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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Hidirova, Mohiniso B. Turgunov, Abrorjon M. Department of Energy and Applied Sciences Kimyo International University in Tashkent Tashkent Uzbekistan Department of Algorithms and Mathematical Modeling Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9798350389234

The article examines the regulatory mechanisms of liver cells (LC) - hepatocytes and hepatitis B virus (HBV) based on the regulatory of living systems using functional-differential equations with delayed arguments. Quantitative studies of the LC-HBV system have shown the possibility of the following scenarios for the integration of their genetic systems: suppression of virus activity by hepatocytes;suppression of hepatocyte activity by the virus;symbiotic coexistence of hepatocyte and virus;periodic excitation of viral damage to the hepatocyte;chaotic interaction of molecular genetic systems of LC and HBV, at the same time, "black hole" which is considered one of the most dangerous modes. To analyze the effectiveness of the developed functional-differential equations with delayed arguments, qualitative analysis methods, construction of phase and parametric portraits, methods of determining the location and dynamics of sources, and the technique of constructing a Lamerey diagram on a computer were used. However, this research work presents a mathematical model of the regulatory of the occurrence, development and various ways of progression of HBV in liver cells (hepatocytes). © 2024 IEEE.

关键词： Chaos theory

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Fuzzy Morphological Processing Algorithm of Blood Image 25

Fuzzy Morphological Processing Algorithm of Blood Image

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Turgunov, Abrorjon M. Narzullaev, Temur N. Matyakubov, Marks Ya. Payzieva, Munira T. Kamolova, Sevara J. Rakhmonova, Nilufar N. Department of Algorithms and Mathematical Modeling Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9798350389234

This article, a morphological image processing algorithm is developed for early detection of viral hepatitis from microscopic blood images. It is mentioned that it can be used to accurately determine each boundary detail in the fuzzy morphological processing of the gray image of the blood image. Boundary detection leads to higher recognition results in neural network training. Compared to the work of a number of scholars, our method offers such performance, but it offers improved dynamics and flexibility in the formulation of linguistic boundary criteria, which can be a leading factor in the design of image processing systems with dynamic and flexible rules, such as Type 2 allows fuzzy rules, which offers an interesting alternative to currently common deep learning applications. The validated experimental results show the reliability of the modified method compared to the Chaira method. Mean, entropy and standard deviation were calculated. It turned out to be higher than the values of the Chaira method. © 2024 IEEE.

关键词： Neural networks

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A Method for modeling the Regulation of the Introduction of Genetic Information of the Hepatitis B Virus into the Hepatocyte Genome

A Method for Modeling the Regulation of the Introduction of ...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Mohiniso B. Hidirova Abrorjon M. Turgunov Department of Energy and Applied Sciences Kimyo International University in Tashkent Tashkent Uzbekistan Department of Algorithms and mathematical modeling Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The article examines the regulatory mechanisms of liver cells (LC) - hepatocytes and hepatitis B virus (HBV) based on the regulatory of living systems using functional-differential equations with delayed arguments. Quantitative studies of the LC-HBV system have shown the possibility of the following scenarios for the integration of their genetic systems: suppression of virus activity by hepatocytes; suppression of hepatocyte activity by the virus; symbiotic coexistence of hepatocyte and virus; periodic excitation of viral damage to the hepatocyte; chaotic interaction of molecular genetic systems of LC and HBV, at the same time, “black hole” which is considered one of the most dangerous modes. To analyze the effectiveness of the developed functional-differential equations with delayed arguments, qualitative analysis methods, construction of phase and parametric portraits, methods of determining the location and dynamics of sources, and the technique of constructing a Lamerey diagram on a computer were used. However, this research work presents a mathematical model of the regulatory of the occurrence, development and various ways of progression of HBV in liver cells (hepatocytes).

关键词： Symbiosis Ethics Enzymes Computer vision Computer viruses Liver diseases Training data

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Fuzzy Morphological Processing Algorithm of Blood Image

Fuzzy Morphological Processing Algorithm of Blood Image

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Abrorjon M. Turgunov Temur N. Narzullaev Marks Ya. Matyakubov Munira T. Payzieva Sevara J. Kamolova Nilufar N. Rakhmonova Department of Algorithms and mathematical modeling Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

关键词： Training Image processing Refining Medical services Reliability Blood X-ray imaging

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New "walk on Equations" Monte Carlo Algorithm for Linear Systems 15

New "walk on Equations" Monte Carlo Algorithm for Linear Sys...

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15th Conference of the Euro-American Consortium for Promoting the Application of Mathematics in Technical and Natural Sciences, AMiTaNS 2023

作者： Todorov, Venelin Georgiev, Slavi Apostolov, Stoyan Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences 8 Acad. Georgi Bonchev Str. Sofia1113 Bulgaria Department of Parallel Algorithms and Machine Learning with A Laboratory in Neurotechnologies Institute of Information and Communication Technologies Bulgarian Academy of Sciences 25A Acad. Georgi Bonchev Str. Sofia1113 Bulgaria Department of Applied Mathematics and Statistics University of Ruse 8 Studentska Str. Ruse7004 Bulgaria Department of Mathematical Analysis University of Sofia 8 James Bourchier Blvd. Sofia1164 Bulgaria

A novel version of Monte Carlo algorithm for solving systems of linear algebraic equations is presented and studied. The algorithm is similar to the "Walk on Equations"Monte Carlo method recently developed by Ivan Dimov, Sylvain Maire and Jean Michel Sellier. It is done a comparison with the Gauss-Seidel method for matrices up to size of 212. The algorithm could be drastically improved by choosing appropriate values for the relaxation parameters, which in turn leads to dramatic reduction in time and lower relative errors for a given number of iterations. What is more, a sequential Monte Carlo method of John Halton based on an iterative use of the control variate method has been applied. Some of the most important numerical applications are the large system, coming from a finite element approximation of problems, describing a beam structure in constructive mechanics, and the block-diagonal matrices, which come from discretization of models in a regime-switching economy. © Published under licence by IOP Publishing Ltd.

关键词： Monte Carlo methods

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Stochastic Approaches for the Multidimensional Volterra Integral Equation 11th

Stochastic Approaches for the Multidimensional Volterra In...

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11th International Conference on New Trends in the Applications of Differential Equations in Sciences, NTADES 2024

作者： Todorov, Venelin Georgiev, Slavi Apostolov, Stoyan Dimov, Ivan Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia Bulgaria Department of Parallel Algorithms and Machine Learning with a Laboratory in Neurotechnologies Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria Department of Applied Mathematics and Statistics Faculty of Natural Sciences and Education University of Ruse Ruse Bulgaria Department of Mathematical Analysis Faculty of Mathematics and Informatics University of Sofia Sofia Bulgaria

ISBN: (纸本)9783031833977

In this study, we explore a stochastic methodology for addressing Volterra integral equations, particularly focusing on a multidimensional context. We provide a comprehensive examination of the method’s potential strengths and limitations, discussing its applicability. The stochastic approach is rigorously tested against a set of multidimensional benchmark problems, demonstrating its effectiveness and providing a framework for further investigation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Integral equations

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Novel Stochastic Sequences for Multidimensional Air Pollution Modelling 11th

Novel Stochastic Sequences for Multidimensional Air Polluti...

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11th International Conference on New Trends in the Applications of Differential Equations in Sciences, NTADES 2024

作者： Todorov, Venelin Georgiev, Slavi Apostolov, Stoyan Dimitrov, Yuri Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia Bulgaria Department of Parallel Algorithms and Machine Learning with a Laboratory in Neurotechnologies Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria Department of Applied Mathematics and Statistics Faculty of Natural Sciences and Education University of Ruse Ruse Bulgaria Department of Mathematical Analysis Faculty of Mathematics and Informatics University of Sofia Sofia Bulgaria Department of Mathematics Physics and Informatics Faculty of Forest Industry University of Forestry Sofia Bulgaria

ISBN: (纸本)9783031833977

This paper introduces a sophisticated approach to multidimensional sensitivity analysis by utilizing novel stochastic techniques for air pollution modeling within the large-scale, long-range transport framework of the Unified Danish Eulerian Model (UNI-DEM). This model plays a crucial role in assessing the detrimental impacts of elevated air pollution levels, and our research leverages it to tackle essential environmental protection issues. We develop and implement advanced Monte Carlo and quasi-Monte Carlo methods, incorporating specialized lattice sequences, to enhance the computational efficiency of multidimensional numerical integration. The study centers on evaluating the sensitivity of the UNI-DEM model outputs to variations in anthropogenic pollutant emissions and the rates of key chemical reactions. Our algorithms are applied to calculate global Sobol sensitivity indices, assessing the influence of several input parameters on significant air pollutant concentrations across diverse European cities with varying geographical characteristics. The goal of this research is to deepen the understanding of factors influencing air pollution and to support the development of effective strategies for reducing its harmful environmental impacts. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Air quality

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Advanced Unbiased Monte Carlo for Multidimensional Fredholm Integral Equations 11th

Advanced Unbiased Monte Carlo for Multidimensional Fredholm ...

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11th International Conference on New Trends in the Applications of Differential Equations in Sciences, NTADES 2024

ISBN: (纸本)9783031833977

Integral equations play a crucial role in various domains of applied mathematics, physics, and engineering. They are extensively utilized in fields such as mechanics, geophysics, kinetic theory of gases, quantum mechanics, mathematical economics, and queuing theory, among others. The broad applicability of these equations necessitates the development and study of efficient, reliable, and versatile methods for their solution. In this paper, we focus on an unbiased stochastic approach to solve multidimensional Fredholm integral equations of the second kind. The proposed method is designed to maintain high accuracy while minimizing computational complexity, making it suitable for handling complex problems involving irregular kernels and solutions. Through rigorous analysis and extensive numerical experiments, we demonstrate the robustness and effectiveness of this approach, highlighting its potential advantages over traditional deterministic methods, particularly in higher-dimensional spaces where conventional techniques often struggle with the curse of dimensionality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fredholm integral equations

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Approximating Geometric Knapsack via L-packings

Approximating Geometric Knapsack via L-packings

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作者： Gálvez, Waldo Grandoni, Fabrizio Ingala, Salvatore Heydrich, Sandy Khan, Arindam Wiese, Andreas Department of Computer Science Technical University of Munich Garching Germany Chair of Approximation Algorithms IDSIA USI-SUPSI via la Santa 1 Lugano-Viganello6962 Switzerland Department of Optimization Fraunhofer Institute for Industrial Mathematics Kaiserslautern Germany Department of Computer Science and Automation Indian Institute of Science Bangalore India Department of Industrial Engineering Center for Mathematical Modeling Universidad de Chile Chile

We study the two-dimensional geometric knapsack problem, in which we are given a set of n axis-aligned rectangular items, each one with an associated profit, and an axis-aligned square knapsack. The goal is to find a (non-overlapping) packing of a maximum profit subset of items inside the knapsack (without rotating items). The best-known polynomial-time approximation factor for this problem (even just in the cardinality case) is 2+ϵ [Jansen and Zhang, SODA 2004]. In this article we present a polynomial-time 17/9+ϵ © 2021 Association for Computing Machinery.

关键词： Profitability

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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