Computational Procedure Research Articles

Hierarchical Games and Computational Procedures in the Linear Case

Hierarchical Games and Computational Procedures in the Linear Case

NUMERICAL-ANALYTICAL METHOD OF DECOMPOSITION-AUTOCOMPENSATION FOR SOLVING THE SIGNAL RECOGNITION PROBLEM BASED ON INACCURATE OBSERVATIONS

A numerical-analytical method is developed to solve the problem of optimal recognition of a set of possible signals observed as an additive mixture containing not only a fluctuation observation error (with an unknown statistical distribution) but also a singular interference (with parametric uncertainty). The method allows for both the detection of signals present in the mixture and the estimation of their parameters within a specified quality criterion and associated constraints. The proposed method, based on the idea of generalized invariant-unbiased estimation of linear functional values, enables decomposition of the computational procedure and autocompensation of singular interference without resorting to the traditional expansion of the state space. Linear spectral decompositions in specified functional bases are used for the parametric finite-dimensional representation of signals and interference, while knowledge of the correlation matrix of the observation error is sufficient for error description. Random and systematic errors are analyzed, and an illustrative example is provided.

Optimizing the planning process in computed tomography-based image-guided adaptive brachytherapy for cervical cancer using a spreadsheet-based daily dose management system.

This study developed a system to reduce the treatment planning time for cervical cancer brachytherapy. An in-house Excel spreadsheet was developed to streamline dosimetric evaluation by combining external beam radiotherapy and brachytherapy doses, while also displaying daily dose constraints, a novel feature of the system. This system was validated in 46 consecutive patients who underwent intracavitary and interstitial brachytherapy using several applicators and required more complex dose calculation procedures than intracavitary brachytherapy alone. The proposed system included contouring and catheter reconstruction using multiple treatment planning systems simultaneously and was integrated with Excel spreadsheets for rapid dosimetric evaluation. The median time required for treatment planning was 36min (range: 12-72min), which was a much shorter time than those reported previously. This optimized system demonstrated the potential to increase the efficiency of brachytherapy planning to meet prescribed dose constraints without compromising treatment quality.

Low-cost rolling ball viscometer for the evaluation of Newtonian and shear-thinning fluids

Abstract This article describes the design and testing of a low-cost automatic rolling-ball viscometer. The device has been manufactured from three-dimensional printed parts and conventional and affordable mechanical and electronic components. It is controlled by an Arduino MEGA with a custom code that includes manual and automatic measuring modes. Both the type of viscometer and the models used are, in principle, valid for Newtonian and power-law fluids. However, measurement and calculation procedures have been developed that also makes it possible to determine the viscosity of Herschel–Bulkley fluids that might exhibit a yield stress behaviour within the range studied. By these procedures, viscosity values have been obtained for model fluids – Newtonian, power-law, and Herschel–Bulkley fluids – and compared to those obtained with a commercial rotational rheometer. The proposed setup and measuring method have thus proven to provide very reasonably accurate viscosity values for a low-cost device.

An Integrative Perspective on Algorithm Aversion and Appreciation in Decision-Making

People have conflicting responses for support from algorithms or humans in decision-making. On the one hand, they fail to benefit from algorithms due to algorithm aversion, as they reject decisions provided by algorithms more frequently than those made by humans. On the other hand, many prefer algorithmic over human advice, an effect of algorithm appreciation. However, currently, we lack a shared understanding of these constructs’ meaning and measurements, resulting in a lack of theoretical integration of empirical findings. Thus, in this research note, we conceptualize algorithm aversion as the preference for humans over algorithms in decision-making and analyze approaches in current research to measure this preference. First, we outline the implications of focusing on a specific understanding of algorithms as computational procedures or as embedded in material or nonmaterial objects. Then, we classify four decision configurations that distinguish individuals’ evaluations of algorithms, human advisors, their own judgments, or combinations of these. Consequently, we develop a classification scheme that provides guidance for future research to develop more specific hypotheses on the direction of preferences (aversion vs. appreciation) and the effect of moderators.

A novel approach using iterative g-function and chaotic cooperation search for accurate voltage calculation of double and triple diode solar cell models

The solar cells can be accurately represented via double and triple-diode models (DDM and TDM, respectively). In this paper, a novel iterative procedure based on applying the g-function is proposed for double and triple solar cell voltage calculation for the first time. The proposed iterative procedure is performed without any approximations, while its application overcomes numerical limitations when applying literature-accepted approaches based on the Lambert W function. Also, one notable advantage of the proposed procedure is its effectiveness with arbitrary starting point values. Second, in this paper, an original equation for calculating solar cells’ root mean square error (RMSE) voltage (RMSEU) in the DDM and TDM, which aids in parameter estimation, is proposed. Third, the paper introduces a new metaheuristic algorithm called the Chaotic Cooperation Search Algorithm (ChCSA) for estimating solar cell parameters. The proposed approach (iterative procedure for voltage-current representation as well as a novel algorithm) is tested on two well-known solar cells in the literature and on measured current-voltage characteristics for different weather conditions. Applying the proposed algorithm and the novel iterative procedure for DDM and TDM voltage calculations demonstrated the accuracy and efficiency of the proposed approach for solar cell parameter estimation. In order to achieve the appropriate accuracy, it was shown that only a few iterations of the proposed iterative procedure are needed for the majority of measurement points in both observed cells. Furthermore, the application of the proposed algorithm outperforms existing algorithms in solar cell parameter estimation. Moreover, with the well-known Photowatt-PWP 201 solar module, the application of the proposed algorithm enables the estimation of the parameters of the solar cell so that the RMSEU value is reduced by about 50 % compared to the results obtained for the parameters determined by numerous approaches from the literature. Therefore, the presented research offers a novel and original double and triple solar cell modeling perspective.

EWMA control chart framework for efficient Maxwell quality characteristic monitoring: An application to the aerospace industry

The Maxwell distribution is extensively employed in statistical modeling to analyze data, notably in the fields of chemistry, astrophysics, demography, actuarial sciences, economics, industry, and engineering. Recently, the application of the Maxwell data generating process (DGP) has focused extensively on the domain of statistical control charts. The V chart and VSQ chart are often used to identify unexpected changes in the distributional shift of the Maxwell process. The VSQ chart offers considerably better performance than the V chart for detecting moderate to large shifts in the scale parameter. However, the VSQ chart adopts the fundamental structure of the Shewhart monitoring scheme and is insensitive to small alterations in the target parameter. We propose a new control chart, namely, the Maxwell exponentially weighted moving average (MXEWMA) chart, for improved monitoring of quality attributes that are assumed to conform to Maxwell data generation. The factors used to design the parameters of the proposed chart are computed at different false alarm probabilities and across various sample sizes. The effectiveness of the suggested scheme is considered in terms of the different features of the run length (RL) distribution, including the average, median and standard deviation. A comparative study of the MXEWMA chart with the existing VSQ chart was performed across various sample sizes. The comparative analysis showed that the MXEWMA chart is an effective alternative and performs well in detecting reasonably small shifts in the parameter. Simulated data are employed to describe the computational procedure of the MXEWMA scheme. The simulation analysis demonstrated that the MXEWMA chart outperforms the existing method in identifying slight changes in the studied parameters. A real dataset is also considered to support the theoretical part of the work.

Computational Thinking Integrated in School Subjects – A Cross-Case Analysis of Students’ Experiences

The integration of computational thinking (CT) into K-12 education offers substantial potential to improve digital literacy and deepen students’ understanding across various subject areas. By embedding computational procedures and solution-oriented approaches into traditional curricula, students can develop essential skills that are critical for thriving in an increasingly digital world. However, the effective integration of CT into subject-specific learning poses challenges for educators, largely due to a lack of training and experience in implementing interdisciplinary instructional strategies. This study explores the impact of integrating CT into K-12 education through diverse instructional approaches, including modelling, storytelling, and unplugged activities. The research examines how students' subject knowledge, CT concepts, and practices evolved under each CT integration practice, as well as their acceptance toward CT integrated lessons. The study was conducted in different subjects, including language arts, biology, and physics, and at different grade levels. The technology acceptance model was used as a theoretical framework to understand students' adoption towards the different integration practices. The study revealed that different CT integration practices yield varying impacts on students' attitudes, particularly in relation to their prior programming experiences. Namely, primary school students with prior programming experience display a higher behavioural intention due to a lack of early biases toward programming. Conversely, secondary school students, less familiar with interdisciplinary approaches, initially show less enthusiasm for future engagement. These insights underscore the need for tailored instructional strategies that consider students' prior experiences and the broader goal of preparing them to contribute to a technologically driven society.

Is model-based dose calculation based on cone-beam computed tomography suitable for adaptive treatment planning in brachytherapy?

Model-based dose calculation considering tissue compositions is increasingly being investigated in brachytherapy. The aim of this study was to assess the suitability of modern cone-beam computed tomography (CBCT) imaging compared to conventional computed tomography (CT) scans for this purpose. By means of aphantom study, we evaluated the CT numbers and electron densities measured using amodern CBCT device as well as aconventional CT scanner for various materials. Based on this, we compared dose calculations (using the TG-43 formalism as well as model-based collapsed cone calculations assuming uniform materials [ACEuniform] and considering CT numbers [ACECT#]) on planning CTs and control CBCTs for patients with cervical and breast cancer as well as phantom-simulated skin cancer cases. Assessing dosimetric deviations between the planning CTs and control CBCTs acquired during the treatment course served to estimate interfractional implant variations. The comparison of ACEuniform-ACECT# deviations between planning CTs and control CBCTs revealed no statistically significant difference for almost all examined dose parameters. Dosimetric deviations between model-based dose calculations and TG-43 were partly significant but of small magnitude (< 10 cGy per fraction). Interfractional dosimetric variations were substantially larger than the dosimetric differences found between the various dose calculation procedures. Model-based dose calculation based on modern CBCT imaging was suitable. However, the found differences between these calculations and the TG-43 formalism should be investigated in dose-outcome analyses. The observed interfractional dosimetric variations revealed the importance of performing treatment quality assurance.

Unlocking Cognitive Analysis Potential in Alzheimer's Disease Clinical Trials: Investigating Hierarchical Linear Models for Analyzing Novel Measurement Burst Design Data.

Measurement burst designs typically administer brief cognitive tests four times per day for 1 week, resulting in a maximum of 28 data points per week per test for every 6 months. In Alzheimer's disease clinical trials, utilizing measurement burst designs holds great promise for boosting statistical power by collecting huge amount of data. However, appropriate methods for analyzing these complex datasets are not well investigated. Furthermore, the large amount of burst design data also poses tremendous challenges for traditional computational procedures such as SAS mixed or Nlmixed. We propose to analyze burst design data using novel hierarchical linear mixed effects models or hierarchical mixed models for repeated measures. Through simulations and real-world data applications using the novel SAS procedure Hpmixed, we demonstrate these hierarchical models' efficiency over traditional models. Our sample simulation and analysis code can serve as a catalyst to facilitate the methodology development for burst design data.

Assessment of the Load-Bearing Capacity of the Old Railway Bridge With Encased Steel Beams

The subject of this study is the inventory and assessment of the load-bearing capacity of a railway bridge. The analysis was conducted on a bridge with a concrete slab reinforced by steel beams as the load-bearing element. The structure is located in the village of Bukowina, Warmian-Masurian Voivodeship, Poland. The aim of the study is to assess the load-bearing capacity of the bridge. The structure’s geometry was measured, and its concrete strength class determined. This article presents the results of stress limitation calculations for the tested bridge. Three calculation procedures based on two approaches—a concrete-encased beam and a bending section reinforced with rigid inserts — were applied. The analysis demonstrated that, despite the unesthetic appearance of the bridge, it meets the stress limitation requirements. Though over a hundred years old, the structure remains suitable for use today.

Assessment of turbulence adjoint method in sensitivity calculation and aerodynamic design optimization of turbomachinery cascades

Adjoint-based optimization faces the challenges from sensitivity accuracy when applying in design optimization of turbomachinery cascades with strong turbulence flow. In the study, sensitivities of aerodynamic parameters of different cascades are calculated using the discrete adjoint method, which are then used for design optimization of the cascades. The principles of adjoint method are firstly introduced and the procedures of sensitivity calculation using discrete adjoint method are described. Aerodynamic sensitivities of a high-pressure-turbine cascade and a controlled-diffusion compressor cascade are calculated by both the turbulence adjoint and constant-eddy-viscosity (CEV) adjoint methods. Through comparisons against the sensitivities by finite difference method, the improved accuracy in sensitivity calculation by turbulence adjoint method is demonstrated. Moreover, at the off-design condition of the compressor cascade with intensified turbulence flow, more improvements in sensitivity accuracy are gained. Finally, aerodynamic design optimizations of these two cascades are conducted. The results illustrate that more gains in performance improvements can be obtained by turbulence adjoint method, especially in the optimization of compressor cascade at the off-design condition. The impacts of aerodynamic shape optimization on performance variations of the cascades are addressed.

Estimating lexical diversity using the moving average type-token ratio (MATTR): Pros and cons

Several recent studies have strongly recommended the use of the moving average type-token ratio (MATTR) to estimate the lexical diversity (LD) of a text because it is the only length-insensitive index that can compare texts of different sizes. After pointing out that a length-insensitive index was proposed in the 1960s and is still being used, I analyse the properties of the MATTR computational procedure that enable it to control for the effects of length. This index is an excellent choice for evaluating the fluctuation of the LD throughout a relatively long text. However, its use for evaluating the overall LD of a text is questionable because the impact of tokens on the score varies according to their position in the text. I illustrate this problem using pseudo-texts and show that this impact is likely to affect a significant proportion of texts by analysing the distribution of hapaxes in texts by learners of Italian, Czech, German and English as a second language (L2).

SIMPLIFIED METHOD FOR ESTIMATING A DYNAMIC LOADRATING FOR ROLLING BEARINGS

The method for calculating the dynamic load ratings of rolling bearings is described in the ISO 281 standard.The calculation procedure presented there requires reading appropriate values from many tables, dependingon the geometry of the bearing components. This approach makes numerical calculations and quick estimationof the dynamic load ratings for various bearing design variants difficult. Moreover, the tables are discrete(they provide selected values, e.g. for nominal bearing contact angles every 15), and intermediate values,in accordance with the commentary included in the ISO 281 standard, should be calculated using linearinterpolation. However, in reality, the parameters given in the tables are not linearly dependent on each other,which makes this interpolation inaccurate. In the context of the mentioned imperfections of the ISO 281standard, the aim of the work is to simplify the calculation procedure, adapt it to numerical applications,and replace linear interpolation with an appropriate non-linear function. The difference between the valuescalculated according to the proposed formula and the value calculated according to the ISO 281 standard is onaverage less than 0.5%.

Fast Type-II Hartley Transform Algorithms for Short-Length Input Sequences

This paper presents the type-II fast discrete Hartley transform (DHT-II) algorithms for input data sequences of lengths from 2 to 8. The starting point for developing the eight algorithms is the representation of DHT-II as a matrix–vector product. The underlying matrices usually have a good block structure. These matrices must then be successfully factorized to obtain a computational procedure that reduces the number of operations in computing the matrix–vector product. In some cases, it is necessary to pre-decompose the original matrices into submatrices and rearrange the rows and/or columns of the resulting matrices to find the factorizations that would substantially save the arithmetic operations. As a result of applying the pointed transformations, we synthesized the final algorithms with reduced computational complexity. The correctness of the obtained algorithmic solutions was theoretically justified using the rigorous mathematical background of each of them. Then, the complex algorithms were further tested using the MATLAB R2023b software to confirm their performance. Finally, an evaluation of the computational complexity for each obtained solution was compared with the computational complexity of the direct calculation of the matrix–vector product and existing fast DHT-II algorithms. The obtained factorizations of the DHT-II transformation matrices on average reduce the number of additions by 5% and the number of multiplications by 73% compared with the direct calculation of the matrix–vector product.

NUMERICAL SIMULATION IN CALCULATIONS OF TECHNOLOGICAL SYSTEMS OF ELECTROMAGNETIC PROCESSING. PART I: PROPAGATION OF THE ELECTROMAGNETIC FIELD

The article deals with the problem of numerical modeling when calculating electromagnetic field propagation in electromagnetic molding systems. From the analysis of open information sources, it follows that the problem of numerical modeling when creating new technological operations of electromagnetic molding or when improving existing ones is relevant in a scientific and practical sense. This is due to the need to perform adequate numerical modeling and computational analysis of technological systems and technological operations at the stage of creation and improvement. With regard to technological systems of electromagnetic processing, calculation schemes and models should make it possible to study the propagation of a non-stationary electromagnetic field and to study the processes of nonlinear deformation of technological elements, which is caused by the force interaction of the induced electromagnetic field with the field of the source. Adequate numerical modeling must be based on appropriate calculation procedures based on numerical methods. The article substantiates the need to use numerical methods for calculation analysis, which allow creating calculation schemes closer to reality to a greater extent compared to the case of using analytical approaches and methods. The most effective numerical method is the finite element method, which allows the analysis of the non-stationary electromagnetic field and deformation within the same calculation scheme. In this case, within the framework of the finite element method, iterative schemes can be created that allow taking into account nonlinear effects. Here, nonlinear effects can be caused by the dependence of the mechanical and electrophysical properties of the material on temperature, the plastic nature of the deformation, as well as the need to account for contact phenomena. The results of modeling the propagation of the electromagnetic field of a single-turn inductor are presented.

Synchronized motion of interface residues for evaluating protein-RNA complex binding affinity: Application to aptamer-mediated inhibition of TDP-43 aggregates.

Investigating the binding between proteins and aptamers, such as peptides or RNA molecules, is of crucial importance both for understanding the molecular mechanisms that regulate cellular activities and for therapeutic applications in several pathologies. Here, a new computational procedure, employing mainly docking, clustering analysis, and molecular dynamics simulations, was designed to estimate the binding affinities between a protein and some RNA aptamers, through the investigation of the dynamical behavior of the predicted molecular complex. Using the state-of-the-art software catRAPID, we computationally designed a set of RNA aptamers interacting with the TAR DNA-binding protein 43 (TDP-43), a protein associated with several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). We thus devised a computational protocol to predict the RNA-protein molecular complex, so that the structural and dynamical behavior of such a complex can be investigated through extensive molecular dynamics simulation. We hypothesized that the coordinated and synchronized motion of the protein-binding residues, when in contact with RNA molecule, is a critical requisite in order to have a stable binding. Indeed, we calculated the motion covariance exhibited by the interface residues during molecular dynamics simulation: we tested the results against experimental measurements of binding affinity (in this case, the dissociation constant) for six RNA molecules, resulting in a linear correlation of about 0.9. Our findings suggest that the synchronized movement of interface residues plays a pivotal role in ensuring the stability within RNA-protein complexes, moreover providing insights into the contribution of each interface residue. This promising pipeline could thus contribute to the design of RNA aptamers interacting with proteins.

Exploring the application of molecular simulation technology in food sector: Focusing on food component interactions and food quality

The intricate interactions between component molecules that occur during food processing and storage are challenging to elucidate with traditional experimental techniques at the molecular level. Molecular simulation technology, conversely, offer an expedient methodology for investigating these molecular behaviors and anticipating macroscopic experimental phenomena. This review outlines the fundamental principles of molecular simulation techniques commonly employed in the field of food science and their associated computational procedures. It also examines their applications in the context of food component interactions and the quality control of proteins, carbohydrates, and lipids. This technique can be employed to elucidate the interactions between food nutrients, facilitate the rapid detection of pesticide and veterinary drug residues, identify foodborne pathogens and biotoxins, and conduct molecular mechanism analysis of toxicological effects at the atomic and molecular levels. By dynamically characterizing changes in molecular conformation, electron transfer and bonding processes, molecular simulation has become an important tool for optimizing food processing and storage conditions. Further studies should investigate the relationship between molecular conformational changes and food quality in greater depth and seek to optimize the application of molecular simulation in food science in order to provide critical insights into practical operations.

Cluster Perturbation Theory for Core Excited States and Core Ionization Potentials Using Core-Valence Separation.

The development of accurate and fast computational procedures for the ab initio calculation of X-ray spectroscopies is paramount to facilitate theoretical analysis of modern X-ray experiments on molecules. Herein, we present the extension of Cluster Perturbation theory to comprehend the calculation of core excited states and core ionization potentials using the core-valence separation approximation, which has seen widespread success for various quantum chemistry methods. We derive the theoretical framework for introducing core-valence separation into Cluster Perturbation series for excitation energies and display the performance of the methodology in S(D) orbital excitation spaces. The obtained core excitation energies on a test set of medium sized organic molecules show that carbon, nitrogen, and oxygen K-edge excitation energies can be determined with errors below 2 eV relative to the CCSD reference results using the developed CPS(D) excitation energy models which can be used for systems way beyond the reach of conventional CCSD.

Green extraction of prostaglandin analogs in cosmetics using deep eutectic solvents and detection via LC-MS/MS

Prostaglandin analogs (bimatoprost, travoprost, tafluprost, etc.) have similar effects to prostaglandins and are effective drugs for treating glaucoma. These compounds exhibit abnormal reactions such as causing eyelash growth, with several cases being reported of people purchasing them to increase eyelash growth; however, some cases have reported side effects such as pigmentation and dry eyes. In the Republic of Korea, cosmetics are not medicines for treating diseases; therefore, cosmetics cannot contain drugs or have labels that could mislead people. However, there are cases in which products claim to elongate and enrich eyelashes. Concerns about the abnormal reactions of these products are constantly growing, and the absence of analytical methods for illicit compounds (prostaglandins and their analogs) in cosmetics (eyelash growth serums) renders monitoring challenging. Accordingly, in this study, we sought to develop an LC-MS/MS method for facile and fast analysis of compounds illegally mixed into eyelash growth serums.Green analytical chemistry has recently emerged because of environmental concerns. In line with this trend, we developed an optimal method by comparing the methods mainly used in cosmetic pretreatment (solvent extraction, QuEChERS, and solid phase extraction) with a method using deep eutectic solvents (DESs), which is an eco-friendly solvent. As a result of validation according to the International Conference on Harmonization guidelines, the limit of detection was 0.20–9.34 ng/mL, and the limit of quantification was 0.60–28.31 ng/mL. Recovery, linearity, precision, and accuracy were within acceptable ranges. Additionally, using the Analytical GREEnness calculator and complex green analytical procedure index tools, we confirmed that the method using the DES was greener than the other methods. In this study, we developed an analytical method for illicit compounds contained in eyelash growth serums, offering an eco-friendly approach for the prevention of the distribution of illegal cosmetics.