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Перегляд за Автор "Lisovychenko, O."

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    An Approach to Creating a Flexible Manufacturing Modeling System
    (КПІ ім. Ігоря Сікорського, 2019) Shcherbinsky, A.; Lisovychenko, O.; Bondarenko, O.
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    An Approach To DSS Methods Usage At Vehicles Recognition And Identification
    (КПІ ім. Ігоря Сікорського, 2021) Yakovlev, A.; Lisovychenko, O.
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    Application of artificial intelligence models to solve the problem of loss of control over the drone
    (КПІ ім. Ігоря Сікорського, 2023) Akhaladze, A.; Lisovychenko, O.; Bogdanova, N.
    This article considers an approach to solving the problem of losing control over a swarm of drones when the connection with the IoT infrastructure is lost. The use of artificial intelligence models of Azure Cognitive Service was proposed to search and classify the command by the operator when creating a duplicate control system. The designed control system has the possibility of deployment on each drone before the execution of the flight plan, maintenance of performance in conditions of lack of communication with the IoT infrastructure in the presence of only visual contact with the operator.
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    An approach for image annotation automatization for artificial intelligence models learning
    (КПІ ім. Ігоря Сікорського, 2020) Yakovlev, A.; Lisovychenko, O.
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    Comprehensive analysis of the students’ motivation connection to the massive open online courses completion rate
    (КПІ ім. Ігоря Сікорського, 2019) Parkhomenko, A.; Segol, R.; Lisovychenko, O.
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    Data analysis using microservices to solve forecasting problem
    (КПІ ім. Ігоря Сікорського, 2021) Bondar, O.; Lisovychenko, O.
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    Determining The Efficiency Of Online Learning Models
    (КПІ ім. Ігоря Сікорського, 2020) Parkhomenko, A.; Segol, R.; Lisovychenko, O.
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    Development of subject-oriented innovative software products based on artificial intelligence systems
    (КПІ ім. Ігоря Сікорського, 2024) Stenin, A.; Pasko, V.; Lisovychenko, O.; Polshakova, O.; Soldatov, V.
    This article analyzes existing models of the development process of innovative software products for a specific subject area. Taking into account the multialternative nature of solutions at each stage of innovative software products development and compliance with constantly changing requirements, this article proposes an information and logical model of innovative software products development management process based on artificial intelligence systems. The essence of the proposed approach is that the development of an innovative software products is interpreted as an information object that changes in content and structure in the process of its creation. The presence of uncertainty and a large amount of information requires the use of intelligent decision support systems at each stage of ISP development.
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    Functional organization of system of support of decision-making of organizational management
    (КПІ ім. Ігоря Сікорського, 2020) Ostapchenko, K.; Lisovychenko, O.; Evdokimov, V.
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    Graphical shell for constructing user-entered arithmetic functions
    (КПІ ім. Ігоря Сікорського, 2023) Smolij, V.; Smolij, N.; Lisovychenko, O.
    The article has a relevant topic in the scientific and practical aspect development of a graphical shell of a software application for constructing functions of two variables entered by the user. The choice of the programming language and the use of the OpenGL software interface are justified. The quality of the construction of the framework of the function depending on the calculation step was investigated. A technique for calculating function coordinates for the applied software interface is proposed. The scaling of the test function and the use of GLSL geometry shaders to create lighting simulation are analyzed. The purpose of the work is to create a graphical shell of a software application for constructing functions of two variables entered by the user.
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    Improving the efficiency of streaming video processing through the use of serverless technologies
    (КПІ ім. Ігоря Сікорського, 2021) Akhaladze, I.; Lisovychenko, O.
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    Improving the qualifications of doctors on the base of intelligent decision support systems
    (КПІ ім. Ігоря Сікорського, 2025) Stenin, A.; Pasko, V.; Lisovychenko, O.; Soldatov, V.
    The development of medical intelligent decision-making support systems (IDSS) provides an opportunity not only for advisory assistance at various stages of the medical and diagnostic process, but also the opportunity to improve the qualifications of doctors when using IDSS. The use of IDSS contributes to the acquisition of additional knowledge by the doctor in the case of an incomplete manifestation of the clinical picture and in complex cases, in particular, in rare diseases. This article proposes the structure and composition of the IDSS of medicinal decisions, for which it is proposed to use a combined approach based on the frame structure of the knowledge model using production rules. The production rules issue an explanation understandable to the doctor, which includes a list of signs, taking into account which the diagnostic hypothesis is formed. As an example, several production rules are given regarding the identification of possible diseases of patients based on the level of general blood analysis indicators. The essence of the mechanism of fuzzy logical derivation is to determine the dependence of the output logistic variable (consequent) on the corresponding input logistic variable (antecedent) taking into account the reliability factor and the knowledge importance factor.
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    Increasing the reliability of the communication channel between agents in a multi-agent environment based on Azure IoT services
    (КПІ ім. Ігоря Сікорського, 2022) Akhaladze, А.; Lisovychenko, O.
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    Influence of the opponent color model on the generalization capacity of neural networks
    (КПІ ім. Ігоря Сікорського, 2022) Paladiiev, O.; Lisovychenko, O.
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    Real-time video stream analysis based on Azure serverless services
    (КПІ ім. Ігоря Сікорського, 2022) Akhaladze, I.; Lisovychenko, O.
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    Review And Analysis One Of The Approaches To Training The Neural Network Model
    (КПІ ім. Ігоря Сікорського, 2020) Bondar, O.; Lisovychenko, O.
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    Simulation tools: formal language for cellular automatons behavior description
    (КПІ ім. Ігоря Сікорського, 2022) Smolij, N.; Lisovychenko, O.; Smolij, V.
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    Software evolution from system perspective
    (КПІ ім. Ігоря Сікорського, 2024) Linevych, O.; Lisovychenko, O.
    Abstract: Currently, software evolution takes an unpredictable amount of time. The purpose of the article is to describe the study of 7 popular and 1 new development method and their impact on the rate of evolution. The new method is the most effective, as it collects the most information on the connections between data and processes.
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    Solution of the communication problem in the conditions of loss of communication with Azure Iot Hub
    (КПІ ім. Ігоря Сікорського, 2023) Akhaladze, I.; Lisovychenko, O.
    An architectural approach and software methods for ensuring a stable communication channel between swarm members in the absence of communication with the control hub are considered and proposed. The proposed architectural approach and software methods make it possible to provide multi-channel communication between drones in a swarm in the low frequency range. The channel ensures guaranteed delivery of messages, even in case of interference or noise.
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    Synchronization of flight trajectories based on the architecture of THE "Internet of Things" in the implementation of swarm management
    (КПІ ім. Ігоря Сікорського, 2022) Akhaladze, А.; Lisovychenko, O.
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