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15th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / The 7th International Conference on Emerging Data and Industry 4.0, EDI40 2024

作者： Ukibassov, B.M. Rakhmetulayeva, S.B. Zhanabekov, Zh.O. Bolshibayeva, A.K. Yasar, Ansar-Ul-Haque Information Systems Department International Information Technology University Almaty050040 Kazakhstan Mathematical Computer Modeling International Information Technology University Almaty050040 Kazakhstan Transportation Research Institute Hasselt University Hasselt3500 Belgium

The article covers the implementation of anatomy constrained contrastive (ACC) learning networks on a dataset of echocardiographic images with the purpose of segmenting heart chambers for further study. The dataset was partially synthetic, generated using slicing of 3D models of the heart. The images were generated using cycle-consistent generative adversarial networks (CycleGAN) and contrastive unpaired translation (CUT) approaches. By utilizing both CycleGAN and CUT approaches, the generated images captured a wide range of variations in heart chamber segmentation, allowing for a more comprehensive study of the different anatomical features. Proposed approach augments the implementation of ACC learning networks and partially solves the data scarcity problem when it comes to segmentation implementation. © 2024 Elsevier B.V.. All rights reserved.

关键词： Heart

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On Some Issues of mathematical modeling of Various Approaches to Learning 15

On Some Issues of Mathematical Modeling of Various Approache...

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Gonchar, Dmitry Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Modeling of Design Systems Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The enlarged model of comparison of various concepts of education (culturally appropriate and nature-like) in compulsory secondary school proposed earlier by the author is supplemented by taking into account feedback on the health of students, which makes it possible to move from the appropriate modeling of the school 'in the moment' to modeling it in time dynamics. © 2022 IEEE.

关键词： Education computing

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

Comparative effectiveness of models and methods for diagnosi...

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Smart Information Systems and Technologies (SIST), IEEE International Conference on

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

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

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.

关键词： Accuracy Biological systems Clinical trials mathematical models Fuzzy set theory Medical diagnosis Expert systems

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Unveling the Precision of Deep Learning Models for Stock Price Prediction: A Comparative Analysis of Bi-LSTM, LSTM, and GRU 2

Unveling the Precision of Deep Learning Models for Stock Pri...

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2nd International Conference on Converging Technology in Electrical and Information Engineering, ICCTEIE 2023

作者： Baihaqi, Thirza Sugiyarto, Matthew Aaron Daksa, Rayhan Prawira Kurniadi, Felix Indra Fakhruddin, Muhammad Erandi, Hasitha Bina Nusantara University School of Computer Science Data Science Department Jakarta11530 Indonesia University of Colombo Research and Development Centre for Mathematical Modeling Department of Mathematics Colombo00300 Sri Lanka

ISBN: (纸本)9798350370645

Due to the unpredictability of the stock market, accurate prognostic models are necessary for investing. In recent years, machine learning techniques, specifically deep learning algorithms, have grown in popularity for predicting stock prices. This paper seeks to compare the stock-price forecasting abilities of several deep learning models, including LSTM, Bi-LSTM, and GRU. The algorithms make use of the capabilities of Recurrent Neural Networks (RNNs), with a particular emphasis on the Long-Short Term Memory (LSTM) model. The primary objective is to evaluate the accuracy of these machine learning algorithms at predicting stock market values and to determine how the number of training epochs affects model performance. Through comparative analysis, we intend to identify the most accurate model for predicting stock prices. Using historical stock market data, the research involves training and evaluating the various models. Common evaluation metrics, such as Root Mean Square Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE), are used to evaluate the performance of each model. In terms of RMSE, MSE, and MAE, the bi-LSTM model outperforms the other models, obtaining values of 0.00029, 0.00029, and 0.01 respectively. © 2023 IEEE.

关键词： Long short-term memory

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Formation of Water Quality of Surface Water Bodies Used in the Material Processing

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Fluid Dynamics & Materials Processing 2024年第4期20卷 815-828页

作者： Tatyana Lyubimova Anatoly Lepikhin Yanina Parshakova Irina Zayakina Alibek Issakhov Laboratory of Computational Fluid Dynamics Laboratory Institute of Continuous Media Mechanics UB RASPerm614068Russia Laboratory of Land Hydrology Problems Mining Institute UB RASPerm614000Russia Department of Theoretical Physics Perm State UniversityPerm614990Russia Department of Mathematical and Computer Modeling Al-Farabi Kazakh National UniversityAlmaty050040Republic of Kazakhstan

In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required *** in many regions of the world,there is an acute problem of providing industry with water of a required *** solution is an urgent and difficult *** water quality of surface water bodies is formed by a combination of a large number of both natural and anthropogenic factors,and is often significantly heterogeneous not only in the water area,but also in *** a rule,the water supply of large industrial enterprises is located along the river *** are the most important nodes of river *** the mechanism of transport of pollutants at the confluence of rivers is critical for assessing water *** recent years,thanks to the data of satellite images,the interest of researchers in the phenomenon of mixing the waters of merging rivers has *** nature of the merger is influenced by the formation of transverse *** the framework of this work,a study of vorticity,as well as the width of the mixing zone,depending on the distance from the confluence,the speeds of the merging rivers and the angle of confluence was carried *** the consumer properties of water are largely determined by its chemical and physical indicators,the intensity of mixing,determined largely by the nature of the secondary circulation,is of fundamental importance for assessing the distribution of hydrochemical indicators of water quality in the mixing *** characteristics are important not only for organizing water intake for drinking and technical purposes with the best consumer properties,but also for organizing an effective monitoring system for confluence zones.

关键词： Water for material processing water quality formation of transverse circulation

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Angioplasty Virtual Reality Simulator: modeling of Blood Flow in an Artery 12

Angioplasty Virtual Reality Simulator: Modeling of Blood Flo...

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12th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Alipova, Bakhyt Tokmukhamedova, Fatima Bolatov, Zhiger Daineko, Yevgeniya Ipalakova, Madina Tsoy, Dana International It University Mathematical and Computer Modeling 050040 Kazakhstan University of Kentucky Mechanical and Aerospace Engineering 40506-0503 United States International It University Research Activities 050040 Kazakhstan International It University International Affairs 050040 Kazakhstan International It University Computer Engineering 050040 Kazakhstan

ISBN: (纸本)9798350358056

Blood flow in human arteries considered as an important aspect of health care. Due to the large amount of difficulties conducting in-vivo experiments, the use of computational fluid dynamics (CFD) to simulate pulsatile flow in the blood artery has become a promising alternative approach. In this paper the 2-dimensional model of blood flow in the rectangular coordinates is formed by numerical approach and the simulation by Unity Engine is provided. The simulation showed that the blood flow was laminar within the artery. The velocity magnitude of blood was highest at the center of the artery and gradually decreased towards the walls due to the no-slip condition. These results are consistent with previous experimental and computational studies of blood flow in arteries. © 2023 IEEE.

关键词： CFD compressible flow finite difference Navier-Stokes equation pulsatile blood flow simulation unity engine

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Networks with the structure of a combined combinatorial block design

Networks with the structure of a combined combinatorial bloc...

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2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Frolov, Alexander Kochetova, Natalya NRU MPEI Mathematical and Computer Modeling Dept. NRU MPEI Moscow Russia

ISBN: (纸本)9781665412629

There are considered networks possessing structure of combined combinatorial block design. The latter are built on the basis of any balanced incomplete combinatorial block design and are distinguished by an explicit representation of both blocks and duality blocks. Considered networks are built on the basis of connecting internal and external subnets, corresponding to blocks and duality blocks of a combinatorial block design. Such systems can be computer networks, key spaces of wireless sensor networks, communication systems and others. The combined representation of blocks and duality blocks is convenient for constructing routing algorithms in such systems, taking into account possible degradation. It is shown that the same combined combinatorial block design can be a model of different systems. © 2021 IEEE.

关键词： Wireless sensor networks

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LinkMed: Entity Recognition and Relation Extraction from Clinical Notes in Spanish

LinkMed: Entity Recognition and Relation Extraction from Cli...

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2023 Iberian Languages Evaluation Forum, IberLEF 2023

作者： Muñoz-Castro, Carlos Carvallo, Andrés Rojas, Matías Aracena, Claudio Guerra, Rodrigo Pizarro, Benjamín Dunstan, Jocelyn National Center for Artificial Intelligence Chile Faculty of Physical and Mathematical Sciences Universidad de Chile Chile Department of Computer Science Pontificia Universidad Católica de Chile Chile Institute for Mathematical and Computational Engineering Pontificia Universidad Católica de Chile Chile Center for Mathematical Modeling Universidad de Chile Chile Millenium Institute Foundational Research on Data Chile

Relation extraction is an essential component of Natural Language Processing (NLP) and significantly influences information retrieval and structured information extraction. Within clinical notes, the task is needed to establish connections among illnesses, therapies, indications, and other medical concepts. Motivated by the above, in this work, we propose a two-step model approach for entity linking;in the first step, we solve entity recognition, and in the second, a relation classification approach. We evaluated our approach in a Spanish corpus of the TESTLINK challenge in IberLEF2023 (Iberian Languages Evaluation Forum), comprising 81 clinical notes to train and 80 clinical notes to test. Our results show competitive performance with a precision of 0.47, recall of 0.43, and F1-score of 0.45, presenting an effective strategy for relation extraction from clinical notes in Spanish. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Information retrieval

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Interpretable Deep Learning for DDoS Defense: A SHAP-based Approach in Cloud Computing

Interpretable Deep Learning for DDoS Defense: A SHAP-based A...

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2024 International Conference on Circuit, Systems and Communication, ICCSC 2024

作者： Ouhssini, Mohamed Afdel, Karim Akouhar, Mohamed Agherrabi, Elhafed Abarda, Abdallah University Ibn Zohr Lab Siv Department of Computer Science Agadir Morocco University Ibn Tofail Lab Partial Differential Equations Algebra and Spectral Geometry Kenitra Morocco University Ibn Zohr Lab IRF-SIC Department of Computer Science Agadir Morocco Hassan First University Lab of Mathematical Modeling and Economic Calculations Settat Morocco

ISBN: (纸本)9798350365306

This paper proposes an explainable deep learning model that combines CNNs and LSTMs to detect and mitigate DDoS attacks in cloud computing environments. The model leverages spatial and temporal patterns in network traffic data, and integrates SHAP for interpretability. Evaluation using diverse datasets confirms its effectiveness, and a Genetic Algorithm optimizes hyperparameters. The model provides actionable insights to aid security professionals in safeguarding cloud systems. © 2024 IEEE.

关键词： Cloud security

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On an Alternative form of the Constraint Equations for the Delta Robot and Ways to Take them into Account in modeling 4

On an Alternative form of the Constraint Equations for the D...

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4th International Conference on Control Systems, mathematical modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Krasinskiy, Aleksandr Rudnenko, Aleksandr Khafizov, Murad Moscow State University of Food Production Department of Physical and Mathematical Disciplines Moscow Russia Moscow Aviation Institute Department of Probability Theory and Computer Modeling Moscow Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

For the Delta robot, one of the most famous and successfully used parallel manipulators, anew, different from all previously used forms of constraints equations, is proposed, based on the fact that, due to the presence of parallelograms in the lower links of the manipulator, for the executive link (moving platform) only translational movement is possible. On this basis, a rigorous nonlinear modeling of the constraints was performed with the inclusion of only three angles of rotation of the output shafts of the actuator motor gearboxes. Further simplification is achieved by moving from the traditionally used Lagrange equations with constraint multipliers, in which the mathematical model includes 6 second-order differential equations and 3 algebraic constraint equations, to equations free from Lagrange multipliers in the Shulgin form. As a result, the complete nonlinear model consists of 3 second-order differential equations and 3 first-order differential equations - time-differentiated equations and geometric constraints. © 2022 IEEE.

关键词： Lagrange multipliers

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