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Computation
Volume 12
Issue 12
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Computation, Volume 12, Issue 12 (December 2024) – 20 articles

Cover Story (view full-size image): Quantum mechanics/molecular mechanics (QM/MM) umbrella sampling molecular dynamics (MD) simulations give us an important clue about the transition states of chemical reactions and their free energy levels. By applying this method to the chiral-selective aminoacylation of an RNA minihelix (primitive form of tRNA), we elucidated, for the first time, the “flowing” atomistic mechanisms of the reaction and showed that the left-handed amino acid (L-alanine) moiety stabilizes the transition state more than the right-handed amino acid (D-alanine), resulting in L-alanine preference in the aminoacylation reaction in the RNA. Our results provided an important clue to the origin of “homochirality”, in which proteins in biological systems are composed exclusively of left-handed amino acids. View this paper
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15 pages, 12297 KiB  
Article
Enhancing Accessibility: Automated Tactile Graphics Generation for Individuals with Visual Impairments
by Yehor Dzhurynskyi, Volodymyr Mayik and Lyudmyla Mayik
Computation 2024, 12(12), 251; https://doi.org/10.3390/computation12120251 - 23 Dec 2024
Viewed by 261
Abstract
This study addresses the accessibility challenges faced by individuals with visual impairments due to limited access to graphic information, which significantly impacts their educational and social integration. Traditional methods for producing tactile graphics are labor-intensive and require specialized expertise, limiting their availability. Recent [...] Read more.
This study addresses the accessibility challenges faced by individuals with visual impairments due to limited access to graphic information, which significantly impacts their educational and social integration. Traditional methods for producing tactile graphics are labor-intensive and require specialized expertise, limiting their availability. Recent advancements in generative models, such as GANs, diffusion models, and VAEs, offer potential solutions to automate the creation of tactile images. In this work, we propose a novel generative model conditioned on text prompts, integrating a Bidirectional and Auto-Regressive Transformer (BART) and Vector Quantized Variational Auto-Encoder (VQ-VAE). This model transforms textual descriptions into tactile graphics, addressing key requirements for legibility and accessibility. The model’s performance was evaluated using cross-entropy, perplexity, mean square error, and CLIP Score metrics, demonstrating its ability to generate high-quality, customizable tactile images. Testing with educational and rehabilitation institutions confirmed the practicality and efficiency of the system, which significantly reduces production time and requires minimal operator expertise. The proposed approach enhances the production of inclusive educational materials, enabling improved access to quality education and fostering greater independence for individuals with visual impairments. Future research will focus on expanding the training dataset and refining the model for complex scenarios. Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Public Health)
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19 pages, 314 KiB  
Article
Development of Blockchain Technology in Financial Accounting
by Olha Prokopenko, Artem Koldovskiy, Marina Khalilova, Aigul Orazbayeva and José Machado
Computation 2024, 12(12), 250; https://doi.org/10.3390/computation12120250 - 23 Dec 2024
Viewed by 375
Abstract
This study investigates the transformative potential of blockchain technology in financial accounting by examining its applications, challenges, and implications. The study begins with a review of blockchain’s origins and its ability to address inefficiencies, fraud risks, and transparency limitations in traditional accounting. A [...] Read more.
This study investigates the transformative potential of blockchain technology in financial accounting by examining its applications, challenges, and implications. The study begins with a review of blockchain’s origins and its ability to address inefficiencies, fraud risks, and transparency limitations in traditional accounting. A mixed-methods approach was employed, combining qualitative thematic analysis and quantitative statistical techniques. The qualitative analysis involved thematic coding of data from case studies and organizational reports, while the quantitative analysis assessed financial data using descriptive and inferential statistical methods. Eight organizations from diverse industries—including banking, retail, and technology—were purposively sampled to capture varied experiences and applications of blockchain technology. Key findings reveal blockchain’s ability to enhance transparency, efficiency, and security in financial transactions, offering significant advantages for financial reporting and auditing. However, challenges such as regulatory uncertainties, scalability concerns, and technical complexities remain barriers to its widespread adoption. This research provides actionable recommendations to overcome these challenges and maximize blockchain’s benefits in financial accounting. By integrating theoretical insights with empirical evidence, this study contributes to advancing the understanding of blockchain’s role in transforming financial practices, offering practical guidance for academia and industry practitioners alike. Full article
(This article belongs to the Section Computational Social Science)
18 pages, 930 KiB  
Case Report
Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform
by Nikoletta Samaridi, Evangelos Papakitsos and Nikitas Karanikolas
Computation 2024, 12(12), 249; https://doi.org/10.3390/computation12120249 - 23 Dec 2024
Viewed by 251
Abstract
One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek [...] Read more.
One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek language and, given the scientifically certified usability of the ontological structuring of data in the field of the semantic web and cognitive computing, a new ontology of the Modern Greek language at the level of structure and vocabulary is presented in this paper, using the Protégé platform. With the specific logical and structured form of knowledge representation to express, this research processes and exploits in an easy and useful way the distributed semantics of linguistic information. Full article
(This article belongs to the Special Issue Recent Advances on Computational Linguistics and Natural Language Processing)
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21 pages, 7605 KiB  
Article
Additive Manufacturing Gyroid Structures Used as Crash Energy Management
by Horacio Rostro-González, Guillermo Reyes-Pozo, Josep Maria Puigoriol-Forcada, Francisco-José López-Valdés, Sriharsha Srinivas Sundarram and Andres-Amador Garcia-Granada
Computation 2024, 12(12), 248; https://doi.org/10.3390/computation12120248 - 19 Dec 2024
Viewed by 459
Abstract
Gyroid-like structures are promising in terms of energy absorption levels. Due to additive manufacturing, they can now be manufactured and verified for different functions. In this article, it has been proven that a Gyroid manufactured by FDM using PLA with 0.2 relative density [...] Read more.
Gyroid-like structures are promising in terms of energy absorption levels. Due to additive manufacturing, they can now be manufactured and verified for different functions. In this article, it has been proven that a Gyroid manufactured by FDM using PLA with 0.2 relative density must be oriented so that compression takes place along the build direction to obtain higher levels of force and energy. The Gyroid can be scaled, allowing the use of a single compression curve with almost constant forces up to 50% compression. The model to predict properties as a function of relative density fits well with a power-law for n = 2.2. The ability of the Gyroid to absorb energy per kilogram is about seven times lower than that of a solid PLA cube, but it can be used to obtain desired levels of deceleration. It is possible to use a simple constant deceleration model to define the Gyroid size, mass, and velocity of the object to be impacted. The use of this approach allows the tailored combination of Gyroid sizes to meet multi-objective impact targets. The simulation of impacts with a finite element model of only 125 solid elements is possible with errors below 10%. By combining different Gyroid sizes, two different safety regulations can be met. Modeling the Gyroid by meshing the real geometry allows for the local maximum force magnified at high strain rates, but it is not able to correctly predict densification. Full article
(This article belongs to the Special Issue Advances in Crash Simulations: Modeling, Analysis, and Applications)
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21 pages, 2773 KiB  
Article
Comparative Analysis of Energy Efficiency in Conventional, Modular, and 3D-Printing Construction Using Building Information Modeling and Multi-Criteria Decision-Making
by Abdullah Al Masri, Assed N. Haddad and Mohammad K. Najjar
Computation 2024, 12(12), 247; https://doi.org/10.3390/computation12120247 - 18 Dec 2024
Viewed by 454
Abstract
Energy efficiency has become a crucial focus with the growing attention on sustainable development and decreasing energy consumption in the built environment. Different construction methods are being applied worldwide, such as conventional, modular, and 3D-printing methods, to increase energy efficiency in buildings. This [...] Read more.
Energy efficiency has become a crucial focus with the growing attention on sustainable development and decreasing energy consumption in the built environment. Different construction methods are being applied worldwide, such as conventional, modular, and 3D-printing methods, to increase energy efficiency in buildings. This study aims to enhance the decision-making process by identifying optimal construction techniques, material selection, and ventilation window dimensions to promote sustainable energy use in buildings. A novel framework combining Building Information Modeling (BIM), computational analysis, and Multi-Criteria Decision-Making (MCDM) approaches is applied to assess the energy use intensity (EUI), annual electric energy consumption, and lifecycle energy cost across multiple sequences for each type of construction. Computational analysis in this research is combined in two main tools. Minitab is utilized for experimental design to determine the number and configurations of sequences analyzed. The Simple Additive Weighting (SAW) method, applied as an MCDM tool, is used to assess and rank the performance of sequences based on equally weighted criteria. Subsequently, 3D models of case study buildings are developed, and energy simulations are conducted using Autodesk Revit and Autodesk Green Building Studio, respectively, as BIM tools to compare the energy performance of various design alternatives. The results revealed that 3D printing surpassed other methods, where Sequence 7 achieved approximately 10.3% higher efficiency than modular methods and 40.5% better performance than conventional methods in the evaluated criteria. The findings underscore the higher energy efficiency of 3D printing, followed by modular construction as a competitive method, while conventional methods lagged significantly. Full article
(This article belongs to the Special Issue Applications of Intelligent Computing and Modeling in Construction Engineering)
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12 pages, 5871 KiB  
Article
Classical Chaos in a Driven One-Dimensional Quartic Anharmonic Oscillator
by Yun-Hsi Lin and Jeng-Da Chai
Computation 2024, 12(12), 246; https://doi.org/10.3390/computation12120246 - 17 Dec 2024
Viewed by 356
Abstract
In this work, we investigate the transition from regular dynamics to chaotic behavior in a one-dimensional quartic anharmonic classical oscillator driven by a time-dependent external square-wave force. Owing to energy conservation, the motion of an undriven quartic anharmonic oscillator is regular, periodic, and [...] Read more.
In this work, we investigate the transition from regular dynamics to chaotic behavior in a one-dimensional quartic anharmonic classical oscillator driven by a time-dependent external square-wave force. Owing to energy conservation, the motion of an undriven quartic anharmonic oscillator is regular, periodic, and stable. For a driven quartic anharmonic oscillator, the equations of motion cannot be solved analytically due to the presence of an anharmonic term in the potential energy function. Using the fourth-order Runge–Kutta method to numerically solve the equations of motion for the driven quartic anharmonic oscillator, we find that the oscillator motion under the influence of a sufficiently small driving force remains regular, while by gradually increasing the driving force, a series of nonlinear resonances can occur, grow, overlap, and ultimately disappear due to the emergence of chaos. Full article
(This article belongs to the Special Issue Mathematical Modeling and Study of Nonlinear Dynamic Processes)
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18 pages, 6754 KiB  
Article
A Novel Megastable Chaotic System with Hidden Attractors and Its Parameter Estimation Using the Sparrow Search Algorithm
by Atefeh Ahmadi, Vijeesh Vijayan, Hayder Natiq, Alexander N. Pchelintsev, Karthikeyan Rajagopal and Sajad Jafari
Computation 2024, 12(12), 245; https://doi.org/10.3390/computation12120245 - 15 Dec 2024
Viewed by 372
Abstract
This work proposes a new two-dimensional dynamical system with complete nonlinearity. This system inherits its nonlinearity from trigonometric and hyperbolic functions like sine, cosine, and hyperbolic sine functions. This system gives birth to infinite but countable coexisting attractors before and after being forced. [...] Read more.
This work proposes a new two-dimensional dynamical system with complete nonlinearity. This system inherits its nonlinearity from trigonometric and hyperbolic functions like sine, cosine, and hyperbolic sine functions. This system gives birth to infinite but countable coexisting attractors before and after being forced. These two megastable systems differ in the coexisting attractors’ type. Only limit cycles are possible in the autonomous version, but torus and chaotic attractors can emerge after transforming to the nonautonomous version. Because of the position of equilibrium points in different attractors’ attraction basins, this system can simultaneously exhibit self-excited and hidden coexisting attractors. This system’s dynamic behaviors are studied using state space, bifurcation diagram, Lyapunov exponents (LEs) spectrum, and attraction basins. Finally, the forcing term’s amplitude and frequency are unknown parameters that need to be found. The sparrow search algorithm (SSA) is used to estimate these parameters, and the cost function is designed based on the proposed system’s return map. The simulation results show this algorithm’s effectiveness in identifying and estimating parameters of the novel megastable chaotic system. Full article
(This article belongs to the Special Issue Mathematical Modeling and Study of Nonlinear Dynamic Processes)
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37 pages, 1647 KiB  
Article
Inventory Model for Instantaneously Deteriorating Items with Multiple Trade Facilities, Stock- and Price-Dependent Demand, and Full Backlogging
by Rabeya Sarker, Md. Sharif Uddin, Md Abu Helal, Aminur Rahman Khan, Ali AlArjani and El-Awady Attia
Computation 2024, 12(12), 244; https://doi.org/10.3390/computation12120244 - 12 Dec 2024
Viewed by 562
Abstract
This paper formulates six inventory models for products with instantaneous deterioration, focusing on the impacts of full and partial advance payment structures. The demand function depends on both price and stock levels and accounts for shortages through full backlogging. The primary objective is [...] Read more.
This paper formulates six inventory models for products with instantaneous deterioration, focusing on the impacts of full and partial advance payment structures. The demand function depends on both price and stock levels and accounts for shortages through full backlogging. The primary objective is to determine the optimal payment policy under varying trade facilities, analyzing six distinct payment scenarios commonly employed in business practice. Each model is presented with closed-form solutions and supported by mathematical formulations. For each case, algorithms and mathematical proofs are developed to determine the optimal cycle duration and corresponding unit cost. Numerical examples and 2D graphical representations generated using MATLAB are included to validate the proposed models. Additionally, a sensitivity analysis is conducted to examine the effects of each payment policy and parameter variation, providing key managerial insights into payment planning in inventory management. Full article
(This article belongs to the Section Computational Social Science)
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16 pages, 2062 KiB  
Article
Numerical Determination of a Time-Dependent Boundary Condition for a Pseudoparabolic Equation from Integral Observation
by Miglena N. Koleva and Lubin G. Vulkov
Computation 2024, 12(12), 243; https://doi.org/10.3390/computation12120243 - 11 Dec 2024
Viewed by 483
Abstract
The third-order pseudoparabolic equations represent models of filtration, the movement of moisture and salts in soils, heat and mass transfer, etc. Such non-classical equations are often referred to as Sobolev-type equations. We consider an inverse problem for identifying an unknown time-dependent boundary condition [...] Read more.
The third-order pseudoparabolic equations represent models of filtration, the movement of moisture and salts in soils, heat and mass transfer, etc. Such non-classical equations are often referred to as Sobolev-type equations. We consider an inverse problem for identifying an unknown time-dependent boundary condition in a two-dimensional linear pseudoparabolic equation from integral-type measured output data. Using the integral measurements, we reduce the two-dimensional inverse problem to a one-dimensional problem. Then, we apply appropriate substitution to overcome the non-local nature of the problem. The inverse ill-posed problem is reformulated as a direct well-posed problem. The well-posedness of the direct and inverse problems is established. We develop a computational approach for recovering the solution and unknown boundary function. The results from numerical experiments are presented and discussed. Full article
(This article belongs to the Special Issue Mathematical Modeling and Study of Nonlinear Dynamic Processes)
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19 pages, 1354 KiB  
Article
Assessing the Impact of Psyllid Pesticide Resistance on the Spread of Citrus Huanglongbing and Its Ecological Paradox
by Runyun Gan, Youquan Luo and Shujing Gao
Computation 2024, 12(12), 242; https://doi.org/10.3390/computation12120242 - 5 Dec 2024
Viewed by 572
Abstract
Excessive use of pesticides can lead to pesticide resistance in citrus psyllids, and studies have shown that this resistance is related to population genetics. This article proposes a dynamic model of Huanglongbing (HLB) that integrates the population genetics of the citrus psyllid vector [...] Read more.
Excessive use of pesticides can lead to pesticide resistance in citrus psyllids, and studies have shown that this resistance is related to population genetics. This article proposes a dynamic model of Huanglongbing (HLB) that integrates the population genetics of the citrus psyllid vector and considers the fitness cost associated with pesticide resistance to study how pesticide use affects the development of pesticide resistance at the population level. The basic reproduction number is introduced as a metric to assess whether HLB can be effectively controlled. Additionally, this article explores the impact of different parameters on the spread of HLB. Numerical simulations illustrate that the basic reproduction number decreases as the fitness cost of resistance increases, while an increase in the resistance index leads to an increase in the basic reproduction number. However, when the fitness cost is sufficiently high, a larger resistance index may result in a basic reproduction number less than 1, leading to the extinction of Asian citrus psyllid (ACP), thus causing a paradox effect. Full article
(This article belongs to the Section Computational Biology)
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32 pages, 12061 KiB  
Article
Design of Trabecular Bone Mimicking Voronoi Lattice-Based Scaffolds and CFD Modelling of Non-Newtonian Power Law Blood Flow Behaviour
by Haja-Sherief N. Musthafa and Jason Walker
Computation 2024, 12(12), 241; https://doi.org/10.3390/computation12120241 - 5 Dec 2024
Viewed by 622
Abstract
Designing scaffolds similar to the structure of trabecular bone requires specialised algorithms. Existing scaffold designs for bone tissue engineering have repeated patterns that do not replicate the random stochastic porous structure of the internal architecture of bones. In this research, the Voronoi tessellation [...] Read more.
Designing scaffolds similar to the structure of trabecular bone requires specialised algorithms. Existing scaffold designs for bone tissue engineering have repeated patterns that do not replicate the random stochastic porous structure of the internal architecture of bones. In this research, the Voronoi tessellation method is applied to create random porous biomimetic structures. A volume mesh created from the shape of a Zygoma fracture acts as a boundary for the generation of random seed points by point spacing to create Voronoi cells and Voronoi diagrams. The Voronoi lattices were obtained by adding strut thickness to the Voronoi diagrams. Gradient Voronoi scaffolds of pore sizes (19.8 µm to 923 µm) similar to the structure of the trabecular bone were designed. A Finite Element Method-based computational fluid dynamics (CFD) simulation was performed on all designed Voronoi scaffolds to predict the pressure drops and permeability of non-Newtonian blood flow behaviour using the power law material model. The predicted permeability (0.33 × 10−9 m2 to 2.17 × 10−9 m2) values of the Voronoi scaffolds from the CFD simulation are comparable with the permeability of scaffolds and bone specimens from other research works. Full article
(This article belongs to the Section Computational Engineering)
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10 pages, 551 KiB  
Article
Theil’s Index of Inequality: Computation of Value-Validity Correction
by Tarald O. Kvålseth
Computation 2024, 12(12), 240; https://doi.org/10.3390/computation12120240 - 5 Dec 2024
Viewed by 440
Abstract
The Theil index is one of the most popular indices of economic inequality, one reason for which is no doubt due to its convenient additive decomposition property. One of its weaknesses, however, is its lack of any intuitively meaningful interpretations. Another, and more [...] Read more.
The Theil index is one of the most popular indices of economic inequality, one reason for which is no doubt due to its convenient additive decomposition property. One of its weaknesses, however, is its lack of any intuitively meaningful interpretations. Another, and more serious, limitation of Theil’s index, as argued in this paper, is its lack of the value-validity property. That is, this index does not meet a particular condition based on metric distances between income-share distributions required in order for the range of potential index values to provide true, realistic, and valid representations of the economic inequality characteristic. After outlining the value-validity condition, this paper derives a simple transformation of Theil’s index that meets this condition to a high degree of approximation. Randomly generated income-share distributions are used to demonstrate and verify the validity of the corrected index. The new index formulation, which is simply a power function of Theil’s index, can then be used to make appropriate and reliable representations of absolute and relative difference comparisons of economic inequalities. Full article
(This article belongs to the Section Computational Social Science)
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23 pages, 4695 KiB  
Article
Dynamic Modeling of Bacterial Cellulose Production Using Combined Substrate- and Biomass-Dependent Kinetics
by Alejandro Rincón, Fredy E. Hoyos and John E. Candelo-Becerra
Computation 2024, 12(12), 239; https://doi.org/10.3390/computation12120239 - 3 Dec 2024
Viewed by 507
Abstract
In this work, kinetic models are assessed to describe bacterial cellulose (BC) production, substrate consumption, and biomass growth by K. xylinus in a batch-stirred tank bioreactor, under 700 rpm and 500 rpm agitation rates. The kinetic models commonly used for Acetobacter or Gluconacetobacter [...] Read more.
In this work, kinetic models are assessed to describe bacterial cellulose (BC) production, substrate consumption, and biomass growth by K. xylinus in a batch-stirred tank bioreactor, under 700 rpm and 500 rpm agitation rates. The kinetic models commonly used for Acetobacter or Gluconacetobacter were fitted to published data and compared using the Akaike Information Criterion (AIC). A stepwise fitting procedure was proposed for model selection to reduce computation effort, including a first calibration in which only the biomass and substrate were simulated, a selection of the three most effective models in terms of AIC, and a calibration of the three selected models with the simulation of biomass, substrate, and product. Also, an uncoupled product equation involving a modified Monod substrate function is proposed for a 500 rpm agitation rate, leading to an improved prediction of BC productivity. The M2c and M1c models were the most efficient for biomass growth and substrate consumption for the combined AIC, under 700 rpm and 500 rpm agitation rates, respectively. The average coefficients of determination for biomass, substrate, and product predictions were 0.981, 0.994, and 0.946 for the 700 rpm agitation rate, and 0.984, 0.991, and 0.847 for the 500 rpm agitation rate. It is shown that the prediction of BC productivity is improved through the proposed substrate function, whereas the computation effort is reduced through the proposed model fitting procedure. Full article
(This article belongs to the Section Computational Biology)
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10 pages, 9289 KiB  
Perspective
Quantum Mechanics/Molecular Mechanics Simulations for Chiral-Selective Aminoacylation: Unraveling the Nature of Life
by Tadashi Ando and Koji Tamura
Computation 2024, 12(12), 238; https://doi.org/10.3390/computation12120238 - 2 Dec 2024
Viewed by 666
Abstract
Biological phenomena are chemical reactions, which are inherently non-stopping or “flowing” in nature. Molecular dynamics (MD) is used to analyze the dynamics and energetics of interacting atoms, but it cannot handle chemical reactions involving bond formation and breaking. Quantum mechanics/molecular mechanics (QM/MM) umbrella [...] Read more.
Biological phenomena are chemical reactions, which are inherently non-stopping or “flowing” in nature. Molecular dynamics (MD) is used to analyze the dynamics and energetics of interacting atoms, but it cannot handle chemical reactions involving bond formation and breaking. Quantum mechanics/molecular mechanics (QM/MM) umbrella sampling MD simulations gives us a significant clue about transition states of chemical reactions and their energy levels, which are the pivotal points in understanding the nature of life. To demonstrate the importance of this method, we present here the results of our application of it to the elucidation of the mechanism of chiral-selective aminoacylation of an RNA minihelix considered to be a primitive form of tRNA. The QM/MM MD simulation, for the first time, elucidated the “flowing” atomistic mechanisms of the reaction and indicated that the L-Ala moiety stabilizes the transition state more than D-Ala, resulting in L-Ala preference in the aminoacylation reaction in the RNA. The QM/MM method not only provides important clues to the elucidation of the origin of homochirality of biological systems, but also is expected to become an important tool that will play a critical role in the analysis of biomolecular reactions, combined with the development of artificial intelligence. Full article
(This article belongs to the Section Computational Biology)
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22 pages, 1650 KiB  
Article
Interpretable Conversation Routing via the Latent Embeddings Approach
by Daniil Maksymenko and Oleksii Turuta
Computation 2024, 12(12), 237; https://doi.org/10.3390/computation12120237 - 1 Dec 2024
Viewed by 447
Abstract
Large language models (LLMs) are quickly implemented to answer question and support systems to automate customer experience across all domains, including medical use cases. Models in such environments should solve multiple problems like general knowledge questions, queries to external sources, function calling and [...] Read more.
Large language models (LLMs) are quickly implemented to answer question and support systems to automate customer experience across all domains, including medical use cases. Models in such environments should solve multiple problems like general knowledge questions, queries to external sources, function calling and many others. Some cases might not even require a full-on text generation. They possibly need different prompts or even different models. All of it can be managed by a routing step. This paper focuses on interpretable few-shot approaches for conversation routing like latent embeddings retrieval. The work here presents a benchmark, a sorrow analysis, and a set of visualizations of the way latent embeddings routing works for long-context conversations in a multilingual, domain-specific environment. The results presented here show that the latent embeddings router is able to achieve performance on the same level as LLM-based routers with additional interpretability and higher level of control over model decision-making. Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Public Health)
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18 pages, 1427 KiB  
Article
Asymptotic and Probabilistic Perturbation Analysis of Controllable Subspaces
by Vera Angelova, Mihail Konstantinov and Petko Petkov
Computation 2024, 12(12), 236; https://doi.org/10.3390/computation12120236 - 28 Nov 2024
Viewed by 379
Abstract
In this paper, we consider the sensitivity of the controllable subspaces of single-input linear control systems to small perturbations of the system matrices. The analysis is based on the strict component-wise asymptotic bounds for the matrix of the orthogonal transformation to canonical form [...] Read more.
In this paper, we consider the sensitivity of the controllable subspaces of single-input linear control systems to small perturbations of the system matrices. The analysis is based on the strict component-wise asymptotic bounds for the matrix of the orthogonal transformation to canonical form derived by the method of the splitting operators. The asymptotic bounds are used to obtain probabilistic bounds on the angles between perturbed and unperturbed controllable subspaces implementing the Markoff inequality. It is demonstrated that the probability bounds allow us to obtain sensitivity estimates, which are much tighter than the usual deterministic bounds. The analysis is illustrated by a high-order example. Full article
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27 pages, 2988 KiB  
Article
UAV Mission Computer Operation Mode Optimization Focusing on Computational Energy Efficiency and System Responsiveness
by Oleksandr Liubimov, Ihor Turkin, Valeriy Cheranovskiy and Lina Volobuieva
Computation 2024, 12(12), 235; https://doi.org/10.3390/computation12120235 - 27 Nov 2024
Viewed by 592
Abstract
The rising popularity of UAVs and other autonomous control systems coupled with real-time operating systems has increased the complexity of developing systems with the proper robustness, performance, and reactivity. The growing demand for more sophisticated computational tasks, proportionally larger payloads, battery limitations, and [...] Read more.
The rising popularity of UAVs and other autonomous control systems coupled with real-time operating systems has increased the complexity of developing systems with the proper robustness, performance, and reactivity. The growing demand for more sophisticated computational tasks, proportionally larger payloads, battery limitations, and smaller take-off mass requires higher energy efficiency for all avionics and mission computers. This paper aims to develop a technique for experimentally studying the indicators of reactivity and energy consumption in a computing platform for unmanned aerial vehicles (UAVs). The paper provides an experimental assessment of the ‘Boryviter 0.1’ computing platform, which is implemented on the ATSAMV71 microprocessor and operates under the open-source FreeRTOS operating system. The results are the basis for developing algorithms and energy-efficient design strategies for the mission computer to solve the optimization problem. This paper provides experimental results of measurements of the energy consumed by the microcontroller and estimates of the reduction in system energy consumption due to additional time costs for suspending and resuming the computer’s operation. The results show that the ‘Boryviter 0.1’ computing platform can be used as a UAV mission computer for typical flight control tasks requiring real-time computing under the influence of external factors. As a further work direction, we plan to investigate the proposed energy-saving algorithms within the planned NASA F’Prime software flight framework. Such an investigation, which should use the mission computer’s actual flight computation load, will help to qualify the obtained energy-saving methods and their implementation results. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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23 pages, 5123 KiB  
Article
Application of Smart Condensed H-Adsorption Nanocomposites in Batteries: Energy Storage Systems and DFT Computations
by Fatemeh Mollaamin and Majid Monajjemi
Computation 2024, 12(12), 234; https://doi.org/10.3390/computation12120234 - 27 Nov 2024
Viewed by 504
Abstract
A comprehensive investigation of hydrogen grabbing towards the formation of hetero-clusters of AlGaN–H, Si–AlGaN–H, Ge–AlGaN–H, Pd–AlGaN–H, and Pt–AlGaN–H was carried out using DFT computations at the CAM–B3LYP–D3/6-311+G (d,p) level of theory. The notable fragile signal intensity close to the parallel edge of the [...] Read more.
A comprehensive investigation of hydrogen grabbing towards the formation of hetero-clusters of AlGaN–H, Si–AlGaN–H, Ge–AlGaN–H, Pd–AlGaN–H, and Pt–AlGaN–H was carried out using DFT computations at the CAM–B3LYP–D3/6-311+G (d,p) level of theory. The notable fragile signal intensity close to the parallel edge of the nanocluster sample might be owing to silicon or germanium binding-induced non-spherical distribution of Si–AlGaN or Ge–AlGaN hetero-clusters. Based on TDOS, the excessive growth technique of doping silicon, germanium, palladium, or platinum is a potential approach to designing high-efficiency hybrid semipolar gallium nitride devices in a long-wavelength zone. Therefore, it can be considered that palladium or platinum atoms in the functionalized Pd–AlGaN or Pt–AlGaN might have more impressive sensitivity for accepting the electrons in the process of hydrogen adsorption. The advantages of platinum or palladium over aluminum gallium nitride include its higher electron and hole mobility, allowing platinum or palladium doping devices to operate at higher frequencies than silicon or germanium doping devices. In fact, it can be observed that doped hetero-clusters of Pd–AlGaN or Pt–AlGaN might ameliorate the capability of AlGaN in transistor cells for energy storage. Full article
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40 pages, 773 KiB  
Article
Multiple Behavioral Conditions of the Forward Exchange Rates and Stock Market Return in the South Asian Stock Markets During COVID-19: A Novel MT-QARDL Approach
by Mosab I. Tabash, Adel Ahmed, Suzan Sameer Issa, Marwan Mansour, Manishkumar Varma and Mujeeb Saif Mohsen Al-Absy
Computation 2024, 12(12), 233; https://doi.org/10.3390/computation12120233 - 26 Nov 2024
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Abstract
This study examines the short- and long-term effects of multiple quantiles of forward exchange rate premiums (FERPs) and COVID-19 cases on the quantiles of stock market returns (SMRs). We extend the Quantile Autoregressive Distributive Lag (QARDL) model, and the Multiple Threshold Non-linear Autoregressive [...] Read more.
This study examines the short- and long-term effects of multiple quantiles of forward exchange rate premiums (FERPs) and COVID-19 cases on the quantiles of stock market returns (SMRs). We extend the Quantile Autoregressive Distributive Lag (QARDL) model, and the Multiple Threshold Non-linear Autoregressive Distributive Lag (NARDL) model propose a new Multiple Threshold Quantile Autoregressive Distributive Lag (MT-QARDL) approach. Unlike MT-NARDL, QARDL, and NARDL, the MT-QARDL model, which integrates the MT-NARDL model and the quantile regression methodology, captures both short- and long-term locational and sign-based asymmetries. For instance, at lower quantiles for Indian and Sri Lankan SMRs, bearish FERP exerts a positive influence, while bullish FERP has a negative effect during COVID-19. Conversely, bullish FERP negatively affects lower quantiles of SMRs of Bangladesh, India, and Sri Lanka, whereas bearish FERP either yields an opposite effect or remain statistically insignificant during COVID-19. The findings underscore long-term sign-based asymmetries due to the differential bearish and bullish FERP impact during COVID-19. However, in the long term, location-based asymmetries also existed as bullish FERP negative influence the SMRs of India, Bangladesh and Sri Lanka at higher quantiles but SMRs at lower quantiles insignificantly respond to the bullish FERP fluctuations during COVID-19. Full article
(This article belongs to the Special Issue Computational Approaches in Corporate Finance, Risk Management and Financial Markets)
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13 pages, 5738 KiB  
Article
Automated Cervical Cancer Screening Using Single-Cell Segmentation and Deep Learning: Enhanced Performance with Liquid-Based Cytology
by Mariangel Rodríguez, Claudio Córdova, Isabel Benjumeda and Sebastián San Martín
Computation 2024, 12(12), 232; https://doi.org/10.3390/computation12120232 - 26 Nov 2024
Viewed by 750
Abstract
Cervical cancer (CC) remains a significant health issue, especially in low- and middle-income countries (LMICs). While Pap smears are the standard screening method, they have limitations, like low sensitivity and subjective interpretation. Liquid-based cytology (LBC) offers improvements but still relies on manual analysis. [...] Read more.
Cervical cancer (CC) remains a significant health issue, especially in low- and middle-income countries (LMICs). While Pap smears are the standard screening method, they have limitations, like low sensitivity and subjective interpretation. Liquid-based cytology (LBC) offers improvements but still relies on manual analysis. This study explored the potential of deep learning (DL) for automated cervical cell classification using both Pap smears and LBC samples. A novel image segmentation algorithm was employed to extract single-cell patches for training a ResNet-50 model. The model trained on LBC images achieved remarkably high sensitivity (0.981), specificity (0.979), and accuracy (0.980), outperforming previous CNN models. However, the Pap smear dataset model achieved significantly lower performance (0.688 sensitivity, 0.762 specificity, 0.8735 accuracy). This suggests that noisy and poor cell definition in Pap smears pose challenges for automated classification, whereas LBC provides better classifiable cells patches. These findings demonstrate the potential of AI-powered cervical cell classification for improving CC screening, particularly with LBC. The high accuracy and efficiency of DL models combined with effective segmentation can contribute to earlier detection and more timely intervention. Future research should focus on implementing explainable AI models to increase clinician trust and facilitate the adoption of AI-assisted CC screening in LMICs. Full article
(This article belongs to the Section Computational Engineering)
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