Акгуль Найзагараева - Academia.edu (original) (raw)
Акгуль Найзагараева
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Papers by Акгуль Найзагараева
AIP Conference Proceedings, Dec 31, 2022
Eastern-European Journal of Enterprise Technologies
The process of clustering of normalized vegetation indices in five regions with a total area of 2... more The process of clustering of normalized vegetation indices in five regions with a total area of 2565 hectares of the North Kazakhstan region was studied. A methodological approach to organizing the clustering process is proposed using the vegetation indices NDVI, MSAVI, ReCI, NDWI and NDRE, taking into account individual characteristics in the three main phases of spring wheat development As a result of the research, vegetation indices were grouped into 3 classes using the k-means clustering method. The first cluster contained vegetation indices whose maximum values occupied about 33.98% of the total area of the study area. It was found that NDVImax located in the first cluster was positively correlated with soil-corrected vegetation indices MSAVI and crop moisture indicators NDMI (R2=0.92). The second cluster is characterized by minimum values of NDVImax coefficients at the germination, tillering and ripening phases (from 0.53 to 0.55). The lowest values of vegetation indices occup...
Сandidate of Technical Sciences, Senior Lecturer* G u l n a r A b d y g a l i k o v a Сandidate o... more Сandidate of Technical Sciences, Senior Lecturer* G u l n a r A b d y g a l i k o v a Сandidate of Pedagogical Sciences, Senior Lecturer* A k g u l N a i z a g a r a y e v a Master of Engineering, Senior Lecturer* A i s u l u I s m a i l o v a PhD, Associate Professor*
International Journal of Electrical and Computer Engineering (IJECE), 2023
In the directions of modern medicine, a new area of processing and analysis of visual data is act... more In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing-a radio municipality-a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.
AIP Conference Proceedings, Dec 31, 2022
Eastern-European Journal of Enterprise Technologies
The process of clustering of normalized vegetation indices in five regions with a total area of 2... more The process of clustering of normalized vegetation indices in five regions with a total area of 2565 hectares of the North Kazakhstan region was studied. A methodological approach to organizing the clustering process is proposed using the vegetation indices NDVI, MSAVI, ReCI, NDWI and NDRE, taking into account individual characteristics in the three main phases of spring wheat development As a result of the research, vegetation indices were grouped into 3 classes using the k-means clustering method. The first cluster contained vegetation indices whose maximum values occupied about 33.98% of the total area of the study area. It was found that NDVImax located in the first cluster was positively correlated with soil-corrected vegetation indices MSAVI and crop moisture indicators NDMI (R2=0.92). The second cluster is characterized by minimum values of NDVImax coefficients at the germination, tillering and ripening phases (from 0.53 to 0.55). The lowest values of vegetation indices occup...
Сandidate of Technical Sciences, Senior Lecturer* G u l n a r A b d y g a l i k o v a Сandidate o... more Сandidate of Technical Sciences, Senior Lecturer* G u l n a r A b d y g a l i k o v a Сandidate of Pedagogical Sciences, Senior Lecturer* A k g u l N a i z a g a r a y e v a Master of Engineering, Senior Lecturer* A i s u l u I s m a i l o v a PhD, Associate Professor*
International Journal of Electrical and Computer Engineering (IJECE), 2023
In the directions of modern medicine, a new area of processing and analysis of visual data is act... more In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing-a radio municipality-a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.