Authors:Ihor Zakutynskyi; Ihor Rabodzei, Stanislav Burmakin, Oleksandr Kalishuk, Vitalii Nebylytsia Abstract: The object of this research is the process of load balancing in distributed Internet of Things (IoT) systems. Within this work, a complex of problems related to efficient load distribution has been addressed. The authors conducted an analysis of existing load-balancing approaches and their drawbacks and proposed an enhanced architecture for the MQTT broker. Additionally, methods and algorithms for load balancing were developed based on multi-criteria server monitoring. Furthermore, the authors created a mathematical model to assess the uniformity of load distribution in the system and introduced a corresponding metric – the load distribution coefficient. In order to evaluate the proposed load balancing methods, a series of experiments were conducted, including the simulation of a distributed IoT system with non-deterministic load. The main goal of these experiments was to assess the uniformity of MQTT load distribution by the broker. The results of the experiments confirmed the hypothesis of improved load distribution efficiency through multi-criteria monitoring-based balancing. The utilization of the proposed load-balancing methods allowed for a more efficient utilization of computational resources. It was found that when using the proposed methods, in the case of non-deterministic load in the IoT system, the load distribution coefficient on average exceeded the corresponding indicator of existing methods by 70 %. In addition, the value of this coefficient for the proposed methods remains virtually unchanged throughout the experiment, which is evidence of the stable operation of the system as a whole. The results obtained can be useful in the development of modern IoT systems. PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Nurzhan Mukazhanov; Zhibek Alibiyeva, Aigerim Yerimbetova, Aizhan Kassymova, Nursulu Alibiyeva Abstract: The presented paper is devoted to the development of a method for identifying and correcting spelling errors in Kazakh texts. In this paper, the study object is methods for more accurate correction of spelling errors in Kazakh texts. The aim of the study is to develop an augmented version of the Damerau-Levenshtein method for correcting spelling errors in Kazakh language texts. Automatic detection and correction of spelling errors have become a default feature in modern text editors for working with text data, in text messaging applications such as chatbots, messengers, etc. However, although this task is well solved in geographically widespread languages, it has not been fully solved in languages with a small audience, such as the Kazakh language. The methods developed so far cannot correct all spelling errors found in Kazakh texts. Therefore, the development of a method with specific algorithms for spelling error correction in Kazakh texts is considered. As a result of the research work, algorithms for correcting errors found in Kazakh language texts were developed, and the developed algorithms were included in the Damerau-Levenshtein method. The experimental testing results of the augmented Damerau- Levenshtein method showed 97.2 % accuracy in correcting specific errors found only in Kazakh words and 92.8 % accuracy in correcting common errors from letter symbols. The standard Damerau-Levenshtein method testing results showed 76.4 % accuracy in correcting specific errors found only in Kazakh words. The results of the tests in correcting common errors from letter symbols with the standard Damerau-Levenshtein were approximately the same with the augmented Damerau-Levenshtein method, the accuracy is 92.2 %. The extent and conditions of practical application of the results are implemented by including them in text editors, messengers, e-mails and similar applications that work with text data. PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Sergii Khlamov; Vadym Savanevych, Vladimir Vlasenko, Tetiana Trunova, Volodymyr Troianskyi, Roman Gerasimenko, Viktoriia Shvedun Abstract: The variability of shooting conditions affects the quality of images of Solar System objects in a series of frames. Identification of a frame with the corresponding part of the sky becomes difficult if the quality is poor. Because of this fact, the detection quality indicators and estimation of the position of Solar System objects are significantly reduced when using already known methods and international astronomical catalogs. To solve this problem, the procedure of full identification of measurements of objects on digital frames was devised. This procedure is based on the formation of triplets (triangles) of primary identification from the side of the digital frame and the astronomical catalog. Positional coordinates on the frame and ideal tangential coordinates from the catalog were used. Owing to this, a comparison of the primary identification triplets was carried out by comparing the calculated angles of the triangle vertices. The identity of the hypothesis was determined by comparison with the acceptable deviation. The use of the developed full identification procedure makes it possible to reduce the number of false detections and improve identification with reference astronomical objects. The study showed that when identifying frames, astrometry has better accuracy of reference to the starry sky. In addition, the standard deviation of frame identification errors in this case is 6–9 times less than without using the devised procedure. The procedure developed for complete identification was practically tested within the framework of the CoLiTec project. It was implemented in the Lemur software for automated detection of new and tracking of known objects. Owing to the use of Lemur software and the proposed computational procedure implemented in it, more than 700,000 measurements of various astronomical objects under study were successfully identified. PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Aigul Mimenbayeva; Samat Artykbayev, Raya Suleimenova, Gulnar Abdygalikova, Akgul Naizagarayeva, Aisulu Ismailova Abstract: The process of clustering of normalized vegetation indices in five regions with a total area of 2565 hectares of the North Kazakhstan region was studied. A methodological approach to organizing the clustering process is proposed using the vegetation indices NDVI, MSAVI, ReCI, NDWI and NDRE, taking into account individual characteristics in the three main phases of spring wheat development As a result of the research, vegetation indices were grouped into 3 classes using the k-means clustering method. The first cluster contained vegetation indices whose maximum values occupied about 33.98% of the total area of the study area. It was found that NDVImax located in the first cluster was positively correlated with soil-corrected vegetation indices MSAVI and crop moisture indicators NDMI (R2=0.92). The second cluster is characterized by minimum values of NDVImax coefficients at the germination, tillering and ripening phases (from 0.53 to 0.55). The lowest values of vegetation indices occupied 35.9 % in the germination phase, 37.9 % in the tillering phase, and 40.1 % of the field from the total area. The third cluster is characterized by average values of vegetation indices in all three phases. A correlation matrix was also constructed to assess the closeness of the relationship between actual yield and NDVI vegetation indices. The maximum coefficient was obtained at the germination phase, R=0.94 with a minimum significance coefficient p=0.018. The approach used in this study can be useful in the analysis of satellite data, as it can improve the sensitivity of the constellation procedure. From a practical point of view, the results obtained make it possible to assess the condition of agricultural crops in the early stages of the growing season, which makes it possible to improve their productivity based on the results of cluster analysis PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Hasan Polat; Nabaz Mawlood Ali Abstract: Housing accounts for the largest share of the volume of the construction sector. Housing is the living space that people use on a permanent or temporary basis. Living space is also expected to have the desired quality. Quality requires construction in accordance with specified conditions and rules. In order to minimize possible errors in the design and construction process and to achieve the desired level of quality, continuous, scientific and instrumental controls are required. In recent years, with the rapid development of technology, methods have been developed that have achieved good results using integrated technology, which has begun to replace the quality controls performed by traditional methods. This new technology partnership called Building Information Modelling and Laser Scanning is described in this study. The aim of the study is to show that human error in building inspection can be minimized with the help of technology. In the study, a building was selected from a sample public housing project. Two dimensional projects of the building were converted into three dimensions using Building Information Modelling. In the current state of construction, point clouds were captured using laser scanning. The point clouds were converted to three dimensions. The construction defects were calculated by overlaying the BIM model with the real point cloud data. After checking, it was found that 2.2 % of the productions were defective productions. It was found that 97.8 % of the productions were within acceptable tolerance limits. The results obtained on a sample residential building demonstrate the importance of these new solutions for quality control and error-free production PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Anar Utegenova; Akylbek Bapyshev, Zhanna Suimenbayeva, Alisher Aden, Ruslan Kassym, Serikov Tansaule Abstract: Standardization and technical regulation involve the digitization of international and regional standards into "smart" standards, introducing new requirements for the presentation of complex industrial manuals. The introduction of artificial intelligence and machine learning into the process of standardization, improving process automation, data analysis will provide an opportunity to create innovative standards. Creation of machine-readable standards and their presentation in the form of a database will contribute to better interoperability between systems. The article demonstrates the method of ontological engineering for the automation of partial methodological examination of documents in accordance with the National Standardization Plan. As part of the experiment, an independent tool was developed, based on the extraction of qualitative data, using an uncontrolled automatic keyword extraction algorithm. The algorithm does not require the creation of a learning corpus, can be applied to any text and language, and does not have limitations on the amount of processed data. The algorithm provides adjustment of the parameters of the repetition of keywords, with the possibility of taking into account less important keywords. The work presents the following components: model classification standards, essence extraction module, categorization, thesaurus formation, monitoring and analysis. Calculations were carried out using formalization, determination of the target function, establishment of similarity measures, and description of document features. The work presents the theoretical aspect of application, design and description of the functional system. PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Bohdan Yurkov; Serhii Asmolovskyi, Viktor Pererva, Dmytro Voronovskyi, Sergei Kulagin Abstract: The object of the study in this work is pressure spikes in the accumulator tank of the xenon feed system for electric propulsion. The presence of significant pressure spikes in the accumulator tank of the feed system causes a change in the mass flow and, accordingly, a significant deterioration of the thruster parameters - thrust, specific impulse and efficiency. The problem that was solved in this work is to find ways to reduce pressure spikes while minimizing the volume of the accumulator tank without using additional elements. The analysis of literary sources showed that the specified problem is typical and has not been solved for small-volume accumulator tanks yet. To solve this problem, theoretical and experimental determination of pressure spikes that occur during the work on feedback from sensors was carried out, and an improved method of filling the accumulator tank was proposed. As a result of research, it was determined that pressure spikes that go beyond the permissible range (±3 %) appear at an inlet pressure of 3.5 MPa. With an increase of inlet pressure, the pressure spikes also increase. As a result of research, it was found that for an inlet pressure of up to 3 MPa, it is appropriate to work on feedback from pressure sensors. For pressure values from 3 to 6 MPa, it is necessary to use the experimentally obtained formula to determine the accumulator tank filling time. For a pressure of more than 6 MPa, it is necessary to work in the bang-bang mode. The research made it possible to determine the optimal modes of filling the accumulator tank. Presented modes allow to use a small-volume accumulator tank with the minimization of the valve activations number, in which stable operation of the thruster is maintained. The conclusions obtained as a result of the research can be useful for most developers of feed systems for electric propulsion. PubDate: Tue, 31 Oct 2023 00:00:00 +020
Authors:Oleh Pihnastyi; Dmytro Kudii Abstract: The object of this study is the material flow incoming the conveyor. The actual problem of calculating the stochastic characteristics of the input material flow of a transport system, based on the typification of the input material flow, is being solved. When constructing a model of the input material flow, methods of similarity theory were used. A criterion has developed for dividing the realization of the input material flow into a deterministic and stochastic component, which makes it possible to represent the stochastic component of the input flow in the form of an realization of a centered ergodic process. A method is presented for calculating amplitude and phase frequency spectra for the components of the input material flow, based on specified types of theoretical correlation functions. The calculating accuracy of the normalized correlation function values is e~0.05. Distinctive features of the obtained results are that the typification method of the input material flow is based on the use of the amplitude spectrum for the input material flow. A special feature of the results obtained is that a single realization of the input material flow was used to model the input material flow. The scope of application of the obtained results is the mining industry. The developed methodology for calculating the statistical characteristics of the input material flow allow to improve the accuracy of algorithms for optimal control of the flow parameters of the transport system for a mining enterprise. The condition for the practical application of the obtained results is the presence in the sections of the transport conveyor of measuring sensors that determine the speed of the belt and the amount of material in the bunker PubDate: Tue, 31 Oct 2023 00:00:00 +020
Open Access journal
