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International Conference on information Science and Communications technologies (ICISCT)

作者： Kunduz Medetova Djamshid Sultanov Department of system and applied programming Tashkent university of information technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of hardware and software of management systems in telcommunications Tashkent university of information technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper presents methods for solving problems using the method of fuzzy logic. This method serves to study the characteristics of determining the level of compliance of a candidate for an existing vacant position. When measuring compliance with database requirements based on the results of assessing compliance with the requirements of an employee for a position. The use of artificial intelligence in personnel records gives high efficiency and serves for decision making.

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Analysis of Hardware and Software Tools for Implementation of Cognitive Radio Networks

Analysis of Hardware and Software Tools for Implementation o...

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International Conference on information Science and Communications technologies (ICISCT)

作者： Ernazar Reypnazarov Halimjon Khujamatov Doston Khasanov Zamira Allamuratova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Dean of the Computer Enjineering Faculty Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Data Communication Networks and Systems Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Information-Computer Technologies and Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper analyzes of the hardware and software tools for implementing a cognitive radio network. In particular, software-configurable radio modules, which are considered the main element of the cognitive network, were studied according to their main characteristics, among which the widely used ones were comparatively analyzed. As a result of the analysis, the HackRF One device was selected as the most preferred option for cognitive network research, and its working principles, structure, and characteristics were revealed in detail. It also provides information about the GNU Radio software environment and its capabilities, which are used to operate the HackRF One device.

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Evolutionary Algorithm for Calculating the Optimal Temperature Regime of the Catalytic Process

Evolutionary Algorithm for Calculating the Optimal Temperatu...

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International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Evgenia Antipina Svetlana Mustafina Andrey Antipin Department of Scientific Research Ufa University of Science and Technology Ufa Russia Faculty of Mathematics and Information Technologies Ufa University of Science and Technology Ufa Russia Department of Applied Informatics and Programming Sterlitamak Branch of Ufa University of Science and Technology Sterlitamak Russia

The paper formulates an algorithm for searching the optimal temperature regime of the catalytic process in an ideal mixing reactor. The problem of optimal control of the catalytic process is formulated in a general form. To find its numerical solution, an algorithm based on the method of differential evolution is described. The algorithm allows to obtain an approximate solution of the optimization problem in a time acceptable from the practical point of view. A computational experiment for the dimerization process of alphamethylstyrene is carried out. The optimal temperature profile for achieving the maximum yield of reaction products – linear dimers – is obtained.

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Hooked on audio! Unveiling the secrets of podcast stickiness through social identity and uses and gratification theories

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Technology in Society 2024年 76卷

作者： Lin, Sheng-Wei Huang, Chia-Ding Department of Information Management College of Management National Chung Cheng University No.168 Sec. 1 University Rd. Chiayi Minhsiung62102 Taiwan Equipment Application Programming Engineer Episil Technologies Inc No.18 Innovation Road Ⅰ Science Based Industrial Park Hsin-Chu30076 Taiwan

The study integrated the social identity theory and the uses and gratification theory in probing factors behind the stickiness of audience to podcast programs, mainly in the two dimensions of perceived characteristics of the podcast creator (identity similarity, identity uniqueness, identity prestige, sincerity, and self-disclosure) and perceived podcast features (entertaining, narrative transportation, and multitasking). Podcast creator characteristics can affect audience stickiness via their psychological response (wishful identification, parasocial relationship). The study was conducted via a questionnaire survey, soliciting 302 valid responses and employing the partial least squares technique for testing hypotheses. The study finds that except for identity distinctiveness and self-disclosure, all the other podcast creator characteristics positively influence the audience's psychological response and, thus, their stickiness to podcasts. Among podcast program nature, both entertaining and narrative transportation affect podcast stickiness significantly, but multitasking has no significant influence. The study provides theoretical and practical insight into the audience stickiness issue for digital audio media podcasts. © 2023 Elsevier Ltd

关键词： Multitasking

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Research of Energy Detection Method in Spectrum Sensing in Cognitive Radio Networks

Research of Energy Detection Method in Spectrum Sensing in C...

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International Conference on information Science and Communications technologies (ICISCT)

作者： Ernazar Reypnazarov Halimjon Khujamatov Doston Khasanov Zamira Allamuratova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Computer Enjineering Faculty Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Data Communication Networks and Systems Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Information-Computer Technologies and Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

This paper presents the threshold value determination model, its implementation algorithm, and the characteristics of the threshold value depending on the probability of false signal detection, developed for the purpose of researching the method of energy determination in spectrum sensing in cognitive radio networks. Also, the main methods of single-band spectrum sensing in cognitive radio networks were initially studied in the article, and the main spectrum detection algorithms were comparatively analyzed.

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Using Machine Learning Techniques for Assessing Media Text Readability

Using Machine Learning Techniques for Assessing Media Text R...

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

作者： Andrey Laputenko Tatiana Evtushenko Elena Klochkova Nina Yevtushenko Department of Information Technologies National Research Tomsk State University Tomsk Russian Federation Graduate School of Applied Linguistics and Translation Studies Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russian Federation Department of Software Engineering Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russian Federation

The paper addresses the problem of assessing media text readability depending on the correlation of objective and subjective text complexity. Objective text complexity refers to a set of measurable characteristics such as baseline, morphological, syntactic and lexical characteristics of a media text (a piece of news published on university websites), which is calculated automatically for each text. In total, 34 parameters are considered. Subjective text complexity score is assigned to each text by human experts who assess the clarity, structure, cohesion and coherence of the text. The correlation between subjective and objective text complexity is studied using machine learning models. The readability level is measured using machine learning methods and regression-correlation analysis. Namely, an artificial neural network and regression models are used. It is demonstrated that the use of polynomial features and lasso regularization allows to get a compact regression model of a high quality. The use of the chosen machine learning techniques made it possible to estimate the impact of distinct linguistic features on the readability level.

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Methodology of Teaching programming Science Through Online Platforms

Methodology of Teaching Programming Science Through Online P...

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Informatics, Electronics, and Radio Engineering (PIERE), International Conference Problems of

作者： Akram Nishanov Oybek Allamov Janar Yusupova Marks Matyakubov Baxtiyor Qalandarov Reyimberganov Bahrom Department of Systematic and Practical Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Software Engineering Urgench Branch of Tashkent University of Information Technology named after Muhammad al-Khwarizmi Urgench Uzbekistan Master of Urgench branch of TATU named after Muhammad al-Khwarizmi Urgench Branch of Tashkent University of Information Technology named after Muhammad al-Khwarizmi Urgench Uzbekistan Student of Urgench branch of TATU named after Muhammad al-Khwarizmi Urgench Branch of Tashkent University of Information Technology named after Muhammad al-Khwarizmi Urgench Uzbekistan

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

This article presents an experiment conducted among students of the Faculty of “Software Engineering” of the Urgench branch of TATU named after Muhammad al-Khwarizmi. Teaching programming using online platforms in education has shown promising results in improving student outcomes. This article discusses the methodology used, the comparative results, and the impact of the platform on software education. The rapid adoption of online platforms in education has changed the way programming is taught, providing students with an interactive, hands-on learning environment. This shift is especially relevant in teaching programming, where real-time feedback and practice are essential to mastering algorithms and coding concepts. The study compared two groups: one was trained using the https://***/platform and the assignments were checked using this system, and the second group was trained using traditional methods. The results showed that students who used the online platform had a high level of mastery, which highlighted the effectiveness of integrating https://***/into programming education.

关键词： Education Software algorithms Real-time systems Software Encoding Computer science education Problem-solving Informatics programming profession

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Prototype Memory for Large-scale Face Representation Learning

arXiv

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arXiv 2021年

作者： Smirnov, Evgeny Garaev, Nikita Galyuk, Vasiliy Lukyanets, Evgeny Speech Technology Center Saint Petersburg194044 Russia Department of Information Technologies and Programming ITMO University Saint Petersburg197101 Russia

Face representation learning using datasets with a massive number of identities requires appropriate training methods Softmax-based approach, currently the state-of-the-art in face recognition, in its usual "full softmax" form is not suitable for datasets with millions of persons Several methods, based on the "sampled softmax" approach, were proposed to remove this limitation These methods, however, have a set of disadvantages One of them is a problem of "prototype obsolescence": classifier weights (prototypes) of the rarely sampled classes receive too scarce gradients and become outdated and detached from the current encoder state, resulting in incorrect training signals This problem is especially serious in ultra-large-scale datasets In this paper, we propose a novel face representation learning model called Prototype Memory, which alleviates this problem and allows training on a dataset of any size Prototype Memory consists of the limited-size memory module for storing recent class prototypes and employs a set of algorithms to update it in appropriate way New class prototypes are generated on the fly using exemplar embeddings in the current mini-batch These prototypes are enqueued to the memory and used in a role of classifier weights for softmax classification-based training To prevent obsolescence and keep the memory in close connection with the encoder, prototypes are regularly refreshed, and oldest ones are dequeued and disposed of Prototype Memory is computationally efficient and independent of dataset size It can be used with various loss functions, hard example mining algorithms and encoder architectures We prove the effectiveness of the proposed model by extensive experiments on popular face recognition benchmarks. © 2021, CC BY.

关键词： Face recognition

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Digital education in the coronavirus era 1

Digital education in the coronavirus era

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1st International Scientific Conference on Advances in Science, Engineering and Digital Education, ASEDU 2020

作者： Dzhangarov, A.I. Hanmurzaev, H.E. Potapova, N.V. Department of Programming and Information and Communication Chechen State University Sheripova Street 32 Groznyy364093 Russia Department of Information Educational Technologies Kuban State University Stavropol'skaya street 149 Krasnodar350001 Russia

following work outlines a study of the transformation of the educational process during the coronavirus pandemic. The object of the study is the Moscow region, which in the study is represented by seven universities. The subject of the research is the reports of students of these universities, which contain an opinion about the quality of distance education and the degree of satisfaction with it. Messages were collected and classified using machine learning methods-they were grouped according to various topics, from organizational issues to questions of personal well-being. Based on the results of the research carried out, a general assessment of the digital educational process by students is given. © Published under licence by IOP Publishing Ltd.

关键词： Coronavirus

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Design of a model for disinfection robot system

Design of a model for disinfection robot system

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2020 International Conference on information Science and Communications technologies, ICISCT 2020

作者： Nosirov, Khabibullo Begmatov, Shohruh Arabboev, Mukhriddin Medetova, Kunduz Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Television and Radio Broadcasting Systems Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Kwarizmi Department of Hardware and Software of Control Systems in Telecommunications Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Systems and Applied Programming Tashkent Uzbekistan

ISBN: (纸本)9781728199696

Following for hygiene and sanitation requirements have always been the most significant factor to stay healthy in human life. Proper cleaning and sanitation measures are one of the important ways to fight against various viruses. In recent years, the use of modern technology in sanitation has helped to fight against infectious diseases. One such modern technology is disinfection robot. Disinfection robots are increasingly used in all around the world. Use of these disinfection robots reduce the risk of infection, cost of traditional cleaning and disinfection, and most importantly acquires confidence and security of individuals. In this paper, we design a model for robot-disinfector. This robot is inspired on/from a technique, which consists of disinfecting places autonomously in order to save human life from infections. The main advantages of the designed robot are the novelty, multi-functionality, and the availability at an affordable cost. © 2020 IEEE.

关键词： Robots

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