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Tashkent University of Information Technologies

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Tashkent University of Information Technologies named after Muhammad al-Khwarizmi is an educational institution that provides students with the academic knowledge necessary to become highly qualified specialists and actively shape the future of our country. The wide range of subjects offered by the university provides students with a modern education and, in turn, represents a solution to social and global challenges. Continuing education lays the foundation for lifelong exploration. The concept of innovation is seen as an important basis for the continuous improvement of the university. The university strives to maintain the quality of education at the level of world requirements, providing continuous training for teachers by supporting dialogue between teachers and students.

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Browsing Tashkent University of Information Technologies by Scopus Q "Q3"

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    Citation Count: 4
    Algorithms and Service for Digital Processing of Two-Dimensional Geophysical Fields Using Octave Method
    (Springer international Publishing Ag, 2022) Zaynidinov, H. N.; Singh, Dhananjay; Yusupov, I; Makhmudjanov, S. U.; Department of Artificial Intelligence
    This paper covers new algorithms for digital signal processing of two-dimensional geophysical fields using octave method, which predicts the mineral value of the field in terms of signal energy value. In addition, it addresses and shows a functional scheme of the platform service based on cloud technologies. The essence of the work is that the geophysical data are two-dimensional, so their volume is very large. This requires the use of fast algorithms for digital processing of large amounts of data. Therefore, if we use the octave method effectively, the required result is obtained by calculating the value of the signal energy and comparing the finite difference of these values with its previous value.
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    Application of Daubechies Wavelets in Digital Processing of Biomedical Signals and Images
    (Springer Science and Business Media Deutschland GmbH, 2024) Zaynidinov, H.; Juraev, U.; Tishlikov, S.; Modullayev, J.; Department of Artificial Intelligence
    Wavelet analysis of one-dimensional signals has proven effective in deciphering the electrocardiogram (ECG). Promising results have already been obtained from their analysis. In particular, it has been shown that anomalous effects in the ECG are mainly manifested on much larger scales (low frequencies), while normal structures are characterized by relatively small scales (high frequencies). Denoising is one of the urgent problems of digital processing of biomedical signals and tomographic images. Wavelet methods are relatively new and are a method of denoising using wavelet functions. Wavelets allow for the analysis of various types of signals and effective noise removal, so it is of particular interest to study their potential to improve image quality. It is very convenient to use DWT (Discrete Wavelet Transform) in digital image processing, because it provides deep insight into the main spatial and frequency features. Wavelets provide excellent time-frequency localization, meaning they can capture both transient and stationary features in signals and images. This localization capability is especially valuable in medical applications where signals may contain abrupt changes or irregular patterns. In this paper, we will discuss the method of biomedical signal restoration and denoising in tomographic images using different wavelet functions such as Haar wavelet, Symlet, Meyer wavelet, Daubechies wavelet. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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    Digital Processing of Blood Image by Applying Two-Dimensional Haar Wavelets
    (Springer international Publishing Ag, 2021) Zaynidinov, H. N.; Yusupov, I; Juraev, J. U.; Singh, Dhananjay; Department of Artificial Intelligence
    In this work, compression and zero coefficients have been determined by using digital processing of the blood image that is 1 mu l (approximately one drop of blood) in the Haar wavelet. Also using this amount, an algorithm is proposed to define the number of leukocytes in human blood. We know that there are currently two types of methods for determining the number of leukocytes: grease and counting by using a microscope. This is a loss of time, causes a number of errors and inconveniences. By using this algorithm, a program has been developed to calculate the number of leukocytes with high accuracy in a blood image of 1 mu l (about one drop of blood).
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    Iot-Enabled Mobile Device for Electrogastrography Signal Processing
    (Springer international Publishing Ag, 2021) Zaynidinov, Hakimjon; Makhmudjanov, Sarvar; Rajabov, Farkhad; Singh, Dhananjay; Department of Artificial Intelligence
    Electrogastrography (EGG) is a powerful instrument that represents and provides high time precision for direct heart activities. After processing the chest skin for the contact process by network electrodes, the conventional method of collecting heart signals involves the presence of electrodes directly connected to the patient's chest using gelatin. One of the most critical activities is tracking the clinical signs of cardiac patients. A real-time EGG signal acquisition and processing device is developed to observe patients in various IoT-based environments is discussed in this article. The EGG signals that are detected are passed to special software. For further protection, it is ensured that the transmission of the EGG signal from the patient without distortion to the doctors should take place. The ambulatory and wearable device for the transmission of real-time EGG signals is discussed in this article in order to monitor patients in various environments. For further analysis, the captured EGG signal is transferred to software and signals are transferred to the doctors for real-time evaluation of the patient.
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    Methods for Determining the Optimal Sampling Step of Signals in the Process of Device and Computer Integration
    (Springer international Publishing Ag, 2022) Zaynidinov, Hakimjon; Singh, Dhananjay; Makhmudjanov, Sarvar; Yusupov, Ibrohimbek; Department of Artificial Intelligence
    In this paper, digital signal processing methods and its solution for HCI were described. Mostly, problems are connected to taking signals or data from real time devices. Data is often serial, stream or etc. device and computer integration in HCI focuses to digital signal processing. Today, the use of interpolation methods in the digital processing of biomedical signals is important, and at the same time allows the detection and diagnosis of diseases as a result of digital processing of biomedical signals. This paper discusses the construction of a signal model using the spline-wavelet interpolation formula for equal intervals in the digital processing of biomedical signals.