejo-Saucedo and Pandian Vasant

Computation 2022, 10(7), 113; https://doi.org/10.3390/computation10070113 - 04 Jul 2022

Cited by 5 | Viewed by 2278

Abstract

The packing of different circles in a circular container under balancing and distance conditions is considered. Two problems are studied: the first minimizes the container’s radius, while the second maximizes the minimal distance between circles, as well as between circles and the boundary [...] Read more.

The packing of different circles in a circular container under balancing and distance conditions is considered. Two problems are studied: the first minimizes the container’s radius, while the second maximizes the minimal distance between circles, as well as between circles and the boundary of the container. Mathematical models and solution strategies are provided and illustrated with computational results. Full article

(This article belongs to the Special Issue Intelligent Computing, Modeling and its Applications)

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14 pages, 7605 KiB

Open AccessArticle

Rapid Detection of Cardiac Pathologies by Neural Networks Using ECG Signals (1D) and sECG Images (3D)

by Evelyn Aguiar-Salazar, Fernando Villalba-Meneses, Andrés Tirado-Espín, Daniel Amaguaña-Marmol and Diego Almeida-Galárraga

Computation 2022, 10(7), 112; https://doi.org/10.3390/computation10070112 - 30 Jun 2022

Cited by 4 | Viewed by 2419

Abstract

Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health [...] Read more.

Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health services or the time the public health system takes to refer the patient to a cardiologist. In addition, the variety of cardiac pathologies (more than 20 types) is a problem in diagnosing the disease. On the other hand, surface electrocardiography (sECG) is a little-explored technique for this diagnosis. sECGs are three-dimensional images (two dimensions in space and one in time). In this way, the signals were taken in one-dimensional format and analyzed using neural networks. Following the transformation of the one-dimensional signals to three-dimensional signals, they were analyzed in the same sense. For this research, two models based on LSTM and ResNet34 neural networks were developed, which showed high accuracy, 98.71% and 93.64%, respectively. This study aims to propose the basis for developing Decision Support Software (DSS) based on machine learning models. Full article

(This article belongs to the Special Issue Bioinspiration: The Path from Engineering to Nature)

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15 pages, 813 KiB

Open AccessArticle

Analysis of Electrical Models for Photovoltaic Cells under Uniform and Partial Shading Conditions

by Bonie Johana Restrepo-Cuestas, Mariana Durango-Flórez, Luz Adriana Trejos-Grisales and Carlos Andrés Ramos-Paja

Computation 2022, 10(7), 111; https://doi.org/10.3390/computation10070111 - 30 Jun 2022

Cited by 1 | Viewed by 1673

Abstract

This paper compares the performance of three electrical models (the single diode model, the Bishop model, and the Direct–Reverse model) in representing photovoltaic cells. Such comparison is performed in both the first quadrant (positive cell voltage and current—

Q_{1}

) and the [...] Read more.

This paper compares the performance of three electrical models (the single diode model, the Bishop model, and the Direct–Reverse model) in representing photovoltaic cells. Such comparison is performed in both the first quadrant (positive cell voltage and current—

Q_{1}

) and the second quadrant (negative cell voltage and positive cell current—

Q_{2}

). The analysis conducted here is based on the I–-V curves of a PV cell obtained experimentally. The parameters of each model are estimated using a Genetic Algorithm. The root mean square error and the mean absolute percentage error are computed to validate the estimation stage. Likewise, the behavior of each parameter of the models is analyzed by calculating their mean and standard deviation. Some places of interest on the I–V curve, such as the short–circuit point, the open–circuit point, and the maximum power point, are also estimated and compared. Full article

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23 pages, 1950 KiB

Open AccessArticle

An Optical Camera Communication Using Novel Hybrid Frequency Shift and Pulse Width Modulation Technique for Li-Fi

by Sanket Salvi and Geetha Vasantha

Computation 2022, 10(7), 110; https://doi.org/10.3390/computation10070110 - 30 Jun 2022

Cited by 4 | Viewed by 2228

Abstract

With an increase in network-connected devices, the existing Radio Frequency (RF) spectrum is getting highly saturated. Non-RF-based communication systems have recently garnered attention as they can be considered an alternative to RF-based systems for some applications. The availability of efficient and low-cost electronic [...] Read more.

With an increase in network-connected devices, the existing Radio Frequency (RF) spectrum is getting highly saturated. Non-RF-based communication systems have recently garnered attention as they can be considered an alternative to RF-based systems for some applications. The availability of efficient and low-cost electronic components like Light Emitting Diode (LED), photodiode, and cameras have been pivotal in building communications systems using visible light. High-speed communication using visible light can be achieved with customized hardware and software. Visible Light Communication (VLC) uses various properties of light to encode digital data, which is then modulated and transmitted over a short distance to the receiver. Photodiodes are inexpensive and provide low complexity implementation, but their adoption requires modifying existing devices to house dedicated sensors. On the other hand, in Optical Camera Communication (OCC), existing camera-based receivers are used to extract encoded data using properties of light like color, blink frequency, intensity, and polarity. In this paper, a novel OCC technique to achieve improved robustness using a Hybrid Frequency Shift Pulse Width Modulation (HFSPDM) is proposed, implemented, and evaluated. The performance of the proposed technique is compared for a short distance with On-Off Keying (OOK) and Binary Frequency Shift-OOK (BFSOOK) due to similar computational requirements. It was observed that the proposed technique used a 17% lesser number of frames than BFSOOK and provided 8% better BER than OOK under a test environment. It also supports longer distance communication than OOK as it is less sensitive to external noise. Full article

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18 pages, 6531 KiB

Open AccessArticle

Effect of Key Phytochemicals from Andrographis paniculata, Tinospora cordifolia, and Ocimum sanctum on PLpro-ISG15 De-Conjugation Machinery—A Computational Approach

by Prachi Singh, Shruthi S. Bhat, Ardra Punnapuzha, Amrutha Bhagavatula, Babu U. Venkanna, Rafiq Mohamed and Raghavendra P. Rao

Computation 2022, 10(7), 109; https://doi.org/10.3390/computation10070109 - 30 Jun 2022

Cited by 3 | Viewed by 1973

Abstract

ISGylation is an important process through which interferon-stimulated genes (ISGs) elicit an antiviral response in the host cells. Several viruses, including the SARS-CoV-2, suppress the host immune response by reversing the ISGylation through a process known as de-ISGylation. The PLpro of SARS-CoV-2 interacts [...] Read more.

ISGylation is an important process through which interferon-stimulated genes (ISGs) elicit an antiviral response in the host cells. Several viruses, including the SARS-CoV-2, suppress the host immune response by reversing the ISGylation through a process known as de-ISGylation. The PLpro of SARS-CoV-2 interacts with the host ISG15 and brings about de-ISGylation. Hence, inhibiting the de-ISGylation to restore the activity of ISGs can be an attractive strategy to augment the host immune response against SARS-CoV-2. In the present study, we evaluated several phytochemicals from well-known immunomodulatory herbs, viz. Andrographispaniculata (AG), Tinospora cordifolia (GU), and Ocimum sanctum (TU) for their effect on deISGylation that was mediated by the PLpro of SARS-CoV2. For this purpose, we considered the complex 6XA9, which represents the interaction between SARS-CoV-2 PLpro and ISG15 proteins. The phytochemicals from these herbs were first evaluated for their ability to bind to the interface region between PLpro and ISG15. Molecular docking studies indicated that 14-deoxy-15-isopropylidene-11,12-didehydroandrographolide (AG1), Isocolumbin (GU1), and Orientin (TU1) from AG, GU, and TU, respectively possess better binding energy. The molecular dynamic parameters and MMPBSA calculations indicated that AG1, GU1, and TU1 could favorably bind to the interface and engaged key residues between (PLpro-ISG15)-complex. Protein–protein MMPBSA calculations indicated that GU1 and TU1 could disrupt the interactions between ISG15 and PLpro. Our studies provide a novel molecular basis for the immunomodulatory action of these phytochemicals and open up new strategies to evaluate drug molecules for their effect on de-ISGylation to overcome the virus-mediated immune suppression. Full article

(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))

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21 pages, 7209 KiB

Open AccessArticle

Monitoring of Temperature Measurements for Different Flow Regimes in Water and Galinstan with Long Short-Term Memory Networks and Transfer Learning of Sensors

by Stella Pantopoulou, Victoria Ankel, Matthew T. Weathered, Darius D. Lisowski, Anthonie Cilliers, Lefteri H. Tsoukalas and Alexander Heifetz

Computation 2022, 10(7), 108; https://doi.org/10.3390/computation10070108 - 29 Jun 2022

Cited by 13 | Viewed by 1874

Abstract

Temperature sensing is one of the most common measurements of a nuclear reactor monitoring system. The coolant fluid flow in a reactor core depends on the reactor power state. We investigated the monitoring and estimation of the thermocouple time series using machine learning [...] Read more.

Temperature sensing is one of the most common measurements of a nuclear reactor monitoring system. The coolant fluid flow in a reactor core depends on the reactor power state. We investigated the monitoring and estimation of the thermocouple time series using machine learning for a range of flow regimes. Measurement data were obtained, in two separate experiments, in a flow loop filled with water and with liquid metal Galinstan. We developed long short-term memory (LSTM) recurrent neural networks (RNNs) for sensor predictions by training on the sensor’s own prior history, and transfer learning LSTM (TL-LSTM) by training on a correlated sensor’s prior history. Sensor cross-correlations were identified by calculating the Pearson correlation coefficient of the time series. The accuracy of LSTM and TL-LSTM predictions of temperature was studied as a function of Reynolds number (Re). The root-mean-square error (RMSE) for the test segment of time series of each sensor was shown to linearly increase with Re for both water and Galinstan fluids. Using linear correlations, we estimated the range of values of Re for which RMSE is smaller than the thermocouple measurement uncertainty. For both water and Galinstan fluids, we showed that both LSTM and TL-LSTM provide reliable estimations of temperature for typical flow regimes in a nuclear reactor. The LSTM runtime was shown to be substantially smaller than the data acquisition rate, which allows for performing estimation and validation of sensor measurements in real time. Full article

(This article belongs to the Special Issue Recent Advances in Process Modeling and Optimisation)

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22 pages, 1498 KiB

Open AccessArticle

A Prospective Method for Generating COVID-19 Dynamics

by Kamal Khairudin Sukandar, Andy Leonardo Louismono, Metra Volisa, Rudy Kusdiantara, Muhammad Fakhruddin, Nuning Nuraini and Edy Soewono

Computation 2022, 10(7), 107; https://doi.org/10.3390/computation10070107 - 24 Jun 2022

Cited by 5 | Viewed by 1636

Abstract

Generating dynamic operators are constructed here from the cumulative case function to recover all state dynamics of a Susceptible–Exposed–Infectious–Recovered (SEIR) model for COVID-19 transmission. In this study, recorded and unrecorded EIRs and a time-dependent infection rate are taken into account to accommodate immeasurable [...] Read more.

Generating dynamic operators are constructed here from the cumulative case function to recover all state dynamics of a Susceptible–Exposed–Infectious–Recovered (SEIR) model for COVID-19 transmission. In this study, recorded and unrecorded EIRs and a time-dependent infection rate are taken into account to accommodate immeasurable control and intervention processes. Generating dynamic operators are built and implemented on the cumulative cases. All infection processes, which are hidden in this cumulative function, can be recovered entirely by implementing the generating operators. Direct implementation of the operators on the cumulative function gives all recorded state dynamics. Further, the unrecorded daily infection rate is estimated from the ratio between IFR and CFR. The remaining dynamics of unrecorded states are directly obtained from the generating operators. The simulations are conducted using infection data provided by Worldometers from ten selected countries. It is shown that the higher number of daily PCR tests contributed directly to reducing the effective reproduction ratio. The simulations of all state dynamics, infection rates, and effective reproduction ratios for several countries in the first and second waves of transmissions are presented. This method directly measures daily transmission indicators, which can be effectively used for the day-to-day control of the epidemic. Full article

(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))

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18 pages, 652 KiB

Open AccessArticle

Digital Transformation of Signatures: Suggesting Functional Symmetry Approach for Loan Agreements

by Viktor Titov, Pavel Shust, Victor Dostov, Anna Leonova, Svetlana Krivoruchko, Nadezhda Lvova, Iurii Guzov, Angelina Vashchuk, Natalia Pokrovskaia, Anton Braginets and Mikhail Zaboev

Computation 2022, 10(7), 106; https://doi.org/10.3390/computation10070106 - 24 Jun 2022

Cited by 2 | Viewed by 1615

Abstract

This article aims to formulate proposals for regulatory bodies whose implementation would ensure the effective introduction of civil circulation into electronic signatures, with minimal costs for economic entities. While electronic signatures have been widely discussed in academic literature, there are still gaps in [...] Read more.

This article aims to formulate proposals for regulatory bodies whose implementation would ensure the effective introduction of civil circulation into electronic signatures, with minimal costs for economic entities. While electronic signatures have been widely discussed in academic literature, there are still gaps in the understanding of similarities and differences between electronic and handwritten signatures, the functional specifics of the relationship between them, and the role of electronic signatures for electronic contract. Our research has allowed us to overcome this gap adopting a functional symmetry approach based on measuring the distance between fuzzy sets and the Mamdani fuzzy inference algorithm. This made it possible to form an estimate of the degree of functional symmetry between different types of signatures in a fuzzy and exact form. Correspondingly, we argue that the signature can be viewed as a set of procedures rather than as a single act in order to achieve functional symmetry with a handwritten signature. The case of online lending was used to test and prove this hypothesis. Therefore, regulating electronic signatures needs to focus on the efficiency of this processes for ex ante identification, capturing the intent, ensuring the inalterability and providing reliable evidence, irrespective of the type of electronic signature that is used. It was also revealed that the proposed functional symmetry approach can be combined with a fuzziness index analysis to provide new prospects for further research. Full article

(This article belongs to the Section Computational Engineering)

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17 pages, 2231 KiB

Open AccessArticle

Constructing a Region DSGE Model with Institutional Features of Territorial Development

by Julia Dubrovskaya, Dmitriy Shults and Elena Kozonogova

Computation 2022, 10(7), 105; https://doi.org/10.3390/computation10070105 - 23 Jun 2022

Cited by 4 | Viewed by 2163

Abstract

The growing importance of regional units in national economies gives rise to the objective need to improve the tools of spatial management. The construction of realistic development scenarios and forecasts is possible on the basis of the DSGE models’ tools. At the same [...] Read more.

The growing importance of regional units in national economies gives rise to the objective need to improve the tools of spatial management. The construction of realistic development scenarios and forecasts is possible on the basis of the DSGE models’ tools. At the same time, models of a similar class that describe socio-economic processes at the level of the regional economy are practically not represented in modern studies. The purpose of the paper is to build a model of the regional economy based on DSGE tools. A feature of the proposed model is the consideration of spatial features through budget expenditures on the digitalization of such areas as healthcare and education. The high importance of these costs became evident during the COVID-19 crisis, when the consequences of underfunding IT costs in education and healthcare led to slowing economic growth. We have allocated health and education expenses in the standard budget limit of the regional government. On the basis of the developed model, response functions for shocks of exogenous variables for 20 periods were built. The result of the simulation is the response functions of endogenous variables in response to the fading growth in the share of spending on human capital in the region, as well as the obtained values of elasticities for a single change in shocks. Full article

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14 pages, 1249 KiB

Open AccessArticle

An Improved Homogeneous Ensemble Technique for Early Accurate Detection of Type 2 Diabetes Mellitus (T2DM)

by Umuhire Mucyo Faustin and Beiji Zou

Computation 2022, 10(7), 104; https://doi.org/10.3390/computation10070104 - 23 Jun 2022

Cited by 1 | Viewed by 1439

Abstract

The objective of the present study is to improve the genetic algorithm (GA) supremacy in selecting the most suitable and relevant features within a highly dimensional dataset. This results in cost reduction and improving classification performance. During text classification, employing terms such as [...] Read more.

The objective of the present study is to improve the genetic algorithm (GA) supremacy in selecting the most suitable and relevant features within a highly dimensional dataset. This results in cost reduction and improving classification performance. During text classification, employing terms such as features using vector space representation can result in a high dimensionality of future space. This condition presents some issues, including high computation cost in data analysis and deteriorating classification accuracy performance. Several computational feature selection techniques can be applied in eliminating the least significant features within a dataset, including a genetic algorithm. The present study improved the performance of the classifier in classifying Pima Indian diabetes data. Despite the popularity of GA in the feature selection area, it does not provide the most optimal features due to one of its underlying issues: premature convergence due to insufficient population diversity in the future generations. GA was improved in its crossover operator using two steps: define a variable slice point on the size of the gene to be interchanged for every offspring generation and apply feature frequency scores in deciding the interchanging of genes. The above obtained results to the proposed technique will be better results than the results for standard GA. Our proposed algorithm attained an accuracy of 97.5%, precision of 98, recall of 97% and F1-score of 97%. Full article

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Computation, Volume 10, Issue 7 (July 2022) – 24 articles

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