Automation of ultrasonic inspection processes for welded joints is a relevant and crucial topic in modern industry. Ultrasonic inspection is employed to detect defects in welded joints, such as cracks, bubbles, and other irregularities that may affect the strength and reliability of structures. The automation of this process involves the use of specialized equipment and software for the automatic execution of ultrasonic scanning and analysis of results. This enhances the speed and accuracy of inspections, reduces the impact of human factors, and improves overall process efficiency. Key stages of automation include the development of algorithms for processing ultrasonic information, integration with welding equipment, creation of interfaces for operator interaction, and the establishment of monitoring and reporting systems. The application of automated ultrasonic inspection of welded joints leads to improved manufacturing quality, reduced risks of defects, and increased reliability and safety in the operation of structures and machinery.

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Research and development in humanoid robotics have persisted since the1900s, focusing on two core challenges: the mechanical aspect of achieving human-like movement and the software aspect of emulating human behavior.
These challenges, often addressed through advancements in control theory, drive the exploration of achieving balance and mobility on uneven terrain for the Darwin-Op humanoid robot. While the primary emphasis was on control theory, an ancillary goal involved vision control for identifying non-flat surfaces like ramps or stairs, using specific color detection.

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Relevance of the topic.
Currently, the wide implementation of computer technologies in medicine is noted. The use and analysis of artificial intelligence define a promising field that contributes to the acceleration of the development of medical science. In order to automate, increase efficiency and improve the accuracy of diagnostic methods, the use of convolutional neural networks is proposed.

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The master's thesis on the topic "Automated Camera Stabilization System" consists of an introduction, five chapters, conclusions summarizing the entire work, and a bibliography. The dissertation comprises 86 pages of main text, 44 illustrations, 31 tables, and 12 references, with a total volume of 99 pages.
Research Object: Video camera stabilization process
Research Subject: Automated camera stabilization system
Research Objective: Enhancing the accuracy of video camera stabilization

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The master's thesis contains the following components: a list of notations and abbreviations, an introduction, five main chapters, general conclusions and a list of references to the literature used. Contains 83 pages, 18 figures, 28 tables, 19 references.
The aim and task of the dissertation. Conducting a study of a two-channel capacitive MEMS sensitive element based on an automated stabilization system.

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  1. Nazarenko A. Tree-axis sensitive of an UAV automated control system
  2. Labunskyi P. Automatic eddy current flaw detector with defect coordinate fixation using a computer mouse
  3. Nekrasova O. Automated rehabilitation tool for the lower limb
  4. Leskovets B. Automated system of remote environmental monitoring

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АСНК КПІ ім. Ігоря Сікорського, 2021