The topic of the thesis project is the research and development of an automated bicycle ergonomic adjustment system to increase the speed of selecting the best cyclist's seating position based on anthropometric data to increase comfort and prevent joint injuries during pedaling.
In the course of the work, an overview of existing automated systems for ergonomic adjustment of the bicycle will be conducted, an overview of the principle of operation and load cells, their main types of construction. An overview of the screw-nut transmission, its characteristics, advantages and disadvantages. The modern electrical engineering base is considered, on the basis of which the electrical schematic diagram of the system is built.
Calculations of the required control ranges of the system are carried out. The main components of the movement mechanisms are calculated. The materials were selected and the designs of the stand parts were developed.

The objective of the diploma project is to develop a mobile ophthalmoscope with additional functionalities that can be utilized in the field of medicine.
Within the framework of this project, extensive research has been conducted to explore the theoretical foundations aimed at ensuring precise and detailed examination of the fundus of the eye. A device for assessing and diagnosing the condition of the eyes has been meticulously designed. The optical system of the device has been meticulously modeled, and meticulous component selection has been performed. A comprehensive electrical circuit diagram and assembly drawings have been meticulously developed.
The work is presented in a comprehensive manner, spanning 72 pages (excluding appendices), encompassing three chapters, accompanied by 36 illustrations and referencing 22 relevant scholarly sources.

The purpose of this bachelor's thesis project is to develop an automated lighting system for the interfloor staircase of a cottage. In the course of the project, various types of lighting were studied, and existing analogues of automated lighting systems for stairs were analyzed.
After the analysis, the optimal type of lighting was chosen that best meets the requirements of efficiency, energy saving, and ease of use. To implement the system, the appropriate components were selected to ensure the required quality and functionality.
Next, structural, functional and electrical schematic diagrams were prepared to show the interconnection of the system components and how they work.

In this bachelor's project, an ultrasonic thickness gauge was designed to control metal products, the main feature of which is the ability to synchronize with mobile devices based on the Android operating system.
The first section was devoted to the analysis of the areas of application of ultrasonic thickness gauges and the relevance of their use. A comparative description of the most popular thickness gauges in our time was made according to the physical principles of measurement, namely ultrasonic and eddy currents. Different methods of ultrasonic thickness measurement are also considered, and their analysis made it possible to select an ultrasonic method of thickness measurement for the designed device. The technical characteristics of existing devices with the possibility of synchronization are considered, and their relevance is substantiated.

Today, achieving high accuracy in real-time object recognition is an urgent problem in many fields, such as computer vision, autonomous vehicles, medical diagnostics, and many others. The rapid development of technology and the increasing amount of available data have made it possible to use machine learning and neural networks to achieve this goal.
In this thesis, we have developed an automated photometric system for object recognition. In the first part of the work, different types of automated systems for object recognition are considered and analyzed. Different approaches to the implementation of computer vision are analyzed. Neural networks, including various types of neural networks and convolutional networks, are discussed in detail. Particular attention was paid to the overview of frameworks used in this area, as well as applications for data collection and data markup.
In the practical part of the work, the system's block diagram and algorithm were developed, and the selection of hardware and software components was made. The data collection process was also reviewed. Mathematical modeling of neural network training was performed and the results were analyzed.

АСНК КПІ ім. Ігоря Сікорського, 2021