Journal Description
Computation
Computation
is a peer-reviewed journal of computational science and engineering published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), CAPlus / SciFinder, Inspec, dblp, and other databases.
- Journal Rank: JCR - Q2 (Mathematics, Interdisciplinary Applications) / CiteScore - Q2 (Applied Mathematics)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
1.9 (2023);
5-Year Impact Factor:
2.0 (2023)
Latest Articles
Second-Order Modified Nonstandard Explicit Euler and Explicit Runge–Kutta Methods for n-Dimensional Autonomous Differential Equations
Computation 2024, 12(9), 183; https://doi.org/10.3390/computation12090183 - 9 Sep 2024
Abstract
Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD
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Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD methods are only first-order accurate. This paper introduces two new classes of explicit second-order modified NSFD methods for solving n-dimensional autonomous dynamical systems. These explicit methods extend previous work by incorporating novel denominator functions to ensure both elementary stability and second-order accuracy. This paper also provides a detailed mathematical analysis and validates the methods through numerical simulations on various biological systems.
Full article
(This article belongs to the Special Issue Advanced Numerical Methods for Solving Differential Equations with Applications in Science and Engineering)
Open AccessArticle
An Analysis of the Stress–Strain State of a Layer on Two Cylindrical Bearings
by
Vitaly Miroshnikov, Oleksandr Denshchykov, Iaroslav Grebeniuk and Oleksandr Savin
Computation 2024, 12(9), 182; https://doi.org/10.3390/computation12090182 - 6 Sep 2024
Abstract
A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type
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A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type conditions (normal displacements and tangential stresses) are specified on the insides of the pipes. Stresses are set on the flat surfaces of the layer. The objective of this study is to obtain the stress–strain state of the body of the layer under different geometric characteristics of the model. The solution to the problem is presented in the form of the Lamé equation, whose terms are written in different coordinate systems. The generalized Fourier method is used to transfer the basic solutions between coordinate systems. By satisfying the boundary and conjugation conditions, the problem is reduced to a system of infinite linear algebraic equations of the second kind, to which the reduction method is applied. After finding the unknowns, using the generalized Fourier method, it is possible to find the stress–strain state at any point of the body. The numerical study of the stress state showed high convergence of the approximate solutions to the exact one. The stress–strain state of the composite body was analyzed for different geometric parameters and different pipe materials. The results obtained can be used for the preliminary determination of the geometric parameters of the model and the materials of the joints. The proposed solution method can be used not only to calculate the stress state of bearing joints, but also of bushings (under specified conditions of rigid contact without friction on the internal surfaces).
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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Open AccessArticle
Some Aspects of the Effects of Dry Friction Discontinuities on the Behaviour of Dynamic Systems
by
Stelian Alaci, Costica Lupascu, Ionut-Cristian Romanu, Delia-Aurora Cerlinca and Florina-Carmen Ciornei
Computation 2024, 12(9), 181; https://doi.org/10.3390/computation12090181 - 5 Sep 2024
Abstract
Most studies in the literature consider the value of the coefficient of dynamic friction to be constant. We studied the evolution of a dynamic system when the coefficient of friction results in different values depending on the contact surfaces. A system with four
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Most studies in the literature consider the value of the coefficient of dynamic friction to be constant. We studied the evolution of a dynamic system when the coefficient of friction results in different values depending on the contact surfaces. A system with four balls fixed on an aluminium plate was driven with constant velocity into motion on the coaxial races of two identical outer bearing rings. The assembly presents a motion with periodic variable amplitude between two extremes, a fact that suggests the presence of a periodical excitation. The test was repeated, but this time, new bodies were used, which were two identical bodies made of two balls rigidised via a short cylindrical rod. When the rings were driven into rotational motion, the two bodies performed different motions; if the bodies were inter-changed, the differences between the motions remained. The rings were analysed, and a small region on the race of one ring was observed, where the roughness was considerably greater than the rest of the surface. Then, a mathematical model for the dynamic system with different friction coefficients was proposed and solved. This model is capable of simulating different situations, such as oscillatory motion and circular motion, with or without separation of the contacting bodies. Here, we present a dynamic model with Hertzian contact points in the presence of dry friction, with the coefficient of friction changing suddenly on the contacting surfaces.
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(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Optimized Calculation of Radial and Axial Magnetic Forces between Two Non-Coaxial Coils of Rectangular Cross-Section with Parallel Axes
by
Slobodan Babic, Eray Guven, Kai-Hong Song and Yao Luo
Computation 2024, 12(9), 180; https://doi.org/10.3390/computation12090180 - 4 Sep 2024
Abstract
In this paper, we introduce a new algorithm for calculating the radial and axial magnetic forces between two non-coaxial circular loops with parallel axes. These formulas are derived from a modified version of Grover’s formula for mutual inductance between the coils in question.
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In this paper, we introduce a new algorithm for calculating the radial and axial magnetic forces between two non-coaxial circular loops with parallel axes. These formulas are derived from a modified version of Grover’s formula for mutual inductance between the coils in question. Utilizing these formulas, we compute the radial and axial magnetic forces between two non-coaxial thick coils of rectangular cross-sections with parallel axes. In these calculations, we apply the filament method and conduct investigations to determine the optimal number of subdivisions for the coils in terms of computational time and accuracy. The method presented in this paper is also applicable to all conventional non-coaxial coils, such as disks, solenoids, and non-conventional coils like Bitter coils, all with parallel axes. This paper emphasizes the accuracy and computational efficiency of the calculations. Furthermore, the new method is validated according to several previously established methods.
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(This article belongs to the Section Computational Engineering)
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Open AccessArticle
PyIncentiveBC: A Python Module for Simulation of Incentivization Mechanism Implemented in Blockchain-Based Systems
by
Abdellah Ouaguid, Mohamed Hanine, Zouhair Chiba, Noreddine Abghour and Mohammed Ouzzif
Computation 2024, 12(9), 179; https://doi.org/10.3390/computation12090179 - 3 Sep 2024
Abstract
The diversity of approaches for retaining participants in a Blockchain-based system complicates benchmarking. The majority of proposals for rewarding and penalizing participants in these systems are limited to their own set of data and scenarios, making it hard to compare their effectiveness. To
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The diversity of approaches for retaining participants in a Blockchain-based system complicates benchmarking. The majority of proposals for rewarding and penalizing participants in these systems are limited to their own set of data and scenarios, making it hard to compare their effectiveness. To overcome these challenges, we developed PyIncentiveBC, a free, open-source, and modular simulator designed to evaluate the reliability of any approach, incorporating a dynamic and proportionate incentivization mechanism proposed in our previous work. PyIncentiveBC aims to provide the scientific communities with an extensible software solution facilitating the benchmarking of existing approaches with new ones proposed by them.
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(This article belongs to the Section Computational Engineering)
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Open AccessArticle
The Development of a Novel Transient Signal Analysis: A Wavelet Transform Approach
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Eduardo Gómez-Luna, Dixon E. Cuadros-Orta, John E. Candelo-Becerra and Juan C. Vasquez
Computation 2024, 12(9), 178; https://doi.org/10.3390/computation12090178 - 3 Sep 2024
Abstract
This paper presents a new method for the analysis of transient signals in the frequency domain based on the Continuous Wavelet Transform (CWT). The proposed case study involves test signals measured from an electronic switch considering open and close operations. The source is
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This paper presents a new method for the analysis of transient signals in the frequency domain based on the Continuous Wavelet Transform (CWT). The proposed case study involves test signals measured from an electronic switch considering open and close operations. The source is connected to inductive, resistive, and capacitive loads. Resonance behaviors are introduced and compared with the Discrete Fourier Transform (DFT). Multiple factors, such as reliability, repeatability, high noise attenuation, and the smoothing of the analyzed spectrum, are considered in this study. This proposed study highlights the effectiveness of CWT in signal processing, especially in obtaining a detailed spectrum that reveals the behavior of electrical circuits. Resonance behaviors were analyzed, demonstrating that the signal processing performed by CWT is better for spectrum analysis than DFT. This study shows the potential of CWT to analyze transient electrical signals, specifically for identifying and characterizing the behavior of load connections and disconnections.
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(This article belongs to the Section Computational Engineering)
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Open AccessCorrection
Correction: Oldrieve, R.M. Teaching K–3 Multi-Digit Arithmetic Computation to Students with Slow Language Processing. Computation 2024, 12, 128
by
Richard M. Oldrieve
Computation 2024, 12(9), 177; https://doi.org/10.3390/computation12090177 - 3 Sep 2024
Abstract
Error in Figure/Table [...]
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(This article belongs to the Special Issue Computations in Mathematics, Mathematical Education, and Science)
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Open AccessArticle
On the Impact of Discrete Atomic Compression on Image Classification by Convolutional Neural Networks
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Viktor Makarichev, Vladimir Lukin and Iryna Brysina
Computation 2024, 12(9), 176; https://doi.org/10.3390/computation12090176 - 1 Sep 2024
Abstract
Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is
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Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is an approach providing image compression and encryption simultaneously. It has two processing modes: lossless and lossy. The latter one ensures a higher compression ratio in combination with inevitable quality loss that may affect decompressed image analysis, in particular, classification. In this paper, we explore the impact of distortions produced by DAC on performance of several state-of-the-art classifiers based on convolutional neural networks (CNNs). The classic, block-splitting and chroma subsampling modes of DAC are considered. It is shown that each of them produces a quite small effect on MobileNetV2, VGG16, VGG19, ResNet50, NASNetMobile and NASNetLarge models. This research shows that, using the DAC approach, memory expenses can be reduced without significant degradation of performance of the aforementioned CNN-based classifiers.
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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Open AccessArticle
In Silico Drug Screening for Hepatitis C Virus Using QSAR-ML and Molecular Docking with Rho-Associated Protein Kinase 1 (ROCK1) Inhibitors
by
Joshua R. De Borja and Heherson S. Cabrera
Computation 2024, 12(9), 175; https://doi.org/10.3390/computation12090175 - 31 Aug 2024
Abstract
The enzyme ROCK1 plays a pivotal role in the disruption of the tight junction protein CLDN1, a downstream effector influencing various cellular functions such as cell migration, adhesion, and polarity. Elevated levels of ROCK1 pose challenges in HCV, where CLDN1 serves as a
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The enzyme ROCK1 plays a pivotal role in the disruption of the tight junction protein CLDN1, a downstream effector influencing various cellular functions such as cell migration, adhesion, and polarity. Elevated levels of ROCK1 pose challenges in HCV, where CLDN1 serves as a crucial entry factor for viral infections. This study integrates a drug screening protocol, employing a combination of quantitative structure–activity relationship machine learning (QSAR-ML) techniques; absorption, distribution, metabolism, and excretion (ADME) predictions; and molecular docking. This integrated approach allows for the effective screening of specific compounds, using their calculated features and properties as guidelines for selecting drug-like candidates targeting ROCK1 inhibition in HCV treatment. The QSAR-ML model, validated with scores of 0.54 (R2), 0.15 (RMSE), and 0.71 (CCC), demonstrates its predictive capabilities. The ADME-Docking study’s final results highlight notable compounds from ZINC15, specifically ZINC000071318464, ZINC000073170040, ZINC000058568630, ZINC000058591055, and ZINC000058574949. These compounds exhibit the best ranking Vina scores for protein–ligand binding with the crystal structure of ROCK1 at the C2 pocket site. The generated features and calculated pIC50 bioactivity of these compounds provide valuable insights, facilitating the identification of structurally similar candidates in the ongoing exploration of drugs for ROCK1 inhibition.
Full article
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Biology)
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Open AccessArticle
FPGA-Based Numerical Simulation of the Chaotic Synchronization of Chua Circuits
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Leonardo Rentería, Margarita Mayacela, Klever Torres, Wladimir Ramírez, Rolando Donoso and Rodrigo Acosta
Computation 2024, 12(9), 174; https://doi.org/10.3390/computation12090174 - 31 Aug 2024
Abstract
The objective of this work was to design and implement a system based on reconfigurable hardware as a study tool for the synchronization of chaotic circuits. Mathematical models were established for one circuit, two synchronized, and multiple synchronized Chua circuits. An ordinary differential
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The objective of this work was to design and implement a system based on reconfigurable hardware as a study tool for the synchronization of chaotic circuits. Mathematical models were established for one circuit, two synchronized, and multiple synchronized Chua circuits. An ordinary differential equation solver was developed applying Euler’s method using the Verilog hardware description language and synthesized on a Spartan 3E FPGA (Field-Programmable Gate Array) equipped with a 32-bit RISC processor, 64 MB of DDR SDRAM, and 4 Mb of PROM. With a step size of 0.005 and a total of 10,000 iterations, the state equations for one and three Chua circuits were solved at a time of 0.2 ms and a frequency of 50 Mhz. The logical resources used by the system did not exceed 4%. To verify the operation, a numerical simulation was carried out using the Octave V9.1.0 calculation software on an Intel(R) Core i7-9750H CPU 2.59 GHz computer, obtaining the same results but in a time of 493 ms and 3.177 s for one and three circuits, respectively.
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(This article belongs to the Section Computational Engineering)
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Open AccessArticle
A Deep Learning Model for Detecting Fake Medical Images to Mitigate Financial Insurance Fraud
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Muhammad Asad Arshed, Shahzad Mumtaz, Ștefan Cristian Gherghina, Neelam Urooj, Saeed Ahmed and Christine Dewi
Computation 2024, 12(9), 173; https://doi.org/10.3390/computation12090173 - 29 Aug 2024
Abstract
Artificial Intelligence and Deepfake Technologies have brought a new dimension to the generation of fake data, making it easier and faster than ever before—this fake data could include text, images, sounds, videos, etc. This has brought new challenges that require the faster development
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Artificial Intelligence and Deepfake Technologies have brought a new dimension to the generation of fake data, making it easier and faster than ever before—this fake data could include text, images, sounds, videos, etc. This has brought new challenges that require the faster development of tools and techniques to avoid fraudulent activities at pace and scale. Our focus in this research study is to empirically evaluate the use and effectiveness of deep learning models such as Convolutional Neural Networks (CNNs) and Patch-based Neural Networks in the context of successful identification of real and fake images. We chose the healthcare domain as a potential case study where the fake medical data generation approach could be used to make false insurance claims. For this purpose, we obtained publicly available skin cancer data and used recently introduced stable diffusion approaches—a more effective technique than prior approaches such as Generative Adversarial Network (GAN)—to generate fake skin cancer images. To the best of our knowledge, and based on the literature review, this is one of the few research studies that uses images generated using stable diffusion along with real image data. As part of the exploratory analysis, we analyzed histograms of fake and real images using individual color channels and averaged across training and testing datasets. The histogram analysis demonstrated a clear change by shifting the mean and overall distribution of both real and fake images (more prominent in blue and green) in the training data whereas, in the test data, both means were different from the training data, so it appears to be non-trivial to set a threshold which could give better predictive capability. We also conducted a user study to observe where the naked eye could identify any patterns for classifying real and fake images, and the accuracy of the test data was observed to be 68%. The adoption of deep learning predictive approaches (i.e., patch-based and CNN-based) has demonstrated similar accuracy (~100%) in training and validation subsets of the data, and the same was observed for the test subset with and without StratifiedKFold (k = 3). Our analysis has demonstrated that state-of-the-art exploratory and deep-learning approaches are effective enough to detect images generated from stable diffusion vs. real images.
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(This article belongs to the Special Issue Computational Medical Image Analysis—2nd Edition)
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Open AccessArticle
Amide–π Interactions in the Structural Stability of Proteins: Role in the Oligomeric Phycocyanins
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Luka M. Breberina, Mario V. Zlatović, Srđan Đ. Stojanović and Milan R. Nikolić
Computation 2024, 12(9), 172; https://doi.org/10.3390/computation12090172 - 27 Aug 2024
Abstract
This study investigates the influences and environmental preferences of amide–π interactions, a relatively unexplored class of charge-free interactions, in oligomeric phycocyanins. In a data set of 20 proteins, we observed 2086 amide–π interactions, all of which were part of the protein backbone. Phe
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This study investigates the influences and environmental preferences of amide–π interactions, a relatively unexplored class of charge-free interactions, in oligomeric phycocyanins. In a data set of 20 proteins, we observed 2086 amide–π interactions, all of which were part of the protein backbone. Phe and Tyr residues were found to be involved in amide–π interactions more frequently than Trp or His. The most favorable amide–π interactions occurred within a pair distance range of 5–7 Å, with a distinct angle preference for T-shaped ring arrangements. Multiple interaction patterns suggest that approximately 76% of the total interacting residues participate in multiple amide–π interactions. Our ab initio calculations revealed that most amide–π interactions have energy from 0 to −2 kcal/mol. Stabilization centers of phycocyanins showed that all residues in amide–π interactions play a crucial role in locating one or more such centers. Around 78% of the total interacting residues in the dataset contribute to creating hot-spot regions. Notably, the amide–π interacting residues were found to be highly evolutionarily conserved. These findings enhance our understanding of the structural stability and potential for protein engineering of phycocyanins used as bioactive natural colorants in various industries, including food and pharmaceuticals.
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(This article belongs to the Section Computational Chemistry)
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Open AccessArticle
Synthesis of Self-Checking Circuits for Train Route Traffic Control at Intermediate Stations with Control of Calculations Based on Weight-Based Sum Codes
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Dmitry V. Efanov, Artyom V. Pashukov, Evgenii M. Mikhailiuta, Valery V. Khóroshev, Ruslan B. Abdullaev, Dmitry G. Plotnikov, Aushra V. Banite, Alexander V. Leksashov, Dmitry N. Khomutov, Dilshod Kh. Baratov and Davron Kh. Ruziev
Computation 2024, 12(9), 171; https://doi.org/10.3390/computation12090171 - 26 Aug 2024
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When synthesizing systems for railway interlocking, it is recommended to use automated models to implement the logic of railway automation and remote control units. Finite-state machines (FSMs) can be implemented on any hardware component. When using relay technology, the functional safety of electrical
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When synthesizing systems for railway interlocking, it is recommended to use automated models to implement the logic of railway automation and remote control units. Finite-state machines (FSMs) can be implemented on any hardware component. When using relay technology, the functional safety of electrical interlocking is achieved by using uncontrolled (safety) relays with a high coefficient of asymmetry of failures in types 1 → 0 and 0 → 1. When using programmable components, the use of backup and diverse protection methods is required. This paper presents a flexible approach to synthesizing FSMs for railway automation and remote control units that offer both individual and route-based control. Unlike existing solutions, this proposal considers the pre-failure states of railway automation and remote control units during the finite-state machine synthesis stage. This enables the implementation of self-checking and self-diagnostic modules to manage automation units. By increasing the number of states for individual devices and considering the states of interconnected objects, the transition graphs can be expanded. This expansion allows for the synthesis of the transition graph of the control subsystem and other systems. The authors used a field-programmable gate array (FPGA) to implement a finite-state machine. In this case, the proposal is to encode the states of a finite-state machine using weight-based sum codes in the residue class ring based on a given modulus. The best coverage of errors occurring at the outputs of the logic converter in the structure of the FSM can be ensured by selecting the weighting coefficients and the value of the module. This paper presents an example of synthesizing an FPGA-based FSM using state encoding through modular weight-based sum codes. The operation of the synthesized device was modeled. It was found to operate according to the same algorithm as the real devices. When synthesizing self-checking and self-controlled train control devices, it is recommended to consider the solutions proposed in this paper.
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Open AccessArticle
Statistical Synthesis and Analysis of Functionally Deterministic Signal Processing Techniques for Multi-Antenna Direction Finder Operation
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Semen Zhyla, Eduard Tserne, Yevhenii Volkov, Sergey Shevchuk, Oleg Gribsky, Dmytro Vlasenko, Volodymyr Kosharskyi and Danyil Kovalchuk
Computation 2024, 12(9), 170; https://doi.org/10.3390/computation12090170 - 23 Aug 2024
Abstract
This manuscript focuses on the process of measuring the angular positions of radio sources using radio engineering systems. This study aims to improve the accuracy of measuring the angular positions of sources that radiate functionally determined signals and to expand the range of
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This manuscript focuses on the process of measuring the angular positions of radio sources using radio engineering systems. This study aims to improve the accuracy of measuring the angular positions of sources that radiate functionally determined signals and to expand the range of the unambiguous operation angles for multi-antenna radio direction finders. To achieve this goal, the following tasks were addressed: (1) defining the models of signals, noise, and their statistical characteristics, (2) developing the theoretical foundations of statistical optimization methods for measuring the angular positions of radio sources in multi-antenna radio direction finders, (3) optimizing the structures of radio direction finders with different configurations, (4) analyzing the accuracy and range of the unambiguous measurement angles in the developed methods, and (5) conducting experimental measurements to confirm the main results. The methods used are based on the statistical theory of optimization for remote sensing and radar systems. For the specified type of signals, given by functionally deterministic models, a likelihood function was constructed, and its maxima were determined for different multi-antenna direction finder configurations. The results of statistical synthesis were verified through simulation modeling and experiments. The primary approach to improving measurement accuracy and expanding the range of unambiguous angles involves combining antennas with different spatial characteristics and optimally integrating classical radio direction-finding methods. The following results were obtained: (1) theoretical studies and simulation modeling confirmed the existence of a contradiction between high resolution and the width of the range of the unambiguous measurements in two-antenna radio direction finders, (2) an improved signal processing method was developed for a four-antenna radio direction finder with a pair of high-gain and a pair of low-gain antennas, and (3) to achieve maximum direction-finding accuracy within the unambiguous measurement range, a new signal processing method was synthesized for a six-element radio receiver, combining processing in two amplitude direction finders and one phase direction finder. This work provides a foundation for further theoretical studies, highlights the specifics of combining engineering measurements in direction-finding systems, and offers examples of rapid verification of new methods through computer modeling and experimental measurements.
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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Open AccessArticle
Analogue Computation Converter for Nonhomogeneous Second-Order Linear Ordinary Differential Equation
by
Gabriel Nicolae Popa and Corina Maria Diniș
Computation 2024, 12(8), 169; https://doi.org/10.3390/computation12080169 - 20 Aug 2024
Abstract
Among many other applications, electronic converters can be used with sensors with analogue outputs (DC voltage). This article presents an analogue computation converter with two DC voltages at the inputs (one input changes the frequency of the output signal, another input changes the
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Among many other applications, electronic converters can be used with sensors with analogue outputs (DC voltage). This article presents an analogue computation converter with two DC voltages at the inputs (one input changes the frequency of the output signal, another input changes the amplitude of the output signal) that provide a periodic sinusoidal signal (with variable frequency and amplitude) at the output. On the basis of the analogue computation converter is a nonhomogeneous second-order linear ordinary differential equation which is solved analogically. The analogue computation converter consists of analogue multipliers and operational amplifiers, composed of seven function circuits: two analogue multiplication circuits, two analogue addition circuits, one non-inverting amplifier, and two integration circuits (with RC time constants). At the output of an oscillator is a sinusoidal signal which depends on the DC voltages applied on two inputs (0 ÷ 10 V): at one input, a DC voltage is applied to linearly change the sinusoidal frequency output (up to tens of kHz, according to two time constants), and at the other input, a DC voltage is applied to linearly change the amplitude of the oscillator output signal (up to 10 V). It can be used with sensors which have a DC output voltage and must be converted to a sine wave signal with variable frequency and amplitude with the aim of transmitting information over longer distances through wires. This article presents the detailed theory of the functioning, simulations, and experiments of the analogue computation converter.
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(This article belongs to the Section Computational Engineering)
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Open AccessArticle
Dislocation Interactions with Hcp- and χ-Phase Particles in Tungsten: Molecular Dynamics Insights into Mechanical Strengthening Mechanisms
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Yu. R. Sharapova, A. M. Kazakov, R. I. Babicheva, A. S. Semenov, A. A. Izosimov and E. A. Korznikova
Computation 2024, 12(8), 168; https://doi.org/10.3390/computation12080168 - 19 Aug 2024
Abstract
Our study investigates the interaction of dislocations with hexagonal close-packed (hcp) and chi-phase (χ) particles in body-centred cubic (bcc) tungsten (W) using molecular dynamics simulations. The research aims to understand how these interactions influence the mechanical properties of W, particularly in the context
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Our study investigates the interaction of dislocations with hexagonal close-packed (hcp) and chi-phase (χ) particles in body-centred cubic (bcc) tungsten (W) using molecular dynamics simulations. The research aims to understand how these interactions influence the mechanical properties of W, particularly in the context of neutron irradiation environments. The simulations were conducted with spherical and cylindrical particles at various temperatures and cell sizes to observe the effects on critical shear stress. Results indicate that the shape and size of the particles significantly affect the critical shear stress required for dislocation movement, with cylindrical particles requiring higher stresses than spherical ones. Additionally, the study found that temperature variations have a more pronounced effect on χ-phase particles compared to hcp-phase particles. Our findings provide insights into the strengthening mechanisms in W-Re alloys and suggest potential pathways for enhancing the material’s performance under extreme conditions.
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(This article belongs to the Section Computational Engineering)
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Open AccessReview
Methods for Detecting the Patient’s Pupils’ Coordinates and Head Rotation Angle for the Video Head Impulse Test (vHIT), Applicable for the Diagnosis of Vestibular Neuritis and Pre-Stroke Conditions
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G. D. Mamykin, A. A. Kulesh, Fedor L. Barkov, Y. A. Konstantinov, D. P. Sokol’chik and Vladimir Pervadchuk
Computation 2024, 12(8), 167; https://doi.org/10.3390/computation12080167 - 18 Aug 2024
Abstract
In the contemporary era, dizziness is a prevalent ailment among patients. It can be caused by either vestibular neuritis or a stroke. Given the lack of diagnostic utility of instrumental methods in acute isolated vertigo, the differentiation of vestibular neuritis and stroke is
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In the contemporary era, dizziness is a prevalent ailment among patients. It can be caused by either vestibular neuritis or a stroke. Given the lack of diagnostic utility of instrumental methods in acute isolated vertigo, the differentiation of vestibular neuritis and stroke is primarily clinical. As a part of the initial differential diagnosis, the physician focuses on the characteristics of nystagmus and the results of the video head impulse test (vHIT). Instruments for accurate vHIT are costly and are often utilized exclusively in healthcare settings. The objective of this paper is to review contemporary methodologies for accurately detecting the position of pupil centers in both eyes of a patient and for precisely extracting their coordinates. Additionally, the paper describes methods for accurately determining the head rotation angle under diverse imaging and lighting conditions. Furthermore, the suitability of these methods for vHIT is being evaluated. We assume the maximum allowable error is 0.005 radians per frame to detect pupils’ coordinates or 0.3 degrees per frame while detecting the head position. We found that for such conditions, the most suitable approaches for head posture detection are deep learning (including LSTM networks), search by template matching, linear regression of EMG sensor data, and optical fiber sensor usage. The most relevant approaches for pupil localization for our medical tasks are deep learning, geometric transformations, decision trees, and RASNAC. This study might assist in the identification of a number of approaches that can be employed in the future to construct a high-accuracy system for vHIT based on a smartphone or a home computer, with subsequent signal processing and initial diagnosis.
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(This article belongs to the Special Issue Deep Learning Applications in Medical Imaging)
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Open AccessReview
Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
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Diandra Chika Fransisca, Sukono, Diah Chaerani and Nurfadhlina Abdul Halim
Computation 2024, 12(8), 166; https://doi.org/10.3390/computation12080166 - 18 Aug 2024
Abstract
Traditional mean-variance (MV) models, considered effective in stable conditions, often prove inadequate in uncertain market scenarios. Therefore, there is a need for more robust and better portfolio optimization methods to handle the fluctuations and uncertainties in asset returns and covariances. This study aims
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Traditional mean-variance (MV) models, considered effective in stable conditions, often prove inadequate in uncertain market scenarios. Therefore, there is a need for more robust and better portfolio optimization methods to handle the fluctuations and uncertainties in asset returns and covariances. This study aims to perform a Systematic Literature Review (SLR) on robust portfolio mean-variance (RPMV) in stock investment utilizing genetic algorithms (GAs). The SLR covered studies from 1995 to 2024, allowing a thorough analysis of the evolution and effectiveness of robust portfolio optimization methods over time. The method used to conduct the SLR followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The result of the SLR presented a novel strategy to combine robust optimization methods and a GA in order to enhance RPMV. The uncertainty parameters, cardinality constraints, optimization constraints, risk-aversion parameters, robust covariance estimators, relative and absolute robustness, and parameters adopted were unable to develop portfolios capable of maintaining performance despite market uncertainties. This led to the inclusion of GAs to solve the complex optimization problems associated with RPMV efficiently, as well as fine-tuning parameters to improve solution accuracy. In three papers, the empirical validation of the results was conducted using historical data from different global capital markets such as Hang Seng (Hong Kong), Data Analysis Expressions (DAX) 100 (Germany), the Financial Times Stock Exchange (FTSE) 100 (U.K.), S&P 100 (USA), Nikkei 225 (Japan), and the Indonesia Stock Exchange (IDX), and the results showed that the RPMV model optimized with a GA was more stable and provided higher returns compared with traditional MV models. Furthermore, the proposed method effectively mitigated market uncertainties, making it a valuable tool for investors aiming to optimize portfolios under uncertain conditions. The implications of this study relate to handling uncertainty in asset returns, dynamic portfolio parameters, and the effectiveness of GAs in solving portfolio optimization problems under uncertainty, providing near-optimal solutions with relatively lower computational time.
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(This article belongs to the Special Issue Quantitative Finance and Risk Management Research: 2nd Edition)
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Open AccessArticle
Numerical Modeling and Simulation of Vehicular Crashes into Three-Bar Metal Bridge Rail
by
Howie Fang, Christopher Jaus, Qian Wang, Emre Palta, Lukasz Pachocki and Dawid Bruski
Computation 2024, 12(8), 165; https://doi.org/10.3390/computation12080165 - 17 Aug 2024
Abstract
Advanced finite element (FE) modeling and simulations were performed on vehicular crashes into a three-bar metal bridge rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing
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Advanced finite element (FE) modeling and simulations were performed on vehicular crashes into a three-bar metal bridge rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing Safety Hardware (MASH) Test Level 2 (TL-2) and Test Level 3 (TL-3) requirements. The test vehicle models were first validated using full-scale physical crash tests conducted on a two-bar metal bridge using a sedan and a pickup truck with similar overall physical properties and sizes to their respective vehicles used in the simulations. The validated vehicular models were then used to evaluate the crash performance of the TMBR using MASH evaluation criteria for structural adequacy, occupant risk, and post-impact trajectory. The TMBR met all MASH TL-2 requirements but failed to meet the MASH TL-3 Criteria H and N requirements when impacted by the sedan. The TMBR was also evaluated under in-service conditions (behind a 1.52 m wide sidewalk) and impacted by the sedan under MASH TL-3 conditions. The simulation results showed that the TMBR behind a sidewalk met all safety requirements except for the occupant impact velocity in the longitudinal direction, which exceeded the MASH limit by 3.93%.
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(This article belongs to the Special Issue Advances in Crash Simulations: Modeling, Analysis, and Applications)
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Remarks on the Connection of the Riemann Hypothesis to Self-Approximation
by
Antanas Laurinčikas
Computation 2024, 12(8), 164; https://doi.org/10.3390/computation12080164 - 14 Aug 2024
Abstract
By the Bagchi theorem, the Riemann hypothesis (all non-trivial zeros lie on the critical line) is equivalent to the self-approximation of the function by shifts . In this paper, it is determined
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By the Bagchi theorem, the Riemann hypothesis (all non-trivial zeros lie on the critical line) is equivalent to the self-approximation of the function by shifts . In this paper, it is determined that the Riemann hypothesis is equivalent to the positivity of density of the set of the above shifts approximating with all but at most countably many accuracies . Also, the analogue of an equivalent in terms of positive density in short intervals is discussed.
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