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Model of fractured medium and nondestructive control of composite materials

Chinese Journal of Aeronautics 2024年第2期37卷 93-99页

作者： Vasily GOLUBEV Ilia NIKITIN Katerina BEKLEMYSHEVA Department of Computers Science and Numerical Mathematics Moscow Institute of Physics and TechnologyDolgoprudny 141700Russia Mathematical Modeling and Management Department of InformatizationInstitute of Computer Aided Design RASMoscow 123056Russia

Non-destructive testing of composites is an important issue in the modern aircraft *** are susceptible to the barely visible impact damage which can affect the residual strength of the material and occurs both during production and *** continuum model for describing the damaged zone is *** slip theory relations used for a continuous distribution of slip planes are *** the initial stage,the isotropic background model is *** model allows the material slippage along the fractures based on the Coulomb friction law with the small viscous *** this regime,the govern system of equations becomes *** overcome this difficulty,the explicit-implicit grid-characteristic scheme is *** standard ultrasound diagnostic procedure of damaged composite materials is successfully *** with the trivial free-surface fracture model,different reactions on the compression and stretch waves are *** approach provided an effective way for the simulation of complex dynamic behavior of damage zones.

关键词： Non-destructive testing Composite materials Numerical modeling Continuum model Grid-characteristic method

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Determination of the Optimal Number of Topics in the LDA Model When Working with Large Arrays of Text Data

Determination of the Optimal Number of Topics in the LDA Mod...

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2023 IEEE International Conference on Smart Information Systems and Technologies, SIST 2023

作者： Baimakhanbetov, Mukhit International It University Department of Mathematical and Computer Modeling Almaty33224 Kazakhstan

ISBN: (纸本)9798350335040

The article presents the issues of thematic modeling. The existing approaches for determining the optimal number of topics when working with text data are considered. Calculated metrics such as coherence score, perplexity. There are many widely used methods for determining topics when working with text data. But most of the methods are developed based on the Latent Dirichlet Allocation (LDA). One of the main disadvantages of the probabilistic LDA model is the parameter θ, which the researcher must determine in advance, which is often impossible to know a priori. One of the main adopted strategies is the calculation of a series of LDA models with a different number of topics in a certain quantitative range, followed by the calculation of the quality metrics of the resulting topics. © 2023 IEEE.

关键词： Statistics

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Comparative effectiveness of models and methods for diagnosing diseases of internal organs 4

Comparative effectiveness of models and methods for diagnosi...

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4th IEEE International Conference on Smart Information Systems and Technologies, SIST 2024

作者： Myrzakerimova, Alua Khikmetov, Askar Kolesnikova, Kateryna Information Systems Department IITU Almaty Kazakhstan Mathematical Computer Modeling Department IITU Almaty Kazakhstan

ISBN: (纸本)9798350374865

Among the various applications of IT in healthcare, automated systems for diagnosing diseases stand out for their utilization of mathematical models in medical decision-making. These systems, capable of analyzing extensive datasets, offer a level of speed and accuracy in diagnosing diseases of internal organs that often surpasses human capability. This paper aims to elucidate and validate the effectiveness of these automated systems through a comprehensive approach involving comparative studies and clinical trials. By examining the accuracy of different mathematical models and highlighting the percentage of cases correctly identified by expert systems, this research underscores the systems' proficiency in rapid data processing and analysis. Drawing on previous research, the complexity of medical diagnostics is explored through the diversity of diagnostic indicators and the development of robust mathematical models based on fuzzy set theory and gradient projection techniques. The paper presents a scheme of the automated diagnostic system, detailing its core components and the innovative use of case-based reasoning. Through a retrospective analysis and clinical trial outcomes, the effectiveness of the proposed system is demonstrated, showcasing its significant potential to enhance diagnostic accuracy and efficiency in the medical field. © 2024 IEEE.

关键词： Expert systems

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On the Solvability of the Generalized Neumann Problem for a Higher-Order Elliptic Equation in an Infinite Domain

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Journal of mathematical Sciences (United States) 2024年第2期278卷 342-353页

作者： Koshanov, B.D. Soldatov, A.P. Institute of Mathematics and Mathematical Modeling Almaty Kazakhstan Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russian Federation

We consider the generalized Neumann problem for a 2lth-order elliptic equation with constant real higher-order coefficients in an infinite domain containing the exterior of some circle and bounded by a sufficiently smooth contour. It consists in specifying of the (k_j − 1)th-order normal derivatives where 1 ≤ k ₁ <.. < k_l ≤ 2l;for k_j = j it turns into the Dirichlet problem, and for k_j = j + 1 into the Neumann problem. Under certain assumptions about the coefficients of the equation at infinity, a necessary and sufficient condition for the Fredholm property of this problem is obtained and a formula for its index in Hölder spaces is given. © 2024, Springer Nature Switzerland AG.

关键词： 2lth-order elliptic equation Fredholm property generalized Neumann problem Hölder space index infinite domain

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Evaluation of Modern Generative Networks for EchoCG Image Generation

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computers, Materials & Continua 2024年第12期81卷 4503-4523页

作者： Sabina Rakhmetulayeva Zhandos Zhanabekov Aigerim Bolshibayeva Department of Cybersecurity Information Processing and StorageSatbayev UniversityAlmaty050000Kazakhstan Department of Mathematical Computer Modeling International IT UniversityAlmaty050000Kazakhstan Department of Information Systems International IT UniversityAlmaty050000Kazakhstan

The applications of machine learning(ML)in the medical domain are often hindered by the limited availability of high-quality *** address this challenge,we explore the synthetic generation of echocardiography images(echoCG)using state-of-the-art generative *** conduct a comprehensive evaluation of three prominent methods:Cycle-consistent generative adversarial network(CycleGAN),Contrastive Unpaired Translation(CUT),and Stable Diffusion 1.5 with Low-Rank Adaptation(LoRA).Our research presents the data generation methodol-ogy,image samples,and evaluation strategy,followed by an extensive user study involving licensed cardiologists and surgeons who assess the perceived quality and medical soundness of the generated *** findings indicate that Stable Diffusion outperforms both CycleGAN and CUT in generating images that are nearly indistinguishable from real echoCG images,making it a promising tool for augmenting medical ***,we also identify limitations in the synthetic images generated by CycleGAN and CUT,which are easily distinguishable as non-realistic by medical *** study highlights the potential of diffusion models in medical imaging and their applicability in addressing data scarcity,while also outlining the areas for future improvement.

关键词： Synthetic image generation synthetic echogcardiography generative adversarial networks CycleGAN latent diffusion models stable diffusion

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DeepSurNet-NSGA II:Deep Surrogate Model-Assisted Multi-Objective Evolutionary Algorithm for Enhancing Leg Linkage in Walking Robots

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computers, Materials & Continua 2024年第10期81卷 229-249页

作者： Sayat Ibrayev Batyrkhan Omarov Arman Ibrayeva Zeinel Momynkulov Joldasbekov Institute of Mechanics and Engineering Almaty050000Kazakhstan Department of Mathematical and Computer Modeling International Information Technology UniversityAlmaty050000Kazakhstan Department of Information Systems Al-Farabi Kazakh National UniversityAlmaty050000Kazakhstan

This research paper presents a comprehensive investigation into the effectiveness of the DeepSurNet-NSGA II(Deep Surrogate Model-Assisted Non-dominated Sorting Genetic Algorithm II)for solving complex multiobjective optimization problems,with a particular focus on robotic leg-linkage *** study introduces an innovative approach that integrates deep learning-based surrogate models with the robust Non-dominated Sorting Genetic Algorithm II,aiming to enhance the efficiency and precision of the optimization *** a series of empirical experiments and algorithmic analyses,the paper demonstrates a high degree of correlation between solutions generated by the DeepSurNet-NSGA II and those obtained from direct experimental methods,underscoring the algorithm’s capability to accurately approximate the Pareto-optimal frontier while significantly reducing computational *** methodology encompasses a detailed exploration of the algorithm’s configuration,the experimental setup,and the criteria for performance evaluation,ensuring the reproducibility of results and facilitating future advancements in the *** findings of this study not only confirm the practical applicability and theoretical soundness of the DeepSurNet-NSGA II in navigating the intricacies of multi-objective optimization but also highlight its potential as a transformative tool in engineering and design *** bridging the gap between complex optimization challenges and achievable solutions,this research contributes valuable insights into the optimization domain,offering a promising direction for future inquiries and technological innovations.

关键词： Multi-objective optimization genetic algorithm surrogate model deep learning walking robots

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Ensemble Approach Combining Deep Residual Networks and BiGRU with Attention Mechanism for Classification of Heart Arrhythmias

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computers, Materials & Continua 2024年第7期80卷 341-359页

作者： Batyrkhan Omarov Meirzhan Baikuvekov Daniyar Sultan Nurzhan Mukazhanov Madina Suleimenova Maigul Zhekambayeva Department of Information Systems Al-Farabi Kazakh National UniversityAlmaty050040Kazakhstan Department of Mathematical and Computer Modeling International Information Technology UniversityAlmaty050040Kazakhstan Department of Software Engineering Satbayev UniversityAlmaty050013Kazakhstan

This research introduces an innovative ensemble approach,combining Deep Residual Networks(ResNets)and Bidirectional Gated Recurrent Units(BiGRU),augmented with an Attention Mechanism,for the classification of heart *** escalating prevalence of cardiovascular diseases necessitates advanced diagnostic tools to enhance accuracy and *** model leverages the deep hierarchical feature extraction capabilities of ResNets,which are adept at identifying intricate patterns within electrocardiogram(ECG)data,while BiGRU layers capture the temporal dynamics essential for understanding the sequential nature of ECG *** integration of an Attention Mechanism refines the model’s focus on critical segments of ECG data,ensuring a nuanced analysis that highlights the most informative features for arrhythmia *** on a comprehensive dataset of 12-lead ECG recordings,our ensemble model demonstrates superior performance in distinguishing between various types of arrhythmias,with an accuracy of 98.4%,a precision of 98.1%,a recall of 98%,and an F-score of 98%.This novel combination of convolutional and recurrent neural networks,supplemented by attention-driven mechanisms,advances automated ECG analysis,contributing significantly to healthcare’s machine learning applications and presenting a step forward in developing non-invasive,efficient,and reliable tools for early diagnosis and management of heart diseases.

关键词： CNN BiGRU ensemble deep learning ECG arrhythmia heart disease

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Automatic Coding at Scale: Design and Deployment of a Nationwide System for Normalizing Referrals in the Chilean Public Healthcare System 5

Automatic Coding at Scale: Design and Deployment of a Nation...

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5th Workshop on Clinical Natural Language Processing, ClinicalNLP 2023. held at ACL 2023

作者： Villena, Fabián Rojas, Matías Arias, Felipe Pacheco, Jorge Vera, Paulina Dunstan, Jocelyn Center for Mathematical Modeling Department of Computer Sciences University of Chile Chile Center for Mathematical Modeling University of Chile Chile Dept. of Statistics and Health Information Chilean Ministry of Health Chile Dept. Computer Science & IMC Pontifical Catholic University of Chile Chile

ISBN: (纸本)9781959429883

The disease coding task involves assigning a unique identifier from a controlled vocabulary to each disease mentioned in a clinical document. This task is relevant since it allows information extraction from unstructured data to perform, for example, epidemiological studies about the incidence and prevalence of diseases in a determined context. However, the manual coding process is subject to errors as it requires medical personnel to be competent in coding rules and terminology. In addition, this process consumes a lot of time and energy, which could be allocated to more clinically relevant tasks. These difficulties can be addressed by developing computational systems that automatically assign codes to diseases. In this way, we propose a two-step system for automatically coding diseases in referrals from the Chilean public healthcare system. Specifically, our model uses a state-of-the-art NER model for recognizing disease mentions and a search engine system based on Elasticsearch for assigning the most relevant codes associated with these disease mentions. The system's performance was evaluated on referrals manually coded by clinical experts. Our system obtained a MAP score of 0.63 for the subcategory level and 0.83 for the category level, close to the best-performing models in the literature. This system could be a support tool for health professionals, optimizing the coding and management process. Finally, to guarantee reproducibility, we publicly release the code of our models and experiments. © 2023 Association for Computational Linguistics.

关键词： Search engines

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Numerical Simulation and Parallel Computing of Acoustic Wave Equation in Isotropic-Heterogeneous Media

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computer modeling in Engineering & Sciences 2024年第11期141卷 1867-1881页

作者： Arshyn Altybay Niyaz Tokmagambetov Department of Differential Equations Institute of Mathematics and Mathematical ModelingAlmaty050010Kazakhstan Department of Computer Science Al-Farabi Kazakh National UniversityAlmaty050040Kazakhstan Centre de Recerca Matemática Edifici C Bellaterra(Barcelona)08193Spain

In this paper,we consider the numerical implementation of the 2D wave equation in isotropic-heterogeneous *** stability analysis of the scheme using the von Neumann stability method has been *** conducted a study on modeling the propagation of acoustic waves in a heterogeneous medium and performed numerical simulations in various heterogeneous media at different time *** parallel code using Compute Unified Device Architecture(CUDA)technology and tested on domains of various *** analysis showed that our parallel approach showed significant speedup compared to sequential code on the Central Processing Unit(CPU).The proposed parallel visualization simulator can be an important tool for numerous wave control systems in engineering practice.

关键词： Acoustic wave simulation numerical simulation isotropic-heterogeneous media graphics processing unit(GPU) von Neumann stability analysis

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-Linear Problem for a Circular Domain and Its Application to Composites

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Lobachevskii Journal of Mathematics 2024年第12期45卷 6173-6185页

作者： Mityushev, V.V. Zhunussova, Zh. Kh. Faculty of Computer Science and Telecommunications Cracow University of Technology Krakow Poland Al-Farabi Kazakh National University Almaty Kazakhstan Institute of Mathematics and Mathematical Modeling Almaty Kazakhstan

Abstract: We develop the method of functional equations to solve the -linear problem for analytic functions for a circular coated domain. The solution is obtained in the form of series in symbolic form. Numerical examples are given, and the accuracy of the obtained solutions are analyzed. The -linear problem models antiplane shear in elastic fiber composites. © Pleiades Publishing, Ltd. 2024.

关键词： antiplane deformation conformal mapping method of functional equations successive approximation method symbolic computations

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