Наукові публікації та матеріали кафедри авіаційних комп'ютерно-інтегрованих комплексів (НОВА)
Permanent URI for this collectionhttp://er.nau.edu.ua/handle/NAU/58730
Browse
Recent Submissions
Item Adaptive Control of Manipulator Robots in a Dynamic Environment Using Neural Networks(National Aviation University, 2024-06-26) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Khotsyanovsky, Volodymyr; Хоцянівський, Володимир ПетровичThe purpose of the study is to develop an approach to planning the trajectory of the manipulator robot using an intelligent system based on neural networks. For this purpose, the work considered the processes of planning and deploying the movement of the robot. The analysis of existing methods of planning the movement of manipulator robots and the review of intelligent control systems made it possible to obtain a complete picture of the current state of this issue. A system is proposed that can perceive the environment and control the movement of the robot by generating the correct control commands. For this, 3 tasks were solved, namely: analysis of the environment in order to determine its features, determination of the trajectory in order to neutralize the collision and determination of controlled influences for the executive authorities in order to implement the movement. The functionality and structure of the neural network for solving each of the tasks are proposed.Item Automated Camouflage Design Based on Artificial Intelligence(National Aviation University, 2024-06-28) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Bashenko, M. O.; Башенко, Микита ОлександровичThe article discusses the development of a camouflage uniform production system for civilian use with an emphasis on survival and hunting. Effective camouflage requires precise reproduction of the colors, textures, and patterns of specific landscapes, increasing hunting success and unnoticed movement. The technological process of fabric dyeing, necessary for the production of high-quality camouflage uniforms, includes fabric preparation, dyeing and strict quality control.. Fabric preparation includes cleaning, soaking, bleaching, and mercerization to ensure uniform dye absorption and durability. Dyeing methods vary by fabric type, with reactive dyes for natural fibers and disperse dyes for synthetics. Quality control includes visual inspections and tests for colorfastness under various conditions. Advanced dyeing techniques such as continuous dyeing, spray dyeing, stencil dyeing and digital printing have been analyzed to offer certain advantages. Machines like the Mimaki TX300P handle various fabric widths with high precision and reliability, enhancing efficiency. Automation using the Mimaki TX300P streamlines the dyeing process, optimizing ink consumption and integrating fabric loading, printing, and cutting systems. A customer relationship management system further automates garment creation, enhancing design, order management, and quality control. Tools like CLO3D enable detailed 3D modeling and accurate pattern reproduction. The customer relationship management system coordinates production stages and provides precise paint usage recommendations, ensuring efficient resource management and high-quality outcomes. In conclusion, developing and automating fabric dyeing processes for camouflage uniforms involve advanced technologies and meticulous quality control, ensuring durable, colorfast camouflage clothing that blends effectively into natural environments for civilian use.Item Intelligent System of Generation of Camouflage Patterns Based on Artificial Intelligence Technologies(National Aviation University, 2024-06-28) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Nikulin, Dmytro; Нікулін, Дмитро ОлеговичThe work is devoted to the development of an intelligent system for generating camouflage patterns based on artificial intelligence technologies. A generative-competitive network is used as an intellectual element of this system. To solve the problem of the collapse mode, the architecture of progressively growing GANs (ProGAN) is used. The system allows you to generate completely new camouflage patterns for the selected area by iteratively improving the pattern. Due to the mechanism of restrictions, it is possible to fix the desired aspects of the drawing (color scheme, pattern, number of colors) from an existing drawing and adapt it to the desired area. The system provides the possibility of generating micropatterns on the drawings to improve camouflage at close distances. When evaluating a camouflage pattern, the system takes into account additional parameters, such as angle (from the ground and air), time and weather.Item Two-circuit System of Automated Control of Low-Altitude Helicopter Flight(National Aviation University, 2024-03-29) Filyashkin, Mykola; Філяшкін, Микола КириловичThe mode of automatic control of a low-altitude flight of a helicopter over heavily rugged terrain based on information about the inclined range is considered. It is shown that at high flight speeds it is impossible to overcome strictly vertical obstacles without changing the angle of inclination of the rangefinder antenna to the horizon depending on the flight speed, or without reducing the flight speed when approaching such an obstacle. Algorithms for controlling low-altitude flight using a two-channel scheme are proposed, namely, at high speeds through the longitudinal channel of the swashplate, and at low speeds – through the channel of the general pitch of the main rotor. The problem of optimal control of low-altitude helicopter flight is formulated, which can be presented as a variational problem with restrictions on phase coordinates and control influences. Ways to optimize the process of circumventing an obstacle with forecasting the trajectory of the helicopter on a certain section of the route with subsequent stabilization of the helicopter on this trajectory are shown.Item Method of Planning and Coordination of Robot Movement Using Neural Networks for Solution of Dynamic Production Scenarios(National Aviation University, 2024-03-29) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Khotsyanovsky, Volodymyr; Хоцянівський, Володимир ПетровичThe purpose of the study is to develop an approach to planning the trajectory of a robot manipulator using an intelligent system based on neural networks. For this purpose, the work considered the processes of planning and deploying the movement of the robot. The analysis of existing methods of planning the movement of robot manipulators and the review of intelligent control systems provided a comprehensive picture of the current state of this issue. A system is proposed that can perceive the environment and controls the movement of the robot by generating correct control commands. For this purpose, 3 tasks were solved, namely, the analysis of the environment in order to determine its features, the determination of the trajectory in order to neutralize the collision, and the determination of controlled influences for the executive bodies in order to implement the movement. The functionality and structure of the neural network for solving each of the tasks is proposed. The proposed approach is compared with existing approaches on key parameters, such as the execution time of the planned movement and the time of calculating the movement trajectory. The results confirmed that the use of neural network to optimize the trajectory and dynamic prediction to avoid obstacles significantly increased the adaptability of the system to the changing conditions of the production environment, which opens up new opportunities for improving automated processes and providing optimal conditions for the functioning of manipulator robots in real-time.Item Intelegence Design of Hybrid Vertical-axis Rotors(National Aviation University, 2023-12-27) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Stanislavchuk, Oleksandr; Станіславчук, Олександр ВалентиновичThe work is devoted to the necessity of creating the vertical-axis rotors of wind power stations in the urban area, which can be placed on roofs and makes it possible to increase their energy productivity by 60-70%. It is shown that the locations of such rotors on roofs has its own characteristics, which consists in the need to take into account the shape of the topography of the house, its storey, the direction and speed of the winds above it, and others. Examples of implementation of wind farms are considered and it is proven that their energy efficiency can be increased due to the use of hybrid vertical-axis rotors, which consist of a combination of Darrieus and Savonius rotors, where the Darrieus rotor is the main source(s) of wind energy conversion into the electric one, while the Savonius rotor(s) provide the acceleration of the Darrieus rotors. For the implementation it has been used the genetic algorithm. An inelegance design system has been developed. An example of the application of this system for the design of a hybrid rotor is given.Item Odometrical Navigation Systems(National Aviation University, 2024-03-29) Ablesimov, Aleksandr; Аблесімов, Олександр КостянтиновичThe technology for determining the location of an object on the ground is the foundation for building vehicle navigation systems and surveillance systems after them. In general, such navigation systems make it possible to determine the coordinates of the vehicle’s location and its directional angle, find the direction to the destination, and calculate the coordinates of observation objects. The technical implementation of systems can be quite diverse – from implementation on mechanical elements to their implementation using microelectronics elements. The main factors in the development of navigation systems are the transition to computer-integrated systems and resource-saving technologies. This will make it possible to increase the accuracy of navigation information, obtain a significant gain in the weight and size characteristics of the equipment, reduce its energy consumption and increase reliability. The possibility of modernization of odometrical navigation systems based on integrated computer technologies is considered.Item A Comprehensive Framework for Underwater Object Detection Based on Improved YOLOv8(National Aviation University, 2024-03-29) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Savchenko, Mykhailo; Савченко, Михайло ВолодимировичUnderwater object detection poses unique challenges due to issues such as poor visibility, small densely packed objects, and target occlusion. In this paper, we propose a comprehensive framework for underwater object detection based on improved YOLOv8, addressing these challenges and achieving superior performance. Our framework integrates several key enhancements including Contrast Limited Adaptive Histogram Equalization for image preprocessing, a lightweight GhostNetV2 backbone, Coordinate Attention mechanism, and Deformable ConvNets v4 for improved feature representation. Through experimentation on the UTDAC2020 dataset, our model achieves 82.35% precision, 80.98 % recall, and 86.21 % mean average precision at IoU = 0.5. Notably, our framework outperforms the YOLOv8s model by a significant margin, while also being 15.1% smaller in terms of computational complexity. These results underscore the efficiency of our proposed framework for underwater object detection tasks, demonstrating its potential for real-world applications in underwater environments.Item Summation Circuits of Automatic Control Systems(National Aviation University, 2024-03-29) Ablesimov, Aleksandr; Аблесімов, Олександр Костянтинович; Miroshnychenko, Vladyslav; Мірошниченко, Владислав Анатолійович; Chubatyuk, Ilya; Чубатюк, Ілля ІгоровичDuring the operation of the stabilization systems, the parameters of the control object and the regulator can change for various reasons within fairly wide limits. In such cases, they speak of the presence of parametric uncertainty. Note that the main indicator of the quality of the stabilization system is considered to be the accuracy of the stabilization of the control object. As theoretical studies show, the accuracy of stabilization systems directly depends on their rigidity and damping, because they directly affect the formation of the moment of stabilization and determine the effectiveness of the system's response to external disturbances. Changing stiffness and damping in order to ensure the necessary efficiency of stabilization systems is the basis of their operational adjustments. To change these parameters, there are summation circuits in the systems. Will the change in the summation circuit type affect the solution to the main task of the operational adjustment of the stabilization system? This article considers the possibilities of summation circuits to ensure the optimality of the settings of the stabilization system.Item Modeling Complex for Studies of Methodical and Instrumental Errors of the Strapdown Inertial Navigation System(National Aviation University, 2023-12-27) Filyashkin, Mykola; Філяшкін, Микола Кирилович; Smirnov, Oleg; Смірнов, Олег ІгоровичTo study the accuracy characteristics, a strapdown inertial navigation system is represented as a set of kinematic equations and equations of a mathematical model of the Earth. Based on the mathematical model in the Matlab-Simulink package, a modeling complex was created, consisting of subsystems of the reference and studied navigation system, subsystems of the reference and simplified model of the Earth and a subsystem of primary information sensors. In navigation subsystems, kinematic equations of inertial navigation algorithms are solved, and matrices of direction cosines are formed. In the subsystems of the Earth model, the parameters of the Earth's spheroid and the acceleration of gravity are calculated. The sensor models are developed based on the characteristics of low-cost microelectromechanical sensors. The purpose of the study was to assess methodological and instrumental errors as the difference in the dead reckoning signals of the flight navigation parameters of the reference and studied navigation systems. Methodological errors of the system are played up by simplifications of the parameters of the earth's spheroid, and instrumental errors are caused by errors in inertial sensors.Item Determination of Marketing Parameters for Building a Demand Forecasting Model using Neural Networks(National Aviation University, 2023-12-27) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Novikov, Mikhaylo; Новіков, Mихайло СергійовичThis article is devoted to finding marketing parameters for building a demand forecasting model using neural networks using real data. The work deals with the problem of modeling product demand on the market in marketing using artificial intelligence and machine learning methods. The main features of existing approaches to building models of products on the market, their advantages and disadvantages are shown. The need for their improvement has been identified. A new methodology for solving the problem is presented. The model's demonstrated ability to predict consumer demand based on a variety of marketing parameters helps businesses plan inventory, production, and personnel more effectively and can lead to significant cost savings and improved efficiency.Item Structural-parametric Synthesis of Capsule Neural Networks(National Aviation University, 2023-12-27) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Kudriev, Denys; Кудрєв, Денис ОлексійовичThis work is dedicated to the structural-parametric synthesis of capsule neural networks. A methodology for structural-parametric synthesis of capsule neural networks has been developed, which includes the following algorithms: determining the most influential parameters of the capsule neural network, a hybrid machine learning algorithm. Using the hybrid algorithm, the optimal structure and values of weight coefficients are determined. The hybrid algorithm consists of a genetic algorithm and a gradient algorithm (Adam). 150 topologies of capsule neural networks were evaluated, with an average evaluation time of one generation taking 10 hours. Chromosomes and weights are stored in the generation folder. The chromosome storage format is JSON, using the jsonpickle library for writing. Also, when forming a new generation, chromosome files from previous generations are used as a "cache". If a chromosome of the same structure exists, the accuracy is assigned immediately to avoid unnecessary training of neural networks. As a result of using the hybrid algorithm, the optimal topology and parameters of the capsule neural network for classification tasks have been found.Item Twitter Fake News Detection Using Graph Neural Networks(National Aviation University, 2023-12-27) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Bylym, Kyrylo; Билим, Кирило ІгоровичThis article is devoted to the intellectual processing of text information for the purpose of detecting rail news. To solve the given task, the use of deep graph neural networks is proposed. Fake news detection based on user preferences is augmented with deeper graph neural network topologies, including Hierarchical Graph Pooling with Structure Learning, to improve the graph convolution operation and capture richer contextual relationships in news graphs. The paper presents the possibilities of extending the framework of fake news detection based on user preferences using deep graph neural networks to improve fake news recognition. Evaluation on the FakeNewsNet dataset (a subset of Gossipcop) using the PyTorch Geometric and PyTorch Lightning frameworks demonstrates that the developed deep graph neural network model achieves 94% accuracy in fake news classification. The results show that deeper graph neural networks with integrated text and graph features offer promising options for reliable and accurate fake news detection, paving the way for improved information quality in social networks and beyond.Item Aircraft Fuel Measurement System Based on Hydrostatic Pressure Sensor(National Aviation University, 2023-09-29) Smirnov, Oleg; Смірнов, Олег Ігорович; Filyashkin, Мykola; Філяшкін, Микола КириловичThe construction of an aircraft fuel-measuring system based on hydrostatic pressure sensors is considered, which makes it possible to determine the fuel residue in the aircraft tanks during its evolutions. With the evolution of aircraft, measuring the fuel residue in existing fuel metering systems using float and capacitive fuel level sensors has a rather complex electromechanical design and significant weight and size characteristics. This together affects the reliability of such systems as a whole and leads to significant methodological errors in determining the remaining fuel during maneuverable flight. The proposed system using hydrostatic pressure sensors and a computer can significantly increase the efficiency of existing fuel metering systems, and can also be used for calibration tests both on the ground and in flight.Item Long-term Demand Forecasting: using an Ensemble of Neural Networks to Improve Accuracy(National Aviation University, 2023-09-29) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Samoshyn, Andrii; Самошин, Андрій ОлександровичThis research paper proposes a method of long-term demand forecasting based on an ensemble of neural networks that considers the novelty of the data. A tool for creating the ensemble was developed that uses a bagging technique as well as a modification that allows for the relevance and novelty of the data to be considered when creating training samples for each model in the ensemble. The study examines and compares the developed method with known approaches to long-term demand forecasting. Experimental results have indicated that the proposed approach allows for obtaining more accurate and reliable demand forecasts compared to existing methods. The results emphasize the importance of data in the demand forecasting process and indicate the potential of the proposed method to eventually improve inventory management strategies and product planning.Item Semi-supervised Learning Based on Graph Stochastic Co-Training(National Aviation University, 2023-09-29) Sineglazov, Victor; Синєглазов, Віктор Михайлович; Yarovyi, Serhi; Яровий, Сергій СергійовичThis article is devoted to the development of a new approach in semi-supervised machine learning. The goal of this article is to analyze the accuracy of the single-view co-training system, based on the use of a modified graph-based stochastic label propagation algorithm for a multiclass classification problem. Graph transformation of data is preceded by feature decomposition, with three algorithms being compared: Singular Value Decomposition, Truncated Singular Value Decomposition, Iterative Primary Component Analysis, Kernel Primary Component Analysis. To improve the accuracy of the proposed method, additional parameter was included in the label propagation algorithm, allowing for the usage of the algorithm in co-training systems. Further performance increases are achieved via optimization of data modification, which is achieved by applying feature decomposition methods and parallelizing the calculation-heavy processes. As examples of practical use were considered solutions to the problem of multiclass classification for standard datasets of the library sklearn and for the real dataset Traffic Signs Preprocessed. Analyses of the results of the implementation of the proposed approach showed improvements in accuracy and of performance solving the multiclass classification problem.Item Recommender Systems Based on Reinforced Learning(National Aviation University, 2023-06-27) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Sheruda, A. V.; Шеруда, Андрій ВолодимировичThis article is devoted to the problem of building recommender systems based on the use of artificial intelligence methods. The paper analyzes the algorithms of recommender systems. Analyzes the Markov decision-making process in the context of recommender systems. Approaches to the adaptation of reinforcement learning algorithms to the task of recommendations (transition from the task of supervised learning to the task of reinforcement learning) are considered. Reinforcement learning algorithms Deep Deterministic Policy Gradient and Twin Delayed DDPG were implemented with their own environment simulating the user's reaction, and the results were compared. The structure of a recommender system has been developed, in which the recommender agent generates a list of offers for an individual user, using his previous history of ratings. In the system itself, the user has the ability to interact only with the space of recommended films. This can be compared to the main YouTube page, which is a feed with suggestions, but we have a user interacting only with this feed and his reaction to objects in the recommendation space falls into recommender agent, which regulates the parameters of the model in the learning process.Item Quantum Convolution Neural Network(National Aviation University, 2023-06-27) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Chynnyk, P. A.; Чинник, Петро АнатолійовичIn this work, quantum convolutional neural networks are considered in the task of recognizing handwritten digits. A proprietary quantum scheme for the convolutional layer of a quantum convolutional neural network is proposed. A proprietary quantum scheme for the pooling layer of a quantum convolutional neural network is proposed. The results of learning quantum convolutional neural networks are analyzed. The built models were compared and the best one was selected based on the accuracy, recall, precision and f1-score metrics. A comparative analysis was made with the classic convolutional neural network based on accuracy, recall, precision and f1-score metrics. The object of the study is the task of recognizing numbers. The subject of research is convolutional neural network, quantum convolutional neural network. The result of this work can be applied in the further research of quantum computing in the tasks of artificial intelligence.Item Modification of Semi-supervised Algorithm Based on Gaussian Random Fields and Harmonic Functions(National Aviation University, 2023-06-27) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Chumachenko, O. I.; Чумаченко, Олена Іллівна; Lesohorskyi, K. S.; Лесогорський, Кирило СергійовичIn this paper we propose an improvement for a semi-supervised learning algorithm based on Gaussian random fields and harmonic functions. Semi-supervised learning based on Gaussian random fields and harmonic functions is a graph-based semi-supervised learning method that uses data point similarity to connect unlabeled data points with labeled data points, thus achieving label propagation. The proposed improvement concerns the way of determining similarity between two points by using a hybrid RBF-kNN kernel. This improvement makes the algorithm more resilient to noise and makes label propagation more locality-aware. The proposed improvement was tested on five synthetic datasets. Results indicate that there is no improvement for datasets with big margin between classes, however in datasets with low margin proposed approach with hybrid kernel outperforms existing algorithms with a simple kernel.Item Comparative Analysis of Text Vectorization Methods(National Aviation University, 2023-06-27) Sineglazov, V. M.; Синєглазов, Віктор Михайлович; Savenko I. M., I. M.; Савенко, Ілля МихайловичThe paper considers methods of vectorization of textual properties of natural language in the context of the task of intellectual text analysis. The most common methods of statistical analysis of feature extraction and methods that taking into account the context are analyzed. The work describes the above types of text embeddings and their most common variations and implementations. Their comparative analysis was performed, which showed the relationship between the type of task of intellectual text analysis and the method showing the best metrics. The topology of the neural network, which is the basis for solving the problem and obtaining metrics, is described, and implemented. The comparative analysis was carried out using the relative time analysis of the theory of algorithms and classification metrics: accuracy, f1-score, precision, recall. The classification metrics are taken from the results of building a neural network model using the described framing methods. As a result, in the task of analyzing the tonality of the text, the statistical method of framing based on n-grams of character sequences turned out to be the best.